Pantheon SEMPARIS Le serveur des séminaires parisiens Paris

Statut Confirmé
Domaines cond-mat.stat-mech
Date Mercredi 10 Fevrier 2021
Heure 14:30
Institut LPENS
Nom de l'orateur Sanzeni
Prenom de l'orateur Alessandro
Addresse email de l'orateur
Institution de l'orateur Duke University and NIH, USA
Titre Dynamics of cortical circuits: underlying mechanisms and computational implications
Résumé Understanding the biophysical mechanisms underlying the dynamics of cortical circuits in the brain is one of the major challenges in neuroscience. Electrophysiological recordings show that the cerebral cortex is characterized by irregular neural activity, which manifests itself in the high temporal variability of spiking and the broad distribution of firing rates. Theoretical works have shown that irregular activity emerges dynamically in network models if the coupling between cells is strong, i.e. if the mean number of synaptic connections per neuron K is large and synaptic strength is of order 1/\sqrt{K}. However, the degree to which these models capture the mechanisms underlying neuronal firing in cortical circuits is not fully understood. In particular, results have been derived using simplified neuron models, characterized by current-based synapses, and an understanding of how irregular firing emerges in more biologically realistic neuron models is still lacking. In this talk, I will discuss biophysical mechanisms shaping the dynamics of neural activity in cortical circuits. First I will show that, in network models with conductance-based synapses, irregular firing emerges if synaptic strength is of order 1/\log(K) and, unlike in current-based models, persists even under the large heterogeneity of connections that has been reported experimentally. I will then discuss how dynamical stability can be implemented in cortical circuits and provide experimental evidence of the critical role played by recurrent inhibition in stabilizing neural dynamics in the mouse cortex. I will conclude by discussing the computational consequences of these results for how cortical circuits process sensory information.
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