The role of degree distribution in shaping the dynamics in networks of sparsely connected spiking neurons
Neuronal network models often assume a fixed probability of connectionbetween neurons. This assumption leads to random networks withbinomial in-degree and out-degree distributions which are relatively narrow. Here I study the effect of broaddegree distributions on network dynamics by interpolati...
Main Author: | Alex eRoxin |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2011-03-01
|
Series: | Frontiers in Computational Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/Journal/10.3389/fncom.2011.00008/full |
Similar Items
-
Correlations of Higher Order in Networks of Spiking Neurons
by: Jovanovic, Stojan
Published: (2016) -
Modeling Oscillatory Phase and Phase Synchronization With Neuronal Excitation and Input Strength in Cortical Network
by: Daming Wang, et al.
Published: (2018-01-01) -
Super-Selective Reconstruction of Causal and Direct Connectivity With Application to in vitro iPSC Neuronal Networks
by: Francesca Puppo, et al.
Published: (2021-07-01) -
Synchronization from second order network connectivity statistics
by: Liqiong eZhao, et al.
Published: (2011-07-01) -
Bayesian Estimation of Phase Dynamics Based on Partially Sampled Spikes Generated by Realistic Model Neurons
by: Kento Suzuki, et al.
Published: (2018-01-01)