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.
Schweighofer, Nicolas
Professor of Biokinesiology and Physical Therapy
Nicolas Schweighofer is a professor of biokinesiology and physical therapy and holds joint appointments in computer science, biomedical engineering and neuroscience at USC. He is also the director of the Center for Statistics and Computation in Biokinesiology. He co-founded computational neurorehabilitation, an emerging field at the intersection of neurorehabilitation, computational neuroscience, motor control and learning, and artificial intelligence (AI). The overarching goals of computational neurorehabilitation are to understand and to further improve motor recovery following neurologic injury by mathematically modeling and simulating the neural processes underlying the change in behavior due to rehabilitation. In his current research, he is investigating how predictive models of recovery, informed by the neuroscience of stroke recovery and motor learning, as well as large datasets, can provide the basis for AI methods that suggest timing, dosage and content of rehabilitation. Such an approach will transform neurorehabilitation by guiding clinicians, patients and healthcare providers in the optimization of treatments via precision rehabilitation.
Sieburth, Derek
Associate Professor of Physiology & Neuroscience
Our lab is interested in understanding how neuronal signal transduction pathways regulate neurotransmitter secretion and how this impacts the function of underlying neuronal circuits that control behavioral output.
