Working memory and decision-making: From microcircuits to the global brain


Xiao-Jing Wang

(New York University)

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Date: January 30, 2017


In this talk, I will first discuss “cognitive-type” microcircuits capable of working memory and decision-making computation. In particular, I will briefly summarize a model characterized by slow (NMDA-receptor dependent) recurrent attractor dynamics, its experimental tests as well as applications to shed insights into deficits associated with psychiatric disorders. This line of research has led us to study multi-region brain systems based on mesoscopic connectome and physiological experiments. We have developed large-scale cortex modeling of macaque monkey and mouse. By taking into account cortical heterogeneity, the model naturally gives rise to a hierarchy of timescales and, endowed with a laminar structure of the cortex, it captures frequency-dependent interactions between bottom-up and top-down processes. Moreover, in a complex brain system, routing of information between areas must be flexibly gated according to behavioral demands. We proposed such a gating mechanism with a disinhibitory circuit motif implemented by three subtypes of (PV+, SOM+ and VIP+) inhibitory neurons, and I will report a recent finding that the relative distribution of these three interneuron classes varies markedly across the whole mouse cortex. Circuit modeling across levels, combined with training multi-module recurrent networks, represents a promising approach to elucidate high-dimensional dynamics and functions of the global brain.

Created: Tuesday, January 31st, 2017