A neural mechanism for conserved value computations integrating information and rewards
Ethan S. Bromberg-Martin, Yang-Yang Feng, Takaya Ogasawara, Jesse White, Kaining Zhang, Ilya E. Monosov
Abstract
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.