Consider the range of social behaviours we engage in every day. In each case, there are a multitude of unknowns, reflecting the many sources of uncertainty inherent to social inference. We describe ...how uncertainty manifests in social environments (the thoughts and intentions of others are largely hidden, making it difficult to predict a person's behaviour) and why people are motivated to reduce the aversive feelings generated by uncertainty. We propose a three-part model whereby social uncertainty is initially reduced through automatic modes of inference (such as impression formation) before more control-demanding modes of inference (such as perspective-taking) are deployed to narrow one's predictions even more. Finally, social uncertainty is attenuated further through learning processes that update these predictions based on new information. Our framework integrates research across fields to offer an account of the mechanisms motivating social cognition and action, laying the groundwork for future experiments that can illuminate the impact of uncertainty on social cognition.
Debates over the function(s) of dorsal anterior cingulate cortex (dACC) have persisted for decades. So too have demonstrations of the region's association with cognitive control. Researchers have ...struggled to account for this association and, simultaneously, dACC's involvement in phenomena related to evaluation and motivation. We describe a recent integrative theory that achieves this goal. It proposes that dACC serves to specify the currently optimal allocation of control by determining the overall expected value of control (EVC), thereby licensing the associated cognitive effort. The EVC theory accounts for dACC's sensitivity to a wide array of experimental variables, and their relationship to subsequent control adjustments. Finally, we contrast our theory with a recent theory proposing a primary role for dACC in foraging-like decisions. We describe why the EVC theory offers a more comprehensive and coherent account of dACC function, including dACC's particular involvement in decisions regarding foraging or otherwise altering one's behavior.
An organism's survival depends on its ability to learn about its environment and to make adaptive decisions in the service of achieving the best possible outcomes in that environment. To study the ...neural circuits that support these functions, researchers have increasingly relied on models that formalize the computations required to carry them out. Here, we review the recent history of computational modeling of learning and decision-making, and how these models have been used to advance understanding of prefrontal cortex function. We discuss how such models have advanced from their origins in basic algorithms of updating and action selection to increasingly account for complexities in the cognitive processes required for learning and decision-making, and the representations over which they operate. We further discuss how a deeper understanding of the real-world complexities in these computations has shed light on the fundamental constraints on optimal behavior, and on the complex interactions between corticostriatal pathways to determine such behavior. The continuing and rapid development of these models holds great promise for understanding the mechanisms by which animals adapt to their environments, and what leads to maladaptive forms of learning and decision-making within clinical populations.
The dorsal anterior cingulate cortex (dACC) has a near-ubiquitous presence in the neuroscience of cognitive control. It has been implicated in a diversity of functions, from reward processing and ...performance monitoring to the execution of control and action selection. Here, we propose that this diversity can be understood in terms of a single underlying function: allocation of control based on an evaluation of the expected value of control (EVC). We present a normative model of EVC that integrates three critical factors: the expected payoff from a controlled process, the amount of control that must be invested to achieve that payoff, and the cost in terms of cognitive effort. We propose that dACC integrates this information, using it to determine whether, where and how much control to allocate. We then consider how the EVC model can explain the diverse array of findings concerning dACC function.
The dorsal anterior cingulate cortex (dACC) has been implicated in diverse functions related to cognitive control. Here, Shenhav et al. propose a unifying view of dACC function where dACC integrates information about the expected value of control to determine whether, where and how much control to allocate.
In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly understood. Although most researchers agree that mental effort is aversive and stems from limitations in ...our capacity to exercise cognitive control, it is unclear what gives rise to those limitations and why they result in an experience of control as costly. The presence of these control costs also raises further questions regarding how best to allocate mental effort to minimize those costs and maximize the attendant benefits. This review explores recent advances in computational modeling and empirical research aimed at addressing these questions at the level of psychological process and neural mechanism, examining both the limitations to mental effort exertion and how we manage those limited cognitive resources. We conclude by identifying remaining challenges for theoretical accounts of mental effort as well as possible applications of the available findings to understanding the causes of and potential solutions for apparent failures to exert the mental effort required of us.
Researchers and educators have long wrestled with the question of how best to teach their clients be they humans, non-human animals or machines. Here, we examine the role of a single variable, the ...difficulty of training, on the rate of learning. In many situations we find that there is a sweet spot in which training is neither too easy nor too hard, and where learning progresses most quickly. We derive conditions for this sweet spot for a broad class of learning algorithms in the context of binary classification tasks. For all of these stochastic gradient-descent based learning algorithms, we find that the optimal error rate for training is around 15.87% or, conversely, that the optimal training accuracy is about 85%. We demonstrate the efficacy of this 'Eighty Five Percent Rule' for artificial neural networks used in AI and biologically plausible neural networks thought to describe animal learning.
Many important moral decisions, particularly at the policy level, require the evaluation of choices involving outcomes of variable magnitude and probability. Many economic decisions involve the same ...problem. It is not known whether and to what extent these structurally isomorphic decisions rely on common neural mechanisms. Subjects undergoing fMRI evaluated the moral acceptability of sacrificing a single life to save a larger group of variable size and probability of dying without action. Paralleling research on economic decision making, the ventromedial prefrontal cortex and ventral striatum were specifically sensitive to the “expected moral value” of actions, i.e., the expected number of lives lost/saved. Likewise, the right anterior insula was specifically sensitive to outcome probability. Other regions tracked outcome certainty and individual differences in utilitarian tendency. The present results suggest that complex life-and-death moral decisions that affect others depend on neural circuitry adapted for more basic, self-interested decision making involving material rewards.
► Complex moral decision making parallels complex economic decision making ► vmPFC encodes subjective representations of expected value in life-and-death judgment ► Insula activity tracks differences in behavioral sensitivity to probability of death ► Ventral striatal activity tracks individual sensitivity to “expected moral value”
To invest effort into any cognitive task, people must be sufficiently motivated. Whereas prior research has focused primarily on how the cognitive control required to complete these tasks is ...motivated by the potential rewards for success, it is also known that control investment can be equally motivated by the potential negative consequence for failure. Previous theoretical and experimental work has yet to examine how positive and negative incentives differentially influence the manner and intensity with which people allocate control. Here, we develop and test a normative model of control allocation under conditions of varying positive and negative performance incentives. Our model predicts, and our empirical findings confirm, that rewards for success and punishment for failure should differentially influence adjustments to the evidence accumulation rate versus response threshold, respectively. This dissociation further enabled us to infer how motivated a given person was by the consequences of success versus failure.
Disgust reactions can be elicited using stimuli that engender orogastric rejection (e.g., pus and vomit; core disgust stimuli) but also using images of bloody injuries or medical procedures (e.g., ...surgeries; blood body boundary violation B-BV disgust stimuli). These two types of disgust reaction are presumed to be connected by a common evolutionary function of avoiding either food- or blood-borne contaminants. However, reactions to bloody injuries are typically conflated with reactions to the potential pain being experienced by the victim. This may explain why the two forms of "disgust", although similarly communicated (through self-report and facial expressions), evince different patterns of physiological reactivity. Therefore, we tested whether the communicative similarities and physiological dissimilarities would hold when markers of potential contamination in the latter category are removed, leaving only painful injuries that lack blood or explicit body-envelope violations. Participants viewed films that depicted imagery associated with (a) core disgust, (b) painful injuries, or (c) neutral scenes while we measured facial, cardiovascular, and gastric reactivity. Whereas communicative measures (self-report and facial muscles) suggested that participants experienced increased disgust for core disgust and painful injuries, peripheral physiology dissociated the two: core disgust decreased normal gastric activity and painful-injury disgust decelerated heart rate and increased heart rate variability. These findings suggest that expressions of disgust toward bodily injuries may reflect a fundamentally different affective response than those evoked by core disgust and that this (cardiovascularly mediated) response may in fact be more closely tied to pain perceptions (or empathy) rather than contaminant-laden stimuli.
Decomposing the Motivation to Exert Mental Effort Shenhav, Amitai; Prater Fahey, Mahalia; Grahek, Ivan
Current directions in psychological science : a journal of the American Psychological Society,
08/2021, Volume:
30, Issue:
4
Journal Article
Peer reviewed
Open access
Achieving most goals demands cognitive control, yet people vary widely in their success at meeting these demands. Although motivation is known to be fundamental to determining success at achieving a ...goal, what determines motivation to perform a given task remains poorly understood. Here, we describe recent efforts toward addressing this question using the expected-value-of-control model, which simulates the process by which people weigh the costs and benefits of exerting mental effort. This model functionally decomposes this cost-benefit analysis and has been used to fill gaps in understanding of the mechanisms of mental effort and to generate novel predictions about the sources of variability in real-world performance. We discuss the opportunities the model provides for formalizing hypotheses about why people vary in their motivation to perform tasks, as well as for understanding limitations in researchers’ ability to test these hypotheses using a given measure of performance.
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