• David Badre is a leader in computational cognitive neuroscience, using human neuroscience methods from fMRI to ECoG to test mechanistic theories of the human mind and brain.
• Michael Frank is a leading computational neuroscientist who has extensive experience in bridging different levels of analysis and description in computational theory, and testing these with empirical tests both in humans and in animal models. He has also used this computational approach to study how brain-behavior relationships are altered as a function of disease and treatments, helping to develop the burgeoning field of computational psychiatry and neurology.
• Christopher Moore is a leader in systems neuroscience, studying circuit level computations in animal models. Going back to his own graduate training, Moore has long worked to bridge his research in animals with fMRI and MEG studies in humans, including by using biophysically realistic computational modeling.

To qualify for this cross-training program, students must have completed at least two years of their graduate studies at Brown University and propose a project that will span experimental models or approaches and benefit from different disciplines. 

Students must be enrolled in one of the following Ph.D. programs: Applied Mathematics; Biomedical Engineering; Biostatistics; Cognitive, Linguistic & Psychological Sciences; Computer Science; and Neuroscience. 

ICoN supports up to seven students annually. International students are eligible to apply.

Nominations are accepted during the spring semester for the following academic year. 

For more information, download this presentation about the ICoN training program, or contact Kristin Webster. 

ICoN includes 27 trainers from six academic departments and two clinical departments at Brown University.

See the list