Subjective Value Of Reward Research Articles

Neural reward system reflects individual value comparison strategy in cost-benefit decisions

AbstractA core assumption in decision neuroscience is that individuals decide between options by comparing option-specific subjective reward values. Psychological accounts challenge this view and suggest that decisions are better explained by comparisons between choice attributes than by comparisons between option-specific values, casting doubts on the interpretation of activation in the neural reward system as subjective value signals. Here, we provide neuroimaging and pharmacological evidence that value-related neural activity follows the value comparison strategy employed by an individual on the psychological level. Neural model comparisons reveal that activation in the striatum, rather than generally reflecting attribute-wise or option-wise value comparisons, reflects the value comparison strategy that provides the best explanation for an individual’s choice behavior. Strikingly, manipulating activation in the dopaminergic reward system reveals that dopamine antagonism counteracts the engagement in an individual’s dominant value comparison strategy. Together, our findings provide evidence for the biological plausibility of psychological accounts of decision making and emphasize the importance of neural model comparisons to prevent misinterpretations of brain activation.

Representation of Anticipated Rewards and Punishments in the Human Brain.

Subjective value is a core concept in neuroeconomics, serving as the basis for decision making. Despite the extensive literature on the neural encoding of subjective reward value in humans, the neural representation of punishment value remains relatively understudied. This review synthesizes current knowledge on the neural representation of reward value, including methodologies, involved brain regions, and the concept of common currency representation of diverse reward types in decision-making and learning processes. We then critically examine existing research on the neural representation of punishment value, highlighting conceptual and methodological challenges in human studies and insights gained from animal research. Finally, we explore how individual differences in reward and punishment processing may be linked to various mental illnesses, with a focus on stress-related psychopathologies. This review advocates for the integration of both rewards and punishments within value-based decision-making and learning frameworks, leveraging insights from cross-species studies and utilizing ecological gamified paradigms to reflect real-life scenarios.

Dopamine neurons encode trial-by-trial subjective reward value in an auction-like task

The dopamine reward prediction error signal is known to be subjective but has so far only been assessed in aggregate choices. However, personal choices fluctuate across trials and thus reflect the instantaneous subjective reward value. In the well-established Becker-DeGroot-Marschak (BDM) auction-like mechanism, participants are encouraged to place bids that accurately reveal their instantaneous subjective reward value; inaccurate bidding results in suboptimal reward (“incentive compatibility”). In our experiment, male rhesus monkeys became experienced over several years to place accurate BDM bids for juice rewards without specific external constraints. Their bids for physically identical rewards varied trial by trial and increased overall for larger rewards. In these highly experienced animals, responses of midbrain dopamine neurons followed the trial-by-trial variations of bids despite constant, explicitly predicted reward amounts. Inversely, dopamine responses were similar with similar bids for different physical reward amounts. Support Vector Regression demonstrated accurate prediction of the animals’ bids by as few as twenty dopamine neurons. Thus, the phasic dopamine reward signal reflects instantaneous subjective reward value.

The role of impulsivity and binge eating in outpatients with overweight or obesity: an EEG temporal discounting study

BackgroundBinge eating (BE) is associated with a range of cognitive control deficits related to impulsivity, including lower response inhibition, preference for immediate gratification, and maladaptive decision-making. The aim was to investigate whether impulsivity and BE may interact with the decision process and underlying brain activity in outpatients with overweight or obesity who are starting a treatment to achieve weight loss.MethodsA sample of 26 treatment-seeking outpatients with overweight or obesity was evaluated for impulsivity, BE, and temporal discounting rates. Impulsivity was measured with the Barratt Impulsiveness Scale (BIS-11), according to which two groups were composed: high BIS and low BIS; BE was assessed with the eating disorders module of the Structured Clinical Interview for DSM5—Research Version, according to which two groups were composed: with (BE group) or without BE (NBE group). Changes in subjective value of rewards were measured with the Temporal Discounting Task (TDt) where participants had to choice between sooner but smaller vs. later but larger monetary rewards. These choices were made in two differently delayed conditions (“Now” and “Not-now”). Brain rhythms were recorded through high-density electroencephalogram (hd-EEG) during the TDt.ResultsPatients with BE reported more impulsive tendencies and perceived sooner rewards as more gratifying when both options were delayed (Not-now condition, p = 0.02). The reward choice in the TDt was accompanied by a general EEG alpha band desynchronization in parietal areas observed without differences between experimental conditions and patients groups. No effects were observed within the Now condition or in the other EEG bands.ConclusionsThe tendency to favor immediate rewards may constitute an obstacle to adhering to treatment plans and achieving weight loss goals for outpatients with overweight or obesity. Clinicians are therefore encouraged to include psychological factors, such as impulsivity and dysfunctional eating behaviors, when designing weight loss programs. By addressing these psychological aspects, clinicians can better support patients in overcoming barriers to adherence and achieving sustainable weight loss.Trial registrationThis study was approved by the Ethics Committee of the Department of Psychological, Health, and Territorial Sciences of the University G. d’Annunzio of Chieti-Pescara (Prot. n. 254 of 03/14/2017).

A dopamine mechanism for reward maximization

Individual survival and evolutionary selection require biological organisms to maximize reward. Economic choice theories define the necessary and sufficient conditions, and neuronal signals of decision variables provide mechanistic explanations. Reinforcement learning (RL) formalisms use predictions, actions, and policies to maximize reward. Midbrain dopamine neurons code reward prediction errors (RPE) of subjective reward value suitable for RL. Electrical and optogenetic self-stimulation experiments demonstrate that monkeys and rodents repeat behaviors that result in dopamine excitation. Dopamine excitations reflect positive RPEs that increase reward predictions via RL; against increasing predictions, obtaining similar dopamine RPE signals again requires better rewards than before. The positive RPEs drive predictions higher again and thus advance a recursive reward-RPE-prediction iteration toward better and better rewards. Agents also avoid dopamine inhibitions that lower reward prediction via RL, which allows smaller rewards than before to elicit positive dopamine RPE signals and resume the iteration toward better rewards. In this way, dopamine RPE signals serve a causal mechanism that attracts agents via RL to the best rewards. The mechanism improves daily life and benefits evolutionary selection but may also induce restlessness and greed.

Spontaneous neural activity in the three principal networks underlying delay discounting: a resting-state fMRI study.

Delay discounting, the decline in the subjective value of future rewards over time, has traditionally been understood through a tripartite neural network model, comprising the valuation, cognitive control, and prospection networks. To investigate the applicability of this model in a resting-state context, we employed a monetary choice questionnaire to quantify delay discounting and utilized resting-state functional magnetic resonance imaging (rs-fMRI) to explore the role of spontaneous brain activity, specifically regional homogeneity (ReHo), in influencing individual differences in delay discounting across a large cohort (N = 257). Preliminary analyses revealed a significant negative correlation between delay discounting tendencies and the ReHo in both the left insula and the right hippocampus, respectively. Subsequent resting-state functional connectivity (RSFC) analyses, using these regions as seed ROIs, disclosed that all implicated brain regions conform to the three principal networks traditionally associated with delay discounting. Our findings offer novel insights into the role of spontaneous neural activity in shaping individual variations in delay discounting at both regional and network levels, providing the first empirical evidence supporting the applicability of the tripartite network model in a resting-state context.

Brain responses and connectivity to visual meal compositions: An EEG investigation into food liking

Understanding food liking, which shapes individual preferences for certain foods, is important for enhancing consumer satisfaction, encouraging healthier eating habits, and developing effective nutritional interventions. In this study, we aimed to investigate the neural underpinnings of food liking. We used electroencephalography (EEG) as a neuroscientific approach and visual food stimuli comprising various compositions of Korean meals. Our focus was to examine changes in brain responses and functional connectivity resulting from variations in visual meal compositions. The behavioral results showed that participants exhibited increased liking for meals with increased compositions. EEG source analysis demonstrated increased activity in the anterior insula, fusiform gyrus, precuneus, ventromedial prefrontal cortex, and medial orbitofrontal cortex (mOFC) and decreased activity in the dorsolateral prefrontal cortex (dlPFC) with increased meal liking. Furthermore, functional connectivity analysis revealed reduced connectivity between the dlPFC and both the mOFC and the anterior insula with increased meal liking. Notably, lower dlPFC-mOFC connectivity was associated with a greater preference for visual meal stimuli. Together, these results suggest that a decrease in neural communication between the brain regions responsible for subjective reward value processing and cognitive control, indicating a shift in attention towards the rewarding aspects of food, plays a significant role in food-liking decisions. Our study also emphasizes the integral role of various brain regions in determining food preference, thereby providing evidence for further neuroscientific investigations into dietary decision-making processes.

Temporal discounting in children and adolescents with and without attention-deficit/hyperactivity disorder: a comparison of four scoring methods

ABSTRACT Temporal discounting (TD) tasks measure the preference for immediate rewards over larger delayed rewards and have been widely used to study impulsivity in children and adolescents with Attention-Deficit/Hyperactivity Disorder (ADHD). Relatively impulsive individuals tend to show high inconsistency in their choices, which makes it difficult to determine commonly used TD outcome measures (e.g., area under the curve, AUC). In this study, we leveraged two published datasets to compare four methods to compute TD outcome measures in children and adolescents (8–17 years) with (n = 107) and without ADHD (n = 128): two predetermined rules methods, a proportion method, and logistic regression. In both datasets, when using the two predetermined rules methods and the proportion method, TD outcomes were highly correlated and group differences in TD were similar. When using logistic regression, a large proportion of AUCs (95% in dataset 1; 33% in dataset 2) could not be computed due to inconsistent choice patterns. These findings indicate that predetermined rules methods (for studies with small sample sizes and experienced raters) and a proportion method (for studies with larger sample sizes or less experienced raters) are recommended over logistic regression when determining subjective reward values for participants with inconsistent choice patterns.

Dissociable neural after-effects of cognitive and physical effort expenditure during reward evaluation.

The reward after-effect of effort expenditure refers to the phenomenon that previous effort investment changes the subjective value of rewards when obtained. However, the neural mechanisms underlying the after-effects of effort exertion are still not fully understood. We investigated the modulation of reward after-effects by effort type (cognitive vs. physical) through the lens of neural dynamics. Thirty-two participants performed a physically or cognitively demanding task during an effort phase and then played a simple gambling game during a subsequent reward phase to earn monetary rewards while their electroencephalogram (EEG) was recorded. We found that previous effort expenditure decreased electrocortical activity during feedback evaluation. Importantly, this effort effect occurred in a domain-general manner during the early stage (as indexed by the reward positivity) but in a domain-specific manner during the later and more elaborative stage (as indexed by the P3 and delta oscillation) of reward evaluation. Additionally, effort expenditure enhanced P3 sensitivity to feedback valence regardless of effort type. Our findings suggest that cognitive and physical effort, although bearing some surface resemblance to each other, may have dissociable neural influences on the reward after-effects.

Worth the Work? Monkeys Discount Rewards by a Subjective Adapting Effort Cost.

All life must solve how to allocate limited energy resources to maximize benefits from scarce opportunities. Economic theory posits decision makers optimize choice by maximizing the subjective benefit (utility) of reward minus the subjective cost (disutility) of the required effort. While successful in many settings, this model does not fully account for how experience can alter reward-effort trade-offs. Here, we test how well the subtractive model of effort disutility explains the behavior of two male nonhuman primates (Macaca mulatta) in a binary choice task in which reward quantity and physical effort to obtain were varied. Applying random utility modeling to independently estimate reward utility and effort disutility, we show the subtractive effort model better explains out-of-sample choice behavior when compared with parabolic and exponential effort discounting. Furthermore, we demonstrate that effort disutility depends on previous experience of effort: in analogy to work from behavioral labor economics, we develop a model of reference-dependent effort disutility to explain the increased willingness to expend effort following previous experience of effortful options in a session. The result of this analysis suggests that monkeys discount reward by an effort cost that is measured relative to an expected effort learned from previous trials. When this subjective cost of effort, a function of context and experience, is accounted for, trial-by-trial choices can be explained by the subtractive cost model of effort. Therefore, in searching for net utility signals that may underpin effort-based decision-making in the brain, careful measurement of subjective effort costs is an essential first step.SIGNIFICANCE STATEMENT All decision-makers need to consider how much effort they need to expend when evaluating potential options. Economic theories suggest that the optimal way to choose is by cost-benefit analysis of reward against effort. To be able to do this efficiently over many decision contexts, this needs to be done flexibly, with appropriate adaptation to context and experience. Therefore, in aiming to understand how this might be achieved in the brain, it is important to first carefully measure the subjective cost of effort. Here, we show monkeys make reward-effort cost-benefit decisions, subtracting the subjective cost of effort from the subjective value of rewards. Moreover, the subjective cost of effort is dependent on the monkeys' experience of effort in previous trials.

Mouse-cursor trajectories reveal reduced contextual influence on decision conflict during delay discounting in anorexia nervosa.

The capacity of individuals with anorexia nervosa (AN) to forgo immediate food rewards in their long-term pursuit of thinness is thought to reflect elevated self-control and/or abnormal reward sensitivity. Prior research attempted to capture an increased tendency to delay gratification in AN using delay-discounting tasks that assess how rapidly the subjective value of rewards decreases as a function of time until receipt. However, significant effects were mostly subtle or absent. Here, we tested whether the process leading to such decisions might be altered in AN. We recorded mouse-cursor movement trajectories leading to the final choice in a computerized delay-discounting task (238 trials) in 55 acutely underweight females with AN and pairwise age-matched female healthy controls (HC). We tested for group differences in deviations from a direct choice path, a measure of conflict strength in decision making, and whether group moderated the effect of several predictors of conflict strength (e.g., choice difficulty, consistency). We also explored reaction times and changes in trajectory directions (X-flips). No group differences in delay-discounting parameters or movement trajectories were detected. However, the effect of the aforementioned predictors on deviations (and to a lesser extent reaction times) was reduced in AN. These findings suggest that while delay discounting and conflict strength in decision making are generally unaltered in AN, conflict strength was more stable across different decisions in the disorder. This might enable individuals with AN to pursue (maladaptive) long-term body-weight goals, because particularly conflicting choices may not be experienced as such. The deviations from a direct path of mouse-cursor movements during a computerized delay-discounting task varied less in people with anorexia nervosa. Assuming such deviations measure decision conflict, we speculate that this increased stability might help people with anorexia nervosa achieve their long-term weight goals, as for them the struggle with the decision to eat high-calorie meals when hungry will be milder, so they would be more likely to skip them.

Physical effort paradox during reward evaluation and links to perceived control.

Effort expenditure not only prospectively discounts the reward associated with it but also retrospectively adds the subjective value of reward, which is known as the effort paradox. This study aimed to resolve the effort paradox during reward evaluation through the critical lens of neural dynamics and its potential moderators. In total, 40 participants completed an effort-reward task wherein they exerted varying physical efforts to obtain an opportunity to win monetary rewards by active or passive decision-making. We found that after-effects of physical effort expenditure during reward evaluation unfolded as an effort paradox over time, manifesting itself as an effort discounting effect during the reward positivity (RewP) period but as an effort enhancement effect during the late positive potential (LPP) interval. Then, we found a dynamic balance between the discounting effect and the enhancement effect such that the more effort discounted the RewP at the early stage, the more effort increased the LPP at the late stage. Moreover, we observed that the effort-reward relationship was modulated by perceived control such that it increased the reward sensitivity effect and decreased the effort discounting effect. Together, our findings provide new insights into the neural mechanisms underlying the after-effects of physical effort exertion during reward evaluation.

The Impact of Social Media Salience on the Subjective Value of Social Cues

Like face-to-face interactions, evidence shows that interacting on social media is rewarding. However, the rewards associated with social media are subject to unpredictable delays, which may shape how they are experienced. Specifically, these delays might enhance the subjective desirability of social rewards and subsequent reward-seeking behavior by sensitizing people to the presence of such rewards. Here, we ask whether thinking about a recent social media post or conversation influences the subjective value of monetary and social rewards. Across two studies, we find that individuals who are thinking about a recent social media post are more likely to sacrifice small financial gains for the chance to see a genuine smile (a social reward) compared with those who are thinking about a recent conversation. This suggests that rather than satisfying social needs, thinking about social media interactions enhances the subjective value of social rewards, potentially explaining the incentive value of social media.

Cognitive effort for self, strangers, and charities

Effort is aversive and often avoided, even when earning benefits for oneself. Yet, people sometimes work hard for others. How do people decide who is worth their effort? Prior work shows people avoid physical effort for strangers relative to themselves, but invest more physical effort for charity. Here, we find that people avoid cognitive effort for others relative to themselves, even when the cause is a personally meaningful charity. In two studies, participants repeatedly decided whether to invest cognitive effort to gain financial rewards for themselves and others. In Study 1, participants (N = 51; 150 choices) were less willing to invest cognitive effort for a charity than themselves. In Study 2, participants (N = 47; 225 choices) were more willing to work cognitively for a charity than an intragroup stranger, but again preferred cognitive exertion that benefited themselves. Computational modeling suggests that, unlike prior physical effort findings, cognitive effort discounted the subjective value of rewards linearly. Exploratory machine learning analyses suggest that people who represented others more similarly to themselves were more willing to invest effort on their behalf, opening up new avenues for future research.

Neural encoding of food and monetary reward delivery

Different types of rewards such as food and money can similarly drive our behavior owing to shared brain processes encoding their subjective value. However, while the value of money is abstract and needs to be learned, the value of food is rooted in the innate processing of sensory properties and nutritional utilization. Yet, the actual consumption of food and the receipt of money have never been directly contrasted in the same experiment, questioning what unique neural processes differentiate those reward types. To fill this gap, we examined the distinct and common neural responses to the delivery of food and monetary rewards during fMRI.In a novel experimental approach, we parametrically manipulated the subjective value of food and monetary rewards by modulating the quantities of administered palatable milkshake and monetary gains. The receipt of increasing amounts of milkshake and money recruited the ventral striatum and the ventromedial prefrontal cortex, previously associated with value encoding. Notably, the consumption and the subsequent evaluation of increasing quantities of milkshake relative to money revealed an extended recruitment of brain regions related to taste, somatosensory processing, and salience. Moreover, we detected a decline of reward encoding in the ventral tegmental area, nucleus accumbens, and vmPFC, indicating that these regions may be susceptible to time-dependent effects upon accumulation of food and money rewards.Relative to monetary gains, the consumption and evaluation of palatable milkshakes engaged complex neural processing over and above value tracking, emphasizing the critical contribution of taste and other sensory properties to the processing of food rewards. Furthermore, our results highlight the need to closely monitor metabolic states and neural responses to the accumulation of rewards to pinpoint the mechanisms underlying time-dependent dynamics of reward-related processing.

The Resting-State Neural Network of Delay Discounting.

Delay discounting is a common phenomenon in daily life, which refers to the subjective value of a future reward decreasing as a function of time. Previous studies have identified several cortical regions involved in delay discounting, but the neural network constructed by the cortical regions of delay discounting is less clear. In this study, we employed resting-state functional magnetic resonance imaging (RS-fMRI) to measure the spontaneous neural activity in a large sample of healthy young adults and used the Monetary Choice Questionnaire to directly measure participants’ level of delay discounting. To identify the neural network of delay discounting at rest, we used an individual difference approach to explore brain regions whose spontaneous activities were related to delay discounting across the whole brain. Then, these brain regions served as seeds to identify the neural network of delay discounting. We found that the fractional amplitude of low-frequency fluctuations (fALFF) of the left insula were positively correlated to delay discounting. More importantly, its connectivity to the anterior cingulate cortex was read out for participants’ behavioral performance in the task of delay discounting. In short, our study provides empirical evidence that insula-anterior cingulate cortex connectivity may serve as a part of the neural network for delay discounting.

A meta-analysis of the effects of episodic future thinking on delay discounting

Delay discounting (DD) refers to the phenomenon in which the subjective value of future rewards is reduced over time. There are individual differences in the DD rate, and increased discounting has been observed in those with various psychiatric disorders. Episodic future thinking (EFT) is the act of vividly imagining events that may happen in the future. Studies have shown that EFT could reduce DD, although inconsistent results have been reported. The aim of this meta-analysis was to clarify the efficacy with which EFT reduces DD and to identify potential moderators. Forty-seven studies (including 63 contrasts) were included in the final analysis. EFT was found to significantly reduce DD (Hedges’ g = 0.52). Moderator analysis showed that positive EFT ( g = 0.64) was more effective in reducing DD than EFT with the valence not specifically mentioned ( g = 0.28) and EFT with neutral or negative valence ( g = –0.03). In addition, several factors related to the control task and DD task were related to the efficacy of EFT to reduce DD. These findings have implications for using EFT to reduce DD in the future.

Reward Value Revealed by Auction in Rhesus Monkeys.

Economic choice is thought to involve the elicitation of the subjective values of the choice options. Thus far, value estimation in animals has relied on stochastic choices between multiple options presented in repeated trials and expressed from averages of dozens of trials. However, subjective reward valuations are made moment-to-moment and do not always require alternative options; their consequences are usually felt immediately. Here, we describe a Becker-DeGroot-Marschak (BDM) auction-like mechanism that provides more direct and simple valuations with immediate consequences. The BDM encourages agents to truthfully reveal their true subjective value in individual choices ("incentive compatibility"). Male monkeys reliably placed well-ranked BDM bids for up to five juice volumes while paying from a water budget. The bids closely approximated the average subjective values estimated with conventional binary choices (BCs), thus demonstrating procedural invariance and aligning with the wealth of knowledge acquired with these less direct estimation methods. The feasibility of BDM bidding in monkeys paves the way for an analysis of subjective neuronal value signals in single trials rather than from averages; the feasibility also bridges the gap to the increasingly used BDM method in human neuroeconomics.SIGNIFICANCE STATEMENT The subjective economic value of rewards cannot be measured directly but must be inferred from observable behavior. Until now, the estimation method in animals was rather complex and required comparison between several choice options during repeated choices; thus, such methods did not respect the imminence of the outcome from individual choices. However, human economic research has developed a simple auction-like procedure that can reveal in a direct and immediate manner the true subjective value in individual choices [Becker-DeGroot-Marschak (BDM) mechanism]. The current study implemented this mechanism in rhesus monkeys and demonstrates its usefulness for eliciting meaningful value estimates of liquid rewards. The mechanism allows future neurophysiological assessment of subjective reward value signals in single trials of controlled animal tasks.

Relationship of ventral striatum activation during effort discounting to clinical amotivation severity in schizophrenia

Motivational deficits play a central role in disability due to negative symptoms of schizophrenia (SZ), but limited pathophysiological understanding impedes critically needed therapeutic development. We applied an fMRI Effort Discounting Task (EDT) that quantifies motivation using a neuroeconomic decision-making approach, capturing the degree to which effort requirements produce reductions in the subjective value (SV) of monetary reward. An analyzed sample of 21 individuals with SZ and 23 group-matched controls performed the EDT during fMRI. We hypothesized that ventral striatum (VS) as well as extended brain motivation circuitry would encode SV, integrating reward and effort costs. We also hypothesized that VS hypoactivation during EDT decisions would demonstrate a dimensional relationship with clinical amotivation severity, reflecting greater suppression by effort costs. As hypothesized, VS as well as a broader cortico-limbic network were activated during the EDT and this activation correlated positively with SV. In SZ, activation to task decisions was reduced selectively in VS. Greater VS reductions correlated with more severe clinical amotivation in SZ and across all participants. However, these diagnosis and amotivation effects could not be explained by the response to parametric variation in reward, effort, or model-based SV. Our findings demonstrate that VS hypofunction in schizophrenia is manifested during effort-based decisions and reflects dimensional motivation impairment. Dysfunction of VS impacting effort-based decision-making can provide a target for biomarker development to guide novel efforts to assess and treat disabling amotivation.

Unique features of stimulus-based probabilistic reversal learning.

Reversal learning paradigms are widely used assays of behavioral flexibility with their probabilistic versions being more amenable to studying integration of reward outcomes over time. Prior research suggests differences between initial and reversal learning, including higher learning rates, a greater need for inhibitory control, and more perseveration after reversals. However, it is not well-understood what aspects of stimulus-based reversal learning are unique to reversals, and whether and how observed differences depend on reward probability. Here, we used a visual probabilistic discrimination and reversal learning paradigm where male and female rats selected between a pair of stimuli associated with different reward probabilities. We compared accuracy, rewards collected, omissions, latencies, win-stay/lose-shift strategies, and indices of perseveration across two different reward probability schedules. We found that discrimination and reversal learning are behaviorally more unique than similar: Fit of choice behavior using reinforcement learning models revealed a lower sensitivity to the difference in subjective reward values (greater exploration) and higher learning rates for the reversal phase. We also found latencies to choose the better option were greater in females than males, but only for the reversal phase. Further, animals employed more win-stay strategies during early discrimination and increased perseveration during early reversal learning. Interestingly, a consistent reward probability group difference emerged with a richer environment associated with longer reward collection latencies than a leaner environment. Future studies should systematically compare the neural correlates of fine-grained behavioral measures to reveal possible dissociations in how the circuitry is recruited in each phase. (PsycInfo Database Record (c) 2021 APA, all rights reserved).