Lesions to different regions of frontal cortex have dissociable effects on voluntary persistence.

Deciding how long to keep waiting for uncertain future rewards is a complex problem. Previous research has shown that choosing to stop waiting results from an evaluative process that weighs the subjective value of the awaited reward against the opportunity cost of waiting. Activity in ventromedial prefrontal cortex (vmPFC) tracks the dynamics of this evaluation, while activation in the dorsomedial prefrontal cortex (dmPFC) and anterior insula (AI) ramps up before a decision to quit is made.

Dynamic estimation of the attentional field from visual cortical activity.

Navigating around the world, we must adaptively allocate attention to our surroundings based on anticipated future stimuli and events. This allocation of spatial attention boosts visuocortical representations at attended locations and locally enhances perception. Indeed, spatial attention has often been analogized to a "spotlight" shining on the item of relevance.

The effects of emotional arousal on pupil size depend on luminance.

Pupillometry is widely used to measure arousal states. The primary functional role of the pupil, however, is to respond to the luminance of visual inputs. We previously demonstrated that cognitive effort-related arousal interacted multiplicatively with luminance, with the strongest pupillary effects of arousal occurring at low-to-mid luminances (< 37 cd/m), implying a narrow range of conditions ideal for assessing cognitive arousal-driven pupillary differences.

Lesions to different regions of frontal cortex have dissociable effects on voluntary persistence.

Deciding how long to keep waiting for uncertain future rewards is a complex problem. Previous research has shown that choosing to stop waiting results from an evaluative process that weighs the subjective value of the awaited reward against the opportunity cost of waiting. In functional neuroimaging data, activity in ventromedial prefrontal cortex (vmPFC) tracks the dynamics of this evaluation, while activation in the dorsomedial prefrontal cortex (dmPFC) and anterior insula (AI) ramps up before a decision to quit is made.

Statistical information about reward timing is insufficient for promoting optimal persistence decisions.

When deciding how long to keep waiting for delayed rewards that will arrive at an uncertain time, different distributions of possible reward times dictate different optimal strategies for maximizing reward. When reward timing distributions are heavy-tailed (e.g.

Experience-driven recalibration of learning from surprising events.

Different environments favor different patterns of adaptive learning. A surprising event that in one context would accelerate belief updating might, in another context, be downweighted as a meaningless outlier. Here, we investigated whether people would spontaneously regulate the influence of surprise on learning in response to event-by-event experiential feedback.

Assessing evidence accumulation and rule learning in humans with an online game.

Evidence accumulation, an essential component of perception and decision making, is frequently studied with psychophysical tasks involving noisy or ambiguous stimuli. In these tasks, participants typically receive verbal or written instructions that describe the strategy that should be used to guide decisions. Although convenient and effective, explicit instructions can influence learning and decision making strategies and can limit comparisons with animal models, in which behaviors are reinforced through feedback.

Arousal-based pupil modulation is dictated by luminance.

Pupillometry has become a standard measure for assessing arousal state. However, environmental factors such as luminance, a primary dictator of pupillary responses, often vary across studies. To what degree does luminance interact with arousal-driven pupillary changes? Here, we parametrically assessed luminance-driven pupillary responses across a wide-range of luminances, while concurrently manipulating cognitive arousal using auditory math problems of varying difficulty.

Choices favoring cognitive effort in a foraging environment decrease when multiple forms of effort and delay are interleaved.

Cognitive and physical effort are typically regarded as costly, but demands for effort also seemingly boost the appeal of prospects under certain conditions. One contextual factor that might influence choices for or against effort is the mix of different types of demand a decision maker encounters in a given environment. In two foraging experiments, participants encountered prospective rewards that required equally long intervals of cognitive effort, physical effort, or unfilled delay.

Dynamic Network Analysis Demonstrates the Formation of Stable Functional Networks During Rule Learning.

Variations in the functional connectivity of large-scale cortical brain networks may explain individual differences in learning ability. We used a dynamic network analysis of fMRI data to identify changes in functional brain networks that are associated with context-dependent rule learning. During fMRI scanning, naïve subjects performed a cognitive task designed to test their ability to learn context-dependent rules.

Eye movements reflect adaptive predictions and predictive precision.

Successful decision-making depends on the ability to form predictions about uncertain future events. Existing evidence suggests predictive representations are not limited to point estimates but also include information about the associated level of predictive uncertainty. Estimates of predictive uncertainty have an important role in governing the rate at which beliefs are updated in response to new observations.

Variability in the analysis of a single neuroimaging dataset by many teams.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data.

Functional brain network reconfiguration during learning in a dynamic environment.

When learning about dynamic and uncertain environments, people should update their beliefs most strongly when new evidence is most informative, such as when the environment undergoes a surprising change or existing beliefs are highly uncertain. Here we show that modulations of surprise and uncertainty are encoded in a particular, temporally dynamic pattern of whole-brain functional connectivity, and this encoding is enhanced in individuals that adapt their learning dynamics more appropriately in response to these factors. The key feature of this whole-brain pattern of functional connectivity is stronger connectivity, or functional integration, between the fronto-parietal and other functional systems.

Time-conjunctive representations of future events.

It is widely accepted that people can predict the relative imminence of future events. However, it is unknown whether the timing of future events is represented using only a "strength-like" estimate or if future events are represented conjunctively with their position on a mental timeline. We examined how people judge temporal relationships among anticipated future events using the novel Judgment of Anticipated Co-Occurrence (JACO) task.

Spectral partitioning identifies individual heterogeneity in the functional network topography of ventral and anterior medial prefrontal cortex.

Regions of human medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) are part of the default network (DN), and additionally are implicated in diverse cognitive functions ranging from autobiographical memory to subjective valuation. Our ability to interpret the apparent co-localization of task-related effects with DN-regions is constrained by a limited understanding of the individual-level heterogeneity in mPFC/PCC functional organization. Here we used cortical surface-based meta-analysis to identify a parcel in human PCC that was more strongly associated with the DN than with valuation effects.

Dissociable Forms of Uncertainty-Driven Representational Change Across the Human Brain.

Environmental change can lead decision makers to shift rapidly among different behavioral regimes. These behavioral shifts can be accompanied by rapid changes in the firing pattern of neural networks. However, it is unknown what the populations of neurons that participate in such "network reset" phenomena are representing.

The effects of acute stress on the calibration of persistence.

People frequently fail to wait for delayed rewards after choosing them. These preference reversals are sometimes thought to reflect self-control failure. Other times, however, continuing to wait for a delayed reward may be counterproductive (e.

Do Political and Economic Choices Rely on Common Neural Substrates? A Systematic Review of the Emerging Neuropolitics Literature.

The methods of cognitive neuroscience are beginning to be applied to the study of political behavior. The neural substrates of value-based decision-making have been extensively examined in economic contexts; this might provide a powerful starting point for understanding political decision-making. Here, we asked to what extent the neuropolitics literature to date has used conceptual frameworks and experimental designs that make contact with the reward-related approaches that have dominated decision neuroscience.

Medial prefrontal cortical activity reflects dynamic re-evaluation during voluntary persistence.

Deciding how long to keep waiting for future rewards is a nontrivial problem, especially when the timing of rewards is uncertain. We carried out an experiment in which human decision makers waited for rewards in two environments in which reward-timing statistics favored either a greater or lesser degree of behavioral persistence. We found that decision makers adaptively calibrated their level of persistence for each environment.

Functionally dissociable influences on learning rate in a dynamic environment.

Maintaining accurate beliefs in a changing environment requires dynamically adapting the rate at which one learns from new experiences. Beliefs should be stable in the face of noisy data but malleable in periods of change or uncertainty. Here we used computational modeling, psychophysics, and fMRI to show that adaptive learning is not a unitary phenomenon in the brain.

Neural and behavioral evidence for an intrinsic cost of self-control.

The capacity for self-control is critical to adaptive functioning, yet our knowledge of the underlying processes and mechanisms is presently only inchoate. Theoretical work in economics has suggested a model of self-control centering on two key assumptions: (1) a division within the decision-maker between two 'selves' with differing preferences; (2) the idea that self-control is intrinsically costly. Neuroscience has recently generated findings supporting the 'dual-self' assumption.

The valuation system: a coordinate-based meta-analysis of BOLD fMRI experiments examining neural correlates of subjective value.

Numerous experiments have recently sought to identify neural signals associated with the subjective value (SV) of choice alternatives. Theoretically, SV assessment is an intermediate computational step during decision making, in which alternatives are placed on a common scale to facilitate value-maximizing choice. Here we present a quantitative, coordinate-based meta-analysis of 206 published fMRI studies investigating neural correlates of SV.

Rational temporal predictions can underlie apparent failures to delay gratification.

An important category of seemingly maladaptive decisions involves failure to postpone gratification. A person pursuing a desirable long-run outcome may abandon it in favor of a short-run alternative that has been available all along. Here we present a theoretical framework in which this seemingly irrational behavior emerges from stable preferences and veridical judgments.

Decision makers calibrate behavioral persistence on the basis of time-interval experience.

A central question in intertemporal decision making is why people reverse their own past choices. Someone who initially prefers a long-run outcome might fail to maintain that preference for long enough to see the outcome realized. Such behavior is usually understood as reflecting preference instability or self-control failure.