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Selective attention to affective value alters how the brain processes taste stimuli.

How does selective attention to affect influence sensory processing? In an fMRI investigation, when subjects were instructed to remember and rate the pleasantness of a taste stimulus, 0.1 M monosodium glutamate, activations were greater in the medial orbitofrontal and pregenual cingulate cortex than when subjects were instructed to remember and rate the intensity of the taste. When the subjects were instructed to remember and rate the intensity, activations were greater in the insular taste cortex. An interaction analysis showed that this dissociation of taste processing, depending on whether attention to pleasantness or intensity was relevant, was highly significant (P < 0.0002). Thus, depending on the context in which tastes are presented and whether affect is relevant, the brain responds to a taste differently. These findings show that, when attention is paid to affective value, the brain systems engaged to represent the sensory stimulus of taste are different from those engaged when attention is directed to the physical properties of a stimulus such as its intensity. This differential biasing of brain regions engaged in processing a sensory stimulus, depending on whether the cognitive demand is for affect-related vs. more sensory-related processing, may be an important aspect of cognition and attention. This has many implications for understanding the effects not only of taste but also of other sensory stimuli.

Decisions under ambiguity and decisions under risk: correlations with executive functions and comparisons of two different gambling tasks with implicit and explicit rules.

We conducted two experiments with healthy subjects to investigate the possible relationships between Iowa Gambling Task (IGT) performance and executive functions as well as IGT performance and decision-making in a task with explicit rules, the Game of Dice Task (GDT). Results indicated that only the last trials of the IGT were correlated with executive functions and GDT performance. We suggest that the IGT taps into two mechanisms of decision-making: decisions under ambiguity in the first trials and decisions under risk in the latter trials. Results have impact on the interpretation of deficient IGT performance in patients with frontal lobe dysfunctions.

Nonhuman Primates Satisfy Utility Maximization in Compliance with the Continuity Axiom of Expected Utility Theory.

Expected Utility Theory (EUT), the first axiomatic theory of risky choice, describes choices as a utility maximization process: decision makers assign a subjective value (utility) to each choice option and choose the one with the highest utility. The continuity axiom, central to Expected Utility Theory and its modifications, is a necessary and sufficient condition for the definition of numerical utilities. The axiom requires decision makers to be indifferent between a gamble and a specific probabilistic combination of a more preferred and a less preferred gamble. While previous studies demonstrated that monkeys choose according to combinations of objective reward magnitude and probability, a concept-driven experimental approach for assessing the axiomatically defined conditions for maximizing utility by animals is missing. We experimentally tested the continuity axiom for a broad class of gamble types in 4 male rhesus macaque monkeys, showing that their choice behavior complied with the existence of a numerical utility measure as defined by the economic theory. We used the numerical quantity specified in the continuity axiom to characterize subjective preferences in a magnitude-probability space. This mapping highlighted a trade-off relation between reward magnitudes and probabilities, compatible with the existence of a utility function underlying subjective value computation. These results support the existence of a numerical utility function able to describe choices, allowing for the investigation of the neuronal substrates responsible for coding such rigorously defined quantity.SIGNIFICANCE STATEMENT A common assumption of several economic choice theories is that decisions result from the comparison of subjectively assigned values (utilities). This study demonstrated the compliance of monkey behavior with the continuity axiom of Expected Utility Theory, implying a subjective magnitude-probability trade-off relation, which supports the existence of numerical utility directly linked to the theoretical economic framework. We determined a numerical utility measure able to describe choices, which can serve as a correlate for the neuronal activity in the quest for brain structures and mechanisms guiding decisions.

Preferences for nutrients and sensory food qualities identify biological sources of economic values in monkeys.

Value is a foundational concept in reinforcement learning and economic choice theory. In these frameworks, individuals choose by assigning values to objects and learn by updating values with experience. These theories have been instrumental for revealing influences of probability, risk, and delay on choices. However, they do not explain how values are shaped by intrinsic properties of the choice objects themselves. Here, we investigated how economic value derives from the biologically critical components of foods: their nutrients and sensory qualities. When monkeys chose nutrient-defined liquids, they consistently preferred fat and sugar to low-nutrient alternatives. Rather than maximizing energy indiscriminately, they seemed to assign subjective values to specific nutrients, flexibly trading them against offered reward amounts. Nutrient-value functions accurately modeled these preferences, predicted choices across contexts, and accounted for individual differences. The monkeys' preferences shifted their daily nutrient balance away from dietary reference points, contrary to ecological foraging models but resembling human suboptimal eating in free-choice situations. To identify the sensory basis of nutrient values, we developed engineering tools that measured food textures on biological surfaces, mimicking oral conditions. Subjective valuations of two key texture parameters-viscosity and sliding friction-explained the monkeys' fat preferences, suggesting a texture-sensing mechanism for nutrient values. Extended reinforcement learning and choice models identified candidate neuronal mechanisms for nutrient-sensitive decision-making. These findings indicate that nutrients and food textures constitute critical reward components that shape economic values. Our nutrient-choice paradigm represents a promising tool for studying food-reward mechanisms in primates to better understand human-like eating behavior and obesity.

Primate prefrontal neurons signal economic risk derived from the statistics of recent reward experience.

Risk derives from the variation of rewards and governs economic decisions, yet how the brain calculates risk from the frequency of experienced events, rather than from explicit risk-descriptive cues, remains unclear. Here, we investigated whether neurons in dorsolateral prefrontal cortex process risk derived from reward experience. Monkeys performed in a probabilistic choice task in which the statistical variance of experienced rewards evolved continually. During these choices, prefrontal neurons signaled the reward-variance associated with specific objects ('object risk') or actions ('action risk'). Crucially, risk was not derived from explicit, risk-descriptive cues but calculated internally from the variance of recently experienced rewards. Support-vector-machine decoding demonstrated accurate neuronal risk discrimination. Within trials, neuronal signals transitioned from experienced reward to risk (risk updating) and from risk to upcoming choice (choice computation). Thus, prefrontal neurons encode the statistical variance of recently experienced rewards, complying with formal decision variables of object risk and action risk.

Neural Basis for Economic Saving Strategies in Human Amygdala-Prefrontal Reward Circuits.

Economic saving is an elaborate behavior in which the goal of a reward in the future directs planning and decision-making in the present. Here, we measured neural activity while subjects formed simple economic saving strategies to accumulate rewards and then executed their strategies through choice sequences of self-defined lengths. Before the initiation of a choice sequence, prospective activations in the amygdala predicted subjects' internal saving plans and their value up to two minutes before a saving goal was achieved. The valuation component of this planning activity persisted during execution of the saving strategy and predicted subjects' economic behavior across different tasks and testing days. Functionally coupled amygdala and prefrontal cortex activities encoded distinct planning components that signaled the transition from saving strategy formation to execution and reflected individual differences in saving behavior. Our findings identify candidate neural mechanisms for economic saving in amygdala and prefrontal cortex and suggest a novel planning function for the human amygdala in directing strategic behavior toward self-determined future rewards.

Componential Granger causality, and its application to identifying the source and mechanisms of the top-down biased activation that controls attention to affective vs sensory processing.

We describe a new measure of Granger causality, componential Granger causality, and show how it can be applied to the identification of the directionality of influences between brain areas with functional neuroimaging data. Componential Granger causality measures the effect of y on x, but allows interaction effects between y and x to be measured. In addition, the terms in componential Granger causality sum to 1, allowing causal effects to be directly compared between systems. We show using componential Granger causality analysis applied to an fMRI investigation that there is a top-down attentional effect from the anterior dorsolateral prefrontal cortex to the orbitofrontal cortex when attention is paid to the pleasantness of a taste, and that this effect depends on the activity in the orbitofrontal cortex as shown by the interaction term. Correspondingly there is a top-down attentional effect from the posterior dorsolateral prefrontal cortex to the insular primary taste cortex when attention is paid to the intensity of a taste, and this effect depends on the activity of the insular primary taste cortex as shown by the interaction term. Componential Granger causality thus not only can reveal the directionality of effects between areas (and these can be bidirectional), but also allows the mechanisms to be understood in terms of whether the causal influence of one system on another depends on the state of the system being causally influenced. Componential Granger causality measures the full effects of second order statistics by including variance and covariance effects between each time series, thus allowing interaction effects to be measured, and also provides a systematic framework within which to measure the effects of cross, self, and noise contributions to causality. The findings reveal some of the mechanisms involved in a biased activation theory of selective attention.

Different representations of relative and absolute subjective value in the human brain.

Relative reward value is important for the choice between a set of available rewards, and absolute reward value for stable and consistent economic choice. It is unclear whether in the human brain subjective absolute value representations can be dissociated from relative reward value representations. Using fMRI, we investigated how the subjective pleasantness of an odor is influenced by whether the odor is presented in the context of a relatively more pleasant or less pleasant odor. We delivered two of a set of four odors separated by a delay of 6 s, with the instruction to rate the pleasantness of the second odor, and searched for brain regions where the activations were correlated with the absolute pleasantness rating of the second odor, and for brain regions where the activations were correlated with the difference in pleasantness of the second from the first odor, that is, with relative pleasantness. Activations in the anterolateral orbitofrontal cortex tracked the relative subjective pleasantness, whereas activations in the anterior insula tracked the relative subjective unpleasantness. In contrast, in the medial and midorbitofrontal cortex activations tracked the absolute pleasantness of the stimuli. Thus, both relative and absolute subjective value signals which provide important inputs to decision-making processes about which stimulus to choose are separately and simultaneously represented in the human brain.

Warm pleasant feelings in the brain.

Warm and cold stimuli have affective components such as feeling pleasant or unpleasant, and these components may have survival value, for approach to warmth and avoidance of cold may be reinforcers or goals for action built into us during evolution to direct our behaviour to stimuli that are appropriate for survival. Understanding the brain processing that underlies these prototypical reinforcers provides a direct approach to understanding the brain mechanisms of emotion. In an fMRI investigation in humans, we showed that the mid-orbitofrontal and pregenual cingulate cortex and the ventral striatum have activations that are correlated with the subjective pleasantness ratings made to warm (41 degrees C) and cold (12 degrees C) stimuli, and combinations of warm and cold stimuli, applied to the hand. Activations in the lateral and some more anterior parts of the orbitofrontal cortex were correlated with the unpleasantness of the stimuli. In contrast, activations in the somatosensory cortex and ventral posterior insula were correlated with the intensity but not the pleasantness of the thermal stimuli. A principle thus appears to be that processing related to the affective value and associated subjective emotional experience of thermal stimuli that are important for survival is performed in different brain areas to those where activations are related to sensory properties of the stimuli such as their intensity. This conclusion appears to be the case for processing in a number of sensory modalities, and the finding with such prototypical stimuli as warm and cold provides strong support for this principle.

A hedonically complex odor mixture produces an attentional capture effect in the brain.

A counter-intuitive property of many pleasant and attractive stimuli is that they are hedonically complex, containing both pleasant and unpleasant components. A striking example is the floral scent of natural jasmine, which may contain more than 6% of indole, a pure chemical which is usually rated as unpleasant. Using fMRI we investigate the hypothesis that the interaction between the pleasant and unpleasant components in the hedonically complex natural jasmine produces an attentional capture effect in the brain. First, to localize brain areas involved in selective attention to odor, we compared neural activity in response to jasmine without indole when participants explicitly and selectively attended to either its pleasantness or intensity, with neural activity when no selective attention was required. We then show that the superior frontal gyrus has increased activity both when selective attention is being paid to jasmine without indole, and also when no selective attention is required but an unpleasant component is added to it to produce a hedonically complex mixture. The attentional capture effect in the superior frontal gyrus by the mixture was related to the hedonic complexity of the mixture across subjects; could not be explained by salience, intensity, or pleasantness; and was specific to the superior frontal gyrus in that it was not found in other prefrontal areas activated by selective attention. The investigation supports the new hypothesis that the affective potency of stimuli with mixed pleasant and unpleasant components is related at least in part to the recruitment of mechanisms in the brain involved in attentional capture and enhancement.

Neural Mechanisms for Accepting and Rejecting Artificial Social Partners in the Uncanny Valley.

Artificial agents are becoming prevalent across human life domains. However, the neural mechanisms underlying human responses to these new, artificial social partners remain unclear. The uncanny valley (UV) hypothesis predicts that humans prefer anthropomorphic agents but reject them if they become too humanlike-the so-called UV reaction. Using fMRI, we investigated neural activity when subjects evaluated artificial agents and made decisions about them. Across two experimental tasks, the ventromedial prefrontal cortex (VMPFC) encoded an explicit representation of subjects' UV reactions. Specifically, VMPFC signaled the subjective likability of artificial agents as a nonlinear function of humanlikeness, with selective low likability for highly humanlike agents. In exploratory across-subject analyses, these effects explained individual differences in psychophysical evaluations and preference choices. Functionally connected areas encoded critical inputs for these signals: the temporoparietal junction encoded a linear humanlikeness continuum, whereas nonlinear representations of humanlikeness in dorsomedial prefrontal cortex (DMPFC) and fusiform gyrus emphasized a human-nonhuman distinction. Following principles of multisensory integration, multiplicative combination of these signals reconstructed VMPFC's valuation function. During decision making, separate signals in VMPFC and DMPFC encoded subjects' decision variable for choices involving humans or artificial agents, respectively. A distinct amygdala signal predicted rejection of artificial agents. Our data suggest that human reactions toward artificial agents are governed by a neural mechanism that generates a selective, nonlinear valuation in response to a specific feature combination (humanlikeness in nonhuman agents). Thus, a basic principle known from sensory coding-neural feature selectivity from linear-nonlinear transformation-may also underlie human responses to artificial social partners.SIGNIFICANCE STATEMENT Would you trust a robot to make decisions for you? Autonomous artificial agents are increasingly entering our lives, but how the human brain responds to these new artificial social partners remains unclear. The uncanny valley (UV) hypothesis-an influential psychological framework-captures the observation that human responses to artificial agents are nonlinear: we like increasingly anthropomorphic artificial agents, but feel uncomfortable if they become too humanlike. Here we investigated neural activity when humans evaluated artificial agents and made personal decisions about them. Our findings suggest a novel neurobiological conceptualization of human responses toward artificial agents: the UV reaction-a selective dislike of highly humanlike agents-is based on nonlinear value-coding in ventromedial prefrontal cortex, a key component of the brain's reward system.

Prediction of economic choice by primate amygdala neurons.

The amygdala is a key structure of the brain's reward system. Existing theories view its role in decision-making as restricted to an early valuation stage that provides input to decision mechanisms in downstream brain structures. However, the extent to which the amygdala itself codes information about economic choices is unclear. Here, we report that individual neurons in the primate amygdala predict behavioral choices in an economic decision task. We recorded the activity of amygdala neurons while monkeys chose between saving liquid reward with interest and spending the accumulated reward. In addition to known value-related responses, we found that activity in a group of amygdala neurons predicted the monkeys' upcoming save-spend choices with an average accuracy of 78%. This choice-predictive activity occurred early in trials, even before information about specific actions associated with save-spend choices was available. For a substantial number of neurons, choice-differential activity was specific for free, internally generated economic choices and not observed in a control task involving forced imperative choices. A subgroup of choice-predictive neurons did not show relationships to value, movement direction, or visual stimulus features. Choice-predictive activity in some amygdala neurons was preceded by transient periods of value coding, suggesting value-to-choice transitions and resembling decision processes in other brain systems. These findings suggest that the amygdala might play an active role in economic decisions. Current views of amygdala function should be extended to incorporate a role in decision-making beyond valuation.

A dynamic code for economic object valuation in prefrontal cortex neurons.

Neuronal reward valuations provide the physiological basis for economic behaviour. Yet, how such valuations are converted to economic decisions remains unclear. Here we show that the dorsolateral prefrontal cortex (DLPFC) implements a flexible value code based on object-specific valuations by single neurons. As monkeys perform a reward-based foraging task, individual DLPFC neurons signal the value of specific choice objects derived from recent experience. These neuronal object values satisfy principles of competitive choice mechanisms, track performance fluctuations and follow predictions of a classical behavioural model (Herrnstein's matching law). Individual neurons dynamically encode both, the updating of object values from recently experienced rewards, and their subsequent conversion to object choices during decision-making. Decoding from unselected populations enables a read-out of motivational and decision variables not emphasized by individual neurons. These findings suggest a dynamic single-neuron and population value code in DLPFC that advances from reward experiences to economic object values and future choices.

Primate amygdala neurons evaluate the progress of self-defined economic choice sequences.

The amygdala is a prime valuation structure yet its functions in advanced behaviors are poorly understood. We tested whether individual amygdala neurons encode a critical requirement for goal-directed behavior: the evaluation of progress during sequential choices. As monkeys progressed through choice sequences toward rewards, amygdala neurons showed phasic, gradually increasing responses over successive choice steps. These responses occurred in the absence of external progress cues or motor preplanning. They were often specific to self-defined sequences, typically disappearing during instructed control sequences with similar reward expectation. Their build-up rate reflected prospectively the forthcoming choice sequence, suggesting adaptation to an internal plan. Population decoding demonstrated a high-accuracy progress code. These findings indicate that amygdala neurons evaluate the progress of planned, self-defined behavioral sequences. Such progress signals seem essential for aligning stepwise choices with internal plans. Their presence in amygdala neurons may inform understanding of human conditions with amygdala dysfunction and deregulated reward pursuit.

Functions of primate amygdala neurons in economic decisions and social decision simulation.

Long implicated in aversive processing, the amygdala is now recognized as a key component of the brain systems that process rewards. Beyond reward valuation, recent findings from single-neuron recordings in monkeys indicate that primate amygdala neurons also play an important role in decision-making. The reward value signals encoded by amygdala neurons constitute suitable inputs to economic decision processes by being sensitive to reward contingency, relative reward quantity and temporal reward structure. During reward-based decisions, individual amygdala neurons encode both the value inputs and corresponding choice outputs of economic decision processes. The presence of such value-to-choice transitions in single amygdala neurons, together with other well-defined signatures of decision computation, indicate that a decision mechanism may be implemented locally within the primate amygdala. During social observation, specific amygdala neurons spontaneously encode these decision signatures to predict the choices of social partners, suggesting neural simulation of the partner's decision-making. The activity of these 'simulation neurons' could arise naturally from convergence between value neurons and social, self-other discriminating neurons. These findings identify single-neuron building blocks and computational architectures for decision-making and social behavior in the primate amygdala. An emerging understanding of the decision function of primate amygdala neurons can help identify potential vulnerabilities for amygdala dysfunction in human conditions afflicting social cognition and mental health.

How pleasant and unpleasant stimuli combine in different brain regions: odor mixtures.

Many affective stimuli are hedonically complex mixtures containing both pleasant and unpleasant components. To investigate whether the brain represents the overall affective value of such complex stimuli, or the affective value of the different components simultaneously, we used functional magnetic resonance imaging to measure brain activations to a pleasant odor (jasmine), an unpleasant odor (indole), and a mixture of the two that was pleasant. In brain regions that represented the pleasantness of the odors such as the medial orbitofrontal cortex (as shown by activations that correlated with the pleasantness ratings), the mixture produced activations of similar magnitude to the pleasant jasmine, but very different from the unpleasant indole. These regions thus emphasize the pleasant aspects of the mixture. In contrast, in regions representing the unpleasantness of odors such as the dorsal anterior cingulate and midorbitofrontal cortex the mixture produced activations that were relatively further from the pleasant component jasmine and closer to the indole. These regions thus emphasize the unpleasant aspects of the mixture. Thus mixtures that are found pleasant can have components that are separately pleasant and unpleasant, and the brain can separately and simultaneously represent the positive and negative hedonic value of a complex affective stimulus that contains both pleasant and unpleasant olfactory components. This type of representation may be important for affective decision making in the brain in that separate representations of different affective components of the same sensory stimulus may provide the inputs for making a decision about whether to choose the stimulus or not.

Human cortical representation of oral temperature.

The temperature of foods and fluids is a major factor that determines their pleasantness and acceptability. Studies of nonhuman primates have shown that many neurons in cortical taste areas receive and process not only chemosensory inputs, but oral thermosensory (temperature) inputs as well. We investigated whether changes in oral temperature activate these areas in humans, or middle or posterior insular cortex, the areas most frequently identified for the encoding of temperature information from the human hand. In the fMRI study we identified areas of activation in response to innocuous, temperature-controlled (cooled and warmed, 5, 20 and 50 degrees C) liquid introduced into the mouth. The oral temperature stimuli activated the insular taste cortex (identified by glucose taste stimuli), a part of the somatosensory cortex, the orbitofrontal cortex, the anterior cingulate cortex, and the ventral striatum. Brain regions where activations correlated with the pleasantness ratings of the oral temperature stimuli included the orbitofrontal cortex and pregenual cingulate cortex. We conclude that a network of taste- and reward-responsive regions of the human brain is also activated by intra-oral thermal stimulation, and that the pleasant subjective states elicited by oral thermal stimuli are correlated with the activations in the orbitofrontal cortex and pregenual cingulate cortex. Thus the pleasantness of oral temperature is represented in brain regions shown in previous studies to represent the pleasantness of the taste and flavour of food. Bringing together these different oral representations in the same brain regions may enable particular combinations to influence the pleasantness of foods.

Choice, difficulty, and confidence in the brain.

To provide a neurobiological basis for understanding decision-making and decision confidence, we describe and analyze a neuronal spiking attractor-based model of decision-making that makes predictions about synaptic and neuronal activity, the fMRI BOLD response, and behavioral choice as a function of the easiness of the decision, and thus decision confidence. The spiking network model predicts probabilistic decision-making with faster and larger neuronal responses on easy versus difficult choices, that is as the discriminability DeltaI between the choices increases, and these and the synaptic currents in turn predict larger BOLD responses as the discriminability increases. Confidence, which increases with discriminability, thus emerges from the firing rates of the decision-making neurons in the choice attractor network. In two fMRI studies, we confirm these predictions by showing that brain areas such as medial prefrontal cortex area 10 implicated in choice decision-making between pleasant stimuli have BOLD activations linearly related to the easiness of both olfactory and warm pleasantness choices. Further, this signature is not found in orbitofrontal cortex areas that represent on a continuous scale the value of the stimuli, but are not implicated in the choice itself. This provides a unifying and fundamental approach to decision-making and decision confidence, and to how spiking-related noise in the brain affects choice, confidence, synaptic and neuronal activity, and fMRI signals.

Food labels promote healthy choices by a decision bias in the amygdala.

Food labeling is the major health policy strategy to counter rising obesity rates. Based on traditional economic theory, such strategies assume that detailed nutritional information will necessarily help individuals make better, healthier choices. However, in contrast to the well-known utility of labels in food marketing, evidence for the efficacy of nutritional labeling is mixed. Psychological and behavioral economic theories suggest that successful marketing strategies activate automatic decision biases and emotions, which involve implicit emotional brain systems. Accordingly, simple, intuitive food labels that engage these neural systems could represent a promising approach for promoting healthier choices. Here we used functional MRI to investigate this possibility. Healthy, mildly hungry subjects performed a food evaluation task and a food choice task. The main experimental manipulation was to pair identical foods with simple labels that emphasized either taste benefits or health-related food properties. We found that such labels biased food evaluations in the amygdala, a core emotional brain system. When labels biased the amygdala's evaluations towards health-related food properties, the strength of this bias predicted behavioral shifts towards healthier choices. At the time of decision-making, amygdala activity encoded key decision variables, potentially reflecting active amygdala participation in food choice. Our findings underscore the potential utility of food labeling in health policy and indicate a principal role for emotional brain systems when labels guide food choices.

Non-human primates satisfy utility maximization in compliance with the continuity axiom of Expected Utility Theory