This title appears in the Scientific Report :
2016
Please use the identifier:
http://hdl.handle.net/2128/9848 in citations.
Correlated activity of periodically driven binary networks
Correlated activity of periodically driven binary networks
Experiments showed that excess synchronous spike events are locked to the phase of LFP beta-oscillations more strongly than spikes not part of such events [Denker et al. 2011, Cereb. Cortex]. To identify themechanisms by which correlations depend on the phase of the LFP,which primarily reflects inpu...
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Personal Name(s): | Kühn, Tobias (Corresponding author) |
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Denker, Michael / Mana, PierGianLuca / Grün, Sonja / Helias, Moritz | |
Contributing Institute: |
Computational and Systems Neuroscience; INM-6 |
Imprint: |
2016
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Conference: | 80. Jahrestagung der DPG und DPG-Frühjahrstagung, Regensburg (Germany), 2016-03-06 - 2016-03-11 |
Document Type: |
Abstract |
Research Program: |
Theory of multi-scale neuronal networks The Human Brain Project Supercomputing and Modelling for the Human Brain Theory, modelling and simulation Connectivity and Activity |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Experiments showed that excess synchronous spike events are locked to the phase of LFP beta-oscillations more strongly than spikes not part of such events [Denker et al. 2011, Cereb. Cortex]. To identify themechanisms by which correlations depend on the phase of the LFP,which primarily reflects input activity, we examine a balanced network of homogeneously connected binary model neurons [Ginzburg etal. 1994, PRE] receiving input from a sinusoidal perturbation. The Glauber dynamics of the network is simulated and approximated by mean-field theory. Treating the periodic input in linear response theory,the cyclostationary first two moments are analytically computed. They agree with their simulated counterparts over a wide parameter range. The zero-time lag correlations consist of two terms, one due to the modulated susceptibility (via the external input and network feedback) and one due to the time-varying autocorrelations. For some parameters, this leads to resonant correlations and non-resonant mean activities. Our results can help to answer the salient question how oscillations in mesoscopic signals and spike correlations interact. Supported by the Helmholtz foundation (VH-NG-1028, SMHB); EUGrant 604102 (HBP). Simulations with NEST (nest-simulator.org). |