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The corresponding page is
https://modeldb.science/235053
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Sparse connectivity is required for decorrelation, pattern separation (Cayco-Gajic et al 2017)
 
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Model Information
Model File
Citations
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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Cayco-GajicEtAl2017
analytical_model
biophysical_model
grc_lemsDefinitions
input_statistics
network_structures
readme.html
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