AI teaches neuroscience about reward signalling.

Computer scientists have successfully developed reinforcement learning algorithms that present outcomes and rewards along a probability distribution. Previously, such algorithms simply presented an average outcome and associated reward. A spread of possible outcomes is of course truer to life. Neuroscientists have taken a leaf out of the AI book and discovered that the brain works in a similar fashion. Thus, the neurons in the dopaminergic reward prediction error network are all different. They too react to outcomes along a distribution curve.

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