Memory and decision-making
How do we use our previous experiences to imagine the future?  How does our imagination for the future influence the decisions we make in the present?  My primary interest is understanding how memories contribute to decision processes. My research examines how humans and animals learn to predict the dynamic processes and use these prediction in behavior.

Analysis of animal behavior suggests that animals maintain complex representations of their world ranging from simple spatial maps of an environment to complex contingency schedules.  My experimental work focuses on understanding what information animals use to guide their decisions.  Do animals imagine the future before making a choice?  How do humans do it?  That's what we hope to find out.  We will be starting two behavioral projects this spring.  The first will examine how rats find and exploit short-cuts in spatial mazes.  The second will examine how humans plan spatial trajectories in a virtual navigation task (video game).

Mathematical models provide a method to investigate the computations that underlie behavior and provide deep insights for understanding many different brain signals. My current theoretical work links recent developments in machine learning (e.g. reinforcement learning and structure learning) with neuroscience and psychology.

An interplay between theory and experiment is essential for understanding the role of memory and imagination in decision-making. Experiments provide a critical leverage point for testing different theories.  Theory allows us to understand what experiment will be most informative and to conduct experiments more efficiently.  Although not everyone does both (and I wouldn't expect it), putting these together often yields amazing results!

Collaborators and collaborations
Science is a collaborative endeavor.  Here's a short list of my current collaborators and collaboration project topics.

A. David Redish - University of Minnesota
Rat navigation, multi-unit extracellular recording, theoretical neuroscience

Paul Schrater - University of Minnesota
Behavior and theory of decision-making, mathematical models of behavior.

David Crowe - Augsburg College (Minneapolis, MN)
Memory, imagery and problem solving, magnetoencephalography


Topics
Neuroscience of learning and memory, decision making
Theoretical neuroscience and machine learning


Methods
Animal behavior, inactivations, multi-unit extracellular recording
Computational modeling, reinforcement learning, probabilistic learning

Images
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