Pantheon SEMPARIS Le serveur des séminaires parisiens Paris

Statut Confirmé
Date Vendredi 3 Décembre 2021
Heure 13:00
Institut LPENS
Salle Salle Favard, IBENS
Nom de l'orateur Chen
Prenom de l'orateur Xiaowen
Addresse email de l'orateur
Institution de l'orateur LPENS
Titre Inferring collective behavior and control principles in a small brain
Résumé In large neuronal networks, functions emerge through the collective behavior of many interconnected neurons. Recent technical development of whole brain imaging in Caenorhabditis elegans - a nematode with 302 neurons, allowed us to ask if such emergence reaches down to even the smallest brains. In the first part of this talk, I will discuss how we use the maximum entropy principle to construct pairwise probabilistic models for the collective activity of 50+ neurons in C. elegans. These models successfully predict higher order statistical structure in the data, the topological features of the structural connectome, and show signatures of collective behavior. In the second part, I will present two ways of how perturbing the inferred model of neuronal activity can shed light on the control principles in the brain, which in turn facilitates future perturbation experiments. Firstly, by ablating and clamping neurons, we discover that the worm brain is both robust against damages and efficient in transmitting information. Secondly, by examining the local information geometry of the model, we find that a few, "pivotal" neurons account for most of the system's sensitivity, suggesting a sparse mechanism for control of the collective behavior. Finally, if time allows, I will briefly describe my current work at ENS on inferring statistical models with long memory kernel for collective dynamics in a group of social animals.
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