Rouhani, Nina
Assistant Professor of Psychology
The Interactive Cognition Lab uses an interdisciplinary framework, drawing from computational neuroscience, cognitive science and psychology, to uncover how learning and memory processes guide individual and interactive behavior in the laboratory and real world.
Schier, Lindsey
Associate Professor of Biological Sciences
The Schier lab seeks to understand how the chemical constituents of foods and fluids are sensed, how these oral and postoral signals are processed in the brain and channeled into the behavioral outputs that subserve energy balance.
Schwartzman, Jessica
Assistant Professor of Clinical Pediatrics
The Training and Research to Empower NeuroDiversity (TREND) Lab uses multi-method approaches, including electroencephalogram (EEG), behavioral observation and clinical interviews to study risk and protective factors for depression, suicide, and other mental health outcomes in youth with autism and other neurodivergent conditions. We also partner with autistic and other neurodivergent people to adapt and design treatments for the individual and family. The TREND Lab focuses on characterizing and treating adverse mental health outcomes in youth with autism and other neurodivergent conditions.
Tao, Huizhong W.
Professor of Physiology and Neuroscience
My lab studies how the mouse brain processes visual information and transforms it into behavior. Our research focuses on identifying the neural circuits involved in visual perception and how these circuits drive visually guided actions. We use a combination of techniques—including electrophysiology to record neural activity, microendoscopic calcium imaging to monitor populations of neurons in freely moving animals, and both optogenetics and chemogenetics to precisely manipulate specific circuit components. By integrating these approaches, we aim to understand how visual signals are encoded, transmitted, and used to guide behavior at the level of individual neurons and larger networks.
Watts, Alan
Professor of Biological Sciences
My work focuses on understanding how the brain contributes to the development, manifestation, and complications of diabetes and obesity, primarily on how this happens at the neural network level. In particular, I am interested in how interoceptive and exteroceptive signals interact with the brain to control endocrine and behavioral responses to energy deficits. Currently I am using neuroinformatic methods to explore how the rat brain connectome can reveal the organization of the control networks that influence the behavioral, endocrine, and autonomic motor events associated with metabolic physiology and its dysfunction.
