Starts 22 Jun 2021 15:00
Ends 22 Jun 2021 16:00
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The neural mechanisms that generate an extensible library of motor motifs and flexibly string them into arbitrary sequences are unclear. We developed a model in which inhibitory basal ganglia output neurons project to thalamic units that are themselves bidirectionally connected to a recurrent cortical network. We model the basal ganglia inhibitory patterns as silencing some thalamic neurons while leaving others disinhibited and free to interact with cortex during specific motifs. We show that a small number of disinhibited thalamic neurons can control cortical dynamics to generate specific motor output in a noise robust way. Additionally, a single ‘preparatory’ thalamocortical network can produce fast cortical dynamics that support rapid transitions between any pair of learned motifs. If the thalamic units associated with each sequence component are segregated, many motor outputs can be learned without interference and then combined in arbitrary orders for the flexible production of long and complex motor sequences. Our results suggest that the motor thalamocortical network architecture is well-suited to implement the stringing of re-usable skilled behavioral primitives, and have implications for engineering artificial networks for robust hierarchical motor control.