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.
Model Type: Realistic Network
Simulation Environment: MATLAB
Implementer(s): Sadeh, Sadra [s.sadeh at ucl.ac.uk]
References:
Sadeh S, Clopath C. (2020). Theory of neuronal perturbome in cortical networks Proceedings of the National Academy of Sciences of the United States of America. 117 [PubMed]