Medial Frontal Cortex Activity Predicts Information Sampling in Economic Choice

Common neural choice signals can emerge artefactually amid multiple distinct value signals

Previous work has identified characteristic neural signatures of value-based decision-making, including neural dynamics that closely resemble the ramping evidence accumulation process believed to underpin choice. Here we test whether these signatures of the choice process can be temporally dissociated from additional, choice-'independent' value signals. Indeed, EEG activity during value-based choice revealed distinct spatiotemporal clusters, with a stimulus-locked cluster reflecting affective reactions to choice sets and a response-locked cluster reflecting choice difficulty. Surprisingly, 'neither' of these clusters met the criteria for an evidence accumulation signal. Instead, we found that stimulus-locked activity can 'mimic' an evidence accumulation process when aligned to the response. Re-analysing four previous studies, including three perceptual decision-making studies, we show that response-locked signatures of evidence accumulation disappear when stimulus-locked and response-locked activity are modelled jointly. Collectively, our findings show that neural signatures of value can reflect choice-independent processes and look deceptively like evidence accumulation.

Neural mechanisms of information seeking

We ubiquitously seek information to make better decisions. Particularly in the modern age, when more information is available at our fingertips than ever, the information we choose to collect determines the quality of our decisions. Decision neuroscience has long adopted empirical approaches where the information available to decision-makers is fully controlled by the researchers, leaving neural mechanisms of information seeking less understood. Although information seeking has long been studied in the context of the exploration-exploitation trade-off, recent studies have widened the scope to investigate more overt information seeking in a way distinct from other decision processes. Insights gained from these studies, accumulated over the last few years, raise the possibility that information seeking is driven by the reward system signaling the subjective value of information. In this piece, we review findings from the recent studies, highlighting the conceptual and empirical relationships between distinct literatures, and discuss future research directions necessary to establish a more comprehensive understanding of how individuals seek information as a part of value-based decision-making.

A Distinct Neural Code Supports Prospection of Future Probabilities During Instrumental Information-Seeking

To make adaptive decisions, we must actively demand information, but relatively little is known about the mechanisms of active information gathering. An open question is how the brain estimates expected information gains (EIG) when comparing the current decision uncertainty with the uncertainty that is expected after gathering information. We examined this question using fMRI in a task in which people placed bids to obtain information in conditions that varied independently by prior decision uncertainty, information diagnosticity, and the penalty for an erroneous choice. Consistent with value of information theory, bids were sensitive to EIG and its components of prior certainty and expected posterior certainty. Expected posterior certainty was decoded above chance from multivoxel activation patterns in the posterior parietal and extrastriate cortices. This representation was independent of instrumental rewards and overlapped with distinct representations of EIG and prior certainty. Thus, posterior parietal and extrastriate cortices are candidates for mediating the prospection of posterior probabilities as a key step to estimate EIG during active information gathering.

Social learning across adolescence: A Bayesian neurocognitive perspective

Adolescence is a period of social re-orientation in which we are generally more prone to peer influence and the updating of our beliefs based on social information, also called social learning, than in any other stage of our life. However, how do we know when to use social information and whose information to use and how does this ability develop across adolescence? Here, we review the social learning literature from a behavioral, neural and computational viewpoint, focusing on the development of brain systems related to executive functioning, value-based decision-making and social cognition. We put forward a Bayesian reinforcement learning framework that incorporates social learning about value associated with particular behavior and uncertainty in our environment and experiences. We discuss how this framework can inform us about developmental changes in social learning, including how the assessment of uncertainty and the ability to adaptively discriminate between information from different social sources change across adolescence. By combining reward-based decision-making in the domains of both informational and normative influence, this framework explains both negative and positive social peer influence in adolescence.

Anterior cingulate cortex causally supports flexible learning under motivationally challenging and cognitively demanding conditions

Anterior cingulate cortex (ACC) and striatum (STR) contain neurons encoding not only the expected values of actions, but also the value of stimulus features irrespective of actions. Values about stimulus features in ACC or STR might contribute to adaptive behavior by guiding fixational information sampling and biasing choices toward relevant objects, but they might also have indirect motivational functions by enabling subjects to estimate the value of putting effort into choosing objects. Here, we tested these possibilities by modulating neuronal activity in ACC and STR of nonhuman primates using transcranial ultrasound stimulation while subjects learned the relevance of objects in situations with varying motivational and cognitive demands. Motivational demand was indexed by varying gains and losses during learning, while cognitive demand was varied by increasing the uncertainty about which object features could be relevant during learning. We found that ultrasound stimulation of the ACC, but not the STR, reduced learning efficiency and prolonged information sampling when the task required averting losses and motivational demands were high. Reduced learning efficiency was particularly evident at higher cognitive demands and when subjects experienced loss of already attained tokens. These results suggest that the ACC supports flexible learning of feature values when loss experiences impose a motivational challenge and when uncertainty about the relevance of objects is high. Taken together, these findings provide causal evidence that the ACC facilitates resource allocation and improves visual information sampling during adaptive behavior.

Indoor Air Pollution and Decision-Making Behavior: An Interdisciplinary Review

The human brain is constantly exposed to air pollutants, some of which might be disruptive or even lethal to certain neurons implicated in abstract features of cognitive function. In this review, we present new evidence from behavioral and neural studies in humans, suggesting a link between indoor fine particulate matter and decision-making behavior. To illustrate this relationship, we use qualitative sources, such as historical documents of the Vietnam War to develop hypotheses of how aerial transmission of pollutants might obstruct alternative choices during the evaluation of policy decisions. We first describe the neural circuits driving decision-making processes by addressing how neurons and their cognate receptors directly evaluate and transduce physical phenomena into sensory perceptions that allow us to decide the best course of action among competing alternatives. We then raise the possibility that indoor air pollutants might also impact cell-signaling systems outside the brain parenchyma to further obstruct the computational analysis of the social environment. We also highlight how particulate matter might be pathologically integrated into the brain to override control of sensory decisions, and thereby perturb selection of choice. These lines of research aim to extend our understanding of how inhalation of airborne particulates and toxicants in smoke, for example, might contribute to cognitive impairment and negative health outcomes.

Medial and orbital frontal cortex in decision-making and flexible behavior

The medial frontal cortex and adjacent orbitofrontal cortex have been the focus of investigations of decision-making, behavioral flexibility, and social behavior. We review studies conducted in humans, macaques, and rodents and argue that several regions with different functional roles can be identified in the dorsal anterior cingulate cortex, perigenual anterior cingulate cortex, anterior medial frontal cortex, ventromedial prefrontal cortex, and medial and lateral parts of the orbitofrontal cortex. There is increasing evidence that the manner in which these areas represent the value of the environment and specific choices is different from subcortical brain regions and more complex than previously thought. Although activity in some regions reflects distributions of reward and opportunities across the environment, in other cases, activity reflects the structural relationships between features of the environment that animals can use to infer what decision to take even if they have not encountered identical opportunities in the past.

Dynamic Representation of the Subjective Value of Information

To improve future decisions, people should seek information based on the value of information (VOI), which depends on the current evidence and the reward structure of the upcoming decision. When additional evidence is supplied, people should update the VOI to adjust subsequent information seeking, but the neurocognitive mechanisms of this updating process remain unknown. We used a modified beads task to examine how the VOI is represented and updated in the human brain of both sexes. We theoretically derived, and empirically verified, a normative prediction that the VOI depends on decision evidence and is biased by reward asymmetry. Using fMRI, we found that the subjective VOI is represented in the right dorsolateral prefrontal cortex (DLPFC). Critically, this VOI representation was updated when additional evidence was supplied, showing that the DLPFC dynamically tracks the up-to-date VOI over time. These results provide new insights into how humans adaptively seek information in the service of decision-making.SIGNIFICANCE STATEMENT For adaptive decision-making, people should seek information based on what they currently know and the extent to which additional information could improve the decision outcome, formalized as the VOI. Doing so requires dynamic updating of VOI according to outcome values and newly arriving evidence. We formalize these principles using a normative model and show that information seeking in people adheres to them. Using fMRI, we show that the underlying subjective VOI is represented in the dorsolateral prefrontal cortex and, critically, that it is updated in real time according to newly arriving evidence. Our results reveal the computational and neural dynamics through which evidence and values are combined to inform constantly evolving information-seeking decisions.