The McDonnell Center for Systems Neuroscience
Teaching and research conducted by the McDonnell Center for Systems Neuroscience explores the ways in which the brain acquires, modifies and stores information during cognitive processes, efforts that are of critical importance to Princeton scientists as they advance knowledge of neural coding and dynamics.
Neural coding refers to the ways in which information is represented in the electrical and biochemical signals in neurons (perception and short-term memory) and the patterns of synaptic connections (long-term memory). Neural dynamics refers to the patterns of nerve cell electrical and chemical activity in which information is created, manipulated, and stored. Neural dynamics are involved in decision-making, planning, and executing sequences of behavior.
The list below details some research efforts in these areas.
Neural computation in the retina, Michael Berry
Neuronal functions of immune molecules, Lisa Boulanger
Quantitative approaches to systems neuroscience, Carlos Brody
Neural mechanisms of cognitive control, Jonathan Cohen
Neurovirology, Lynn Enquist
Primate neuroethology and multisensory integration, Asif Ghazanfar
Neurogenesis and hippocampal function, Elizabeth Gould
Sensorimotor integration, Michael Graziano
Functions of the cerebral cortex in behavior, Charles Gross
Neural mechanisms of visual perception and attention, Sabine Kastner
Molecular mechanisms of aging, Coleen Murphy
Neural codes underlying olfactory and auditory perception in Drosphila, Mala Murthy
Human and animal reinforcement learning and decision making, Yael Niv
Measurement and analysis of neural circuit dynamics, David Tank
Learning rules and design principles in neural circuits, Samuel Wang