University of Southern California

USC Neuroscience

Computational Neuroscience

The field of computational neuroscience seeks to systemize the analysis of various levels of organization of the brain within a computational or mathematical framework. Classically concerned with Hodgkin-Huxley-type models of spiking dynamics or simple Hebbian learning between neurons, the field of computational neuroscience has grown immensely in the past decades and is now more comprehensive in its focus, and seeks to characterize much broader areas of research in the neurosciences, including, for instance, the molecular cascading events during transmitter release, developmental and plasticity-related neural (re)organization, motor control, attention and 'binding', reinforcement learning, schema theory, and reasoning and decision-making. Participants from various fields bring expertise in robotics, cognitive science, engineering, mathematics, physics, computer science, molecular biology, psychology and philosophy. Indeed, the USC Computational Neuroscience Journal Club seeks to discuss with knowledgeable graduate students topics as diverse as the field itself.

Contact: Brad Gasser for more details and to join the mailing list.