Professor Jack Gallant, a UC Berkeley neuroscientist, and his colleagues published a study in 2011 in the journal Current Biology, where they presented a new motion-energy encoding model that largely overcomes the limitations of slow BOLD signals in fMRI. The model describes fast visual information and slow hemodynamics by separate components. The authors recorded BOLD signals in occipitotemporal visual cortex of human subjects who watched natural movies and fit the model separately to individual voxels. Visualization of the fit models reveals how early visual areas represent the information in movies. They also constructed a Bayesian decoder which provides remarkable reconstructions of the viewed movies. These results demonstrate that dynamic brain activity measured under naturalistic conditions can be decoded using current fMRI technology.

This could have tremendous implications for stroke, coma patients or blind patients by creating artificial retinas, for instance.

For the full article, please click here

Youtube movie: Brain Activity Reconstruction