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WKW Frontiers in Neuroscience: Dr. Kevin LaBar

9/25/2018

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Kevin LaBar, Ph.D., Sept 26, 2018
"An Information Mapping Approach to Emotion Representation in the Brain”

William K. Warren, Jr.  Frontiers in Neuroscience Lecture 
Laureate Psychiatric Clinic and Hospital Conference Center 
11:00 am - 11:45 am    Registration and Lunch, lunch stops being served at 11:45 - no exceptions
12:00 pm - 1:00 pm     Program

Kevin S. LaBar is a Professor in the Center for Cognitive Neuroscience and Department of Psychology & Neuroscience at Duke University. He earned his Ph.D. at New York University and completed postdoctoral studies at Yale University. He was an Instructor of Neurology at Northwestern University Medical School prior to joining the Duke faculty in 1999. His research seeks to understand how emotions are processed in the brain and how they bias cognitive functions. He addresses these questions using behavioral, psychophysiological, neuroimaging, and patient-based research approaches. Dr. LaBar received Young Investigator awards from the National Alliance for Research on Schizophrenia and Depression, Oak Ridge Associated Universities, and the Cognitive Neuroscience Society, as well as a CAREER award from the National Science Foundation. He was elected Fellow of the Association for Psychological Science in 2010 and received the honorary Frijda Chair in Cognitive Sciences from the University of Amsterdam in 2012. Dr. LaBar serves as Deputy Editor for neuroscience content in Science Advances, the on-line extension of Science magazine. He has published over 150 journal articles and book chapters, and is a senior editor and co-author of the Sinauer textbook Principles of Cognitive Neuroscience. His work is currently funded by the National Science Foundation and the National Institutes of Health. 
 
Learning objectives: 
  1. To know the conceptual differences among prominent psychological theories of emotion.
  2. To learn how machine learning tools can be applied to study the representation of specific emotions in the brain.
  3. To understand how advanced neuroimaging tools can decode patterns of spontaneous emotion from resting-state fMRI data.

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