Literature DB >> 26496044

Periodic Forcing of Inhibition-Stabilized Networks: Nonlinear Resonances and Phase-Amplitude Coupling.

Romain Veltz1, Terrence J Sejnowski2.   

Abstract

Inhibition-stabilized networks (ISNs) are neural architectures with strong positive feedback among pyramidal neurons balanced by strong negative feedback from inhibitory interneurons, a circuit element found in the hippocampus and the primary visual cortex. In their working regime, ISNs produce damped oscillations in the [Formula: see text]-range in response to inputs to the inhibitory population. In order to understand the properties of interconnected ISNs, we investigated periodic forcing of ISNs. We show that ISNs can be excited over a range of frequencies and derive properties of the resonance peaks. In particular, we studied the phase-locked solutions, the torus solutions, and the resonance peaks. Periodically forced ISNs respond with (possibly multistable) phase-locked activity, whereas networks with sustained intrinsic oscillations respond more dynamically to periodic inputs with tori. Hence, the dynamics are surprisingly rich, and phase effects alone do not adequately describe the network response. This strengthens the importance of phase-amplitude coupling as opposed to phase-phase coupling in providing multiple frequencies for multiplexing and routing information.

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Year:  2015        PMID: 26496044      PMCID: PMC4763930          DOI: 10.1162/NECO_a_00786

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  37 in total

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5.  Excitatory and inhibitory interactions in localized populations of model neurons.

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Journal:  Biophys J       Date:  1972-01       Impact factor: 4.033

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9.  Regulating Cortical Oscillations in an Inhibition-Stabilized Network.

Authors:  Monika P Jadi; Terrence J Sejnowski
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2014-04-21       Impact factor: 10.961

10.  Phase-amplitude descriptions of neural oscillator models.

Authors:  Kyle Ca Wedgwood; Kevin K Lin; Ruediger Thul; Stephen Coombes
Journal:  J Math Neurosci       Date:  2013-01-24       Impact factor: 1.300

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  6 in total

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5.  A new description of epileptic seizures based on dynamic analysis of a thalamocortical model.

Authors:  H Sohanian Haghighi; A H D Markazi
Journal:  Sci Rep       Date:  2017-10-19       Impact factor: 4.379

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  6 in total

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