In the past decade, scientists have been excited about new analytical methods, using machine learning, that allow us to track information coded in patterns of brain activity. We can use them to “read” out from brain activity what participants are looking at or paying attention to, or even what they are imagining. But are the codes we read out with our machine learning algorithms actually the same codes used by the brain? To find out, CBU scientists examined how information coding changes when participants make mistakes. We found that codes in key frontoparietal brain regions predicted what sort of error a person would make, while codes elsewhere in the brain did not. This suggests a key role for activity in frontoparietal brain regions in determining behavioural performance and provides a method to determine which brain codes are meaningfully related to human behaviour.
Citation: Woolgar, A., Dermody, N., Afshar, S., Williams, M. A., & Rich, A. N. (2019). Meaningful patterns of information in the brain revealed through analysis of errors. bioRxiv, 673681.
Citation: Linking the brain with behaviour: the neural dynamics of success and failure in goal-directed behaviour
Amanda K. Robinson, Anina N. Rich, Alexandra Woolgar (bioRxiv 2021)