About Integrative Neuroscience

The Integrative Neuroscience Program is an Interdisciplinary Program. This means that it is not a formal department, but rather, is made up of faculty and courses from four departments: Psychology, Biological Sciences (Rose Hill), Natural Sciences (Lincoln Center), and Computer and Information Science. Our students take courses in these departments to fulfill the requirements of the major (as outlined below). Within the major, students choose one of three tracks that align with each of the member departments: Cell and Molecular, Cognitive, and Systems and Computational. The design of the major also ensures that students have exposure to each of these disciplines so that their work can be informed by multiple perspectives.

• Cellular and molecular neuroscience comprises studies of the biological mechanisms that determine development, function, and plasticity of neural cells and tissues. Experimentally, it may employ techniques and tools also used to study cell types and tissues at the cellular and subcellular level, including high-resolution fluorescence microscopy, live cell function assays, and biochemical protein analytics. Depending on the specific research question, model systems studied in the laboratory may be single gene/protein analytics, studies of model cells in culture and research on complex neural tissues in situ and ex situ in model organisms. In vivio studies may also involve human clinical trials. Courses in this track focus on topics such as genetics, physiology, and cell biology.


• Cognitive neuroscience involves the study of biological structures and processes, particularly neural circuitry and substrates that underlie human mental processes and psychological/ cognitive functioning. As a branch of both psychology and neuroscience, the field of cognitive neuroscience uses research techniques such as neuroimaging and neuropsychological testing to examine cognitive abilities that arise from typical and atypical brain development. Courses in this track focus on topics such as cognition, memory, behavior analysis, and research methods.


• Systems and computational neuroscience uses data analysis and modeling techniques to study cognition. Neural systems are explored at diverse scales, spanning from groups of tens of neurons to networks across cortical regions, to "factor graphs" decomposing perception and action into interrelated conceptual units. Courses in this track focus on topics such as bioinformatics, mathematical modeling, and computer programming.