Title
Self-Organization In Balanced State Networks By Stdp And Homeostatic Plasticity
Abstract
Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network.
Year
DOI
Venue
2015
10.1371/journal.pcbi.1004420
PLOS COMPUTATIONAL BIOLOGY
Field
DocType
Volume
Population,Synaptic scaling,Nonsynaptic plasticity,Neuroscience,Developmental plasticity,Biology,Synaptic plasticity,Artificial intelligence,Genetics,Metaplasticity,Homeostatic plasticity,Homosynaptic plasticity
Journal
11
Issue
ISSN
Citations 
9
1553-7358
6
PageRank 
References 
Authors
0.51
19
3
Name
Order
Citations
PageRank
Felix Effenberger1375.94
Jost Jürgen27114.59
Anna Levina3193.72