When we learn a new skill, the brain has to decide ' cell by cell ' what to change. New research from MIT suggests it can do that with surprising precision, sending targeted feedback to individual neurons so each one can adjust its activity in the right direction. The finding echoes a key idea from modern artificial intelligence. Many AI systems learn by comparing their output to a target, computing an 'error' signal, and using it to fine-tune connections within the network. A long-standing question has been whether the brain also uses that kind of individualized feedback. In an open-access study published in the Feb. 25 issue of the journal Nature, MIT researchers report evidence that it does. A research team led by Mark Harnett, a McGovern Institute for Brain Research investigator and associate professor in the Department of Brain and Cognitive Sciences at MIT, discovered these instructive signals in mice by training animals to control the activity of specific neurons using a...
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