Sensory and Motor Systems
Author: Alvaro Deleglise | email: alvarodeleglise@gmail.com
Alvaro Deleglise 1°, Patricio Donnelly-Kehoe 2°, Florencia Jacobacci 1°, Guillermina Griffa 1°, Jorge Jovicich 4°, Jorge Armony 3°, Julien Doyon 3°, Valeria Della-Maggiore 1°
1° CONICET Universidad de Buenos Aires. IFIBIO Houssay. Buenos Aires, Argentina.
2° Departamento de Investigación e Innovación , Kozaca SA. Rosario, Argentina
3° McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC, H3A 2B4, Canada
4° Center for Mind/Brain Sciences, University of Trento, Rovereto, 38068, Trento, Italy
Recent studies point to a role of the hippocampus in motor sequence learning (MSL). Here we analyzed its functional connectivity dynamics at the high-temporal resolution by applying the Leading Eigenvector Dynamics Analysis approach while subjects performed a MSL task alternating blocks of practice with rest periods. We used unsupervised learning techniques at the volume level to detect a discrete number of phase-locking (PL) states that characterize MSL, based on the phase relationship between brain areas, and define state trajectories for each participant. Using metrics from the physics of dynamical systems we then examined how different PL states differed between task and rest epochs, and between early and late learning. During task periods, MSL increased both the probability of occurrence and the time spent in a state composed by regions from sensorimotor and attentional networks. When comparing early and late rest epochs, we found an increased occurrence of a bilateral hippocampus-default-mode network state during early training. In contrast, late training was associated with a higher occurrence of a state composed by regions of the default-mode. Altogether, these findings highlight the participation of the hippocampus in different states with distinct dynamic features across training. Given that MSL gains in performance occur during early training, our results suggest that they could be supported by the increased excursion into an hippocampal-default mode PL state.