The Program in Quantitative and Computational Neuroscience (QCN) is a special track within the Certificate in Neuroscience. It is designed for undergraduates who wish to pursue a quantitative approach to the study of brain function. As is the case with the Program in Neuroscience certificate, graduates of the QCN track will be prepared to meet the entry requirements of graduate schools in neuroscience, as well as molecular biology or psychology; in addition, QCN students will have acquired quantitative data analysis, modeling, and programming skills.
The following is a list of faculty members who have expressed willingness to advise Neuroscience students for Junior Independent Research or Senior Thesis Projects. Please check with these faculty about their availability and specific projects.
Michael Berry (MOL) Neural computation in the retina
Matt Botvinick (PSY) Neural and computational basis of cognitive control, decision making, working memory
Lisa Boulanger (MOL) Neuronal functions of immune molecules
Carlos Brody (MOL) Computational neuroscience
Timothy Buschman (PSY) Dynamics of executive function
Jonathan Cohen (PSY) Neural mechanisms of cognitive control
Lynn Enquist (MOL) Neurovirology
Asif Ghazanfar (PSY) How did the brain evolve to perceive speech?
Elizabeth Gould (PSY) Neurogenesis and hippocampal function
Michael Graziano (PSY) Sensorimotor integration
Uri Hasson (PSY)Temporal scale of neural processing,the neural basis of inter-group differences and social communication
Philip Holmes (MAE) Mathematical modeling
Sabine Kastner (PSY) Neural mechanisms for visual perception
Carolyn McBride (Ecology and Evolutionary Biology) Molecular and neural basis of behavioral evolution
Coleen Murphy (MOL) Molecular mechanisms of aging
Mala Murthy (MOL) Neurophysiology of olfactory and auditory perception in Drosophila
Yael Niv (PSY) Human and animal reinforcement learning and decision
Kenneth Norman (PSY) Neural mechanisms of episodic and semantic memory
Jonathan Pillow (PSY) Neural information processing, machine learning, and statistical modeling of neural data
Sebastian Seung (Computer Science) Structure and function of neural circuits
David Tank (MOL/PHY) Measurement and analysis of neural circuit dynamics
Samuel Wang (MOL) Learning rules and design principles in neural circuits