Anastasia Gorelova in Phys.Org:
In a paper published in Nature Neuroscience last week, University of Pittsburgh researchers described how reward signals in the brain are modulated by uncertainty. Dopamine signals are intertwined with reward learning; they teach the brain which cues or actions predict the best rewards. New findings from the Stauffer lab at Pitt School of Medicine indicate that dopamine signals also reflect the certainty surrounding reward predictions. In short, dopamine signals might teach the brain about the likelihood of getting a reward.
Briefly, what is the background for this study?
KR: We were studying ambiguity—a complex environmental factor that makes it hard for humans and animals to know what to predict—and this project was a cool detour that arose organically from our preliminary data. We found something interesting that we were not expecting, and we saw it to completion.
WS: Dopamine neurons are crucial for reward learning. Dopamine neurons are activated by rewards that are better than predicted and suppressed by rewards that are worse than predicted. This pattern of activity is reminiscent of “reward prediction errors,” the differences between received and predicted rewards. Reward prediction errors are crucial to animal and machine learning. However, in classical animal and machine learning theories, ‘predicted rewards’ are simply the average value of past outcomes. Although these predictions are useful, it would be much more useful to predict average values as well as more complex statistics that reflect uncertainty. Therefore, we wanted to know whether dopamine teaching signals reflect those more complex statistics, and whether they could be used to teach the brain about real-world incentives.