A computational model of single-neuron perturbations (Sadeh and Clopath 2020)

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A computational model to study the effect of single-neuron perturbations in large-scale excitatory-inhibitory networks of the primary visual cortex. Neuronal receptive fields and connectivity are constrained by experimental literature. The model addresses how the influence of perturbing an excitatory neuron ("influencer") in the network on other neurons ("influencees") depends on the similarity of their receptive fields. Specifically, in which regimes this influence is dominated by amplification or suppression, and how it relates to functional properties of neurons.
1 . Sadeh S, Clopath C (2020) Theory of neuronal perturbome in cortical networks PNAS (accepted)
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Gap Junctions:
Simulation Environment: MATLAB;
Model Concept(s):
Implementer(s): Sadeh, Sadra [s.sadeh at ucl.ac.uk];
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