Computer model explains how people act for rewards

Their model revealed how several brain signals work together to shape the inputs so the appropriate action is chosen.

“The model reveals that the relative strength of cortical inputs, which represent different possible actions, to the two populations of dopamine responsive cells, determines whether an action is selected or suppressed,” added professor Kevin Gurney from the University of Sheffield.

The model could provide new insights into the mechanisms behind motor disorders such as Parkinson’s disease.

It may also shed light on conditions involving abnormal learning such as addiction, the authors concluded.

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