---
_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'
article_processing_charge: No
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: 2025-09-23T09:36:19Z
day: '01'
department:
- _id: ToHe
- _id: GaTk
doi: 10.1145/2688906
external_id:
isi:
- '000354789200002'
intvolume: ' 25'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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. '
article_processing_charge: No
arxiv: 1
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.
corr_author: '1'
date_created: 2018-12-11T11:54:32Z
date_published: 2015-01-01T00:00:00Z
date_updated: 2025-09-23T09:53:07Z
day: '01'
department:
- _id: GaTk
doi: 10.1534/genetics.114.171850
external_id:
arxiv:
- '1404.5599'
isi:
- '000347712900004'
intvolume: ' 199'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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'
article_processing_charge: No
arxiv: 1
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).
corr_author: '1'
date_created: 2018-12-11T11:54:49Z
date_published: 2015-06-15T00:00:00Z
date_updated: 2025-09-23T09:46:10Z
day: '15'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.91.062710
external_id:
arxiv:
- '1501.04015'
isi:
- '000356131600006'
intvolume: ' 91'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 91
year: '2015'
...
---
_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).
corr_author: '1'
date_created: 2022-02-25T11:42:25Z
date_published: 2015-06-10T00:00:00Z
date_updated: 2025-04-15T06:50:01Z
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
license: https://creativecommons.org/licenses/by/4.0/
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: '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: 2025-09-23T08:31:14Z
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: '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: 2025-09-23T08:43:16Z
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: '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: 2025-09-23T08:43:16Z
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: '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: 2025-09-23T08:43:16Z
day: '23'
ddc:
- '576'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1004055
ec_funded: 1
external_id:
isi:
- '000352195700006'
file:
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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
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has_accepted_license: '1'
intvolume: ' 11'
isi: 1
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:
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status: public
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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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 11
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.
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: 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: 2026-07-29T11:31:13Z
day: '06'
ddc:
- '576'
department:
- _id: NiBa
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pgen.1005639
ec_funded: 1
external_id:
isi:
- '000366179000022'
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'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 11
year: '2015'
...
---
_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.
article_processing_charge: No
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.
corr_author: '1'
date_created: 2018-12-11T11:56:28Z
date_published: 2014-03-04T00:00:00Z
date_updated: 2025-09-29T11:23:30Z
day: '04'
department:
- _id: GaTk
doi: 10.1016/j.bpj.2014.01.014
external_id:
isi:
- '000332501300022'
pmid:
- '24606943'
intvolume: ' 106'
isi: 1
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:
- 0006-3495
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 106
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: 'This 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
article_processing_charge: No
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).
corr_author: '1'
date_created: 2018-12-11T11:56:36Z
date_published: 2014-01-02T00:00:00Z
date_updated: 2025-09-29T11:14:06Z
day: '02'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1003408
external_id:
isi:
- '000337948500010'
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'
isi: 1
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_identifier:
issn:
- 1553-734X
publication_status: published
publisher: Public Library of Science
publist_id: '4689'
pubrep_id: '436'
quality_controlled: '1'
related_material:
record:
- id: '5562'
relation: research_data
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 10
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
arxiv: 1
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).
corr_author: '1'
date_created: 2018-12-11T11:56:11Z
date_published: 2014-06-16T00:00:00Z
date_updated: 2025-09-29T11:34:45Z
day: '16'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.89.062809
ec_funded: 1
external_id:
arxiv:
- '1403.3209'
isi:
- '000337733900007'
intvolume: ' 89'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 89
year: '2014'
...
---
_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.
article_processing_charge: No
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 27. Neural Information Processing Systems Foundation;
2014:2024-2032.'
apa: 'Savin, C., & Denève, S. (2014). Spatio-temporal representations of uncertainty
in spiking neural networks (Vol. 27, pp. 2024–2032). Presented at the NIPS: Neural
Information Processing Systems, Montreal, Canada: Neural Information Processing
Systems Foundation.'
chicago: Savin, Cristina, and Sophie Denève. “Spatio-Temporal Representations of
Uncertainty in Spiking Neural Networks,” 27:2024–32. Neural Information Processing
Systems Foundation, 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. 27, 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. 27,
2024–2032.'
mla: Savin, Cristina, and Sophie Denève. Spatio-Temporal Representations of Uncertainty
in Spiking Neural Networks. Vol. 27, no. January, Neural Information Processing
Systems Foundation, 2014, pp. 2024–32.
short: C. Savin, S. Denève, in:, Neural Information Processing Systems Foundation,
2014, pp. 2024–2032.
conference:
end_date: 2014-12-13
location: Montreal, Canada
name: 'NIPS: Neural Information Processing Systems'
start_date: 2014-12-08
corr_author: '1'
date_created: 2018-12-11T11:53:35Z
date_published: 2014-01-01T00:00:00Z
date_updated: 2025-06-03T11:45:08Z
day: '01'
department:
- _id: GaTk
intvolume: ' 27'
issue: January
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://papers.nips.cc/paper/5343-spatio-temporal-representations-of-uncertainty-in-spiking-neural-networks.pdf
month: '01'
oa: 1
oa_version: None
page: 2024 - 2032
publication_status: published
publisher: Neural Information Processing Systems Foundation
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 27
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
article_processing_charge: No
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: 2025-09-29T13:08:33Z
day: '14'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.7554/eLife.03722
external_id:
isi:
- '000209685300001'
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'
isi: 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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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
arxiv: 1
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: 2025-09-29T13:03:34Z
day: '04'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1103/PhysRevE.89.032701
external_id:
arxiv:
- '1402.0430'
isi:
- '000332274100002'
intvolume: ' 89'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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'
article_processing_charge: No
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: 2025-09-29T12:26:34Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1111/1365-2435.12207
external_id:
isi:
- '000335954900016'
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'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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.
article_processing_charge: No
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.
corr_author: '1'
date_created: 2018-12-11T11:54:46Z
date_published: 2014-11-07T00:00:00Z
date_updated: 2025-09-29T12:12:23Z
day: '07'
department:
- _id: GaTk
doi: 10.1016/j.jtbi.2014.06.039
external_id:
isi:
- '000341800600017'
intvolume: ' 360'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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'
article_processing_charge: No
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).
corr_author: '1'
date_created: 2018-12-11T11:54:46Z
date_published: 2014-05-28T00:00:00Z
date_updated: 2025-09-29T12:11:13Z
day: '28'
department:
- _id: GaTk
doi: 10.3389/fncom.2014.00057
external_id:
isi:
- '000336715400001'
intvolume: ' 8'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 8
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.
article_processing_charge: No
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: 2025-09-29T13:17:53Z
day: '19'
ddc:
- '530'
- '571'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1002/ece3.1150
external_id:
isi:
- '000340575000015'
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'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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: 2025-09-29T14:27:23Z
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'
...