Literature DB >> 10490940

Synchrony and desynchrony in integrate-and-fire oscillators.

S R Campbell1, D L Wang, C Jayaprakash.   

Abstract

Due to many experimental reports of synchronous neural activity in the brain, there is much interest in understanding synchronization in networks of neural oscillators and its potential for computing perceptual organization. Contrary to Hopfield and Herz (1995), we find that networks of locally coupled integrate-and-fire oscillators can quickly synchronize. Furthermore, we examine the time needed to synchronize such networks. We observe that these networks synchronize at times proportional to the logarithm of their size, and we give the parameters used to control the rate of synchronization. Inspired by locally excitatory globally inhibitory oscillator network (LEGION) dynamics with relaxation oscillators (Terman & Wang, 1995), we find that global inhibition can play a similar role of desynchronization in a network of integrate-and-fire oscillators. We illustrate that a LEGION architecture with integrate-and-fire oscillators can be similarly used to address image analysis.

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Year:  1999        PMID: 10490940     DOI: 10.1162/089976699300016160

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


  5 in total

1.  Long-term meditators self-induce high-amplitude gamma synchrony during mental practice.

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Review 2.  Cognitive architecture of perceptual organization: from neurons to gnosons.

Authors:  Peter A van der Helm
Journal:  Cogn Process       Date:  2011-11-16

3.  Measuring predictability of autonomous network transitions into bursting dynamics.

Authors:  Sima Mofakham; Michal Zochowski
Journal:  PLoS One       Date:  2015-04-09       Impact factor: 3.240

4.  Biologically inspired information processing and synchronization in ensembles of non-identical threshold-potential nanostructures.

Authors:  Javier Cervera; José A Manzanares; Salvador Mafé
Journal:  PLoS One       Date:  2013-01-22       Impact factor: 3.240

5.  An Oscillatory Neural Autoencoder Based on Frequency Modulation and Multiplexing.

Authors:  Karthik Soman; Vignesh Muralidharan; V Srinivasa Chakravarthy
Journal:  Front Comput Neurosci       Date:  2018-07-10       Impact factor: 2.380

  5 in total

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