Columbia University Medical Center

DEPARTMENT OF NEUROSCIENCE

Gary Sean Escola, MD, PhD

Gary Sean Escola, MD, PhD
  • Department of Psychiatry
    Division of Integrative Neuroscience
  • Assistant Professor of Psychiatry at CUMC

Behaviors and cognitions arise from an interplay between neural activity driven by external stimuli and internal activity patterns or “brain states” that reflect motivation, intention, and experience. Historically, neuroscience research has focused almost exclusively on stimulus-driven activity, ignoring the impact of internal state. Clearly, to develop robust computational theories of cognitive function and to understand how computations may fail in psychiatric disease, we must develop a new neuroscience that measures and models both externally and internally generated neural activity and seeks to reveal the interactions between them. On the data side, we must be able to detect transitions between internal states and analyze stimulus-evoked responses within the context of the state in which they occur. On the theory side, we must develop models for how internal states are generated, changed during behavior, and affect sensory responses. These are the goals of my research.

Education & Training

  • MD, Columbia University College of Physicians and Surgeons
  • Residency: NewYork-Presbyterian Hospital/Columbia University Medical Center
  • Lab Locations

    Jerome L. Greene Science Center

    3227 Broadway
    New York, NY 10027

    Phone:
    (646) 774-6102
    Email:
    gse3@columbia.edu

    Research Interests

    Theoretical neuroscience
    Computational psychiatry
    Cognitive/Systems neuroscience
    Motor systems
    Computation and theory

    Lab Members

    Publications

    • Escola S, Fontanini A, Katz D, and Paninski L. Hidden Markov models for the stimulus-response relationships of multi-state neural systems. Neural Computation, 2011 May;23(5):1071–132.
    • Escola S, Eisele M, Miller K, and Paninski L. Maximally reliable Markov chains under energy constraints. Neural Computation, 2009 Jul;21(7):1863–912.