--- _id: '1928' abstract: - lang: eng text: In infectious disease epidemiology the basic reproductive ratio, R0, is defined as the average number of new infections caused by a single infected individual in a fully susceptible population. Many models describing competition for hosts between non-interacting pathogen strains in an infinite population lead to the conclusion that selection favors invasion of new strains if and only if they have higher R0 values than the resident. Here we demonstrate that this picture fails in finite populations. Using a simple stochastic SIS model, we show that in general there is no analogous optimization principle. We find that successive invasions may in some cases lead to strains that infect a smaller fraction of the host population, and that mutually invasible pathogen strains exist. In the limit of weak selection we demonstrate that an optimization principle does exist, although it differs from R0 maximization. For strains with very large R0, we derive an expression for this local fitness function and use it to establish a lower bound for the error caused by neglecting stochastic effects. Furthermore, we apply this weak selection limit to investigate the selection dynamics in the presence of a trade-off between the virulence and the transmission rate of a pathogen. acknowledgement: J.H. received support from the Zdenek Bakala Foundation and the Mobility Fund of Charles University in Prague. author: - first_name: Jan full_name: Humplik, Jan id: 2E9627A8-F248-11E8-B48F-1D18A9856A87 last_name: Humplik - first_name: Alison full_name: Hill, Alison last_name: Hill - first_name: Martin full_name: Nowak, Martin last_name: Nowak citation: ama: Humplik J, Hill A, Nowak M. Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. 2014;360:149-162. doi:10.1016/j.jtbi.2014.06.039 apa: Humplik, J., Hill, A., & Nowak, M. (2014). Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. Elsevier. https://doi.org/10.1016/j.jtbi.2014.06.039 chicago: Humplik, Jan, Alison Hill, and Martin Nowak. “Evolutionary Dynamics of Infectious Diseases in Finite Populations.” Journal of Theoretical Biology. Elsevier, 2014. https://doi.org/10.1016/j.jtbi.2014.06.039. ieee: J. Humplik, A. Hill, and M. Nowak, “Evolutionary dynamics of infectious diseases in finite populations,” Journal of Theoretical Biology, vol. 360. Elsevier, pp. 149–162, 2014. ista: Humplik J, Hill A, Nowak M. 2014. Evolutionary dynamics of infectious diseases in finite populations. Journal of Theoretical Biology. 360, 149–162. mla: Humplik, Jan, et al. “Evolutionary Dynamics of Infectious Diseases in Finite Populations.” Journal of Theoretical Biology, vol. 360, Elsevier, 2014, pp. 149–62, doi:10.1016/j.jtbi.2014.06.039. short: J. Humplik, A. Hill, M. Nowak, Journal of Theoretical Biology 360 (2014) 149–162. date_created: 2018-12-11T11:54:46Z date_published: 2014-11-07T00:00:00Z date_updated: 2021-01-12T06:54:08Z day: '07' department: - _id: GaTk doi: 10.1016/j.jtbi.2014.06.039 intvolume: ' 360' language: - iso: eng month: '11' oa_version: None page: 149 - 162 publication: Journal of Theoretical Biology publication_status: published publisher: Elsevier publist_id: '5166' scopus_import: 1 status: public title: Evolutionary dynamics of infectious diseases in finite populations type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 360 year: '2014' ... --- _id: '1931' abstract: - lang: eng text: A wealth of experimental evidence suggests that working memory circuits preferentially represent information that is behaviorally relevant. Still, we are missing a mechanistic account of how these representations come about. Here we provide a simple explanation for a range of experimental findings, in light of prefrontal circuits adapting to task constraints by reward-dependent learning. In particular, we model a neural network shaped by reward-modulated spike-timing dependent plasticity (r-STDP) and homeostatic plasticity (intrinsic excitability and synaptic scaling). We show that the experimentally-observed neural representations naturally emerge in an initially unstructured circuit as it learns to solve several working memory tasks. These results point to a critical, and previously unappreciated, role for reward-dependent learning in shaping prefrontal cortex activity. acknowledgement: Supported in part by EC MEXT project PLICON and the LOEWE-Program “Neuronal Coordination Research Focus Frankfurt” (NeFF). Jochen Triesch was supported by the Quandt foundation. article_number: '57' author: - first_name: Cristina full_name: Savin, Cristina id: 3933349E-F248-11E8-B48F-1D18A9856A87 last_name: Savin - first_name: Jochen full_name: Triesch, Jochen last_name: Triesch citation: ama: Savin C, Triesch J. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 2014;8(MAY). doi:10.3389/fncom.2014.00057 apa: Savin, C., & Triesch, J. (2014). Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. Frontiers Research Foundation. https://doi.org/10.3389/fncom.2014.00057 chicago: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations in Working Memory Circuits.” Frontiers in Computational Neuroscience. Frontiers Research Foundation, 2014. https://doi.org/10.3389/fncom.2014.00057. ieee: C. Savin and J. Triesch, “Emergence of task-dependent representations in working memory circuits,” Frontiers in Computational Neuroscience, vol. 8, no. MAY. Frontiers Research Foundation, 2014. ista: Savin C, Triesch J. 2014. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 8(MAY), 57. mla: Savin, Cristina, and Jochen Triesch. “Emergence of Task-Dependent Representations in Working Memory Circuits.” Frontiers in Computational Neuroscience, vol. 8, no. MAY, 57, Frontiers Research Foundation, 2014, doi:10.3389/fncom.2014.00057. short: C. Savin, J. Triesch, Frontiers in Computational Neuroscience 8 (2014). date_created: 2018-12-11T11:54:46Z date_published: 2014-05-28T00:00:00Z date_updated: 2021-01-12T06:54:09Z day: '28' department: - _id: GaTk doi: 10.3389/fncom.2014.00057 intvolume: ' 8' issue: MAY language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4035833/ month: '05' oa: 1 oa_version: Submitted Version publication: Frontiers in Computational Neuroscience publication_status: published publisher: Frontiers Research Foundation publist_id: '5163' quality_controlled: '1' scopus_import: 1 status: public title: Emergence of task-dependent representations in working memory circuits type: journal_article user_id: 4435EBFC-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2014' ... --- _id: '2028' abstract: - lang: eng text: 'Understanding the dynamics of noisy neurons remains an important challenge in neuroscience. Here, we describe a simple probabilistic model that accurately describes the firing behavior in a large class (type II) of neurons. To demonstrate the usefulness of this model, we show how it accurately predicts the interspike interval (ISI) distributions, bursting patterns and mean firing rates found by: (1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental data from squid giant axon with a noisy input current and (3) experimental data on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple model has 6 parameters, however, in some cases, two of these parameters are coupled and only 5 parameters account for much of the known behavior. From these parameters, many properties of spiking can be found through simple calculation. Thus, we show how the complex effects of noise can be understood through a simple and general probabilistic model.' acknowledgement: 'This work is supported by AFOSR grant FA 9550-11-1-0165, program grant RPG 24/2012 from the Human Frontiers of Science (DBF) and travel support from the European Commission Marie Curie International Reintegration Grant PIRG04-GA-2008-239429 (KB). DP was supported by NIHR01 GM104987 and the Wyss Institute of Biologically Inspired Engineering. ' article_processing_charge: No author: - first_name: Katarina full_name: Bodova, Katarina id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87 last_name: Bodova orcid: 0000-0002-7214-0171 - first_name: David full_name: Paydarfar, David last_name: Paydarfar - first_name: Daniel full_name: Forger, Daniel last_name: Forger citation: ama: Bodova K, Paydarfar D, Forger D. Characterizing spiking in noisy type II neurons. Journal of Theoretical Biology. 2014;365:40-54. doi:10.1016/j.jtbi.2014.09.041 apa: Bodova, K., Paydarfar, D., & Forger, D. (2014). Characterizing spiking in noisy type II neurons. Journal of Theoretical Biology. Academic Press. https://doi.org/10.1016/j.jtbi.2014.09.041 chicago: Bodova, Katarina, David Paydarfar, and Daniel Forger. “Characterizing Spiking in Noisy Type II Neurons.” Journal of Theoretical Biology. Academic Press, 2014. https://doi.org/10.1016/j.jtbi.2014.09.041. ieee: K. Bodova, D. Paydarfar, and D. Forger, “Characterizing spiking in noisy type II neurons,” Journal of Theoretical Biology, vol. 365. Academic Press, pp. 40–54, 2014. ista: Bodova K, Paydarfar D, Forger D. 2014. Characterizing spiking in noisy type II neurons. Journal of Theoretical Biology. 365, 40–54. mla: Bodova, Katarina, et al. “Characterizing Spiking in Noisy Type II Neurons.” Journal of Theoretical Biology, vol. 365, Academic Press, 2014, pp. 40–54, doi:10.1016/j.jtbi.2014.09.041. short: K. Bodova, D. Paydarfar, D. Forger, Journal of Theoretical Biology 365 (2014) 40–54. date_created: 2018-12-11T11:55:18Z date_published: 2014-10-12T00:00:00Z date_updated: 2022-08-25T14:00:47Z day: '12' ddc: - '570' department: - _id: GaTk doi: 10.1016/j.jtbi.2014.09.041 file: - access_level: open_access checksum: a9dbae18d3233b3dab6944fd3f2cd49e content_type: application/pdf creator: system date_created: 2018-12-12T10:17:58Z date_updated: 2020-07-14T12:45:25Z file_id: '5316' file_name: IST-2016-444-v1+1_1-s2.0-S0022519314005888-main.pdf file_size: 2679222 relation: main_file file_date_updated: 2020-07-14T12:45:25Z has_accepted_license: '1' intvolume: ' 365' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '10' oa: 1 oa_version: Published Version page: 40 - 54 publication: ' Journal of Theoretical Biology' publication_status: published publisher: Academic Press publist_id: '5043' pubrep_id: '444' quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1016/j.jtbi.2015.03.013 scopus_import: '1' status: public title: Characterizing spiking in noisy type II neurons tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 365 year: '2014' ... --- _id: '2183' abstract: - lang: eng text: 'We describe a simple adaptive network of coupled chaotic maps. The network reaches a stationary state (frozen topology) for all values of the coupling parameter, although the dynamics of the maps at the nodes of the network can be nontrivial. The structure of the network shows interesting hierarchical properties and in certain parameter regions the dynamics is polysynchronous: Nodes can be divided in differently synchronized classes but, contrary to cluster synchronization, nodes in the same class need not be connected to each other. These complicated synchrony patterns have been conjectured to play roles in systems biology and circuits. The adaptive system we study describes ways whereby this behavior can evolve from undifferentiated nodes.' acknowledgement: "V.B.S. is partially supported by contract MEC (Grant No. AYA2010-22111-C03-02).\r\n" article_number: '062809' article_processing_charge: No author: - first_name: Vicente full_name: Botella Soler, Vicente id: 421234E8-F248-11E8-B48F-1D18A9856A87 last_name: Botella Soler orcid: 0000-0002-8790-1914 - first_name: Paul full_name: Glendinning, Paul last_name: Glendinning citation: ama: Botella Soler V, Glendinning P. Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 2014;89(6). doi:10.1103/PhysRevE.89.062809 apa: Botella Soler, V., & Glendinning, P. (2014). Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics. https://doi.org/10.1103/PhysRevE.89.062809 chicago: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft Matter Physics. American Institute of Physics, 2014. https://doi.org/10.1103/PhysRevE.89.062809. ieee: V. Botella Soler and P. Glendinning, “Hierarchy and polysynchrony in an adaptive network ,” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 6. American Institute of Physics, 2014. ista: Botella Soler V, Glendinning P. 2014. Hierarchy and polysynchrony in an adaptive network . Physical Review E Statistical Nonlinear and Soft Matter Physics. 89(6), 062809. mla: Botella Soler, Vicente, and Paul Glendinning. “Hierarchy and Polysynchrony in an Adaptive Network .” Physical Review E Statistical Nonlinear and Soft Matter Physics, vol. 89, no. 6, 062809, American Institute of Physics, 2014, doi:10.1103/PhysRevE.89.062809. short: V. Botella Soler, P. Glendinning, Physical Review E Statistical Nonlinear and Soft Matter Physics 89 (2014). date_created: 2018-12-11T11:56:11Z date_published: 2014-06-16T00:00:00Z date_updated: 2022-08-25T14:04:45Z day: '16' department: - _id: GaTk doi: 10.1103/PhysRevE.89.062809 ec_funded: 1 intvolume: ' 89' issue: '6' language: - iso: eng main_file_link: - open_access: '1' url: http://arxiv.org/abs/1403.3209 month: '06' oa: 1 oa_version: Preprint project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: Physical Review E Statistical Nonlinear and Soft Matter Physics publication_status: published publisher: American Institute of Physics publist_id: '4798' quality_controlled: '1' scopus_import: '1' status: public title: 'Hierarchy and polysynchrony in an adaptive network ' type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 89 year: '2014' ... --- _id: '2231' abstract: - lang: eng text: Based on the measurements of noise in gene expression performed during the past decade, it has become customary to think of gene regulation in terms of a two-state model, where the promoter of a gene can stochastically switch between an ON and an OFF state. As experiments are becoming increasingly precise and the deviations from the two-state model start to be observable, we ask about the experimental signatures of complex multistate promoters, as well as the functional consequences of this additional complexity. In detail, we i), extend the calculations for noise in gene expression to promoters described by state transition diagrams with multiple states, ii), systematically compute the experimentally accessible noise characteristics for these complex promoters, and iii), use information theory to evaluate the channel capacities of complex promoter architectures and compare them with the baseline provided by the two-state model. We find that adding internal states to the promoter generically decreases channel capacity, except in certain cases, three of which (cooperativity, dual-role regulation, promoter cycling) we analyze in detail. author: - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 citation: ama: Rieckh G, Tkačik G. Noise and information transmission in promoters with multiple internal states. Biophysical Journal. 2014;106(5):1194-1204. doi:10.1016/j.bpj.2014.01.014 apa: Rieckh, G., & Tkačik, G. (2014). Noise and information transmission in promoters with multiple internal states. Biophysical Journal. Biophysical Society. https://doi.org/10.1016/j.bpj.2014.01.014 chicago: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in Promoters with Multiple Internal States.” Biophysical Journal. Biophysical Society, 2014. https://doi.org/10.1016/j.bpj.2014.01.014. ieee: G. Rieckh and G. Tkačik, “Noise and information transmission in promoters with multiple internal states,” Biophysical Journal, vol. 106, no. 5. Biophysical Society, pp. 1194–1204, 2014. ista: Rieckh G, Tkačik G. 2014. Noise and information transmission in promoters with multiple internal states. Biophysical Journal. 106(5), 1194–1204. mla: Rieckh, Georg, and Gašper Tkačik. “Noise and Information Transmission in Promoters with Multiple Internal States.” Biophysical Journal, vol. 106, no. 5, Biophysical Society, 2014, pp. 1194–204, doi:10.1016/j.bpj.2014.01.014. short: G. Rieckh, G. Tkačik, Biophysical Journal 106 (2014) 1194–1204. date_created: 2018-12-11T11:56:28Z date_published: 2014-03-04T00:00:00Z date_updated: 2021-01-12T06:56:10Z day: '04' department: - _id: GaTk doi: 10.1016/j.bpj.2014.01.014 external_id: pmid: - '24606943' intvolume: ' 106' issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026790/ month: '03' oa: 1 oa_version: Submitted Version page: 1194 - 1204 pmid: 1 publication: Biophysical Journal publication_identifier: issn: - '00063495' publication_status: published publisher: Biophysical Society publist_id: '4730' quality_controlled: '1' scopus_import: 1 status: public title: Noise and information transmission in promoters with multiple internal states type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 106 year: '2014' ...