--- _id: '9871' abstract: - lang: eng text: The positional information in a discrete morphogen field with Gaussian noise is computed. article_processing_charge: No author: - first_name: Patrick full_name: Hillenbrand, Patrick last_name: Hillenbrand - first_name: Ulrich full_name: Gerland, Ulrich last_name: Gerland - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Hillenbrand P, Gerland U, Tkačik G. Computation of positional information in a discrete morphogen field. 2016. doi:10.1371/journal.pone.0163628.s003 apa: Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Computation of positional information in a discrete morphogen field. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628.s003 chicago: Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Computation of Positional Information in a Discrete Morphogen Field.” Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.s003. ieee: P. Hillenbrand, U. Gerland, and G. Tkačik, “Computation of positional information in a discrete morphogen field.” Public Library of Science, 2016. ista: Hillenbrand P, Gerland U, Tkačik G. 2016. Computation of positional information in a discrete morphogen field, Public Library of Science, 10.1371/journal.pone.0163628.s003. mla: Hillenbrand, Patrick, et al. Computation of Positional Information in a Discrete Morphogen Field. Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.s003. short: P. Hillenbrand, U. Gerland, G. Tkačik, (2016). date_created: 2021-08-10T09:27:35Z date_updated: 2023-02-21T16:56:40Z day: '27' department: - _id: GaTk doi: 10.1371/journal.pone.0163628.s003 month: '09' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1270' relation: used_in_publication status: public status: public title: Computation of positional information in a discrete morphogen field type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2016' ... --- _id: '1128' abstract: - lang: eng text: "The process of gene expression is central to the modern understanding of how cellular systems\r\nfunction. In this process, a special kind of regulatory proteins, called transcription factors,\r\nare important to determine how much protein is produced from a given gene. As biological\r\ninformation is transmitted from transcription factor concentration to mRNA levels to amounts of\r\nprotein, various sources of noise arise and pose limits to the fidelity of intracellular signaling.\r\nThis thesis concerns itself with several aspects of stochastic gene expression: (i) the mathematical\r\ndescription of complex promoters responsible for the stochastic production of biomolecules,\r\n(ii) fundamental limits to information processing the cell faces due to the interference from multiple\r\nfluctuating signals, (iii) how the presence of gene expression noise influences the evolution\r\nof regulatory sequences, (iv) and tools for the experimental study of origins and consequences\r\nof cell-cell heterogeneity, including an application to bacterial stress response systems." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh citation: ama: Rieckh G. Studying the complexities of transcriptional regulation. 2016. apa: Rieckh, G. (2016). Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria. chicago: Rieckh, Georg. “Studying the Complexities of Transcriptional Regulation.” Institute of Science and Technology Austria, 2016. ieee: G. Rieckh, “Studying the complexities of transcriptional regulation,” Institute of Science and Technology Austria, 2016. ista: Rieckh G. 2016. Studying the complexities of transcriptional regulation. Institute of Science and Technology Austria. mla: Rieckh, Georg. Studying the Complexities of Transcriptional Regulation. Institute of Science and Technology Austria, 2016. short: G. Rieckh, Studying the Complexities of Transcriptional Regulation, Institute of Science and Technology Austria, 2016. date_created: 2018-12-11T11:50:18Z date_published: 2016-08-01T00:00:00Z date_updated: 2023-09-07T11:44:34Z day: '01' ddc: - '570' degree_awarded: PhD department: - _id: GaTk file: - access_level: closed checksum: ec453918c3bf8e6f460fd1156ef7b493 content_type: application/pdf creator: dernst date_created: 2019-08-13T11:46:25Z date_updated: 2019-08-13T11:46:25Z file_id: '6815' file_name: Thesis_Georg_Rieckh_w_signature_page.pdf file_size: 2614660 relation: main_file - access_level: open_access checksum: 51ae398166370d18fd22478b6365c4da content_type: application/pdf creator: dernst date_created: 2020-09-21T11:30:40Z date_updated: 2020-09-21T11:30:40Z file_id: '8542' file_name: Thesis_Georg_Rieckh.pdf file_size: 6096178 relation: main_file success: 1 file_date_updated: 2020-09-21T11:30:40Z has_accepted_license: '1' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: '114' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publist_id: '6232' status: public supervisor: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 title: Studying the complexities of transcriptional regulation type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2016' ... --- _id: '1358' abstract: - lang: eng text: 'Gene regulation relies on the specificity of transcription factor (TF)–DNA interactions. Limited specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to noncognate TF–DNA interactions or remains erroneously inactive. As each TF can have numerous interactions with noncognate cis-regulatory elements, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyse the effects of global crosstalk on gene regulation. We find that crosstalk presents a significant challenge for organisms with low-specificity TFs, such as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting at equilibrium, including variants of cooperativity and combinatorial regulation. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements.' article_number: '12307' author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307 apa: Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016). Intrinsic limits to gene regulation by global crosstalk. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms12307 chicago: Friedlander, Tamar, Roshan Prizak, Calin C Guet, Nicholas H Barton, and Gašper Tkačik. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms12307. ieee: T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic limits to gene regulation by global crosstalk,” Nature Communications, vol. 7. Nature Publishing Group, 2016. ista: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits to gene regulation by global crosstalk. Nature Communications. 7, 12307. mla: Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature Communications, vol. 7, 12307, Nature Publishing Group, 2016, doi:10.1038/ncomms12307. short: T. Friedlander, R. Prizak, C.C. Guet, N.H. Barton, G. Tkačik, Nature Communications 7 (2016). date_created: 2018-12-11T11:51:34Z date_published: 2016-08-04T00:00:00Z date_updated: 2023-09-07T12:53:49Z day: '04' ddc: - '576' department: - _id: GaTk - _id: NiBa - _id: CaGu doi: 10.1038/ncomms12307 ec_funded: 1 file: - access_level: open_access checksum: fe3f3a1526d180b29fe691ab11435b78 content_type: application/pdf creator: system date_created: 2018-12-12T10:12:01Z date_updated: 2020-07-14T12:44:46Z file_id: '4919' file_name: IST-2016-627-v1+1_ncomms12307.pdf file_size: 861805 relation: main_file - access_level: open_access checksum: 164864a1a675f3ad80e9917c27aba07f content_type: application/pdf creator: system date_created: 2018-12-12T10:12:02Z date_updated: 2020-07-14T12:44:46Z file_id: '4920' file_name: IST-2016-627-v1+2_ncomms12307-s1.pdf file_size: 1084703 relation: main_file file_date_updated: 2020-07-14T12:44:46Z has_accepted_license: '1' intvolume: ' 7' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '08' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Nature Communications publication_status: published publisher: Nature Publishing Group publist_id: '5887' pubrep_id: '627' quality_controlled: '1' related_material: record: - id: '6071' relation: dissertation_contains status: public scopus_import: 1 status: public title: Intrinsic limits to gene regulation by global crosstalk tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 7 year: '2016' ... --- _id: '10794' abstract: - lang: eng text: Mathematical models are of fundamental importance in the understanding of complex population dynamics. For instance, they can be used to predict the population evolution starting from different initial conditions or to test how a system responds to external perturbations. For this analysis to be meaningful in real applications, however, it is of paramount importance to choose an appropriate model structure and to infer the model parameters from measured data. While many parameter inference methods are available for models based on deterministic ordinary differential equations, the same does not hold for more detailed individual-based models. Here we consider, in particular, stochastic models in which the time evolution of the species abundances is described by a continuous-time Markov chain. These models are governed by a master equation that is typically difficult to solve. Consequently, traditional inference methods that rely on iterative evaluation of parameter likelihoods are computationally intractable. The aim of this paper is to present recent advances in parameter inference for continuous-time Markov chain models, based on a moment closure approximation of the parameter likelihood, and to investigate how these results can help in understanding, and ultimately controlling, complex systems in ecology. Specifically, we illustrate through an agricultural pest case study how parameters of a stochastic individual-based model can be identified from measured data and how the resulting model can be used to solve an optimal control problem in a stochastic setting. In particular, we show how the matter of determining the optimal combination of two different pest control methods can be formulated as a chance constrained optimization problem where the control action is modeled as a state reset, leading to a hybrid system formulation. acknowledgement: "The authors would like to acknowledge contributions from Baptiste Mottet who performed preliminary analysis regarding parameter inference for the considered case study in a student project (Mottet, 2014/2015).\r\nThe research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement No. [291734] and from SystemsX under the project SignalX." article_number: '42' article_processing_charge: No article_type: original author: - first_name: Francesca full_name: Parise, Francesca last_name: Parise - first_name: John full_name: Lygeros, John last_name: Lygeros - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 citation: ama: 'Parise F, Lygeros J, Ruess J. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 2015;3. doi:10.3389/fenvs.2015.00042' apa: 'Parise, F., Lygeros, J., & Ruess, J. (2015). Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. Frontiers. https://doi.org/10.3389/fenvs.2015.00042' chicago: 'Parise, Francesca, John Lygeros, and Jakob Ruess. “Bayesian Inference for Stochastic Individual-Based Models of Ecological Systems: A Pest Control Simulation Study.” Frontiers in Environmental Science. Frontiers, 2015. https://doi.org/10.3389/fenvs.2015.00042.' ieee: 'F. Parise, J. Lygeros, and J. Ruess, “Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study,” Frontiers in Environmental Science, vol. 3. Frontiers, 2015.' ista: 'Parise F, Lygeros J, Ruess J. 2015. Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study. Frontiers in Environmental Science. 3, 42.' mla: 'Parise, Francesca, et al. “Bayesian Inference for Stochastic Individual-Based Models of Ecological Systems: A Pest Control Simulation Study.” Frontiers in Environmental Science, vol. 3, 42, Frontiers, 2015, doi:10.3389/fenvs.2015.00042.' short: F. Parise, J. Lygeros, J. Ruess, Frontiers in Environmental Science 3 (2015). date_created: 2022-02-25T11:42:25Z date_published: 2015-06-10T00:00:00Z date_updated: 2022-02-25T11:59:23Z day: '10' ddc: - '000' - '570' department: - _id: ToHe - _id: GaTk doi: 10.3389/fenvs.2015.00042 ec_funded: 1 file: - access_level: open_access checksum: 26c222487564e1be02a11d688d6f769d content_type: application/pdf creator: dernst date_created: 2022-02-25T11:55:26Z date_updated: 2022-02-25T11:55:26Z file_id: '10795' file_name: 2015_FrontiersEnvironmScience_Parise.pdf file_size: 1371201 relation: main_file success: 1 file_date_updated: 2022-02-25T11:55:26Z has_accepted_license: '1' intvolume: ' 3' keyword: - General Environmental Science language: - iso: eng month: '06' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Frontiers in Environmental Science publication_identifier: issn: - 2296-665X publication_status: published publisher: Frontiers quality_controlled: '1' scopus_import: '1' status: public title: 'Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 3 year: '2015' ... --- _id: '1539' abstract: - lang: eng text: 'Many stochastic models of biochemical reaction networks contain some chemical species for which the number of molecules that are present in the system can only be finite (for instance due to conservation laws), but also other species that can be present in arbitrarily large amounts. The prime example of such networks are models of gene expression, which typically contain a small and finite number of possible states for the promoter but an infinite number of possible states for the amount of mRNA and protein. One of the main approaches to analyze such models is through the use of equations for the time evolution of moments of the chemical species. Recently, a new approach based on conditional moments of the species with infinite state space given all the different possible states of the finite species has been proposed. It was argued that this approach allows one to capture more details about the full underlying probability distribution with a smaller number of equations. Here, I show that the result that less moments provide more information can only stem from an unnecessarily complicated description of the system in the classical formulation. The foundation of this argument will be the derivation of moment equations that describe the complete probability distribution over the finite state space but only low-order moments over the infinite state space. I will show that the number of equations that is needed is always less than what was previously claimed and always less than the number of conditional moment equations up to the same order. To support these arguments, a symbolic algorithm is provided that can be used to derive minimal systems of unconditional moment equations for models with partially finite state space. ' article_number: '244103' author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 citation: ama: Ruess J. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 2015;143(24). doi:10.1063/1.4937937 apa: Ruess, J. (2015). Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. American Institute of Physics. https://doi.org/10.1063/1.4937937 chicago: Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics. American Institute of Physics, 2015. https://doi.org/10.1063/1.4937937. ieee: J. Ruess, “Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space,” Journal of Chemical Physics, vol. 143, no. 24. American Institute of Physics, 2015. ista: Ruess J. 2015. Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space. Journal of Chemical Physics. 143(24), 244103. mla: Ruess, Jakob. “Minimal Moment Equations for Stochastic Models of Biochemical Reaction Networks with Partially Finite State Space.” Journal of Chemical Physics, vol. 143, no. 24, 244103, American Institute of Physics, 2015, doi:10.1063/1.4937937. short: J. Ruess, Journal of Chemical Physics 143 (2015). date_created: 2018-12-11T11:52:36Z date_published: 2015-12-22T00:00:00Z date_updated: 2021-01-12T06:51:28Z day: '22' ddc: - '000' department: - _id: ToHe - _id: GaTk doi: 10.1063/1.4937937 ec_funded: 1 file: - access_level: open_access checksum: 838657118ae286463a2b7737319f35ce content_type: application/pdf creator: system date_created: 2018-12-12T10:07:43Z date_updated: 2020-07-14T12:45:01Z file_id: '4641' file_name: IST-2016-593-v1+1_Minimal_moment_equations.pdf file_size: 605355 relation: main_file file_date_updated: 2020-07-14T12:45:01Z has_accepted_license: '1' intvolume: ' 143' issue: '24' language: - iso: eng month: '12' oa: 1 oa_version: Published Version project: - _id: 25EE3708-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '267989' name: Quantitative Reactive Modeling - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Journal of Chemical Physics publication_status: published publisher: American Institute of Physics publist_id: '5632' pubrep_id: '593' quality_controlled: '1' scopus_import: 1 status: public title: Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 143 year: '2015' ... --- _id: '1538' abstract: - lang: eng text: Systems biology rests on the idea that biological complexity can be better unraveled through the interplay of modeling and experimentation. However, the success of this approach depends critically on the informativeness of the chosen experiments, which is usually unknown a priori. Here, we propose a systematic scheme based on iterations of optimal experiment design, flow cytometry experiments, and Bayesian parameter inference to guide the discovery process in the case of stochastic biochemical reaction networks. To illustrate the benefit of our methodology, we apply it to the characterization of an engineered light-inducible gene expression circuit in yeast and compare the performance of the resulting model with models identified from nonoptimal experiments. In particular, we compare the parameter posterior distributions and the precision to which the outcome of future experiments can be predicted. Moreover, we illustrate how the identified stochastic model can be used to determine light induction patterns that make either the average amount of protein or the variability in a population of cells follow a desired profile. Our results show that optimal experiment design allows one to derive models that are accurate enough to precisely predict and regulate the protein expression in heterogeneous cell populations over extended periods of time. acknowledgement: 'J.R., F.P., and J.L. acknowledge support from the European Commission under the Network of Excellence HYCON2 (highly-complex and networked control systems) and SystemsX.ch under the SignalX Project. J.R. acknowledges support from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013 under REA (Research Executive Agency) Grant 291734. M.K. acknowledges support from Human Frontier Science Program Grant RP0061/2011 (www.hfsp.org). ' author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Francesca full_name: Parise, Francesca last_name: Parise - first_name: Andreas full_name: Milias Argeitis, Andreas last_name: Milias Argeitis - first_name: Mustafa full_name: Khammash, Mustafa last_name: Khammash - first_name: John full_name: Lygeros, John last_name: Lygeros citation: ama: Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 2015;112(26):8148-8153. doi:10.1073/pnas.1423947112 apa: Ruess, J., Parise, F., Milias Argeitis, A., Khammash, M., & Lygeros, J. (2015). Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1423947112 chicago: Ruess, Jakob, Francesca Parise, Andreas Milias Argeitis, Mustafa Khammash, and John Lygeros. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1423947112. ieee: J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, and J. Lygeros, “Iterative experiment design guides the characterization of a light-inducible gene expression circuit,” PNAS, vol. 112, no. 26. National Academy of Sciences, pp. 8148–8153, 2015. ista: Ruess J, Parise F, Milias Argeitis A, Khammash M, Lygeros J. 2015. Iterative experiment design guides the characterization of a light-inducible gene expression circuit. PNAS. 112(26), 8148–8153. mla: Ruess, Jakob, et al. “Iterative Experiment Design Guides the Characterization of a Light-Inducible Gene Expression Circuit.” PNAS, vol. 112, no. 26, National Academy of Sciences, 2015, pp. 8148–53, doi:10.1073/pnas.1423947112. short: J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, J. Lygeros, PNAS 112 (2015) 8148–8153. date_created: 2018-12-11T11:52:36Z date_published: 2015-06-30T00:00:00Z date_updated: 2021-01-12T06:51:27Z day: '30' department: - _id: ToHe - _id: GaTk doi: 10.1073/pnas.1423947112 ec_funded: 1 external_id: pmid: - '26085136' intvolume: ' 112' issue: '26' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4491780/ month: '06' oa: 1 oa_version: Submitted Version page: 8148 - 8153 pmid: 1 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '5633' quality_controlled: '1' scopus_import: 1 status: public title: Iterative experiment design guides the characterization of a light-inducible gene expression circuit type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 112 year: '2015' ... --- _id: '1564' article_number: '145' author: - first_name: Matthieu full_name: Gilson, Matthieu last_name: Gilson - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Friedemann full_name: Zenke, Friedemann last_name: Zenke citation: ama: 'Gilson M, Savin C, Zenke F. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 2015;9(11). doi:10.3389/fncom.2015.00145' apa: 'Gilson, M., Savin, C., & Zenke, F. (2015). Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2015.00145' chicago: 'Gilson, Matthieu, Cristina Savin, and Friedemann Zenke. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience. Frontiers Research Foundation, 2015. https://doi.org/10.3389/fncom.2015.00145.' ieee: 'M. Gilson, C. Savin, and F. Zenke, “Editorial: Emergent neural computation from the interaction of different forms of plasticity,” Frontiers in Computational Neuroscience, vol. 9, no. 11. Frontiers Research Foundation, 2015.' ista: 'Gilson M, Savin C, Zenke F. 2015. Editorial: Emergent neural computation from the interaction of different forms of plasticity. Frontiers in Computational Neuroscience. 9(11), 145.' mla: 'Gilson, Matthieu, et al. “Editorial: Emergent Neural Computation from the Interaction of Different Forms of Plasticity.” Frontiers in Computational Neuroscience, vol. 9, no. 11, 145, Frontiers Research Foundation, 2015, doi:10.3389/fncom.2015.00145.' short: M. Gilson, C. Savin, F. Zenke, Frontiers in Computational Neuroscience 9 (2015). date_created: 2018-12-11T11:52:45Z date_published: 2015-11-30T00:00:00Z date_updated: 2021-01-12T06:51:37Z day: '30' ddc: - '570' department: - _id: GaTk doi: 10.3389/fncom.2015.00145 ec_funded: 1 file: - access_level: open_access checksum: cea73b6d3ef1579f32da10b82f4de4fd content_type: application/pdf creator: system date_created: 2018-12-12T10:12:09Z date_updated: 2020-07-14T12:45:02Z file_id: '4927' file_name: IST-2016-479-v1+1_fncom-09-00145.pdf file_size: 187038 relation: main_file file_date_updated: 2020-07-14T12:45:02Z has_accepted_license: '1' intvolume: ' 9' issue: '11' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Frontiers in Computational Neuroscience publication_status: published publisher: Frontiers Research Foundation publist_id: '5607' pubrep_id: '479' quality_controlled: '1' scopus_import: 1 status: public title: 'Editorial: Emergent neural computation from the interaction of different forms of plasticity' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 9 year: '2015' ... --- _id: '1570' abstract: - lang: eng text: Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher-level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no systemspecific modifications of the DEP rule. They rather arise from the underlying mechanism of spontaneous symmetry breaking,which is due to the tight brain body environment coupling. The new synaptic rule is biologically plausible and would be an interesting target for neurobiological investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution. author: - first_name: Ralf full_name: Der, Ralf last_name: Der - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius citation: ama: Der R, Martius GS. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 2015;112(45):E6224-E6232. doi:10.1073/pnas.1508400112 apa: Der, R., & Martius, G. S. (2015). Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1508400112 chicago: Der, Ralf, and Georg S Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1508400112. ieee: R. Der and G. S. Martius, “Novel plasticity rule can explain the development of sensorimotor intelligence,” PNAS, vol. 112, no. 45. National Academy of Sciences, pp. E6224–E6232, 2015. ista: Der R, Martius GS. 2015. Novel plasticity rule can explain the development of sensorimotor intelligence. PNAS. 112(45), E6224–E6232. mla: Der, Ralf, and Georg S. Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.” PNAS, vol. 112, no. 45, National Academy of Sciences, 2015, pp. E6224–32, doi:10.1073/pnas.1508400112. short: R. Der, G.S. Martius, PNAS 112 (2015) E6224–E6232. date_created: 2018-12-11T11:52:47Z date_published: 2015-11-10T00:00:00Z date_updated: 2021-01-12T06:51:40Z day: '10' department: - _id: ChLa - _id: GaTk doi: 10.1073/pnas.1508400112 ec_funded: 1 external_id: pmid: - '26504200' intvolume: ' 112' issue: '45' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4653169/ month: '11' oa: 1 oa_version: Submitted Version page: E6224 - E6232 pmid: 1 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '5601' quality_controlled: '1' scopus_import: 1 status: public title: Novel plasticity rule can explain the development of sensorimotor intelligence type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 112 year: '2015' ... --- _id: '1658' abstract: - lang: eng text: Continuous-time Markov chain (CTMC) models have become a central tool for understanding the dynamics of complex reaction networks and the importance of stochasticity in the underlying biochemical processes. When such models are employed to answer questions in applications, in order to ensure that the model provides a sufficiently accurate representation of the real system, it is of vital importance that the model parameters are inferred from real measured data. This, however, is often a formidable task and all of the existing methods fail in one case or the other, usually because the underlying CTMC model is high-dimensional and computationally difficult to analyze. The parameter inference methods that tend to scale best in the dimension of the CTMC are based on so-called moment closure approximations. However, there exists a large number of different moment closure approximations and it is typically hard to say a priori which of the approximations is the most suitable for the inference procedure. Here, we propose a moment-based parameter inference method that automatically chooses the most appropriate moment closure method. Accordingly, contrary to existing methods, the user is not required to be experienced in moment closure techniques. In addition to that, our method adaptively changes the approximation during the parameter inference to ensure that always the best approximation is used, even in cases where different approximations are best in different regions of the parameter space. alternative_title: - LNCS author: - first_name: Sergiy full_name: Bogomolov, Sergiy id: 369D9A44-F248-11E8-B48F-1D18A9856A87 last_name: Bogomolov orcid: 0000-0002-0686-0365 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000−0002−2985−7724 - first_name: Andreas full_name: Podelski, Andreas last_name: Podelski - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Christian full_name: Schilling, Christian last_name: Schilling citation: ama: Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. Adaptive moment closure for parameter inference of biochemical reaction networks. 2015;9308:77-89. doi:10.1007/978-3-319-23401-4_8 apa: 'Bogomolov, S., Henzinger, T. A., Podelski, A., Ruess, J., & Schilling, C. (2015). Adaptive moment closure for parameter inference of biochemical reaction networks. Presented at the CMSB: Computational Methods in Systems Biology, Nantes, France: Springer. https://doi.org/10.1007/978-3-319-23401-4_8' chicago: Bogomolov, Sergiy, Thomas A Henzinger, Andreas Podelski, Jakob Ruess, and Christian Schilling. “Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks.” Lecture Notes in Computer Science. Springer, 2015. https://doi.org/10.1007/978-3-319-23401-4_8. ieee: S. Bogomolov, T. A. Henzinger, A. Podelski, J. Ruess, and C. Schilling, “Adaptive moment closure for parameter inference of biochemical reaction networks,” vol. 9308. Springer, pp. 77–89, 2015. ista: Bogomolov S, Henzinger TA, Podelski A, Ruess J, Schilling C. 2015. Adaptive moment closure for parameter inference of biochemical reaction networks. 9308, 77–89. mla: Bogomolov, Sergiy, et al. Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks. Vol. 9308, Springer, 2015, pp. 77–89, doi:10.1007/978-3-319-23401-4_8. short: S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, C. Schilling, 9308 (2015) 77–89. conference: end_date: 2015-09-18 location: Nantes, France name: 'CMSB: Computational Methods in Systems Biology' start_date: 2015-09-16 date_created: 2018-12-11T11:53:18Z date_published: 2015-09-01T00:00:00Z date_updated: 2023-02-21T16:17:24Z day: '01' department: - _id: ToHe - _id: GaTk doi: 10.1007/978-3-319-23401-4_8 ec_funded: 1 intvolume: ' 9308' language: - iso: eng month: '09' oa_version: None page: 77 - 89 project: - _id: 25EE3708-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '267989' name: Quantitative Reactive Modeling - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 25832EC2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S 11407_N23 name: Rigorous Systems Engineering - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication_status: published publisher: Springer publist_id: '5492' quality_controlled: '1' related_material: record: - id: '1148' relation: later_version status: public scopus_import: 1 series_title: Lecture Notes in Computer Science status: public title: Adaptive moment closure for parameter inference of biochemical reaction networks type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 9308 year: '2015' ... --- _id: '1697' abstract: - lang: eng text: Motion tracking is a challenge the visual system has to solve by reading out the retinal population. It is still unclear how the information from different neurons can be combined together to estimate the position of an object. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bar’s position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. We then took advantage of this unprecedented precision to explore the spatial structure of the retina’s population code. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar’s position. Instead, we found that most ganglion cells in the salamander fired sparsely and idiosyncratically, so that their neural image did not track the bar. Furthermore, ganglion cell activity spanned an area much larger than predicted by their receptive fields, with cells coding for motion far in their surround. As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision. This organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits. acknowledgement: 'This work was supported by grants EY 014196 and EY 017934 to MJB, ANR OPTIMA, the French State program Investissements d’Avenir managed by the Agence Nationale de la Recherche [LIFESENSES: ANR-10-LABX-65], and by a EC grant from the Human Brain Project (CLAP) to OM, the Austrian Research Foundation FWF P25651 to VBS and GT. VBS is partially supported by contracts MEC, Spain (Grant No. AYA2010- 22111-C03-02, Grant No. AYA2013-48623-C2-2 and FEDER Funds).' article_number: e1004304 author: - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Vicente full_name: Botella Soler, Vicente id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: Kristina full_name: Simmons, Kristina last_name: Simmons - first_name: Thierry full_name: Mora, Thierry last_name: Mora - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Michael full_name: Berry, Michael last_name: Berry citation: ama: Marre O, Botella Soler V, Simmons K, Mora T, Tkačik G, Berry M. High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. 2015;11(7). doi:10.1371/journal.pcbi.1004304 apa: Marre, O., Botella Soler, V., Simmons, K., Mora, T., Tkačik, G., & Berry, M. (2015). High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004304 chicago: Marre, Olivier, Vicente Botella Soler, Kristina Simmons, Thierry Mora, Gašper Tkačik, and Michael Berry. “High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.” PLoS Computational Biology. Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004304. ieee: O. Marre, V. Botella Soler, K. Simmons, T. Mora, G. Tkačik, and M. Berry, “High accuracy decoding of dynamical motion from a large retinal population,” PLoS Computational Biology, vol. 11, no. 7. Public Library of Science, 2015. ista: Marre O, Botella Soler V, Simmons K, Mora T, Tkačik G, Berry M. 2015. High accuracy decoding of dynamical motion from a large retinal population. PLoS Computational Biology. 11(7), e1004304. mla: Marre, Olivier, et al. “High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.” PLoS Computational Biology, vol. 11, no. 7, e1004304, Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004304. short: O. Marre, V. Botella Soler, K. Simmons, T. Mora, G. Tkačik, M. Berry, PLoS Computational Biology 11 (2015). date_created: 2018-12-11T11:53:31Z date_published: 2015-07-01T00:00:00Z date_updated: 2021-01-12T06:52:35Z day: '01' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004304 file: - access_level: open_access checksum: 472b979f3f1cffb37b3e503f085115ca content_type: application/pdf creator: system date_created: 2018-12-12T10:16:25Z date_updated: 2020-07-14T12:45:12Z file_id: '5212' file_name: IST-2016-455-v1+1_journal.pcbi.1004304.pdf file_size: 4673930 relation: main_file file_date_updated: 2020-07-14T12:45:12Z has_accepted_license: '1' intvolume: ' 11' issue: '7' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science publist_id: '5447' pubrep_id: '455' quality_controlled: '1' scopus_import: 1 status: public title: High accuracy decoding of dynamical motion from a large retinal population tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2015' ... --- _id: '1701' abstract: - lang: eng text: 'The activity of a neural network is defined by patterns of spiking and silence from the individual neurons. Because spikes are (relatively) sparse, patterns of activity with increasing numbers of spikes are less probable, but, with more spikes, the number of possible patterns increases. This tradeoff between probability and numerosity is mathematically equivalent to the relationship between entropy and energy in statistical physics. We construct this relationship for populations of up to N = 160 neurons in a small patch of the vertebrate retina, using a combination of direct and model-based analyses of experiments on the response of this network to naturalistic movies. We see signs of a thermodynamic limit, where the entropy per neuron approaches a smooth function of the energy per neuron as N increases. The form of this function corresponds to the distribution of activity being poised near an unusual kind of critical point. We suggest further tests of criticality, and give a brief discussion of its functional significance. ' acknowledgement: "Research was supported in part by National Science Foundation Grants PHY-1305525, PHY-1451171, and CCF-0939370, by National Institutes of Health Grant R01 EY14196, and by Austrian Science Foundation Grant FWF P25651. Additional support was provided by the\r\nFannie and John Hertz Foundation, by the Swartz Foundation, by the W. M. Keck Foundation, and by the Simons Foundation." author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Thierry full_name: Mora, Thierry last_name: Mora - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Dario full_name: Amodei, Dario last_name: Amodei - first_name: Stephanie full_name: Palmer, Stephanie last_name: Palmer - first_name: Michael full_name: Berry Ii, Michael last_name: Berry Ii - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Tkačik G, Mora T, Marre O, et al. Thermodynamics and signatures of criticality in a network of neurons. PNAS. 2015;112(37):11508-11513. doi:10.1073/pnas.1514188112 apa: Tkačik, G., Mora, T., Marre, O., Amodei, D., Palmer, S., Berry Ii, M., & Bialek, W. (2015). Thermodynamics and signatures of criticality in a network of neurons. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1514188112 chicago: Tkačik, Gašper, Thierry Mora, Olivier Marre, Dario Amodei, Stephanie Palmer, Michael Berry Ii, and William Bialek. “Thermodynamics and Signatures of Criticality in a Network of Neurons.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1514188112. ieee: G. Tkačik et al., “Thermodynamics and signatures of criticality in a network of neurons,” PNAS, vol. 112, no. 37. National Academy of Sciences, pp. 11508–11513, 2015. ista: Tkačik G, Mora T, Marre O, Amodei D, Palmer S, Berry Ii M, Bialek W. 2015. Thermodynamics and signatures of criticality in a network of neurons. PNAS. 112(37), 11508–11513. mla: Tkačik, Gašper, et al. “Thermodynamics and Signatures of Criticality in a Network of Neurons.” PNAS, vol. 112, no. 37, National Academy of Sciences, 2015, pp. 11508–13, doi:10.1073/pnas.1514188112. short: G. Tkačik, T. Mora, O. Marre, D. Amodei, S. Palmer, M. Berry Ii, W. Bialek, PNAS 112 (2015) 11508–11513. date_created: 2018-12-11T11:53:33Z date_published: 2015-09-15T00:00:00Z date_updated: 2021-01-12T06:52:37Z day: '15' department: - _id: GaTk doi: 10.1073/pnas.1514188112 external_id: pmid: - '26330611' intvolume: ' 112' issue: '37' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4577210/ month: '09' oa: 1 oa_version: Submitted Version page: 11508 - 11513 pmid: 1 project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '5440' quality_controlled: '1' scopus_import: 1 status: public title: Thermodynamics and signatures of criticality in a network of neurons type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 112 year: '2015' ... --- _id: '1861' abstract: - lang: eng text: Continuous-time Markov chains are commonly used in practice for modeling biochemical reaction networks in which the inherent randomness of themolecular interactions cannot be ignored. This has motivated recent research effort into methods for parameter inference and experiment design for such models. The major difficulty is that such methods usually require one to iteratively solve the chemical master equation that governs the time evolution of the probability distribution of the system. This, however, is rarely possible, and even approximation techniques remain limited to relatively small and simple systems. An alternative explored in this article is to base methods on only some low-order moments of the entire probability distribution. We summarize the theory behind such moment-based methods for parameter inference and experiment design and provide new case studies where we investigate their performance. acknowledgement: "HYCON2; EC; European Commission\r\n" article_number: '8' author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: John full_name: Lygeros, John last_name: Lygeros citation: ama: Ruess J, Lygeros J. Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. 2015;25(2). doi:10.1145/2688906 apa: Ruess, J., & Lygeros, J. (2015). Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. ACM. https://doi.org/10.1145/2688906 chicago: Ruess, Jakob, and John Lygeros. “Moment-Based Methods for Parameter Inference and Experiment Design for Stochastic Biochemical Reaction Networks.” ACM Transactions on Modeling and Computer Simulation. ACM, 2015. https://doi.org/10.1145/2688906. ieee: J. Ruess and J. Lygeros, “Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks,” ACM Transactions on Modeling and Computer Simulation, vol. 25, no. 2. ACM, 2015. ista: Ruess J, Lygeros J. 2015. Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks. ACM Transactions on Modeling and Computer Simulation. 25(2), 8. mla: Ruess, Jakob, and John Lygeros. “Moment-Based Methods for Parameter Inference and Experiment Design for Stochastic Biochemical Reaction Networks.” ACM Transactions on Modeling and Computer Simulation, vol. 25, no. 2, 8, ACM, 2015, doi:10.1145/2688906. short: J. Ruess, J. Lygeros, ACM Transactions on Modeling and Computer Simulation 25 (2015). date_created: 2018-12-11T11:54:25Z date_published: 2015-02-01T00:00:00Z date_updated: 2021-01-12T06:53:41Z day: '01' department: - _id: ToHe - _id: GaTk doi: 10.1145/2688906 intvolume: ' 25' issue: '2' language: - iso: eng month: '02' oa_version: None publication: ACM Transactions on Modeling and Computer Simulation publication_status: published publisher: ACM publist_id: '5238' quality_controlled: '1' scopus_import: 1 status: public title: Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 25 year: '2015' ... --- _id: '1885' abstract: - lang: eng text: 'The concept of positional information is central to our understanding of how cells determine their location in a multicellular structure and thereby their developmental fates. Nevertheless, positional information has neither been defined mathematically nor quantified in a principled way. Here we provide an information-theoretic definition in the context of developmental gene expression patterns and examine the features of expression patterns that affect positional information quantitatively. We connect positional information with the concept of positional error and develop tools to directly measure information and error from experimental data. We illustrate our framework for the case of gap gene expression patterns in the early Drosophila embryo and show how information that is distributed among only four genes is sufficient to determine developmental fates with nearly single-cell resolution. Our approach can be generalized to a variety of different model systems; procedures and examples are discussed in detail. ' author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Julien full_name: Dubuis, Julien last_name: Dubuis - first_name: Mariela full_name: Petkova, Mariela last_name: Petkova - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor citation: ama: 'Tkačik G, Dubuis J, Petkova M, Gregor T. Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. 2015;199(1):39-59. doi:10.1534/genetics.114.171850' apa: 'Tkačik, G., Dubuis, J., Petkova, M., & Gregor, T. (2015). Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. Genetics Society of America. https://doi.org/10.1534/genetics.114.171850' chicago: 'Tkačik, Gašper, Julien Dubuis, Mariela Petkova, and Thomas Gregor. “Positional Information, Positional Error, and Readout Precision in Morphogenesis: A Mathematical Framework.” Genetics. Genetics Society of America, 2015. https://doi.org/10.1534/genetics.114.171850.' ieee: 'G. Tkačik, J. Dubuis, M. Petkova, and T. Gregor, “Positional information, positional error, and readout precision in morphogenesis: A mathematical framework,” Genetics, vol. 199, no. 1. Genetics Society of America, pp. 39–59, 2015.' ista: 'Tkačik G, Dubuis J, Petkova M, Gregor T. 2015. Positional information, positional error, and readout precision in morphogenesis: A mathematical framework. Genetics. 199(1), 39–59.' mla: 'Tkačik, Gašper, et al. “Positional Information, Positional Error, and Readout Precision in Morphogenesis: A Mathematical Framework.” Genetics, vol. 199, no. 1, Genetics Society of America, 2015, pp. 39–59, doi:10.1534/genetics.114.171850.' short: G. Tkačik, J. Dubuis, M. Petkova, T. Gregor, Genetics 199 (2015) 39–59. date_created: 2018-12-11T11:54:32Z date_published: 2015-01-01T00:00:00Z date_updated: 2021-01-12T06:53:50Z day: '01' department: - _id: GaTk doi: 10.1534/genetics.114.171850 intvolume: ' 199' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1404.5599 month: '01' oa: 1 oa_version: Preprint page: 39 - 59 publication: Genetics publication_status: published publisher: Genetics Society of America publist_id: '5210' quality_controlled: '1' scopus_import: 1 status: public title: 'Positional information, positional error, and readout precision in morphogenesis: A mathematical framework' type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 199 year: '2015' ... --- _id: '1940' abstract: - lang: eng text: We typically think of cells as responding to external signals independently by regulating their gene expression levels, yet they often locally exchange information and coordinate. Can such spatial coupling be of benefit for conveying signals subject to gene regulatory noise? Here we extend our information-theoretic framework for gene regulation to spatially extended systems. As an example, we consider a lattice of nuclei responding to a concentration field of a transcriptional regulator (the "input") by expressing a single diffusible target gene. When input concentrations are low, diffusive coupling markedly improves information transmission; optimal gene activation functions also systematically change. A qualitatively new regulatory strategy emerges where individual cells respond to the input in a nearly step-like fashion that is subsequently averaged out by strong diffusion. While motivated by early patterning events in the Drosophila embryo, our framework is generically applicable to spatially coupled stochastic gene expression models. article_number: '062710' author: - first_name: Thomas R full_name: Sokolowski, Thomas R id: 3E999752-F248-11E8-B48F-1D18A9856A87 last_name: Sokolowski orcid: 0000-0002-1287-3779 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Sokolowski TR, Tkačik G. Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2015;91(6). doi:10.1103/PhysRevE.91.062710 apa: Sokolowski, T. R., & Tkačik, G. (2015). Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.91.062710 chicago: Sokolowski, Thomas R, and Gašper Tkačik. “Optimizing Information Flow in Small Genetic Networks. IV. Spatial Coupling.” Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics, 2015. https://doi.org/10.1103/PhysRevE.91.062710. ieee: T. R. Sokolowski and G. Tkačik, “Optimizing information flow in small genetic networks. IV. Spatial coupling,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 91, no. 6. American Institute of Physics, 2015. ista: Sokolowski TR, Tkačik G. 2015. Optimizing information flow in small genetic networks. IV. Spatial coupling. Physical Review E Statistical Nonlinear and Soft Matter Physics. 91(6), 062710. mla: Sokolowski, Thomas R., and Gašper Tkačik. “Optimizing Information Flow in Small Genetic Networks. IV. Spatial Coupling.” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 91, no. 6, 062710, American Institute of Physics, 2015, doi:10.1103/PhysRevE.91.062710. short: T.R. Sokolowski, G. Tkačik, Physical Review E Statistical Nonlinear and Soft Matter Physics 91 (2015). date_created: 2018-12-11T11:54:49Z date_published: 2015-06-15T00:00:00Z date_updated: 2021-01-12T06:54:13Z day: '15' department: - _id: GaTk doi: 10.1103/PhysRevE.91.062710 intvolume: ' 91' issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1501.04015 month: '06' oa: 1 oa_version: Preprint publication: Physical Review E Statistical Nonlinear and Soft Matter Physics publication_status: published publisher: American Institute of Physics publist_id: '5145' quality_controlled: '1' scopus_import: 1 status: public title: Optimizing information flow in small genetic networks. IV. Spatial coupling type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 91 year: '2015' ... --- _id: '9718' article_processing_charge: No author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Avraham E. full_name: Mayo, Avraham E. last_name: Mayo - first_name: Tsvi full_name: Tlusty, Tsvi last_name: Tlusty - first_name: Uri full_name: Alon, Uri last_name: Alon citation: ama: Friedlander T, Mayo AE, Tlusty T, Alon U. Supporting information text. 2015. doi:10.1371/journal.pcbi.1004055.s001 apa: Friedlander, T., Mayo, A. E., Tlusty, T., & Alon, U. (2015). Supporting information text. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055.s001 chicago: Friedlander, Tamar, Avraham E. Mayo, Tsvi Tlusty, and Uri Alon. “Supporting Information Text.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.s001. ieee: T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Supporting information text.” Public Library of Science, 2015. ista: Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Supporting information text, Public Library of Science, 10.1371/journal.pcbi.1004055.s001. mla: Friedlander, Tamar, et al. Supporting Information Text. Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004055.s001. short: T. Friedlander, A.E. Mayo, T. Tlusty, U. Alon, (2015). date_created: 2021-07-26T08:35:23Z date_published: 2015-03-23T00:00:00Z date_updated: 2023-02-23T10:16:13Z day: '23' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004055.s001 month: '03' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1827' relation: used_in_publication status: public status: public title: Supporting information text type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ... --- _id: '1827' abstract: - lang: eng text: Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved. article_processing_charge: No author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Avraham full_name: Mayo, Avraham last_name: Mayo - first_name: Tsvi full_name: Tlusty, Tsvi last_name: Tlusty - first_name: Uri full_name: Alon, Uri last_name: Alon citation: ama: Friedlander T, Mayo A, Tlusty T, Alon U. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 2015;11(3). doi:10.1371/journal.pcbi.1004055 apa: Friedlander, T., Mayo, A., Tlusty, T., & Alon, U. (2015). Evolution of bow-tie architectures in biology. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055 chicago: Friedlander, Tamar, Avraham Mayo, Tsvi Tlusty, and Uri Alon. “Evolution of Bow-Tie Architectures in Biology.” PLoS Computational Biology. Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055. ieee: T. Friedlander, A. Mayo, T. Tlusty, and U. Alon, “Evolution of bow-tie architectures in biology,” PLoS Computational Biology, vol. 11, no. 3. Public Library of Science, 2015. ista: Friedlander T, Mayo A, Tlusty T, Alon U. 2015. Evolution of bow-tie architectures in biology. PLoS Computational Biology. 11(3). mla: Friedlander, Tamar, et al. “Evolution of Bow-Tie Architectures in Biology.” PLoS Computational Biology, vol. 11, no. 3, Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004055. short: T. Friedlander, A. Mayo, T. Tlusty, U. Alon, PLoS Computational Biology 11 (2015). date_created: 2018-12-11T11:54:14Z date_published: 2015-03-23T00:00:00Z date_updated: 2023-02-23T14:07:51Z day: '23' ddc: - '576' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004055 ec_funded: 1 file: - access_level: open_access checksum: b8aa66f450ff8de393014b87ec7d2efb content_type: application/pdf creator: system date_created: 2018-12-12T10:15:39Z date_updated: 2020-07-14T12:45:17Z file_id: '5161' file_name: IST-2016-452-v1+1_journal.pcbi.1004055.pdf file_size: 1811647 relation: main_file file_date_updated: 2020-07-14T12:45:17Z has_accepted_license: '1' intvolume: ' 11' issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science publist_id: '5278' pubrep_id: '452' quality_controlled: '1' related_material: record: - id: '9718' relation: research_data status: public - id: '9773' relation: research_data status: public scopus_import: 1 status: public title: Evolution of bow-tie architectures in biology tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2015' ... --- _id: '9773' article_processing_charge: No author: - first_name: Tamar full_name: Friedlander, Tamar id: 36A5845C-F248-11E8-B48F-1D18A9856A87 last_name: Friedlander - first_name: Avraham E. full_name: Mayo, Avraham E. last_name: Mayo - first_name: Tsvi full_name: Tlusty, Tsvi last_name: Tlusty - first_name: Uri full_name: Alon, Uri last_name: Alon citation: ama: Friedlander T, Mayo AE, Tlusty T, Alon U. Evolutionary simulation code. 2015. doi:10.1371/journal.pcbi.1004055.s002 apa: Friedlander, T., Mayo, A. E., Tlusty, T., & Alon, U. (2015). Evolutionary simulation code. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1004055.s002 chicago: Friedlander, Tamar, Avraham E. Mayo, Tsvi Tlusty, and Uri Alon. “Evolutionary Simulation Code.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pcbi.1004055.s002. ieee: T. Friedlander, A. E. Mayo, T. Tlusty, and U. Alon, “Evolutionary simulation code.” Public Library of Science, 2015. ista: Friedlander T, Mayo AE, Tlusty T, Alon U. 2015. Evolutionary simulation code, Public Library of Science, 10.1371/journal.pcbi.1004055.s002. mla: Friedlander, Tamar, et al. Evolutionary Simulation Code. Public Library of Science, 2015, doi:10.1371/journal.pcbi.1004055.s002. short: T. Friedlander, A.E. Mayo, T. Tlusty, U. Alon, (2015). date_created: 2021-08-05T12:58:07Z date_published: 2015-03-23T00:00:00Z date_updated: 2023-02-23T10:16:13Z day: '23' department: - _id: GaTk doi: 10.1371/journal.pcbi.1004055.s002 month: '03' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1827' relation: used_in_publication status: public status: public title: Evolutionary simulation code type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ... --- _id: '9712' article_processing_charge: No author: - first_name: Murat full_name: Tugrul, Murat id: 37C323C6-F248-11E8-B48F-1D18A9856A87 last_name: Tugrul orcid: 0000-0002-8523-0758 - first_name: Tiago full_name: Paixao, Tiago id: 2C5658E6-F248-11E8-B48F-1D18A9856A87 last_name: Paixao orcid: 0000-0003-2361-3953 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Tugrul M, Paixao T, Barton NH, Tkačik G. Other fitness models for comparison & for interacting TFBSs. 2015. doi:10.1371/journal.pgen.1005639.s001 apa: Tugrul, M., Paixao, T., Barton, N. H., & Tkačik, G. (2015). Other fitness models for comparison & for interacting TFBSs. Public Library of Science. https://doi.org/10.1371/journal.pgen.1005639.s001 chicago: Tugrul, Murat, Tiago Paixao, Nicholas H Barton, and Gašper Tkačik. “Other Fitness Models for Comparison & for Interacting TFBSs.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pgen.1005639.s001. ieee: M. Tugrul, T. Paixao, N. H. Barton, and G. Tkačik, “Other fitness models for comparison & for interacting TFBSs.” Public Library of Science, 2015. ista: Tugrul M, Paixao T, Barton NH, Tkačik G. 2015. Other fitness models for comparison & for interacting TFBSs, Public Library of Science, 10.1371/journal.pgen.1005639.s001. mla: Tugrul, Murat, et al. Other Fitness Models for Comparison & for Interacting TFBSs. Public Library of Science, 2015, doi:10.1371/journal.pgen.1005639.s001. short: M. Tugrul, T. Paixao, N.H. Barton, G. Tkačik, (2015). date_created: 2021-07-23T12:00:37Z date_published: 2015-11-06T00:00:00Z date_updated: 2023-02-23T10:09:08Z day: '06' department: - _id: NiBa - _id: CaGu - _id: GaTk doi: 10.1371/journal.pgen.1005639.s001 month: '11' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1666' relation: used_in_publication status: public status: public title: Other fitness models for comparison & for interacting TFBSs type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ... --- _id: '1666' abstract: - lang: eng text: Evolution of gene regulation is crucial for our understanding of the phenotypic differences between species, populations and individuals. Sequence-specific binding of transcription factors to the regulatory regions on the DNA is a key regulatory mechanism that determines gene expression and hence heritable phenotypic variation. We use a biophysical model for directional selection on gene expression to estimate the rates of gain and loss of transcription factor binding sites (TFBS) in finite populations under both point and insertion/deletion mutations. Our results show that these rates are typically slow for a single TFBS in an isolated DNA region, unless the selection is extremely strong. These rates decrease drastically with increasing TFBS length or increasingly specific protein-DNA interactions, making the evolution of sites longer than ∼ 10 bp unlikely on typical eukaryotic speciation timescales. Similarly, evolution converges to the stationary distribution of binding sequences very slowly, making the equilibrium assumption questionable. The availability of longer regulatory sequences in which multiple binding sites can evolve simultaneously, the presence of “pre-sites” or partially decayed old sites in the initial sequence, and biophysical cooperativity between transcription factors, can all facilitate gain of TFBS and reconcile theoretical calculations with timescales inferred from comparative genomics. author: - first_name: Murat full_name: Tugrul, Murat id: 37C323C6-F248-11E8-B48F-1D18A9856A87 last_name: Tugrul orcid: 0000-0002-8523-0758 - first_name: Tiago full_name: Paixao, Tiago id: 2C5658E6-F248-11E8-B48F-1D18A9856A87 last_name: Paixao orcid: 0000-0003-2361-3953 - first_name: Nicholas H full_name: Barton, Nicholas H id: 4880FE40-F248-11E8-B48F-1D18A9856A87 last_name: Barton orcid: 0000-0002-8548-5240 - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Tugrul M, Paixao T, Barton NH, Tkačik G. Dynamics of transcription factor binding site evolution. PLoS Genetics. 2015;11(11). doi:10.1371/journal.pgen.1005639 apa: Tugrul, M., Paixao, T., Barton, N. H., & Tkačik, G. (2015). Dynamics of transcription factor binding site evolution. PLoS Genetics. Public Library of Science. https://doi.org/10.1371/journal.pgen.1005639 chicago: Tugrul, Murat, Tiago Paixao, Nicholas H Barton, and Gašper Tkačik. “Dynamics of Transcription Factor Binding Site Evolution.” PLoS Genetics. Public Library of Science, 2015. https://doi.org/10.1371/journal.pgen.1005639. ieee: M. Tugrul, T. Paixao, N. H. Barton, and G. Tkačik, “Dynamics of transcription factor binding site evolution,” PLoS Genetics, vol. 11, no. 11. Public Library of Science, 2015. ista: Tugrul M, Paixao T, Barton NH, Tkačik G. 2015. Dynamics of transcription factor binding site evolution. PLoS Genetics. 11(11). mla: Tugrul, Murat, et al. “Dynamics of Transcription Factor Binding Site Evolution.” PLoS Genetics, vol. 11, no. 11, Public Library of Science, 2015, doi:10.1371/journal.pgen.1005639. short: M. Tugrul, T. Paixao, N.H. Barton, G. Tkačik, PLoS Genetics 11 (2015). date_created: 2018-12-11T11:53:21Z date_published: 2015-11-06T00:00:00Z date_updated: 2023-09-07T11:53:49Z day: '06' ddc: - '576' department: - _id: NiBa - _id: CaGu - _id: GaTk doi: 10.1371/journal.pgen.1005639 ec_funded: 1 file: - access_level: open_access checksum: a4e72fca5ccf40ddacf4d08c8e46b554 content_type: application/pdf creator: system date_created: 2018-12-12T10:07:58Z date_updated: 2020-07-14T12:45:10Z file_id: '4657' file_name: IST-2016-463-v1+1_journal.pgen.1005639.pdf file_size: 2580778 relation: main_file file_date_updated: 2020-07-14T12:45:10Z has_accepted_license: '1' intvolume: ' 11' issue: '11' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation publication: PLoS Genetics publication_status: published publisher: Public Library of Science publist_id: '5483' pubrep_id: '463' quality_controlled: '1' related_material: record: - id: '9712' relation: research_data status: public - id: '1131' relation: dissertation_contains status: public scopus_import: 1 status: public title: Dynamics of transcription factor binding site evolution tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2015' ... --- _id: '1576' abstract: - lang: eng text: 'Gene expression is controlled primarily by interactions between transcription factor proteins (TFs) and the regulatory DNA sequence, a process that can be captured well by thermodynamic models of regulation. These models, however, neglect regulatory crosstalk: the possibility that noncognate TFs could initiate transcription, with potentially disastrous effects for the cell. Here, we estimate the importance of crosstalk, suggest that its avoidance strongly constrains equilibrium models of TF binding, and propose an alternative nonequilibrium scheme that implements kinetic proofreading to suppress erroneous initiation. This proposal is consistent with the observed covalent modifications of the transcriptional apparatus and predicts increased noise in gene expression as a trade-off for improved specificity. Using information theory, we quantify this trade-off to find when optimal proofreading architectures are favored over their equilibrium counterparts. Such architectures exhibit significant super-Poisson noise at low expression in steady state.' article_number: '248101' author: - first_name: Sarah A full_name: Cepeda Humerez, Sarah A id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87 last_name: Cepeda Humerez - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Cepeda Humerez SA, Rieckh G, Tkačik G. Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. 2015;115(24). doi:10.1103/PhysRevLett.115.248101 apa: Cepeda Humerez, S. A., Rieckh, G., & Tkačik, G. (2015). Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.115.248101 chicago: Cepeda Humerez, Sarah A, Georg Rieckh, and Gašper Tkačik. “Stochastic Proofreading Mechanism Alleviates Crosstalk in Transcriptional Regulation.” Physical Review Letters. American Physical Society, 2015. https://doi.org/10.1103/PhysRevLett.115.248101. ieee: S. A. Cepeda Humerez, G. Rieckh, and G. Tkačik, “Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation,” Physical Review Letters, vol. 115, no. 24. American Physical Society, 2015. ista: Cepeda Humerez SA, Rieckh G, Tkačik G. 2015. Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation. Physical Review Letters. 115(24), 248101. mla: Cepeda Humerez, Sarah A., et al. “Stochastic Proofreading Mechanism Alleviates Crosstalk in Transcriptional Regulation.” Physical Review Letters, vol. 115, no. 24, 248101, American Physical Society, 2015, doi:10.1103/PhysRevLett.115.248101. short: S.A. Cepeda Humerez, G. Rieckh, G. Tkačik, Physical Review Letters 115 (2015). date_created: 2018-12-11T11:52:49Z date_published: 2015-12-08T00:00:00Z date_updated: 2023-09-07T12:55:21Z day: '08' department: - _id: GaTk doi: 10.1103/PhysRevLett.115.248101 ec_funded: 1 intvolume: ' 115' issue: '24' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1504.05716 month: '12' oa: 1 oa_version: Preprint project: - _id: 25B07788-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '250152' name: Limits to selection in biology and in evolutionary computation publication: Physical Review Letters publication_status: published publisher: American Physical Society publist_id: '5595' quality_controlled: '1' related_material: record: - id: '6473' relation: part_of_dissertation status: public scopus_import: 1 status: public title: Stochastic proofreading mechanism alleviates crosstalk in transcriptional regulation type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 115 year: '2015' ... --- _id: '1655' abstract: - lang: eng text: Quantifying behaviors of robots which were generated autonomously from task-independent objective functions is an important prerequisite for objective comparisons of algorithms and movements of animals. The temporal sequence of such a behavior can be considered as a time series and hence complexity measures developed for time series are natural candidates for its quantification. The predictive information and the excess entropy are such complexity measures. They measure the amount of information the past contains about the future and thus quantify the nonrandom structure in the temporal sequence. However, when using these measures for systems with continuous states one has to deal with the fact that their values will depend on the resolution with which the systems states are observed. For deterministic systems both measures will diverge with increasing resolution. We therefore propose a new decomposition of the excess entropy in resolution dependent and resolution independent parts and discuss how they depend on the dimensionality of the dynamics, correlations and the noise level. For the practical estimation we propose to use estimates based on the correlation integral instead of the direct estimation of the mutual information based on next neighbor statistics because the latter allows less control of the scale dependencies. Using our algorithm we are able to show how autonomous learning generates behavior of increasing complexity with increasing learning duration. acknowledgement: This work was supported by the DFG priority program 1527 (Autonomous Learning) and by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 318723 (MatheMACS) and from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement no. 291734. article_processing_charge: No author: - first_name: Georg S full_name: Martius, Georg S id: 3A276B68-F248-11E8-B48F-1D18A9856A87 last_name: Martius - first_name: Eckehard full_name: Olbrich, Eckehard last_name: Olbrich citation: ama: Martius GS, Olbrich E. Quantifying emergent behavior of autonomous robots. Entropy. 2015;17(10):7266-7297. doi:10.3390/e17107266 apa: Martius, G. S., & Olbrich, E. (2015). Quantifying emergent behavior of autonomous robots. Entropy. MDPI. https://doi.org/10.3390/e17107266 chicago: Martius, Georg S, and Eckehard Olbrich. “Quantifying Emergent Behavior of Autonomous Robots.” Entropy. MDPI, 2015. https://doi.org/10.3390/e17107266. ieee: G. S. Martius and E. Olbrich, “Quantifying emergent behavior of autonomous robots,” Entropy, vol. 17, no. 10. MDPI, pp. 7266–7297, 2015. ista: Martius GS, Olbrich E. 2015. Quantifying emergent behavior of autonomous robots. Entropy. 17(10), 7266–7297. mla: Martius, Georg S., and Eckehard Olbrich. “Quantifying Emergent Behavior of Autonomous Robots.” Entropy, vol. 17, no. 10, MDPI, 2015, pp. 7266–97, doi:10.3390/e17107266. short: G.S. Martius, E. Olbrich, Entropy 17 (2015) 7266–7297. date_created: 2018-12-11T11:53:17Z date_published: 2015-10-23T00:00:00Z date_updated: 2023-10-17T11:42:00Z day: '23' ddc: - '000' department: - _id: ChLa - _id: GaTk doi: 10.3390/e17107266 ec_funded: 1 file: - access_level: open_access checksum: 945d99631a96e0315acb26dc8541dcf9 content_type: application/pdf creator: system date_created: 2018-12-12T10:12:25Z date_updated: 2020-07-14T12:45:08Z file_id: '4943' file_name: IST-2016-464-v1+1_entropy-17-07266.pdf file_size: 6455007 relation: main_file file_date_updated: 2020-07-14T12:45:08Z has_accepted_license: '1' intvolume: ' 17' issue: '10' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: 7266 - 7297 project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Entropy publication_status: published publisher: MDPI publist_id: '5495' pubrep_id: '464' quality_controlled: '1' scopus_import: '1' status: public title: Quantifying emergent behavior of autonomous robots tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 17 year: '2015' ... --- _id: '1708' abstract: - lang: eng text: It has been long argued that, because of inherent ambiguity and noise, the brain needs to represent uncertainty in the form of probability distributions. The neural encoding of such distributions remains however highly controversial. Here we present a novel circuit model for representing multidimensional real-valued distributions using a spike based spatio-temporal code. Our model combines the computational advantages of the currently competing models for probabilistic codes and exhibits realistic neural responses along a variety of classic measures. Furthermore, the model highlights the challenges associated with interpreting neural activity in relation to behavioral uncertainty and points to alternative population-level approaches for the experimental validation of distributed representations. author: - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Sophie full_name: Denève, Sophie last_name: Denève citation: ama: 'Savin C, Denève S. Spatio-temporal representations of uncertainty in spiking neural networks. In: Vol 3. Neural Information Processing Systems; 2014:2024-2032.' apa: 'Savin, C., & Denève, S. (2014). Spatio-temporal representations of uncertainty in spiking neural networks (Vol. 3, pp. 2024–2032). Presented at the NIPS: Neural Information Processing Systems, Montreal, Canada: Neural Information Processing Systems.' chicago: Savin, Cristina, and Sophie Denève. “Spatio-Temporal Representations of Uncertainty in Spiking Neural Networks,” 3:2024–32. Neural Information Processing Systems, 2014. ieee: 'C. Savin and S. Denève, “Spatio-temporal representations of uncertainty in spiking neural networks,” presented at the NIPS: Neural Information Processing Systems, Montreal, Canada, 2014, vol. 3, no. January, pp. 2024–2032.' ista: 'Savin C, Denève S. 2014. Spatio-temporal representations of uncertainty in spiking neural networks. NIPS: Neural Information Processing Systems vol. 3, 2024–2032.' mla: Savin, Cristina, and Sophie Denève. Spatio-Temporal Representations of Uncertainty in Spiking Neural Networks. Vol. 3, no. January, Neural Information Processing Systems, 2014, pp. 2024–32. short: C. Savin, S. Denève, in:, Neural Information Processing Systems, 2014, pp. 2024–2032. conference: end_date: 2014-12-13 location: Montreal, Canada name: 'NIPS: Neural Information Processing Systems' start_date: 2014-12-08 date_created: 2018-12-11T11:53:35Z date_published: 2014-01-01T00:00:00Z date_updated: 2021-01-12T06:52:40Z day: '01' department: - _id: GaTk intvolume: ' 3' issue: January language: - iso: eng main_file_link: - url: http://papers.nips.cc/paper/5343-spatio-temporal-representations-of-uncertainty-in-spiking-neural-networks.pdf month: '01' oa_version: None page: 2024 - 2032 publication_status: published publisher: Neural Information Processing Systems publist_id: '5427' quality_controlled: '1' scopus_import: 1 status: public title: Spatio-temporal representations of uncertainty in spiking neural networks type: conference user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 3 year: '2014' ... --- _id: '1886' abstract: - lang: eng text: 'Information processing in the sensory periphery is shaped by natural stimulus statistics. In the periphery, a transmission bottleneck constrains performance; thus efficient coding implies that natural signal components with a predictably wider range should be compressed. In a different regime—when sampling limitations constrain performance—efficient coding implies that more resources should be allocated to informative features that are more variable. We propose that this regime is relevant for sensory cortex when it extracts complex features from limited numbers of sensory samples. To test this prediction, we use central visual processing as a model: we show that visual sensitivity for local multi-point spatial correlations, described by dozens of independently-measured parameters, can be quantitatively predicted from the structure of natural images. This suggests that efficient coding applies centrally, where it extends to higher-order sensory features and operates in a regime in which sensitivity increases with feature variability.' article_number: e03722 author: - first_name: Ann full_name: Hermundstad, Ann last_name: Hermundstad - first_name: John full_name: Briguglio, John last_name: Briguglio - first_name: Mary full_name: Conte, Mary last_name: Conte - first_name: Jonathan full_name: Victor, Jonathan last_name: Victor - first_name: Vijay full_name: Balasubramanian, Vijay last_name: Balasubramanian - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Hermundstad A, Briguglio J, Conte M, Victor J, Balasubramanian V, Tkačik G. Variance predicts salience in central sensory processing. eLife. 2014;(November). doi:10.7554/eLife.03722 apa: Hermundstad, A., Briguglio, J., Conte, M., Victor, J., Balasubramanian, V., & Tkačik, G. (2014). Variance predicts salience in central sensory processing. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.03722 chicago: Hermundstad, Ann, John Briguglio, Mary Conte, Jonathan Victor, Vijay Balasubramanian, and Gašper Tkačik. “Variance Predicts Salience in Central Sensory Processing.” ELife. eLife Sciences Publications, 2014. https://doi.org/10.7554/eLife.03722. ieee: A. Hermundstad, J. Briguglio, M. Conte, J. Victor, V. Balasubramanian, and G. Tkačik, “Variance predicts salience in central sensory processing,” eLife, no. November. eLife Sciences Publications, 2014. ista: Hermundstad A, Briguglio J, Conte M, Victor J, Balasubramanian V, Tkačik G. 2014. Variance predicts salience in central sensory processing. eLife. (November), e03722. mla: Hermundstad, Ann, et al. “Variance Predicts Salience in Central Sensory Processing.” ELife, no. November, e03722, eLife Sciences Publications, 2014, doi:10.7554/eLife.03722. short: A. Hermundstad, J. Briguglio, M. Conte, J. Victor, V. Balasubramanian, G. Tkačik, ELife (2014). date_created: 2018-12-11T11:54:32Z date_published: 2014-11-14T00:00:00Z date_updated: 2021-01-12T06:53:50Z day: '14' ddc: - '570' department: - _id: GaTk doi: 10.7554/eLife.03722 file: - access_level: open_access checksum: 766ac8999ac6e3364f10065a06024b8f content_type: application/pdf creator: system date_created: 2018-12-12T10:12:04Z date_updated: 2020-07-14T12:45:20Z file_id: '4922' file_name: IST-2016-420-v1+1_e03722.full.pdf file_size: 5117086 relation: main_file file_date_updated: 2020-07-14T12:45:20Z has_accepted_license: '1' issue: November language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 254D1A94-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 25651-N26 name: Sensitivity to higher-order statistics in natural scenes publication: eLife publication_status: published publisher: eLife Sciences Publications publist_id: '5209' pubrep_id: '420' quality_controlled: '1' scopus_import: 1 status: public title: Variance predicts salience in central sensory processing tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 year: '2014' ... --- _id: '1896' abstract: - lang: eng text: 'Biopolymer length regulation is a complex process that involves a large number of biological, chemical, and physical subprocesses acting simultaneously across multiple spatial and temporal scales. An illustrative example important for genomic stability is the length regulation of telomeres - nucleoprotein structures at the ends of linear chromosomes consisting of tandemly repeated DNA sequences and a specialized set of proteins. Maintenance of telomeres is often facilitated by the enzyme telomerase but, particularly in telomerase-free systems, the maintenance of chromosomal termini depends on alternative lengthening of telomeres (ALT) mechanisms mediated by recombination. Various linear and circular DNA structures were identified to participate in ALT, however, dynamics of the whole process is still poorly understood. We propose a chemical kinetics model of ALT with kinetic rates systematically derived from the biophysics of DNA diffusion and looping. The reaction system is reduced to a coagulation-fragmentation system by quasi-steady-state approximation. The detailed treatment of kinetic rates yields explicit formulas for expected size distributions of telomeres that demonstrate the key role played by the J factor, a quantitative measure of bending of polymers. The results are in agreement with experimental data and point out interesting phenomena: an appearance of very long telomeric circles if the total telomere density exceeds a critical value (excess mass) and a nonlinear response of the telomere size distributions to the amount of telomeric DNA in the system. The results can be of general importance for understanding dynamics of telomeres in telomerase-independent systems as this mode of telomere maintenance is similar to the situation in tumor cells lacking telomerase activity. Furthermore, due to its universality, the model may also serve as a prototype of an interaction between linear and circular DNA structures in various settings.' acknowledgement: The work was supported by the VEGA Grant No. 1/0459/13 (R.K. and K.B.). article_number: '032701' article_processing_charge: No author: - first_name: Richard full_name: Kollár, Richard last_name: Kollár - first_name: Katarína full_name: Bod'ová, Katarína id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bod'ová orcid: 0000-0002-7214-0171 - first_name: Jozef full_name: Nosek, Jozef last_name: Nosek - first_name: Ľubomír full_name: Tomáška, Ľubomír last_name: Tomáška citation: ama: Kollár R, Bodova K, Nosek J, Tomáška Ľ. Mathematical model of alternative mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear and Soft Matter Physics. 2014;89(3). doi:10.1103/PhysRevE.89.032701 apa: Kollár, R., Bodova, K., Nosek, J., & Tomáška, Ľ. (2014). Mathematical model of alternative mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.89.032701 chicago: Kollár, Richard, Katarina Bodova, Jozef Nosek, and Ľubomír Tomáška. “Mathematical Model of Alternative Mechanism of Telomere Length Maintenance.” Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics, 2014. https://doi.org/10.1103/PhysRevE.89.032701. ieee: R. Kollár, K. Bodova, J. Nosek, and Ľ. Tomáška, “Mathematical model of alternative mechanism of telomere length maintenance,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 3. American Institute of Physics, 2014. ista: Kollár R, Bodova K, Nosek J, Tomáška Ľ. 2014. Mathematical model of alternative mechanism of telomere length maintenance. Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(3), 032701. mla: Kollár, Richard, et al. “Mathematical Model of Alternative Mechanism of Telomere Length Maintenance.” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 3, 032701, American Institute of Physics, 2014, doi:10.1103/PhysRevE.89.032701. short: R. Kollár, K. Bodova, J. Nosek, Ľ. Tomáška, Physical Review E Statistical Nonlinear and Soft Matter Physics 89 (2014). date_created: 2018-12-11T11:54:35Z date_published: 2014-03-04T00:00:00Z date_updated: 2022-08-01T10:50:10Z day: '04' department: - _id: NiBa - _id: GaTk doi: 10.1103/PhysRevE.89.032701 intvolume: ' 89' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1402.0430 month: '03' oa: 1 oa_version: Submitted Version publication: Physical Review E Statistical Nonlinear and Soft Matter Physics publication_status: published publisher: American Institute of Physics publist_id: '5198' scopus_import: '1' status: public title: Mathematical model of alternative mechanism of telomere length maintenance type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 89 year: '2014' ... --- _id: '1909' abstract: - lang: eng text: 'Summary: Phenotypes are often environmentally dependent, which requires organisms to track environmental change. The challenge for organisms is to construct phenotypes using the most accurate environmental cue. Here, we use a quantitative genetic model of adaptation by additive genetic variance, within- and transgenerational plasticity via linear reaction norms and indirect genetic effects respectively. We show how the relative influence on the eventual phenotype of these components depends on the predictability of environmental change (fast or slow, sinusoidal or stochastic) and the developmental lag τ between when the environment is perceived and when selection acts. We then decompose expected mean fitness into three components (variance load, adaptation and fluctuation load) to study the fitness costs of within- and transgenerational plasticity. A strongly negative maternal effect coefficient m minimizes the variance load, but a strongly positive m minimises the fluctuation load. The adaptation term is maximized closer to zero, with positive or negative m preferred under different environmental scenarios. Phenotypic plasticity is higher when τ is shorter and when the environment changes frequently between seasonal extremes. Expected mean population fitness is highest away from highest observed levels of phenotypic plasticity. Within- and transgenerational plasticity act in concert to deliver well-adapted phenotypes, which emphasizes the need to study both simultaneously when investigating phenotypic evolution.' acknowledgement: 'Engineering and Physical Sciences Research Council. Grant Number: EP/H031928/1' author: - first_name: Thomas full_name: Ezard, Thomas last_name: Ezard - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Rebecca full_name: Hoyle, Rebecca last_name: Hoyle citation: ama: Ezard T, Prizak R, Hoyle R. The fitness costs of adaptation via phenotypic plasticity and maternal effects. Functional Ecology. 2014;28(3):693-701. doi:10.1111/1365-2435.12207 apa: Ezard, T., Prizak, R., & Hoyle, R. (2014). The fitness costs of adaptation via phenotypic plasticity and maternal effects. Functional Ecology. Wiley-Blackwell. https://doi.org/10.1111/1365-2435.12207 chicago: Ezard, Thomas, Roshan Prizak, and Rebecca Hoyle. “The Fitness Costs of Adaptation via Phenotypic Plasticity and Maternal Effects.” Functional Ecology. Wiley-Blackwell, 2014. https://doi.org/10.1111/1365-2435.12207. ieee: T. Ezard, R. Prizak, and R. Hoyle, “The fitness costs of adaptation via phenotypic plasticity and maternal effects,” Functional Ecology, vol. 28, no. 3. Wiley-Blackwell, pp. 693–701, 2014. ista: Ezard T, Prizak R, Hoyle R. 2014. The fitness costs of adaptation via phenotypic plasticity and maternal effects. Functional Ecology. 28(3), 693–701. mla: Ezard, Thomas, et al. “The Fitness Costs of Adaptation via Phenotypic Plasticity and Maternal Effects.” Functional Ecology, vol. 28, no. 3, Wiley-Blackwell, 2014, pp. 693–701, doi:10.1111/1365-2435.12207. short: T. Ezard, R. Prizak, R. Hoyle, Functional Ecology 28 (2014) 693–701. date_created: 2018-12-11T11:54:40Z date_published: 2014-06-01T00:00:00Z date_updated: 2021-01-12T06:54:00Z day: '01' ddc: - '570' department: - _id: NiBa - _id: GaTk doi: 10.1111/1365-2435.12207 file: - access_level: open_access checksum: 3cbe8623174709a8ceec2103246f8fe0 content_type: application/pdf creator: system date_created: 2018-12-12T10:15:45Z date_updated: 2020-07-14T12:45:20Z file_id: '5167' file_name: IST-2016-419-v1+1_Ezard_et_al-2014-Functional_Ecology.pdf file_size: 536154 relation: main_file file_date_updated: 2020-07-14T12:45:20Z has_accepted_license: '1' intvolume: ' 28' issue: '3' language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: 693 - 701 publication: Functional Ecology publication_status: published publisher: Wiley-Blackwell publist_id: '5186' pubrep_id: '419' scopus_import: 1 status: public title: The fitness costs of adaptation via phenotypic plasticity and maternal effects tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 28 year: '2014' ... --- _id: '1928' abstract: - lang: eng text: In infectious disease epidemiology the basic reproductive ratio, R0, is defined as the average number of new infections caused by a single infected individual in a fully susceptible population. Many models describing competition for hosts between non-interacting pathogen strains in an infinite population lead to the conclusion that selection favors invasion of new strains if and only if they have higher R0 values than the resident. Here we demonstrate that this picture fails in finite populations. Using a simple stochastic SIS model, we show that in general there is no analogous optimization principle. We find that successive invasions may in some cases lead to strains that infect a smaller fraction of the host population, and that mutually invasible pathogen strains exist. In the limit of weak selection we demonstrate that an optimization principle does exist, although it differs from R0 maximization. For strains with very large R0, we derive an expression for this local fitness function and use it to establish a lower bound for the error caused by neglecting stochastic effects. Furthermore, we apply this weak selection limit to investigate the selection dynamics in the presence of a trade-off between the virulence and the transmission rate of a pathogen. acknowledgement: J.H. received support from the Zdenek Bakala Foundation and the Mobility Fund of Charles University in Prague. author: - first_name: Jan full_name: Humplik, Jan id: 2E9627A8-F248-11E8-B48F-1D18A9856A87 last_name: Humplik - first_name: Alison full_name: Hill, Alison last_name: Hill - first_name: Martin full_name: Nowak, Martin last_name: Nowak citation: ama: Humplik J, Hill A, Nowak M. Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. 2014;360:149-162. doi:10.1016/j.jtbi.2014.06.039 apa: Humplik, J., Hill, A., & Nowak, M. (2014). Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. Elsevier. https://doi.org/10.1016/j.jtbi.2014.06.039 chicago: Humplik, Jan, Alison Hill, and Martin Nowak. “Evolutionary Dynamics of Infectious Diseases in Finite Populations.” Journal of Theoretical Biology. Elsevier, 2014. https://doi.org/10.1016/j.jtbi.2014.06.039. ieee: J. Humplik, A. Hill, and M. Nowak, “Evolutionary dynamics of infectious diseases in finite populations,” Journal of Theoretical Biology, vol. 360. Elsevier, pp. 149–162, 2014. ista: Humplik J, Hill A, Nowak M. 2014. Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. 360, 149–162. mla: Humplik, Jan, et al. “Evolutionary Dynamics of Infectious Diseases in Finite Populations.” Journal of Theoretical Biology, vol. 360, Elsevier, 2014, pp. 149–62, doi:10.1016/j.jtbi.2014.06.039. short: J. Humplik, A. Hill, M. Nowak, Journal of Theoretical Biology 360 (2014) 149–162. date_created: 2018-12-11T11:54:46Z date_published: 2014-11-07T00:00:00Z date_updated: 2021-01-12T06:54:08Z day: '07' department: - _id: GaTk doi: 10.1016/j.jtbi.2014.06.039 intvolume: ' 360' language: - iso: eng month: '11' oa_version: None page: 149 - 162 publication: Journal of Theoretical Biology publication_status: published publisher: Elsevier publist_id: '5166' scopus_import: 1 status: public title: Evolutionary dynamics of infectious diseases in finite populations type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 360 year: '2014' ... --- _id: '1931' abstract: - lang: eng text: A wealth of experimental evidence suggests that working memory circuits preferentially represent information that is behaviorally relevant. Still, we are missing a mechanistic account of how these representations come about. Here we provide a simple explanation for a range of experimental findings, in light of prefrontal circuits adapting to task constraints by reward-dependent learning. In particular, we model a neural network shaped by reward-modulated spike-timing dependent plasticity (r-STDP) and homeostatic plasticity (intrinsic excitability and synaptic scaling). We show that the experimentally-observed neural representations naturally emerge in an initially unstructured circuit as it learns to solve several working memory tasks. These results point to a critical, and previously unappreciated, role for reward-dependent learning in shaping prefrontal cortex activity. acknowledgement: Supported in part by EC MEXT project PLICON and the LOEWE-Program “Neuronal Coordination Research Focus Frankfurt” (NeFF). Jochen Triesch was supported by the Quandt foundation. article_number: '57' author: - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Jochen full_name: Triesch, Jochen last_name: Triesch citation: ama: Savin C, Triesch J. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 2014;8(MAY). doi:10.3389/fncom.2014.00057 apa: Savin, C., & Triesch, J. (2014). Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2014.00057 chicago: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations in Working Memory Circuits.” Frontiers in Computational Neuroscience. Frontiers Research Foundation, 2014. https://doi.org/10.3389/fncom.2014.00057. ieee: C. Savin and J. Triesch, “Emergence of task-dependent representations in working memory circuits,” Frontiers in Computational Neuroscience, vol. 8, no. MAY. Frontiers Research Foundation, 2014. ista: Savin C, Triesch J. 2014. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 8(MAY), 57. mla: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations in Working Memory Circuits.” Frontiers in Computational Neuroscience, vol. 8, no. MAY, 57, Frontiers Research Foundation, 2014, doi:10.3389/fncom.2014.00057. short: C. Savin, J. Triesch, Frontiers in Computational Neuroscience 8 (2014). date_created: 2018-12-11T11:54:46Z date_published: 2014-05-28T00:00:00Z date_updated: 2021-01-12T06:54:09Z day: '28' department: - _id: GaTk doi: 10.3389/fncom.2014.00057 intvolume: ' 8' issue: MAY language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035833/ month: '05' oa: 1 oa_version: Submitted Version publication: Frontiers in Computational Neuroscience publication_status: published publisher: Frontiers Research Foundation publist_id: '5163' quality_controlled: '1' scopus_import: 1 status: public title: Emergence of task-dependent representations in working memory circuits type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2014' ... --- _id: '2028' abstract: - lang: eng text: 'Understanding the dynamics of noisy neurons remains an important challenge in neuroscience. Here, we describe a simple probabilistic model that accurately describes the firing behavior in a large class (type II) of neurons. To demonstrate the usefulness of this model, we show how it accurately predicts the interspike interval (ISI) distributions, bursting patterns and mean firing rates found by: (1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental data from squid giant axon with a noisy input current and (3) experimental data on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple model has 6 parameters, however, in some cases, two of these parameters are coupled and only 5 parameters account for much of the known behavior. From these parameters, many properties of spiking can be found through simple calculation. Thus, we show how the complex effects of noise can be understood through a simple and general probabilistic model.' acknowledgement: 'This work is supported by AFOSR grant FA 9550-11-1-0165, program grant RPG 24/2012 from the Human Frontiers of Science (DBF) and travel support from the European Commission Marie Curie International Reintegration Grant PIRG04-GA-2008-239429 (KB). DP was supported by NIHR01 GM104987 and the Wyss Institute of Biologically Inspired Engineering. ' article_processing_charge: No author: - first_name: Katarina full_name: Bodova, Katarina id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bodova orcid: 0000-0002-7214-0171 - first_name: David full_name: Paydarfar, David last_name: Paydarfar - first_name: Daniel full_name: Forger, Daniel last_name: Forger citation: ama: Bodova K, Paydarfar D, Forger D. Characterizing spiking in noisy type II neurons. Journal of Theoretical Biology. 2014;365:40-54. doi:10.1016/j.jtbi.2014.09.041 apa: Bodova, K., Paydarfar, D., & Forger, D. (2014). Characterizing spiking in noisy type II neurons. Journal of Theoretical Biology. Academic Press. https://doi.org/10.1016/j.jtbi.2014.09.041 chicago: Bodova, Katarina, David Paydarfar, and Daniel Forger. “Characterizing Spiking in Noisy Type II Neurons.” Journal of Theoretical Biology. Academic Press, 2014. https://doi.org/10.1016/j.jtbi.2014.09.041. ieee: K. Bodova, D. Paydarfar, and D. Forger, “Characterizing spiking in noisy type II neurons,” Journal of Theoretical Biology, vol. 365. Academic Press, pp. 40–54, 2014. ista: Bodova K, Paydarfar D, Forger D. 2014. Characterizing spiking in noisy type II neurons. Journal of Theoretical Biology. 365, 40–54. mla: Bodova, Katarina, et al. “Characterizing Spiking in Noisy Type II Neurons.” Journal of Theoretical Biology, vol. 365, Academic Press, 2014, pp. 40–54, doi:10.1016/j.jtbi.2014.09.041. short: K. Bodova, D. Paydarfar, D. Forger, Journal of Theoretical Biology 365 (2014) 40–54. date_created: 2018-12-11T11:55:18Z date_published: 2014-10-12T00:00:00Z date_updated: 2022-08-25T14:00:47Z day: '12' ddc: - '570' department: - _id: GaTk doi: 10.1016/j.jtbi.2014.09.041 file: - access_level: open_access checksum: a9dbae18d3233b3dab6944fd3f2cd49e content_type: application/pdf creator: system date_created: 2018-12-12T10:17:58Z date_updated: 2020-07-14T12:45:25Z file_id: '5316' file_name: IST-2016-444-v1+1_1-s2.0-S0022519314005888-main.pdf file_size: 2679222 relation: main_file file_date_updated: 2020-07-14T12:45:25Z has_accepted_license: '1' intvolume: ' 365' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '10' oa: 1 oa_version: Published Version page: 40 - 54 publication: ' Journal of Theoretical Biology' publication_status: published publisher: Academic Press publist_id: '5043' pubrep_id: '444' quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1016/j.jtbi.2015.03.013 scopus_import: '1' status: public title: Characterizing spiking in noisy type II neurons tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 365 year: '2014' ... --- _id: '2183' abstract: - lang: eng text: 'We describe a simple adaptive network of coupled chaotic maps. The network reaches a stationary state (frozen topology) for all values of the coupling parameter, although the dynamics of the maps at the nodes of the network can be nontrivial. The structure of the network shows interesting hierarchical properties and in certain parameter regions the dynamics is polysynchronous: Nodes can be divided in differently synchronized classes but, contrary to cluster synchronization, nodes in the same class need not be connected to each other. These complicated synchrony patterns have been conjectured to play roles in systems biology and circuits. The adaptive system we study describes ways whereby this behavior can evolve from undifferentiated nodes.' acknowledgement: "V.B.S. is partially supported by contract MEC (Grant No. AYA2010-22111-C03-02).\r\n" article_number: '062809' article_processing_charge: No author: - first_name: Vicente full_name: Botella Soler, Vicente id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: Paul full_name: Glendinning, Paul last_name: Glendinning citation: ama: Botella Soler V, Glendinning P. Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 2014;89(6). doi:10.1103/PhysRevE.89.062809 apa: Botella Soler, V., & Glendinning, P. (2014). Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.89.062809 chicago: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics, 2014. https://doi.org/10.1103/PhysRevE.89.062809. ieee: V. Botella Soler and P. Glendinning, “Hierarchy and polysynchrony in an adaptive network ,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 6. American Institute of Physics, 2014. ista: Botella Soler V, Glendinning P. 2014. Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(6), 062809. mla: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 6, 062809, American Institute of Physics, 2014, doi:10.1103/PhysRevE.89.062809. short: V. Botella Soler, P. Glendinning, Physical Review E Statistical Nonlinear and Soft Matter Physics 89 (2014). date_created: 2018-12-11T11:56:11Z date_published: 2014-06-16T00:00:00Z date_updated: 2022-08-25T14:04:45Z day: '16' department: - _id: GaTk doi: 10.1103/PhysRevE.89.062809 ec_funded: 1 intvolume: ' 89' issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1403.3209 month: '06' oa: 1 oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Physical Review E Statistical Nonlinear and Soft Matter Physics publication_status: published publisher: American Institute of Physics publist_id: '4798' quality_controlled: '1' scopus_import: '1' status: public title: 'Hierarchy and polysynchrony in an adaptive network ' type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 89 year: '2014' ... --- _id: '2231' abstract: - lang: eng text: Based on the measurements of noise in gene expression performed during the past decade, it has become customary to think of gene regulation in terms of a two-state model, where the promoter of a gene can stochastically switch between an ON and an OFF state. As experiments are becoming increasingly precise and the deviations from the two-state model start to be observable, we ask about the experimental signatures of complex multistate promoters, as well as the functional consequences of this additional complexity. In detail, we i), extend the calculations for noise in gene expression to promoters described by state transition diagrams with multiple states, ii), systematically compute the experimentally accessible noise characteristics for these complex promoters, and iii), use information theory to evaluate the channel capacities of complex promoter architectures and compare them with the baseline provided by the two-state model. We find that adding internal states to the promoter generically decreases channel capacity, except in certain cases, three of which (cooperativity, dual-role regulation, promoter cycling) we analyze in detail. author: - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Rieckh G, Tkačik G. Noise and information transmission in promoters with multiple internal states. Biophysical Journal. 2014;106(5):1194-1204. doi:10.1016/j.bpj.2014.01.014 apa: Rieckh, G., & Tkačik, G. (2014). Noise and information transmission in promoters with multiple internal states. Biophysical Journal. Biophysical Society. https://doi.org/10.1016/j.bpj.2014.01.014 chicago: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in Promoters with Multiple Internal States.” Biophysical Journal. Biophysical Society, 2014. https://doi.org/10.1016/j.bpj.2014.01.014. ieee: G. Rieckh and G. Tkačik, “Noise and information transmission in promoters with multiple internal states,” Biophysical Journal, vol. 106, no. 5. Biophysical Society, pp. 1194–1204, 2014. ista: Rieckh G, Tkačik G. 2014. Noise and information transmission in promoters with multiple internal states. Biophysical Journal. 106(5), 1194–1204. mla: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in Promoters with Multiple Internal States.” Biophysical Journal, vol. 106, no. 5, Biophysical Society, 2014, pp. 1194–204, doi:10.1016/j.bpj.2014.01.014. short: G. Rieckh, G. Tkačik, Biophysical Journal 106 (2014) 1194–1204. date_created: 2018-12-11T11:56:28Z date_published: 2014-03-04T00:00:00Z date_updated: 2021-01-12T06:56:10Z day: '04' department: - _id: GaTk doi: 10.1016/j.bpj.2014.01.014 external_id: pmid: - '24606943' intvolume: ' 106' issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026790/ month: '03' oa: 1 oa_version: Submitted Version page: 1194 - 1204 pmid: 1 publication: Biophysical Journal publication_identifier: issn: - '00063495' publication_status: published publisher: Biophysical Society publist_id: '4730' quality_controlled: '1' scopus_import: 1 status: public title: Noise and information transmission in promoters with multiple internal states type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 106 year: '2014' ... --- _id: '3263' abstract: - lang: eng text: Adaptation in the retina is thought to optimize the encoding of natural light signals into sequences of spikes sent to the brain. While adaptive changes in retinal processing to the variations of the mean luminance level and second-order stimulus statistics have been documented before, no such measurements have been performed when higher-order moments of the light distribution change. We therefore measured the ganglion cell responses in the tiger salamander retina to controlled changes in the second (contrast), third (skew) and fourth (kurtosis) moments of the light intensity distribution of spatially uniform temporally independent stimuli. The skew and kurtosis of the stimuli were chosen to cover the range observed in natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear models that capture well the retinal encoding properties across all stimuli. We found that the encoding properties of retinal ganglion cells change only marginally when higher-order statistics change, compared to the changes observed in response to the variation in contrast. By analyzing optimal coding in LN-type models, we showed that neurons can maintain a high information rate without large dynamic adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli, spatio-temporal summation within the receptive field averages away non-gaussian aspects of the light intensity distribution. acknowledgement: "This work was supported by The Israel Science Foundation and The Human Frontiers Science Program.\r\nWe thank the referees for helping significantly improve this paper. We also thank Vijay Balasubramanian, Kristina Simmons, and Jason Prentice for stimulating discussions. GT wishes to thank the faculty and students of the “Methods in Computational Neuroscience” course at Marine Biological Laboratory, Woods Hole.\r\n" article_number: e85841 author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Anandamohan full_name: Ghosh, Anandamohan last_name: Ghosh - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman - first_name: Ronen full_name: Segev, Ronen last_name: Segev citation: ama: Tkačik G, Ghosh A, Schneidman E, Segev R. Adaptation to changes in higher-order stimulus statistics in the salamander retina. PLoS One. 2014;9(1). doi:10.1371/journal.pone.0085841 apa: Tkačik, G., Ghosh, A., Schneidman, E., & Segev, R. (2014). Adaptation to changes in higher-order stimulus statistics in the salamander retina. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0085841 chicago: Tkačik, Gašper, Anandamohan Ghosh, Elad Schneidman, and Ronen Segev. “Adaptation to Changes in Higher-Order Stimulus Statistics in the Salamander Retina.” PLoS One. Public Library of Science, 2014. https://doi.org/10.1371/journal.pone.0085841. ieee: G. Tkačik, A. Ghosh, E. Schneidman, and R. Segev, “Adaptation to changes in higher-order stimulus statistics in the salamander retina,” PLoS One, vol. 9, no. 1. Public Library of Science, 2014. ista: Tkačik G, Ghosh A, Schneidman E, Segev R. 2014. Adaptation to changes in higher-order stimulus statistics in the salamander retina. PLoS One. 9(1), e85841. mla: Tkačik, Gašper, et al. “Adaptation to Changes in Higher-Order Stimulus Statistics in the Salamander Retina.” PLoS One, vol. 9, no. 1, e85841, Public Library of Science, 2014, doi:10.1371/journal.pone.0085841. short: G. Tkačik, A. Ghosh, E. Schneidman, R. Segev, PLoS One 9 (2014). date_created: 2018-12-11T12:02:20Z date_published: 2014-01-21T00:00:00Z date_updated: 2021-01-12T07:42:14Z day: '21' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pone.0085841 file: - access_level: open_access checksum: 1d5816b343abe5eadc3eb419bcece971 content_type: application/pdf creator: system date_created: 2018-12-12T10:13:28Z date_updated: 2020-07-14T12:46:06Z file_id: '5011' file_name: IST-2016-432-v1+1_journal.pone.0085841.pdf file_size: 1568524 relation: main_file file_date_updated: 2020-07-14T12:46:06Z has_accepted_license: '1' intvolume: ' 9' issue: '1' language: - iso: eng month: '01' oa: 1 oa_version: Published Version publication: PLoS One publication_status: published publisher: Public Library of Science publist_id: '3385' pubrep_id: '432' quality_controlled: '1' scopus_import: 1 status: public title: Adaptation to changes in higher-order stimulus statistics in the salamander retina tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3FFCCD3A-F248-11E8-B48F-1D18A9856A87 volume: 9 year: '2014' ... --- _id: '537' abstract: - lang: eng text: Transgenerational effects are broader than only parental relationships. Despite mounting evidence that multigenerational effects alter phenotypic and life-history traits, our understanding of how they combine to determine fitness is not well developed because of the added complexity necessary to study them. Here, we derive a quantitative genetic model of adaptation to an extraordinary new environment by an additive genetic component, phenotypic plasticity, maternal and grandmaternal effects. We show how, at equilibrium, negative maternal and negative grandmaternal effects maximize expected population mean fitness. We define negative transgenerational effects as those that have a negative effect on trait expression in the subsequent generation, that is, they slow, or potentially reverse, the expected evolutionary dynamic. When maternal effects are positive, negative grandmaternal effects are preferred. As expected under Mendelian inheritance, the grandmaternal effects have a lower impact on fitness than the maternal effects, but this dual inheritance model predicts a more complex relationship between maternal and grandmaternal effects to constrain phenotypic variance and so maximize expected population mean fitness in the offspring. author: - first_name: Roshan full_name: Prizak, Roshan id: 4456104E-F248-11E8-B48F-1D18A9856A87 last_name: Prizak - first_name: Thomas full_name: Ezard, Thomas last_name: Ezard - first_name: Rebecca full_name: Hoyle, Rebecca last_name: Hoyle citation: ama: Prizak R, Ezard T, Hoyle R. Fitness consequences of maternal and grandmaternal effects. Ecology and Evolution. 2014;4(15):3139-3145. doi:10.1002/ece3.1150 apa: Prizak, R., Ezard, T., & Hoyle, R. (2014). Fitness consequences of maternal and grandmaternal effects. Ecology and Evolution. Wiley-Blackwell. https://doi.org/10.1002/ece3.1150 chicago: Prizak, Roshan, Thomas Ezard, and Rebecca Hoyle. “Fitness Consequences of Maternal and Grandmaternal Effects.” Ecology and Evolution. Wiley-Blackwell, 2014. https://doi.org/10.1002/ece3.1150. ieee: R. Prizak, T. Ezard, and R. Hoyle, “Fitness consequences of maternal and grandmaternal effects,” Ecology and Evolution, vol. 4, no. 15. Wiley-Blackwell, pp. 3139–3145, 2014. ista: Prizak R, Ezard T, Hoyle R. 2014. Fitness consequences of maternal and grandmaternal effects. Ecology and Evolution. 4(15), 3139–3145. mla: Prizak, Roshan, et al. “Fitness Consequences of Maternal and Grandmaternal Effects.” Ecology and Evolution, vol. 4, no. 15, Wiley-Blackwell, 2014, pp. 3139–45, doi:10.1002/ece3.1150. short: R. Prizak, T. Ezard, R. Hoyle, Ecology and Evolution 4 (2014) 3139–3145. date_created: 2018-12-11T11:47:02Z date_published: 2014-07-19T00:00:00Z date_updated: 2021-01-12T08:01:30Z day: '19' ddc: - '530' - '571' department: - _id: NiBa - _id: GaTk doi: 10.1002/ece3.1150 file: - access_level: open_access checksum: e32abf75a248e7a11811fd7f60858769 content_type: application/pdf creator: system date_created: 2018-12-12T10:11:31Z date_updated: 2020-07-14T12:46:38Z file_id: '4886' file_name: IST-2018-934-v1+1_Prizak_et_al-2014-Ecology_and_Evolution.pdf file_size: 621582 relation: main_file file_date_updated: 2020-07-14T12:46:38Z has_accepted_license: '1' intvolume: ' 4' issue: '15' language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: 3139 - 3145 publication: Ecology and Evolution publication_status: published publisher: Wiley-Blackwell publist_id: '7280' pubrep_id: '934' scopus_import: 1 status: public title: Fitness consequences of maternal and grandmaternal effects tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2014' ... --- _id: '9752' abstract: - lang: eng text: Redundancies and correlations in the responses of sensory neurons may seem to waste neural resources, but they can also carry cues about structured stimuli and may help the brain to correct for response errors. To investigate the effect of stimulus structure on redundancy in retina, we measured simultaneous responses from populations of retinal ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure; these stimuli and recordings are publicly available online. Responding to spatio-temporally structured stimuli such as natural movies, pairs of ganglion cells were modestly more correlated than in response to white noise checkerboards, but they were much less correlated than predicted by a non-adapting functional model of retinal response. Meanwhile, responding to stimuli with purely spatial correlations, pairs of ganglion cells showed increased correlations consistent with a static, non-adapting receptive field and nonlinearity. We found that in response to spatio-temporally correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the pattern of pairwise correlations across stimuli where receptive field measurements were possible. article_processing_charge: No author: - first_name: Kristina full_name: Simmons, Kristina last_name: Simmons - first_name: Jason full_name: Prentice, Jason last_name: Prentice - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Jan full_name: Homann, Jan last_name: Homann - first_name: Heather full_name: Yee, Heather last_name: Yee - first_name: Stephanie full_name: Palmer, Stephanie last_name: Palmer - first_name: Philip full_name: Nelson, Philip last_name: Nelson - first_name: Vijay full_name: Balasubramanian, Vijay last_name: Balasubramanian citation: ama: 'Simmons K, Prentice J, Tkačik G, et al. Data from: Transformation of stimulus correlations by the retina. 2014. doi:10.5061/dryad.246qg' apa: 'Simmons, K., Prentice, J., Tkačik, G., Homann, J., Yee, H., Palmer, S., … Balasubramanian, V. (2014). Data from: Transformation of stimulus correlations by the retina. Dryad. https://doi.org/10.5061/dryad.246qg' chicago: 'Simmons, Kristina, Jason Prentice, Gašper Tkačik, Jan Homann, Heather Yee, Stephanie Palmer, Philip Nelson, and Vijay Balasubramanian. “Data from: Transformation of Stimulus Correlations by the Retina.” Dryad, 2014. https://doi.org/10.5061/dryad.246qg.' ieee: 'K. Simmons et al., “Data from: Transformation of stimulus correlations by the retina.” Dryad, 2014.' ista: 'Simmons K, Prentice J, Tkačik G, Homann J, Yee H, Palmer S, Nelson P, Balasubramanian V. 2014. Data from: Transformation of stimulus correlations by the retina, Dryad, 10.5061/dryad.246qg.' mla: 'Simmons, Kristina, et al. Data from: Transformation of Stimulus Correlations by the Retina. Dryad, 2014, doi:10.5061/dryad.246qg.' short: K. Simmons, J. Prentice, G. Tkačik, J. Homann, H. Yee, S. Palmer, P. Nelson, V. Balasubramanian, (2014). date_created: 2021-07-30T08:13:52Z date_published: 2014-11-07T00:00:00Z date_updated: 2023-02-23T10:35:57Z day: '07' department: - _id: GaTk doi: 10.5061/dryad.246qg main_file_link: - open_access: '1' url: https://doi.org/10.5061/dryad.246qg month: '11' oa: 1 oa_version: Published Version publisher: Dryad related_material: record: - id: '2277' relation: used_in_publication status: public status: public title: 'Data from: Transformation of stimulus correlations by the retina' type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2014' ... --- _id: '2257' abstract: - lang: eng text: 'Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such “K-pairwise” models—being systematic extensions of the previously used pairwise Ising models—provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1) estimating its entropy, which constrains the population''s capacity to represent visual information; 2) classifying activity patterns into a small set of metastable collective modes; 3) showing that the neural codeword ensembles are extremely inhomogenous; 4) demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction.' acknowledgement: "\r\n\r\n\r\n\r\nThis work was funded by NSF grant IIS-0613435, NSF grant PHY-0957573, NSF grant CCF-0939370, NIH grant R01 EY14196, NIH grant P50 GM071508, the Fannie and John Hertz Foundation, the Swartz Foundation, the WM Keck Foundation, ANR Optima and the French State program “Investissements d'Avenir” [LIFESENSES: ANR-10-LABX-65], and the Austrian Research Foundation FWF P25651." article_number: e1003408 author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Dario full_name: Amodei, Dario last_name: Amodei - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman - first_name: William full_name: Bialek, William last_name: Bialek - first_name: Michael full_name: Berry, Michael last_name: Berry citation: ama: Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry M. Searching for collective behavior in a large network of sensory neurons. PLoS Computational Biology. 2014;10(1). doi:10.1371/journal.pcbi.1003408 apa: Tkačik, G., Marre, O., Amodei, D., Schneidman, E., Bialek, W., & Berry, M. (2014). Searching for collective behavior in a large network of sensory neurons. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1003408 chicago: Tkačik, Gašper, Olivier Marre, Dario Amodei, Elad Schneidman, William Bialek, and Michael Berry. “Searching for Collective Behavior in a Large Network of Sensory Neurons.” PLoS Computational Biology. Public Library of Science, 2014. https://doi.org/10.1371/journal.pcbi.1003408. ieee: G. Tkačik, O. Marre, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Searching for collective behavior in a large network of sensory neurons,” PLoS Computational Biology, vol. 10, no. 1. Public Library of Science, 2014. ista: Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry M. 2014. Searching for collective behavior in a large network of sensory neurons. PLoS Computational Biology. 10(1), e1003408. mla: Tkačik, Gašper, et al. “Searching for Collective Behavior in a Large Network of Sensory Neurons.” PLoS Computational Biology, vol. 10, no. 1, e1003408, Public Library of Science, 2014, doi:10.1371/journal.pcbi.1003408. short: G. Tkačik, O. Marre, D. Amodei, E. Schneidman, W. Bialek, M. Berry, PLoS Computational Biology 10 (2014). date_created: 2018-12-11T11:56:36Z date_published: 2014-01-02T00:00:00Z date_updated: 2024-02-21T13:46:14Z day: '02' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1003408 file: - access_level: open_access checksum: c720222c5e924a4acb17f23b9381a6ca content_type: application/pdf creator: system date_created: 2018-12-12T10:12:46Z date_updated: 2020-07-14T12:45:35Z file_id: '4965' file_name: IST-2016-436-v1+1_journal.pcbi.1003408.pdf file_size: 2194790 relation: main_file file_date_updated: 2020-07-14T12:45:35Z has_accepted_license: '1' intvolume: ' 10' issue: '1' language: - iso: eng main_file_link: - open_access: '1' url: http://repository.ist.ac.at/id/eprint/436 month: '01' oa: 1 oa_version: Published Version publication: PLoS Computational Biology publication_identifier: issn: - 1553734X publication_status: published publisher: Public Library of Science publist_id: '4689' pubrep_id: '436' quality_controlled: '1' related_material: record: - id: '5562' relation: popular_science status: public scopus_import: 1 status: public title: Searching for collective behavior in a large network of sensory neurons tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 10 year: '2014' ... --- _id: '2413' abstract: - lang: eng text: 'Progress in understanding the global brain dynamics has remained slow to date in large part because of the highly multiscale nature of brain activity. Indeed, normal brain dynamics is characterized by complex interactions between multiple levels: from the microscopic scale of single neurons to the mesoscopic level of local groups of neurons, and finally to the macroscopic level of the whole brain. Among the most difficult tasks are those of identifying which scales are significant for a given particular function and describing how the scales affect each other. It is important to realize that the scales of time and space are linked together, or even intertwined, and that causal inference is far more ambiguous between than within levels. We approach this problem from the perspective of our recent work on simultaneous recording from micro- and macroelectrodes in the human brain. We propose a physiological description of these multilevel interactions, based on phase–amplitude coupling of neuronal oscillations that operate at multiple frequencies and on different spatial scales. Specifically, the amplitude of the oscillations on a particular spatial scale is modulated by phasic variations in neuronal excitability induced by lower frequency oscillations that emerge on a larger spatial scale. Following this general principle, it is possible to scale up or scale down the multiscale brain dynamics. It is expected that large-scale network oscillations in the low-frequency range, mediating downward effects, may play an important role in attention and consciousness.' alternative_title: - Reviews of Nonlinear Dynamics and Complexity author: - first_name: Mario full_name: Valderrama, Mario last_name: Valderrama - first_name: Vicente full_name: Botella Soler, Vicente id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: Michel full_name: Le Van Quyen, Michel last_name: Le Van Quyen citation: ama: 'Valderrama M, Botella Soler V, Le Van Quyen M. Neuronal oscillations scale up and scale down the brain dynamics . In: Meyer M, Pesenson Z, eds. Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain. Wiley-VCH; 2013. doi:10.1002/9783527671632.ch08' apa: 'Valderrama, M., Botella Soler, V., & Le Van Quyen, M. (2013). Neuronal oscillations scale up and scale down the brain dynamics . In M. Meyer & Z. Pesenson (Eds.), Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain. Wiley-VCH. https://doi.org/10.1002/9783527671632.ch08' chicago: 'Valderrama, Mario, Vicente Botella Soler, and Michel Le Van Quyen. “Neuronal Oscillations Scale up and Scale down the Brain Dynamics .” In Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, edited by Misha Meyer and Z. Pesenson. Wiley-VCH, 2013. https://doi.org/10.1002/9783527671632.ch08.' ieee: 'M. Valderrama, V. Botella Soler, and M. Le Van Quyen, “Neuronal oscillations scale up and scale down the brain dynamics ,” in Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, M. Meyer and Z. Pesenson, Eds. Wiley-VCH, 2013.' ista: 'Valderrama M, Botella Soler V, Le Van Quyen M. 2013.Neuronal oscillations scale up and scale down the brain dynamics . In: Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain. Reviews of Nonlinear Dynamics and Complexity, .' mla: 'Valderrama, Mario, et al. “Neuronal Oscillations Scale up and Scale down the Brain Dynamics .” Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, edited by Misha Meyer and Z. Pesenson, Wiley-VCH, 2013, doi:10.1002/9783527671632.ch08.' short: 'M. Valderrama, V. Botella Soler, M. Le Van Quyen, in:, M. Meyer, Z. Pesenson (Eds.), Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, Wiley-VCH, 2013.' date_created: 2018-12-11T11:57:31Z date_published: 2013-08-01T00:00:00Z date_updated: 2021-01-12T06:57:20Z day: '01' department: - _id: GaTk doi: 10.1002/9783527671632.ch08 editor: - first_name: Misha full_name: Meyer, Misha last_name: Meyer - first_name: Z. full_name: Pesenson, Z. last_name: Pesenson language: - iso: eng month: '08' oa_version: None publication: 'Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain' publication_identifier: eisbn: - '9783527671632' isbn: - '9783527411986 ' publication_status: published publisher: Wiley-VCH publist_id: '4513' quality_controlled: '1' scopus_import: 1 status: public title: 'Neuronal oscillations scale up and scale down the brain dynamics ' type: book_chapter user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 year: '2013' ... --- _id: '2818' abstract: - lang: eng text: Models of neural responses to stimuli with complex spatiotemporal correlation structure often assume that neurons are selective for only a small number of linear projections of a potentially high-dimensional input. In this review, we explore recent modeling approaches where the neural response depends on the quadratic form of the input rather than on its linear projection, that is, the neuron is sensitive to the local covariance structure of the signal preceding the spike. To infer this quadratic dependence in the presence of arbitrary (e.g., naturalistic) stimulus distribution, we review several inference methods, focusing in particular on two information theory–based approaches (maximization of stimulus energy and of noise entropy) and two likelihood-based approaches (Bayesian spike-triggered covariance and extensions of generalized linear models). We analyze the formal relationship between the likelihood-based and information-based approaches to demonstrate how they lead to consistent inference. We demonstrate the practical feasibility of these procedures by using model neurons responding to a flickering variance stimulus. author: - first_name: Kanaka full_name: Rajan, Kanaka last_name: Rajan - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Rajan K, Marre O, Tkačik G. Learning quadratic receptive fields from neural responses to natural stimuli. Neural Computation. 2013;25(7):1661-1692. doi:10.1162/NECO_a_00463 apa: Rajan, K., Marre, O., & Tkačik, G. (2013). Learning quadratic receptive fields from neural responses to natural stimuli. Neural Computation. MIT Press . https://doi.org/10.1162/NECO_a_00463 chicago: Rajan, Kanaka, Olivier Marre, and Gašper Tkačik. “Learning Quadratic Receptive Fields from Neural Responses to Natural Stimuli.” Neural Computation. MIT Press , 2013. https://doi.org/10.1162/NECO_a_00463. ieee: K. Rajan, O. Marre, and G. Tkačik, “Learning quadratic receptive fields from neural responses to natural stimuli,” Neural Computation, vol. 25, no. 7. MIT Press , pp. 1661–1692, 2013. ista: Rajan K, Marre O, Tkačik G. 2013. Learning quadratic receptive fields from neural responses to natural stimuli. Neural Computation. 25(7), 1661–1692. mla: Rajan, Kanaka, et al. “Learning Quadratic Receptive Fields from Neural Responses to Natural Stimuli.” Neural Computation, vol. 25, no. 7, MIT Press , 2013, pp. 1661–92, doi:10.1162/NECO_a_00463. short: K. Rajan, O. Marre, G. Tkačik, Neural Computation 25 (2013) 1661–1692. date_created: 2018-12-11T11:59:45Z date_published: 2013-07-01T00:00:00Z date_updated: 2021-01-12T06:59:56Z day: '01' department: - _id: GaTk doi: 10.1162/NECO_a_00463 external_id: arxiv: - '1209.0121' intvolume: ' 25' issue: '7' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1209.0121 month: '07' oa: 1 oa_version: Preprint page: 1661 - 1692 publication: Neural Computation publication_status: published publisher: 'MIT Press ' publist_id: '3983' quality_controlled: '1' scopus_import: 1 status: public title: Learning quadratic receptive fields from neural responses to natural stimuli type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 25 year: '2013' ... --- _id: '2850' abstract: - lang: eng text: "Recent work emphasizes that the maximum entropy principle provides a bridge between statistical mechanics models for collective behavior in neural networks and experiments on networks of real neurons. Most of this work has focused on capturing the measured correlations among pairs of neurons. Here we suggest an alternative, constructing models that are consistent with the distribution of global network activity, i.e. the probability that K out of N cells in the network generate action potentials in the same small time bin. The inverse problem that we need to solve in constructing the model is analytically tractable, and provides a natural 'thermodynamics' for the network in the limit of large N. We analyze the responses of neurons in a small patch of the retina to naturalistic stimuli, and find that the implied thermodynamics is very close to an unusual critical point, in which the entropy (in proper units) is exactly equal to the energy. © 2013 IOP Publishing Ltd and SISSA Medialab srl.\r\n" acknowledgement: "his work was supported in part by NSF Grants IIS-0613435 and PHY-0957573, by NIH Grants R01 EY14196 and P50 GM071508, by the Fannie and John Hertz Foundation, by the Human Frontiers Science Program, by the Swartz Foundation, and by the WM Keck Foundation.\r\n" article_number: P03011 article_processing_charge: No article_type: original author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Thierry full_name: Mora, Thierry last_name: Mora - first_name: Dario full_name: Amodei, Dario last_name: Amodei - first_name: Michael full_name: Berry, Michael last_name: Berry - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. The simplest maximum entropy model for collective behavior in a neural network. Journal of Statistical Mechanics Theory and Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03011 apa: Tkačik, G., Marre, O., Mora, T., Amodei, D., Berry, M., & Bialek, W. (2013). The simplest maximum entropy model for collective behavior in a neural network. Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd. https://doi.org/10.1088/1742-5468/2013/03/P03011 chicago: Tkačik, Gašper, Olivier Marre, Thierry Mora, Dario Amodei, Michael Berry, and William Bialek. “The Simplest Maximum Entropy Model for Collective Behavior in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd., 2013. https://doi.org/10.1088/1742-5468/2013/03/P03011. ieee: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, and W. Bialek, “The simplest maximum entropy model for collective behavior in a neural network,” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing Ltd., 2013. ista: Tkačik G, Marre O, Mora T, Amodei D, Berry M, Bialek W. 2013. The simplest maximum entropy model for collective behavior in a neural network. Journal of Statistical Mechanics Theory and Experiment. 2013(3), P03011. mla: Tkačik, Gašper, et al. “The Simplest Maximum Entropy Model for Collective Behavior in a Neural Network.” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3, P03011, IOP Publishing Ltd., 2013, doi:10.1088/1742-5468/2013/03/P03011. short: G. Tkačik, O. Marre, T. Mora, D. Amodei, M. Berry, W. Bialek, Journal of Statistical Mechanics Theory and Experiment 2013 (2013). date_created: 2018-12-11T11:59:55Z date_published: 2013-03-12T00:00:00Z date_updated: 2021-01-12T07:00:14Z day: '12' department: - _id: GaTk doi: 10.1088/1742-5468/2013/03/P03011 external_id: arxiv: - '1207.6319' intvolume: ' 2013' issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1207.6319 month: '03' oa: 1 oa_version: Preprint publication: Journal of Statistical Mechanics Theory and Experiment publication_status: published publisher: IOP Publishing Ltd. publist_id: '3942' quality_controlled: '1' scopus_import: 1 status: public title: The simplest maximum entropy model for collective behavior in a neural network type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2013 year: '2013' ... --- _id: '2851' abstract: - lang: eng text: The number of possible activity patterns in a population of neurons grows exponentially with the size of the population. Typical experiments explore only a tiny fraction of the large space of possible activity patterns in the case of populations with more than 10 or 20 neurons. It is thus impossible, in this undersampled regime, to estimate the probabilities with which most of the activity patterns occur. As a result, the corresponding entropy - which is a measure of the computational power of the neural population - cannot be estimated directly. We propose a simple scheme for estimating the entropy in the undersampled regime, which bounds its value from both below and above. The lower bound is the usual 'naive' entropy of the experimental frequencies. The upper bound results from a hybrid approximation of the entropy which makes use of the naive estimate, a maximum entropy fit, and a coverage adjustment. We apply our simple scheme to artificial data, in order to check their accuracy; we also compare its performance to those of several previously defined entropy estimators. We then apply it to actual measurements of neural activity in populations with up to 100 cells. Finally, we discuss the similarities and differences between the proposed simple estimation scheme and various earlier methods. © 2013 IOP Publishing Ltd and SISSA Medialab srl. article_number: P03015 author: - first_name: Michael full_name: Berry, Michael last_name: Berry - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Julien full_name: Dubuis, Julien last_name: Dubuis - first_name: Olivier full_name: Marre, Olivier last_name: Marre - first_name: Ravá full_name: Da Silveira, Ravá last_name: Da Silveira citation: ama: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. A simple method for estimating the entropy of neural activity. Journal of Statistical Mechanics Theory and Experiment. 2013;2013(3). doi:10.1088/1742-5468/2013/03/P03015 apa: Berry, M., Tkačik, G., Dubuis, J., Marre, O., & Da Silveira, R. (2013). A simple method for estimating the entropy of neural activity. Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd. https://doi.org/10.1088/1742-5468/2013/03/P03015 chicago: Berry, Michael, Gašper Tkačik, Julien Dubuis, Olivier Marre, and Ravá Da Silveira. “A Simple Method for Estimating the Entropy of Neural Activity.” Journal of Statistical Mechanics Theory and Experiment. IOP Publishing Ltd., 2013. https://doi.org/10.1088/1742-5468/2013/03/P03015. ieee: M. Berry, G. Tkačik, J. Dubuis, O. Marre, and R. Da Silveira, “A simple method for estimating the entropy of neural activity,” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3. IOP Publishing Ltd., 2013. ista: Berry M, Tkačik G, Dubuis J, Marre O, Da Silveira R. 2013. A simple method for estimating the entropy of neural activity. Journal of Statistical Mechanics Theory and Experiment. 2013(3), P03015. mla: Berry, Michael, et al. “A Simple Method for Estimating the Entropy of Neural Activity.” Journal of Statistical Mechanics Theory and Experiment, vol. 2013, no. 3, P03015, IOP Publishing Ltd., 2013, doi:10.1088/1742-5468/2013/03/P03015. short: M. Berry, G. Tkačik, J. Dubuis, O. Marre, R. Da Silveira, Journal of Statistical Mechanics Theory and Experiment 2013 (2013). date_created: 2018-12-11T11:59:56Z date_published: 2013-03-12T00:00:00Z date_updated: 2021-01-12T07:00:14Z day: '12' department: - _id: GaTk doi: 10.1088/1742-5468/2013/03/P03015 intvolume: ' 2013' issue: '3' language: - iso: eng month: '03' oa_version: None publication: Journal of Statistical Mechanics Theory and Experiment publication_status: published publisher: IOP Publishing Ltd. publist_id: '3941' quality_controlled: '1' scopus_import: 1 status: public title: A simple method for estimating the entropy of neural activity type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2013 year: '2013' ... --- _id: '2863' abstract: - lang: eng text: Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population. article_number: e1002922 author: - first_name: Einat full_name: Granot Atedgi, Einat last_name: Granot Atedgi - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Ronen full_name: Segev, Ronen last_name: Segev - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman citation: ama: Granot Atedgi E, Tkačik G, Segev R, Schneidman E. Stimulus-dependent maximum entropy models of neural population codes. PLoS Computational Biology. 2013;9(3). doi:10.1371/journal.pcbi.1002922 apa: Granot Atedgi, E., Tkačik, G., Segev, R., & Schneidman, E. (2013). Stimulus-dependent maximum entropy models of neural population codes. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1002922 chicago: Granot Atedgi, Einat, Gašper Tkačik, Ronen Segev, and Elad Schneidman. “Stimulus-Dependent Maximum Entropy Models of Neural Population Codes.” PLoS Computational Biology. Public Library of Science, 2013. https://doi.org/10.1371/journal.pcbi.1002922. ieee: E. Granot Atedgi, G. Tkačik, R. Segev, and E. Schneidman, “Stimulus-dependent maximum entropy models of neural population codes,” PLoS Computational Biology, vol. 9, no. 3. Public Library of Science, 2013. ista: Granot Atedgi E, Tkačik G, Segev R, Schneidman E. 2013. Stimulus-dependent maximum entropy models of neural population codes. PLoS Computational Biology. 9(3), e1002922. mla: Granot Atedgi, Einat, et al. “Stimulus-Dependent Maximum Entropy Models of Neural Population Codes.” PLoS Computational Biology, vol. 9, no. 3, e1002922, Public Library of Science, 2013, doi:10.1371/journal.pcbi.1002922. short: E. Granot Atedgi, G. Tkačik, R. Segev, E. Schneidman, PLoS Computational Biology 9 (2013). date_created: 2018-12-11T12:00:00Z date_published: 2013-03-01T00:00:00Z date_updated: 2021-01-12T07:00:20Z day: '01' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1002922 file: - access_level: open_access checksum: 5a30876c193209fa05b26db71845dd16 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:45Z date_updated: 2020-07-14T12:45:52Z file_id: '5099' file_name: IST-2013-120-v1+1_journal.pcbi.1002922.pdf file_size: 1548120 relation: main_file file_date_updated: 2020-07-14T12:45:52Z has_accepted_license: '1' intvolume: ' 9' issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Published Version publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science publist_id: '3926' pubrep_id: '120' quality_controlled: '1' scopus_import: 1 status: public title: Stimulus-dependent maximum entropy models of neural population codes tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 9 year: '2013' ... --- _id: '2861' abstract: - lang: eng text: We consider a two-parameter family of piecewise linear maps in which the moduli of the two slopes take different values. We provide numerical evidence of the existence of some parameter regions in which the Lyapunov exponent and the topological entropy remain constant. Analytical proof of this phenomenon is also given for certain cases. Surprisingly however, the systems with that property are not conjugate as we prove by using kneading theory. article_number: '125101' author: - first_name: Vicente full_name: Botella Soler, Vicente id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: José full_name: Oteo, José last_name: Oteo - first_name: Javier full_name: Ros, Javier last_name: Ros - first_name: Paul full_name: Glendinning, Paul last_name: Glendinning citation: ama: 'Botella Soler V, Oteo J, Ros J, Glendinning P. Lyapunov exponent and topological entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical and Theoretical. 2013;46(12). doi:10.1088/1751-8113/46/12/125101' apa: 'Botella Soler, V., Oteo, J., Ros, J., & Glendinning, P. (2013). Lyapunov exponent and topological entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical and Theoretical. IOP Publishing Ltd. https://doi.org/10.1088/1751-8113/46/12/125101' chicago: 'Botella Soler, Vicente, José Oteo, Javier Ros, and Paul Glendinning. “Lyapunov Exponent and Topological Entropy Plateaus in Piecewise Linear Maps.” Journal of Physics A: Mathematical and Theoretical. IOP Publishing Ltd., 2013. https://doi.org/10.1088/1751-8113/46/12/125101.' ieee: 'V. Botella Soler, J. Oteo, J. Ros, and P. Glendinning, “Lyapunov exponent and topological entropy plateaus in piecewise linear maps,” Journal of Physics A: Mathematical and Theoretical, vol. 46, no. 12. IOP Publishing Ltd., 2013.' ista: 'Botella Soler V, Oteo J, Ros J, Glendinning P. 2013. Lyapunov exponent and topological entropy plateaus in piecewise linear maps. Journal of Physics A: Mathematical and Theoretical. 46(12), 125101.' mla: 'Botella Soler, Vicente, et al. “Lyapunov Exponent and Topological Entropy Plateaus in Piecewise Linear Maps.” Journal of Physics A: Mathematical and Theoretical, vol. 46, no. 12, 125101, IOP Publishing Ltd., 2013, doi:10.1088/1751-8113/46/12/125101.' short: 'V. Botella Soler, J. Oteo, J. Ros, P. Glendinning, Journal of Physics A: Mathematical and Theoretical 46 (2013).' date_created: 2018-12-11T11:59:59Z date_published: 2013-03-29T00:00:00Z date_updated: 2021-01-12T07:00:19Z day: '29' department: - _id: GaTk doi: 10.1088/1751-8113/46/12/125101 intvolume: ' 46' issue: '12' language: - iso: eng month: '03' oa_version: None publication: 'Journal of Physics A: Mathematical and Theoretical' publication_status: published publisher: IOP Publishing Ltd. publist_id: '3928' quality_controlled: '1' scopus_import: 1 status: public title: Lyapunov exponent and topological entropy plateaus in piecewise linear maps type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 46 year: '2013' ... --- _id: '2913' abstract: - lang: eng text: 'The ability of an organism to distinguish between various stimuli is limited by the structure and noise in the population code of its sensory neurons. Here we infer a distance measure on the stimulus space directly from the recorded activity of 100 neurons in the salamander retina. In contrast to previously used measures of stimulus similarity, this "neural metric" tells us how distinguishable a pair of stimulus clips is to the retina, based on the similarity between the induced distributions of population responses. We show that the retinal distance strongly deviates from Euclidean, or any static metric, yet has a simple structure: we identify the stimulus features that the neural population is jointly sensitive to, and show the support-vector-machine- like kernel function relating the stimulus and neural response spaces. We show that the non-Euclidean nature of the retinal distance has important consequences for neural decoding.' article_number: '058104' author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Einat full_name: Granot Atedgi, Einat last_name: Granot Atedgi - first_name: Ronen full_name: Segev, Ronen last_name: Segev - first_name: Elad full_name: Schneidman, Elad last_name: Schneidman citation: ama: 'Tkačik G, Granot Atedgi E, Segev R, Schneidman E. Retinal metric: a stimulus distance measure derived from population neural responses. Physical Review Letters. 2013;110(5). doi:10.1103/PhysRevLett.110.058104' apa: 'Tkačik, G., Granot Atedgi, E., Segev, R., & Schneidman, E. (2013). Retinal metric: a stimulus distance measure derived from population neural responses. Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.110.058104' chicago: 'Tkačik, Gašper, Einat Granot Atedgi, Ronen Segev, and Elad Schneidman. “Retinal Metric: A Stimulus Distance Measure Derived from Population Neural Responses.” Physical Review Letters. American Physical Society, 2013. https://doi.org/10.1103/PhysRevLett.110.058104.' ieee: 'G. Tkačik, E. Granot Atedgi, R. Segev, and E. Schneidman, “Retinal metric: a stimulus distance measure derived from population neural responses,” Physical Review Letters, vol. 110, no. 5. American Physical Society, 2013.' ista: 'Tkačik G, Granot Atedgi E, Segev R, Schneidman E. 2013. Retinal metric: a stimulus distance measure derived from population neural responses. Physical Review Letters. 110(5), 058104.' mla: 'Tkačik, Gašper, et al. “Retinal Metric: A Stimulus Distance Measure Derived from Population Neural Responses.” Physical Review Letters, vol. 110, no. 5, 058104, American Physical Society, 2013, doi:10.1103/PhysRevLett.110.058104.' short: G. Tkačik, E. Granot Atedgi, R. Segev, E. Schneidman, Physical Review Letters 110 (2013). date_created: 2018-12-11T12:00:18Z date_published: 2013-01-28T00:00:00Z date_updated: 2021-01-12T07:00:39Z day: '28' department: - _id: GaTk doi: 10.1103/PhysRevLett.110.058104 intvolume: ' 110' issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1205.6598 month: '01' oa: 1 oa_version: Preprint publication: Physical Review Letters publication_status: published publisher: American Physical Society publist_id: '3830' quality_controlled: '1' scopus_import: 1 status: public title: 'Retinal metric: a stimulus distance measure derived from population neural responses' type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 110 year: '2013' ... --- _id: '3261' abstract: - lang: eng text: Cells in a developing embryo have no direct way of "measuring" their physical position. Through a variety of processes, however, the expression levels of multiple genes come to be correlated with position, and these expression levels thus form a code for "positional information." We show how to measure this information, in bits, using the gap genes in the Drosophila embryo as an example. Individual genes carry nearly two bits of information, twice as much as expected if the expression patterns consisted only of on/off domains separated by sharp boundaries. Taken together, four gap genes carry enough information to define a cell's location with an error bar of ~1% along the anterior-posterior axis of the embryo. This precision is nearly enough for each cell to have a unique identity, which is the maximum information the system can use, and is nearly constant along the length of the embryo. We argue that this constancy is a signature of optimality in the transmission of information from primary morphogen inputs to the output of the gap gene network. author: - first_name: Julien full_name: Dubuis, Julien last_name: Dubuis - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Eric full_name: Wieschaus, Eric last_name: Wieschaus - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Dubuis J, Tkačik G, Wieschaus E, Gregor T, Bialek W. Positional information, in bits. PNAS. 2013;110(41):16301-16308. doi:10.1073/pnas.1315642110 apa: Dubuis, J., Tkačik, G., Wieschaus, E., Gregor, T., & Bialek, W. (2013). Positional information, in bits. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1315642110 chicago: Dubuis, Julien, Gašper Tkačik, Eric Wieschaus, Thomas Gregor, and William Bialek. “Positional Information, in Bits.” PNAS. National Academy of Sciences, 2013. https://doi.org/10.1073/pnas.1315642110. ieee: J. Dubuis, G. Tkačik, E. Wieschaus, T. Gregor, and W. Bialek, “Positional information, in bits,” PNAS, vol. 110, no. 41. National Academy of Sciences, pp. 16301–16308, 2013. ista: Dubuis J, Tkačik G, Wieschaus E, Gregor T, Bialek W. 2013. Positional information, in bits. PNAS. 110(41), 16301–16308. mla: Dubuis, Julien, et al. “Positional Information, in Bits.” PNAS, vol. 110, no. 41, National Academy of Sciences, 2013, pp. 16301–08, doi:10.1073/pnas.1315642110. short: J. Dubuis, G. Tkačik, E. Wieschaus, T. Gregor, W. Bialek, PNAS 110 (2013) 16301–16308. date_created: 2018-12-11T12:02:19Z date_published: 2013-10-08T00:00:00Z date_updated: 2021-01-12T07:42:13Z day: '08' ddc: - '570' department: - _id: GaTk doi: 10.1073/pnas.1315642110 external_id: pmid: - '24089448' file: - access_level: open_access checksum: ecd859fe52a562193027d428b5524a8d content_type: application/pdf creator: dernst date_created: 2019-01-22T13:53:23Z date_updated: 2020-07-14T12:46:06Z file_id: '5873' file_name: 2013_PNAS_Dubuis.pdf file_size: 1670548 relation: main_file file_date_updated: 2020-07-14T12:46:06Z has_accepted_license: '1' intvolume: ' 110' issue: '41' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: 16301 - 16308 pmid: 1 publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '3387' quality_controlled: '1' scopus_import: 1 status: public title: Positional information, in bits type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 110 year: '2013' ... --- _id: '499' abstract: - lang: eng text: Exposure of an isogenic bacterial population to a cidal antibiotic typically fails to eliminate a small fraction of refractory cells. Historically, fractional killing has been attributed to infrequently dividing or nondividing "persisters." Using microfluidic cultures and time-lapse microscopy, we found that Mycobacterium smegmatis persists by dividing in the presence of the drug isoniazid (INH). Although persistence in these studies was characterized by stable numbers of cells, this apparent stability was actually a dynamic state of balanced division and death. Single cells expressed catalase-peroxidase (KatG), which activates INH, in stochastic pulses that were negatively correlated with cell survival. These behaviors may reflect epigenetic effects, because KatG pulsing and death were correlated between sibling cells. Selection of lineages characterized by infrequent KatG pulsing could allow nonresponsive adaptation during prolonged drug exposure. author: - first_name: Yurichi full_name: Wakamoto, Yurichi last_name: Wakamoto - first_name: Neraaj full_name: Dhar, Neraaj last_name: Dhar - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Katrin full_name: Schneider, Katrin last_name: Schneider - first_name: François full_name: Signorino Gelo, François last_name: Signorino Gelo - first_name: Stanislas full_name: Leibler, Stanislas last_name: Leibler - first_name: John full_name: Mckinney, John last_name: Mckinney citation: ama: Wakamoto Y, Dhar N, Chait RP, et al. Dynamic persistence of antibiotic-stressed mycobacteria. Science. 2013;339(6115):91-95. doi:10.1126/science.1229858 apa: Wakamoto, Y., Dhar, N., Chait, R. P., Schneider, K., Signorino Gelo, F., Leibler, S., & Mckinney, J. (2013). Dynamic persistence of antibiotic-stressed mycobacteria. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.1229858 chicago: Wakamoto, Yurichi, Neraaj Dhar, Remy P Chait, Katrin Schneider, François Signorino Gelo, Stanislas Leibler, and John Mckinney. “Dynamic Persistence of Antibiotic-Stressed Mycobacteria.” Science. American Association for the Advancement of Science, 2013. https://doi.org/10.1126/science.1229858. ieee: Y. Wakamoto et al., “Dynamic persistence of antibiotic-stressed mycobacteria,” Science, vol. 339, no. 6115. American Association for the Advancement of Science, pp. 91–95, 2013. ista: Wakamoto Y, Dhar N, Chait RP, Schneider K, Signorino Gelo F, Leibler S, Mckinney J. 2013. Dynamic persistence of antibiotic-stressed mycobacteria. Science. 339(6115), 91–95. mla: Wakamoto, Yurichi, et al. “Dynamic Persistence of Antibiotic-Stressed Mycobacteria.” Science, vol. 339, no. 6115, American Association for the Advancement of Science, 2013, pp. 91–95, doi:10.1126/science.1229858. short: Y. Wakamoto, N. Dhar, R.P. Chait, K. Schneider, F. Signorino Gelo, S. Leibler, J. Mckinney, Science 339 (2013) 91–95. date_created: 2018-12-11T11:46:48Z date_published: 2013-01-04T00:00:00Z date_updated: 2021-01-12T08:01:06Z day: '04' department: - _id: CaGu - _id: GaTk doi: 10.1126/science.1229858 intvolume: ' 339' issue: '6115' language: - iso: eng month: '01' oa_version: None page: 91 - 95 publication: Science publication_status: published publisher: American Association for the Advancement of Science publist_id: '7321' quality_controlled: '1' scopus_import: 1 status: public title: Dynamic persistence of antibiotic-stressed mycobacteria type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 339 year: '2013' ... --- _id: '2277' abstract: - lang: eng text: Redundancies and correlations in the responses of sensory neurons may seem to waste neural resources, but they can also carry cues about structured stimuli and may help the brain to correct for response errors. To investigate the effect of stimulus structure on redundancy in retina, we measured simultaneous responses from populations of retinal ganglion cells presented with natural and artificial stimuli that varied greatly in correlation structure; these stimuli and recordings are publicly available online. Responding to spatio-temporally structured stimuli such as natural movies, pairs of ganglion cells were modestly more correlated than in response to white noise checkerboards, but they were much less correlated than predicted by a non-adapting functional model of retinal response. Meanwhile, responding to stimuli with purely spatial correlations, pairs of ganglion cells showed increased correlations consistent with a static, non-adapting receptive field and nonlinearity. We found that in response to spatio-temporally correlated stimuli, ganglion cells had faster temporal kernels and tended to have stronger surrounds. These properties of individual cells, along with gain changes that opposed changes in effective contrast at the ganglion cell input, largely explained the pattern of pairwise correlations across stimuli where receptive field measurements were possible. article_number: e1003344 author: - first_name: Kristina full_name: Simmons, Kristina last_name: Simmons - first_name: Jason full_name: Prentice, Jason last_name: Prentice - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Jan full_name: Homann, Jan last_name: Homann - first_name: Heather full_name: Yee, Heather last_name: Yee - first_name: Stephanie full_name: Palmer, Stephanie last_name: Palmer - first_name: Philip full_name: Nelson, Philip last_name: Nelson - first_name: Vijay full_name: Balasubramanian, Vijay last_name: Balasubramanian citation: ama: Simmons K, Prentice J, Tkačik G, et al. Transformation of stimulus correlations by the retina. PLoS Computational Biology. 2013;9(12). doi:10.1371/journal.pcbi.1003344 apa: Simmons, K., Prentice, J., Tkačik, G., Homann, J., Yee, H., Palmer, S., … Balasubramanian, V. (2013). Transformation of stimulus correlations by the retina. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1003344 chicago: Simmons, Kristina, Jason Prentice, Gašper Tkačik, Jan Homann, Heather Yee, Stephanie Palmer, Philip Nelson, and Vijay Balasubramanian. “Transformation of Stimulus Correlations by the Retina.” PLoS Computational Biology. Public Library of Science, 2013. https://doi.org/10.1371/journal.pcbi.1003344. ieee: K. Simmons et al., “Transformation of stimulus correlations by the retina,” PLoS Computational Biology, vol. 9, no. 12. Public Library of Science, 2013. ista: Simmons K, Prentice J, Tkačik G, Homann J, Yee H, Palmer S, Nelson P, Balasubramanian V. 2013. Transformation of stimulus correlations by the retina. PLoS Computational Biology. 9(12), e1003344. mla: Simmons, Kristina, et al. “Transformation of Stimulus Correlations by the Retina.” PLoS Computational Biology, vol. 9, no. 12, e1003344, Public Library of Science, 2013, doi:10.1371/journal.pcbi.1003344. short: K. Simmons, J. Prentice, G. Tkačik, J. Homann, H. Yee, S. Palmer, P. Nelson, V. Balasubramanian, PLoS Computational Biology 9 (2013). date_created: 2018-12-11T11:56:43Z date_published: 2013-12-05T00:00:00Z date_updated: 2023-02-23T14:07:04Z day: '05' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pcbi.1003344 file: - access_level: open_access checksum: 46722afc4f7eabb0831165d9c1b171ad content_type: application/pdf creator: system date_created: 2018-12-12T10:14:36Z date_updated: 2020-07-14T12:45:36Z file_id: '5089' file_name: IST-2016-410-v1+1_journal.pcbi.1003344.pdf file_size: 3115568 relation: main_file file_date_updated: 2020-07-14T12:45:36Z has_accepted_license: '1' intvolume: ' 9' issue: '12' language: - iso: eng month: '12' oa: 1 oa_version: Published Version publication: PLoS Computational Biology publication_status: published publisher: Public Library of Science publist_id: '4667' pubrep_id: '410' quality_controlled: '1' related_material: record: - id: '9752' relation: research_data status: public scopus_import: 1 status: public title: Transformation of stimulus correlations by the retina tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 9 year: '2013' ... --- _id: '2914' abstract: - lang: eng text: The scale invariance of natural images suggests an analogy to the statistical mechanics of physical systems at a critical point. Here we examine the distribution of pixels in small image patches and show how to construct the corresponding thermodynamics. We find evidence for criticality in a diverging specific heat, which corresponds to large fluctuations in how "surprising" we find individual images, and in the quantitative form of the entropy vs energy. We identify special image configurations as local energy minima and show that average patches within each basin are interpretable as lines and edges in all orientations. acknowledgement: "This work was supported in part by NSF Grants No. IIS-0613435, No. IBN-0344678, and No. PHY-0957573, by NIH Grant No. T32 MH065214, by the Human Frontier Science Program, and by the Swartz Foundation.\r\nCC BY 3.0\r\n" article_number: '018701' article_processing_charge: No article_type: original author: - first_name: Greg full_name: Stephens, Greg last_name: Stephens - first_name: Thierry full_name: Mora, Thierry last_name: Mora - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Stephens G, Mora T, Tkačik G, Bialek W. Statistical thermodynamics of natural images. Physical Review Letters. 2013;110(1). doi:10.1103/PhysRevLett.110.018701 apa: Stephens, G., Mora, T., Tkačik, G., & Bialek, W. (2013). Statistical thermodynamics of natural images. Physical Review Letters. American Physical Society. https://doi.org/10.1103/PhysRevLett.110.018701 chicago: Stephens, Greg, Thierry Mora, Gašper Tkačik, and William Bialek. “Statistical Thermodynamics of Natural Images.” Physical Review Letters. American Physical Society, 2013. https://doi.org/10.1103/PhysRevLett.110.018701. ieee: G. Stephens, T. Mora, G. Tkačik, and W. Bialek, “Statistical thermodynamics of natural images,” Physical Review Letters, vol. 110, no. 1. American Physical Society, 2013. ista: Stephens G, Mora T, Tkačik G, Bialek W. 2013. Statistical thermodynamics of natural images. Physical Review Letters. 110(1), 018701. mla: Stephens, Greg, et al. “Statistical Thermodynamics of Natural Images.” Physical Review Letters, vol. 110, no. 1, 018701, American Physical Society, 2013, doi:10.1103/PhysRevLett.110.018701. short: G. Stephens, T. Mora, G. Tkačik, W. Bialek, Physical Review Letters 110 (2013). date_created: 2018-12-11T12:00:19Z date_published: 2013-01-02T00:00:00Z date_updated: 2023-09-04T11:47:51Z day: '02' ddc: - '530' department: - _id: GaTk doi: 10.1103/PhysRevLett.110.018701 external_id: arxiv: - '0806.2694' file: - access_level: open_access checksum: 72bfbc2094c4680e8a8a6bed668cd06d content_type: application/pdf creator: system date_created: 2018-12-12T10:18:44Z date_updated: 2020-07-14T12:45:53Z file_id: '5366' file_name: IST-2016-401-v1+1_1281.full.pdf file_size: 416965 relation: main_file file_date_updated: 2020-07-14T12:45:53Z has_accepted_license: '1' intvolume: ' 110' issue: '1' language: - iso: eng month: '01' oa: 1 oa_version: Published Version publication: Physical Review Letters publication_status: published publisher: American Physical Society publist_id: '3829' pubrep_id: '401' quality_controlled: '1' status: public title: Statistical thermodynamics of natural images tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 110 year: '2013' ... --- _id: '3262' abstract: - lang: eng text: Living cells must control the reading out or "expression" of information encoded in their genomes, and this regulation often is mediated by transcription factors--proteins that bind to DNA and either enhance or repress the expression of nearby genes. But the expression of transcription factor proteins is itself regulated, and many transcription factors regulate their own expression in addition to responding to other input signals. Here we analyze the simplest of such self-regulatory circuits, asking how parameters can be chosen to optimize information transmission from inputs to outputs in the steady state. Some nonzero level of self-regulation is almost always optimal, with self-activation dominant when transcription factor concentrations are low and self-repression dominant when concentrations are high. In steady state the optimal self-activation is never strong enough to induce bistability, although there is a limit in which the optimal parameters are very close to the critical point. acknowledgement: "We thank T. Gregor, E. F. Wieschaus, and, especially, C. G. Callan for helpful discussions.\r\nWork at Princeton was supported in part by NSF Grants No. PHY–0957573 and No. CCF–0939370, by NIH Grant No. R01 GM077599, and by the W. M. Keck Foundation. For part of this work, G.T. was supported in part by NSF Grant No. EF–0928048 and by the Vice Provost for Research at the University of Pennsylvania." article_number: '041903' author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Aleksandra full_name: Walczak, Aleksandra last_name: Walczak - first_name: William full_name: Bialek, William last_name: Bialek citation: ama: Tkačik G, Walczak A, Bialek W. Optimizing information flow in small genetic networks. III. A self-interacting gene. Physical Review E statistical nonlinear and soft matter physics . 2012;85(4). doi:10.1103/PhysRevE.85.041903 apa: Tkačik, G., Walczak, A., & Bialek, W. (2012). Optimizing information flow in small genetic networks. III. A self-interacting gene. Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics. https://doi.org/10.1103/PhysRevE.85.041903 chicago: Tkačik, Gašper, Aleksandra Walczak, and William Bialek. “Optimizing Information Flow in Small Genetic Networks. III. A Self-Interacting Gene.” Physical Review E Statistical Nonlinear and Soft Matter Physics . American Institute of Physics, 2012. https://doi.org/10.1103/PhysRevE.85.041903. ieee: G. Tkačik, A. Walczak, and W. Bialek, “Optimizing information flow in small genetic networks. III. A self-interacting gene,” Physical Review E statistical nonlinear and soft matter physics , vol. 85, no. 4. American Institute of Physics, 2012. ista: Tkačik G, Walczak A, Bialek W. 2012. Optimizing information flow in small genetic networks. III. A self-interacting gene. Physical Review E statistical nonlinear and soft matter physics . 85(4), 041903. mla: Tkačik, Gašper, et al. “Optimizing Information Flow in Small Genetic Networks. III. A Self-Interacting Gene.” Physical Review E Statistical Nonlinear and Soft Matter Physics , vol. 85, no. 4, 041903, American Institute of Physics, 2012, doi:10.1103/PhysRevE.85.041903. short: G. Tkačik, A. Walczak, W. Bialek, Physical Review E Statistical Nonlinear and Soft Matter Physics 85 (2012). date_created: 2018-12-11T12:02:20Z date_published: 2012-04-01T00:00:00Z date_updated: 2021-01-12T07:42:14Z day: '01' department: - _id: GaTk doi: 10.1103/PhysRevE.85.041903 intvolume: ' 85' issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1112.5026 month: '04' oa: 1 oa_version: Preprint publication: ' Physical Review E statistical nonlinear and soft matter physics ' publication_status: published publisher: American Institute of Physics publist_id: '3386' quality_controlled: '1' scopus_import: 1 status: public title: Optimizing information flow in small genetic networks. III. A self-interacting gene type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 85 year: '2012' ... --- _id: '3274' abstract: - lang: eng text: A boundary element model of a tunnel running through horizontally layered soil with anisotropic material properties is presented. Since there is no analytical fundamental solution for wave propagation inside a layered orthotropic medium in 3D, the fundamental displacements and stresses have to be calculated numerically. In our model this is done in the Fourier domain with respect to space and time. The assumption of a straight tunnel with infinite extension in the x direction makes it possible to decouple the system for every wave number kx, leading to a 2.5D-problem, which is suited for parallel computation. The special form of the fundamental solution, resulting from our Fourier ansatz, and the fact, that the calculation of the boundary integral equation is performed in the Fourier domain, enhances the stability and efficiency of the numerical calculations. acknowledgement: This work was supported by the Austrian Federal Ministry of Transport, Innovation and Technology under the Grant Bmvit-isb2 and the FFG under the project Pr. Nr. 809089. author: - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Wolfgang full_name: Kreuzer, Wolfgang last_name: Kreuzer - first_name: Holger full_name: Waubke, Holger last_name: Waubke - first_name: Peter full_name: Balazs, Peter last_name: Balazs citation: ama: Rieckh G, Kreuzer W, Waubke H, Balazs P. A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil. Engineering Analysis with Boundary Elements. 2012;36(6):960-967. doi:10.1016/j.enganabound.2011.12.014 apa: Rieckh, G., Kreuzer, W., Waubke, H., & Balazs, P. (2012). A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil. Engineering Analysis with Boundary Elements. Elsevier. https://doi.org/10.1016/j.enganabound.2011.12.014 chicago: Rieckh, Georg, Wolfgang Kreuzer, Holger Waubke, and Peter Balazs. “A 2.5D-Fourier-BEM Model for Vibrations in a Tunnel Running through Layered Anisotropic Soil.” Engineering Analysis with Boundary Elements. Elsevier, 2012. https://doi.org/10.1016/j.enganabound.2011.12.014. ieee: G. Rieckh, W. Kreuzer, H. Waubke, and P. Balazs, “A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil,” Engineering Analysis with Boundary Elements, vol. 36, no. 6. Elsevier, pp. 960–967, 2012. ista: Rieckh G, Kreuzer W, Waubke H, Balazs P. 2012. A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil. Engineering Analysis with Boundary Elements. 36(6), 960–967. mla: Rieckh, Georg, et al. “A 2.5D-Fourier-BEM Model for Vibrations in a Tunnel Running through Layered Anisotropic Soil.” Engineering Analysis with Boundary Elements, vol. 36, no. 6, Elsevier, 2012, pp. 960–67, doi:10.1016/j.enganabound.2011.12.014. short: G. Rieckh, W. Kreuzer, H. Waubke, P. Balazs, Engineering Analysis with Boundary Elements 36 (2012) 960–967. date_created: 2018-12-11T12:02:24Z date_published: 2012-06-01T00:00:00Z date_updated: 2021-01-12T07:42:19Z day: '01' department: - _id: GaTk doi: 10.1016/j.enganabound.2011.12.014 intvolume: ' 36' issue: '6' language: - iso: eng month: '06' oa_version: None page: 960 - 967 publication: ' Engineering Analysis with Boundary Elements' publication_status: published publisher: Elsevier publist_id: '3372' quality_controlled: '1' scopus_import: 1 status: public title: A 2.5D-Fourier-BEM model for vibrations in a tunnel running through layered anisotropic soil type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 36 year: '2012' ... --- _id: '3374' abstract: - lang: eng text: Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network's inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted 'positional information'. article_number: '153102' author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Aleksandra full_name: Walczak, Aleksandra last_name: Walczak citation: ama: 'Tkačik G, Walczak A. Information transmission in genetic regulatory networks a review. Journal of Physics: Condensed Matter. 2011;23(15). doi:10.1088/0953-8984/23/15/153102' apa: 'Tkačik, G., & Walczak, A. (2011). Information transmission in genetic regulatory networks a review. Journal of Physics: Condensed Matter. IOP Publishing Ltd. https://doi.org/10.1088/0953-8984/23/15/153102' chicago: 'Tkačik, Gašper, and Aleksandra Walczak. “Information Transmission in Genetic Regulatory Networks a Review.” Journal of Physics: Condensed Matter. IOP Publishing Ltd., 2011. https://doi.org/10.1088/0953-8984/23/15/153102.' ieee: 'G. Tkačik and A. Walczak, “Information transmission in genetic regulatory networks a review,” Journal of Physics: Condensed Matter, vol. 23, no. 15. IOP Publishing Ltd., 2011.' ista: 'Tkačik G, Walczak A. 2011. Information transmission in genetic regulatory networks a review. Journal of Physics: Condensed Matter. 23(15), 153102.' mla: 'Tkačik, Gašper, and Aleksandra Walczak. “Information Transmission in Genetic Regulatory Networks a Review.” Journal of Physics: Condensed Matter, vol. 23, no. 15, 153102, IOP Publishing Ltd., 2011, doi:10.1088/0953-8984/23/15/153102.' short: 'G. Tkačik, A. Walczak, Journal of Physics: Condensed Matter 23 (2011).' date_created: 2018-12-11T12:02:58Z date_published: 2011-04-01T00:00:00Z date_updated: 2021-01-12T07:43:03Z day: '01' department: - _id: GaTk doi: 10.1088/0953-8984/23/15/153102 intvolume: ' 23' issue: '15' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1101.4240 month: '04' oa: 1 oa_version: Submitted Version publication: 'Journal of Physics: Condensed Matter' publication_status: published publisher: IOP Publishing Ltd. publist_id: '3233' quality_controlled: '1' scopus_import: 1 status: public title: Information transmission in genetic regulatory networks a review type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 23 year: '2011' ... --- _id: '3384' abstract: - lang: eng text: Here we introduce a database of calibrated natural images publicly available through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we acquired about six-megapixel images of Okavango Delta of Botswana, a tropical savanna habitat similar to where the human eye is thought to have evolved. Some sequences of images were captured unsystematically while following a baboon troop, while others were designed to vary a single parameter such as aperture, object distance, time of day or position on the horizon. Images are available in the raw RGB format and in grayscale. Images are also available in units relevant to the physiology of human cone photoreceptors, where pixel values represent the expected number of photoisomerizations per second for cones sensitive to long (L), medium (M) and short (S) wavelengths. This database is distributed under a Creative Commons Attribution-Noncommercial Unported license to facilitate research in computer vision, psychophysics of perception, and visual neuroscience. article_number: e20409 author: - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: Patrick full_name: Garrigan, Patrick last_name: Garrigan - first_name: Charles full_name: Ratliff, Charles last_name: Ratliff - first_name: Grega full_name: Milcinski, Grega last_name: Milcinski - first_name: Jennifer full_name: Klein, Jennifer last_name: Klein - first_name: Lucia full_name: Seyfarth, Lucia last_name: Seyfarth - first_name: Peter full_name: Sterling, Peter last_name: Sterling - first_name: David full_name: Brainard, David last_name: Brainard - first_name: Vijay full_name: Balasubramanian, Vijay last_name: Balasubramanian citation: ama: Tkačik G, Garrigan P, Ratliff C, et al. Natural images from the birthplace of the human eye. PLoS One. 2011;6(6). doi:10.1371/journal.pone.0020409 apa: Tkačik, G., Garrigan, P., Ratliff, C., Milcinski, G., Klein, J., Seyfarth, L., … Balasubramanian, V. (2011). Natural images from the birthplace of the human eye. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0020409 chicago: Tkačik, Gašper, Patrick Garrigan, Charles Ratliff, Grega Milcinski, Jennifer Klein, Lucia Seyfarth, Peter Sterling, David Brainard, and Vijay Balasubramanian. “Natural Images from the Birthplace of the Human Eye.” PLoS One. Public Library of Science, 2011. https://doi.org/10.1371/journal.pone.0020409. ieee: G. Tkačik et al., “Natural images from the birthplace of the human eye,” PLoS One, vol. 6, no. 6. Public Library of Science, 2011. ista: Tkačik G, Garrigan P, Ratliff C, Milcinski G, Klein J, Seyfarth L, Sterling P, Brainard D, Balasubramanian V. 2011. Natural images from the birthplace of the human eye. PLoS One. 6(6), e20409. mla: Tkačik, Gašper, et al. “Natural Images from the Birthplace of the Human Eye.” PLoS One, vol. 6, no. 6, e20409, Public Library of Science, 2011, doi:10.1371/journal.pone.0020409. short: G. Tkačik, P. Garrigan, C. Ratliff, G. Milcinski, J. Klein, L. Seyfarth, P. Sterling, D. Brainard, V. Balasubramanian, PLoS One 6 (2011). date_created: 2018-12-11T12:03:01Z date_published: 2011-06-16T00:00:00Z date_updated: 2021-01-12T07:43:07Z day: '16' ddc: - '570' department: - _id: GaTk doi: 10.1371/journal.pone.0020409 file: - access_level: open_access checksum: 307d4356916471306e3705ac65b82fa1 content_type: application/pdf creator: system date_created: 2018-12-12T10:09:25Z date_updated: 2020-07-14T12:46:11Z file_id: '4749' file_name: IST-2015-379-v1+1_journal.pone.0020409.pdf file_size: 1424768 relation: main_file file_date_updated: 2020-07-14T12:46:11Z has_accepted_license: '1' intvolume: ' 6' issue: '6' language: - iso: eng month: '06' oa: 1 oa_version: Published Version publication: PLoS One publication_status: published publisher: Public Library of Science publist_id: '3223' pubrep_id: '379' quality_controlled: '1' scopus_import: 1 status: public title: Natural images from the birthplace of the human eye tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 6 year: '2011' ...