Adaptive information seeking is critical for goal-directed behavior. Growing evidence suggests the importance of intrinsic motives such as curiosity or need for novelty, mediated through dopaminergic valuation systems, in driving information-seeking behavior. However, valuing information for its own sake can be highly suboptimal when agents need to evaluate instrumental benefit of information in a forward-looking manner.

Specifically, using a task where subjects could purchase information to reduce uncertainty about outcomes of a monetary lottery, we found information purchase decisions could be captured by a computational model incorporating utility of anticipation, a form of noninstrumental motive for information seeking, in addition to instrumental benefits.

Neurally, trial-by-trial variation was correlated with activity in striatum and ventromedial prefrontal cortex. Furthermore, cross-categorical decoding revealed that, within these regions. These findings provide support for the common currency hypothesis and shed insight on neurocognitive mechanisms underlying information-seeking behavior. Collecting too little information, paying too much for information, not discriminating relevant information from irrelevant ones, or acting on unreliable or false information, can all result in failure to achieve desired goals. Understanding neurocognitive mechanisms of adaptive information seeking is not only important in neuroscience, psychology, and economics, but also has wide real-world applications, such as policymaking, public health, and artificial intelligence.

The importance to evaluate forward-looking instrumental benefit has long been recognized in economic and ethological studies of decision-making, owing to abundance of information seeking in problems ranging from comparison shopping to job/mate search. Normative economic accounts presume that agents acquire information only as a consequence of utility maximization. Specifically, instrumental benefit of information is measured as value of information (VOI), i.e., how much it would improve choices and expected utility (EU); agents acquire the information only if its VOI outweighs its cost.

Although normative VOI calculation may be computationally more complex than basic rewards (e.g., food or money), subsequent processes of cost-benefit analysis and action selection can be similar to other types of value-driven choices.