Computer model explains how people act for rewards

Learning to associate rewarding outcomes with specific actions is a key part of survival like searching for food or avoiding predators.

Researchers wanted to look at how people learned from feedback – particularly how people learned to associate actions to new unexpected outcomes.

“To do this, we created a series of computational models to show how the firing of dopamine neurons caused by receiving reward ultimately translates into selecting the causative action more frequently in the future,” explained Mark Humphries from the University of Manchester.

It is already known that actions are represented in the cortex — the brain’s outer layer of neural tissue — and rewarding outcomes activate neurons that release a brain chemical called dopamine.

These neuronal signals are sent to another area of the brain, the striatum which plays an important role in selecting which action to take.

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