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Title : A neurocomputational model of automatic sequence production Abbreviated title : Automaticity in sequence production

Most behaviors unfold in time and include a sequence of sub-movements or cognitive activities. In addition, most behaviors are automatic and repeated daily throughout life. Yet, relatively little is known about the neurobiology of automatic sequence production. Past research suggests a gradual transfer from the associative striatum to the sensorimotor striatum, but a number of more recent studies challenge this role of the basal ganglia in automatic sequence production. In this article, we propose a new neurocomputational model of automatic sequence production in which the main role of the basal ganglia is to train cortical-cortical connections within the premotor areas that are responsible for automatic sequence production. The new model is used to simulate four different data sets from human and non-human animals, including (1) behavioral data (e.g., response times), (2) electrophysiology data (e.g., single-neuron recordings), (3) macro-structure data (e.g., transcranial magnetic stimulation), and (4) neurological circuit data (e.g., inactivation studies). We conclude with a comparison of the new model with existing models of automatic sequence production and discuss a possible new role for the basal ganglia in automaticity and its implication for Parkinson’s disease.