Discovery from brain image data (and more): language in the brain
Tom M. Mitchell · 2019
How does the human brain use neural activity to create and represent meanings of words, phrases, sentences and stories? One way to study this question is to collect brain image data to observe neural activity while people read text. We have been doing such experiments with fMRI (1 mm spatial resolution) and MEG (1 msec time resolution) brain imaging, and developing novel machine learning approaches to analyze this data. As a result, we have learned answers to questions such as "Are the neural encodings of word meaning the same in your brain and mine?", and "What sequence of neurally encoded information flows through the brain during the half-second in which the brain comprehends a word?" This talk will summarize our machine learning approach to data discovery, and some of what we have learned about the human brain as a result. We will also consider the question of how reuse and aggregation of such scientific data might change the future of research in cognitive neuroscience.