Literature DB >> 24571097

Effect of heterogeneity and noise on cross frequency phase-phase and phase-amplitude coupling.

Ruben Tikidji-Hamburyan1, Eric C Lin, Sonia Gasparini, Carmen C Canavier.   

Abstract

Cross-frequency coupling is hypothesized to play a functional role in neural computation. We apply phase resetting theory to two types of cross-frequency coupling that can occur when a slower oscillator periodically forces one or more oscillators: phase-phase coupling, in which the two oscillations are phase-locked, and phase-amplitude coupling, in which the amplitude of the driven oscillation is modulated. Our first result is that the shape of the phase resetting curve predicts the tightness of locking to a pulsatile forcing periodic input at any ratio of forced to intrinsic period; the tightness of the locking decreases as the ratio increases. Theoretical expressions were obtained for the probability density of the phases for a population of heterogeneous oscillators or a noisy single oscillator. Results were confirmed using two types of simulated networks and experiments on hippocampal CA1 neurons. Theoretical expressions were also obtained and confirmed for the probability density of N spike times within a single cycle of low frequency forcing. The second result is a suggested mechanism for phase-amplitude coupling in which progressive desynchronization leads to decreasing amplitude during a low frequency forcing cycle. Network simulations confirmed the theoretical viability of this mechanism, and that it generalizes to more diffuse input.

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Year:  2014        PMID: 24571097      PMCID: PMC3972019          DOI: 10.3109/0954898X.2014.886781

Source DB:  PubMed          Journal:  Network        ISSN: 0954-898X            Impact factor:   1.273


  37 in total

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4.  The gamma oscillation: master or slave?

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5.  Type-II phase resetting curve is optimal for stochastic synchrony.

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Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-07-16

6.  Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model.

Authors:  X J Wang; G Buzsáki
Journal:  J Neurosci       Date:  1996-10-15       Impact factor: 6.167

7.  Synchrony in excitatory neural networks.

Authors:  D Hansel; G Mato; C Meunier
Journal:  Neural Comput       Date:  1995-03       Impact factor: 2.026

Review 8.  The functional role of cross-frequency coupling.

Authors:  Ryan T Canolty; Robert T Knight
Journal:  Trends Cogn Sci       Date:  2010-11       Impact factor: 20.229

Review 9.  Cellular bases of hippocampal EEG in the behaving rat.

Authors:  G Buzsáki; L W Leung; C H Vanderwolf
Journal:  Brain Res       Date:  1983-10       Impact factor: 3.252

10.  Cross-frequency coupling between neuronal oscillations.

Authors:  Ole Jensen; Laura L Colgin
Journal:  Trends Cogn Sci       Date:  2007-06-04       Impact factor: 20.229

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  4 in total

1.  Feedback control of variability in the cycle period of a central pattern generator.

Authors:  Ryan M Hooper; Ruben A Tikidji-Hamburyan; Carmen C Canavier; Astrid A Prinz
Journal:  J Neurophysiol       Date:  2015-09-02       Impact factor: 2.714

2.  Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period.

Authors:  Sharon E Norman; Robert J Butera; Carmen C Canavier
Journal:  J Neurophysiol       Date:  2016-06-08       Impact factor: 2.714

Review 3.  Phase-resetting as a tool of information transmission.

Authors:  Carmen C Canavier
Journal:  Curr Opin Neurobiol       Date:  2014-12-17       Impact factor: 6.627

4.  Slow noise in the period of a biological oscillator underlies gradual trends and abrupt transitions in phasic relationships in hybrid neural networks.

Authors:  Umeshkanta S Thounaojam; Jianxia Cui; Sharon E Norman; Robert J Butera; Carmen C Canavier
Journal:  PLoS Comput Biol       Date:  2014-05-15       Impact factor: 4.475

  4 in total

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