Objectives

      We study how the brain learns from experience in order to make good future decisions. We re focused on how information is processed in neural circuits linking the prefrontal cortex, basal ganglia, hippocampus, and their innervation by dopamine neurons. Our aim is to advance a theory of how long term memory (via consolidation), working memory, and reinforcement learning mesh in this circuit to form a representation of the environment useful for guiding decisions. This circuit formed early in vertebrate evolution, and plays a fundamental role in regulating behaviour for food, sex, and safety by exerting regulation on structures such as the hypothalamus and by biasing competition among other brain circuits that control volitional actions. Dysfunction of this circuit presents in many mental illnesses involving altered perceptions, attention, memory, and mood.
      Our current focus is the establishment of mental models of the world in the anterior cingulate cortex and nearby regions, and the effects of input from the hippocampus (consolidation and indexed recall) and dopamine/basal ganglia (reinfrocement learning). We use advanced imaging techniques and computational tools to study this in rodent models and humans.
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Computational neurosci. and machine learning

Using advanced algorithms to analyze neural data and to test brain-inspired network architectures.

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Ensemble neural activity

Monitoring large-scale brain activity in behaving animals

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Neurophysiology

Effects of abused drugs, stress, and other risk factors of mental illness on the structure and function of the brain

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