Planning activity for internally generated reward goals in monkey amygdala neurons

Intrinsic anticipatory motives in non-human primate food consumption behavior

Future-oriented behavior is regarded as a cornerstone of human cognition. One key phenomenon through which future orientation can be studied is the delay of gratification, when consumption of an immediate reward is withstood to achieve a larger reward later. The delays used in animal delay of gratification paradigms are rather short to be considered relevant for studying human-like future orientation. Here, for the first time, we show that rhesus macaques exhibit human-relevant future orientation downregulating their operant food consumption in anticipation of a nutritionally equivalent but more palatable food with an unprecedentedly long delay of approximately 2.5 h. Importantly, this behavior is not a result of conditioning but intrinsic to the animals. Our results show that the cognitive time horizon of primates, when tested in ecologically valid foraging-like experiments, extends much further into the future than previously considered, opening up new avenues for translational biomedical research.

Development of an assessment method for freely moving nonhuman primates' eating behavior using manual and deep learning analysis

Purpose

Although eating is imperative for survival, few comprehensive methods have been developed to assess freely moving nonhuman primates' eating behavior. In the current study, we distinguished eating behavior into appetitive and consummatory phases and developed nine indices to study them using manual and deep learning-based (DeepLabCut) techniques.

Method

The indices were utilized to three rhesus macaques by different palatability and hunger levels to validate their utility. To execute the experiment, we designed the eating behavior cage and manufactured the artificial food. The total number of trials was 3, with 1 trial conducted using natural food and 2 trials using artificial food.

Result

As a result, the indices of highest utility for hunger effect were approach frequency and consummatory duration. Appetitive composite score and consummatory duration showed the highest utility for palatability effect. To elucidate the effects of hunger and palatability, we developed 2D visualization plots based on manual indices. These 2D visualization methods could intuitively depict the palatability perception and hunger internal state. Furthermore, the developed deep learning-based analysis proved accurate and comparable with manual analysis. When comparing the time required for analysis, deep learning-based analysis was 24-times faster than manual analysis. Moreover, temporal and spatial dynamics were visualized via manual and deep learning-based analysis. Based on temporal dynamics analysis, the patterns were classified into four categories: early decline, steady decline, mid-peak with early incline, and late decline. Heatmap of spatial dynamics and trajectory-related visualization could elucidate a consumption posture and a higher spatial occupancy of food zone in hunger and with palatable food.

Discussion

Collectively, this study describes a newly developed and validated multi-phase method for assessing freely moving nonhuman primate eating behavior using manual and deep learning-based analyses. These effective tools will prove valuable in food reward (palatability effect) and homeostasis (hunger effect) research.

Human amygdala compared to orbitofrontal cortex connectivity, and emotion

The amygdala and orbitofrontal cortex have been implicated in emotion. To understand these regions better in humans, their effective connectivity with 360 cortical regions was measured in 171 humans from the Human Connectome Project, and complemented with functional connectivity and diffusion tractography. The human amygdala has effective connectivity from few cortical regions compared to the orbitofrontal cortex: primarily from auditory cortex A5 and the related superior temporal gyrus and temporal pole regions; the piriform (olfactory) cortex; the lateral orbitofrontal cortex 47m; somatosensory cortex; the hippocampus, entorhinal cortex, perirhinal cortex, and parahippocampal TF; and from the cholinergic nucleus basalis. The amygdala has effective connectivity to the hippocampus, entorhinal and perirhinal cortex; to the temporal pole; and to the lateral orbitofrontal cortex. The orbitofrontal cortex has effective connectivity from gustatory, olfactory, and temporal visual, auditory and pole cortex, and to the pregenual anterior and posterior cingulate cortex, hippocampal system, and prefrontal cortex, and provides for rewards and punishers to be used in reported emotions, and memory and navigation to goals. Given the paucity of amygdalo-neocortical connectivity in humans, it is proposed that the human amygdala is involved primarily in autonomic and conditioned responses via brainstem connectivity, rather than in reported (declarative) emotion.

Amygdala-cortical collaboration in reward learning and decision making

Adaptive reward-related decision making requires accurate prospective consideration of the specific outcome of each option and its current desirability. These mental simulations are informed by stored memories of the associative relationships that exist within an environment. In this review, I discuss recent investigations of the function of circuitry between the basolateral amygdala (BLA) and lateral (lOFC) and medial (mOFC) orbitofrontal cortex in the learning and use of associative reward memories. I draw conclusions from data collected using sophisticated behavioral approaches to diagnose the content of appetitive memory in combination with modern circuit dissection tools. I propose that, via their direct bidirectional connections, the BLA and OFC collaborate to help us encode detailed, outcome-specific, state-dependent reward memories and to use those memories to enable the predictions and inferences that support adaptive decision making. Whereas lOFC→BLA projections mediate the encoding of outcome-specific reward memories, mOFC→BLA projections regulate the ability to use these memories to inform reward pursuit decisions. BLA projections to lOFC and mOFC both contribute to using reward memories to guide decision making. The BLA→lOFC pathway mediates the ability to represent the identity of a specific predicted reward and the BLA→mOFC pathway facilitates understanding of the value of predicted events. Thus, I outline a neuronal circuit architecture for reward learning and decision making and provide new testable hypotheses as well as implications for both adaptive and maladaptive decision making.

A neuronal mechanism for motivational control of behavior

Acting to achieve goals depends on the ability to motivate specific behaviors based on their predicted consequences given an individual’s internal state. However, the underlying neuronal mechanisms that encode and maintain such specific motivational control of behavior are poorly understood. Here, we used Ca²⁺ imaging and optogenetic manipulations in the basolateral amygdala of freely moving mice performing noncued, self-paced instrumental goal-directed actions to receive and consume rewards. We found that distinct neuronal activity patterns sequentially represent the entire action-consumption behavioral sequence. Whereas action-associated patterns integrated the identity, value, and expectancy of pursued goals, consumption-associated patterns reflected the identity and value of experienced outcomes. Thus, the interplay between these patterns allows the maintenance of specific motivational states necessary to adaptively direct behavior toward prospective rewards.

Volume and Connectivity Differences in Brain Networks Associated with Cognitive Constructs of Binge Eating

Bulimia nervosa (BN) and binge eating disorder (BED) are characterized by episodes of eating large amounts of food while experiencing a loss of control. Recent studies suggest that the underlying causes of BN/BED consist of a complex system of environmental cues, atypical processing of food stimuli, altered behavioral responding, and structural/functional brain differences compared with healthy controls (HC). In this narrative review, we provide an integrative account of the brain networks associated with the three cognitive constructs most integral to BN and BED, namely increased reward sensitivity, decreased cognitive control, and altered negative affect and stress responding. We show altered activity in BED/BN within several brain networks, specifically in the striatum, insula, prefrontal cortex (PFC) and orbitofrontal cortex (OFC), and cingulate gyrus. Numerous key nodes in these networks also differ in volume and connectivity compared with HC. We provide suggestions for how this integration may guide future research into these brain networks and cognitive constructs.

Toward a holistic view of value and social processing in the amygdala: Insights from primate behavioral neurophysiology

Located medially within the temporal lobes, the amygdala is a formation of heterogenous nuclei that has emerged as a target for investigations into the neural bases of both primitive and complex behaviors. Although modern neuroscience has eschewed the practice of assigning broad functions to distinct brain regions, the amygdala has classically been associated with regulating negative emotional processes (such as fear or aggression), primarily through research performed in rodent models. Contemporary studies, particularly those in non-human primate models, have provided evidence for a role of the amygdala in other aspects of cognition such as valuation of stimuli or shaping social behaviors. Consequently, many modern perspectives now also emphasize the amygdala's role in processing positive affect and social behaviors. Importantly, several recent experiments have examined the intersection of two seemingly autonomous domains; how both valence/value and social stimuli are simultaneously represented in the amygdala. Results from these studies suggest that there is an overlap between valence/value processing and the processing of social behaviors at the level of single neurons. These findings have prompted researchers investigating the neurophysiological mechanisms underlying social interactions to question what contributions reward-related processes in the amygdala make in shaping social behaviors. In this review, we will examine evidence, primarily from primate neurophysiology, suggesting that value-related processes in the amygdala interact with the processing of social stimuli, and explore holistic hypotheses about how these amygdalar interactions might be instantiated.

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.

Movement errors during skilled motor performance engage distinct prediction error mechanisms

The brain detects deviations from intended behaviors by estimating the mismatch between predicted and actual outcomes. Axiomatic to these computations are salience and valence prediction error signals, which alert the brain to the occurrence and value of unexpected events. Despite the theoretical assertion of these prediction error signals, it is unknown whether and how brain mechanisms underlying their computations support error processing during skilled motor behavior. Here we demonstrate, with functional magnetic resonance imaging, that internal detection, i.e., without externally-provided feedback, of self-generated movement errors evokes instantaneous activity increases within the salience network and delayed lingering decreases within the nucleus accumbens - a key structure in the reward valuation pathway. A widespread suppression within the sensorimotor network was also observed. Our findings suggest that neural computations of salience and valence prediction errors during skilled motor behaviors operate on different time-scales and, therefore, may contribute differentially to immediate and longer-term adaptive processes.

From bed to bench side: Reverse translation to optimize neuromodulation for mood disorders

The advent of neuroimaging has provided foundational insights into the neural basis of psychiatric conditions, such as major depression. Across countless studies, dysfunction has been localized to distinct parts of the limbic system. Specific knowledge about affected locations has led to the development of circuit modulation therapies to correct dysfunction, notably deep brain stimulation (DBS). This and other emerging neuromodulation approaches have shown great promise, but their refinement has been slow and fundamental questions about their mechanisms of action remain. Here, we argue that their continued development requires reverse translation to animal models with close homology to humans, namely, nonhuman primates. With a particular focus on DBS approaches for depression, we highlight the parts of the brain that have been targeted by neuromodulation in humans, their efficacy, and why nonhuman primates are the most suitable model in which to conduct their refinement. We finish by highlighting key gaps in our knowledge that need to be filled to allow more rapid progress toward effective therapies in patients for whom all other treatment attempts have failed.

The contribution of nonhuman primate research to the understanding of emotion and cognition and its clinical relevance

Psychiatric disorders are often conceptualized as arising from dysfunctional interactions between neural systems mediating cognitive and emotional processes. Mechanistic insights into these interactions have been lacking in part because most work in emotions has occurred in rodents, often without concurrent manipulations of cognitive variables. Nonhuman primate (NHP) model systems provide a powerful platform for investigating interactions between cognitive operations and emotions due to NHPs' strong homology with humans in behavioral repertoire and brain anatomy. Recent electrophysiological studies in NHPs have delineated how neural signals in the amygdala, a brain structure linked to emotion, predict impending appetitive and aversive stimuli. In addition, abstract conceptual information has also been shown to be represented in the amygdala and in interconnected brain structures such as the hippocampus and prefrontal cortex. Flexible adjustments of emotional behavior require the ability to apply conceptual knowledge and generalize to different, often novel, situations, a hallmark example of interactions between cognitive and emotional processes. Elucidating the neural mechanisms that explain how the brain processes conceptual information in relation to emotional variables promises to provide important insights into the pathophysiology accounting for symptoms in neuropsychiatric disorders.

Multidimensional Neural Selectivity in the Primate Amygdala

The amygdala contributes to multiple functions including attention allocation, sensory processing, decision-making, and the elaboration of emotional behaviors. The diversity of functions attributed to the amygdala is reflected in the response selectivity of its component neurons. Previous work claimed that subsets of neurons differentiate between broad categories of stimuli (e.g., objects vs faces, rewards vs punishment), while other subsets are narrowly specialized to respond to individual faces or facial features (e.g., eyes). Here we explored the extent to which the same neurons contribute to more than one neural subpopulation in a task that activated multiple functions of the amygdala. The subjects (Macaca mulatta) watched videos depicting conspecifics or inanimate objects, and learned by trial and error to choose the individuals or objects associated with the highest rewards. We found that the same neurons responded selectively to two or more of the following task events or stimulus features: (1) alerting, task-related stimuli (fixation icon, video start, and video end); (2) reward magnitude; (3) stimulus categories (social vs nonsocial); and (4) stimulus-unique features (faces, eyes). A disproportionate number of neurons showed selectivity for all of the examined stimulus features and task events. These results suggest that neurons that appear specialized and uniquely tuned to specific stimuli (e.g., face cells, eye cells) are likely to respond to multiple other types of stimuli or behavioral events, if/when these become behaviorally relevant in the context of a complex task. This multidimensional selectivity supports a flexible, context-dependent evaluation of inputs and subsequent decision making based on the activity of the same neural ensemble.

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.

Four Social Brain Regions, Their Dysfunctions, and Sequelae, Extensively Explain Autism Spectrum Disorder Symptomatology

Autism spectrum disorder (ASD) is a challenging neurodevelopmental disorder with symptoms in social, language, sensory, motor, cognitive, emotional, repetitive behavior, and self-sufficient living domains. The important research question examined is the elucidation of the pathogenic neurocircuitry that underlies ASD symptomatology in all its richness and heterogeneity. The presented model builds on earlier social brain research, and hypothesizes that four social brain regions largely drive ASD symptomatology: amygdala, orbitofrontal cortex (OFC), temporoparietal cortex (TPC), and insula. The amygdala's contributions to ASD largely derive from its major involvement in fine-grained intangible knowledge representations and high-level guidance of gaze. In addition, disrupted brain regions can drive disturbance of strongly interconnected brain regions to produce further symptoms. These and related effects are proposed to underlie abnormalities of the visual cortex, inferior frontal gyrus (IFG), caudate nucleus, and hippocampus as well as associated symptoms. The model is supported by neuroimaging, neuropsychological, neuroanatomical, cellular, physiological, and behavioral evidence. Collectively, the model proposes a novel, parsimonious, and empirically testable account of the pathogenic neurocircuitry of ASD, an extensive account of its symptomatology, a novel physiological biomarker with potential for earlier diagnosis, and novel experiments to further elucidate the mechanisms of brain abnormalities and symptomatology in ASD.

What, If, and When to Move: Basal Ganglia Circuits and Self-Paced Action Initiation

Deciding what to do and when to move is vital to our survival. Clinical and fundamental studies have identified basal ganglia circuits as critical for this process. The main input nucleus of the basal ganglia, the striatum, receives inputs from frontal, sensory, and motor cortices and interconnected thalamic areas that provide information about potential goals, context, and actions and directly or indirectly modulates basal ganglia outputs. The striatum also receives dopaminergic inputs that can signal reward prediction errors and also behavioral transitions and movement initiation. Here we review studies and models of how direct and indirect pathways can modulate basal ganglia outputs to facilitate movement initiation, and we discuss the role of cortical and dopaminergic inputs to the striatum in determining what to do and if and when to do it. Complex but exciting scenarios emerge that shed new light on how basal ganglia circuits modulate self-paced movement initiation.

Distinct cortical-amygdala projections drive reward value encoding and retrieval

The value of an anticipated rewarding event is a crucial component of the decision to engage in its pursuit. But little is known of the networks responsible for encoding and retrieving this value. By using biosensors and pharmacological manipulations, we found that basolateral amygdala (BLA) glutamatergic activity tracks and mediates encoding and retrieval of the state-dependent incentive value of a palatable food reward. Projection-specific, bidirectional chemogenetic and optogenetic manipulations revealed that the orbitofrontal cortex (OFC) supports the BLA in these processes. Critically, the function of ventrolateral and medial OFC→BLA projections is doubly dissociable. Whereas lateral OFC→BLA projections are necessary and sufficient for encoding of the positive value of a reward, medial OFC→BLA projections are necessary and sufficient for retrieving this value from memory. These data reveal a new circuit for adaptive reward valuation and pursuit and provide insight into the dysfunction in these processes that characterizes myriad psychiatric diseases.

Amygdala Represents Diverse Forms of Intangible Knowledge, That Illuminate Social Processing and Major Clinical Disorders

Amygdala is an intensively researched brain structure involved in social processing and multiple major clinical disorders, but its functions are not well understood. The functions of a brain structure are best hypothesized on the basis of neuroanatomical connectivity findings, and of behavioral, neuroimaging, neuropsychological and physiological findings. Among the heaviest neuroanatomical interconnections of amygdala are those with perirhinal cortex (PRC), but these are little considered in the theoretical literature. PRC integrates complex, multimodal, meaningful and fine-grained distributed representations of objects and conspecifics. Consistent with this connectivity, amygdala is hypothesized to contribute meaningful and fine-grained representations of intangible knowledge for integration by PRC. Behavioral, neuroimaging, neuropsychological and physiological findings further support amygdala mediation of a diversity of such representations. These representations include subjective valence, impact, economic value, noxiousness, importance, ingroup membership, social status, popularity, trustworthiness and moral features. Further, the formation of amygdala representations is little understood, and is proposed to be often implemented through embodied cognition mechanisms. The hypothesis builds on earlier work, and makes multiple novel contributions to the literature. It highlights intangible knowledge, which is an influential but insufficiently researched factor in social and other behaviors. It contributes to understanding the heavy but neglected amygdala-PRC interconnections, and the diversity of amygdala-mediated intangible knowledge representations. Amygdala is a social brain region, but it does not represent species-typical social behaviors. A novel proposal to clarify its role is postulated. The hypothesis is also suggested to illuminate amygdala's involvement in several core symptoms of autism spectrum disorder (ASD). Specifically, novel and testable explanations are proposed for the ASD symptoms of disorganized visual scanpaths, apparent social disinterest, preference for concrete cognition, aspects of the disorder's heterogeneity, and impairment in some activities of daily living. Together, the presented hypothesis demonstrates substantial explanatory potential in the neuroscience, social and clinical domains.

Amygdala activity for the modulation of goal-directed behavior in emotional contexts

Choosing valuable objects and rewarding actions is critical for survival. While such choices must be made in a way that suits the animal’s circumstances, the neural mechanisms underlying such context-appropriate behavior are unclear. To address this question, we devised a context-dependent reward-seeking task for macaque monkeys. Each trial started with the appearance of one of many visual scenes containing two or more objects, and the monkey had to choose the good object by saccade to get a reward. These scenes were categorized into two dimensions of emotional context: dangerous versus safe and rich versus poor. We found that many amygdala neurons were more strongly activated by dangerous scenes, by rich scenes, or by both. Furthermore, saccades to target objects occurred more quickly in dangerous than in safe scenes and were also quicker in rich than in poor scenes. Thus, amygdala neuronal activity and saccadic reaction times were negatively correlated in each monkey. These results suggest that amygdala neurons facilitate targeting saccades predictably based on aspects of emotional context, as is necessary for goal-directed and social behavior.

The amygdala is known to control passive fear responses (e.g., freezing), but it is unclear if it also contributes to active behaviors. To reach certain goals, we (humans and animals) often need to go through fearful environments. We hypothesized that the amygdala contributes to such an active behavior and devised a new foraging task for macaque monkeys in which various emotional contexts changed across many environments. This “exciting” task provoked extremely fast learning and high-capacity memory of objects and environments, and thereby caused extremely fast goal-directed behaviors. We found that the goal-directed behavior was affected by the emotional context in two dimensions (dangerous–safe and rich–poor) separately from the object values. Then, many neurons in the amygdala responded to the environments before any object appeared and did so selectively, depending on the emotional context of the environment. The neuronal activity was tightly correlated with the reaction time of goal-directed behavior across the contexts: faster behavior in dangerous or rich context. These results suggest that the amygdala facilitates goal-directed behavior by focusing on emotional contexts. Such a function is also important for emotional–social behavior and its disorder, including averted eye gaze in autism.

Neural encoding of choice during a delayed response task in primate striatum and orbitofrontal cortex

Reward outcomes are available in many diverse situations and all involve choice. If there are multiple outcomes each rewarding, then decisions regarding relative value lead to choosing one over another. Important factors related to choice context should be encoded and utilized for this form of adaptive choosing. These factors can include the number of alternatives, the pacing of choice behavior and the possibility to reverse one's choice. An essential step in understanding if the context of choice is encoded is to directly compare choice with a context in which choice is absent. Neural activity in orbitofrontal cortex and striatum encodes potential value parameters related to reward quality and quantity as well as relative preference. We examined how neural activations in these brain regions are sensitive to choice situations and potentially involved in a prediction for the upcoming outcome selection. Neural activity was recorded and compared between a two-choice spatial delayed response task and an imperative 'one-option' task. Neural activity was obtained that extended from the instruction cue to the movement similar to previous work utilizing the identical imperative task. Orbitofrontal and striatal neural responses depended upon the decision about the choice of which reward to collect. Moreover, signals to predictive instruction cues that precede choice were selective for the choice situation. These neural responses could reflect chosen value with greater information on relative value of individual options as well as encode choice context itself embedded in the task as a part of the post-decision variable.

Free choice shapes normalized value signals in medial orbitofrontal cortex

Normalization is a common cortical computation widely observed in sensory perception, but its importance in perception of reward value and decision making remains largely unknown. We examined (1) whether normalized value signals occur in the orbitofrontal cortex (OFC) and (2) whether changes in behavioral task context influence the normalized representation of value. We record medial OFC (mOFC) single neuron activity in awake-behaving monkeys during a reward-guided lottery task. mOFC neurons signal the relative values of options via a divisive normalization function when animals freely choose between alternatives. The normalization model, however, performed poorly in a variant of the task where only one of the two possible choice options yields a reward and the other was certain not to yield a reward (so called: “forced choice”). The existence of such context-specific value normalization may suggest that the mOFC contributes valuation signals critical for economic decision making when meaningful alternative options are available.

Neurons in prefrontal areas including the medial orbitofrontal cortex (mOFC) represent the relative reward value of choices. Here the authors report that mOFC neurons implement divisive normalization to encode the relative values of lottery options only when the decision involves free choice.

Optogenetic Inhibition Reveals Distinct Roles for Basolateral Amygdala Activity at Discrete Time Points during Risky Decision Making

Decision making is a multifaceted process, consisting of several distinct phases that likely require different cognitive operations. Previous work showed that the basolateral amygdala (BLA) is a critical substrate for decision making involving risk of punishment; however, it is unclear how the BLA is recruited at different stages of the decision process. To this end, the current study used optogenetics to inhibit the BLA during specific task phases in a model of risky decision making (risky decision-making task) in which rats choose between a small, "safe" reward and a large reward accompanied by varying probabilities of footshock punishment. Male Long-Evans rats received intra-BLA microinjections of viral vectors carrying either halorhodopsin (eNpHR3.0-mCherry) or mCherry alone (control) followed by optic fiber implants and were trained in the risky decision-making task. Laser delivery during the task occurred during intertrial interval, deliberation, or reward outcome phases, the latter of which was further divided into the three possible outcomes (small, safe; large, unpunished; large, punished). Inhibition of the BLA selectively during the deliberation phase decreased choice of the large, risky outcome (decreased risky choice). In contrast, BLA inhibition selectively during delivery of the large, punished outcome increased risky choice. Inhibition had no effect during the other phases, nor did laser delivery affect performance in control rats. Collectively, these data indicate that the BLA can either inhibit or promote choice of risky options, depending on the phase of the decision process in which it is active.SIGNIFICANCE STATEMENT To date, most behavioral neuroscience research on neural mechanisms of decision making has used techniques that preclude assessment of distinct phases of the decision process. Here we show that optogenetic inhibition of the BLA has opposite effects on choice behavior in a rat model of risky decision making, depending on the phase in which inhibition occurs. BLA inhibition during a period of deliberation between small, safe and large, risky outcomes decreased risky choice. In contrast, BLA inhibition during receipt of the large, punished outcome increased risky choice. These findings highlight the importance of temporally targeted approaches to understand neural substrates underlying complex cognitive processes. More importantly, they reveal novel information about dynamic BLA modulation of risky choice.

In monkeys making value-based decisions, amygdala neurons are sensitive to cue value as distinct from cue salience

Neurons in the lateral intraparietal (LIP) area of macaque monkey parietal cortex respond to cues predicting rewards and penalties of variable size in a manner that depends on the motivational salience of the predicted outcome (strong for both large reward and large penalty) rather than on its value (positive for large reward and negative for large penalty). This finding suggests that LIP mediates the capture of attention by salient events and does not encode value in the service of value-based decision making. It leaves open the question whether neurons elsewhere in the brain encode value in the identical task. To resolve this issue, we recorded neuronal activity in the amygdala in the context of the task employed in the LIP study. We found that responses to reward-predicting cues were similar between areas, with the majority of reward-sensitive neurons responding more strongly to cues that predicted large reward than to those that predicted small reward. Responses to penalty-predicting cues were, however, markedly different. In the amygdala, unlike LIP, few neurons were sensitive to penalty size, few penalty-sensitive neurons favored large over small penalty, and the dependence of firing rate on penalty size was negatively correlated with its dependence on reward size. These results indicate that amygdala neurons encoded cue value under circumstances in which LIP neurons exhibited sensitivity to motivational salience. However, the representation of negative value, as reflected in sensitivity to penalty size, was weaker than the representation of positive value, as reflected in sensitivity to reward size.NEW & NOTEWORTHY This is the first study to characterize amygdala neuronal responses to cues predicting rewards and penalties of variable size in monkeys making value-based choices. Manipulating reward and penalty size allowed distinguishing activity dependent on motivational salience from activity dependent on value. This approach revealed in a previous study that neurons of the lateral intraparietal (LIP) area encode motivational salience. Here, it reveals that amygdala neurons encode value. The results establish a sharp functional distinction between the two areas.

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.

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Neural activity was measured during planning and execution of economic saving

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Amygdala activity predicted the planned number of saving steps and their value

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Amygdala-frontal circuits coded plan components and individual saving differences

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The results suggest a new function for the human amygdala in economic planning

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.

DOI:http://dx.doi.org/10.7554/eLife.18731.001

Amygdala and Ventral Striatum Make Distinct Contributions to Reinforcement Learning

Reinforcement learning (RL) theories posit that dopaminergic signals are integrated within the striatum to associate choices with outcomes. Often overlooked is that the amygdala also receives dopaminergic input and is involved in Pavlovian processes that influence choice behavior. To determine the relative contributions of the ventral striatum (VS) and amygdala to appetitive RL, we tested rhesus macaques with VS or amygdala lesions on deterministic and stochastic versions of a two-arm bandit reversal learning task. When learning was characterized with an RL model relative to controls, amygdala lesions caused general decreases in learning from positive feedback and choice consistency. By comparison, VS lesions only affected learning in the stochastic task. Moreover, the VS lesions hastened the monkeys' choice reaction times, which emphasized a speed-accuracy trade-off that accounted for errors in deterministic learning. These results update standard accounts of RL by emphasizing distinct contributions of the amygdala and VS to RL.

Neural mechanisms of social decision-making in the primate amygdala

Social decisions require evaluation of costs and benefits to oneself and others. Long associated with emotion and vigilance, the amygdala has recently been implicated in both decision-making and social behavior. The amygdala signals reward and punishment, as well as facial expressions and the gaze of others. Amygdala damage impairs social interactions, and the social neuropeptide oxytocin (OT) influences human social decisions, in part, by altering amygdala function. Here we show in monkeys playing a modified dictator game, in which one individual can donate or withhold rewards from another, that basolateral amygdala (BLA) neurons signaled social preferences both across trials and across days. BLA neurons mirrored the value of rewards delivered to self and others when monkeys were free to choose but not when the computer made choices for them. We also found that focal infusion of OT unilaterally into BLA weakly but significantly increased both the frequency of prosocial decisions and attention to recipients for context-specific prosocial decisions, endorsing the hypothesis that OT regulates social behavior, in part, via amygdala neuromodulation. Our findings demonstrate both neurophysiological and neuroendocrinological connections between primate amygdala and social decisions.

It All Depends on the Context, but Also on the Amygdala

Behavioral flexibility requires the brain to maintain and rely on cognitive contexts for dictating appropriate responses. Saez et al. (2015) demonstrate that such abstract rule-based representations co-exist in prefrontal cortices and in the amygdala, with the latter being surprisingly crucial for correct performance.

The basolateral amygdala in reward learning and addiction

Sophisticated behavioral paradigms partnered with the emergence of increasingly selective techniques to target the basolateral amygdala (BLA) have resulted in an enhanced understanding of the role of this nucleus in learning and using reward information. Due to the wide variety of behavioral approaches many questions remain on the circumscribed role of BLA in appetitive behavior. In this review, we integrate conclusions of BLA function in reward-related behavior using traditional interference techniques (lesion, pharmacological inactivation) with those using newer methodological approaches in experimental animals that allow in vivo manipulation of cell type-specific populations and neural recordings. Secondly, from a review of appetitive behavioral tasks in rodents and monkeys and recent computational models of reward procurement, we derive evidence for BLA as a neural integrator of reward value, history, and cost parameters. Taken together, BLA codes specific and temporally dynamic outcome representations in a distributed network to orchestrate adaptive responses. We provide evidence that experiences with opiates and psychostimulants alter these outcome representations in BLA, resulting in long-term modified action.

Basolateral amygdala rapid glutamate release encodes an outcome-specific representation vital for reward-predictive cues to selectively invigorate reward-seeking actions

Environmental stimuli have the ability to generate specific representations of the rewards they predict and in so doing alter the selection and performance of reward-seeking actions. The basolateral amygdala participates in this process, but precisely how is unknown. To rectify this, we monitored, in near-real time, basolateral amygdala glutamate concentration changes during a test of the ability of reward-predictive cues to influence reward-seeking actions (Pavlovian-instrumental transfer). Glutamate concentration was found to be transiently elevated around instrumental reward seeking. During the Pavlovian-instrumental transfer test these glutamate transients were time-locked to and correlated with only those actions invigorated by outcome-specific motivational information provided by the reward-predictive stimulus (i.e., actions earning the same specific outcome as predicted by the presented CS). In addition, basolateral amygdala AMPA, but not NMDA glutamate receptor inactivation abolished the selective excitatory influence of reward-predictive cues over reward seeking. These data support [corrected] the hypothesis that transient glutamate release in the BLA can encode the outcome-specific motivational information provided by reward-predictive stimuli.