---
_id: '14901'
abstract:
- lang: eng
text: Global services like navigation, communication, and Earth observation have
increased dramatically in the 21st century due to advances in outer space industries.
But as orbits become increasingly crowded with both satellites and inevitable
space debris pollution, continued operations become endangered by the heightened
risks of debris collisions in orbit. Kessler Syndrome is the term for when a critical
threshold of orbiting debris triggers a runaway positive feedback loop of debris
collisions, creating debris congestion that can render orbits unusable. As this
potential tipping point becomes more widely recognized, there have been renewed
calls for debris mitigation and removal. Here, we combine complex systems and
social-ecological systems approaches to study how these efforts may affect space
debris accumulation and the likelihood of reaching Kessler Syndrome. Specifically,
we model how debris levels are affected by future launch rates, cleanup activities,
and collisions between extant debris. We contextualize and interpret our dynamic
model within a discussion of existing space debris governance and other social,
economic, and geopolitical factors that may influence effective collective management
of the orbital commons. In line with previous studies, our model finds that debris
congestion may be reached in less than 200 years, though a holistic management
strategy combining removal and mitigation actions can avoid such outcomes while
continuing space activities. Moreover, although active debris removal may be particularly
effective, the current lack of market and governance support may impede its implementation.
Research into these critical dynamics and the multi-faceted variables that influence
debris outcomes can support policymakers in curating impactful governance strategies
and realistic transition pathways to sustaining debris-free orbits. Overall, our
study is useful for communicating about space debris sustainability in policy
and education settings by providing an exploration of policy portfolio options
supported by a simple and clear social-ecological modeling approach.
acknowledgement: The authors would like to thank the special issue co-editors, Marco
Janssen and Xiao-Shan Yap, and the anonymous reviewers for their comments that helped
improve the manuscript. The paper also benefited from suggestions by other author
participants in this special issue. We would also like to thank the 2022 Santa Fe
Institute Complex Systems Summer School for providing space to initiate this study.
article_processing_charge: Yes
article_type: original
author:
- first_name: Keiko
full_name: Nomura, Keiko
last_name: Nomura
- first_name: Simon
full_name: Rella, Simon
id: B4765ACA-AA38-11E9-AC9A-0930E6697425
last_name: Rella
- first_name: Haily
full_name: Merritt, Haily
last_name: Merritt
- first_name: Mathieu
full_name: Baltussen, Mathieu
last_name: Baltussen
- first_name: Darcy
full_name: Bird, Darcy
last_name: Bird
- first_name: Annika
full_name: Tjuka, Annika
last_name: Tjuka
- first_name: Dan
full_name: Falk, Dan
last_name: Falk
citation:
ama: Nomura K, Rella S, Merritt H, et al. Tipping points of space debris in low
earth orbit. International Journal of the Commons. 2024;18(1). doi:10.5334/ijc.1275
apa: Nomura, K., Rella, S., Merritt, H., Baltussen, M., Bird, D., Tjuka, A., &
Falk, D. (2024). Tipping points of space debris in low earth orbit. International
Journal of the Commons. Ubiquity Press. https://doi.org/10.5334/ijc.1275
chicago: Nomura, Keiko, Simon Rella, Haily Merritt, Mathieu Baltussen, Darcy Bird,
Annika Tjuka, and Dan Falk. “Tipping Points of Space Debris in Low Earth Orbit.”
International Journal of the Commons. Ubiquity Press, 2024. https://doi.org/10.5334/ijc.1275.
ieee: K. Nomura et al., “Tipping points of space debris in low earth orbit,”
International Journal of the Commons, vol. 18, no. 1. Ubiquity Press, 2024.
ista: Nomura K, Rella S, Merritt H, Baltussen M, Bird D, Tjuka A, Falk D. 2024.
Tipping points of space debris in low earth orbit. International Journal of the
Commons. 18(1).
mla: Nomura, Keiko, et al. “Tipping Points of Space Debris in Low Earth Orbit.”
International Journal of the Commons, vol. 18, no. 1, Ubiquity Press, 2024,
doi:10.5334/ijc.1275.
short: K. Nomura, S. Rella, H. Merritt, M. Baltussen, D. Bird, A. Tjuka, D. Falk,
International Journal of the Commons 18 (2024).
date_created: 2024-01-30T11:58:02Z
date_published: 2024-01-11T00:00:00Z
date_updated: 2024-02-05T10:10:27Z
day: '11'
ddc:
- '550'
department:
- _id: GradSch
- _id: GaTk
doi: 10.5334/ijc.1275
file:
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content_type: application/pdf
creator: dernst
date_created: 2024-02-05T10:06:35Z
date_updated: 2024-02-05T10:06:35Z
file_id: '14939'
file_name: 2023_IntJourCommons_Nomura.pdf
file_size: 1305786
relation: main_file
success: 1
file_date_updated: 2024-02-05T10:06:35Z
has_accepted_license: '1'
intvolume: ' 18'
issue: '1'
keyword:
- Sociology and Political Science
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: International Journal of the Commons
publication_identifier:
issn:
- 1875-0281
publication_status: published
publisher: Ubiquity Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Tipping points of space debris in low earth orbit
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: 18
year: '2024'
...
---
_id: '15020'
abstract:
- lang: eng
text: "This thesis consists of four distinct pieces of work within theoretical biology,
with two themes in common: the concept of optimization in biological systems,
and the use of information-theoretic tools to quantify biological stochasticity
and statistical uncertainty.\r\nChapter 2 develops a statistical framework for
studying biological systems which we believe to be optimized for a particular
utility function, such as retinal neurons conveying information about visual stimuli.
We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the
expected utility. We explore how such priors aid inference of system parameters
with limited data and enable optimality hypothesis testing: is the utility higher
than by chance?\r\nChapter 3 examines the ultimate biological optimization process:
evolution by natural selection. As some individuals survive and reproduce more
successfully than others, populations evolve towards fitter genotypes and phenotypes.
We formalize this as accumulation of genetic information, and use population genetics
theory to study how much such information can be accumulated per generation and
maintained in the face of random mutation and genetic drift. We identify the population
size and fitness variance as the key quantities that control information accumulation
and maintenance.\r\nChapter 4 reuses the concept of genetic information from Chapter
3, but from a different perspective: we ask how much genetic information organisms
actually need, in particular in the context of gene regulation. For example, how
much information is needed to bind transcription factors at correct locations
within the genome? Population genetics provides us with a refined answer: with
an increasing population size, populations achieve higher fitness by maintaining
more genetic information. Moreover, regulatory parameters experience selection
pressure to optimize the fitness-information trade-off, i.e. minimize the information
needed for a given fitness. This provides an evolutionary derivation of the optimization
priors introduced in Chapter 2.\r\nChapter 5 proves an upper bound on mutual information
between a signal and a communication channel output (such as neural activity).
Mutual information is an important utility measure for biological systems, but
its practical use can be difficult due to the large dimensionality of many biological
channels. Sometimes, a lower bound on mutual information is computed by replacing
the high-dimensional channel outputs with decodes (signal estimates). Our result
provides a corresponding upper bound, provided that the decodes are the maximum
posterior estimates of the signal."
acknowledged_ssus:
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Michal
full_name: Hledik, Michal
id: 4171253A-F248-11E8-B48F-1D18A9856A87
last_name: Hledik
citation:
ama: Hledik M. Genetic information and biological optimization. 2024. doi:10.15479/at:ista:15020
apa: Hledik, M. (2024). Genetic information and biological optimization.
Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:15020
chicago: Hledik, Michal. “Genetic Information and Biological Optimization.” Institute
of Science and Technology Austria, 2024. https://doi.org/10.15479/at:ista:15020.
ieee: M. Hledik, “Genetic information and biological optimization,” Institute of
Science and Technology Austria, 2024.
ista: Hledik M. 2024. Genetic information and biological optimization. Institute
of Science and Technology Austria.
mla: Hledik, Michal. Genetic Information and Biological Optimization. Institute
of Science and Technology Austria, 2024, doi:10.15479/at:ista:15020.
short: M. Hledik, Genetic Information and Biological Optimization, Institute of
Science and Technology Austria, 2024.
date_created: 2024-02-23T14:02:04Z
date_published: 2024-02-23T00:00:00Z
date_updated: 2024-03-06T14:22:52Z
day: '23'
ddc:
- '576'
- '519'
degree_awarded: PhD
department:
- _id: GradSch
- _id: NiBa
- _id: GaTk
doi: 10.15479/at:ista:15020
ec_funded: 1
file:
- access_level: open_access
checksum: b2d3da47c98d481577a4baf68944fe41
content_type: application/pdf
creator: mhledik
date_created: 2024-02-23T13:50:53Z
date_updated: 2024-02-23T13:50:53Z
file_id: '15021'
file_name: hledik thesis pdfa 2b.pdf
file_size: 7102089
relation: main_file
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content_type: application/zip
creator: mhledik
date_created: 2024-02-23T13:50:54Z
date_updated: 2024-02-23T14:20:16Z
file_id: '15022'
file_name: hledik thesis source.zip
file_size: 14014790
relation: source_file
file_date_updated: 2024-02-23T14:20:16Z
has_accepted_license: '1'
keyword:
- Theoretical biology
- Optimality
- Evolution
- Information
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: '158'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 2665AAFE-B435-11E9-9278-68D0E5697425
grant_number: RGP0034/2018
name: Can evolution minimize spurious signaling crosstalk to reach optimal performance?
- _id: bd6958e0-d553-11ed-ba76-86eba6a76c00
grant_number: '101055327'
name: Understanding the evolution of continuous genomes
publication_identifier:
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '7553'
relation: part_of_dissertation
status: public
- id: '12081'
relation: part_of_dissertation
status: public
- id: '7606'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
title: Genetic information and biological optimization
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2024'
...
---
_id: '13127'
abstract:
- lang: eng
text: Cooperative disease defense emerges as group-level collective behavior, yet
how group members make the underlying individual decisions is poorly understood.
Using garden ants and fungal pathogens as an experimental model, we derive the
rules governing individual ant grooming choices and show how they produce colony-level
hygiene. Time-resolved behavioral analysis, pathogen quantification, and probabilistic
modeling reveal that ants increase grooming and preferentially target highly-infectious
individuals when perceiving high pathogen load, but transiently suppress grooming
after having been groomed by nestmates. Ants thus react to both, the infectivity
of others and the social feedback they receive on their own contagiousness. While
inferred solely from momentary ant decisions, these behavioral rules quantitatively
predict hour-long experimental dynamics, and synergistically combine into efficient
colony-wide pathogen removal. Our analyses show that noisy individual decisions
based on only local, incomplete, yet dynamically-updated information on pathogen
threat and social feedback can lead to potent collective disease defense.
acknowledged_ssus:
- _id: LifeSc
acknowledgement: We thank Mike Bidochka for the fungal strains, the ISTA Social Immunity
Team for ant collection, Hanna Leitner for experimental and molecular support, Jennifer
Robb and Lukas Lindorfer for microscopy, and the LabSupport Facility at ISTA for
general laboratory support. We further thank Victor Mireles, Iain Couzin, Fabian
Theis and the Social Immunity Team for continued feedback throughout, and Michael
Sixt, Yuko Ulrich, Koos Boomsma, Erika Dawson, Megan Kutzer and Hinrich Schulenburg
for comments on the manuscript. This project has received funding from the European
Research Council (ERC) under the European Union’s Horizon 2020 research and innovation
program (Grant No. 771402; EPIDEMICSonCHIP) to SC, from the Scientific Grant Agency
of the Slovak Republic (Grant No. 1/0521/20) to KB, and the Human Frontier Science
Program (Grant No. RGP0065/2012) to GT.
article_number: '3232'
article_processing_charge: Yes
article_type: original
author:
- first_name: Barbara E
full_name: Casillas Perez, Barbara E
id: 351ED2AA-F248-11E8-B48F-1D18A9856A87
last_name: Casillas Perez
- 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: Anna V
full_name: Grasse, Anna V
id: 406F989C-F248-11E8-B48F-1D18A9856A87
last_name: Grasse
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Sylvia
full_name: Cremer, Sylvia
id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87
last_name: Cremer
orcid: 0000-0002-2193-3868
citation:
ama: Casillas Perez BE, Bodova K, Grasse AV, Tkačik G, Cremer S. Dynamic pathogen
detection and social feedback shape collective hygiene in ants. Nature Communications.
2023;14. doi:10.1038/s41467-023-38947-y
apa: Casillas Perez, B. E., Bodova, K., Grasse, A. V., Tkačik, G., & Cremer,
S. (2023). Dynamic pathogen detection and social feedback shape collective hygiene
in ants. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-023-38947-y
chicago: Casillas Perez, Barbara E, Katarina Bodova, Anna V Grasse, Gašper Tkačik,
and Sylvia Cremer. “Dynamic Pathogen Detection and Social Feedback Shape Collective
Hygiene in Ants.” Nature Communications. Springer Nature, 2023. https://doi.org/10.1038/s41467-023-38947-y.
ieee: B. E. Casillas Perez, K. Bodova, A. V. Grasse, G. Tkačik, and S. Cremer, “Dynamic
pathogen detection and social feedback shape collective hygiene in ants,” Nature
Communications, vol. 14. Springer Nature, 2023.
ista: Casillas Perez BE, Bodova K, Grasse AV, Tkačik G, Cremer S. 2023. Dynamic
pathogen detection and social feedback shape collective hygiene in ants. Nature
Communications. 14, 3232.
mla: Casillas Perez, Barbara E., et al. “Dynamic Pathogen Detection and Social Feedback
Shape Collective Hygiene in Ants.” Nature Communications, vol. 14, 3232,
Springer Nature, 2023, doi:10.1038/s41467-023-38947-y.
short: B.E. Casillas Perez, K. Bodova, A.V. Grasse, G. Tkačik, S. Cremer, Nature
Communications 14 (2023).
date_created: 2023-06-11T22:00:40Z
date_published: 2023-06-03T00:00:00Z
date_updated: 2023-08-07T13:09:09Z
day: '03'
ddc:
- '570'
department:
- _id: SyCr
- _id: GaTk
doi: 10.1038/s41467-023-38947-y
ec_funded: 1
external_id:
isi:
- '001002562700005'
pmid:
- '37270641'
file:
- access_level: open_access
checksum: 4af0393e3ed47b3fc46e68b81c3c1007
content_type: application/pdf
creator: dernst
date_created: 2023-06-13T08:05:46Z
date_updated: 2023-06-13T08:05:46Z
file_id: '13132'
file_name: 2023_NatureComm_CasillasPerez.pdf
file_size: 2358167
relation: main_file
success: 1
file_date_updated: 2023-06-13T08:05:46Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 2649B4DE-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '771402'
name: Epidemics in ant societies on a chip
- _id: 255008E4-B435-11E9-9278-68D0E5697425
grant_number: RGP0065/2012
name: Information processing and computation in fish groups
publication: Nature Communications
publication_identifier:
eissn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '12945'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Dynamic pathogen detection and social feedback shape collective hygiene in
ants
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: 14
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
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.
date_created: 2023-03-26T22:01:08Z
date_published: 2023-03-20T00:00:00Z
date_updated: 2023-08-16T12:41:53Z
day: '20'
ddc:
- '570'
department:
- _id: GaTk
- _id: GradSch
doi: 10.1038/s43588-023-00410-9
ec_funded: 1
external_id:
arxiv:
- '2108.06686'
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'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 254-263
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'
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2023'
...
---
_id: '14515'
abstract:
- lang: eng
text: Most natural and engineered information-processing systems transmit information
via signals that vary in time. Computing the information transmission rate or
the information encoded in the temporal characteristics of these signals requires
the mutual information between the input and output signals as a function of time,
i.e., between the input and output trajectories. Yet, this is notoriously difficult
because of the high-dimensional nature of the trajectory space, and all existing
techniques require approximations. We present an exact Monte Carlo technique called
path weight sampling (PWS) that, for the first time, makes it possible to compute
the mutual information between input and output trajectories for any stochastic
system that is described by a master equation. The principal idea is to use the
master equation to evaluate the exact conditional probability of an individual
output trajectory for a given input trajectory and average this via Monte Carlo
sampling in trajectory space to obtain the mutual information. We present three
variants of PWS, which all generate the trajectories using the standard stochastic
simulation algorithm. While direct PWS is a brute-force method, Rosenbluth-Rosenbluth
PWS exploits the analogy between signal trajectory sampling and polymer sampling,
and thermodynamic integration PWS is based on a reversible work calculation in
trajectory space. PWS also makes it possible to compute the mutual information
between input and output trajectories for systems with hidden internal states
as well as systems with feedback from output to input. Applying PWS to the bacterial
chemotaxis system, consisting of 182 coupled chemical reactions, demonstrates
not only that the scheme is highly efficient but also that the number of receptor
clusters is much smaller than hitherto believed, while their size is much larger.
acknowledgement: "We thank Bela Mulder, Tom Shimizu, Fotios Avgidis, Peter Bolhuis,
and Daan Frenkel for useful discussions and a careful reading of the manuscript,
and we thank Age Tjalma for support with obtaining the Gaussian approximation of
the chemotaxis system. This work is part of the Dutch Research Council (NWO) and
was performed at the research institute AMOLF. This project has received funding
from the European Research Council (ERC) under the European Union’s Horizon 2020
research and innovation program (Grant Agreement No. 885065) and was\r\nfinancially
supported by NWO through the “Building a Synthetic Cell (BaSyC)” Gravitation Grant
(024.003.019)."
article_number: '041017'
article_processing_charge: Yes
article_type: original
author:
- first_name: Manuel
full_name: Reinhardt, Manuel
last_name: Reinhardt
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Pieter Rein
full_name: Ten Wolde, Pieter Rein
last_name: Ten Wolde
citation:
ama: 'Reinhardt M, Tkačik G, Ten Wolde PR. Path weight sampling: Exact Monte Carlo
computation of the mutual information between stochastic trajectories. Physical
Review X. 2023;13(4). doi:10.1103/PhysRevX.13.041017'
apa: 'Reinhardt, M., Tkačik, G., & Ten Wolde, P. R. (2023). Path weight sampling:
Exact Monte Carlo computation of the mutual information between stochastic trajectories.
Physical Review X. American Physical Society. https://doi.org/10.1103/PhysRevX.13.041017'
chicago: 'Reinhardt, Manuel, Gašper Tkačik, and Pieter Rein Ten Wolde. “Path Weight
Sampling: Exact Monte Carlo Computation of the Mutual Information between Stochastic
Trajectories.” Physical Review X. American Physical Society, 2023. https://doi.org/10.1103/PhysRevX.13.041017.'
ieee: 'M. Reinhardt, G. Tkačik, and P. R. Ten Wolde, “Path weight sampling: Exact
Monte Carlo computation of the mutual information between stochastic trajectories,”
Physical Review X, vol. 13, no. 4. American Physical Society, 2023.'
ista: 'Reinhardt M, Tkačik G, Ten Wolde PR. 2023. Path weight sampling: Exact Monte
Carlo computation of the mutual information between stochastic trajectories. Physical
Review X. 13(4), 041017.'
mla: 'Reinhardt, Manuel, et al. “Path Weight Sampling: Exact Monte Carlo Computation
of the Mutual Information between Stochastic Trajectories.” Physical Review
X, vol. 13, no. 4, 041017, American Physical Society, 2023, doi:10.1103/PhysRevX.13.041017.'
short: M. Reinhardt, G. Tkačik, P.R. Ten Wolde, Physical Review X 13 (2023).
date_created: 2023-11-12T23:00:55Z
date_published: 2023-10-26T00:00:00Z
date_updated: 2023-11-13T09:03:30Z
day: '26'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.1103/PhysRevX.13.041017
external_id:
arxiv:
- '2203.03461'
file:
- access_level: open_access
checksum: 32574aeebcca7347a4152c611b66b3d5
content_type: application/pdf
creator: dernst
date_created: 2023-11-13T09:00:19Z
date_updated: 2023-11-13T09:00:19Z
file_id: '14522'
file_name: 2023_PhysReviewX_Reinhardt.pdf
file_size: 1595223
relation: main_file
success: 1
file_date_updated: 2023-11-13T09:00:19Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '4'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
publication: Physical Review X
publication_identifier:
eissn:
- 2160-3308
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Path weight sampling: Exact Monte Carlo computation of the mutual information
between stochastic trajectories'
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: 13
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 of 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 of 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 of 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 of 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: 2023-12-11T11:37:20Z
day: '29'
ddc:
- '570'
department:
- _id: JoCs
- _id: GaTk
doi: 10.1523/JNEUROSCI.0194-23.2023
ec_funded: 1
external_id:
pmid:
- '37758476'
file:
- access_level: closed
checksum: e2503c8f84be1050e28f64320f1d5bd2
content_type: application/pdf
creator: dernst
date_created: 2023-12-11T11:30:37Z
date_updated: 2023-12-11T11:30:37Z
embargo: 2024-06-01
embargo_to: open_access
file_id: '14674'
file_name: 2023_JourNeuroscience_Nardin.pdf
file_size: 2280632
relation: main_file
file_date_updated: 2023-12-11T11:30:37Z
has_accepted_license: '1'
intvolume: ' 43'
issue: '48'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1523/JNEUROSCI.0194-23.2023
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 of Neuroscience
quality_controlled: '1'
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 43
year: '2023'
...
---
_id: '12487'
abstract:
- lang: eng
text: Sleep plays a key role in preserving brain function, keeping the brain network
in a state that ensures optimal computational capabilities. Empirical evidence
indicates that such a state is consistent with criticality, where scale-free neuronal
avalanches emerge. However, the relationship between sleep, emergent avalanches,
and criticality remains poorly understood. Here we fully characterize the critical
behavior of avalanches during sleep, and study their relationship with the sleep
macro- and micro-architecture, in particular the cyclic alternating pattern (CAP).
We show that avalanche size and duration distributions exhibit robust power laws
with exponents approximately equal to −3/2 e −2, respectively. Importantly, we
find that sizes scale as a power law of the durations, and that all critical exponents
for neuronal avalanches obey robust scaling relations, which are consistent with
the mean-field directed percolation universality class. Our analysis demonstrates
that avalanche dynamics depends on the position within the NREM-REM cycles, with
the avalanche density increasing in the descending phases and decreasing in the
ascending phases of sleep cycles. Moreover, we show that, within NREM sleep, avalanche
occurrence correlates with CAP activation phases, particularly A1, which are the
expression of slow wave sleep propensity and have been proposed to be beneficial
for cognitive processes. The results suggest that neuronal avalanches, and thus
tuning to criticality, actively contribute to sleep development and play a role
in preserving network function. Such findings, alongside characterization of the
universality class for avalanches, open new avenues to the investigation of functional
role of criticality during sleep with potential clinical application.Significance
statementWe fully characterize the critical behavior of neuronal
avalanches during sleep, and show that avalanches follow precise scaling laws
that are consistent with the mean-field directed percolation universality class.
The analysis provides first evidence of a functional relationship between avalanche
occurrence, slow-wave sleep dynamics, sleep stage transitions and occurrence of
CAP phase A during NREM sleep. Because CAP is considered one of the major guardians
of NREM sleep that allows the brain to dynamically react to external perturbation
and contributes to the cognitive consolidation processes occurring in sleep, our
observations suggest that neuronal avalanches at criticality are associated with
flexible response to external inputs and to cognitive processes, a key assumption
of the critical brain hypothesis.
acknowledgement: FL acknowledges support from the European Union’s Horizon 2020 research
and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411,
and from the Austrian Science Fund (FWF) under the Lise Meitner fellowship No. PT1013M03318.
IA acknowledges financial support from the MIUR PRIN 2017WZFTZP.
article_processing_charge: Yes
article_type: original
author:
- first_name: Silvia
full_name: Scarpetta, Silvia
last_name: Scarpetta
- first_name: Niccolò
full_name: Morrisi, Niccolò
last_name: Morrisi
- first_name: Carlotta
full_name: Mutti, Carlotta
last_name: Mutti
- first_name: Nicoletta
full_name: Azzi, Nicoletta
last_name: Azzi
- first_name: Irene
full_name: Trippi, Irene
last_name: Trippi
- first_name: Rosario
full_name: Ciliento, Rosario
last_name: Ciliento
- first_name: Ilenia
full_name: Apicella, Ilenia
last_name: Apicella
- first_name: Giovanni
full_name: Messuti, Giovanni
last_name: Messuti
- first_name: Marianna
full_name: Angiolelli, Marianna
last_name: Angiolelli
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Liborio
full_name: Parrino, Liborio
last_name: Parrino
- first_name: Anna Elisabetta
full_name: Vaudano, Anna Elisabetta
last_name: Vaudano
citation:
ama: Scarpetta S, Morrisi N, Mutti C, et al. Criticality of neuronal avalanches
in human sleep and their relationship with sleep macro- and micro-architecture.
iScience. 2023;26(10):107840. doi:10.1016/j.isci.2023.107840
apa: Scarpetta, S., Morrisi, N., Mutti, C., Azzi, N., Trippi, I., Ciliento, R.,
… Vaudano, A. E. (2023). Criticality of neuronal avalanches in human sleep and
their relationship with sleep macro- and micro-architecture. IScience.
Elsevier. https://doi.org/10.1016/j.isci.2023.107840
chicago: Scarpetta, Silvia, Niccolò Morrisi, Carlotta Mutti, Nicoletta Azzi, Irene
Trippi, Rosario Ciliento, Ilenia Apicella, et al. “Criticality of Neuronal Avalanches
in Human Sleep and Their Relationship with Sleep Macro- and Micro-Architecture.”
IScience. Elsevier, 2023. https://doi.org/10.1016/j.isci.2023.107840.
ieee: S. Scarpetta et al., “Criticality of neuronal avalanches in human sleep
and their relationship with sleep macro- and micro-architecture,” iScience,
vol. 26, no. 10. Elsevier, p. 107840, 2023.
ista: Scarpetta S, Morrisi N, Mutti C, Azzi N, Trippi I, Ciliento R, Apicella I,
Messuti G, Angiolelli M, Lombardi F, Parrino L, Vaudano AE. 2023. Criticality
of neuronal avalanches in human sleep and their relationship with sleep macro-
and micro-architecture. iScience. 26(10), 107840.
mla: Scarpetta, Silvia, et al. “Criticality of Neuronal Avalanches in Human Sleep
and Their Relationship with Sleep Macro- and Micro-Architecture.” IScience,
vol. 26, no. 10, Elsevier, 2023, p. 107840, doi:10.1016/j.isci.2023.107840.
short: S. Scarpetta, N. Morrisi, C. Mutti, N. Azzi, I. Trippi, R. Ciliento, I. Apicella,
G. Messuti, M. Angiolelli, F. Lombardi, L. Parrino, A.E. Vaudano, IScience 26
(2023) 107840.
date_created: 2023-02-02T10:50:17Z
date_published: 2023-10-20T00:00:00Z
date_updated: 2023-12-13T11:11:24Z
day: '20'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1016/j.isci.2023.107840
ec_funded: 1
external_id:
isi:
- '001082331200001'
pmid:
- '37766992'
file:
- access_level: open_access
checksum: f499836af172ecc9865de4bb41fa99d1
content_type: application/pdf
creator: dernst
date_created: 2023-10-09T07:23:46Z
date_updated: 2023-10-09T07:23:46Z
file_id: '14412'
file_name: 2023_iScience_Scarpetta.pdf
file_size: 4872708
relation: main_file
success: 1
file_date_updated: 2023-10-09T07:23:46Z
has_accepted_license: '1'
intvolume: ' 26'
isi: 1
issue: '10'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: '107840'
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
publication: iScience
publication_identifier:
eissn:
- 2589-0042
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Criticality of neuronal avalanches in human sleep and their relationship with
sleep macro- and micro-architecture
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: 26
year: '2023'
...
---
_id: '14862'
article_number: ckad160.597
article_processing_charge: No
author:
- first_name: Simon
full_name: Rella, Simon
id: B4765ACA-AA38-11E9-AC9A-0930E6697425
last_name: Rella
- first_name: Y
full_name: Kulikova, Y
last_name: Kulikova
- first_name: Aygul
full_name: Minnegalieva, Aygul
id: 87DF77F0-1D9A-11EA-B6AE-CE443DDC885E
last_name: Minnegalieva
- first_name: Fyodor
full_name: Kondrashov, Fyodor
id: 44FDEF62-F248-11E8-B48F-1D18A9856A87
last_name: Kondrashov
orcid: 0000-0001-8243-4694
citation:
ama: 'Rella S, Kulikova Y, Minnegalieva A, Kondrashov F. Complex vaccination strategies
prevent the emergence of vaccine resistance. In: European Journal of Public
Health. Vol 33. Oxford University Press; 2023. doi:10.1093/eurpub/ckad160.597'
apa: Rella, S., Kulikova, Y., Minnegalieva, A., & Kondrashov, F. (2023). Complex
vaccination strategies prevent the emergence of vaccine resistance. In European
Journal of Public Health (Vol. 33). Oxford University Press. https://doi.org/10.1093/eurpub/ckad160.597
chicago: Rella, Simon, Y Kulikova, Aygul Minnegalieva, and Fyodor Kondrashov. “Complex
Vaccination Strategies Prevent the Emergence of Vaccine Resistance.” In European
Journal of Public Health, Vol. 33. Oxford University Press, 2023. https://doi.org/10.1093/eurpub/ckad160.597.
ieee: S. Rella, Y. Kulikova, A. Minnegalieva, and F. Kondrashov, “Complex vaccination
strategies prevent the emergence of vaccine resistance,” in European Journal
of Public Health, 2023, vol. 33, no. Supplement_2.
ista: Rella S, Kulikova Y, Minnegalieva A, Kondrashov F. 2023. Complex vaccination
strategies prevent the emergence of vaccine resistance. European Journal of Public
Health. vol. 33, ckad160.597.
mla: Rella, Simon, et al. “Complex Vaccination Strategies Prevent the Emergence
of Vaccine Resistance.” European Journal of Public Health, vol. 33, no.
Supplement_2, ckad160.597, Oxford University Press, 2023, doi:10.1093/eurpub/ckad160.597.
short: S. Rella, Y. Kulikova, A. Minnegalieva, F. Kondrashov, in:, European Journal
of Public Health, Oxford University Press, 2023.
date_created: 2024-01-22T12:02:28Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2024-01-24T11:16:09Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1093/eurpub/ckad160.597
file:
- access_level: open_access
checksum: 98706755bb4cc5d553818ade7660a7d2
content_type: application/pdf
creator: dernst
date_created: 2024-01-24T11:12:33Z
date_updated: 2024-01-24T11:12:33Z
file_id: '14882'
file_name: 2023_EurJourPublicHealth_Rella.pdf
file_size: 71057
relation: main_file
success: 1
file_date_updated: 2024-01-24T11:12:33Z
has_accepted_license: '1'
intvolume: ' 33'
issue: Supplement_2
keyword:
- Public Health
- Environmental and Occupational Health
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
publication: European Journal of Public Health
publication_identifier:
eissn:
- 1464-360X
issn:
- 1101-1262
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
status: public
title: Complex vaccination strategies prevent the emergence of vaccine resistance
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: conference_abstract
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 33
year: '2023'
...
---
_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).
date_created: 2023-10-08T22:01:15Z
date_published: 2023-10-31T00:00:00Z
date_updated: 2024-01-30T14:07:40Z
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
relation: main_file
success: 1
file_date_updated: 2024-01-30T14:07:08Z
has_accepted_license: '1'
intvolume: ' 42'
isi: 1
issue: '10'
language:
- iso: eng
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'
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: '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. 2022. doi:10.1101/2022.03.03.482657
apa: Lombardi, F., Herrmann, H. J., Parrino, L., Plenz, D., Scarpetta, S., Vaudano,
A. E., … Shriki, O. (2022). Alpha rhythm induces attenuation-amplification dynamics
in neural activity cascades. bioRxiv. Cold Spring Harbor Laboratory. 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. Cold Spring Harbor Laboratory, 2022. 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. Cold Spring Harbor Laboratory,
2022.
ista: Lombardi F, Herrmann HJ, Parrino L, Plenz D, Scarpetta S, Vaudano AE, de Arcangelis
L, Shriki O. 2022. 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, Cold Spring Harbor Laboratory,
2022, 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 (2022).
date_created: 2022-03-04T22:20:59Z
date_published: 2022-03-04T00:00:00Z
date_updated: 2022-03-07T07:28:34Z
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: published
publisher: Cold Spring Harbor Laboratory
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: '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
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: 2022-07-25T07:52:35Z
day: '24'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.1103/PhysRevResearch.4.023240
external_id:
arxiv:
- '2106.02349'
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
relation: main_file
success: 1
file_date_updated: 2022-07-25T07:47:23Z
funded_apc: '1'
has_accepted_license: '1'
intvolume: ' 4'
issue: '2'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
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: '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).
date_created: 2023-01-12T12:08:51Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2023-02-13T09:20:34Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1016/j.coisb.2022.100435
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
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: '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: 2023-08-02T13:34:25Z
day: '04'
ddc:
- '570'
department:
- _id: EdHa
- _id: GaTk
doi: 10.1016/j.bpj.2021.12.006
external_id:
isi:
- '000740815400007'
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
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'
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
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: Steinrueck, Magdalena
last_name: Steinrueck
- 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, Steinrueck 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., Steinrueck, 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 Steinrueck, 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, Steinrueck 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. Steinrueck, D. Toledo-Aparicio, J.P. Bollback,
C.C. Guet, G. Tkačik, ELife 11 (2022).
date_created: 2022-02-06T23:01:32Z
date_published: 2022-01-26T00:00:00Z
date_updated: 2023-08-02T14:09:02Z
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 11
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.
date_created: 2023-01-22T23:00:55Z
date_published: 2022-12-21T00:00:00Z
date_updated: 2023-08-03T14:23:49Z
day: '21'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pbio.3001889
ec_funded: 1
external_id:
isi:
- '000925192000001'
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
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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 20
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. 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.
Proceedings of the 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. Proceedings of the 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, vol. 119,
no. 36. Proceedings of the 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. 119(36), e2123152119.
mla: Hledik, Michal, et al. “Accumulation and Maintenance of Information in Evolution.”
Proceedings of the National Academy of Sciences, vol. 119, no. 36, e2123152119,
Proceedings of the 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 119 (2022).
date_created: 2022-09-11T22:01:55Z
date_published: 2022-08-29T00:00:00Z
date_updated: 2024-03-06T14:22:51Z
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
publication_identifier:
eissn:
- 1091-6490
issn:
- 0027-8424
publication_status: published
publisher: Proceedings of the 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 119
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
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).
date_created: 2021-12-12T23:01:27Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-08-01T10:48:04Z
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: '10912'
abstract:
- lang: eng
text: Brain dynamics display collective phenomena as diverse as neuronal oscillations
and avalanches. Oscillations are rhythmic, with fluctuations occurring at a characteristic
scale, whereas avalanches are scale-free cascades of neural activity. Here we
show that such antithetic features can coexist in a very generic class of adaptive
neural networks. In the most simple yet fully microscopic model from this class
we 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 fluctuations, collective behaviors of nearly-synchronous extreme events
on multiple sensors, to neuronal avalanches unfolding over multiple sensors across
multiple time-bins. Importantly, the inferred parameters correlate with model-independent
signatures of "closeness to criticality", suggesting that the coexistence of scale-specific
(neural oscillations) and scale-free (neuronal avalanches) dynamics in brain activity
occurs close to a non-equilibrium critical point at the onset of self-sustained
oscillations.
acknowledgement: "FL acknowledges support from the European Union’s Horizon 2020 research
and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.
GT\r\nacknowledges the support of the Austrian Science Fund (FWF) under Stand-Alone
Grant\r\nNo. P34015."
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: 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
last_name: De Martino
citation:
ama: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. doi:10.48550/ARXIV.2108.06686
apa: Lombardi, F., Pepic, S., Shriki, O., Tkačik, G., & De Martino, D. (n.d.).
Quantifying the coexistence of neuronal oscillations and avalanches. arXiv. https://doi.org/10.48550/ARXIV.2108.06686
chicago: Lombardi, Fabrizio, Selver Pepic, Oren Shriki, Gašper Tkačik, and Daniele
De Martino. “Quantifying the Coexistence of Neuronal Oscillations and Avalanches.”
arXiv, n.d. https://doi.org/10.48550/ARXIV.2108.06686.
ieee: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, and D. De Martino, “Quantifying
the coexistence of neuronal oscillations and avalanches.” arXiv.
ista: Lombardi F, Pepic S, Shriki O, Tkačik G, De Martino D. Quantifying the coexistence
of neuronal oscillations and avalanches. 10.48550/ARXIV.2108.06686.
mla: Lombardi, Fabrizio, et al. Quantifying the Coexistence of Neuronal Oscillations
and Avalanches. arXiv, doi:10.48550/ARXIV.2108.06686.
short: F. Lombardi, S. Pepic, O. Shriki, G. Tkačik, D. De Martino, (n.d.).
date_created: 2022-03-21T11:41:28Z
date_published: 2021-08-17T00:00:00Z
date_updated: 2022-03-22T07:53:18Z
day: '17'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.48550/ARXIV.2108.06686
ec_funded: 1
external_id:
arxiv:
- '2108.06686'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2108.06686
month: '08'
oa: 1
oa_version: Preprint
page: '37'
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
publication_status: submitted
publisher: arXiv
status: public
title: Quantifying the coexistence of neuronal oscillations and avalanches
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '10579'
abstract:
- lang: eng
text: 'We consider a totally asymmetric simple exclusion process (TASEP) consisting
of particles on a lattice that require binding by a "token" to move. Using a combination
of theory and simulations, we address the following questions: (i) How token binding
kinetics affects the current-density relation; (ii) How the current-density relation
depends on the scarcity of tokens; (iii) How tokens propagate the effects of the
locally-imposed disorder (such a slow site) over the entire lattice; (iv) How
a shared pool of tokens couples concurrent TASEPs running on multiple lattices;
(v) How our results translate to TASEPs with open boundaries that exchange particles
with the reservoir. Since real particle motion (including in systems that inspired
the standard TASEP model, e.g., protein synthesis or movement of molecular motors)
is often catalyzed, regulated, actuated, or otherwise mediated, the token-driven
TASEP dynamics analyzed in this paper should allow for a better understanding
of real systems and enable a closer match between TASEP theory and experimental
observations.'
acknowledgement: B.K. thanks Stefano Elefante, Simon Rella, and Michal Hledík for
their help with the usage of the cluster. B.K. additionally thanks Călin Guet and
his group for help and advice. We thank M. Hennessey-Wesen for constructive comments
on the manuscript. We thank Ankita Gupta (Indian Institute of Technology) for spotting
a typographical error in Eq. (49) in the preprint version of this paper.
article_number: '2112.13558'
article_processing_charge: No
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
citation:
ama: Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process.
arXiv. doi:10.48550/arXiv.2112.13558
apa: Kavcic, B., & Tkačik, G. (n.d.). Token-driven totally asymmetric simple
exclusion process. arXiv. https://doi.org/10.48550/arXiv.2112.13558
chicago: Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple
Exclusion Process.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2112.13558.
ieee: B. Kavcic and G. Tkačik, “Token-driven totally asymmetric simple exclusion
process,” arXiv. .
ista: Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process.
arXiv, 2112.13558.
mla: Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple Exclusion
Process.” ArXiv, 2112.13558, doi:10.48550/arXiv.2112.13558.
short: B. Kavcic, G. Tkačik, ArXiv (n.d.).
date_created: 2021-12-28T06:52:09Z
date_published: 2021-12-27T00:00:00Z
date_updated: 2023-05-03T10:54:05Z
day: '27'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.48550/arXiv.2112.13558
external_id:
arxiv:
- '2112.13558'
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2112.13558
month: '12'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Token-driven totally asymmetric simple exclusion process
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: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
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: 2023-08-04T10:46:29Z
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'
...