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Seminar: 4/1 - David Noelle, UC Merced

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

Prefrontal cortex, dopamine, and autism: Computational connections

  Autism is a complex developmental disorder characterized by deficits
across physical, social, and cognitive domains.  Cognitive
difficulties are found in executive function, "mind reading"
abilities, the integration of information, attention, and the
generalization of learned abilities to novel contexts.  In addition,
physical motor abnormalities, an increased prevalence of seizure
disorders, motor stereotypies, and repetitive behaviors often
accompany the diagnosis.  The diversity of behavioral abnormalities
exhibited in this disorder has prompted an almost equally diverse
collection of psychological theories of autism, including Executive
Dysfunction theories, Theory of Mind based accounts, and Weak Central
Coherence theories.

This talk presents a general computational cognitive neuroscience
model of interactions between the prefrontal cortex and the mesolimbic
dopamine system which, when damaged, produces patterns of behavior
that qualitatively and quantitatively match those observed in people
with autism.  The range of deficits captured by this approach is
fairly broad, including aspects of executive dysfunction, stimulus
overselectivity during conditioning, impaired implicit learning
abilities, lexical disambiguation difficulties, and generalization
problems in category learning.  Thus, this computational account
potentially offers a common neuroscientific explanation for diverse
phenomena that have traditionally been explored within disjoint
psychological frameworks.

Our model of interactions between the prefrontal cortex and the
dopamine system will be described, and simulation results will be
presented to demonstrate the ability of this model to capture the
performance of both healthy and frontally damaged individuals on tasks
involving working memory, cognitive control, and selective attention.
Starting with this model of healthy performance, patterns of behavior
matching those observed in people with autism will be produced by a
simple disruption of dopamine modulation.  Fits to behavorial data
will be presented for a diverse collection of cognitive tasks,
including Stroop, the Wisconsin Card Sorting Task, conditioning to
multi-modal stimuli, a Serial Response Time Task, a lexical
disambiguation task, and a prototype abstraction task.

David C. Noelle is Assistant Professor of Cognitive Science and
Computer Science at the University of California, Merced.  He received
his Ph.D. in Cognitive Science and Computer Science from the
University of California, San Diego.  His research focuses primarily
on computational cognitive neuroscience models of cognitive control,
learning, and memory.  The ongoing work reported in this talk is being
conducted in collaboration with Trent Kriete, Ph.D., who is a
postdoctoral fellow at the University of Colorado, Boulder.