Department News



Ju Tian (l) and Nao Uchida

Imagine you are a child hoping to get a teddy bear from your parents as a birthday gift. What if they gave you a box of candies instead? Or, worse, what if they forgot your birthday entirely? Naturally, you might feel disappointed. On the other hand, you might be quite pleased if your parents gave you the same candies as a surprise on another day. In this case, your response to a gift is dramatically influenced by your expectation. Our brains always compare the rewards we get with what we expected.
But how does this comparison happen in our brains? Neurons that use dopamine as a neurotransmitter (“dopamine neurons”) seem to represent the difference between actual reward and expectation. For instance, dopamine neurons transiently pause their spontaneous firing when an expected reward is omitted. Interestingly, this response occurs when reward was expected but was not granted. In other words, when nothing happened! This signal — a dip in activity — occurs exactly when reward was expected to happen. More generally, dopamine neurons are known to signal error in reward prediction, a.k.a reward prediction errors. When the outcome is better than expected, dopamine neurons increase their firing rates. When the outcome is worse than expected, their firing rates decrease. How dopamine neurons generate these prediction errors remains unknown.
In our study published in Neuron, we examined the contribution of a region of the brain called the habenula to dopamine prediction error signals. The habenula has long been a mysterious area, located at the very center of the brain, bridging the forebrain and the midbrain. Recent studies revealed that neurons in the lateral habenula signal prediction errors, although the direction of the responses (excitation versus inhibition) was opposite that of dopamine neurons. Given the existence of an inhibitory projection from the lateral habenula onto dopamine neurons, it has been hypothesized that dopamine neurons may relay prediction error signals from the habenula. To test this hypothesis, we removed input from the habenula by making an electrolytic lesion and examined what aspects of prediction error signals were affected in dopamine neurons. We found that, in animals with habenula lesions, the dip caused by reward omission was largely diminished. Surprisingly, the dip caused by aversive stimuli (e.g. an air puff) was not affected or enhanced. Note that negative prediction error can occur, for example, (1) when not receiving an expected reward (disappointment) or (2) when receiving an unexpected negative outcome (punishment). Our study showed that these types of negative prediction error are regulated by different mechanisms.
In our previous study (Eshel et al., 2015), we found that reward expectation reduces reward responses in a subtractive fashion. While divisive gain changes are common in the nervous system, subtraction is rarely found in the brain and its mechanisms are unknown. A key feature of subtractive computation is that dopamine neurons reduce their activity below baseline when reward is smaller than expected. In this new study, we found a key mechanism that pushes down dopamine neuron firing below baseline.
Our study also opens doors for future research. We found that many aspects of prediction error signals in dopamine neurons remain intact after large lesions in the habenula. This implies that other inputs to dopamine neurons are also making important contributions to prediction error coding. Based on our anatomical mapping of dopamine inputs (Menegas et al., 2015; Watabe-Uchida et al., 2012), areas such as the striatum, lateral hypothalamus, and tegmental areas are at the top of the list for future investigation.

Read more in Neuron or download PDF








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