Response inhibition in Premotor cortex corresponds to a complex reshuffle of the mesoscopic information network

Despite recent works have investigated functional and effective cortical networks in animal models, the dynamical information transfer among functional modules underneath cognitive control is still largely unknown. Here, we addressed the issue using Transfer Entropy and graph theory methods on neural activities recorded at the mesoscopic scale from a multielectrode array in the dorsal premotor cortex of rhesus monkeys. We focused our analysis on the decision time of a Stop-signal (countermanding) task looking for hallmarks in the network functional configuration, when the Stop signal is presented, that could influence the motor plan maturation. When comparing trials with successful inhibition to those with generated movement the nodes (modules) of the network resulted organized in four classes, hierarchically arranged, and differently partaking in information transfer. Interestingly, the hierarchies and the strength of the information exchanged between modules varied during the task, being different for generated movements and cancelled ones and coupled with distinct levels of network complexity and heterogeneity depending on the motor behaviors explored. Last, we exposed the multiscale structure of the network through the multi-fractal formalism, which allowed us to reveal the generating rules of the network and measure the distance between the information processed in the different behavioral conditions. Our results suggest that the premotor contribution to motor decisions involves a topological reorganization of the mesoscopic functional network whose intrinsic fractal features delineate its behavioral functionalities.