Calvin Lab Auditorium
I will discuss our recent work on developing large-scale modeling of mammalian neocortex, based on mesoscopic directed- and weighted inter-areal connectivity data (Wang and Kennedy 2016). By taking into account a gradient of circuit property across cortical areas, the model naturally gives rise to a hierarchy of timescales (Chaudhuri et al. 2015), and captures interactions of bottom-up and top-down processes mediated by layer-dependent connections (Mejias et al. 2016). Moreover, in a complex brain system, routing of information between areas must be flexibly gated according to behavioral demands. We propose such a gating mechanism with a disinhibitory circuit motif implemented by three subtypes of (PV+, SOM+ and VIP+) inhibitory neurons, the latter’s relative distribution varies markedly across areas in the mammalian cortex (Kim et al. 2017). This model is now being used to investigate distributed working memory representation in a large-scale brain system. Circuit modeling across levels represents a promising approach to elucidate high-dimensional neural dynamics and cognitive functions of the global brain, as well as their deficits associated with psychiatric disorders.