Dr. Yale E. Cohen, Assistant Professor, Dartmouth
Wednesday, May 31, 11 a.m.
TI Auditorium, EC South 2.102
UTD Campus (Get Directions)
Representations of Abstract Categorical Information
Abstract categorization systems should ignore potentially distinctive but functionally meaningless variations. Typically the level of categorization determines which variations are ignored. For example, the unique facial features that identity a person are ignored when the sex of a person is determined. The variation between the sexes is ignored when individuals are categorized as a human or non-human. In this talk, we report the neural basis of abstract categorization of complex acoustic signals. Recordings from individual neurons located in the frontal cortex provide the highest temporal (msec) and spatial (micron) precision possible for investigating the circuitry that underlies complex cognitive processing. These measurements provide new insight into categorization in biological and non-biological systems.
Dr. Cohen’s pioneering research into the neural basis of high level feature extraction and categorization has been supported by the Whitehall Foundation, the Giannini Foundation, the McDonnell - Pew Program, and six research grants from the National Institutes of Health. Dr. Cohen received his B.S.E. degree in electrical Engineering from the University of Michigan, his M.S.E. and Ph.D. degrees from University of Pennsylvania, and his post-doctoral training at Stanford University and California Institute of Technology. Dr. Cohen has been awarded numerous professional awards.
