RESUMO
The dorsal raphe nucleus (DRN) is implicated in psychiatric disorders that feature impaired sensitivity to reward amount, impulsivity when facing reward delays, and risk-seeking when confronting reward uncertainty. However, it has been unclear whether and how DRN neurons signal reward amount, reward delay, and reward uncertainty during multi-attribute value-based decision-making, where subjects consider these attributes to make a choice. We recorded DRN neurons as monkeys chose between offers whose attributes, namely expected reward amount, reward delay, and reward uncertainty, varied independently. Many DRN neurons signaled offer attributes, and this population tended to integrate the attributes in a manner that reflected monkeys' preferences for amount, delay, and uncertainty. After decision-making, in response to post-decision feedback, these same neurons signaled signed reward prediction errors, suggesting a broader role in tracking value across task epochs and behavioral contexts. Our data illustrate how the DRN participates in value computations, guiding theories about the role of the DRN in decision-making and psychiatric disease.
Assuntos
Tomada de Decisões , Núcleo Dorsal da Rafe , Macaca mulatta , Neurônios , Recompensa , Animais , Núcleo Dorsal da Rafe/fisiologia , Núcleo Dorsal da Rafe/metabolismo , Tomada de Decisões/fisiologia , Incerteza , Neurônios/fisiologia , MasculinoRESUMO
Behavioral and economic theory dictate that we decide between options based on their values. However, humans and animals eagerly seek information about uncertain future rewards, even when this does not provide any objective value. This implies that decisions are made by endowing information with subjective value and integrating it with the value of extrinsic rewards, but the mechanism is unknown. Here, we show that human and monkey value judgements obey strikingly conserved computational principles during multi-attribute decisions trading off information and extrinsic reward. We then identify a neural substrate in a highly conserved ancient structure, the lateral habenula (LHb). LHb neurons signal subjective value, integrating information's value with extrinsic rewards, and the LHb predicts and causally influences ongoing decisions. Neurons in key input areas to the LHb largely signal components of these computations, not integrated value signals. Thus, our data uncover neural mechanisms of conserved computations underlying decisions to seek information about the future.