Inhibition perturbations reveals dynamical structure of neural processing (Sadeh & Clopath 2020)

"Perturbation of neuronal activity is key to understanding the brain's functional properties, however, intervention studies typically perturb neurons in a nonspecific manner. Recent optogenetics techniques have enabled patterned perturbations, in which specific patterns of activity can be invoked in identified target neurons to reveal more specific cortical function. Here, we argue that patterned perturbation of neurons is in fact necessary to reveal the specific dynamics of inhibitory stabilization, emerging in cortical networks with strong excitatory and inhibitory functional subnetworks, as recently reported in mouse visual cortex. We propose a specific perturbative signature of these networks and investigate how this can be measured under different experimental conditions. Functionally, rapid spontaneous transitions between selective ensembles of neurons emerge in such networks, consistent with experimental results. Our study outlines the dynamical and functional properties of feature-specific inhibitory-stabilized networks, and suggests experimental protocols that can be used to detect them in the intact cortex."

Model Type: Realistic Network

Cell Type(s): Abstract integrate-and-fire leaky neuron

Simulation Environment: MATLAB

Implementer(s): Sadeh, Sadra [s.sadeh at]


Sadeh S, Clopath C. (2020). Patterned perturbation of inhibition can reveal the dynamical structure of neural processing eLife. 9

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