--- _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: - access_level: open_access checksum: b80ebc889033c365d8f8c05a0c655382 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 license: https://creativecommons.org/licenses/by/4.0/ 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 success: 1 - access_level: closed checksum: eda9b9430da2610fee7ce1c1419a479a 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 license: https://creativecommons.org/licenses/by-nc/4.0/ 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' ...