Modelling gain modulation in stability-optimised circuits (Stroud et al 2018)

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Accession:246004
We supply Matlab code to create 'stability-optimised circuits'. These networks can give rise to rich neural activity transients that resemble primary motor cortex recordings in monkeys during reaching. We also supply code that allows one to learn new network outputs by changing the input-output gain of neurons in a stability-optimised network. Our code recreates the main results of Figure 1 in our related publication.
Reference:
1 . Stroud JP, Porter MA, Hennequin G, Vogels TP (2018) Motor primitives in space and time via targeted gain modulation in cortical networks Nature Neuroscience 21(12):1774-1783 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Connectionist Network;
Brain Region(s)/Organism:
Cell Type(s): Abstract rate-based neuron;
Channel(s):
Gap Junctions:
Receptor(s): M1;
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Learning;
Implementer(s): Stroud, Jake P [jp.stroud at hotmail.com]; Hennequin, Guillaume ; Vogels, Tim [tim.vogels at epfl.ch];
Search NeuronDB for information about:  M1;
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