Jack Gallant is Professor of Psychology at the University of California at Berkeley, and is affiliated with the graduate programs in Bioengineering, Biophysics, Neuroscience and Vision Science. He received his Ph.D. from Yale University and did post-doctoral work at the California Institute of Technology and Washington University Medical School. His research program focuses on constructing quantitative computational models that accurately describe how the brain represents information during natural tasks, and how these representations are modulation by attention. One interesting application of this computational modeling approach is to decode information in the brain in order to reconstruct mental experiences. Because this computational framework can be used to understand and decode brain activity measured by different methods and in different modalities, it has many potential applications in science and technology.

Researchers should cite this work as follows:

• Jack Gallant; NanoBio Node (2012), "[Illinois] Modeling and Decoding the Human Brain ," https://nanohub.org/resources/14420.

1. Beckman
2. IGERT
3. Modeling and Decoding the Human Brain
4. NanoBio Node
5. Neuroengineering
6. Symposium 2012