[초청강연] Mesolimbic dopamine release conveys causal associations - 유망과학자세미나

Mesolimbic dopamine release conveys causal associations
Huijeong Jeong
Department of Neurology, University of California, San Francisco, CA, USA
Learning to predict rewards based on environmental cues is essential for survival. It is widely
believed that animals learn to predict rewards by updating predictions whenever the outcome
deviates from expectations. Such violations of predictions are called reward prediction errors
(RPEs). RPEs are the critical teaching signal in the most widely accepted model for associative
learning—temporal difference reinforcement learning (TDRL). As TDRL RPE has been successful
at explaining the activity dynamics of dopamine, it has become the dominant theory of
dopamine’s role as the critical regulator of learning. However, recent results reported that
dopamine signaling may not be fully consistent with RPEs, suggesting the necessity of new
learning model.
An alternative approach to learn cue-reward associations is to infer the cause of
meaningful outcomes such as rewards. Since causes must precede outcomes, a viable approach
to infer whether a cue causes reward is to learn whether the cue consistently precedes reward.
This approach is advantageous in real world because cues often outnumber the meaningful
outcomes (e.g., rewards). Using this intuition, here we propose a causal inference algorithm that
infers whether a cue is a cause of reward. Based on this algorithm, we denote stimuli (cues or
rewards) whose cause should be learned by the animal as “meaningful causal targets” and
propose that mesolimbic dopamine signals whether a current event is a meaningful causal target.
We found that our model makes similar predictions as RPEs under commonly studied
experimental settings.
Hence, to distinguish between the two hypotheses (RPEs or causal associations), we
performed experimental tests by measuring dopamine release in nucleus accumbens core. We
found that mesolimbic dopamine conveys causal associations but not RPE in every case, thereby
challenging the dominant theory of reward learning in the brain. Our results provide a new
conceptual and biological framework for associative learning.