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

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.

Model Type: Connectionist Network

Cell Type(s): Abstract rate-based neuron

Receptors: M1

Model Concept(s): Learning

Simulation Environment: MATLAB

Implementer(s): Stroud, Jake P [jp.stroud at]; Hennequin, Guillaume ; Vogels, Tim [tim.vogels at]


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 [PubMed]

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