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Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons [article]

Yann Zerlaut, Sandrine Chemla, Frederic Chavane, Alain Destexhe
<span title="2017-07-26">2017</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Here, we present a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions.  ...  Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean-field formalism to model such signals.  ...  Acknowledgments Research supported by the CNRS, the ICODE excellence network, the European Community (Human Brain Project H2020-720270 to A.D., FET Grant BrainScaleS FP7-269921 to A.D. and F.C) and the  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/168385">doi:10.1101/168385</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7shsbi25rfechb4ikjqitqsghy">fatcat:7shsbi25rfechb4ikjqitqsghy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190502205459/https://www.biorxiv.org/content/biorxiv/early/2017/11/12/168385.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a4/54/a454ce5a35e7f138c34037338c877a8a13c2eb36.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/168385"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons

Yann Zerlaut, Sandrine Chemla, Frederic Chavane, Alain Destexhe
<span title="2017-11-15">2017</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2awqvcobm5bw3bostcqrykczhe" style="color: black;">Journal of Computational Neuroscience</a> </i> &nbsp;
Here, we present a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions.  ...  Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean-field formalism to model such signals.  ...  Acknowledgments Research supported by the CNRS, the ICODE excellence network, the European Community (Human Brain Project H2020-720270 to A.D., FET Grant BrainScaleS FP7-269921 to A.D. and F.C) and the  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10827-017-0668-2">doi:10.1007/s10827-017-0668-2</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29139050">pmid:29139050</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j3pzsxqcrjbznhfg4n6ljgtpci">fatcat:j3pzsxqcrjbznhfg4n6ljgtpci</a> </span>
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Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size

Tilo Schwalger, Moritz Deger, Wulfram Gerstner, Lyle J. Graham
<span title="2017-04-19">2017</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ch57atmlprauhhbqdf7x4ytejm" style="color: black;">PLoS Computational Biology</a> </i> &nbsp;
Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models.  ...  The mesoscopic equations are employed to rapidly simulate a model of a local cortical microcircuit consisting of eight neuron types.  ...  The same mean-field arguments as for the current-based model carry over to the case of conductance-based synapses.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pcbi.1005507">doi:10.1371/journal.pcbi.1005507</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28422957">pmid:28422957</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5415267/">pmcid:PMC5415267</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dxz2ilgoqvbjpghcte67cwtdde">fatcat:dxz2ilgoqvbjpghcte67cwtdde</a> </span>
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A mean-field model for conductance-based networks of adaptive exponential integrate-and-fire neurons [article]

Yann Zerlaut, Alain Destexhe
<span title="2017-03-02">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Here, we investigate a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions.  ...  We conclude that the Master Equation formalism can yield mean-field models that predict well the behavior of nonlinear networks with conductance-based interactions and various electrophysiolgical properties  ...  Acknowledgments Research supported by the CNRS, the ICODE excellence network, and the European Community (Human Brain Project, H2020-720270).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1703.00698v1">arXiv:1703.00698v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/i5p5tmibfneireobkmkmxg5lyi">fatcat:i5p5tmibfneireobkmkmxg5lyi</a> </span>
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Biologically Realistic Mean-Field Models of Conductance-Based Networks of Spiking Neurons with Adaptation

Matteo di Volo, Alberto Romagnoni, Cristiano Capone, Alain Destexhe
<span title="2019-02-14">2019</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rckx6fqoszfvva5c53bqivu5am" style="color: black;">Neural Computation</a> </i> &nbsp;
Here, we consider such models based on networks of adaptive exponential integrate-and-fire excitatory and inhibitory neurons.  ...  Using a master equation formalism, we derive a mean-field model of such networks and compare it to the full network dynamics.  ...  Acknowledgments We acknowledge funding from the European Union (Human Brain Project H2020-720270 and H2020-785907). We thank Yann Zerlaut for useful discussions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco_a_01173">doi:10.1162/neco_a_01173</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/g6yxjqx2ibh35dfr7ddipukj34">fatcat:g6yxjqx2ibh35dfr7ddipukj34</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210324033245/https://watermark.silverchair.com/neco_a_01173.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAApwwggKYBgkqhkiG9w0BBwagggKJMIIChQIBADCCAn4GCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMQ4N9CTI4PFaIFtqmAgEQgIICT96uM7-MZkHwJG-4GmWCzqRDR6vyXFWxI49-XDx3cYsC7fKmUwycEADCqsEanfuzA3sH3zcTvVjJaLSOI12BIW7OUv-0q-oeeZj4HdIe4BcOztempxAfPAYEqx4OWfyFR-w95gcawBDtKEymcgZEY4AXPJKN_X6gBDkDFaIMsRn_iemr0MIbSHMwykUb_BipL8SgL-APf5wHMPckqWHKbAx4RVtIfWz4_Uo_eASYPC_SrfZjL3Yi560736BzmCuqrbFbEhlsB6p4sfeU04X1S0UM8s4iUA5cL1xbZ7KOqvKpP1JgCfk_oJ0eRakzJ-WLo8emfUB8kkoUOFx8fXswEBsXfkmNM_FNOOYRdXO5RJpPYMionFY28A-s6H7MgsZYn05Fkb9FW6mGnngBocAOmwVdEJ0dbKik_BQo4NoXw_6R_Ik5E40mMG3deGLevMrB5M-nos1A0G-m93sOU2vK0fyrIrhyrjAulBzJ9EB_W-u5GTdrqsmFo1F-O1om6R6kJJFUkbwHU3Y2yJMx4L2CZGKQP9HBbrb-GyKEzsqXQiyAmy5Ivq-ZD4WsgnB5Y0mkI_I2Dzxuc3ftNZZMzvKW8DR94Q74_FhK433YhtdfZNskcCCv0qlQtwf6xVGXbENO2OTV_BusR-RPS2yKf7GeEvG4HPXl7kgujbcFE6ZADWzI5zPlpOts5dwnltWWpVrQfEXZ74MkUzzKHXM6rNRv5efTOJMaDW4nO8ylTzVAFM72ytld7dm9Ai4f_BOGVcYh-g2MU2wMbJniYnfUDrZKgA" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/43/ea/43eaa55f1de1133e62b4e3922996d343ba294dc6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco_a_01173"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> mitpressjournals.org </button> </a>

Biologically realistic mean-field models of conductance-based networks of spiking neurons with adaptation [article]

Matteo di Volo, Alberto Romagnoni, Cristiano Capone, Alain Destexhe
<span title="2018-06-20">2018</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Here, we consider such models based on networks of Adaptive exponential Integrate and fire excitatory and inhibitory neurons.  ...  Using a Master Equation formalism, we derive a mean-field model of such networks and compare it to the full network dynamics.  ...  Acknowledgements We acknowledge funding from the European Union (Human Brain Project H2020-720270 and H2020-785907). We thank Yann Zerlaut for useful discussions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/352393">doi:10.1101/352393</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fd46ihny7vgb3mwwo6ifntotgm">fatcat:fd46ihny7vgb3mwwo6ifntotgm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190502092514/https://www.biorxiv.org/content/biorxiv/early/2018/08/25/352393.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/47/f8/47f8d1ac8df66619a1c7a705cc250587f6be0cbe.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/352393"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

A novel density-based neural mass model for simulating neuronal network dynamics with conductance-based synapses and membrane current adaptation [article]

Chih-Hsu Huang, Chou-Ching K Lin
<span title="2020-10-10">2020</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
exponential integrate-and-fire neurons.  ...  Here, based on a colored-noise population density method, we derived a novel neural mass model, termed density-based neural mass model (dNMM), as the mean-field description of network dynamics of adaptive  ...  Acknowledgments 546 This study has been supported by the Ministry of Science and Technology, Taiwan, Republic of China 547 under grand no. 108-2321-B-006-024-MY2. 548  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2020.10.09.334144">doi:10.1101/2020.10.09.334144</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vmpn625ylrc4bn3pwez5wxxvoa">fatcat:vmpn625ylrc4bn3pwez5wxxvoa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429133632/https://www.biorxiv.org/content/biorxiv/early/2020/10/10/2020.10.09.334144.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4b/48/4b483e24e096e30ae6051c991de3a1c1a254bf84.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2020.10.09.334144"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

Simo Vanni, Fariba Sharifian, Hanna Heikkinen, Ricardo Vigário
<span title="">2015</span> <i title="American Physiological Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nr2f6gixzrgdlloxlemhfdztdi" style="color: black;">Journal of Neurophysiology</a> </i> &nbsp;
A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input. Biol Cybern 95: 1-19, 2006. Buxton RB, Wong EC, Frank LR.  ...  Simulation of networks of spiking neurons: a review of tools and strategies. J Comput Neurosci 23: 349 -398, 2007. Brunel N, van Rossum MCW. Lapicque's 1907 paper: from frogs to integrate-and-fire.  ...  Our exemplary model for V1 uses an extension of the IF neuron, the exponential integrate and fire (EIF) neuron (Fourcaud-Trocme et al. 2003 ).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1152/jn.00332.2014">doi:10.1152/jn.00332.2014</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/25972586">pmid:25972586</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4533065/">pmcid:PMC4533065</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eu73lu4yn5fvbg5umdw6gtll5y">fatcat:eu73lu4yn5fvbg5umdw6gtll5y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190226071002/http://pdfs.semanticscholar.org/6e25/0cdb0b583642bc026bc0720e93aadbb2479f.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6e/25/6e250cdb0b583642bc026bc0720e93aadbb2479f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1152/jn.00332.2014"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4533065" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin-Huxley models [article]

Mallory Carlu, Omar Chehab, Leonardo Dalla Porta, Damien Depannemaecker, Charlotte Herice, Maciej Jedynak, Elif Koksal Ersoz, Paolo Muratore, Selma Souihel, Cristiano Capone, Yann Zerlaut, Alain Destexhe (+1 others)
<span title="2019-12-10">2019</span> <i title="Cold Spring Harbor Laboratory"> biorxiv/medrxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We present a mean-field formalism able to predict the collective dynamics of large networks of conductance-based interacting spiking neurons.  ...  We apply this formalism to several neuronal models, from the simplest Adaptive Exponential Integrate-and-Fire model to the more complex Hodgkin-Huxley and Morris-Lecar models.  ...  Adaptive Exponential Integrate-and-Fire and Morris-Lecar).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/870345">doi:10.1101/870345</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rxcrff3ovzcitosavxfhkju2hy">fatcat:rxcrff3ovzcitosavxfhkju2hy</a> </span>
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Bridging Single Neuron Dynamics to Global Brain States

Jennifer S. Goldman, Núria Tort-Colet, Matteo di Volo, Eduarda Susin, Jules Bouté, Melissa Dali, Mallory Carlu, Trang-Anh Nghiem, Tomasz Górski, Alain Destexhe
<span title="2019-12-06">2019</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/j33hgvvadjhazfxeupgxga54ai" style="color: black;">Frontiers in Systems Neuroscience</a> </i> &nbsp;
to macroscopic brain dynamics through mesoscopic scales.  ...  Not unlike how microscopic interactions between molecules underlie structures formed in macroscopic states of matter, using statistical physics, the dynamics of microscopic neural phenomena can be linked  ...  Jaynes, Vicente Medel, Archibald Parsons, Mattias Peuvrier, Wolf Singer, Kat Uesat, Bahar Hazal Yalçnkaya, and Yann Zerlaut for useful discussion of the manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fnsys.2019.00075">doi:10.3389/fnsys.2019.00075</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31866837">pmid:31866837</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6908479/">pmcid:PMC6908479</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lhryneyr7baclf2iodmixh4fty">fatcat:lhryneyr7baclf2iodmixh4fty</a> </span>
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Inferring Network Dynamics and Neuron Properties from Population Recordings

Daniele Linaro, Marco Storace, Maurizio Mattia
<span title="">2011</span> <i title="Frontiers Media SA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/oqtegebkbzdxhnnm6apa2dr4ja" style="color: black;">Frontiers in Computational Neuroscience</a> </i> &nbsp;
For this purpose, we propose a novel model-driven identification procedure and apply it to sparsely connected populations of excitatory integrateand-fire neurons with spike frequency adaptation (SFA).  ...  While several available methods assume generic expressions for the system as a black box, we adopt a mean-field theory for the evolution of the network transparently parameterized by identified elements  ...  Cao for a careful reading of the manuscript and Reviewers for helpful comments. Maurizio Mattia is supported by the EU grant to the CORONET project (ref. 269459).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fncom.2011.00043">doi:10.3389/fncom.2011.00043</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/22016731">pmid:22016731</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3191764/">pmcid:PMC3191764</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xfqxjomfafb77ei4yqv56pljs4">fatcat:xfqxjomfafb77ei4yqv56pljs4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829215000/https://fjfsdata01prod.blob.core.windows.net/articles/files/11043/pubmed-zip/.versions/4/.package-entries/fncom-05-00043-r3/fncom-05-00043.pdf?sv=2015-12-11&amp;sr=b&amp;sig=s06btOvh1pXMLGGYOMRJHE2dplyDyn9hhx0Qa%2FBBxJk%3D&amp;se=2017-08-29T21%3A50%3A03Z&amp;sp=r&amp;rscd=attachment%3B%20filename%2A%3DUTF-8%27%27fncom-05-00043.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ca/d9/cad94dcf4e6ebc47342580ef11db5836a0e8d7e7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3389/fncom.2011.00043"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> frontiersin.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3191764" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Thalamocortical Spectral Transmission Relies on Balanced Input Strengths

Matteo Saponati, Jordi Garcia-Ojalvo, Enrico Cataldo, Alberto Mazzoni
<span title="2021-06-04">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/yzolvh3tdzdbxdcclo7p73uk6e" style="color: black;">Brain Topography</a> </i> &nbsp;
Here we investigate this issue with a spiking network model of feedforward connectivity between thalamus and primary sensory cortex reproducing the local field potential of both areas.  ...  , (ii) the gamma resonance dynamics of cortical networks hampers oscillations over the 10–20 Hz range thus weakening alpha range oscillations.  ...  Neuronal dynamics is simulated with the Adaptive Exponential Integrate-and-Fire model (Brette and Gerstner 2005) (1) m dv i, dt = −(v i, − E l ) + Δ exp v i, − v th Δ − 1 g l w i, + 1 g l ∑ ,j C , ij  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10548-021-00851-3">doi:10.1007/s10548-021-00851-3</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34089121">pmid:34089121</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8813837/">pmcid:PMC8813837</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jhtewqbfzrbq3a2nt75fjaok6y">fatcat:jhtewqbfzrbq3a2nt75fjaok6y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210718071955/https://link.springer.com/content/pdf/10.1007/s10548-021-00851-3.pdf?error=cookies_not_supported&amp;code=8cc7bafd-67c5-4d2a-938d-a212e9bc996c" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/39/e3/39e32555684fe77cc4dcacdd49679d30c933d495.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10548-021-00851-3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8813837" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A Master Equation Formalism for Macroscopic Modeling of Asynchronous Irregular Activity States

Sami El Boustani, Alain Destexhe
<span title="">2009</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rckx6fqoszfvva5c53bqivu5am" style="color: black;">Neural Computation</a> </i> &nbsp;
Neural Computation 21, 46-100 (2009) C 2008 Massachusetts Institute of Technology sparsely connected network of conductance-based neurons.  ...  Using master equation formalism, we derive a second-order mean-field set of ordinary differential equations describing the temporal evolution of randomly connected balanced networks.  ...  We thank Olivier Marre, Pierre Yger, Nicolas Brunel, and Romain Brette for fruitful discussions and comments on the manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.2009.02-08-710">doi:10.1162/neco.2009.02-08-710</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/19210171">pmid:19210171</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tiwvfrnk2vas5g5s7ut32f543a">fatcat:tiwvfrnk2vas5g5s7ut32f543a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721215751/http://cns.iaf.cnrs-gif.fr/files/Master2008.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/26/7c/267c73276d3a12f6896e4b491efe5fa4239b3f5c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.2009.02-08-710"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> mitpressjournals.org </button> </a>

A Master Equation Formalism for Macroscopic Modeling of Asynchronous Irregular Activity States

Sami El Boustani, Alain Destexhe
<span title="2008-08-04">2008</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rckx6fqoszfvva5c53bqivu5am" style="color: black;">Neural Computation</a> </i> &nbsp;
Neural Computation 21, 46-100 (2009) C 2008 Massachusetts Institute of Technology sparsely connected network of conductance-based neurons.  ...  Using master equation formalism, we derive a second-order mean-field set of ordinary differential equations describing the temporal evolution of randomly connected balanced networks.  ...  We thank Olivier Marre, Pierre Yger, Nicolas Brunel, and Romain Brette for fruitful discussions and comments on the manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.2008.02-08-710">doi:10.1162/neco.2008.02-08-710</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/df4oyf2z55ew3dekugzcuu3eke">fatcat:df4oyf2z55ew3dekugzcuu3eke</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721215751/http://cns.iaf.cnrs-gif.fr/files/Master2008.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/26/7c/267c73276d3a12f6896e4b491efe5fa4239b3f5c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco.2008.02-08-710"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> mitpressjournals.org </button> </a>

Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity [article]

Bastian Pietras, Valentin Schmutz, Tilo Schwalger
<span title="2022-04-29">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation.  ...  Crucially, our model is bottom-up: it is analytically derived from the dynamics of finite-size networks of Linear-Nonlinear Poisson neurons with short-term synaptic depression.  ...  Acknowledgments This research has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie grant agreement no. 101032806 and the Swiss  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.01675v2">arXiv:2204.01675v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wx6wrtqk65cg3p6xak2ecket5y">fatcat:wx6wrtqk65cg3p6xak2ecket5y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220507045135/https://arxiv.org/pdf/2204.01675v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/15/22/1522a6c731821c97d0855777639d02f6c076d999.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2204.01675v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>
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