A network of reverberating neuronal populations encodes motor decision in macaque premotor cortex

Background We investigate, through in-vivo experiments and theoretical models, the dynamic mechanisms subserving motor decision tasks. The proposed computational framework is based on local reverberations in multiple neuronal subpopulations. Signatures of such reverberations are identified in the simulated multi-modular network of spiking neurons and recognized in the analysis of recorded neural activity. The reported experimental results are compatible with a neuronal substrate in which several local populations undergo sudden transitions as a late reaction to a visual stimulus. Often, such transitions are very plausibly supported by strong local recurrent feedback as in models of decision making [1]. Transitions also occur without clear evidence of local reverberation; the combined evidence suggests the coexistence of "active" and "passive" modules, the latter responding to the activity of the first ones, which together cooperate in order to represent a distributed and well stereotyped motor program.