Venue: 1017 H. H. Dow
Bio1: James V. Haxby is a professor in the Department of Psychological and Brain Sciences at Dartmouth College and the Director for the Dartmouth Center for Cognitive Neuroscience. He is best known for his work on face perception and applications of machine learning in functional neuroimaging. Haxby received a BA from Carleton College in 1973 and completed a Fulbright Scholarship at the University of Bonn in 1974. He obtained a PhD in clinical psychology at the University of Minnesota in 1981. After receiving his PhD, Haxby held several clinical psychology positions at the Minneapolis VA Medical Center. Starting in 1982, Haxby began a two-decade tenure at the National Institutes of Health, working as a research psychologist at the National Institute on Aging and later as chief of the Section on Functional Brain Imaging at the National Institute of Mental Health. In 2002, Haxby began a professorship in the Department of Psychology at Princeton University, and in 2008 became the Evans Family Distinguished Professor of Psychological and Brain Sciences at Dartmouth College.
Haxby’s scientific contributions span several topics in cognitive neuroscience. He has published numerous papers using functional neuroimaging to investigate the cortical organization underlying visual perception and semantic memory.He has also proposed an influential model of face perception where certain brain areas process invariant face properties such identity, while others process dynamic features critical for social interaction, such as emotional expressions and eye gaze. Haxby has played a critical role in introducing machine learning methods to functional magnetic resonance imaging (fMRI) data analysis. This approach was popularized by a paper demonstrating that neural representations of faces and object categories are encoded in a distributed fashion in human ventral temporal cortex, a position that is typically contrasted with more modular accounts of the functional neuroanatomy of face processing.
Computational cognitive neuroscience is a burgeoning field. Sensitive imaging methods can now measure changing patterns of brain activity noninvasively producing massive, rich datasets. With open neuroscience, vast amounts of functional brain imaging data are publicly available. Advances in computational methods for analyzing these data and modeling the underlying cognitive processes have produced a host of sophisticated algorithms that produce surprising new insights, and these algorithms are available in extensive repositories of open source code. Building the interdisciplinary community for this type of collaborative research, however, presents challenges. Taking advantage of these resources requires integration of knowledge of cognitive neuroscience to direct projects to important questions and knowledge of rapidly evolving computational approaches that can tackle these questions in innovative ways. Building an interdisciplinary community will involve developing both productive interdisciplinary collaborative teams and a new breed of “bilingual” computational cognitive neuroscientist.
Prof. Haxby is being hosted my MICDE and the Michigan Neuroimaging Initiative. If you would like to meet Prof. Haxby, please send an email to email@example.com. If you are an MICDE, MIDAS or Neuroscience student or postdoc and would like to join him for lunch, please RSVP here (space is limited, first-come, first-serve)