Can be used for medical diagnosis, has empiric assessment of visual perception and mental control of computers
About
Summary Many research inroads have been made into understanding data from human brain activity. New brain assessment devices beyond classing EEG data, such as MRIs and PET scans, have increased this available data stream. However, the information is often only inferentially related to specific brain activity. There is an important need for individuals with limited physical capacity to control devices and communicate with others. Work towards this end has been pursued in BMI research. There is the potential in brain activity sensing devices to provide these capacities by other means as well. Researchers at the University of California, Berkeley have made important strides in accomplishing these goals with software which can identify natural images from human brain activity. This provides an opportunity for a visual BMI. An encoding model is constructed that describes how visual stimuli are represented in the pattern of activity across visual cortex. The activity that the image produces in visual cortex has proven out to be systematically related to the particular visual stimulus that is being viewed at any point in time. The UCB model is a variant of those that have been developed by the sensory neuroscience community over the last 50 years. The current research suggests that fMRI-based measurements of brain activity contain much more information about underlying neural processes than might have been expected. In fact so much information is available in these signals that one day it may even be possible to reconstruct the visual contents of dreams or visual imagery. To identify which of the images elicited the measured activity the decoder scans through all possible images, and for each image it predicts what pattern of brain activity should have been elicited if that image had actually been seen. Then the decoder simply chooses the image whose predicted brain activity is most similar to the measured brain activity. Decoding visual content is conceptually related to the neural-motor prosthesis BMI work build a decoder that can be used to drive a prosthetic arm or other device from brain activity. While the current research is focused on visual perception, other sensory systems, such as touch, taste, hearing, etc, are also amenable to analysis using the innovative software. The potential use of this technology in the legal system brings with it most of the problems that are already known regarding eyewitness testimony.