Mapping, modeling and decoding the human brain under naturalistic conditions.
Dr. Jack Gallant, University of California, Berkeley
Monday, May 4th at 5:30 p.m., 118 Psychology
This talk is hosted in collaboration with
Social Science Data Analytics.
Social Science Data Analytics.
About Dr. Gallant
Jack Gallant is Chancellor's Professor of Psychology at the University of California at Berkeley. He
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 computational modeling of human brain activity. These models accurately describe how the brain
encodes information during complex, naturalistic tasks, and they show how information about the
external and internal world are mapped systematically across the surface of the cerebral cortex. These
models can also be used to decode information in the brain in order to reconstruct mental experiences.
(Further information about ongoing work in the Gallant laboratory, links to talks and papers, and links
to an online interactive brain viewer can be found at the lab web page.
Abstract
One important goal of Psychology and Neuroscience is to understand the mental and neural basis of natural behavior. This is a challenging problem because natural behavior is difficult to parameterize and measure. Furthermore, natural behavior often involves many different perceptual, motor and cognitive systems distributed broadly across the brain. Over the past 10 years my laboratory has developed a new approach to functional brain mapping that recovers detailed information about the cortical maps mediating natural behavior. We first use functional MRI to measure brain activity while participants perform natural tasks such as watching movies or listening to stories. We analyze these data by means of two statistical approaches developed in my laboratory: voxel-wise modeling (VM) is used to discover how information is mapped across the cortex of each individual subject, and a probabilistic and generative model of areas tiling cortex (PrAGMATiC) is used to recover putative functional areas at the group level. Our results show that even simple natural behaviors involve dozens or hundreds of distinct functional gradients and areas, that these are organized similarly in the brains of different individuals, and that top-down mechanisms such as attention can change these maps on a very short time scale. These statistical modeling tools provide powerful new methods for mapping the representation of many different perceptual and cognitive processes across the human brain, and for decoding brain activity.
Suggested Readings
Tolga Cukur, Shinji Nishimoto, Alexander G. Huth & Jack L. Gallant (2013): Attention during natural vision warps semantic representation across the human brain. Nature Neuroscience, 16(6), 763+.[.pdf]
Alexander G. Huth, Shinji Nishimoto, An T. Vu & Jack L. Gallant. (2012): A continuous semantic space describes the representation of thousands of object and action categories across the human brain. Neuron, 76, 1210-1224.[.pdf]
Thomas Naselaris, Kendrick N. Kay, Shinji Nishimoto & Jack L. Gallant. (2011): Encoding and decoding in fMRI. Neuroimage, 56, 400-410.[.pdf]