Dissociating valuation and saliency signals during decision-making

Neural similarity at temporal lobe and cerebellum predicts out-of-sample preference and recall for video stimuli

The extent to which brains respond similarly to a specific stimulus, across a small group of individuals, has been previously found to predict out-of-sample aggregate preference for that stimulus. However, the location in the brain where neural similarity predicts out-of-sample preference remains unclear. In this article, we attempt to identify the neural substrates in three functional magnetic resonance imaging (fMRI) studies. Two fMRI studies (N = 40 and 20), using previously broadcasted TV commercials, show that spatiotemporal neural similarity at temporal lobe and cerebellum predict out-of-sample preference and recall. A follow-up fMRI study (N = 28) with previously unseen movie-trailers replicated the predictive effect of neural similarity. Moreover, neural similarity provided unique information on out-of-sample preference above and beyond in-sample preference. Overall, the findings suggest that neural similarity at temporal lobe and cerebellum - traditionally associated with sensory integration and emotional processing - may reflect the level of engagement with video stimuli.

Movement Vigor as a Reflection of Subjective Economic Utility

To understand subjective evaluation of an option, various disciplines have quantified the interaction between reward and effort during decision making, producing an estimate of economic utility, namely the subjective 'goodness' of an option. However, variables that affect utility of an option also influence the vigor of movements toward that option. For example, expectation of reward increases speed of saccadic eye movements, whereas expectation of effort decreases this speed. These results imply that vigor may serve as a new, real-time metric with which to quantify subjective utility, and that the control of movements may be an implicit reflection of the brain's economic evaluation of the expected outcome.

Exogenous testosterone and the monoamine-oxidase A polymorphism influence anger, aggression and neural responses to provocation in males

Testosterone and the monoamine oxidase-A (MAOA) polymorphism are potential neuromodulators for aggression. By acting on similar brain circuits, they might interactively influence human behavior. The current study investigates the causal role of testosterone on aggression-related brain activity and the potential interaction with the MAOA polymorphism. In a double-blind process, 93 healthy males received a testosterone or placebo gel. In an fMRI session, participants performed a Taylor aggression paradigm in which they received provoking feedback and could afterwards decide how aggressively they would react. Testosterone and cortisol levels as well as subjective anger were assessed prior and after the task. Circulating testosterone levels were higher in carriers of the long compared to the short MAOA allele. An interaction of the MAOA polymorphism and testosterone administration was identified in the cuneus, where short allele carriers in the placebo group showed diminished activity in the decision period. Task-related anger was significantly higher in this group. Overall, a mesocorticolimbic network was implicated in processing of high versus low provoking feedback, and core hubs of the default mode network were implicated in the subsequent decision after high versus low provocation. Testosterone administration increased activation in this network. The data provides evidence for an interaction of the MAOA polymorphism and exogenous testosterone on anger and suggests that interactive effects on the brain signal could underlie differential emotional reactivity. The increased default mode activation in the testosterone group suggests an enhanced engagement of social cognition related regions possibly supporting responsivity towards social provocation. This article is part of the Special Issue entitled 'Current status of the neurobiology of aggression and impulsivity'.

The evil of banality: When choosing between the mundane feels like choosing between the worst

Our most important decisions often provoke the greatest anxiety, whether we seek the better of two prizes or the lesser of two evils. Yet many of our choices are more mundane, such as selecting from a slate of mediocre but acceptable restaurants. Previous research suggests that choices of decreasing value should provoke decreasing anxiety. Here we show that this is not the case. Across three behavioral studies and one fMRI study, we find that anxiety and its neural correlates demonstrate a U-shaped function of choice set value, greatest when choosing between both the highest value and lowest value sets. Intermediate (moderate-value) choice sets provoke the least anxiety, even when they are just as difficult to select between as the choice sets at the two extremes. We show that these counterintuitive findings are accounted for by decision makers perceiving low-value items as aversive (i.e., negatively motivationally salient) rather than simply unrewarding. Importantly, though, neural signatures of these anxious reactions only appear when participants are required to choose one item from a set and not when simply appraising that set's overall value. Decision makers thus experience anxiety from competing avoidance motivations when forced to select among low-value options, comparable to the competing approach motivations they experience when choosing between high-value items. We further show that a common method of measuring subjective values (willingness to pay) can inadvertently censor a portion of this quadratic pattern, creating the misperception that anxiety simply increases linearly with set value. Collectively, these findings reveal the surprising costs of seemingly banal decisions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Accounting for Taste: A Multi-Attribute Neurocomputational Model Explains the Neural Dynamics of Choices for Self and Others

How do we make choices for others with different preferences from our own? Although neuroimaging studies implicate similar circuits in representing preferences for oneself and others, some models propose that additional corrective mechanisms come online when choices for others diverge from one's own preferences. Here we used event-related potentials (ERPs) in humans, in combination with computational modeling, to examine how social information is integrated in the time leading up to choices for oneself and others. Hungry male and female participants with unrestricted diets selected foods for themselves, a similar unrestricted eater, and a dissimilar, self-identified healthy eater. Across choices for both oneself and others, ERP value signals emerged within the same time window but differentially reflected taste and health attributes based on the recipient's preferences. Choices for the dissimilar recipient were associated with earlier activity localized to brain regions implicated in social cognition, including temporoparietal junction. Finally, response-locked analysis revealed a late ERP component specific to choices for the similar recipient, localized to the parietal lobe, that appeared to reflect differences in the response threshold based on uncertainty. A multi-attribute computational model supported the link between specific ERP components and distinct model parameters, and was not significantly improved by adding time-dependent dual processes. Model simulations suggested that longer response times previously associated with effortful correction may alternatively arise from higher choice uncertainty. Together, these results provide a parsimonious neurocomputational mechanism for social decision-making, additionally explaining divergent patterns of choice and response time data in decisions for oneself and others.SIGNIFICANCE STATEMENT How do we choose for others, particularly when they have different preferences? Whereas some studies suggest that similar neural circuits underlie decision-making for oneself and others, others argue for additional, slower perspective-taking mechanisms. Combining event-related potentials with computational modeling, we found that integration of others' preferences occurs over the same timescale as for oneself while differentially tracking recipient-relevant attributes. Although choosing for others took longer and produced differences in late-emerging neural responses, computational modeling attributed these patterns to greater response caution rather than egocentric bias correction. Computational simulations also correctly predicted when and why choosing differently for others takes longer, suggesting that a model incorporating value integration and evidence accumulation can parsimoniously account for complex patterns in social decision-making.

Ventral striatal response during decision making involving risk and reward is associated with future binge drinking in adolescents

Beginning to engage in heavy alcohol use during adolescence, as opposed to later in life, is associated with elevated risk for a variety of negative consequences, including the development of an alcohol use disorder. Behavioral studies suggest that poor decision making predicts alcohol use during adolescence; however, more research is needed to determine the neurobiological risk factors that underlie this association. Using functional magnetic resonance imaging, brain activation during decision making involving risk and reward was assessed in 47 adolescents (14-15 years old) with no significant history or alcohol or drug use. After baseline assessment, participants completed follow-up interviews every 3 months to assess the duration to onset of binge drinking. Adolescents who made a greater number of risky selections and had greater activation in the nucleus accumbens, precuneus, and occipital cortex during decision making involving greater potential for risk and reward began binge drinking sooner. Findings suggest that heightened activation of reward circuitry during decision making under risk is a neurobiological risk factor for earlier onset of binge drinking. Furthermore, brain activation was a significant predictor of onset to binge drinking, even after controlling for decision-making behavior, suggesting that neurobiological markers may provide additional predictive validity over behavioral assessments. Interventions designed to modify these behavioral and neurobiological risk factors may be useful for curbing heavy alcohol use during adolescence.

Goal Directed and Self-Control Systems in Bulimia Nervosa: An fMRI Study

Background

Binge eating is apparently the opposite of the strict control over food intake typically set by “maladaptive dieters”. Using functional magnetic resonance imaging (fMRI), we investigated the role of goal-directed behaviors, and the related use of self-control, in binge-related food choices in patients with Bulimia Nervosa (BN).

Method

While undergoing fMRI, women aged 18–35 with BN (N = 35) and healthy control women (N = 26) rated foods for healthiness and tastiness and then made food choices on a 5 points Likert scale between two conflicting options: one food with lower healthiness and higher tastiness (defined as uncontrolled choice) than the other food (defined as controlled choice).

Results

BN and healthy participants made more uncontrolled than controlled choices (63% vs 24% and 65% vs 18% respectively). While healthy participants used only food tastiness (chose tastier foods more often) to make food choices (p < .001), BN patients used both food healthiness (chose unhealthy food more often, p < .001) and food tastiness (p < .001) to make binge-related food choices. Activity in the ventromedial prefrontal cortex (vmPFC), which correlated with food choices (p_FWE = 0.02), reflected this difference in the integration of food healthiness and food tastiness into a decision value. Functional connectivity analysis showed that the activity in the dorsolateral prefrontal cortex was coupled with vmPFC activity in uncontrolled food choices (p_FWE = 0.03).

Interpretation

Contrary to what might be expected, not only food tastiness but also unhealthiness (a more abstract cognitive-based attribute than food tastiness) plays a role in uncontrolled choices in BN. These choices are likely goal-directed behaviors and recruit self-control.

The neural bases of price estimation: Effects of size and precision of the estimate

People are often confronted with the need of estimating the market price of goods. An important question is how people estimate prices, given the variability of products and prices available. Using event-related fMRI, we investigated how numerical processing modulates the neural bases of retail price estimation by focusing on two numerical dimensions: the size and precision of the estimates. Participants were presented with several product labels and made market price estimates for those products. Measures of product buying frequency and market price variability were also collected. The estimation of higher prices required longer response times, was associated with greater variation in responses across participants, and correlated with increasing medial and lateral prefrontal cortex (PFC) activity. Moreover, price estimates followed Weber's law, a hallmark feature of numerical processing. Increasing accuracy in price estimation, indexed by decreasing Weber fraction, engaged the intraparietal sulcus (IPS), a critical region in numerical processing. Our findings provide evidence for distinguishable neural mechanisms associated with the size and the precision of price estimates.

Neural Correlates of Drug-Biased Choice in Currently Using and Abstinent Individuals With Cocaine Use Disorder

BACKGROUND

The choice for drugs over alternative reinforcers is a translational hallmark feature of drug addiction. The neural basis of such drug-biased choice is not well understood, particularly in individuals with protracted drug abstinence who cannot ethically participate in studies that offer drug-using opportunities.

METHODS

We developed a functional magnetic resonance imaging drug-choice task to examine the choice for viewing drug-related images, rather than for actually consuming a drug. Actively using (n = 18) and abstaining (n = 19) individuals with a history of cocaine use disorder (CUD: dependence or abuse) and matched healthy control subjects (n = 26) participated.

RESULTS

Individuals with CUD, especially those actively using cocaine outside the laboratory, made more choices than control subjects to view images depicting cocaine (especially when directly compared against images depicting an alternative appetitive reinforcer [food]). Functional magnetic resonance imaging data revealed that in individuals with CUD, the act of making drug-related choices engaged brain regions implicated in choice difficulty or ambivalence (i.e., dorsal anterior cingulate cortex, which was higher in all individuals with CUD than control subjects). Drug-related choices in CUD also engaged brain regions implicated in reward (e.g., midbrain/ventral tegmental area, which was most activated in active users, although this region was not hypothesized a priori).

CONCLUSIONS

These results help clarify the neural mechanisms underlying drug-biased choice in human addiction, which, beyond mechanisms involved in value assignment or reward, may critically involve mechanisms that contribute to resolving difficult decisions. Future studies are needed to validate these behavioral and neural abnormalities as markers of drug seeking and relapse in treatment contexts.

Separate neural representations of prediction error valence and surprise: Evidence from an fMRI meta-analysis

Learning occurs when an outcome differs from expectations, generating a reward prediction error signal (RPE). The RPE signal has been hypothesized to simultaneously embody the valence of an outcome (better or worse than expected) and its surprise (how far from expectations). Nonetheless, growing evidence suggests that separate representations of the two RPE components exist in the human brain. Meta-analyses provide an opportunity to test this hypothesis and directly probe the extent to which the valence and surprise of the error signal are encoded in separate or overlapping networks. We carried out several meta-analyses on a large set of fMRI studies investigating the neural basis of RPE, locked at decision outcome. We identified two valence learning systems by pooling studies searching for differential neural activity in response to categorical positive-versus-negative outcomes. The first valence network (negative > positive) involved areas regulating alertness and switching behaviours such as the midcingulate cortex, the thalamus and the dorsolateral prefrontal cortex whereas the second valence network (positive > negative) encompassed regions of the human reward circuitry such as the ventral striatum and the ventromedial prefrontal cortex. We also found evidence of a largely distinct surprise-encoding network including the anterior cingulate cortex, anterior insula and dorsal striatum. Together with recent animal and electrophysiological evidence this meta-analysis points to a sequential and distributed encoding of different components of the RPE signal, with potentially distinct functional roles.

Embodied valuation: Directional action is associated with item values

We have a lifetime of experience interacting with objects we value. Although many economic theories represent valuation as a purely cognitive process independent of the sensorimotor system, embodied cognitive theory suggests that our memories for items' value should be linked to actions we use to obtain them. Here, we investigated whether the value of real items was associated with specific directional movements toward or away from the body. Participants priced a set of food items to determine their values; they then used directional actions to classify each item as high- or low-value. To determine if value is linked to specific action mappings, movements were referenced either with respect to the object (push toward high-value items; pull away from low-value items) or the self (pull high-value items toward self; push low-value items away). Participants who were assigned (Experiment 1) or chose (Experiment 2) to use an object-referenced action mapping were faster than those using a self-referenced mapping. A control experiment (Experiment 3) using left/right movements found no such difference when action mappings were not toward/away from the body. These results indicate that directional actions toward items are associated with the representation of their value, suggesting an embodied component to economic choice.

Walnut consumption increases activation of the insula to highly desirable food cues: A randomized, double-blind, placebo-controlled, cross-over fMRI study

AIMS

The use of walnuts is recommended for obesity and type 2 diabetes, although the mechanisms through which walnuts may improve appetite control and/or glycaemic control remain largely unknown.

MATERIALS AND METHODS

To determine whether short-term walnut consumption could alter the neural control of appetite using functional magnetic resonance imaging, we performed a randomized, placebo-controlled, double-blind, cross-over trial of 10 patients who received, while living in the controlled environment of a clinical research center, either walnuts or placebo (using a validated smoothie delivery system) for 5 days each, separated by a wash-out period of 1 month.

RESULTS

Walnut consumption decreased feelings of hunger and appetite, assessed using visual analog scales, and increased activation of the right insula to highly desirable food cues.

CONCLUSIONS

These findings suggest that walnut consumption may increase salience and cognitive control processing of highly desirable food cues, leading to the beneficial metabolic effects observed.

The influences and neural correlates of past and present during gambling in humans

During financial decision-making tasks, humans often make "rational" decisions, where they maximize expected reward. However, this rationality may compete with a bias that reflects past outcomes. That is, if one just lost money or won money, this may impact future decisions. It is unclear how past outcomes influence future decisions in humans, and how neural circuits encode present and past information. In this study, six human subjects performed a financial decision-making task while we recorded local field potentials from multiple brain structures. We constructed a model for each subject characterizing bets on each trial as a function of present and past information. The models suggest that some patients are more influenced by previous trial outcomes (i.e., previous return and risk) than others who stick to more fixed decision strategies. In addition, past return and present risk modulated with the activity in the cuneus; while present return and past risk modulated with the activity in the superior temporal gyrus and the angular gyrus, respectively. Our findings suggest that these structures play a role in decision-making beyond their classical functions by incorporating predictions and risks in humans' decision strategy, and provide new insight into how humans link their internal biases to decisions.

Distributed neural representation of saliency controlled value and category during anticipation of rewards and punishments

An extensive literature from cognitive neuroscience examines the neural representation of value, but interpretations of these existing results are often complicated by the potential confound of saliency. At the same time, recent attempts to dissociate neural signals of value and saliency have not addressed their relationship with category information. Using a multi-category valuation task that incorporates rewards and punishments of different nature, we identify distributed neural representation of value, saliency, and category during outcome anticipation. Moreover, we reveal category encoding in multi-voxel blood-oxygen-level-dependent activity patterns of the vmPFC and the striatum that coexist with value signals. These results help clarify ambiguities regarding value and saliency encoding in the human brain and their category independence, lending strong support to the neural "common currency" hypothesis. Our results also point to potential novel mechanisms of integrating multiple aspects of decision-related information.

Influence of ventral tegmental area input on cortico-subcortical networks underlying action control and decision making

It is argued that the mesolimbic system has a more general function in processing all salient events, including and extending beyond rewards. Saliency was defined as an event that is unexpected due to its frequency of occurrence and elicits an attentional-behavioral switch. Using functional magnetic resonance imaging (fMRI), signals were measured in response to the modulation of salience of rewarding and nonrewarding events during a reward-based decision making task, the so called desire-reason dilemma paradigm (DRD). Replicating previous findings, both frequent and infrequent, and therefore salient, reward stimuli elicited reliable activation of the ventral tegmental area (VTA) and ventral striatum (vStr). When immediate reward desiring contradicted the superordinate task-goal, we found an increased activation of the VTA and vStr when the salient reward stimuli were presented compared to the nonsalient reward stimuli, indicating a boosting of activation in these brain regions. Furthermore, we found a significantly increased functional connectivity between the VTA and vStr, confirming the boosting of vStr activation via VTA input. Moreover, saliency per se without a reward association led to an increased activation of brain regions in the mesolimbic reward system as well as the orbitofrontal cortex (OFC), inferior frontal gyrus (IFG), and anterior cingulate cortex (ACC). Finally, findings uncovered multiple increased functional interactions between cortical saliency-processing brain areas and the VTA and vStr underlying detection and processing of salient events and adaptive decision making.

Adaptive scaling of reward in episodic memory: a replication study

Reward is thought to enhance episodic memory formation via dopaminergic consolidation. Bunzeck, Dayan, Dolan, and Duzel [(2010). A common mechanism for adaptive scaling of reward and novelty. Human Brain Mapping, 31, 1380–1394] provided functional magnetic resonance imaging (fMRI) and behavioural evidence that reward and episodic memory systems are sensitive to the contextual value of a reward—whether it is relatively higher or lower—as opposed to absolute value or prediction error. We carried out a direct replication of their behavioural study and did not replicate their finding that memory performance associated with reward follows this pattern of adaptive scaling. An effect of reward outcome was in the opposite direction to that in the original study, with lower reward outcomes leading to better memory than higher outcomes. There was a marginal effect of reward context, suggesting that expected value affected memory performance. We discuss the robustness of the reward memory relationship to variations in reward context, and whether other reward-related factors have a more reliable influence on episodic memory.

Posterior Cingulate Neurons Dynamically Signal Decisions to Disengage during Foraging

Foraging for resources is a fundamental behavior balancing systematic search and strategic disengagement. The foraging behavior of primates is especially complex and requires long-term memory, value comparison, strategic planning, and decision-making. Here we provide evidence from two different foraging tasks that neurons in primate posterior cingulate cortex (PCC) signal decision salience during foraging to motivate disengagement from the current strategy. In our foraging tasks, salience refers to the difference between decision thresholds and the net harvested reward. Salience signals were stronger in poor foraging contexts than rich ones, suggesting low harvest rates recruit mechanisms in PCC that regulate strategic disengagement and exploration during foraging.

Motivated Cognition: Effects of Reward, Emotion, and Other Motivational Factors Across a Variety of Cognitive Domains

A growing body of literature has demonstrated that motivation influences cognitive processing. The breadth of these effects is extensive and span influences of reward, emotion, and other motivational processes across all cognitive domains. As examples, this scope includes studies of emotional memory, value-based attentional capture, emotion effects on semantic processing, reward-related biases in decision making, and the role of approach/avoidance motivation on cognitive scope. Additionally, other less common forms of motivation–cognition interactions, such as self-referential and motoric processing can also be considered instances of motivated cognition. Here I outline some of the evidence indicating the generality and pervasiveness of these motivation influences on cognition, and introduce the associated ‘research nexus’ at Collabra: Psychology.

Anatomical and functional organization of the human substantia nigra and its connections

We investigated the anatomical and functional organization of the human substantia nigra (SN) using diffusion and functional MRI data from the Human Connectome Project. We identified a tripartite connectivity-based parcellation of SN with a limbic, cognitive, motor arrangement. The medial SN connects with limbic striatal and cortical regions and encodes value (greater response to monetary wins than losses during fMRI), while the ventral SN connects with associative regions of cortex and striatum and encodes salience (equal response to wins and losses). The lateral SN connects with somatomotor regions of striatum and cortex and also encodes salience. Behavioral measures from delay discounting and flanker tasks supported a role for the value-coding medial SN network in decisional impulsivity, while the salience-coding ventral SN network was associated with motor impulsivity. In sum, there is anatomical and functional heterogeneity of human SN, which underpins value versus salience coding, and impulsive choice versus impulsive action.

Temporal Dynamics of Sensorimotor Networks in Effort-Based Cost-Benefit Valuation: Early Emergence and Late Net Value Integration

Although physical effort can impose significant costs on decision-making, when and how effort cost information is incorporated into choice remains contested, reflecting a larger debate over the role of sensorimotor networks in specifying behavior. Serial information processing models, in which motor circuits simply implement the output of cognitive systems, hypothesize that effort cost factors into decisions relatively late, via integration with stimulus values into net (combined) value signals in dorsomedial frontal cortex (dmFC). In contrast, ethology-inspired approaches suggest a more active role for the dorsal sensorimotor stream, with effort cost signals emerging rapidly after stimulus onset. Here we investigated the time course of effort cost integration using event-related potentials in hungry human subjects while they made decisions about expending physical effort for appetitive foods. Consistent with the ethological perspective, we found that effort cost was represented from as early as 100-250 ms after stimulus onset, localized to dorsal sensorimotor regions including middle cingulate, somatosensory, and motor/premotor cortices. However, examining the same data time-locked to motor output revealed net value signals combining stimulus value and effort cost approximately -400 ms before response, originating from sensorimotor areas including dmFC, precuneus, and posterior parietal cortex. Granger causal connectivity analysis of the motor effector signal in the time leading to response showed interactions between these sensorimotor regions and ventrolateral prefrontal cortex, a structure associated with adjusting behavior-response mappings. These results suggest that rapid activation of sensorimotor regions interacts with cognitive valuation systems, producing a net value signal reflecting both physical effort and reward contingencies.

SIGNIFICANCE STATEMENT

Although physical effort imposes a cost on choice, when and how effort cost influences neural correlates of decision-making remains contested. This dispute reflects a larger disagreement between cognitive neuroscience and ethology over the role of sensorimotor systems in behavior: are sensorimotor circuits merely implementing the late-stage output of cognitive systems, or engaged rapidly and interactively from early in decision-making? We find that, although early representation of effort cost is associated with sensorimotor regions, these signals are also integrated with cognitive stimulus value representations in the time leading up to motor response. These data suggest that sensorimotor networks interact dynamically with cognitive systems to guide decision-making, providing a first step toward reconciling differing perspectives on sensorimotor roles in valuation and choice.

Dynamic Hippocampal and Prefrontal Contributions to Memory Processes and Representations Blur the Boundaries of Traditional Cognitive Domains

The hippocampus has long been known to be a critical component of the memory system involved in the formation and use of long-term declarative memory. However, recent findings have revealed that the reach of hippocampal contributions extends to a variety of domains and tasks that require the flexible use of cognitive and social behavior, including domains traditionally linked to prefrontal cortex (PFC), such as decision-making. In addition, the prefrontal cortex (PFC) has gained traction as a necessary part of the memory system. These findings challenge the conventional characterizations of hippocampus and PFC as being circumscribed to traditional cognitive domains. Here, we emphasize that the ability to parsimoniously account for the breadth of hippocampal and PFC contributions to behavior, in terms of memory function and beyond, requires theoretical advances in our understanding of their characteristic processing features and mental representations. Notably, several literatures exist that touch upon this issue, but have remained disjointed because of methodological differences that necessarily limit the scope of inquiry, as well as the somewhat artificial boundaries that have been historically imposed between domains of cognition. In particular, this article focuses on the contribution of relational memory theory as an example of a framework that describes both the representations and processes supported by the hippocampus, and further elucidates the role of the hippocampal–PFC network to a variety of behaviors.

Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans

Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo-mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning.

Valence and magnitude ambiguity in feedback processing

BACKGROUND

Outcome feedback which indicates behavioral consequences are crucial for reinforcement learning and environmental adaptation. Nevertheless, outcome information in daily life is often totally or partially ambiguous. Studying how people interpret this kind of information would provide important knowledge about the human evaluative system.

METHODS

This study concentrates on the neural processing of partially ambiguous feedback, that is, either its valence or magnitude is unknown to participants. To address this topic, we sequentially presented valence and magnitude information; electroencephalography (EEG) response to each kind of presentation was recorded and analyzed. The event-related potential components feedback-related negativity (FRN) and P3 were used as indices of neural activity.

RESULTS

Consistent with previous literature, the FRN elicited by ambiguous valence was not significantly different from that elicited by negative valence. On the other hand, the FRN elicited by ambiguous magnitude was larger than both the large and small magnitude, indicating the motivation to seek unambiguous magnitude information. The P3 elicited by ambiguous valence and ambiguous magnitude was not significantly different from that elicited by negative valence and small magnitude, respectively, indicating the emotional significance of feedback ambiguity. Finally, the aforementioned effects also manifested in the stage of information integration.

CONCLUSION

These findings indicate both similarities and discrepancies between the processing of valence ambiguity and that of magnitude ambiguity, which may help understand the mechanisms of ambiguous information processing.

A distributed, hierarchical and recurrent framework for reward-based choice

Many accounts of reward-based choice argue for distinct component processes that are serial and functionally localized. In this Opinion article, we argue for an alternative viewpoint, in which choices emerge from repeated computations that are distributed across many brain regions. We emphasize how several features of neuroanatomy may support the implementation of choice, including mutual inhibition in recurrent neural networks and the hierarchical organization of timescales for information processing across the cortex. This account also suggests that certain correlates of value are emergent rather than represented explicitly in the brain.

Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

Neural Mechanisms of the Transformation from Objective Value to Subjective Utility: Converting from Count to Worth

When deciding, we aim to choose the “best” possible outcome. This is not just selection of the option that is the most numerous or physically largest, as options are translated from objective value (count) to subjective value (worth or utility). We localized the neural instantiation of the value-to-utility transformation to the dorsal anterior midcingulate cortex (daMCC), with independent replication. The daMCC encodes the context-specific information necessary to convert from count to worth. This encoding is not simply a representation of utility or preference, but the interaction of the two. Specifically, the relationship of brain activation to value is dependent on individual preference, with both positive and negative slopes across the population depending on whether each individual's preference results in enhancement or diminishment of the valuation. For a given value, across participants, enhanced daMCC activation corresponds to diminished subjective valuation, deactivation to enhanced subjective valuation, and non-modulated activation with non-modulated subjective valuation. Further, functional connectivity analyses identified brain regions (positive connectivity with the inferior frontal gyrus and negative connectivity with the nucleus accumbens) through which contextual information may be integrated into the daMCC and allow for outputs to modulate valuation signals. All analyses were replicated through an independent within-study replication, with initial testing in the gains domain and replication in the intermixed and mirrored losses trials. We also present and discuss an ancillary finding: we were unable to identify parametric value signals for losses through whole-brain analyses, and ROI analyses of the vmPFC presented non-modulation across loss value levels. These results identify the neural locus of the value-to-utility transformation, and provide a specific computational function for the daMCC in the production of subjective valuation through the integration of value, context, and preferences.

Motivational Context Modulates Prediction Error Response in Schizophrenia

BACKGROUND

Recent findings demonstrate that patients with schizophrenia are worse at learning to predict rewards than losses, suggesting that motivational context modulates learning in this disease. However, these findings derive from studies in patients treated with antipsychotic medications, D2 receptor antagonists that may interfere with the neural systems that underlie motivation and learning. Thus, it remains unknown how motivational context affects learning in schizophrenia, separate from the effects of medication.

METHODS

To examine the impact of motivational context on learning in schizophrenia, we tested 16 unmedicated patients with schizophrenia and 23 matched controls on a probabilistic learning task while they underwent functional magnetic resonance imaging (fMRI) under 2 conditions: one in which they pursued rewards, and one in which they avoided losses. Computational models were used to derive trial-by-trial prediction error responses to feedback.

RESULTS

Patients performed worse than controls on the learning task overall, but there were no behavioral effects of condition. FMRI revealed an attenuated prediction error response in patients in the medial prefrontal cortex, striatum, and medial temporal lobe when learning to predict rewards, but not when learning to avoid losses.

CONCLUSIONS

Patients with schizophrenia showed differences in learning-related brain activity when learning to predict rewards, but not when learning to avoid losses. Together with prior work, these results suggest that motivational deficits related to learning in schizophrenia are characteristic of the disease and not solely a result of antipsychotic treatment.

Food Decision-Making: Effects of Weight Status and Age

Food decisions determine energy intake. Since overconsumption is the main driver of obesity, the effects of weight status on food decision-making are of increasing interest. An additional factor of interest is age, given the rise in childhood obesity, weight gain with aging, and the increased chance of type 2 diabetes in the elderly. The effects of weight status and age on food preference, food cue sensitivity, and self-control are discussed, as these are important components of food decision-making. Furthermore, the neural correlates of food anticipation and choice and how these are affected by weight status and age are discussed. Behavioral studies show that in particular, poor self-control may have an adverse effect on food choice in children and adults with overweight and obesity. Neuroimaging studies show that overweight and obese individuals have altered neural responses to food in brain areas related to reward, self-control, and interoception. Longitudinal studies across the lifespan will be invaluable to unravel the causal factors driving (changes in) food choice, overconsumption, and weight gain.

Theta oscillations integrate functionally segregated sub-regions of the medial prefrontal cortex

Reinforcement learning requires the dynamic interplay of several specialized networks distributed across the brain. A potential mechanism to establish accurate temporal coordination among these paths is through the synchronization of neuronal activity to a common rhythm of neuronal firing. Previous EEG studies have suggested that theta oscillatory activity might be crucial in the integration of information from motivational and attentional paths that converge into the medial Prefrontal Cortex (mPFC) during reward-guided learning. However, due to the low spatial resolution of EEG, this hypothesis has not been directly tested. Here, by combining EEG and fMRI, we show that theta oscillations serve as common substrate for the engagement of separated sub-regions within the mPFC (the pre-Supplementary Motor Area and the dorsomedial Prefrontal Cortex), underlying different cognitive operations (encoding of outcome valence and unsigned prediction errors) through separate functional paths (the Salience and the Central Executive Networks).

Health and Pleasure in Consumers' Dietary Food Choices: Individual Differences in the Brain's Value System

Taking into account how people value the healthiness and tastiness of food at both the behavioral and brain levels may help to better understand and address overweight and obesity-related issues. Here, we investigate whether brain activity in those areas involved in self-control may increase significantly when individuals with a high body-mass index (BMI) focus their attention on the taste rather than on the health benefits related to healthy food choices. Under such conditions, BMI is positively correlated with both the neural responses to healthy food choices in those brain areas associated with gustation (insula), reward value (orbitofrontal cortex), and self-control (inferior frontal gyrus), and with the percent of healthy food choices. By contrast, when attention is directed towards health benefits, BMI is negatively correlated with neural activity in gustatory and reward-related brain areas (insula, inferior frontal operculum). Taken together, these findings suggest that those individuals with a high BMI do not necessarily have reduced capacities for self-control but that they may be facilitated by external cues that direct their attention toward the tastiness of healthy food. Thus, promoting the taste of healthy food in communication campaigns and/or food packaging may lead to more successful self-control and healthy food behaviors for consumers with a higher BMI, an issue which needs to be further researched.

Multivariate Neural Representations of Value during Reward Anticipation and Consummation in the Human Orbitofrontal Cortex

The role of the orbitofrontal cortex (OFC) in value processing is a focus of research. Conventional imaging analysis, where smoothing and averaging are employed, may not be sufficiently sensitive in studying the OFC, which has heterogeneous anatomical structures and functions. In this study, we employed representational similarity analysis (RSA) to reveal the multi-voxel fMRI patterns in the OFC associated with value processing during the anticipatory and the consummatory phases. We found that multi-voxel activation patterns in the OFC encoded magnitude and partial valence information (win vs. loss) but not outcome (favourable vs. unfavourable) during reward consummation. Furthermore, the lateral OFC rather than the medial OFC encoded loss information. Also, we found that OFC encoded values in a similar way to the ventral striatum (VS) or the anterior insula (AI) during reward anticipation regardless of motivated response and to the medial prefrontal cortex (MPFC) and the VS in reward consummation. In contrast, univariate analysis did not show changes of activation in the OFC. These findings suggest an important role of the OFC in value processing during reward anticipation and consummation.

Role of expected reward in frontal eye field during natural scene search

When a saccade is expected to result in a reward, both neural activity in oculomotor areas and the saccade itself (e.g., its vigor and latency) are altered (compared with when no reward is expected). As such, it is unclear whether the correlations of neural activity with reward indicate a representation of reward beyond a movement representation; the modulated neural activity may simply represent the differences in motor output due to expected reward. Here, to distinguish between these possibilities, we trained monkeys to perform a natural scene search task while we recorded from the frontal eye field (FEF). Indeed, when reward was expected (i.e., saccades to the target), FEF neurons showed enhanced responses. Moreover, when monkeys accidentally made eye movements to the target, firing rates were lower than when they purposively moved to the target. Thus, neurons were modulated by expected reward rather than simply the presence of the target. We then fit a model that simultaneously included components related to expected reward and saccade parameters. While expected reward led to shorter latency and higher velocity saccades, these behavioral changes could not fully explain the increased FEF firing rates. Thus, FEF neurons appear to encode motivational factors such as reward expectation, above and beyond the kinematic and behavioral consequences of imminent reward.

Loss aversion is associated with bilateral insula volume. A voxel based morphometry study

Loss aversion is a decision bias, reflecting a greater sensitivity to losses than to gains in a decision situation. Recent neuroscientific research has shown that mesocorticolimbic structures like ventromedial prefrontal cortex and the ventral striatum constitute a bidirectional neural system that processes gains and losses and exhibits a neural basis of loss aversion. On a functional and structural level, the amygdala and insula also seem to play an important role in the processing of loss averse behavior. By applying voxel-based morphometry to structural brain images in N=41 healthy participants, the current study provides further evidence for the relationship of brain structure and loss aversion. The results show a negative correlation of gray matter volume in bilateral posterior insula as well as left medial frontal gyrus with individual loss aversion. Hence, higher loss aversion is associated with lower gray matter volume in these brain areas. Both structures have been discussed to play important roles in the brain's salience network, where the posterior insula is involved in interoception and the detection of salience. The medial frontal gyrus might impact decision making through its dense connections with the anterior cingulate cortex. A possible explanation for the present finding is that structural differences in these regions alter the processing of losses and salience, possibly biasing decision making towards avoidance of negative outcomes.

Human mesostriatal response tracks motivational tendencies under naturalistic goal conflict

Goal conflict situations, involving the simultaneous presence of reward and punishment, occur commonly in real life, and reflect well-known individual differences in the behavioral tendency to approach or avoid. However, despite accumulating neural depiction of motivational processing, the investigation of naturalistic approach behavior and its interplay with individual tendencies is remarkably lacking. We developed a novel ecological interactive scenario which triggers motivational behavior under high or low goal conflict conditions. Fifty-five healthy subjects played the game during a functional magnetic resonance imaging scan. A machine-learning approach was applied to classify approach/avoidance behaviors during the game. To achieve an independent measure of individual tendencies, an integrative profile was composed from three established theoretical models. Results demonstrated that approach under high relative to low conflict involved increased activity in the ventral tegmental area (VTA), peri-aquaductal gray, ventral striatum (VS) and precuneus. Notably, only VS and VTA activations during high conflict discriminated between approach/avoidance personality profiles, suggesting that the relationship between individual personality and naturalistic motivational tendencies is uniquely associated with the mesostriatal pathway. VTA-VS further demonstrated stronger coupling during high vs low conflict. These findings are the first to unravel the multilevel relationship among personality profile, approach tendencies in naturalistic set-up and their underlying neural manifestation, thus enabling new avenues for investigating approach-related psychopathologies.

Gambling on visual performance: neural correlates of metacognitive choice between visual lotteries

A lottery is a list of mutually exclusive outcomes together with their associated probabilities of occurrence. Decision making is often modeled as choices between lotteries and-in typical research on decision under risk-the probabilities are given to the subject explicitly in numerical form. In this study, we examined lottery decision task where the probabilities of receiving various rewards are contingent on the subjects' own visual performance in a random-dot-motion (RDM) discrimination task, a metacognitive or second order judgment. While there is a large literature concerning the RDM task and there is also a large literature on decision under risk, little is known about metacognitive decisions when the source of uncertainty is visual. Using fMRI with humans, we found distinct fronto-striatal and fronto-parietal networks representing subjects' estimates of his or her performance, reward value, and the expected value (EV) of the lotteries. The fronto-striatal network includes the dorsomedial prefrontal cortex and the ventral striatum, involved in reward processing and value-based decision-making. The fronto-parietal network includes the intraparietal sulcus and the ventrolateral prefrontal cortex, which was shown to be involved in the accumulation of sensory evidence during visual decision making and in metacognitive judgments on visual performance. These results demonstrate that-while valuation of performance-based lotteries involves a common fronto-striatal valuation network-an additional network unique to the estimation of task-related performance is recruited for the integration of probability and reward information when probability is inferred from visual performance.

Automatic integration of confidence in the brain valuation signal

A key process in decision-making is estimating the value of possible outcomes. Growing evidence suggests that different types of values are automatically encoded in the ventromedial prefrontal cortex (VMPFC). Here we extend this idea by suggesting that any overt judgment is accompanied by a second-order valuation (a confidence estimate), which is also automatically incorporated in VMPFC activity. In accordance with the predictions of our normative model of rating tasks, two behavioral experiments showed that confidence levels were quadratically related to first-order judgments (age, value or probability ratings). The analysis of three functional magnetic resonance imaging data sets using similar rating tasks confirmed that the quadratic extension of first-order ratings (our proxy for confidence) was encoded in VMPFC activity, even if no confidence judgment was required of the participants. Such an automatic aggregation of value and confidence in a same brain region might provide insight into many distortions of judgment and choice.

Attentional Modulation of Brain Responses to Primary Appetitive and Aversive Stimuli

Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.

Independent component analysis of functional networks for response inhibition: Inter-subject variation in stop signal reaction time

Cognitive control is a critical executive function. Many studies have combined general linear modeling and the stop signal task (SST) to delineate the component processes of cognitive control. For instance, by contrasting stop success (SS) and stop error (SE) trials in the SST, investigators examined regional responses to stop signal inhibition. In contrast to this parameterized approach, independent component analysis (ICA) elucidates brain networks subserving cognitive control. In our earlier work of 59 adults performing the SST during fMRI, we characterized six independent components (ICs). However, none of these ICs correlated with stop signal performance, raising questions about their behavioral validity. Here, in a larger sample (n = 100), we identified and explored 23 ICs for correlation with the stop signal reaction time (SSRT), a measure of the efficiency of response inhibition. At a corrected threshold (P < 0.0005), a paracentral lobule-midcingulate network and a left inferior parietal-supplementary motor-somatomotor network showed a positive correlation between SE beta weight and SSRT. In contrast, a midline cerebellum-thalamus-pallidum network showed a negative correlation between SE beta weight and SSRT. These findings suggest that motor preparation and execution prolongs the SSRT, likely via an interaction between the go and stop processes as suggested by the race model. Behaviorally, consistent with this hypothesis, the difference in G and SE reaction times is positively correlated with SSRT across subjects. These new results highlight the importance of cognitive motor regions in response inhibition and support the utility of ICA in uncovering functional networks for cognitive control in the SST.

Decision-making impairments in Parkinson's disease as a by-product of defective cost-benefit analysis and feedback processing

Studies examining decision-making in people with Parkinson's disease (PD) show impaired performance on a variety of tasks. However, there are also demonstrations that patients with PD can make optimal decisions just like healthy age-matched controls. We propose that the reason for these mixed findings is that PD does not produce a generalized impairment of decision-making, but rather affects sub-components of this process. In this review we evaluate this hypothesis by considering the empirical evidence examining decision-making in PD. We suggest that of the various stages of the decision-making process, the most affected in PD are (1) the cost-benefit analysis stage and (2) the outcome evaluation stage. We consider the implications of this proposal for research in this area.

Anticipatory anxiety disrupts neural valuation during risky choice

Incidental negative emotions unrelated to the current task, such as background anxiety, can strongly influence decisions. This is most evident in psychiatric disorders associated with generalized emotional disturbances. However, the neural mechanisms by which incidental emotions may affect choices remain poorly understood. Here we study the effects of incidental anxiety on human risky decision making, focusing on both behavioral preferences and their underlying neural processes. Although observable choices remained stable across affective contexts with high and low incidental anxiety, we found a clear change in neural valuation signals: during high incidental anxiety, activity in ventromedial prefrontal cortex and ventral striatum showed a marked reduction in (1) neural coding of the expected subjective value (ESV) of risky options, (2) prediction of observed choices, (3) functional coupling with other areas of the valuation system, and (4) baseline activity. At the same time, activity in the anterior insula showed an increase in coding the negative ESV of risky lotteries, and this neural activity predicted whether the risky lotteries would be rejected. This pattern of results suggests that incidental anxiety can shift the focus of neural valuation from possible positive consequences to anticipated negative consequences of choice options. Moreover, our findings show that these changes in neural value coding can occur in the absence of changes in overt behavior. This suggest a possible pathway by which background anxiety may lead to the development of chronic reward desensitization and a maladaptive focus on negative cognitions, as prevalent in affective and anxiety disorders.

Goal- and retrieval-dependent activity in the striatum during memory recognition

The striatum has been associated with successful memory retrieval but the precise functional link still remains unclear. One hypothesis is that striatal activity reflects an active evaluation process of the retrieval outcome dependent on the current behavioral goals rather than being a consequence of memory reactivation. We have recently shown that the striatum also correlates with confidence in memory recognition, which could reflect high subjective value ascribed to high certainty decisions. To examine whether striatal activity during memory recognition reflects subjective value indeed, we conducted an fMRI study using a recognition memory paradigm in which the participants rated not only the recognition confidence but also indicated the pleasantness associated with the previous memory retrieval. The results demonstrated a high positive correlation between confidence and pleasantness both on the behavioral and brain activation level particularly in the striatum. As almost all of variance in the striatal confidence signal could be explained by experienced pleasantness, this part of the striatal memory recognition response probably corresponds to greater subjective value of high confidence responses. While perceived oldness was also strongly correlated with striatal activity, this activation pattern was clearly distinct from that associated with confidence and pleasantness and thus could not be explained by higher subjective value to detect "old" items. Together, these results show that at least two independent processes contribute to striatal activation in recognition memory: a more flexible evaluation response dependent on context and goals captured by memory confidence and a potentially retrieval-related response captured by perceived oldness.

Neural mechanisms for integrating prior knowledge and likelihood in value-based probabilistic inference

In Bayesian decision theory, knowledge about the probabilities of possible outcomes is captured by a prior distribution and a likelihood function. The prior reflects past knowledge and the likelihood summarizes current sensory information. The two combined (integrated) form a posterior distribution that allows estimation of the probability of different possible outcomes. In this study, we investigated the neural mechanisms underlying Bayesian integration using a novel lottery decision task in which both prior knowledge and likelihood information about reward probability were systematically manipulated on a trial-by-trial basis. Consistent with Bayesian integration, as sample size increased, subjects tended to weigh likelihood information more compared with prior information. Using fMRI in humans, we found that the medial prefrontal cortex (mPFC) correlated with the mean of the posterior distribution, a statistic that reflects the integration of prior knowledge and likelihood of reward probability. Subsequent analysis revealed that both prior and likelihood information were represented in mPFC and that the neural representations of prior and likelihood in mPFC reflected changes in the behaviorally estimated weights assigned to these different sources of information in response to changes in the environment. Together, these results establish the role of mPFC in prior-likelihood integration and highlight its involvement in representing and integrating these distinct sources of information.

Impaired self-awareness in human addiction: deficient attribution of personal relevance

Compromised self-awareness of illness-related deficits and behaviors in psychopathology (e.g., schizophrenia) has been associated with deficient functioning of cortical midline regions including the ventromedial prefrontal cortex (vmPFC), implicated in personal relevance. Here, we review and critically analyze recent evidence to suggest that vmPFC abnormalities could similarly underlie deficient tagging of personal relevance in drug addiction, evidenced by a constellation of behaviors encompassing drug-biased attention, negative outcome insensitivity, self-report/behavior dissociation, and social inappropriateness. This novel framework might clarify, for example, why drug-addicted individuals often ruin long-standing relationships or forego important job opportunities while continuing to engage in uncontrolled drug-taking. Therapeutic interventions targeting personal relevance and associated vmPFC functioning could enhance self-awareness and facilitate more adaptive behavior in this chronically relapsing psychopathology.

Ventromedial prefrontal cortex supports affective future simulation by integrating distributed knowledge

Although the future often seems intangible, we can make it more concrete by imagining prospective events. Here, using functional MRI, we demonstrate a mechanism by which the ventromedial prefrontal cortex supports such episodic simulations, and thereby contributes to affective foresight: This region supports processes that (i) integrate knowledge related to the elements that constitute an episode and (ii) represent the episode's emergent affective quality. The ventromedial prefrontal cortex achieves such integration via interactions with distributed cortical regions that process the individual elements. Its activation then signals the affective quality of the ensuing episode, which goes beyond the combined affective quality of its constituting elements. The integrative process further augments long-term retention of the episode, making it available at later time points. This mechanism thus renders the future tangible, providing a basis for farsighted behavior.

Directional influence between the human amygdala and orbitofrontal cortex at the time of decision-making

There is a growing consensus that the brain makes simple choices, such as choosing between an apple and an orange, by assigning value to the options under consideration, and comparing those values to make a choice. There is also a consensus that value signals computed in orbitofrontal cortex (OFC) and amygdala play a critical role in the choice process. However, the nature of the flow of information between OFC and amygdala at the time of decision is still unknown. In order to study this question, simultaneous local field potentials were recorded from OFC and amygdala in human patients while they performed a simple food choice task. Although the interaction of these circuits has been studied in animals, this study examines the effective connectivity directly in the human brain on a moment-by-moment basis. A spectral conditional Granger causality analysis was performed in order to test if the modulation of activity goes mainly from OFC-to-amygdala, from amygdala-to-OFC, or if it is bi-directional. Influence from amygdala-to-OFC was dominant prior to the revealed choice, with a small but significant OFC influence on the amygdala earlier in the trial. Alpha oscillation amplitudes analyzed with the Hilbert-Huang transform revealed differences in choice valence coincident with temporally specific amygdala influence on the OFC.