Robert J. and Nancy D. Carney Institute for Brain Science

ICoN - Interdisciplinary Training in Computational, Cognitive and Systems Neuroscience

The Interdisciplinary Training in Computational, Cognitive, and Systems Neuroscience (ICoN) is a pre-doctoral program in computational cognitive neuroscience. Funds from this program will support the training of advanced pre-doctoral candidates who are capable of applying a combination of empirical and theoretical approaches that decisively address their scientific questions about the mind and brain.

Co-Principal Investigators

  • 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.
  • Stephanie Jones integrates human electrophysiological brain imaging (Magneto- and Electro-encephalography MEG/EEG) and biophysically principled computational neural models to study thalamocortical dynamics of healthy brain function and disease. She has used this integrated approach to study the cellular and circuit level dynamics underlying sensory evoked and spontaneous rhythmic activity in human MEG/EEG recordings and their modulation with perception, attention, practice, and healthy aging. She works closely with clinicians and animal electrophysiologists to develop data driven models that provide testable predictions on brain dynamics and their impact on function. 
  • 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.

Eligibility

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.

How 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 Trainers

ICoN includes 32 trainers from seven academic departments and two clinical departments at Brown University.

See the list