Dottorato in NEUROSCIENZE DEL COMPORTAMENTO

Titolo della tesi: Topology of local information dynamics during motor decision in the premotor cortex of primates.

Despite recent works have investigated functional and effective cortical networks in animal models, the dynamical information transfer underneath most of the higher brain functions is still unknown. Here we address the issue by analysing at the mesoscopic scale neuronal activities from a multielectrode array (96 channels) in the dorsal premotor cortex (PMd) of rhesus monkeys during a countermanding reaching task, requiring dynamical decisions after visual instructions. We used transfer entropy and graph theory to extract the PMd effective network and to quantify the local information patterns corresponding to motor decision-making. We found that the network of information processing is highly heterogeneous, information-spreader hubs exist and exhibit topological differences between movement generation and inhibition. Interestingly, within our framework we identified the presence of a hierarchical organization between four neuronal activity classes involved in the decision-making process. Moreover, we observed that the hierarchical organization changed when movement was executed or cancelled after programmed. We propose that motor decisions are based on the reorganization of local network formed by few subclasses of neuronal modules hierarchically organized