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Dimensionally-reduced visual cortical network model predicts network response and connects system- and cellular-level descriptions
2009
Journal of Computational Neuroscience
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We demonstrate that these dimensionally-reduced models are capable of predicting the response to previously un-encountered input and that the coupling between systems-level variables can be used to reconstruct ...
cellular-level functional connectivities. ...
Acknowledgments This work was supported by (ATS) NIH NIBIB005432 and (LT) NSF DMS-0506257. ...
doi:10.1007/s10827-009-0189-8
pmid:19806444
fatcat:bkcfacipl5fddc7nlcdipyojgm
Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons
2017
Journal of Computational Neuroscience
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We compare the predictions of this mean-field model to simulated networks of RS-FS cells, first at the level of the spontaneous activity of the network, which is well predicted by the analytical description ...
Second, we investigate the response of the network to time-varying external input, and show that the mean-field model predicts the response time course of the population. ...
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 ...
doi:10.1007/s10827-017-0668-2
pmid:29139050
fatcat:j3pzsxqcrjbznhfg4n6ljgtpci
Modeling mesoscopic cortical dynamics using a mean-field model of conductance-based networks of adaptive exponential integrate-and-fire neurons
[article]
2017
bioRxiv
pre-print
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We compare the predictions of this mean-field model to simulated networks of RS-FS cells, first at the level of the spontaneous activity of the network, which is well predicted by the analytical description ...
Second, we investigate the response of the network to time-varying external input, and show that the mean-field model predicts the response time course of the population. ...
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 ...
doi:10.1101/168385
fatcat:7shsbi25rfechb4ikjqitqsghy
Large-scale neural recordings call for new insights to link brain and behavior
[article]
2021
arXiv
pre-print
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We next highlight insights obtained from large-scale neural recordings in diverse model systems, and argue that some of these pose a challenge to traditional theoretical frameworks. ...
level of understanding at stake. ...
While the activity of some neurons could be well predicted by their response to visual stimuli, many more cells responded in ways that could not be captured by existing models of cortical function. ...
arXiv:2103.14662v2
fatcat:7sisaxb7gfgu5as2snh3lpd4nu
'Hierarchy' in the organization of brain networks
2020
Philosophical Transactions of the Royal Society of London. Biological Sciences
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Using the example of the organization of the primate visual cortical system, we explore several contexts in which 'hierarchy' is currently used in the description of brain networks. ...
This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'. ...
Indeed, recent work on cat and monkey cortex indicates that cytoarchitecture-based predictive models of laminar origin of connections consistently outperform other predictive models based on features, ...
doi:10.1098/rstb.2019.0319
pmid:32089116
pmcid:PMC7061955
fatcat:ucjoaipajvainhq6iot32toilq
A mean-field model for conductance-based networks of adaptive exponential integrate-and-fire neurons
[article]
2017
arXiv
pre-print
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We compare the predictions of this mean-field model to simulated networks of RS-FS cells, first at the level of the spontaneous activity of the network, which is well predicted by the mean-field model. ...
Second, we investigate the response of the network to time-varying external input, and show that the mean-field model accurately predicts the response time course of the population. ...
Acknowledgments Research supported by the CNRS, the ICODE excellence network, and the European Community (Human Brain Project, H2020-720270). ...
arXiv:1703.00698v1
fatcat:i5p5tmibfneireobkmkmxg5lyi
Shaping the Cortical Landscape: Functions and Mechanisms of Top-Down Cortical Feedback Pathways
2020
Frontiers in Systems Neuroscience
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At the cellular level, cortical feedback pathways target multiple excitatory and inhibitory populations. ...
Third, we review the conserved cellular targets and circuit impacts of cortical feedback. ...
Behzad Zareian for helpful discussions and comments on a previous version of this manuscript. ...
doi:10.3389/fnsys.2020.00033
pmid:32587506
pmcid:PMC7299084
fatcat:lgrrjbe5rnctpa2kh7r7zhakkq
Selective Activation of Resting-State Networks following Focal Stimulation in a Connectome-Based Network Model of the Human Brain
2016
eNeuro
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Here, we study the effect of SC on the network response to stimulation. We use a human whole-brain network model comprising long-and short-range connections. ...
We systematically activate each cortical or thalamic area, and investigate the network response as a function of its short-and long-range SC. ...
This research was supported by the Brain Network Recovery Group through the James S. ...
doi:10.1523/eneuro.0068-16.2016
pmid:27752540
pmcid:PMC5052665
fatcat:ncowfeb7ufeefbytwoz4n6xxpm
27th Annual Computational Neuroscience Meeting (CNS*2018): Part One
2018
BMC Neuroscience
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Networking Fund of the Helmholtz Association and the Helmholtz Portfolio theme "Supercomputing and Modeling for the Human Brain" and the European Union Seventh Framework Programme (FP7/2007-2013) under ...
Acknowledgements We acknowledge the Initiative and Networking Fund of the Helmholtz Association, the Helmholtz Association through the Helmholtz Portfolio Theme"Supercomputing and Modeling for the Human ...
The resulting motif description provides a reduced order model of the network dynamics. Through this framework we compute the dimensionality of the response. ...
doi:10.1186/s12868-018-0452-x
pmid:30373544
pmcid:PMC6205781
fatcat:xv7pgbp76zbdfksl545xof2vzy
COMPLEXITY IN NEURONAL NETWORKS
[chapter]
2007
Biological Networks
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and in terms of relational topology at the network connectivity level. ...
Indeed, such systems can be viewed as low-dimensional deterministic chaotic systems. ...
doi:10.1142/9789812772367_0009
fatcat:soddgualmrggbdtkp2h5yvkexe
Explanatory models in neuroscience: Part 1 – taking mechanistic abstraction seriously
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2104.01490v1 fatcat:p7ztp7iivvftbf6bnz53p2k62i
These criteria require us, first, to identify a level of description that is both abstract but detailed enough to be "runnable", and then, to construct model-to-brain mappings using the same principles ...
Despite the recent success of neural network models in mimicking animal performance on visual perceptual tasks, critics worry that these models fail to illuminate brain function. ...
real brain's ventral visual system to that same abstract level of description. ...
arXiv:2104.01490v2
fatcat:24fm2ykjjrgddnt442qiowd6du
Bringing Anatomical Information into Neuronal Network Models
[article]
2020
arXiv
pre-print
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Such methods of 'predictive connectomics' estimate connectivity where the data are lacking based on statistical relationships with known quantities. ...
With this chapter we aim to provide guidance to modelers by describing the main types of anatomical data that may be useful for informing neuronal network models. ...
Ongoing research addresses the three-dimensional cellular-level reconstruction of brains at 1 µm resolution, which poses considerable techical challenges for human brains due to their size and topological ...
arXiv:2007.00031v2
fatcat:lud5jok65re5rhecxjtsis3x5u
Neurodynamics of cognition and consciousness
2009
Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems - PerMIS '09
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findings, development of dynamical neural memories, and applications of dynamical approaches to intelligent system. ...
Experimental evidence in humans and other mammalians indicates that complex neurodynamics is crucial for the emergence of higher-level intelligence and consciousness. ...
Dynamic models span from the cellular level to populations, including massively recurrent architectures with complex dynamics [14] [15] [16] . ...
doi:10.1145/1865909.1865939
dblp:conf/permis/0001F09
fatcat:ouyztlnjpbf7rhqi2hxpoug5uq
27th Annual Computational Neuroscience Meeting (CNS*2018): Part Two
2018
BMC Neuroscience
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P271
Predicting runway excitation in nonlinear Hawkes processes ...
Acknowledgments JB was supported by NIH grant F31DC016811 to JB and JB, SC, and RG were supported by NIH R01MH1006674 to SC. ...
stereotypy of cortical activity, and a reduction of its dimensionality. ...
doi:10.1186/s12868-018-0451-y
fatcat:afgrjlnjgjarldkuwo3e2pt5sm
Adaptation of spontaneous activity in the developing visual cortex
2021
eLife
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We postulated that local events shape cortical input selectivity and topography, while global events homeostatically regulate connection strength. ...
We confirmed this prediction by analyzing in vivo spontaneous cortical activity. ...
and ALWOP.216; ALW Vici, no. 865.12.001) and the "Stichting Vrienden van het Herseninstituut" (NZ, CL). ...
doi:10.7554/elife.61619
pmid:33722342
fatcat:ebb75fbm5bghpnw2kc3ifibiay
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