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Seminar: 9/30 - F. Gregory Ashby, University of California, Santa Barbara

11:00 to 12:30 PM      at:  5101 Tolman Hall

Human category unlearning

Huge amounts of money are spent every year on unlearning programs – in drug-treatment facilities, prisons, psychotherapy clinics, and schools. Yet almost all of these programs fail, since recidivism rates are high in each of these fields. Progress on this problem requires a better understanding of the mechanisms that make unlearning so difficult. Much evidence suggests that success on categorization tasks that recruit procedural learning depends on synaptic plasticity within the striatum. A biologically detailed computational model of this striatal-dependent learning is described (based on Ashby & Crossley, 2011, J. of Cognitive Neuroscience). The model assumes that a key component of striatal-dependent learning is provided by the Tonically Active interNeurons (TANs). In their tonic state, the TANs prevent the execution of any striatal-dependent actions, but they learn to pause in rewarding environments, which facilitates the learning and expression of striatal-dependent behaviors. When rewards are unavailable, the TANs cease to pause, which protects striatal learning from decay and prevents unlearning. The model successfully accounts for a variety of single-unit recording and behavioral data. It is also used to design a novel unlearning protocol that shows promising initial signs of success.