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Updated: Aug 30, 2026

Studying Food Reward and Motivation in Humans
Published on: March 19, 2014
Correlated coding of motivation and outcome of decision by dopamine neurons
Takemasa Satoh1, Sadamu Nakai, Tatsuo Sato
1Department of Physiology, Kyoto Prefectural University of Medicine, Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto 602-8566, Japan.
Abstract:
We recorded the activity of midbrain dopamine neurons in an instrumental conditioning task in which monkeys made a series of behavioral decisions on the basis of distinct reward expectations. Dopamine neurons responded to the first visual cue that appeared in each trial [conditioned stimulus (CS)] through which monkeys initiated trial for decision while expecting trial-specific reward probability and volume. The magnitude of neuronal responses to the CS was approximately proportional to reward expectations but with considerable discrepancy. In contrast, CS responses appear to represent motivational properties, because their magnitude at trials with identical reward expectation had significant negative correlation with reaction times of the animal after the CS. Dopamine neurons also responded to reinforcers that occurred after behavioral decisions, and the responses precisely encoded positive and negative reward expectation errors (REEs). The gain of coding REEs by spike frequency increased during learning act-outcome contingencies through a few months of task training, whereas coding of motivational properties remained consistent during the learning. We found that the magnitude of CS responses was positively correlated with that of reinforcers, suggesting a modulation of the effectiveness of REEs as a teaching signal by motivation. For instance, rate of learning could be faster when animals are motivated, whereas it could be slower when less motivated, even at identical REEs. Therefore, the dual correlated coding of motivation and REEs suggested the involvement of the dopamine system, both in reinforcement in more elaborate ways than currently proposed and in motivational function in reward-based decision-making and learning.
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