Separated attractors in neural landscape of motor cortex encoding motor learning
Animals gain motor learning via decrease of variation through repeated training. The secondary motor (M2) cortex shows an indispensable role in the learning process of the rotarod-learning task. Yet, it remains unclear how population decoding in M2 cortex guides the repetitive training to transform into motor enhancement. We recorded neuronal population activity using Ca2+ imaging during this enhancement revealing that neuronal population correlates of the persistent internal learning state evolves in the process of motor learning. With the behavioral micro-states analysis, we identify the growing periodicity, stability, and consistency with two gradually clearer point attractor in the M2 neural state space. The results show the evolution of attractors in M2 participate in decrease of training-acquisition behavior variation and provide a general framework for the mapping between arbitrary non-task motor learning and neural topological structure.