Dissociable neural mechanisms track evidence accumulation for selection of attention versus action

Abstract

Decision-making is typically studied as a sequential process from the selection of what to attend (e.g., between possible tasks, stimuli, or stimulus attributes) to the selection of which actions to take based on the attended information. However, people often gather information across these levels in parallel. For instance, even as they choose their actions, they may continue to evaluate how much to attend other tasks or dimensions of information within a task. We scanned participants while they made such parallel evaluations, simultaneously weighing how much to attend two dynamic stimulus attributes and which response to give based on the attended information. Regions of prefrontal cortex tracked information about the stimulus attributes in dissociable ways, related to either the predicted reward (ventromedial prefrontal cortex) or the degree to which that attribute was being attended (dorsal anterior cingulate, dACC). Within dACC, adjacent regions tracked uncertainty at different levels of the decision, regarding what to attend versus how to respond. These findings bridge research on perceptual and value-based decision-making, demonstrating that people dynamically integrate information in parallel across different levels of decision making.Naturalistic decisions allow an individual to weigh their options within a particular task (e.g., how best to word the introduction to a paper) while also weighing how much to attend other tasks (e.g., responding to e-mails). These different types of decision-making have a hierarchical but reciprocal relationship: Decisions at higher levels inform the focus of attention at lower levels (e.g., whether to select between citations or email addresses) while, at the same time, information at lower levels (e.g., the salience of an incoming email) informs decisions regarding which task to attend. Critically, recent studies suggest that decisions across these levels may occur in parallel, continuously informed by information that is integrated from the environment and from one’s internal milieu1,2.Research on cognitive control and perceptual decision-making has examined how responses are selected when attentional targets are clearly defined (e.g., based on instruction to attend a stimulus dimension), including cases in which responding requires accumulating information regarding a noisy percept (e.g., evidence favoring a left or right response)3-7. Separate research on value-based decision-making has examined how individuals select which stimulus dimension(s) to attend in order to maximize their expected rewards8-11. However, it remains unclear how the accumulation of evidence to select high-level goals and/or attentional targets interacts with the simultaneous accumulation of evidence to select responses according to those goals (e.g., based on the perceptual properties of the stimuli). Recent work has highlighted the importance of such interactions to understanding task selection12-15, multi-attribute decision-making16-18, foraging behavior19-21, cognitive effort22,23, and self-control24-27.While these interactions remain poorly understood, previous research has identified candidate neural mechanisms associated with multi-attribute value-based decision-making11,28,29 and with selecting a response based on noisy information from an instructed attentional target3–5. These research areas have implicated the ventromedial prefrontal cortex (vmPFC) in tracking the value of potential targets of attention (e.g., stimulus attributes)8,11 and the dorsal anterior cingulate cortex (dACC) in tracking an individual’s uncertainty regarding which response to select30–32. It has been further proposed that dACC may differentiate between uncertainty at each of these parallel levels of decision-making (e.g., at the level of task goals or strategies vs. specific motor actions), and that these may be separately encoded at different locations along the dACC’s rostrocaudal axis32,33. However, neural activity within and across these prefrontal regions has not yet been examined in a setting in which information is weighed at both levels within and across trials.Here we use a value-based perceptual decision-making task to examine how people integrate different dynamic sources of information to decide (a) which perceptual attribute to attend and (b) how to respond based on the evidence for that attribute. Participants performed a task in which they regularly faced a conflict between attending the stimulus attribute that offered the greater reward or the attribute that was more perceptually salient (akin to persevering in writing one’s paper when an enticing email awaits). We demonstrate that dACC and vmPFC track evidence for the two attributes in dissociable ways. Across these regions, vmPFC weighs attribute evidence by the reward it predicts and dACC weighs it by its attentional priority (i.e., the degree to which that attribute drives choice). Within dACC, adjacent regions differentiated between uncertainty at the two levels of the decision, regarding what to attend (rostral dACC) versus how to respond (caudal dACC).

A neural network for information seeking

“…ACC information signals changed several hundred milliseconds before gaze shifts, while BG signals changed more proximally to behavior. This finding supports and extends theories that ACC is especially important for motivating behavioral shifts to explore available prospects and learn their reward value and other properties [61][62][63] , tracking their level of uncertainty and how it evolves over time as beliefs are updated in response to surprising outcomes 12,62,[64][65][66][67][68] , and using this information to decide how to control future cognition and behavior 62,69 . In particular, while it is well acknowledged that the ACC needs to receive a broad array of reward-and uncertainty-related information to perform these functions 62,69 , our data indicates that the ACC is not a mere passive recipient of this information; rather, the ACC is tightly linked to the emergence of motivational drive to actively seek out that information from the environment.…”

Neurocomputational mechanisms underlying motivated seeing

“…In addition to the frontoparietal activations, the dorsal anterior cingulate cortex (dACC) and insula were also more active on Motivation Consistent trials. The dACC and insula are part of a salience network involved in the detection of motivationally salient stimuli 40,41 , and the dACC has been recently implicated in determining what stimulus feature to attend to in a perceptual decision-making task 42 . The increased activity in the salience network on Motivation Consistent trials might be responsible for the selection of motivationally relevant features for enhanced processing.…”

The Best Laid Plans: Computational Principles of Anterior Cingulate Cortex

“…The HRL-ACC model applies a similar division of labor to the domain of action selection: dorsal areas of ACC, which are closely linked to motor behavior, control performance over specific tasks (e.g., climbing a barrier in a maze), whereas rostral areas of ACC control the execution of higherlevel options (e.g., switching between egocentric and allocentric navigation strategies) [15]. Recent support for this idea comes from fMRI studies revealing that dACC is sensitive to reward values corresponding to overt gains whereas rACC is more sensitive to higher-level goals [46], and that dACC accumulates evidence about how best to respond in a task whereas rACC accumulates evidence about what task strategy to deploy [47]. Further, a recent study that recorded the intracranial electroencephalogram in humans revealed that rACC determines the set point at which the agent switches between action plans and dACC utilizes feedback to determine whether to continue with or switch between the plans according to that set point [48].…”