Biomimetic model of corticostriatal micro-assemblies discovers a neural code

Abstract

Although computational models have deepened our understanding of neuroscience, it is still highly challenging to link actual low-level physiological activity (spiking, field potentials) and biochemistry (transmitters and receptors) directly with high-level cognitive abilities (decision-making, working memory) and associated disorders. Here, we introduce a mechanistically accurate multi-scale model directly generating simulated physiology from which extended neural and cognitive phenomena emerge. The model produces spiking, fields, phase synchronies, and synaptic change, directly generating working memory, decisions, and categorization. These were then validated on extensive experimental macaque data from which the model received no prior training of any kind. Moreover, the simulation uncovered a previously unknown neural code (“incongruent neurons”) that specifically predicts upcoming erroneous behaviors, also subsequently confirmed in empirical data. The biomimetic model thus directly and predictively links decision and reinforcement signals, of computational interest, with spiking and field codes, of neurobiological importance.