Evan Hart is an Assistant Professor in the Department of Psychology and the Brain and Behavior Institute. He began his research career at the University of Connecticut, after which he obtained his Ph.D. at the University of California, Los Angeles. During his postdoctoral research at the National Institute on Drug Abuse Intramural Research Program, he studied the contributions of frontal cortical areas to value-neutral learning, in addition to the importance of cortical multiplexing for learning. Dr. Hart’s work has been funded by the National Institute of General Medical Sciences (Fi2 postdoctoral Fellowship) and is currently supported by a BRAIN Initiative Diversity K99/R00. His current and future work is focused on the integration of multidimensional information in cortical networks, learning, and memory.
Degrees
-
PhDPsychology, University of California Los Angeles
-
MAPsychology, University of California Los Angeles
-
BAPsychology, University of Connecticut
The lab is interested in smells, sounds, and how we learn about what they mean. Using sensory cues such as smells and sounds to make predictions is necessary for survival, and cues signal several aspects of survival behavior. For example, the aroma of fresh-baked cookies tells us food is available. Road signs tell us where to turn to acquire food, as well as which specific food is offered. We also discriminate cues which share the same meaning. The integrated representation of these features of the behavioral landscape - sensory information, rewards, the identity of those rewards, and the actions required to obtain them - has been called a “cognitive map”, the construction and use of which confer the ability to make predictions based on direct experience and to make inferences in novel situations. We study how and why cognitive maps form during learning, how cognitive maps are used to guide behavior, and how they evolve with experience. How do we apply knowledge about the structure of the world to learn, predict, and adapt?
To address these questions, our primary approach is to record populations, or ensembles, of cortical neuron spiking activity while rats perform complex behavioral tasks. We combine neurophysiological approaches with theory-derived behavioral tasks, genetic interference and imaging tools, and computational analyses. Our goal is to acquire a better fundamental understanding of integrated neural representations, their importance for learning, and, by extension, a better understanding of human cognition.
