Sparse connectivity is required for decorrelation, pattern separation (Cayco-Gajic et al 2017)

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Accession:235053
" ... To investigate the structural and functional determinants of pattern separation we built models of the cerebellar input layer with spatially correlated input patterns, and systematically varied their synaptic connectivity. ..."
Reference:
1 . Cayco-Gajic NA, Clopath C, Silver RA (2017) Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks. Nat Commun 8:1116 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB; Python;
Model Concept(s): Pattern Separation;
Implementer(s): Cayco Gajic, Alex [natasha.gajic at ucl.ac.uk];
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