---
_id: '14402'
abstract:
- lang: eng
text: Alpha oscillations are a distinctive feature of the awake resting state of
the human brain. However, their functional role in resting-state neuronal dynamics
remains poorly understood. Here we show that, during resting wakefulness, alpha
oscillations drive an alternation of attenuation and amplification bouts in neural
activity. Our analysis indicates that inhibition is activated in pulses that last
for a single alpha cycle and gradually suppress neural activity, while excitation
is successively enhanced over a few alpha cycles to amplify neural activity. Furthermore,
we show that long-term alpha amplitude fluctuations—the “waxing and waning” phenomenon—are
an attenuation-amplification mechanism described by a power-law decay of the activity
rate in the “waning” phase. Importantly, we do not observe such dynamics during
non-rapid eye movement (NREM) sleep with marginal alpha oscillations. The results
suggest that alpha oscillations modulate neural activity not only through pulses
of inhibition (pulsed inhibition hypothesis) but also by timely enhancement of
excitation (or disinhibition).
acknowledgement: This research was funded in whole or in part by the Austrian Science
Fund (FWF) (grant PT1013M03318 to F.L.). For the purpose of open access, the author
has applied a CC BY public copyright license to any Author Accepted Manuscript version
arising from this submission. The study was supported by the European Union Horizon
2020 Research and Innovation Program under the Marie Sklodowska-Curie action (grant
agreement 754411 to F.L.) and in part by the NextGenerationEU through the grant
TAlent in ReSearch@University of Padua – STARS@UNIPD (to F.L.) (project BRAINCIP
[brain criticality and information processing]). L.d.A. acknowledges support from
the Italian MIUR project PRIN2017WZFTZP and partial support from NEXTGENERATIONEU
(NGEU) funded by the Ministry of University and Research (MUR), National Recovery
and Resilience Plan (NRRP), and project MNESYS (PE0000006)—a multiscale integrated
approach to the study of the nervous system in health and disease (DN. 1553 11.10.2022).
O.S. acknowledges support from the Israel Science Foundation, grant 504/17. The
work was supported in part by DIRP ZIAMH02797 (to D.P.).
article_number: '113162'
article_processing_charge: Yes
article_type: original
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Hans J.
full_name: Herrmann, Hans J.
last_name: Herrmann
- first_name: Liborio
full_name: Parrino, Liborio
last_name: Parrino
- first_name: Dietmar
full_name: Plenz, Dietmar
last_name: Plenz
- first_name: Silvia
full_name: Scarpetta, Silvia
last_name: Scarpetta
- first_name: Anna Elisabetta
full_name: Vaudano, Anna Elisabetta
last_name: Vaudano
- first_name: Lucilla
full_name: De Arcangelis, Lucilla
last_name: De Arcangelis
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
citation:
ama: 'Lombardi F, Herrmann HJ, Parrino L, et al. Beyond pulsed inhibition: Alpha
oscillations modulate attenuation and amplification of neural activity in the
awake resting state. Cell Reports. 2023;42(10). doi:10.1016/j.celrep.2023.113162'
apa: 'Lombardi, F., Herrmann, H. J., Parrino, L., Plenz, D., Scarpetta, S., Vaudano,
A. E., … Shriki, O. (2023). Beyond pulsed inhibition: Alpha oscillations modulate
attenuation and amplification of neural activity in the awake resting state. Cell
Reports. Elsevier. https://doi.org/10.1016/j.celrep.2023.113162'
chicago: 'Lombardi, Fabrizio, Hans J. Herrmann, Liborio Parrino, Dietmar Plenz,
Silvia Scarpetta, Anna Elisabetta Vaudano, Lucilla De Arcangelis, and Oren Shriki.
“Beyond Pulsed Inhibition: Alpha Oscillations Modulate Attenuation and Amplification
of Neural Activity in the Awake Resting State.” Cell Reports. Elsevier,
2023. https://doi.org/10.1016/j.celrep.2023.113162.'
ieee: 'F. Lombardi et al., “Beyond pulsed inhibition: Alpha oscillations
modulate attenuation and amplification of neural activity in the awake resting
state,” Cell Reports, vol. 42, no. 10. Elsevier, 2023.'
ista: 'Lombardi F, Herrmann HJ, Parrino L, Plenz D, Scarpetta S, Vaudano AE, De
Arcangelis L, Shriki O. 2023. Beyond pulsed inhibition: Alpha oscillations modulate
attenuation and amplification of neural activity in the awake resting state. Cell
Reports. 42(10), 113162.'
mla: 'Lombardi, Fabrizio, et al. “Beyond Pulsed Inhibition: Alpha Oscillations Modulate
Attenuation and Amplification of Neural Activity in the Awake Resting State.”
Cell Reports, vol. 42, no. 10, 113162, Elsevier, 2023, doi:10.1016/j.celrep.2023.113162.'
short: F. Lombardi, H.J. Herrmann, L. Parrino, D. Plenz, S. Scarpetta, A.E. Vaudano,
L. De Arcangelis, O. Shriki, Cell Reports 42 (2023).
corr_author: '1'
date_created: 2023-10-08T22:01:15Z
date_published: 2023-10-31T00:00:00Z
date_updated: 2026-07-06T12:48:55Z
day: '31'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1016/j.celrep.2023.113162
ec_funded: 1
external_id:
isi:
- '001086695500001'
pmid:
- '37777965'
file:
- access_level: open_access
checksum: 9c71eb2a03aa160415f01ad95f49ceb5
content_type: application/pdf
creator: dernst
date_created: 2024-01-30T14:07:08Z
date_updated: 2024-01-30T14:07:08Z
file_id: '14914'
file_name: 2023_CellReports_Lombardi.pdf
file_size: 5599007
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file_date_updated: 2024-01-30T14:07:08Z
has_accepted_license: '1'
intvolume: ' 42'
isi: 1
issue: '10'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '10'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: eb943429-77a9-11ec-83b8-9f471cdf5c67
grant_number: M03318
name: Functional Advantages of Critical Brain Dynamics
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Cell Reports
publication_identifier:
eissn:
- 2211-1247
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
record:
- id: '10821'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: 'Beyond pulsed inhibition: Alpha oscillations modulate attenuation and amplification
of neural activity in the awake resting state'
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: 42
year: '2023'
...
---
_id: '12762'
abstract:
- lang: eng
text: Neurons in the brain are wired into adaptive networks that exhibit collective
dynamics as diverse as scale-specific oscillations and scale-free neuronal avalanches.
Although existing models account for oscillations and avalanches separately, they
typically do not explain both phenomena, are too complex to analyze analytically
or intractable to infer from data rigorously. Here we propose a feedback-driven
Ising-like class of neural networks that captures avalanches and oscillations
simultaneously and quantitatively. In the simplest yet fully microscopic model
version, we can analytically compute the phase diagram and make direct contact
with human brain resting-state activity recordings via tractable inference of
the model’s two essential parameters. The inferred model quantitatively captures
the dynamics over a broad range of scales, from single sensor oscillations to
collective behaviors of extreme events and neuronal avalanches. Importantly, the
inferred parameters indicate that the co-existence of scale-specific (oscillations)
and scale-free (avalanches) dynamics occurs close to a non-equilibrium critical
point at the onset of self-sustained oscillations.
acknowledgement: This research was funded in whole, or in part, by the Austrian Science
Fund (FWF) (grant no. PT1013M03318 to F.L. and no. P34015 to G.T.). For the purpose
of open access, the author has applied a CC BY public copyright licence to any Author
Accepted Manuscript version arising from this submission. The study was supported
by the European Union Horizon 2020 research and innovation program under the Marie
Sklodowska-Curie action (grant agreement No. 754411 to F.L.).
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Selver
full_name: Pepic, Selver
id: F93245C4-C3CA-11E9-B4F0-C6F4E5697425
last_name: Pepic
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
citation:
ama: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Statistical modeling
of adaptive neural networks explains co-existence of avalanches and oscillations
in resting human brain. Nature Computational Science. 2023;3:254-263. doi:10.1038/s43588-023-00410-9
apa: Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., & De Martino, D. (2023).
Statistical modeling of adaptive neural networks explains co-existence of avalanches
and oscillations in resting human brain. Nature Computational Science.
Springer Nature. https://doi.org/10.1038/s43588-023-00410-9
chicago: Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele
De Martino. “Statistical Modeling of Adaptive Neural Networks Explains Co-Existence
of Avalanches and Oscillations in Resting Human Brain.” Nature Computational
Science. Springer Nature, 2023. https://doi.org/10.1038/s43588-023-00410-9.
ieee: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, and D. De Martino, “Statistical
modeling of adaptive neural networks explains co-existence of avalanches and oscillations
in resting human brain,” Nature Computational Science, vol. 3. Springer
Nature, pp. 254–263, 2023.
ista: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. 2023. Statistical modeling
of adaptive neural networks explains co-existence of avalanches and oscillations
in resting human brain. Nature Computational Science. 3, 254–263.
mla: Lombardi, Fabrizio, et al. “Statistical Modeling of Adaptive Neural Networks
Explains Co-Existence of Avalanches and Oscillations in Resting Human Brain.”
Nature Computational Science, vol. 3, Springer Nature, 2023, pp. 254–63,
doi:10.1038/s43588-023-00410-9.
short: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, D. De Martino, Nature Computational
Science 3 (2023) 254–263.
corr_author: '1'
date_created: 2023-03-26T22:01:08Z
date_published: 2023-03-20T00:00:00Z
date_updated: 2026-07-29T06:53:41Z
day: '20'
ddc:
- '570'
department:
- _id: GaTk
- _id: GradSch
doi: 10.1038/s43588-023-00410-9
ec_funded: 1
external_id:
arxiv:
- '2108.06686'
isi:
- '000968161800002'
pmid:
- '38177880'
file:
- access_level: open_access
checksum: 7c63b2b2edfd68aaffe96d70ca6a865a
content_type: application/pdf
creator: dernst
date_created: 2023-08-16T12:39:57Z
date_updated: 2023-08-16T12:39:57Z
file_id: '14073'
file_name: 2023_NatureCompScience_Lombardi.pdf
file_size: 4474284
relation: main_file
success: 1
file_date_updated: 2023-08-16T12:39:57Z
has_accepted_license: '1'
intvolume: ' 3'
isi: 1
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 254-263
pmid: 1
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: eb943429-77a9-11ec-83b8-9f471cdf5c67
grant_number: M03318
name: Functional Advantages of Critical Brain Dynamics
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
publication: Nature Computational Science
publication_identifier:
eissn:
- 2662-8457
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '10912'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Statistical modeling of adaptive neural networks explains co-existence of avalanches
and oscillations in resting human brain
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: 3
year: '2023'
...
---
_id: '14656'
abstract:
- lang: eng
text: Although much is known about how single neurons in the hippocampus represent
an animal's position, how circuit interactions contribute to spatial coding is
less well understood. Using a novel statistical estimator and theoretical modeling,
both developed in the framework of maximum entropy models, we reveal highly structured
CA1 cell-cell interactions in male rats during open field exploration. The statistics
of these interactions depend on whether the animal is in a familiar or novel environment.
In both conditions the circuit interactions optimize the encoding of spatial information,
but for regimes that differ in the informativeness of their spatial inputs. This
structure facilitates linear decodability, making the information easy to read
out by downstream circuits. Overall, our findings suggest that the efficient coding
hypothesis is not only applicable to individual neuron properties in the sensory
periphery, but also to neural interactions in the central brain.
acknowledgement: M.N. was supported by the European Union Horizon 2020 Grant 665385.
J.C. was supported by the European Research Council Consolidator Grant 281511. G.T.
was supported by the Austrian Science Fund (FWF) Grant P34015. C.S. was supported
by an Institute of Science and Technology fellow award and by the National Science
Foundation (NSF) Award No. 1922658. We thank Peter Baracskay, Karola Kaefer, and
Hugo Malagon-Vina for the acquisition of the data. We also thank Federico Stella,
Wiktor Młynarski, Dori Derdikman, Colin Bredenberg, Roman Huszar, Heloisa Chiossi,
Lorenzo Posani, and Mohamady El-Gaby for comments on an earlier version of the manuscript.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Michele
full_name: Nardin, Michele
id: 30BD0376-F248-11E8-B48F-1D18A9856A87
last_name: Nardin
orcid: 0000-0001-8849-6570
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
citation:
ama: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1
interactions optimizes spatial coding across experience. The Journal of Neuroscience.
2023;43(48):8140-8156. doi:10.1523/JNEUROSCI.0194-23.2023
apa: Nardin, M., Csicsvari, J. L., Tkačik, G., & Savin, C. (2023). The structure
of hippocampal CA1 interactions optimizes spatial coding across experience. The
Journal of Neuroscience. Society for Neuroscience. https://doi.org/10.1523/JNEUROSCI.0194-23.2023
chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin.
“The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across
Experience.” The Journal of Neuroscience. Society for Neuroscience, 2023.
https://doi.org/10.1523/JNEUROSCI.0194-23.2023.
ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal
CA1 interactions optimizes spatial coding across experience,” The Journal of
Neuroscience, vol. 43, no. 48. Society for Neuroscience, pp. 8140–8156, 2023.
ista: Nardin M, Csicsvari JL, Tkačik G, Savin C. 2023. The structure of hippocampal
CA1 interactions optimizes spatial coding across experience. The Journal of Neuroscience.
43(48), 8140–8156.
mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes
Spatial Coding across Experience.” The Journal of Neuroscience, vol. 43,
no. 48, Society for Neuroscience, 2023, pp. 8140–56, doi:10.1523/JNEUROSCI.0194-23.2023.
short: M. Nardin, J.L. Csicsvari, G. Tkačik, C. Savin, The Journal of Neuroscience
43 (2023) 8140–8156.
date_created: 2023-12-10T23:00:58Z
date_published: 2023-11-29T00:00:00Z
date_updated: 2026-07-06T12:47:25Z
day: '29'
ddc:
- '570'
department:
- _id: JoCs
- _id: GaTk
doi: 10.1523/JNEUROSCI.0194-23.2023
ec_funded: 1
external_id:
isi:
- '001148071000005'
pmid:
- '37758476'
file:
- access_level: open_access
checksum: e2503c8f84be1050e28f64320f1d5bd2
content_type: application/pdf
creator: dernst
date_created: 2023-12-11T11:30:37Z
date_updated: 2024-06-02T22:30:03Z
embargo: 2024-06-01
file_id: '14674'
file_name: 2023_JourNeuroscience_Nardin.pdf
file_size: 2280632
relation: main_file
file_date_updated: 2024-06-02T22:30:03Z
has_accepted_license: '1'
intvolume: ' 43'
isi: 1
issue: '48'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 8140-8156
pmid: 1
project:
- _id: 257A4776-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '281511'
name: Memory-related information processing in neuronal circuits of the hippocampus
and entorhinal cortex
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: The Journal of Neuroscience
publication_identifier:
eissn:
- 1529-2401
publication_status: published
publisher: Society for Neuroscience
quality_controlled: '1'
related_material:
record:
- id: '10077'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: The structure of hippocampal CA1 interactions optimizes spatial coding across
experience
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: 43
year: '2023'
...
---
_id: '11638'
abstract:
- lang: eng
text: 'Statistical inference is central to many scientific endeavors, yet how it
works remains unresolved. Answering this requires a quantitative understanding
of the intrinsic interplay between statistical models, inference methods, and
the structure in the data. To this end, we characterize the efficacy of direct
coupling analysis (DCA)—a highly successful method for analyzing amino acid sequence
data—in inferring pairwise interactions from samples of ferromagnetic Ising models
on random graphs. Our approach allows for physically motivated exploration of
qualitatively distinct data regimes separated by phase transitions. We show that
inference quality depends strongly on the nature of data-generating distributions:
optimal accuracy occurs at an intermediate temperature where the detrimental effects
from macroscopic order and thermal noise are minimal. Importantly our results
indicate that DCA does not always outperform its local-statistics-based predecessors;
while DCA excels at low temperatures, it becomes inferior to simple correlation
thresholding at virtually all temperatures when data are limited. Our findings
offer insights into the regime in which DCA operates so successfully, and more
broadly, how inference interacts with the structure in the data.'
acknowledgement: This work was supported in part by the Alfred P. Sloan Foundation,
the Simons Foundation, the National Institutes of Health under Award No. R01EB026943,
and the National Science Foundation, through the Center for the Physics of Biological
Function (PHY-1734030).
article_number: '023240'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Vudtiwat
full_name: Ngampruetikorn, Vudtiwat
last_name: Ngampruetikorn
- first_name: Vedant
full_name: Sachdeva, Vedant
last_name: Sachdeva
- first_name: Johanna
full_name: Torrence, Johanna
last_name: Torrence
- first_name: Jan
full_name: Humplik, Jan
id: 2E9627A8-F248-11E8-B48F-1D18A9856A87
last_name: Humplik
- first_name: David J.
full_name: Schwab, David J.
last_name: Schwab
- first_name: Stephanie E.
full_name: Palmer, Stephanie E.
last_name: Palmer
citation:
ama: Ngampruetikorn V, Sachdeva V, Torrence J, Humplik J, Schwab DJ, Palmer SE.
Inferring couplings in networks across order-disorder phase transitions. Physical
Review Research. 2022;4(2). doi:10.1103/PhysRevResearch.4.023240
apa: Ngampruetikorn, V., Sachdeva, V., Torrence, J., Humplik, J., Schwab, D. J.,
& Palmer, S. E. (2022). Inferring couplings in networks across order-disorder
phase transitions. Physical Review Research. American Physical Society.
https://doi.org/10.1103/PhysRevResearch.4.023240
chicago: Ngampruetikorn, Vudtiwat, Vedant Sachdeva, Johanna Torrence, Jan Humplik,
David J. Schwab, and Stephanie E. Palmer. “Inferring Couplings in Networks across
Order-Disorder Phase Transitions.” Physical Review Research. American Physical
Society, 2022. https://doi.org/10.1103/PhysRevResearch.4.023240.
ieee: V. Ngampruetikorn, V. Sachdeva, J. Torrence, J. Humplik, D. J. Schwab, and
S. E. Palmer, “Inferring couplings in networks across order-disorder phase transitions,”
Physical Review Research, vol. 4, no. 2. American Physical Society, 2022.
ista: Ngampruetikorn V, Sachdeva V, Torrence J, Humplik J, Schwab DJ, Palmer SE.
2022. Inferring couplings in networks across order-disorder phase transitions.
Physical Review Research. 4(2), 023240.
mla: Ngampruetikorn, Vudtiwat, et al. “Inferring Couplings in Networks across Order-Disorder
Phase Transitions.” Physical Review Research, vol. 4, no. 2, 023240, American
Physical Society, 2022, doi:10.1103/PhysRevResearch.4.023240.
short: V. Ngampruetikorn, V. Sachdeva, J. Torrence, J. Humplik, D.J. Schwab, S.E.
Palmer, Physical Review Research 4 (2022).
date_created: 2022-07-24T22:01:42Z
date_published: 2022-06-24T00:00:00Z
date_updated: 2025-03-06T14:09:21Z
day: '24'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.1103/PhysRevResearch.4.023240
external_id:
arxiv:
- '2106.02349'
pmid:
- '37576946'
file:
- access_level: open_access
checksum: ed6fdc2a3a096df785fa5f7b17b716c6
content_type: application/pdf
creator: dernst
date_created: 2022-07-25T07:47:23Z
date_updated: 2022-07-25T07:47:23Z
file_id: '11644'
file_name: 2022_PhysicalReviewResearch_Ngampruetikorn.pdf
file_size: 1379683
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success: 1
file_date_updated: 2022-07-25T07:47:23Z
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intvolume: ' 4'
issue: '2'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
pmid: 1
publication: Physical Review Research
publication_identifier:
issn:
- 2643-1564
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Inferring couplings in networks across order-disorder phase transitions
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: '2022'
...
---
_id: '12081'
abstract:
- lang: eng
text: 'Selection accumulates information in the genome—it guides stochastically
evolving populations toward states (genotype frequencies) that would be unlikely
under neutrality. This can be quantified as the Kullback–Leibler (KL) divergence
between the actual distribution of genotype frequencies and the corresponding
neutral distribution. First, we show that this population-level information sets
an upper bound on the information at the level of genotype and phenotype, limiting
how precisely they can be specified by selection. Next, we study how the accumulation
and maintenance of information is limited by the cost of selection, measured as
the genetic load or the relative fitness variance, both of which we connect to
the control-theoretic KL cost of control. The information accumulation rate is
upper bounded by the population size times the cost of selection. This bound is
very general, and applies across models (Wright–Fisher, Moran, diffusion) and
to arbitrary forms of selection, mutation, and recombination. Finally, the cost
of maintaining information depends on how it is encoded: Specifying a single allele
out of two is expensive, but one bit encoded among many weakly specified loci
(as in a polygenic trait) is cheap.'
acknowledgement: We thank Ksenia Khudiakova, Wiktor Młynarski, Sean Stankowski, and
two anonymous reviewers for discussions and comments on the manuscript. G.T. and
M.H. acknowledge funding from the Human Frontier Science Program Grant RGP0032/2018.
N.B. acknowledges funding from ERC Grant 250152 “Information and Evolution.”
article_number: e2123152119
article_processing_charge: No
article_type: original
author:
- first_name: Michal
full_name: Hledik, Michal
id: 4171253A-F248-11E8-B48F-1D18A9856A87
last_name: Hledik
- 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: '1'
citation:
ama: Hledik M, Barton NH, Tkačik G. Accumulation and maintenance of information
in evolution. Proceedings of the National Academy of Sciences of the United
States of America. 2022;119(36). doi:10.1073/pnas.2123152119
apa: Hledik, M., Barton, N. H., & Tkačik, G. (2022). Accumulation and maintenance
of information in evolution. Proceedings of the National Academy of Sciences
of the United States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.2123152119
chicago: Hledik, Michal, Nicholas H Barton, and Gašper Tkačik. “Accumulation and
Maintenance of Information in Evolution.” Proceedings of the National Academy
of Sciences of the United States of America. National Academy of Sciences,
2022. https://doi.org/10.1073/pnas.2123152119.
ieee: M. Hledik, N. H. Barton, and G. Tkačik, “Accumulation and maintenance of information
in evolution,” Proceedings of the National Academy of Sciences of the United
States of America, vol. 119, no. 36. National Academy of Sciences, 2022.
ista: Hledik M, Barton NH, Tkačik G. 2022. Accumulation and maintenance of information
in evolution. Proceedings of the National Academy of Sciences of the United States
of America. 119(36), e2123152119.
mla: Hledik, Michal, et al. “Accumulation and Maintenance of Information in Evolution.”
Proceedings of the National Academy of Sciences of the United States of America,
vol. 119, no. 36, e2123152119, National Academy of Sciences, 2022, doi:10.1073/pnas.2123152119.
short: M. Hledik, N.H. Barton, G. Tkačik, Proceedings of the National Academy of
Sciences of the United States of America 119 (2022).
corr_author: '1'
date_created: 2022-09-11T22:01:55Z
date_published: 2022-08-29T00:00:00Z
date_updated: 2026-04-07T12:59:24Z
day: '29'
ddc:
- '570'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1073/pnas.2123152119
ec_funded: 1
external_id:
isi:
- '000889278400014'
pmid:
- '36037343'
file:
- access_level: open_access
checksum: 6dec51f6567da9039982a571508a8e4d
content_type: application/pdf
creator: dernst
date_created: 2022-09-12T08:08:12Z
date_updated: 2022-09-12T08:08:12Z
file_id: '12091'
file_name: 2022_PNAS_Hledik.pdf
file_size: 2165752
relation: main_file
success: 1
file_date_updated: 2022-09-12T08:08:12Z
has_accepted_license: '1'
intvolume: ' 119'
isi: 1
issue: '36'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: 2665AAFE-B435-11E9-9278-68D0E5697425
grant_number: RGP0034/2018
name: Can evolution minimize spurious signaling crosstalk to reach optimal performance?
publication: Proceedings of the National Academy of Sciences of the United States
of America
publication_identifier:
eissn:
- 1091-6490
issn:
- 0027-8424
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
related_material:
record:
- id: '15020'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Accumulation and maintenance of information in 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: 119
year: '2022'
...
---
_id: '12156'
abstract:
- lang: eng
text: Models of transcriptional regulation that assume equilibrium binding of transcription
factors have been less successful at predicting gene expression from sequence
in eukaryotes than in bacteria. This could be due to the non-equilibrium nature
of eukaryotic regulation. Unfortunately, the space of possible non-equilibrium
mechanisms is vast and predominantly uninteresting. The key question is therefore
how this space can be navigated efficiently, to focus on mechanisms and models
that are biologically relevant. In this review, we advocate for the normative
role of theory—theory that prescribes rather than just describes—in providing
such a focus. Theory should expand its remit beyond inferring mechanistic models
from data, towards identifying non-equilibrium gene regulatory schemes that may
have been evolutionarily selected, despite their energy consumption, because they
are precise, reliable, fast, or otherwise outperform regulation at equilibrium.
We illustrate our reasoning by toy examples for which we provide simulation code.
acknowledgement: 'This work was supported through the Center for the Physics of Biological
Function (PHYe1734030) and by National Institutes of Health Grants R01GM097275 and
U01DK127429 (TG). GT acknowledges the support of the Austrian Science Fund grant
FWF P28844 and the Human Frontiers Science Program. '
article_number: '100435'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Benjamin
full_name: Zoller, Benjamin
last_name: Zoller
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: '1'
citation:
ama: Zoller B, Gregor T, Tkačik G. Eukaryotic gene regulation at equilibrium, or
non? Current Opinion in Systems Biology. 2022;31(9). doi:10.1016/j.coisb.2022.100435
apa: Zoller, B., Gregor, T., & Tkačik, G. (2022). Eukaryotic gene regulation
at equilibrium, or non? Current Opinion in Systems Biology. Elsevier. https://doi.org/10.1016/j.coisb.2022.100435
chicago: Zoller, Benjamin, Thomas Gregor, and Gašper Tkačik. “Eukaryotic Gene Regulation
at Equilibrium, or Non?” Current Opinion in Systems Biology. Elsevier,
2022. https://doi.org/10.1016/j.coisb.2022.100435.
ieee: B. Zoller, T. Gregor, and G. Tkačik, “Eukaryotic gene regulation at equilibrium,
or non?,” Current Opinion in Systems Biology, vol. 31, no. 9. Elsevier,
2022.
ista: Zoller B, Gregor T, Tkačik G. 2022. Eukaryotic gene regulation at equilibrium,
or non? Current Opinion in Systems Biology. 31(9), 100435.
mla: Zoller, Benjamin, et al. “Eukaryotic Gene Regulation at Equilibrium, or Non?”
Current Opinion in Systems Biology, vol. 31, no. 9, 100435, Elsevier, 2022,
doi:10.1016/j.coisb.2022.100435.
short: B. Zoller, T. Gregor, G. Tkačik, Current Opinion in Systems Biology 31 (2022).
corr_author: '1'
date_created: 2023-01-12T12:08:51Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2025-06-11T13:47:43Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1016/j.coisb.2022.100435
external_id:
pmid:
- '36590072'
file:
- access_level: open_access
checksum: 97ef01e0cc60cdc84f45640a0f248fb0
content_type: application/pdf
creator: dernst
date_created: 2023-01-24T12:14:10Z
date_updated: 2023-01-24T12:14:10Z
file_id: '12362'
file_name: 2022_CurrentBiology_Zoller.pdf
file_size: 2214944
relation: main_file
success: 1
file_date_updated: 2023-01-24T12:14:10Z
has_accepted_license: '1'
intvolume: ' 31'
issue: '9'
keyword:
- Applied Mathematics
- Computer Science Applications
- Drug Discovery
- General Biochemistry
- Genetics and Molecular Biology
- Modeling and Simulation
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Current Opinion in Systems Biology
publication_identifier:
issn:
- 2452-3100
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Eukaryotic gene regulation at equilibrium, or non?
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: 31
year: '2022'
...
---
_id: '12332'
abstract:
- lang: eng
text: Activity of sensory neurons is driven not only by external stimuli but also
by feedback signals from higher brain areas. Attention is one particularly important
internal signal whose presumed role is to modulate sensory representations such
that they only encode information currently relevant to the organism at minimal
cost. This hypothesis has, however, not yet been expressed in a normative computational
framework. Here, by building on normative principles of probabilistic inference
and efficient coding, we developed a model of dynamic population coding in the
visual cortex. By continuously adapting the sensory code to changing demands of
the perceptual observer, an attention-like modulation emerges. This modulation
can dramatically reduce the amount of neural activity without deteriorating the
accuracy of task-specific inferences. Our results suggest that a range of seemingly
disparate cortical phenomena such as intrinsic gain modulation, attention-related
tuning modulation, and response variability could be manifestations of the same
underlying principles, which combine efficient sensory coding with optimal probabilistic
inference in dynamic environments.
acknowledgement: "We thank Robbe Goris for generously providing figures from his work
and Ann M. Hermundstad for helpful discussions.\r\nGT & WM were supported by the
Austrian Science Fund Standalone Grant P 34015 \"Efficient Coding with Biophysical
Realism\" (https://pf.fwf.ac.at/) WM was additionally supported by the European
Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie
Grant Agreement No. 754411 (https://ec.europa.eu/research/mariecurieactions/). The
funders had no role in study design, data collection and analysis, decision to publish,
or preparation of the manuscript."
article_processing_charge: No
article_type: original
author:
- first_name: Wiktor F
full_name: Mlynarski, Wiktor F
id: 358A453A-F248-11E8-B48F-1D18A9856A87
last_name: Mlynarski
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: '1'
citation:
ama: Mlynarski WF, Tkačik G. Efficient coding theory of dynamic attentional modulation.
PLoS Biology. 2022;20(12):e3001889. doi:10.1371/journal.pbio.3001889
apa: Mlynarski, W. F., & Tkačik, G. (2022). Efficient coding theory of dynamic
attentional modulation. PLoS Biology. Public Library of Science. https://doi.org/10.1371/journal.pbio.3001889
chicago: Mlynarski, Wiktor F, and Gašper Tkačik. “Efficient Coding Theory of Dynamic
Attentional Modulation.” PLoS Biology. Public Library of Science, 2022.
https://doi.org/10.1371/journal.pbio.3001889.
ieee: W. F. Mlynarski and G. Tkačik, “Efficient coding theory of dynamic attentional
modulation,” PLoS Biology, vol. 20, no. 12. Public Library of Science,
p. e3001889, 2022.
ista: Mlynarski WF, Tkačik G. 2022. Efficient coding theory of dynamic attentional
modulation. PLoS Biology. 20(12), e3001889.
mla: Mlynarski, Wiktor F., and Gašper Tkačik. “Efficient Coding Theory of Dynamic
Attentional Modulation.” PLoS Biology, vol. 20, no. 12, Public Library
of Science, 2022, p. e3001889, doi:10.1371/journal.pbio.3001889.
short: W.F. Mlynarski, G. Tkačik, PLoS Biology 20 (2022) e3001889.
corr_author: '1'
date_created: 2023-01-22T23:00:55Z
date_published: 2022-12-21T00:00:00Z
date_updated: 2025-06-11T13:57:01Z
day: '21'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pbio.3001889
ec_funded: 1
external_id:
isi:
- '000925192000001'
pmid:
- '36542662'
file:
- access_level: open_access
checksum: 5d7f1111a87e5f2c1bf92f8886738894
content_type: application/pdf
creator: dernst
date_created: 2023-01-23T08:46:40Z
date_updated: 2023-01-23T08:46:40Z
file_id: '12337'
file_name: 2022_PloSBiology_Mlynarski.pdf
file_size: 4248838
relation: main_file
success: 1
file_date_updated: 2023-01-23T08:46:40Z
has_accepted_license: '1'
intvolume: ' 20'
isi: 1
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: e3001889
pmid: 1
project:
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: PLoS Biology
publication_identifier:
eissn:
- 1545-7885
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Efficient coding theory of dynamic attentional modulation
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: 20
year: '2022'
...
---
_id: '10530'
abstract:
- lang: eng
text: "Cell dispersion from a confined area is fundamental in a number of biological
processes,\r\nincluding cancer metastasis. To date, a quantitative understanding
of the interplay of single\r\ncell motility, cell proliferation, and intercellular
contacts remains elusive. In particular, the role\r\nof E- and N-Cadherin junctions,
central components of intercellular contacts, is still\r\ncontroversial. Combining
theoretical modeling with in vitro observations, we investigate the\r\ncollective
spreading behavior of colonies of human cancer cells (T24). The spreading of these\r\ncolonies
is driven by stochastic single-cell migration with frequent transient cell-cell
contacts.\r\nWe find that inhibition of E- and N-Cadherin junctions decreases
colony spreading and average\r\nspreading velocities, without affecting the strength
of correlations in spreading velocities of\r\nneighboring cells. Based on a biophysical
simulation model for cell migration, we show that the\r\nbehavioral changes upon
disruption of these junctions can be explained by reduced repulsive\r\nexcluded
volume interactions between cells. This suggests that in cancer cell migration,\r\ncadherin-based
intercellular contacts sharpen cell boundaries leading to repulsive rather than\r\ncohesive
interactions between cells, thereby promoting efficient cell spreading during
collective\r\nmigration.\r\n"
acknowledgement: Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research
Foundation) - Project-ID 201269156 - SFB 1032 (Projects B8 and B12). D.B.B. is supported
in part by a DFG fellowship within the Graduate School of Quantitative Biosciences
Munich (QBM) and by the Joachim Herz Stiftung.
article_processing_charge: No
article_type: original
author:
- first_name: Themistoklis
full_name: Zisis, Themistoklis
last_name: Zisis
- first_name: David
full_name: Brückner, David
id: e1e86031-6537-11eb-953a-f7ab92be508d
last_name: Brückner
orcid: 0000-0001-7205-2975
- first_name: Tom
full_name: Brandstätter, Tom
last_name: Brandstätter
- first_name: Wei Xiong
full_name: Siow, Wei Xiong
last_name: Siow
- first_name: Joseph
full_name: d’Alessandro, Joseph
last_name: d’Alessandro
- first_name: Angelika M.
full_name: Vollmar, Angelika M.
last_name: Vollmar
- first_name: Chase P.
full_name: Broedersz, Chase P.
last_name: Broedersz
- first_name: Stefan
full_name: Zahler, Stefan
last_name: Zahler
citation:
ama: Zisis T, Brückner D, Brandstätter T, et al. Disentangling cadherin-mediated
cell-cell interactions in collective cancer cell migration. Biophysical Journal.
2022;121(1):P44-60. doi:10.1016/j.bpj.2021.12.006
apa: Zisis, T., Brückner, D., Brandstätter, T., Siow, W. X., d’Alessandro, J., Vollmar,
A. M., … Zahler, S. (2022). Disentangling cadherin-mediated cell-cell interactions
in collective cancer cell migration. Biophysical Journal. Elsevier. https://doi.org/10.1016/j.bpj.2021.12.006
chicago: Zisis, Themistoklis, David Brückner, Tom Brandstätter, Wei Xiong Siow,
Joseph d’Alessandro, Angelika M. Vollmar, Chase P. Broedersz, and Stefan Zahler.
“Disentangling Cadherin-Mediated Cell-Cell Interactions in Collective Cancer Cell
Migration.” Biophysical Journal. Elsevier, 2022. https://doi.org/10.1016/j.bpj.2021.12.006.
ieee: T. Zisis et al., “Disentangling cadherin-mediated cell-cell interactions
in collective cancer cell migration,” Biophysical Journal, vol. 121, no.
1. Elsevier, pp. P44-60, 2022.
ista: Zisis T, Brückner D, Brandstätter T, Siow WX, d’Alessandro J, Vollmar AM,
Broedersz CP, Zahler S. 2022. Disentangling cadherin-mediated cell-cell interactions
in collective cancer cell migration. Biophysical Journal. 121(1), P44-60.
mla: Zisis, Themistoklis, et al. “Disentangling Cadherin-Mediated Cell-Cell Interactions
in Collective Cancer Cell Migration.” Biophysical Journal, vol. 121, no.
1, Elsevier, 2022, pp. P44-60, doi:10.1016/j.bpj.2021.12.006.
short: T. Zisis, D. Brückner, T. Brandstätter, W.X. Siow, J. d’Alessandro, A.M.
Vollmar, C.P. Broedersz, S. Zahler, Biophysical Journal 121 (2022) P44-60.
date_created: 2021-12-10T09:48:19Z
date_published: 2022-01-04T00:00:00Z
date_updated: 2025-06-11T13:59:29Z
day: '04'
ddc:
- '570'
department:
- _id: EdHa
- _id: GaTk
doi: 10.1016/j.bpj.2021.12.006
external_id:
isi:
- '000740815400007'
pmid:
- '34890578'
file:
- access_level: open_access
checksum: 1aa7c3478e0c8256b973b632efd1f6b4
content_type: application/pdf
creator: dernst
date_created: 2022-07-29T10:17:10Z
date_updated: 2022-07-29T10:17:10Z
file_id: '11697'
file_name: 2022_BiophysicalJour_Zisis.pdf
file_size: 4475504
relation: main_file
success: 1
file_date_updated: 2022-07-29T10:17:10Z
has_accepted_license: '1'
intvolume: ' 121'
isi: 1
issue: '1'
keyword:
- Biophysics
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '01'
oa: 1
oa_version: Published Version
page: P44-60
pmid: 1
project:
- _id: 9B861AAC-BA93-11EA-9121-9846C619BF3A
name: NOMIS Fellowship Program
publication: Biophysical Journal
publication_identifier:
issn:
- 0006-3495
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Disentangling cadherin-mediated cell-cell interactions in collective cancer
cell migration
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 121
year: '2022'
...
---
_id: '10736'
abstract:
- lang: eng
text: Predicting function from sequence is a central problem of biology. Currently,
this is possible only locally in a narrow mutational neighborhood around a wildtype
sequence rather than globally from any sequence. Using random mutant libraries,
we developed a biophysical model that accounts for multiple features of σ70 binding
bacterial promoters to predict constitutive gene expression levels from any sequence.
We experimentally and theoretically estimated that 10–20% of random sequences
lead to expression and ~80% of non-expressing sequences are one mutation away
from a functional promoter. The potential for generating expression from random
sequences is so pervasive that selection acts against σ70-RNA polymerase binding
sites even within inter-genic, promoter-containing regions. This pervasiveness
of σ70-binding sites implies that emergence of promoters is not the limiting step
in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter
function into a mechanistic model enabled not only more accurate predictions of
gene expression levels, but also identified that promoters evolve more rapidly
than previously thought.
acknowledgement: 'We thank Hande Acar, Nicholas H Barton, Rok Grah, Tiago Paixao,
Maros Pleska, Anna Staron, and Murat Tugrul for insightful comments and input on
the manuscript. This work was supported by: Sir Henry Dale Fellowship jointly funded
by the Wellcome Trust and the Royal Society (grant number 216779/Z/19/Z) to ML;
IPC Grant from IST Austria to ML and SS; European Research Council Funding Programme
7 (2007–2013, grant agreement number 648440) to JPB.'
article_number: e64543
article_processing_charge: No
article_type: original
author:
- first_name: Mato
full_name: Lagator, Mato
id: 345D25EC-F248-11E8-B48F-1D18A9856A87
last_name: Lagator
- first_name: Srdjan
full_name: Sarikas, Srdjan
id: 35F0286E-F248-11E8-B48F-1D18A9856A87
last_name: Sarikas
- first_name: Magdalena
full_name: Steinrück, Magdalena
id: 2C023F40-F248-11E8-B48F-1D18A9856A87
last_name: Steinrück
orcid: 0000-0003-1229-9719
- first_name: David
full_name: Toledo-Aparicio, David
last_name: Toledo-Aparicio
- first_name: Jonathan P
full_name: Bollback, Jonathan P
id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
last_name: Bollback
orcid: 0000-0002-4624-4612
- 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: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Lagator M, Sarikas S, Steinrück M, et al. Predicting bacterial promoter function
and evolution from random sequences. eLife. 2022;11. doi:10.7554/eLife.64543
apa: Lagator, M., Sarikas, S., Steinrück, M., Toledo-Aparicio, D., Bollback, J.
P., Guet, C. C., & Tkačik, G. (2022). Predicting bacterial promoter function
and evolution from random sequences. ELife. eLife Sciences Publications.
https://doi.org/10.7554/eLife.64543
chicago: Lagator, Mato, Srdjan Sarikas, Magdalena Steinrück, David Toledo-Aparicio,
Jonathan P Bollback, Calin C Guet, and Gašper Tkačik. “Predicting Bacterial Promoter
Function and Evolution from Random Sequences.” ELife. eLife Sciences Publications,
2022. https://doi.org/10.7554/eLife.64543.
ieee: M. Lagator et al., “Predicting bacterial promoter function and evolution
from random sequences,” eLife, vol. 11. eLife Sciences Publications, 2022.
ista: Lagator M, Sarikas S, Steinrück M, Toledo-Aparicio D, Bollback JP, Guet CC,
Tkačik G. 2022. Predicting bacterial promoter function and evolution from random
sequences. eLife. 11, e64543.
mla: Lagator, Mato, et al. “Predicting Bacterial Promoter Function and Evolution
from Random Sequences.” ELife, vol. 11, e64543, eLife Sciences Publications,
2022, doi:10.7554/eLife.64543.
short: M. Lagator, S. Sarikas, M. Steinrück, D. Toledo-Aparicio, J.P. Bollback,
C.C. Guet, G. Tkačik, ELife 11 (2022).
corr_author: '1'
date_created: 2022-02-06T23:01:32Z
date_published: 2022-01-26T00:00:00Z
date_updated: 2025-03-31T16:00:23Z
day: '26'
ddc:
- '576'
department:
- _id: CaGu
- _id: GaTk
- _id: NiBa
doi: 10.7554/eLife.64543
ec_funded: 1
external_id:
isi:
- '000751104400001'
pmid:
- '35080492'
file:
- access_level: open_access
checksum: decdcdf600ff51e9a9703b49ca114170
content_type: application/pdf
creator: cchlebak
date_created: 2022-02-07T07:14:09Z
date_updated: 2022-02-07T07:14:09Z
file_id: '10739'
file_name: 2022_ELife_Lagator.pdf
file_size: 5604343
relation: main_file
success: 1
file_date_updated: 2022-02-07T07:14:09Z
has_accepted_license: '1'
intvolume: ' 11'
isi: 1
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 2578D616-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '648440'
name: Selective Barriers to Horizontal Gene Transfer
publication: eLife
publication_identifier:
eissn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
scopus_import: '1'
status: public
title: Predicting bacterial promoter function and evolution from random sequences
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: '2022'
...
---
OA_place: repository
_id: '10821'
abstract:
- lang: eng
text: 'Rhythmical cortical activity has long been recognized as a pillar in the
architecture of brain functions. Yet, the dynamic organization of its underlying
neuronal population activity remains elusive. Here we uncover a unique organizational
principle regulating collective neural dynamics associated with the alpha rhythm
in the awake resting-state. We demonstrate that cascades of neural activity obey
attenuation-amplification dynamics (AAD), with a transition from the attenuation
regime—within alpha cycles—to the amplification regime—across a few alpha cycles—that
correlates with the characteristic frequency of the alpha rhythm. We find that
this short-term AAD is part of a large-scale, size-dependent temporal structure
of neural cascades that obeys the Omori law: Following large cascades, smaller
cascades occur at a rate that decays as a power-law of the time elapsed from such
events—a long-term AAD regulating brain activity over the timescale of seconds.
We show that such an organization corresponds to the "waxing and waning" of the
alpha rhythm. Importantly, we observe that short- and long-term AAD are unique
to the awake resting-state, being absent during NREM sleep. These results provide
a quantitative, dynamical description of the so-far-qualitative notion of the
"waxing and waning" phenomenon, and suggest the AAD as a key principle governing
resting-state dynamics across timescales.'
acknowledgement: FL acknowledges support from the European Union’s Horizon 2020 research
and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.
LdA acknowledges the Italian MIUR project PRIN2017WZFTZP for financial support and
the project E-PASSION of the program VALERE 2019 funded by the University of Campania,
Italy “L. Vanvitelli”. OS acknowledges support from the Israel Science Foundation,
Grant No. 504/17. Supported in part by DIRP ZIAMH02797 to DP.
article_processing_charge: No
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Hans J.
full_name: Herrmann, Hans J.
last_name: Herrmann
- first_name: Liborio
full_name: Parrino, Liborio
last_name: Parrino
- first_name: Dietmar
full_name: Plenz, Dietmar
last_name: Plenz
- first_name: Silvia
full_name: Scarpetta, Silvia
last_name: Scarpetta
- first_name: Anna Elisabetta
full_name: Vaudano, Anna Elisabetta
last_name: Vaudano
- first_name: Lucilla
full_name: de Arcangelis, Lucilla
last_name: de Arcangelis
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
citation:
ama: Lombardi F, Herrmann HJ, Parrino L, et al. Alpha rhythm induces attenuation-amplification
dynamics in neural activity cascades. bioRxiv. doi:10.1101/2022.03.03.482657
apa: Lombardi, F., Herrmann, H. J., Parrino, L., Plenz, D., Scarpetta, S., Vaudano,
A. E., … Shriki, O. (n.d.). Alpha rhythm induces attenuation-amplification dynamics
in neural activity cascades. bioRxiv. https://doi.org/10.1101/2022.03.03.482657
chicago: Lombardi, Fabrizio, Hans J. Herrmann, Liborio Parrino, Dietmar Plenz, Silvia
Scarpetta, Anna Elisabetta Vaudano, Lucilla de Arcangelis, and Oren Shriki. “Alpha
Rhythm Induces Attenuation-Amplification Dynamics in Neural Activity Cascades.”
BioRxiv, n.d. https://doi.org/10.1101/2022.03.03.482657.
ieee: F. Lombardi et al., “Alpha rhythm induces attenuation-amplification
dynamics in neural activity cascades,” bioRxiv. .
ista: Lombardi F, Herrmann HJ, Parrino L, Plenz D, Scarpetta S, Vaudano AE, de Arcangelis
L, Shriki O. Alpha rhythm induces attenuation-amplification dynamics in neural
activity cascades. bioRxiv, 10.1101/2022.03.03.482657.
mla: Lombardi, Fabrizio, et al. “Alpha Rhythm Induces Attenuation-Amplification
Dynamics in Neural Activity Cascades.” BioRxiv, doi:10.1101/2022.03.03.482657.
short: F. Lombardi, H.J. Herrmann, L. Parrino, D. Plenz, S. Scarpetta, A.E. Vaudano,
L. de Arcangelis, O. Shriki, BioRxiv (n.d.).
corr_author: '1'
das_tickbox: '1'
date_created: 2022-03-04T22:20:59Z
date_published: 2022-03-04T00:00:00Z
date_updated: 2026-07-06T12:48:55Z
day: '04'
department:
- _id: GaTk
doi: 10.1101/2022.03.03.482657
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2022.03.03.482657
month: '03'
oa: 1
oa_version: Preprint
page: '25'
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: bioRxiv
publication_status: draft
related_material:
record:
- id: '14402'
relation: later_version
status: public
status: public
title: Alpha rhythm induces attenuation-amplification dynamics in neural activity
cascades
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '10535'
abstract:
- lang: eng
text: Realistic models of biological processes typically involve interacting components
on multiple scales, driven by changing environment and inherent stochasticity.
Such models are often analytically and numerically intractable. We revisit a dynamic
maximum entropy method that combines a static maximum entropy with a quasi-stationary
approximation. This allows us to reduce stochastic non-equilibrium dynamics expressed
by the Fokker-Planck equation to a simpler low-dimensional deterministic dynamics,
without the need to track microscopic details. Although the method has been previously
applied to a few (rather complicated) applications in population genetics, our
main goal here is to explain and to better understand how the method works. We
demonstrate the usefulness of the method for two widely studied stochastic problems,
highlighting its accuracy in capturing important macroscopic quantities even in
rapidly changing non-stationary conditions. For the Ornstein-Uhlenbeck process,
the method recovers the exact dynamics whilst for a stochastic island model with
migration from other habitats, the approximation retains high macroscopic accuracy
under a wide range of scenarios in a dynamic environment.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "Computational resources for the study were provided by the Institute
of Science and Technology, Austria.\r\nKB received funding from the Scientific Grant
Agency of the Slovak Republic under the Grants Nos. 1/0755/19 and 1/0521/20."
article_number: e1009661
article_processing_charge: No
article_type: original
arxiv: 1
author:
- 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: Eniko
full_name: Szep, Eniko
id: 485BB5A4-F248-11E8-B48F-1D18A9856A87
last_name: Szep
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Bodova K, Szep E, Barton NH. Dynamic maximum entropy provides accurate approximation
of structured population dynamics. PLoS Computational Biology. 2021;17(12).
doi:10.1371/journal.pcbi.1009661
apa: Bodova, K., Szep, E., & Barton, N. H. (2021). Dynamic maximum entropy provides
accurate approximation of structured population dynamics. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1009661
chicago: Bodova, Katarina, Eniko Szep, and Nicholas H Barton. “Dynamic Maximum Entropy
Provides Accurate Approximation of Structured Population Dynamics.” PLoS Computational
Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1009661.
ieee: K. Bodova, E. Szep, and N. H. Barton, “Dynamic maximum entropy provides accurate
approximation of structured population dynamics,” PLoS Computational Biology,
vol. 17, no. 12. Public Library of Science, 2021.
ista: Bodova K, Szep E, Barton NH. 2021. Dynamic maximum entropy provides accurate
approximation of structured population dynamics. PLoS Computational Biology. 17(12),
e1009661.
mla: Bodova, Katarina, et al. “Dynamic Maximum Entropy Provides Accurate Approximation
of Structured Population Dynamics.” PLoS Computational Biology, vol. 17,
no. 12, e1009661, Public Library of Science, 2021, doi:10.1371/journal.pcbi.1009661.
short: K. Bodova, E. Szep, N.H. Barton, PLoS Computational Biology 17 (2021).
corr_author: '1'
date_created: 2021-12-12T23:01:27Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2024-10-09T21:01:16Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1371/journal.pcbi.1009661
external_id:
arxiv:
- '2102.03669'
pmid:
- '34851948'
file:
- access_level: open_access
checksum: dcd185d4f7e0acee25edf1d6537f447e
content_type: application/pdf
creator: dernst
date_created: 2022-05-16T08:53:11Z
date_updated: 2022-05-16T08:53:11Z
file_id: '11383'
file_name: 2021_PLOsComBio_Bodova.pdf
file_size: 2299486
relation: main_file
success: 1
file_date_updated: 2022-05-16T08:53:11Z
has_accepted_license: '1'
intvolume: ' 17'
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS Computational Biology
publication_identifier:
eissn:
- 1553-7358
issn:
- 1553-734X
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Dynamic maximum entropy provides accurate approximation of structured population
dynamics
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: '2021'
...
---
_id: '9226'
abstract:
- lang: eng
text: 'Half a century after Lewis Wolpert''s seminal conceptual advance on how cellular
fates distribute in space, we provide a brief historical perspective on how the
concept of positional information emerged and influenced the field of developmental
biology and beyond. We focus on a modern interpretation of this concept in terms
of information theory, largely centered on its application to cell specification
in the early Drosophila embryo. We argue that a true physical variable (position)
is encoded in local concentrations of patterning molecules, that this mapping
is stochastic, and that the processes by which positions and corresponding cell
fates are determined based on these concentrations need to take such stochasticity
into account. With this approach, we shift the focus from biological mechanisms,
molecules, genes and pathways to quantitative systems-level questions: where does
positional information reside, how it is transformed and accessed during development,
and what fundamental limits it is subject to?'
acknowledgement: This work was supported in part by the National Science Foundation,
through the Center for the Physics of Biological Function (PHY-1734030), by the
National Institutes of Health (R01GM097275) and by the Fonds zur Förderung der wissenschaftlichen
Forschung (FWF P28844). Deposited in PMC for release after 12 months.
article_number: dev176065
article_processing_charge: No
article_type: original
author:
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
citation:
ama: Tkačik G, Gregor T. The many bits of positional information. Development.
2021;148(2). doi:10.1242/dev.176065
apa: Tkačik, G., & Gregor, T. (2021). The many bits of positional information.
Development. The Company of Biologists. https://doi.org/10.1242/dev.176065
chicago: Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.”
Development. The Company of Biologists, 2021. https://doi.org/10.1242/dev.176065.
ieee: G. Tkačik and T. Gregor, “The many bits of positional information,” Development,
vol. 148, no. 2. The Company of Biologists, 2021.
ista: Tkačik G, Gregor T. 2021. The many bits of positional information. Development.
148(2), dev176065.
mla: Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.”
Development, vol. 148, no. 2, dev176065, The Company of Biologists, 2021,
doi:10.1242/dev.176065.
short: G. Tkačik, T. Gregor, Development 148 (2021).
date_created: 2021-03-07T23:01:25Z
date_published: 2021-02-01T00:00:00Z
date_updated: 2026-06-18T19:42:53Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1242/dev.176065
external_id:
isi:
- '000613906000007'
pmid:
- '33526425'
intvolume: ' 148'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1242/dev.176065
month: '02'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Development
publication_identifier:
eissn:
- 1477-9129
publication_status: published
publisher: The Company of Biologists
quality_controlled: '1'
scopus_import: '1'
status: public
title: The many bits of positional information
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 148
year: '2021'
...
---
_id: '9283'
abstract:
- lang: eng
text: Gene expression levels are influenced by multiple coexisting molecular mechanisms.
Some of these interactions such as those of transcription factors and promoters
have been studied extensively. However, predicting phenotypes of gene regulatory
networks (GRNs) remains a major challenge. Here, we use a well-defined synthetic
GRN to study in Escherichia coli how network phenotypes depend on local genetic
context, i.e. the genetic neighborhood of a transcription factor and its relative
position. We show that one GRN with fixed topology can display not only quantitatively
but also qualitatively different phenotypes, depending solely on the local genetic
context of its components. Transcriptional read-through is the main molecular
mechanism that places one transcriptional unit (TU) within two separate regulons
without the need for complex regulatory sequences. We propose that relative order
of individual TUs, with its potential for combinatorial complexity, plays an important
role in shaping phenotypes of GRNs.
acknowledgement: "We thank J Bollback, L Hurst, M Lagator, C Nizak, O Rivoire, M Savageau,
G Tkacik, and B Vicozo\r\nfor helpful discussions; A Dolinar and A Greshnova for
technical assistance; T Bollenbach for supplying the strain JW0336; C Rusnac, and
members of the Guet lab for comments. The 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 n˚\r\n628377
(ANS) and an Austrian Science Fund (FWF) grant n˚ I 3901-B32 (CCG)."
article_number: e65993
article_processing_charge: Yes
article_type: original
author:
- first_name: Anna A
full_name: Nagy-Staron, Anna A
id: 3ABC5BA6-F248-11E8-B48F-1D18A9856A87
last_name: Nagy-Staron
orcid: 0000-0002-1391-8377
- first_name: Kathrin
full_name: Tomasek, Kathrin
id: 3AEC8556-F248-11E8-B48F-1D18A9856A87
last_name: Tomasek
orcid: 0000-0003-3768-877X
- first_name: Caroline
full_name: Caruso Carter, Caroline
last_name: Caruso Carter
- first_name: Elisabeth
full_name: Sonnleitner, Elisabeth
last_name: Sonnleitner
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
- first_name: Tiago
full_name: Paixão, Tiago
last_name: Paixão
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Nagy-Staron AA, Tomasek K, Caruso Carter C, et al. Local genetic context shapes
the function of a gene regulatory network. eLife. 2021;10. doi:10.7554/elife.65993
apa: Nagy-Staron, A. A., Tomasek, K., Caruso Carter, C., Sonnleitner, E., Kavcic,
B., Paixão, T., & Guet, C. C. (2021). Local genetic context shapes the function
of a gene regulatory network. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.65993
chicago: Nagy-Staron, Anna A, Kathrin Tomasek, Caroline Caruso Carter, Elisabeth
Sonnleitner, Bor Kavcic, Tiago Paixão, and Calin C Guet. “Local Genetic Context
Shapes the Function of a Gene Regulatory Network.” ELife. eLife Sciences
Publications, 2021. https://doi.org/10.7554/elife.65993.
ieee: A. A. Nagy-Staron et al., “Local genetic context shapes the function
of a gene regulatory network,” eLife, vol. 10. eLife Sciences Publications,
2021.
ista: Nagy-Staron AA, Tomasek K, Caruso Carter C, Sonnleitner E, Kavcic B, Paixão
T, Guet CC. 2021. Local genetic context shapes the function of a gene regulatory
network. eLife. 10, e65993.
mla: Nagy-Staron, Anna A., et al. “Local Genetic Context Shapes the Function of
a Gene Regulatory Network.” ELife, vol. 10, e65993, eLife Sciences Publications,
2021, doi:10.7554/elife.65993.
short: A.A. Nagy-Staron, K. Tomasek, C. Caruso Carter, E. Sonnleitner, B. Kavcic,
T. Paixão, C.C. Guet, ELife 10 (2021).
corr_author: '1'
date_created: 2021-03-23T10:11:46Z
date_published: 2021-03-08T00:00:00Z
date_updated: 2025-06-12T06:36:17Z
day: '08'
ddc:
- '570'
department:
- _id: GaTk
- _id: CaGu
doi: 10.7554/elife.65993
ec_funded: 1
external_id:
isi:
- '000631050900001'
pmid:
- '33683203'
file:
- access_level: open_access
checksum: 3c2f44058c2dd45a5a1027f09d263f8e
content_type: application/pdf
creator: bkavcic
date_created: 2021-03-23T10:12:58Z
date_updated: 2021-03-23T10:12:58Z
file_id: '9284'
file_name: elife-65993-v2.pdf
file_size: 1390469
relation: main_file
success: 1
file_date_updated: 2021-03-23T10:12:58Z
has_accepted_license: '1'
intvolume: ' 10'
isi: 1
keyword:
- Genetics and Molecular Biology
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 2517526A-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '628377'
name: 'The Systems Biology of Transcriptional Read-Through in Bacteria: from Synthetic
Networks to Genomic Studies'
- _id: 268BFA92-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I03901
name: Cybergenetic circuits to test composability of gene networks
publication: eLife
publication_identifier:
issn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
related_material:
record:
- id: '8951'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Local genetic context shapes the function of a gene regulatory network
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: 10
year: '2021'
...
---
_id: '9362'
abstract:
- lang: eng
text: A central goal in systems neuroscience is to understand the functions performed
by neural circuits. Previous top-down models addressed this question by comparing
the behaviour of an ideal model circuit, optimised to perform a given function,
with neural recordings. However, this requires guessing in advance what function
is being performed, which may not be possible for many neural systems. To address
this, we propose an inverse reinforcement learning (RL) framework for inferring
the function performed by a neural network from data. We assume that the responses
of each neuron in a network are optimised so as to drive the network towards ‘rewarded’
states, that are desirable for performing a given function. We then show how one
can use inverse RL to infer the reward function optimised by the network from
observing its responses. This inferred reward function can be used to predict
how the neural network should adapt its dynamics to perform the same function
when the external environment or network structure changes. This could lead to
theoretical predictions about how neural network dynamics adapt to deal with cell
death and/or varying sensory stimulus statistics.
acknowledgement: The authors would like to thank Ulisse Ferrari for useful discussions
and feedback.
article_number: e0248940
article_processing_charge: No
article_type: original
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
citation:
ama: Chalk MJ, Tkačik G, Marre O. Inferring the function performed by a recurrent
neural network. PLoS ONE. 2021;16(4). doi:10.1371/journal.pone.0248940
apa: Chalk, M. J., Tkačik, G., & Marre, O. (2021). Inferring the function performed
by a recurrent neural network. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0248940
chicago: Chalk, Matthew J, Gašper Tkačik, and Olivier Marre. “Inferring the Function
Performed by a Recurrent Neural Network.” PLoS ONE. Public Library of Science,
2021. https://doi.org/10.1371/journal.pone.0248940.
ieee: M. J. Chalk, G. Tkačik, and O. Marre, “Inferring the function performed by
a recurrent neural network,” PLoS ONE, vol. 16, no. 4. Public Library of
Science, 2021.
ista: Chalk MJ, Tkačik G, Marre O. 2021. Inferring the function performed by a recurrent
neural network. PLoS ONE. 16(4), e0248940.
mla: Chalk, Matthew J., et al. “Inferring the Function Performed by a Recurrent
Neural Network.” PLoS ONE, vol. 16, no. 4, e0248940, Public Library of
Science, 2021, doi:10.1371/journal.pone.0248940.
short: M.J. Chalk, G. Tkačik, O. Marre, PLoS ONE 16 (2021).
date_created: 2021-05-02T22:01:28Z
date_published: 2021-04-15T00:00:00Z
date_updated: 2026-04-02T13:58:56Z
day: '15'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0248940
external_id:
isi:
- '000641474900072'
pmid:
- '33857170'
file:
- access_level: open_access
checksum: c52da133850307d2031f552d998f00e8
content_type: application/pdf
creator: kschuh
date_created: 2021-05-04T13:22:19Z
date_updated: 2021-05-04T13:22:19Z
file_id: '9371'
file_name: 2021_pone_Chalk.pdf
file_size: 2768282
relation: main_file
success: 1
file_date_updated: 2021-05-04T13:22:19Z
has_accepted_license: '1'
intvolume: ' 16'
isi: 1
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS ONE
publication_identifier:
eissn:
- 1932-6203
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Inferring the function performed by a recurrent neural network
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: ba8df636-2132-11f1-aed0-ed93e2281fdd
volume: 16
year: '2021'
...
---
_id: '9439'
abstract:
- lang: eng
text: The ability to adapt to changes in stimulus statistics is a hallmark of sensory
systems. Here, we developed a theoretical framework that can account for the dynamics
of adaptation from an information processing perspective. We use this framework
to optimize and analyze adaptive sensory codes, and we show that codes optimized
for stationary environments can suffer from prolonged periods of poor performance
when the environment changes. To mitigate the adversarial effects of these environmental
changes, sensory systems must navigate tradeoffs between the ability to accurately
encode incoming stimuli and the ability to rapidly detect and adapt to changes
in the distribution of these stimuli. We derive families of codes that balance
these objectives, and we demonstrate their close match to experimentally observed
neural dynamics during mean and variance adaptation. Our results provide a unifying
perspective on adaptation across a range of sensory systems, environments, and
sensory tasks.
acknowledgement: We thank D. Kastner and T. Münch for generously providing figures
from their work. We also thank V. Jayaraman, M. Noorman, T. Ma, and K. Krishnamurthy
for useful discussions and feedback on the manuscript. W.F.M. was funded by the
European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie
Grant Agreement No. 754411. A.M.H. was supported by the Howard Hughes Medical Institute.
article_processing_charge: No
article_type: original
author:
- first_name: Wiktor F
full_name: Mlynarski, Wiktor F
id: 358A453A-F248-11E8-B48F-1D18A9856A87
last_name: Mlynarski
- first_name: Ann M.
full_name: Hermundstad, Ann M.
last_name: Hermundstad
citation:
ama: Mlynarski WF, Hermundstad AM. Efficient and adaptive sensory codes. Nature
Neuroscience. 2021;24:998-1009. doi:10.1038/s41593-021-00846-0
apa: Mlynarski, W. F., & Hermundstad, A. M. (2021). Efficient and adaptive sensory
codes. Nature Neuroscience. Springer Nature. https://doi.org/10.1038/s41593-021-00846-0
chicago: Mlynarski, Wiktor F, and Ann M. Hermundstad. “Efficient and Adaptive Sensory
Codes.” Nature Neuroscience. Springer Nature, 2021. https://doi.org/10.1038/s41593-021-00846-0.
ieee: W. F. Mlynarski and A. M. Hermundstad, “Efficient and adaptive sensory codes,”
Nature Neuroscience, vol. 24. Springer Nature, pp. 998–1009, 2021.
ista: Mlynarski WF, Hermundstad AM. 2021. Efficient and adaptive sensory codes.
Nature Neuroscience. 24, 998–1009.
mla: Mlynarski, Wiktor F., and Ann M. Hermundstad. “Efficient and Adaptive Sensory
Codes.” Nature Neuroscience, vol. 24, Springer Nature, 2021, pp. 998–1009,
doi:10.1038/s41593-021-00846-0.
short: W.F. Mlynarski, A.M. Hermundstad, Nature Neuroscience 24 (2021) 998–1009.
date_created: 2021-05-30T22:01:24Z
date_published: 2021-05-20T00:00:00Z
date_updated: 2025-06-12T06:41:38Z
day: '20'
department:
- _id: GaTk
doi: 10.1038/s41593-021-00846-0
ec_funded: 1
external_id:
isi:
- '000652577300003'
pmid:
- '34017131'
intvolume: ' 24'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'https://doi.org/10.1101/669200 '
month: '05'
oa: 1
oa_version: Preprint
page: 998-1009
pmid: 1
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Nature Neuroscience
publication_identifier:
eissn:
- 1546-1726
issn:
- 1097-6256
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Efficient and adaptive sensory codes
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 24
year: '2021'
...
---
_id: '9822'
abstract:
- lang: eng
text: Attachment of adhesive molecules on cell culture surfaces to restrict cell
adhesion to defined areas and shapes has been vital for the progress of in vitro
research. In currently existing patterning methods, a combination of pattern properties
such as stability, precision, specificity, high-throughput outcome, and spatiotemporal
control is highly desirable but challenging to achieve. Here, we introduce a versatile
and high-throughput covalent photoimmobilization technique, comprising a light-dose-dependent
patterning step and a subsequent functionalization of the pattern via click chemistry.
This two-step process is feasible on arbitrary surfaces and allows for generation
of sustainable patterns and gradients. The method is validated in different biological
systems by patterning adhesive ligands on cell-repellent surfaces, thereby constraining
the growth and migration of cells to the designated areas. We then implement a
sequential photopatterning approach by adding a second switchable patterning step,
allowing for spatiotemporal control over two distinct surface patterns. As a proof
of concept, we reconstruct the dynamics of the tip/stalk cell switch during angiogenesis.
Our results show that the spatiotemporal control provided by our “sequential photopatterning”
system is essential for mimicking dynamic biological processes and that our innovative
approach has great potential for further applications in cell science.
acknowledgement: We would like to thank Charlott Leu for the production of our chromium
wafers, Louise Ritter for her contribution of the IF stainings in Figure 4, Shokoufeh
Teymouri for her help with the Bioinert coated slides, and finally Prof. Dr. Joachim
Rädler for his valuable scientific guidance.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Themistoklis
full_name: Zisis, Themistoklis
last_name: Zisis
- first_name: Jan
full_name: Schwarz, Jan
id: 346C1EC6-F248-11E8-B48F-1D18A9856A87
last_name: Schwarz
- first_name: Miriam
full_name: Balles, Miriam
last_name: Balles
- first_name: Maibritt
full_name: Kretschmer, Maibritt
last_name: Kretschmer
- first_name: Maria
full_name: Nemethova, Maria
id: 34E27F1C-F248-11E8-B48F-1D18A9856A87
last_name: Nemethova
- 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: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Janina
full_name: Lange, Janina
last_name: Lange
- 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: Michael K
full_name: Sixt, Michael K
id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
last_name: Sixt
orcid: 0000-0002-4561-241X
- first_name: Stefan
full_name: Zahler, Stefan
last_name: Zahler
citation:
ama: Zisis T, Schwarz J, Balles M, et al. Sequential and switchable patterning for
studying cellular processes under spatiotemporal control. ACS Applied Materials
and Interfaces. 2021;13(30):35545–35560. doi:10.1021/acsami.1c09850
apa: Zisis, T., Schwarz, J., Balles, M., Kretschmer, M., Nemethova, M., Chait, R.
P., … Zahler, S. (2021). Sequential and switchable patterning for studying cellular
processes under spatiotemporal control. ACS Applied Materials and Interfaces.
American Chemical Society. https://doi.org/10.1021/acsami.1c09850
chicago: Zisis, Themistoklis, Jan Schwarz, Miriam Balles, Maibritt Kretschmer, Maria
Nemethova, Remy P Chait, Robert Hauschild, et al. “Sequential and Switchable Patterning
for Studying Cellular Processes under Spatiotemporal Control.” ACS Applied
Materials and Interfaces. American Chemical Society, 2021. https://doi.org/10.1021/acsami.1c09850.
ieee: T. Zisis et al., “Sequential and switchable patterning for studying
cellular processes under spatiotemporal control,” ACS Applied Materials and
Interfaces, vol. 13, no. 30. American Chemical Society, pp. 35545–35560, 2021.
ista: Zisis T, Schwarz J, Balles M, Kretschmer M, Nemethova M, Chait RP, Hauschild
R, Lange J, Guet CC, Sixt MK, Zahler S. 2021. Sequential and switchable patterning
for studying cellular processes under spatiotemporal control. ACS Applied Materials
and Interfaces. 13(30), 35545–35560.
mla: Zisis, Themistoklis, et al. “Sequential and Switchable Patterning for Studying
Cellular Processes under Spatiotemporal Control.” ACS Applied Materials and
Interfaces, vol. 13, no. 30, American Chemical Society, 2021, pp. 35545–35560,
doi:10.1021/acsami.1c09850.
short: T. Zisis, J. Schwarz, M. Balles, M. Kretschmer, M. Nemethova, R.P. Chait,
R. Hauschild, J. Lange, C.C. Guet, M.K. Sixt, S. Zahler, ACS Applied Materials
and Interfaces 13 (2021) 35545–35560.
corr_author: '1'
date_created: 2021-08-08T22:01:28Z
date_published: 2021-08-04T00:00:00Z
date_updated: 2025-07-10T12:02:02Z
day: '04'
ddc:
- '620'
- '570'
department:
- _id: MiSi
- _id: GaTk
- _id: Bio
- _id: CaGu
doi: 10.1021/acsami.1c09850
ec_funded: 1
external_id:
isi:
- '000683741400026'
pmid:
- '34283577'
file:
- access_level: open_access
checksum: b043a91d9f9200e467b970b692687ed3
content_type: application/pdf
creator: asandaue
date_created: 2021-08-09T09:44:03Z
date_updated: 2021-08-09T09:44:03Z
file_id: '9833'
file_name: 2021_ACSAppliedMaterialsAndInterfaces_Zisis.pdf
file_size: 7123293
relation: main_file
success: 1
file_date_updated: 2021-08-09T09:44:03Z
has_accepted_license: '1'
intvolume: ' 13'
isi: 1
issue: '30'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 35545–35560
pmid: 1
project:
- _id: 25FE9508-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '724373'
name: Cellular Navigation Along Spatial Gradients
publication: ACS Applied Materials and Interfaces
publication_identifier:
eissn:
- 1944-8252
issn:
- 1944-8244
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Sequential and switchable patterning for studying cellular processes under
spatiotemporal control
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2021'
...
---
_id: '9828'
abstract:
- lang: eng
text: Amplitude demodulation is a classical operation used in signal processing.
For a long time, its effective applications in practice have been limited to narrowband
signals. In this work, we generalize amplitude demodulation to wideband signals.
We pose demodulation as a recovery problem of an oversampled corrupted signal
and introduce special iterative schemes belonging to the family of alternating
projection algorithms to solve it. Sensibly chosen structural assumptions on the
demodulation outputs allow us to reveal the high inferential accuracy of the method
over a rich set of relevant signals. This new approach surpasses current state-of-the-art
demodulation techniques apt to wideband signals in computational efficiency by
up to many orders of magnitude with no sacrifice in quality. Such performance
opens the door for applications of the amplitude demodulation procedure in new
contexts. In particular, the new method makes online and large-scale offline data
processing feasible, including the calculation of modulator-carrier pairs in higher
dimensions and poor sampling conditions, independent of the signal bandwidth.
We illustrate the utility and specifics of applications of the new method in practice
by using natural speech and synthetic signals.
acknowledgement: The author thanks his colleagues K. Huszár and G. Tkačik for valuable
discussions and comments on the manuscript.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Mantas
full_name: Gabrielaitis, Mantas
id: 4D5B0CBC-F248-11E8-B48F-1D18A9856A87
last_name: Gabrielaitis
orcid: 0000-0002-7758-2016
citation:
ama: Gabrielaitis M. Fast and accurate amplitude demodulation of wideband signals.
IEEE Transactions on Signal Processing. 2021;69:4039-4054. doi:10.1109/TSP.2021.3087899
apa: Gabrielaitis, M. (2021). Fast and accurate amplitude demodulation of wideband
signals. IEEE Transactions on Signal Processing. Institute of Electrical
and Electronics Engineers. https://doi.org/10.1109/TSP.2021.3087899
chicago: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband
Signals.” IEEE Transactions on Signal Processing. Institute of Electrical
and Electronics Engineers, 2021. https://doi.org/10.1109/TSP.2021.3087899.
ieee: M. Gabrielaitis, “Fast and accurate amplitude demodulation of wideband signals,”
IEEE Transactions on Signal Processing, vol. 69. Institute of Electrical
and Electronics Engineers, pp. 4039–4054, 2021.
ista: Gabrielaitis M. 2021. Fast and accurate amplitude demodulation of wideband
signals. IEEE Transactions on Signal Processing. 69, 4039–4054.
mla: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband
Signals.” IEEE Transactions on Signal Processing, vol. 69, Institute of
Electrical and Electronics Engineers, 2021, pp. 4039–54, doi:10.1109/TSP.2021.3087899.
short: M. Gabrielaitis, IEEE Transactions on Signal Processing 69 (2021) 4039–4054.
corr_author: '1'
date_created: 2021-08-08T22:01:31Z
date_published: 2021-06-09T00:00:00Z
date_updated: 2024-10-09T21:00:43Z
day: '09'
department:
- _id: GaTk
doi: 10.1109/TSP.2021.3087899
external_id:
arxiv:
- '2102.04832'
isi:
- '000682123900002'
intvolume: ' 69'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2102.04832
month: '06'
oa: 1
oa_version: Preprint
page: 4039 - 4054
publication: IEEE Transactions on Signal Processing
publication_identifier:
eissn:
- 1941-0476
issn:
- 1053-587X
publication_status: published
publisher: Institute of Electrical and Electronics Engineers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Fast and accurate amplitude demodulation of wideband signals
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 69
year: '2021'
...
---
_id: '7463'
abstract:
- lang: eng
text: Resting-state brain activity is characterized by the presence of neuronal
avalanches showing absence of characteristic size. Such evidence has been interpreted
in the context of criticality and associated with the normal functioning of the
brain. A distinctive attribute of systems at criticality is the presence of long-range
correlations. Thus, to verify the hypothesis that the brain operates close to
a critical point and consequently assess deviations from criticality for diagnostic
purposes, it is of primary importance to robustly and reliably characterize correlations
in resting-state brain activity. Recent works focused on the analysis of narrow-band
electroencephalography (EEG) and magnetoencephalography (MEG) signal amplitude
envelope, showing evidence of long-range temporal correlations (LRTC) in neural
oscillations. However, brain activity is a broadband phenomenon, and a significant
piece of information useful to precisely discriminate between normal (critical)
and pathological behavior (non-critical), may be encoded in the broadband spatio-temporal
cortical dynamics. Here we propose to characterize the temporal correlations in
the broadband brain activity through the lens of neuronal avalanches. To this
end, we consider resting-state EEG and long-term MEG recordings, extract the corresponding
neuronal avalanche sequences, and study their temporal correlations. We demonstrate
that the broadband resting-state brain activity consistently exhibits long-range
power-law correlations in both EEG and MEG recordings, with similar values of
the scaling exponents. Importantly, although we observe that the avalanche size
distribution depends on scale parameters, scaling exponents characterizing long-range
correlations are quite robust. In particular, they are independent of the temporal
binning (scale of analysis), indicating that our analysis captures intrinsic characteristics
of the underlying dynamics. Because neuronal avalanches constitute a fundamental
feature of neural systems with universal characteristics, the proposed approach
may serve as a general, systems- and experiment-independent procedure to infer
the existence of underlying long-range correlations in extended neural systems,
and identify pathological behaviors in the complex spatio-temporal interplay of
cortical rhythms.
acknowledgement: LdA would like to acknowledge the financial support from MIUR-PRIN2017
WZFTZP and VALERE:VAnviteLli pEr la RicErca 2019. FL acknowledges support from the
European Union’s Horizon 2020 research and innovation programme under the Marie
Sklodowska-Curie Grant Agreement No. 754411. HJH would like to thank the Agencies
CAPES and FUNCAP for financial support.
article_processing_charge: No
article_type: original
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Oren
full_name: Shriki, Oren
last_name: Shriki
- first_name: Hans J
full_name: Herrmann, Hans J
last_name: Herrmann
- first_name: Lucilla
full_name: de Arcangelis, Lucilla
last_name: de Arcangelis
citation:
ama: Lombardi F, Shriki O, Herrmann HJ, de Arcangelis L. Long-range temporal correlations
in the broadband resting state activity of the human brain revealed by neuronal
avalanches. Neurocomputing. 2021;461:657-666. doi:10.1016/j.neucom.2020.05.126
apa: Lombardi, F., Shriki, O., Herrmann, H. J., & de Arcangelis, L. (2021).
Long-range temporal correlations in the broadband resting state activity of the
human brain revealed by neuronal avalanches. Neurocomputing. Elsevier.
https://doi.org/10.1016/j.neucom.2020.05.126
chicago: Lombardi, Fabrizio, Oren Shriki, Hans J Herrmann, and Lucilla de Arcangelis.
“Long-Range Temporal Correlations in the Broadband Resting State Activity of the
Human Brain Revealed by Neuronal Avalanches.” Neurocomputing. Elsevier,
2021. https://doi.org/10.1016/j.neucom.2020.05.126.
ieee: F. Lombardi, O. Shriki, H. J. Herrmann, and L. de Arcangelis, “Long-range
temporal correlations in the broadband resting state activity of the human brain
revealed by neuronal avalanches,” Neurocomputing, vol. 461. Elsevier, pp.
657–666, 2021.
ista: Lombardi F, Shriki O, Herrmann HJ, de Arcangelis L. 2021. Long-range temporal
correlations in the broadband resting state activity of the human brain revealed
by neuronal avalanches. Neurocomputing. 461, 657–666.
mla: Lombardi, Fabrizio, et al. “Long-Range Temporal Correlations in the Broadband
Resting State Activity of the Human Brain Revealed by Neuronal Avalanches.” Neurocomputing,
vol. 461, Elsevier, 2021, pp. 657–66, doi:10.1016/j.neucom.2020.05.126.
short: F. Lombardi, O. Shriki, H.J. Herrmann, L. de Arcangelis, Neurocomputing 461
(2021) 657–666.
date_created: 2020-02-06T16:09:14Z
date_published: 2021-05-13T00:00:00Z
date_updated: 2025-04-14T07:44:02Z
day: '13'
department:
- _id: GaTk
doi: 10.1016/j.neucom.2020.05.126
ec_funded: 1
external_id:
isi:
- '000704086300015'
intvolume: ' 461'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2020.02.03.930966
month: '05'
oa: 1
oa_version: Preprint
page: 657-666
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Neurocomputing
publication_identifier:
eissn:
- 1872-8286
issn:
- 0925-2312
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Long-range temporal correlations in the broadband resting state activity of
the human brain revealed by neuronal avalanches
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 461
year: '2021'
...
---
_id: '7553'
abstract:
- lang: eng
text: Normative theories and statistical inference provide complementary approaches
for the study of biological systems. A normative theory postulates that organisms
have adapted to efficiently solve essential tasks, and proceeds to mathematically
work out testable consequences of such optimality; parameters that maximize the
hypothesized organismal function can be derived ab initio, without reference to
experimental data. In contrast, statistical inference focuses on efficient utilization
of data to learn model parameters, without reference to any a priori notion of
biological function, utility, or fitness. Traditionally, these two approaches
were developed independently and applied separately. Here we unify them in a coherent
Bayesian framework that embeds a normative theory into a family of maximum-entropy
“optimization priors.” This family defines a smooth interpolation between a data-rich
inference regime (characteristic of “bottom-up” statistical models), and a data-limited
ab inito prediction regime (characteristic of “top-down” normative theory). We
demonstrate the applicability of our framework using data from the visual cortex,
and argue that the flexibility it affords is essential to address a number of
fundamental challenges relating to inference and prediction in complex, high-dimensional
biological problems.
acknowledgement: The authors thank Dario Ringach for providing the V1 receptive fields
and Olivier Marre for providing the retinal receptive fields. W.M. was funded by
the European Union’s Horizon 2020 research and innovation programme under the Marie
Skłodowska-Curie grant agreement no. 754411. M.H. was funded in part by Human Frontiers
Science grant no. HFSP RGP0032/2018.
article_processing_charge: No
author:
- first_name: Wiktor F
full_name: Mlynarski, Wiktor F
id: 358A453A-F248-11E8-B48F-1D18A9856A87
last_name: Mlynarski
- first_name: Michal
full_name: Hledik, Michal
id: 4171253A-F248-11E8-B48F-1D18A9856A87
last_name: Hledik
- 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: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. Statistical analysis and optimality
of neural systems. Neuron. 2021;109(7):1227-1241.e5. doi:10.1016/j.neuron.2021.01.020
apa: Mlynarski, W. F., Hledik, M., Sokolowski, T. R., & Tkačik, G. (2021). Statistical
analysis and optimality of neural systems. Neuron. Cell Press. https://doi.org/10.1016/j.neuron.2021.01.020
chicago: Mlynarski, Wiktor F, Michal Hledik, Thomas R Sokolowski, and Gašper Tkačik.
“Statistical Analysis and Optimality of Neural Systems.” Neuron. Cell Press,
2021. https://doi.org/10.1016/j.neuron.2021.01.020.
ieee: W. F. Mlynarski, M. Hledik, T. R. Sokolowski, and G. Tkačik, “Statistical
analysis and optimality of neural systems,” Neuron, vol. 109, no. 7. Cell
Press, p. 1227–1241.e5, 2021.
ista: Mlynarski WF, Hledik M, Sokolowski TR, Tkačik G. 2021. Statistical analysis
and optimality of neural systems. Neuron. 109(7), 1227–1241.e5.
mla: Mlynarski, Wiktor F., et al. “Statistical Analysis and Optimality of Neural
Systems.” Neuron, vol. 109, no. 7, Cell Press, 2021, p. 1227–1241.e5, doi:10.1016/j.neuron.2021.01.020.
short: W.F. Mlynarski, M. Hledik, T.R. Sokolowski, G. Tkačik, Neuron 109 (2021)
1227–1241.e5.
corr_author: '1'
date_created: 2020-02-28T11:00:12Z
date_published: 2021-04-07T00:00:00Z
date_updated: 2026-04-07T12:59:24Z
day: '07'
department:
- _id: GaTk
doi: 10.1016/j.neuron.2021.01.020
ec_funded: 1
external_id:
isi:
- '000637809600006'
pmid:
- '33592180'
intvolume: ' 109'
isi: 1
issue: '7'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/848374
month: '04'
oa: 1
oa_version: Preprint
page: 1227-1241.e5
pmid: 1
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Neuron
publication_status: published
publisher: Cell Press
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/can-evolution-be-predicted/
record:
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relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Statistical analysis and optimality of neural systems
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 109
year: '2021'
...
---
_id: '8997'
abstract:
- lang: eng
text: Phenomenological relations such as Ohm’s or Fourier’s law have a venerable
history in physics but are still scarce in biology. This situation restrains predictive
theory. Here, we build on bacterial “growth laws,” which capture physiological
feedback between translation and cell growth, to construct a minimal biophysical
model for the combined action of ribosome-targeting antibiotics. Our model predicts
drug interactions like antagonism or synergy solely from responses to individual
drugs. We provide analytical results for limiting cases, which agree well with
numerical results. We systematically refine the model by including direct physical
interactions of different antibiotics on the ribosome. In a limiting case, our
model provides a mechanistic underpinning for recent predictions of higher-order
interactions that were derived using entropy maximization. We further refine the
model to include the effects of antibiotics that mimic starvation and the presence
of resistance genes. We describe the impact of a starvation-mimicking antibiotic
on drug interactions analytically and verify it experimentally. Our extended model
suggests a change in the type of drug interaction that depends on the strength
of resistance, which challenges established rescaling paradigms. We experimentally
show that the presence of unregulated resistance genes can lead to altered drug
interaction, which agrees with the prediction of the model. While minimal, the
model is readily adaptable and opens the door to predicting interactions of second
and higher-order in a broad range of biological systems.
acknowledgement: 'This work was supported in part by Tum stipend of Knafelj foundation
(to B.K.), Austrian Science Fund (FWF) standalone grants P 27201-B22 (to T.B.) and
P 28844(to G.T.), HFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation
(DFG) individual grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG)
Collaborative Research Centre (SFB) 1310 (to T.B.). '
article_number: e1008529
article_processing_charge: Yes
article_type: original
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Kavcic B, Tkačik G, Bollenbach MT. Minimal biophysical model of combined antibiotic
action. PLOS Computational Biology. 2021;17. doi:10.1371/journal.pcbi.1008529
apa: Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2021). Minimal biophysical
model of combined antibiotic action. PLOS Computational Biology. Public
Library of Science. https://doi.org/10.1371/journal.pcbi.1008529
chicago: Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Minimal Biophysical
Model of Combined Antibiotic Action.” PLOS Computational Biology. Public
Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1008529.
ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Minimal biophysical model of
combined antibiotic action,” PLOS Computational Biology, vol. 17. Public
Library of Science, 2021.
ista: Kavcic B, Tkačik G, Bollenbach MT. 2021. Minimal biophysical model of combined
antibiotic action. PLOS Computational Biology. 17, e1008529.
mla: Kavcic, Bor, et al. “Minimal Biophysical Model of Combined Antibiotic Action.”
PLOS Computational Biology, vol. 17, e1008529, Public Library of Science,
2021, doi:10.1371/journal.pcbi.1008529.
short: B. Kavcic, G. Tkačik, M.T. Bollenbach, PLOS Computational Biology 17 (2021).
date_created: 2021-01-08T07:16:18Z
date_published: 2021-01-07T00:00:00Z
date_updated: 2026-07-06T12:44:35Z
day: '07'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1008529
external_id:
isi:
- '000608045000010'
pmid:
- '33411759'
file:
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checksum: e29f2b42651bef8e034781de8781ffac
content_type: application/pdf
creator: dernst
date_created: 2021-02-04T12:30:48Z
date_updated: 2021-02-04T12:30:48Z
file_id: '9092'
file_name: 2021_PlosComBio_Kavcic.pdf
file_size: 3690053
relation: main_file
success: 1
file_date_updated: 2021-02-04T12:30:48Z
has_accepted_license: '1'
intvolume: ' 17'
isi: 1
keyword:
- Modelling and Simulation
- Genetics
- Molecular Biology
- Antibiotics
- Drug interactions
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: PLOS Computational Biology
publication_identifier:
issn:
- 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
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relation: research_data
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relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Minimal biophysical model of combined antibiotic action
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: '2021'
...