A Critical Role for Human Ventromedial Frontal Lobe in Value Comparison of Complex Objects Based on Attribute Configuration

Disentangling the Component Processes in Complex Planning Impairments Following Ventromedial Prefrontal Lesions

Damage to the ventromedial prefrontal cortex (vmPFC) in humans disrupts planning abilities in naturalistic settings. However, it is unknown which components of planning are affected in these patients, including selecting the relevant information, simulating future states, or evaluating between these states. To address this question, we leveraged computational paradigms to investigate the role of vmPFC in planning, using the board game task "Four-in-a-Row" (18 lesion patients, 9 female; 30 healthy control participants, 16 female) and the simpler "Two-Step" task measuring model-based reasoning (49 lesion patients, 27 female; 20 healthy control participants, 13 female). Damage to vmPFC disrupted performance in Four-in-a-Row compared with both control lesion patients and healthy age-matched controls. We leveraged a computational framework to assess different component processes of planning in Four-in-a-Row and found that impairments following vmPFC damage included shallower planning depth and a tendency to overlook game-relevant features. In the "Two-Step" task, which involves binary choices across a short future horizon, we found little evidence of planning in all groups and no behavioral differences between groups. Complex yet computationally tractable tasks such as "Four-in-a-Row" offer novel opportunities for characterizing neuropsychological planning impairments, which in vmPFC patients we find are associated with oversights and reduced planning depth.

Schemas, reinforcement learning and the medial prefrontal cortex

Schemas are rich and complex knowledge structures about the typical unfolding of events in a context; for example, a schema of a dinner at a restaurant. In this Perspective, we suggest that reinforcement learning (RL), a computational theory of learning the structure of the world and relevant goal-oriented behaviour, underlies schema learning. We synthesize literature about schemas and RL to offer that three RL principles might govern the learning of schemas: learning via prediction errors, constructing hierarchical knowledge using hierarchical RL, and dimensionality reduction through learning a simplified and abstract representation of the world. We then suggest that the orbitomedial prefrontal cortex is involved in both schemas and RL due to its involvement in dimensionality reduction and in guiding memory reactivation through interactions with posterior brain regions. Last, we hypothesize that the amount of dimensionality reduction might underlie gradients of involvement along the ventral-dorsal and posterior-anterior axes of the orbitomedial prefrontal cortex. More specific and detailed representations might engage the ventral and posterior parts, whereas abstraction might shift representations towards the dorsal and anterior parts of the medial prefrontal cortex.

Contributions of Attention to Learning in Multidimensional Reward Environments

Real-world choice options have many features or attributes, whereas the reward outcome from those options only depends on a few features or attributes. It has been shown that humans learn and combine feature-based with more complex conjunction-based learning to tackle challenges of learning in naturalistic reward environments. However, it remains unclear how different learning strategies interact to determine what features or conjunctions should be attended to and control choice behavior, and how subsequent attentional modulations influence future learning and choice. To address these questions, we examined the behavior of male and female human participants during a three-dimensional learning task in which reward outcomes for different stimuli could be predicted based on a combination of an informative feature and conjunction. Using multiple approaches, we found that both choice behavior and reward probabilities estimated by participants were most accurately described by attention-modulated models that learned the predictive values of both the informative feature and the informative conjunction. Specifically, in the reinforcement learning model that best fit choice data, attention was controlled by the difference in the integrated feature and conjunction values. The resulting attention weights modulated learning by increasing the learning rate on attended features and conjunctions. Critically, modulating decision-making by attention weights did not improve the fit of data, providing little evidence for direct attentional effects on choice. These results suggest that in multidimensional environments, humans direct their attention not only to selectively process reward-predictive attributes but also to find parsimonious representations of the reward contingencies for more efficient learning.

Relationship of prefrontal cortex activity with anhedonia and cognitive function in major depressive disorder: an fNIRS study

Background

Major depressive disorder (MDD) is associated with deficits in cognitive function, thought to be related to underlying decreased hedonic experiences. Further research is needed to fully elucidate the role of functional brain activity in this relationship. In this study, we investigated the neurofunctional correlate of the interplay between cognitive function and hedonic experiences in medication-free MDD using functional near-infrared spectroscopy (fNIRS).

Methods

We examine differences of brain activation corresponding to the verbal fluency test (VFT) between MDD patients and healthy controls (HCs). Fifty-six MDD patients and 35 HCs underwent fMRI scanning while performing the VFT. In exploratory analyses, cognitive performance, as assessed by the Cambridge Neuropsychological Test Automated Battery (CANTAB), four dimensions of hedonic processing (desire, motivation, effort, and consummatory pleasure) measured by the Dimensional Anhedonia Rating Scale (DARS), and relative changes in oxygenated hemoglobin concentration during the VFT were compared across groups.

Results

Patients with MDD demonstrated impairments in sustained attention and working memory, accompanied by lower total and subscale scores on the DARS. Compared to healthy controls, MDD patients exhibited reduced activation in the prefrontal cortex (PFC) during the VFT task (t = 2.32 to 4.77, p < 0.001 to 0.02, FDR corrected). DARS motivation, desire, and total scores as well as sustained attention, were positively correlated with activation in the dorsolateral PFC and Broca's area (p < 0.05, FDR corrected).

Conclusions

These findings indicate that changes in prefrontal lobe oxygenated hemoglobin levels, a region implicated in hedonic motivation and cognitive function, may serve as potential biomarkers for interventions targeting individuals with MDD. Our results corroborate the clinical consensus that the prefrontal cortex is a primary target for non-invasive neuromodulatory treatments for depression.

Grid-like entorhinal representation of an abstract value space during prospective decision making

How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming a trajectory through an abstract two-dimensional value space. During this task, the entorhinal cortex exhibited a grid-like representation with an orientation aligned to the axis through the value space most informative for choices. A network of brain regions, including ventromedial prefrontal cortex, tracked the prospective value difference between options. These findings suggest that the entorhinal grid system supports the prediction of future values by representing a cognitive map, which might be used to generate lower-dimensional value signals to guide prospective decision making.

Goal-Dependent Hippocampal Representations Facilitate Self-Control

Hippocampal activity linking past experiences and simulations of the future with current goals can play an important role in decision-making. The representation of information within the hippocampus may be especially critical in situations where one needs to overcome past rewarding experiences and exert self-control. Self-control success or failure may depend on how information is represented in the hippocampus and how effectively the representation process can be modified to achieve a specific goal. We test this hypothesis using representational similarity analyses of human (female/male) neuroimaging data during a dietary self-control task in which individuals must overcome taste temptations to choose healthy foods. We find that self-control is indeed associated with the way individuals represent taste information (valance) in the hippocampus and how taste representations there adapt to align with different goals/contexts. Importantly, individuals who were able to shift their hippocampal representations to a larger degree to align with the current motivation were better able to exert self-control when facing a dietary challenge. These results suggest an alternative or complementary neurobiological pathway leading to self-control success and indicate the need to update the classical view of self-control to continue to advance our understanding of its behavioral and neural underpinnings.SIGNIFICANCE STATEMENT The paper provides a new perspective on what leads to successful self-control at the behavioral and neurobiological levels. Our data suggest that self-control is enhanced when individuals adjust hippocampal processing to align with current goals.

Economic and social values in the brain: evidence from lesions to the human ventromedial prefrontal cortex

Making good economic and social decisions is essential for individual and social welfare. Decades of research have provided compelling evidence that damage to the ventromedial prefrontal cortex (vmPFC) is associated with dramatic personality changes and impairments in economic and social decision-making. However, whether the vmPFC subserves a unified mechanism in the social and non-social domains remains unclear. When choosing between economic options, the vmPFC is thought to guide decision by encoding value signals that reflect the motivational relevance of the options on a common scale. A recent framework, the "extended common neural currency" hypothesis, suggests that the vmPFC may also assign values to social factors and principles, thereby guiding social decision-making. Although neural value signals have been observed in the vmPFC in both social and non-social studies, it is yet to be determined whether they have a causal influence on behavior or merely correlate with decision-making. In this review, we assess whether lesion studies of patients with vmPFC damage offer evidence for such a causal role of the vmPFC in shaping economic and social behavior.

Why it is good to communicate the bad: understanding the influence of message framing in persuasive communication on consumer decision-making processes

Introduction

One approach to bridging the gap between consumer intentions and behavior is persuasive communication to reinforce their intentions and thereby support their behavior change. Message framing has proven to be a useful, persuasive communication tool. However, message framing is considered more complicated than other types of framing because, in addition to concept-specific elements, it is also strongly influenced by and, in turn, influences emotions. Therefore, it is almost impossible for consumers to verbally express their attitudes, so the challenge is to explain and measure its impact. This research aims to help in this regard by suggesting a theoretical model to understand how message framing is processed from a consumer neuroscience perspective. More precisely, the factors that constitute message framing are systematized and built on a reflective-impulsive model and a neural emotion-cognition framework interpreted to explain the persuasive effects of message framing.

Method

A functional magnetic resonance imaging (fMRI) experiment is used to examine the effects of message framing for four different frame types that are hypothesized to affect consumer information processing differently.

Result

The results suggest that communication strategies should take into account the valence of the objects and the frame used. The behavioral results partially confirm the assumption that two types of information processing could take place, as suggested by the reflective-impulsive model. At the neural level, using the network perspective, the results show that certain brain regions primarily associated with emotional and cognitive interaction processes are active during processing, depending on the framing of the message.

Discussion

In cases of indirect avoidance value-consistent framing, it may be good to communicate the bad in the appropriate frame to influence information processing.

Gaze differences in configural and elemental evaluation during multi-attribute decision-making

Introduction

While many everyday choices are between multi-attribute options, how attribute values are integrated to allow such choices remains unclear. Recent findings suggest a distinction between elemental (attribute-by-attribute) and configural (holistic) evaluation of multi-attribute options, with different neural substrates. Here, we asked if there are behavioral or gaze pattern differences between these putatively distinct modes of multi-attribute decision-making.

Methods

Thirty-nine healthy men and women learned the monetary values of novel multi-attribute pseudo-objects (fribbles) and then made choices between pairs of these objects while eye movements were tracked. Value was associated with individual attributes in the elemental condition, and with unique combinations of attributes in the configural condition. Choice, reaction time, gaze fixation time on options and individual attributes, and within- and between-option gaze transitions were recorded.

Results

There were systematic behavioral differences between elemental and configural conditions. Elemental trials had longer reaction times and more between-option transitions, while configural trials had more within-option transitions. The effect of last fixation on choice was more pronounced in the configural condition.

Discussion

We observed differences in gaze patterns and the influence of last fixation location on choice in multi-attribute value-based choices depending on how value is associated with those attributes. This adds support for the claim that multi-attribute option values may emerge either elementally or holistically, reminiscent of similar distinctions in multi-attribute object recognition. This may be important to consider in neuroeconomics research that involve visually-presented complex objects.

Task state representations in vmPFC mediate relevant and irrelevant value signals and their behavioral influence

The ventromedial prefrontal-cortex (vmPFC) is known to contain expected value signals that inform our choices. But expected values even for the same stimulus can differ by task. In this study, we asked how the brain flexibly switches between such value representations in a task-dependent manner. Thirty-five participants alternated between tasks in which either stimulus color or motion predicted rewards. We show that multivariate vmPFC signals contain a rich representation that includes the current task state or context (motion/color), the associated expected value, and crucially, the irrelevant value of the alternative context. We also find that irrelevant value representations in vmPFC compete with relevant value signals, interact with task-state representations and relate to behavioral signs of value competition. Our results shed light on vmPFC's role in decision making, bridging between its role in mapping observations onto the task states of a mental map, and computing expected values for multiple states.

Neural mechanisms underlying the hierarchical construction of perceived aesthetic value

Little is known about how the brain computes the perceived aesthetic value of complex stimuli such as visual art. Here, we used computational methods in combination with functional neuroimaging to provide evidence that the aesthetic value of a visual stimulus is computed in a hierarchical manner via a weighted integration over both low and high level stimulus features contained in early and late visual cortex, extending into parietal and lateral prefrontal cortices. Feature representations in parietal and lateral prefrontal cortex may in turn be utilized to produce an overall aesthetic value in the medial prefrontal cortex. Such brain-wide computations are not only consistent with a feature-based mechanism for value construction, but also resemble computations performed by a deep convolutional neural network. Our findings thus shed light on the existence of a general neurocomputational mechanism for rapidly and flexibly producing value judgements across an array of complex novel stimuli and situations.

Category-specific memory encoding in the medial temporal lobe and beyond: the role of reward

The medial temporal lobe (MTL), including the hippocampus (HC), perirhinal cortex (PRC), and parahippocampal cortex (PHC), is central to memory formation. Reward enhances memory through interplay between the HC and substantia nigra/ventral tegmental area (SNVTA). While the SNVTA also innervates the MTL cortex and amygdala (AMY), their role in reward-enhanced memory is unclear. Prior research suggests category specificity in the MTL cortex, with the PRC and PHC processing object and scene memory, respectively. It is unknown, however, whether reward modulates category-specific memory processes. Furthermore, no study has demonstrated clear category specificity in the MTL for encoding processes contributing to subsequent recognition memory. To address these questions, we had 39 healthy volunteers (27 for all memory-based analyses) undergo functional magnetic resonance imaging while performing an incidental encoding task pairing objects or scenes with high or low reward, followed by a next-day recognition test. Behaviorally, high reward preferably enhanced object memory. Neural activity in the PRC and PHC reflected successful encoding of objects and scenes, respectively. Importantly, AMY encoding effects were selective for high-reward objects, with a similar pattern in the PRC. The SNVTA and HC showed no clear evidence of successful encoding. This behavioral and neural asymmetry may be conveyed through an anterior-temporal memory system, including the AMY and PRC, potentially in interplay with the ventromedial prefrontal cortex.

Filling the gaps: Cognitive control as a critical lens for understanding mechanisms of value-based decision-making

While often seeming to investigate rather different problems, research into value-based decision making and cognitive control have historically offered parallel insights into how people select thoughts and actions. While the former studies how people weigh costs and benefits to make a decision, the latter studies how they adjust information processing to achieve their goals. Recent work has highlighted ways in which decision-making research can inform our understanding of cognitive control. Here, we provide the complementary perspective: how cognitive control research has informed understanding of decision-making. We highlight three particular areas of research where this critical interchange has occurred: (1) how different types of goals shape the evaluation of choice options, (2) how people use control to adjust the ways they make their decisions, and (3) how people monitor decisions to inform adjustments to control at multiple levels and timescales. We show how adopting this alternate viewpoint offers new insight into the determinants of both decisions and control; provides alternative interpretations for common neuroeconomic findings; and generates fruitful directions for future research.

Prefrontal cortex interactions with the amygdala in primates

This review addresses functional interactions between the primate prefrontal cortex (PFC) and the amygdala, with emphasis on their contributions to behavior and cognition. The interplay between these two telencephalic structures contributes to adaptive behavior and to the evolutionary success of all primate species. In our species, dysfunction in this circuitry creates vulnerabilities to psychopathologies. Here, we describe amygdala-PFC contributions to behaviors that have direct relevance to Darwinian fitness: learned approach and avoidance, foraging, predator defense, and social signaling, which have in common the need for flexibility and sensitivity to specific and rapidly changing contexts. Examples include the prediction of positive outcomes, such as food availability, food desirability, and various social rewards, or of negative outcomes, such as threats of harm from predators or conspecifics. To promote fitness optimally, these stimulus-outcome associations need to be rapidly updated when an associative contingency changes or when the value of a predicted outcome changes. We review evidence from nonhuman primates implicating the PFC, the amygdala, and their functional interactions in these processes, with links to experimental work and clinical findings in humans where possible.

Dynamic Computation of Value Signals via a Common Neural Network in Multi-Attribute Decision-Making

Studies in decision neuroscience have identified robust neural representations for the value of choice options. However, overall values often depend on multiple attributes, and it is not well understood how the brain evaluates different attributes and integrates them to combined values. In particular, it is not clear whether attribute values are computed in distinct attribute-specific regions or within the general valuation network known to process overall values. Here, we used an fMRI choice task in which abstract stimuli had to be evaluated based on variations of the attributes color and motion. The behavioral data showed that participants responded faster when overall values were high and attribute value differences were low. On the neural level, we did not find that attribute values were systematically represented in areas V4 and V5, even though these regions are associated with attribute-specific processing of color and motion, respectively. Instead, attribute values were associated with activity in the posterior cingulate cortex, ventral striatum, and posterior inferior temporal gyrus. Further, overall values were represented in dorsolateral and ventromedial prefrontal cortex, and attribute value differences in dorsomedial prefrontal cortex, which suggests that these regions play a key role for the neural integration of attribute values.

The visual prefrontal cortex of anthropoids: interaction with temporal cortex in decision making and its role in the making of "visual animals"

The ventral prefrontal cortex (PFC) of primates-a region strongly implicated in decision making-receives highly processed visual sensory inputs from the inferior temporal cortex (ITC) and perirhinal cortex (PRC) and can therefore be considered visual PFC. Usually, the functions of temporal cortex and visual PFC have been discussed in separate literatures. By considering them together, we aim to clarify the ways in which fronto-temporal networks guide decision making. After discussing the ways in which visual PFC interacts with temporal cortex to promote decision making, we offer specific predictions about the selective roles of the ITC- and PRC-based fronto-temporal networks. Finally, we suggest that an increased reliance on visual PFC in anthropoid primates led to our emergence as 'visual' animals.

The hierarchical construction of value

Here we argue that the assignment of subjective value to potential outcomes at the time of decision-making is an active process, in which individual features of a potential outcome of varying degrees of abstraction are represented hierarchically and integrated in a weighted fashion to produce an overall value judgment. We implicate the lateral orbital and medial prefrontal cortex in this function, situating these areas more broadly within a hierarchical integration process that takes place throughout the cortex for the ultimate purpose of valuing options to guide decisions.

The role of ventromedial prefrontal cortex in reward valuation and future thinking during intertemporal choice

Intertemporal choices require trade-offs between short-term and long-term outcomes. Ventromedial prefrontal cortex (vmPFC) damage causes steep discounting of future rewards (delay discounting [DD]) and impoverished episodic future thinking (EFT). The role of vmPFC in reward valuation, EFT, and their interaction during intertemporal choice is still unclear. Here, 12 patients with lesions to vmPFC and 41 healthy controls chose between smaller-immediate and larger-delayed hypothetical monetary rewards while we manipulated reward magnitude and the availability of EFT cues. In the EFT condition, participants imagined personal events to occur at the delays associated with the larger-delayed rewards. We found that DD was steeper in vmPFC patients compared to controls, and not modulated by reward magnitude. However, EFT cues downregulated DD in vmPFC patients as well as controls. These findings indicate that vmPFC integrity is critical for the valuation of (future) rewards, but not to instill EFT in intertemporal choice.

A Preferential Role for Ventromedial Prefrontal Cortex in Assessing "the Value of the Whole" in Multiattribute Object Evaluation

Everyday decision-making commonly involves assigning values to complex objects with multiple value-relevant attributes. Drawing on object recognition theories, we hypothesized two routes to multiattribute evaluation: assessing the value of the whole object based on holistic attribute configuration or summing individual attribute values. In two samples of healthy human male and female participants undergoing eye tracking and functional magnetic resonance imaging (fMRI) while evaluating novel pseudo objects, we found evidence for both forms of evaluation. Fixations to and transitions between attributes differed systematically when the value of pseudo objects was associated with individual attributes or attribute configurations. Ventromedial prefrontal cortex (vmPFC) and perirhinal cortex were engaged when configural processing was required. These results converge with our recent findings that individuals with vmPFC lesions were impaired in decisions requiring configural evaluation but not when evaluating the sum of the parts. This suggests that multiattribute decision-making engages distinct evaluation mechanisms relying on partially dissociable neural substrates, depending on the relationship between attributes and value.SIGNIFICANCE STATEMENT Decision neuroscience has only recently begun to address how multiple choice-relevant attributes are brought together during evaluation and choice among complex options. Object recognition research makes a crucial distinction between individual attribute and holistic/configural object processing, but how the brain evaluates attributes and whole objects remains unclear. Using fMRI and eye tracking, we found that the vmPFC and the perirhinal cortex contribute to value estimation specifically when value was related to whole objects, that is, predicted by the unique configuration of attributes and not when value was predicted by the sum of individual attribute values. This perspective on the interactions between subjective value and object processing mechanisms provides a novel bridge between the study of object recognition and reward-guided decision-making.

Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features

It is an open question whether preferences for visual art can be lawfully predicted from the basic constituent elements of a visual image. Here, we developed and tested a computational framework to investigate how aesthetic values are formed. We show that it is possible to explain human preferences for a visual art piece based on a mixture of low- and high-level features of the image. Subjective value ratings could be predicted not only within but also across individuals, using a regression model with a common set of interpretable features. We also show that the features predicting aesthetic preference can emerge hierarchically within a deep convolutional neural network trained only for object recognition. Our findings suggest that human preferences for art can be explained at least in part as a systematic integration over the underlying visual features of an image.

Reduced decision bias and more rational decision making following ventromedial prefrontal cortex damage

Human decisions are susceptible to biases, but establishing causal roles of brain areas has proved to be difficult. Here we studied decision biases in 17 people with unilateral medial prefrontal cortex damage and a rare patient with bilateral ventromedial prefrontal cortex (vmPFC) lesions. Participants learned to choose which of two options was most likely to win, and then bet money on the outcome. Thus, good performance required not only selecting the best option, but also the amount to bet. Healthy people were biased by their previous bet, as well as by the unchosen option's value. Unilateral medial prefrontal lesions reduced these biases, leading to more rational decisions. Bilateral vmPFC lesions resulted in more strategic betting, again with less bias from the previous trial, paradoxically improving performance overall. Together, the results suggest that vmPFC normally imposes contextual biases, which in healthy people may actually be suboptimal in some situations.

Causal investigations into orbitofrontal control of human decision making

Although it is widely accepted that the orbitofrontal cortex (OFC) is important for decision making, its precise contribution to behavior remains a topic of debate. While many loss of function experiments have been conducted in animals, causal studies of human OFC function are relatively scarce. This review discusses recent causal investigations into the human OFC, with an emphasis on advances in network-based brain stimulation approaches to indirectly perturb OFC function. Findings show that disruption of human OFC impairs decisions that require mental simulation of outcomes. Taken together, these results support the idea that human OFC contributes to decision making by representing a cognitive map of the task environment, facilitating inference of outcomes not yet experienced. Future work may utilize similar non-invasive approaches in clinical settings to mitigate decision making deficits in neuropsychiatric disorders.

Excitatory-inhibitory tone shapes decision strategies in a hierarchical neural network model of multi-attribute choice

We are constantly faced with decisions between alternatives defined by multiple attributes, necessitating an evaluation and integration of different information sources. Time-varying signals in multiple brain areas are implicated in decision-making; but we lack a rigorous biophysical description of how basic circuit properties, such as excitatory-inhibitory (E/I) tone and cascading nonlinearities, shape attribute processing and choice behavior. Furthermore, how such properties govern choice performance under varying levels of environmental uncertainty is unknown. We investigated two-attribute, two-alternative decision-making in a dynamical, cascading nonlinear neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a final layer producing the decision. Depending on intermediate layer E/I tone, the network displays distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option's attribute information is additively integrated. In regime III, time-varying nonlinear operations amplify the separation between offer distributions by selectively attending to the attribute with the larger differences in input values. At low environmental uncertainty, a linear combination most consistently selects higher valued alternatives. However, at high environmental uncertainty, regime III is more likely than a linear operation to select alternatives with higher value. Furthermore, there are conditions where readout from the intermediate layer could be experimentally indistinguishable from the final layer. Finally, these principles are used to examine multi-attribute decisions in systems with reduced inhibitory tone, leading to predictions of different choice patterns and overall performance between those with restrictions on inhibitory tone and neurotypicals.

Entorhinal and ventromedial prefrontal cortices abstract and generalize the structure of reinforcement learning problems

Knowledge of the structure of a problem, such as relationships between stimuli, enables rapid learning and flexible inference. Humans and other animals can abstract this structural knowledge and generalize it to solve new problems. For example, in spatial reasoning, shortest-path inferences are immediate in new environments. Spatial structural transfer is mediated by cells in entorhinal and (in humans) medial prefrontal cortices, which maintain their co-activation structure across different environments and behavioral states. Here, using fMRI, we show that entorhinal and ventromedial prefrontal cortex (vmPFC) representations perform a much broader role in generalizing the structure of problems. We introduce a task-remapping paradigm, where subjects solve multiple reinforcement learning (RL) problems differing in structural or sensory properties. We show that, as with space, entorhinal representations are preserved across different RL problems only if task structure is preserved. In vmPFC and ventral striatum, representations of prediction error also depend on task structure.

From affective to cognitive processing: Functional organization of the medial frontal cortex

The medial wall of the primate frontal lobe encompasses multiple anatomical subregions. Based on distinct neurophysiological correlates and effects of lesions, individual areas are thought to play unique roles in behavior. Further, evidence suggests that dysfunction localized to specific subregions is commonly found in different neuropsychiatric disorders. The neurobiological underpinnings of these disorders, however, remain far from clear. Here, to better understand the functions of medial frontal cortex (MFC) and its role in psychiatric disease, we focus on its functional organization. We describe the emerging pattern in which more dorsal regions subserve temporally extended cognitive functions and more ventral regions predominantly subserve affective functions. We focus on two specific domains, decision-making and social cognition, that require integration across emotion and cognition. In each case, we discuss the current understanding of the functions believed to depend on subregions of MFC as a stepping-stone to speculate on how they might work in unison. We conclude with an overview of how symptoms of certain psychiatric disorders relate to our understanding of MFC functional organization and how further discovery could fuel advances in circuit-based therapies.

Experimentally revealed stochastic preferences for multicomponent choice options

Realistic, everyday rewards contain multiple components. An apple has taste and size. However, we choose in single dimensions, simply preferring some apples to others. How can such single-dimensional preference relationships refer to multicomponent choice options? Here, we measured how stochastic choices revealed preferences for 2-component milkshakes. The preferences were intuitively graphed as indifference curves that represented the orderly integration of the 2 components as trade-off: parts of 1 component were given up for obtaining 1 additional unit of the other component without a change in preference. The well-ordered, nonoverlapping curves satisfied leave-one-out tests, followed predictions by machine learning decoders and correlated with single-dimensional Becker-DeGroot-Marschak (BDM) auction-like bids for the 2-component rewards. This accuracy suggests a decision process that integrates multiple reward components into single-dimensional estimates in a systematic fashion. In interspecies comparisons, human performance matched that of highly experienced laboratory monkeys, as measured by accuracy of the critical trade-off between bundle components. These data describe the nature of choices of multicomponent choice options and attest to the validity of the rigorous economic concepts and their convenient graphic schemes for explaining choices of human and nonhuman primates. The results encourage formal behavioral and neural investigations of normal, irrational, and pathological economic choices. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Value Neglect: A Critical Role for Ventromedial Frontal Lobe in Learning the Value of Spatial Locations

Whether you are a gazelle bounding to the richest tract of grassland or a return customer heading to the freshest farm stand at a crowded market, the ability to learn the value of spatial locations is important in adaptive behavior. The ventromedial frontal lobe (VMF) is implicated in value-based decisions between objects and in flexibly learning to choose between objects based on feedback. However, it is unclear if this region plays a material-general role in reward learning. Here, we tested whether VMF is necessary for learning the value of spatial locations. People with VMF damage were compared with healthy participants and a control group with frontal damage sparing VMF in an incentivized spatial search task. Participants chose among spatial targets distributed among distractors, rewarded with an expected value that varied along the right-left axis of the screen. People with VMF damage showed a weaker tendency to reap reward in contralesional hemispace. In some individuals, this impairment could be dissociated from the ability to make value-based decisions between objects, assessed separately. This is the first evidence that the VMF is critically involved in reward-guided spatial search and offers a novel perspective on the relationships between value, spatial attention, and decision-making.

Individual Differences in Hippocampal Volume as a Function of BMI and Reward Sensitivity

Sensitivity to reward is a personality trait that predisposes a person to several addictive behaviors, including the presence of different risky behaviors that facilitates uncontrolled eating. However, the multifactorial nature of obesity blurs a direct relationship between the two factors. Here, we studied the brain anatomic correlates of the interaction between reward sensitivity and body mass index (BMI) to investigate whether the coexistence of high BMI and high reward sensitivity structurally alters brain areas specifically involved in the regulation of eating behavior. To achieve this aim, we acquired T1-weighted images and measured reward sensitivity using the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) and BMI in a sample of 206 adults. Results showed that reward sensitivity and BMI were not significantly correlated. However, neuroimaging results confirmed a relationship between BMI and reduced volume in the medial and lateral orbitofrontal cortex, and between reward sensitivity and lower striatum volume. Importantly, the interaction between the two factors was significantly related to the right anterior hippocampus volume, showing that stronger reward sensitivity plus a higher BMI were associated with reduced hippocampal volume. The hippocampus is a brain structure involved in the higher-order regulation of feeding behavior. Thus, a dysfunctional hippocampus may contribute to maintaining a vicious cycle that predisposes people to obesity.

Under construction: ventral and lateral frontal lobe contributions to value-based decision-making and learning

Even apparently simple choices, like selecting a dessert in a pastry shop, involve options characterized by multiple motivationally relevant attributes. Neuroeconomic research suggests that the human brain may track the subjective value of such options, allowing disparate reward-predictive information to be compared in a common currency. However, the brain mechanisms involved in identifying value-predictive features and combining these to assess the value of each decision option remain unclear. Here, we review recent evidence from studies of multi-attribute decision-making in people with focal frontal lobe damage and in healthy people undergoing functional magnetic resonance imaging. This work suggests that ventromedial and lateral prefrontal cortex and orbitofrontal cortex are important for forming value judgments under conditions of complexity. We discuss studies supporting the involvement of these regions in selecting among and evaluating option attributes during value judgment and decision-making and when learning from reward feedback. These findings are consistent with roles for these regions in guiding value construction. They argue for a more nuanced understanding of how ventral and lateral prefrontal cortex contribute to discovering and recognizing value, processes that are required under the complex conditions typical of many everyday decisions.

Beyond a rod through the skull: A systematic review of lesion studies of the human ventromedial frontal lobe

Neuropsychological studies from the past century have associated damage to the ventromedial frontal lobes (VMF) with impairments in a variety of domains, including memory, executive function, emotion, social cognition, and valuation. A central question in the literature is whether these seemingly distinct functions are subserved by different sub-regions within the VMF, or whether VMF supports a broader cognitive process that is crucial to these varied domains. In this comprehensive review of the neuropsychological literature from the last two decades, we present a qualitative synthesis of 184 papers that have examined the psychological impairments that result from VMF damage. We discuss these findings in the context of several theoretical frameworks and advocate for the view that VMF is critical for the formation and representation of schema and cognitive maps.

Orbitofrontal signals for two-component choice options comply with indifference curves of Revealed Preference Theory

Economic choice options contain multiple components and constitute vectorial bundles. The question arises how they are represented by single-dimensional, scalar neuronal signals that are suitable for economic decision-making. Revealed Preference Theory provides formalisms for establishing preference relations between such bundles, including convenient graphic indifference curves. During stochastic choice between bundles with the same two juice components, we identified neuronal signals for vectorial, multi-component bundles in the orbitofrontal cortex of monkeys. A scalar signal integrated the values from all bundle components in the structured manner of the Theory; it followed the behavioral indifference curves within their confidence limits, was indistinguishable between differently composed but equally revealed preferred bundles, predicted bundle choice and complied with an optimality axiom. Further, distinct signals in other neurons coded the option components separately but followed indifference curves as a population. These data demonstrate how scalar signals represent vectorial, multi-component choice options.

The hippocampus supports deliberation during value-based decisions

Choosing between two items involves deliberation and comparison of the features of each item and its value. Such decisions take more time when choosing between options of similar value, possibly because these decisions require more evidence, but the mechanisms involved are not clear. We propose that the hippocampus supports deliberation about value, given its well-known role in prospection and relational cognition. We assessed the role of the hippocampus in deliberation in two experiments. First, using fMRI in healthy participants, we found that BOLD activity in the hippocampus increased as a function of deliberation time. Second, we found that patients with hippocampal damage exhibited more stochastic choices and longer reaction times than controls, possibly due to their failure to construct value-based or internal evidence during deliberation. Both sets of results were stronger in value-based decisions compared to perceptual decisions.