Journal article
Columnar grouping preserves synchronization in neuronal networks with distance-dependent time delays
Physical review. E, v 101(2), pp 022408-022408
14 Feb 2020
PMID: 32168702
Abstract
Neuronal connectivity at the cellular level in the cerebral cortex is far from random, with characteristics that point to a hierarchical design with intricately connected neuronal clusters. Here we investigate computationally the effects of varying neuronal cluster connectivity on network synchronization for two different spatial distributions of clusters: one where clusters are arranged in columns in a grid and the other where neurons from different clusters are spatially intermixed. We characterize each case by measuring the degree of neuronal spiking synchrony as a function of the number of connections per neuron and the degree of intercluster connectivity. We find that in both cases as the number of connections per neuron increases, there is an asynchronous to synchronous transition dependent only on intrinsic parameters of the biophysical model. We also observe in both cases that with very low intercluster connectivity clusters have independent firing dynamics yielding a low degree of synchrony. More importantly, we find that for a high number of connections per neuron but intermediate intercluster connectivity, the two spatial distributions of clusters differ in their response where the clusters in a grid have a higher degree of synchrony than the clusters that are intermixed.
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Details
- Title
- Columnar grouping preserves synchronization in neuronal networks with distance-dependent time delays
- Creators
- Joseph S. Tumulty - Drexel UniversityMichael Royster - Drexel UniversityLuis Cruz - Drexel University
- Publication Details
- Physical review. E, v 101(2), pp 022408-022408
- Publisher
- Amer Physical Soc
- Number of pages
- 12
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Physics
- Web of Science ID
- WOS:000513572500003
- Scopus ID
- 2-s2.0-85080071689
- Other Identifier
- 991019167923204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Physics, Fluids & Plasmas
- Physics, Mathematical