Multistability of clustered states in a globally inhibitory network (Chandrasekaran et al. 2009)

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"We study a network of m identical excitatory cells projecting excitatory synaptic connections onto a single inhibitory interneuron, which is reciprocally coupled to all excitatory cells through inhibitory synapses possessing short-term synaptic depression. We find that such a network with global inhibition possesses multiple stable activity patterns with distinct periods, characterized by the clustering of the excitatory cells into synchronized sub-populations. We prove the existence and stability of n-cluster solutions in a m-cell network. ... Implications for temporal coding and memory storage are discussed."
1 . Chandrasekaran L, Matveev V, Bose A (2009) Multistability of clustered states in a globally inhibitory network Physica D: Nonlinear Phenomena 238(3):253-263
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Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s):
Gap Junctions:
Simulation Environment: MATLAB (web link to model);
Model Concept(s): Temporal Pattern Generation; Simplified Models; Short-term Synaptic Plasticity; Depression; Attractor Neural Network;
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