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Functions of primate amygdala neurons in economic decisions and social decision simulation
Abstract
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.
... However, single-unit recording work in primates and rodents have shown that these regions play a much broader role in cognition relevant to ED and ID shifting. The amygdala has been shown to code reward, learning, attention, novelty, value-based decision-making, and task set representation [8][9][10][11][12][13][14] . This has led to the idea of the amygdala as a multidimensional processor that integrates cognitive and emotional functions by way of its interactions with the extensive number of regions it has anatomical connections to, including PFC 15,16 . ...
... Such slower oscillations may reflect the maintenance of the correct rule in working memory over several trials 45,46 . This working memory representation may be necessary for the decision-making process which has also been shown to involve the amygdala 10 . The long duration effect is also consistent with the theory that the amygdala is involved in coding reward contingencies over long time periods 9 . ...
... Several other types of signals were also found. Delta/theta activity was larger in the amygdala and hippocampus throughout no shift trials relative to shift trials which may also reflect working memory for the correct rule 43,45,46 in service of decision-making 10 . It would be interesting to know what type of representation is being maintained. ...
Adaptive behavior requires the ability to shift responding within (intra-dimensional) or between (extra-dimensional) stimulus dimensions when reward contingencies change. Studies of shifting in humans have focused mainly on the prefrontal cortex and/ or have been restricted to indirect measures of neural activity such as fMRI and lesions. Here, we demonstrate the importance of the amygdala and hippocampus by recording local field potentials directly from these regions intracranially in human epilepsy patients. Reward signals were coded in the high frequency gamma activity (HFG; 60-250 Hz) of both regions and synchronised via low frequency (3-5 Hz) phase-locking only after a shift when patients did not already know the rule and it signalled to stop shifting (“Win-Stay”). In contrast, HFG punishment signals were only seen in the amygdala when the rule then changed and it signalled to start shifting (“Lose-Shift”). During decision-making, hippocampal HFG was more inhibited on non-shift relative to shift trials, suggesting a role in preventing interference in rule representation and amygdala HFG was sensitive to stimulus novelty. The findings expand our understanding of human amygdala-hippocampal function and shifting processes, the disruption of which could contribute to shifting deficits in neuropsychiatric disorders.
... As a core hub in subcortical regions, the amygdala strongly project to the prefrontal cortex (PFC) and also receive substantial projections from the PFC [21,22]. The bidirectional communications between the amygdala and the PFC have been found in modulating multiple complex behaviors, such as decision making and social activity [22,23]. For instance, previous study has reported that the medial PFC-amygdala functional connectivity was positively associated with risk-tolerance in valuebased decision making task [3]. ...
... The MoCA is a widely used screening tool for assessing global cognitive ability, showing high sensitivity in detecting cognitive impairment [37,38]. In order to examine the effect of cognitive decline on risky decision-making, the current analysis included older adults with an extensive range of MoCA (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) and MMSE (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29), and individuals with lower scores of neurocognitive assessments were not excluded. Therefore, it allowed for testing risk-taking behaviors and corresponding neural correlates in cognitively normal and declined older adults. ...
... The MoCA is a widely used screening tool for assessing global cognitive ability, showing high sensitivity in detecting cognitive impairment [37,38]. In order to examine the effect of cognitive decline on risky decision-making, the current analysis included older adults with an extensive range of MoCA (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) and MMSE (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29), and individuals with lower scores of neurocognitive assessments were not excluded. Therefore, it allowed for testing risk-taking behaviors and corresponding neural correlates in cognitively normal and declined older adults. ...
Older adults often have difficulty in making decisions under uncertainty, increasing the risk of financial exploitation. However, it is still under investigation about the extent to which cognitive decline influences risky decision-making and the underlying neural correlates. We hypothesized that the individual differences of risk-taking behavior depend on cognitive integrity, in which the dorsal and ventral fronto-amygdala connectivity would play dissociable roles. In the current study, thirty-six young and 51 older adults were tested with the Iowa gambling task combing resting-state and task-related functional magnetic resonance imaging. The results showed significant changes in behaviors and the fronto-amygdala network in older adults relative to young adults. More importantly, age-effect on risk-taking behaviors was remarkably different in cognitively normal and impaired older adults. In resting-state analysis, task performance was positively correlated with the ventral fronto-amygdala connectivity and negatively correlated with the dorsal fronto-amygdala connectivity in cognitively impaired older adults, compared with cognitively normal individuals. Furthermore, task-related analysis confirmed the relationships between dorsal/ventral fronto-amygdala network and risk-taking behaviors depending on cognitive integrity. These findings indicate that the fronto-amygdala network is crucial for understanding altered risky decision-making in aging, suggesting dissociable contributions of the dorsal and ventral pathways in the context of cognitive decline.
... The amygdala, a cell complex located in the anterior-medial temporal lobe ( Figure 1A), has long been associated with mediating emotional reactions to sensory cues (Rolls, 2000;Baxter and Murray, 2002;Cardinal et al., 2002;Maren and Quirk, 2004;Balleine and Killcross, 2006;Murray, 2007;Ghods-Sharifi et al., 2009;Morrison and Salzman, 2010;Johansen et al., 2011;Janak and Tye, 2015;Gothard, 2020;Pujara et al., 2022). However, recent findings also implicate primate amygdala neurons in more complex cognitive functions, including the pursuit of future rewards through economic, value-based decision-making and planning (Grabenhorst et al., 2012;Hernadi et al., 2015;Grabenhorst et al., 2016;Grabenhorst et al., 2019;Grabenhorst and Schultz, 2021;Grabenhorst et al., 2023). ...
... Its extrinsic and elaborate intrinsic connections (Pitkanen et al., 1997;Pitkanen and Amaral, 1998) enable the amygdala to process the value of sensory stimuli based on learned stimulus-reinforcer associations, and integrate this information with current contexts, memories, and internal states to regulate emotion, attention, memory, physiological and behavioral responses (Rolls, 2000;Paton et al., 2006;Murray, 2007;Johansen et al., 2011;Duvarci and Pare, 2014;Saez et al., 2015;Gothard, 2020;Grabenhorst and Schultz, 2021). The amygdala is a complex structure composed of different subregions with many different cell types. ...
The successful pursuit of future rewards requires forming an internal goal, followed by planning, decision-making, and progress-tracking over multiple steps. The initial step—forming goals and the plans for obtaining them—involves the subjective valuation of an anticipated reward, considering both the reward’s properties and associated delay and physical-effort costs. Recent findings indicate individuals similarly evaluate cognitive effort over time (Johnson and Most, 2023). Success and failure in these processes have been linked to differential life outcomes and psychiatric conditions. Here we review evidence from single-neuron recordings and neuroimaging studies that implicate the amygdala—a brain structure long associated with cue-reactivity and emotion—in decision-making and the planned pursuit of future rewards (Grabenhorst et al., 2012, 2016, 2019, 2023;Hernadi et al., 2015;Zangemeister et al., 2016). The main findings are that, in behavioral tasks in which future rewards can be pursued through planning and stepwise decision-making, amygdala neurons prospectively encode the value of anticipated rewards and related behavioral plans. Moreover, amygdala neurons predict the stepwise choices to pursue these rewards, signal progress toward goals, and distinguish internally generated (i.e., self-determined) choices from externally imposed actions. Importantly, amygdala neurons integrate the subjective value of a future reward with delay and effort costs inherent in pursuing it. This neural evidence identifies three key computations of the primate amygdala that underlie the pursuit of future rewards: (1) forming a self-determined internal goal based on subjective reward-cost valuations, (2) defining a behavioral plan for obtaining the goal, (3) executing this plan through stepwise decision-making and progress-tracking. Based on this framework, we suggest that amygdala neurons constitute vulnerabilities for dysfunction that contribute to maladaptive reward pursuit in psychiatric and behavioral conditions. Consequently, amygdala neurons may also represent potential targets for behavioral-change interventions that aim to improve individual decision-making.
... process these inputs (Tobler et al., 2008;Genevsky et al., 2017). We note that although the amygdala has traditionally been associated with processing negative outcomes, substantial evidence across species implicates the amygdala in processing reward (Paton et al., 2006;Grabenhorst and Schultz, 2021). The present results suggest that the amygdala's functions in reward processing extend to processing the variance-risk associated with the distribution of social reward outcomes. ...
Risk is a fundamental factor affecting individual and social economic decisions, but its neural correlates are largely unexplored in the social domain. The amygdala, together with the dorsal anterior cingulate cortex (dACC), is thought to play a central role in risk-taking. Here, we investigated in human volunteers ( n = 20; 11 females) how risk (defined as the variance of reward probability distributions) in a social situation affects decisions and concomitant neural activity as measured with fMRI. We found separate variance-risk signals for social and nonsocial outcomes in the amygdala. Specifically, amygdala activity increased parametrically with social reward variance of presented choice options and on separate trials with nonsocial reward variance. Behaviorally, 75% of participants were averse to social risk as estimated in a Becker–DeGroot–Marschak auction-like procedure. The stronger this aversion, the more negative the coupling between risk-related amygdala regions and dACC. This negative relation was significant for social risk attitude but not for the attitude toward variance-risk in juice outcomes. Our results indicate that the amygdala and its coupling with dACC process objective and subjectively evaluated social risk. Moreover, while social risk can be captured with a framework originally established by finance theory for nonsocial risk, the amygdala appears to process social risk largely separately from nonsocial risk.
... (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) information processed within the LB subdivision associated with choices, value and rewards evaluation in both social and non-social contexts coded in abstract conceptual format (Gupta et al., 2011;Wellman et al., 2016;O'Neill et al., 2018;Grabenhorst et al., 2019;Dal Monte et al., 2020;Elorette et al., 2020;Jezzini and Padoa-Schioppa, 2020;Grabenhorst and Schultz, 2021;Dal Monte et al., 2022). For instance, the level of complexity in the social network enhances the strength of connectivity between vmPFC and LB (Bickart et al., 2012). ...
The network formed by the amygdala (AMG) and the medial Prefrontal Cortex (mPFC), at the interface between our internal and external environment, has been shown to support some important aspects of behavioral adaptation. Whether and how the anatomo-functional organization of this network evolved across primates remains unclear. Here, we compared AMG nuclei morphological characteristics and their functional connectivity with the mPFC in humans and macaques to identify potential homologies and differences between these species. Based on selected studies, we highlight two subsystems within the AMG-mPFC circuits, likely involved in distinct temporal dynamics of integration during behavioral adaptation. We also show that whereas the mPFC displays a large expansion but a preserved intrinsic anatomo-functional organization, the AMG displays a volume reduction and morphological changes related to specific nuclei. We discuss potential commonalities and differences in the dialogue between AMG nuclei and mPFC in humans and macaques based on available data.
... The amygdala is also heavily interconnected with OFC (Carmichael & Price, 1995;Ghashghaei et al., 2007;Price, 2007), and found to be involved in the similar processes as OFC. Lesions to either OFC or basolateral amygdala (BLA) impair reinforcer devaluation (Baxter et al., 2000;Ostlund & Balleine, 2008;Pickens et al., 2003;Rhodes & Murray, 2013;Wellman et al., 2005)., indicating their causal function in updating subjective values (Grabenhorst & Schultz, 2021) or representing abstract task structures (Gothard, 2020). Under social behavioral contexts, the amygdala has been found to encode a variety of social variables including social cues (Bergan et al., 2014) and social values (Grabenhorst et al., 2019;Munuera et al., 2018) involved in learning and decision-making. ...
The orbitofrontal cortex (OFC) is regarded as one of the core brain areas in a variety of value-based behaviors. Over the past two decades, tremendous knowledge about the OFC function was gained from studying the behaviors of single subjects. As a result, our previous understanding of the OFC's function of encoding decision variables, such as the value and identity of choices, has evolved to the idea that the OFC encodes a more complex representation of the task space as a cognitive map. Accumulating evidence also indicates that the OFC importantly contributes to behaviors in social contexts, especially those involved in cooperative interactions. However, it remains elusive how exactly OFC neurons contribute to social functions and how non-social and social behaviors are related to one another in the computations performed by OFC neurons. In this review, we aim to provide an integrated view of the OFC function across both social and non-social behavioral contexts. We propose that seemingly complex functions of the OFC may be explained by its role in providing a goal-directed cognitive map to guide a wide array of adaptive reward-based behaviors in both social and non-social domains.
... Although as described further below the amygdala may be overshadowed in humans by the orbitofrontal cortex, which has connectivity with the amygdala and that could influence amygdala neuronal responses, it is of interest that (Glasser et al. 2016a;Huang et al. 2022). The abbreviations are provided elsewhere Rolls et al. 2023a) in macaques, some amygdala neurons not only respond to faces (Leonard et al. 1985), but also respond to socially relevant stimuli when macaques interact socially (Grabenhorst et al. 2019;Grabenhorst and Schultz 2021). ...
The orbitofrontal cortex and amygdala are involved in emotion and in motivation, but the relationship between these functions performed by these brain structures is not clear. To address this, a unified theory of emotion and motivation is described in which motivational states are states in which instrumental goal-directed actions are performed to obtain rewards or avoid punishers, and emotional states are states that are elicited when the reward or punisher is or is not received. This greatly simplifies our understanding of emotion and motivation, for the same set of genes and associated brain systems can define the primary or unlearned rewards and punishers such as sweet taste or pain. Recent evidence on the connectivity of human brain systems involved in emotion and motivation indicates that the orbitofrontal cortex is involved in reward value and experienced emotion with outputs to cortical regions including those involved in language, and is a key brain region involved in depression and the associated changes in motivation. The amygdala has weak effective connectivity back to the cortex in humans, and is implicated in brainstem-mediated responses to stimuli such as freezing and autonomic activity, rather than in declarative emotion. The anterior cingulate cortex is involved in learning actions to obtain rewards, and with the orbitofrontal cortex and ventromedial prefrontal cortex in providing the goals for navigation and in reward-related effects on memory consolidation mediated partly via the cholinergic system.
... In other words, the cognitive operations underlying this type of information search might occur both in social and in non-social scenarios. Therefore, by comparing information sampling from social versus non-social sources, we address a long-standing question in cognitive neuroscience, the degree to which any neural process is specialized for, or particularly linked to, social as opposed to non-social cognition (Chang and Dal Monte, 2018;Diaconescu et al., 2017;Frith and Frith, 2010;Frith and Frith, 2012;Grabenhorst and Schultz, 2021;Lockwood et al., 2020a;Lockwood et al., 2018;Soutschek et al., 2016;Wittmann et al., 2018;Rushworth et al., 2012). eLife digest People's decisions are influenced by their beliefs, which may be based on advice from other humans or, alternatively, on information from non-human sources such as road signs. ...
Humans learn about the environment either directly by interacting with it or indirectly by seeking information about it from social sources such as conspecifics. The degree of confidence in the information obtained through either route should determine the impact that it has on adapting and changing behaviour. We examined whether and how behavioural and neural computations differ during non-social learning as opposed to learning from social sources. Trial-wise confidence judgements about non-social and social information sources offered a window into this learning process. Despite matching exactly the statistical features of social and non-social conditions, confidence judgements were more accurate and less changeable when they were made about social as opposed to non-social information sources. In addition to subjective reports of confidence, differences were also apparent in the Bayesian estimates of participants’ subjective beliefs. Univariate activity in dorsomedial prefrontal cortex and posterior temporoparietal junction more closely tracked confidence about social as opposed to non-social information sources. In addition, the multivariate patterns of activity in the same areas encoded identities of social information sources compared to non-social information sources.
For better decisions in social interactions, humans often must understand the thinking of others and predict their actions. Since such predictions are uncertain, multiple predictions may be necessary for better decision-making. However, the neural processes and computations underlying such social decision-making remain unclear. We investigated this issue by developing a behavioral paradigm and performing functional magnetic resonance imaging and computational modeling. In our task, female and male participants were required to predict others’ choices in order to make their own value-based decisions, as the outcome depended on others’ choices. Results showed, to make choices, the participants mostly relied on a value difference (primary) generated from the case where others would make a likely choice, but sometimes they additionally used another value difference (secondary) from the opposite case where others make an unlikely choice. We found that the activations in the posterior cingulate cortex (PCC) correlated with the primary difference while the activations in the right dorsolateral prefrontal cortex (rdlPFC) correlated with the secondary difference. Analysis of neural coupling and temporal dynamics suggested a three-step processing network, beginning with the left amygdala signals for predictions of others’ choices. Modulated by these signals, the PCC and rdlPFC reflect the respective value differences for self-decisions. Finally, the medial prefrontal cortex integrated these decision signals for a final decision. Our findings elucidate the neural process of constructing value-based decisions by predicting others and illuminate their key variables with social modulations, providing insight into the differential functional roles of these brain regions in this process.
Decision-making is influenced by both expected reward and social factors, such as who offered the outcomes. Thus, although a reward might originally be independent from social factors, the two elements are closely related. However, whether and how they are processed separately or conjointly remains unclear. Here, we show that neurons in distinct sub-nuclei of the amygdala encode expected reward and face animacy, which is a vital aspect of face perception. Although these encoding processes are distinct, they rely on partially shared neuronal circuits with characteristic temporal dynamics.
Two male macaque monkeys made saccades under different social and reward contexts, created by presenting facial images with independent attributes: animacy (a monkey or cartoon face) and associated reward (large or small). The stimulus image was presented twice per trial: during the initial stimulus encoding (S1) and before saccades were made (S2). A longer gaze duration for eye region of the monkey versus cartoon images indicated more robust social engagement for realistic faces. During S1, a similar number of lateral nucleus neurons encoded either animacy only with a monkey-image preference, reward only with a large-reward preference, or both. Conversely, neurons in the basal and central nuclei primarily encoded reward, preferring large-versus small-reward associated face images. The reward-dependent modulation was continuous after S1, but was more conspicuous during S1 in the basal nucleus and during both S1 and S2 in the central nucleus. This anatomically- and temporally-specific encoding in the amygdala may underlie the computation and integration of face animacy and reward information.
Significance Statement
Reward and social information are closely related but originally independent, as both influence our decision-making. The amygdala has been associated with both reward and social information coding. However, whether and how they are processed separately or conjointly by individual neurons in the amygdala remains unclear.
We found that neurons in the lateral and basal nuclei encoded face animacy, which is an important aspect of social information, and reward, respectively, during sensory processing. Neurons in the central nucleus encoded reward information during the execution phase. This provides new clarity regarding the mechanisms of separate or integrated social and reward information processing within the amygdala.
One foundational distinction in affective science is between emotion reactivity and regulation. This conceptual distinction has long been assumed to be instantiated in spatially separable brain systems (a typical example: amygdala/insula for reactivity and frontoparietal areas for regulation). In this research, we begin by reviewing previous findings that support and contradict the neural separability hypothesis concerning emotional reactivity and regulation. Further, we conduct a direct test of this hypothesis with empirical data. In five studies involving healthy and clinical samples (total n = 336), we assessed neural responses using fMRI while participants were asked to either react naturally or regulate their emotions (using reappraisal) while viewing emotionally evocative stimuli. Across five studies, we failed to find support for the neural separability hypothesis. In univariate analyses, both presumptive “reactivity” and “regulation” brain regions demonstrated equal or greater activation for the reactivity contrast than for the regulation contrast. In multivariate pattern analyses (MVPA), classifiers decoded reactivity (vs. neutral) trials more accurately than regulation (vs. reactivity) trials using multivoxel data in both presumptive “reactivity” and “regulation” regions. These findings suggest that emotion reactivity and regulation—as measured via fMRI—may not be as spatially separable in the brain as previously assumed. Our secondary whole-brain analyses revealed largely consistent results. We discuss the two theoretical possibilities regarding the neural separability hypothesis and offer thoughts for future research.
The brain appeared for the movement control. Evolution has turned its function into behavior control. In the course of evolution, the brain has evolved into an extremely complex hierarchically organized system. To create a simplified model that algorithmically describes its structure, it was proposed to construct two parallel sequences: a sequence of models of brain structure representing the stages of its phylogeny, and a sequence of animal behavior models at the corresponding stages of phylogeny. As an illustration of the usefulness of such an approach for creating an operational model of a specific brain regions, the functions of the thalamic pulvinar nucleus in the control of visually guided behavior is discussed. It is concluded that the experimentally discovered role of the pulvinar as an initiator and synchronizer of parieto-frontal interactions is due to its main input signals from the superior colliculus and the pretectum.
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 47 m; 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.
People are biased toward seeing outcomes that they are motivated to see. For example, wanting their favored team to prevail biases sports fans to perceive an ambiguous foul in a manner that is favorable to the team they support. Here, we test the hypothesis that such motivational biases in perceptual decision-making are associated with amygdala activity. We used monetary incentives to experimentally manipulate participants to want to see one percept over another while they performed a categorization task involving ambiguous images. Participants were more likely to categorize an image as the category we motivated them to see, suggesting that wanting to see a particular percept biased their perceptual decisions. Heightened amygdala activity was associated with motivation consistent categorizations and tracked trial-by-trial enhancement of neural activity in sensory cortices encoding the desirable category. Analyses using a drift diffusion model further suggest that trial-by-trial amygdala activity was specifically associated with biases in the accumulation of sensory evidence. In contrast, frontoparietal regions commonly associated with biases in perceptual decision-making were not associated with motivational bias. Altogether, our results suggest that wanting to see an outcome biases perceptual decisions via distinct mechanisms and may depend on dynamic fluctuations in amygdala activity.
Human decision-making can be influenced by whether the option is framed as positive or negative, known as the framing effect. Neuroeconomic studies have shown the engagement of the amygdala underlies the framing effect by automatically incorporating emotional (or intuitive) information into the decision process, thus leading to "irrational" decisions or decision biases (De Martino et al. 2006). However, these studies focus only on the gain domain in which the initial state is appetitive, leaving the mechanisms of the framing effect in the loss or aversive domain less understood, which could be equally important or even more dominant for human survival. In the present study, we first replicated De Martino et al.’s research on the framing effect in the gain domain. We then checked the commonality and distinctiveness of the framing effect across gain and loss domains using a similar experimental design combined with functional magnetic resonance imaging (fMRI). Behaviorally, participants showed comparable framing effects in both domains, suggesting a domain-general decision bias. Neuronally, the amygdala represented the framing effect for the gain domain, and its connectivity to vmPFC was positively modulated by framing bias, consistently shown in De Martino et al.’s study. Moreover, the striatum represented the framing effect for the loss domain, and its connectivity to dmPFC was subject to framing bias, suggesting distinctive neural substrates across two domains. Our study accentuates the importance of distinguishing decision processes across appetitive or aversive domains and highlights the role of the cortical-striatal-limbic network underlying the framing effect.
A revised view of the amygdala, its relationship with the prefrontal cortex (PFC), and its role in intelligent human decision-making is proposed. Based on recent findings, we present a framework in which the amygdala plays a central role in the value computations that determine which goals are worth pursuing, while the PFC plays a central role in generating and evaluating possible action plans to realize these goals. We suggest that the amygdala and PFC continuously work together during decision-making and goal pursuit as individuals compute and recompute the value and likelihood of different goals while interacting with a dynamic world. Once seen as chiefly involved in simple stimulus-outcome associative learning, the amygdala is shown to play a sophisticated role in human decision-making by contributing to the moment-by-moment integration of multiple costs and benefits to determine optimal choices. We discuss implications of the framework for brain development, emotion regulation, intelligence, and psychopathology. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
People are biased towards seeing outcomes that they are motivated to see. For example, sports fans often perceive the same ambiguous foul in favor of the team they support. Here, we test the hypothesis that motivational biases in perceptual decision-making arise from amygdala-dependent biases in sensory processing. Human participants were rewarded for correctly categorizing an ambiguous image into one of two categories while undergoing fMRI. On each trial, we used a financial bonus to motivate participants to see one category over another. The reward maximizing strategy was to perform the categorizations accurately, but participants were biased towards categorizing the images as the category we motivated them to see. Heightened amygdala activity was associated with motivation consistent categorizations, and tracked trial-by-trial enhancement of neural activity in sensory cortices that was specific to the desirable category. Analyses using a drift diffusion model provide converging evidence that trial-by-trial amygdala activity was associated with stronger biases in the accumulation of sensory evidence. Prior work examining biases in perceptual decision-making have focused on the role of frontoparietal regions. Our work highlights an important contribution of the amygdala. When people are motivated to see one outcome over another, the amygdala biases perceptual decisions towards those outcomes.
Sensing the nutrient composition of a food and the processing of this information by the brain’s reward system to regulate food consumption are crucial biological needs. However, dysfunction in neural reward pathways may also lead to overconsumption of certain nutrients, contributing to obesity and comorbid diseases. In the context of fat, the oral sensory mechanism of its detection is disputed, although there is substantial evidence for fat detection through oral textural properties. In this thesis, I investigate the neural correlates related to the specific textural properties of oral food stimuli with defined nutrient contents, as well as their formally measured economic reward values and psychophysical ratings during functional Magnetic Resonance Imaging (fMRI) in healthy human volunteers. These results are then correlated with an ad-libitum naturalistic eating test. The thesis contains the following chapters: Chapter I discusses the key background literature; Chapter II focuses on the optimisation of the design and stimuli; Chapter III provides a detailed analysis of behavioural data, through basic psychophysical ratings of food stimuli and modelling of subjective value data; Chapter IV describes the results of the neuroimaging component of the experiment, and Chapter V discusses the results of the project in the context of current literature. This project investigates the textural contributions to sensory fat detection and reward valuation. Crucially, it is the first time a formal fMRI investigation is done on the oral-lubricative nature of fat, demonstrating encoding of sliding friction in the midposterior insula and the oral somatosensory cortex, which supports the concept that fat detection occurs through texture. Furthermore, our results highlight the unique role of the orbitofrontal cortex in processing food texture parameters, their subjective perception, and integration to subjective value, before subsequent evaluation in the ventromedial prefrontal cortex.
Humans learn about the environment either directly by interacting with it or indirectly by seeking information about it from social sources such as conspecifics. The degree of confidence in the information obtained through either route should determine the impact that it has on adapting and changing behaviour. We examined whether and how behavioural and neural computations differ during non-social learning as opposed to learning from social sources. Trial-wise confidence judgments about non-social and social information sources offered a window into this learning process. Despite matching exactly the statistical features of social and non-social conditions, confidence judgments were more accurate and less changeable when they were made about social as opposed to non-social information sources. In addition to subjective reports of confidence, differences were also apparent in the Bayesian estimates of participants' subjective beliefs. Univariate activity in dorsomedial prefrontal cortex (dmPFC) and posterior temporo-parietal junction (pTPJ) more closely tracked confidence about social as opposed to non-social information sources. In addition, the multivariate patterns of activity in the same areas encoded identities of social information sources compared to non-social information sources.
The direction of the eye gaze of others is a prominent social cue in primates and is important for communication1,2,3,4,5,6,7,8,9,10,11. Although gaze can signal threat and elicit anxiety6,12,13, it remains unclear whether it shares neural circuitry with stimulus value. Notably, gaze not only has valence, but can also serve as a predictor of the outcome of a social encounter, which can be either negative or positive2,8,12,13. Here we show that the neural codes for gaze and valence overlap in primates and that they involve two different mechanisms: one for the outcome and another for its expectation. Monkeys participated in the human intruder test13,14, in which a human participant had either a direct or averted gaze, interleaved with blocks of aversive and appetitive conditioning. We find that single neurons in the amygdala encode gaze15, whereas neurons in the anterior cingulate cortex encode the social context16, but not gaze. We identify a shared population in the amygdala for which the neural responses to direct and averted gaze parallel the responses to aversive and appetitive stimulus, respectively. Furthermore, we distinguish between two neural mechanisms—an overall-activity scheme that is used for gaze and the unconditioned stimulus, and a correlated-selectivity scheme that is used for gaze and the conditioned stimulus. These findings provide insights into the origins of the neural mechanisms that underlie the computations of both social interactions and valence, and could help to shed light on mechanisms that underlie social anxiety and the comorbidity between anxiety and impaired social interactions.
The neural systems that underlie reinforcement learning (RL) allow animals to adapt to changes in their environment. In the present study, we examined the hypothesis that the amygdala would have a preferential role in learning the values of visual objects. We compared a group of monkeys (Macaca mulatta) with amygdala lesions to a group of unoperated controls on a two-armed bandit reversal learning task. The task had two conditions. In the What condition, the animals had to learn to select a visual object, independent of its location. And in the Where condition, the animals had to learn to saccade to a location, independent of the object at the location. In both conditions choice-outcome mappings reversed in the middle of the block. We found that monkeys with amygdala lesions had learning deficits in both conditions. Monkeys with amygdala lesions did not have deficits in learning to reverse choice-outcome mappings. Rather, amygdala lesions caused the monkeys to become overly sensitive to negative feedback which impaired their ability to consistently select the more highly valued action or object. These results imply that the amygdala is generally necessary for RL.
Social behaviors recruit multiple cognitive operations that require interactions between cortical and subcortical brain regions. Interareal synchrony may facilitate such interactions between cortical and subcortical neural populations. However, it remains unknown how neurons from different nodes in the social brain network interact during social decision-making. Here we investigated oscillatory neuronal interactions between the basolateral amygdala and the rostral anterior cingulate gyrus of the medial prefrontal cortex while monkeys expressed context-dependent positive or negative other-regarding preference (ORP), whereby decisions affected the reward received by another monkey. Synchronization between the two nodes was enhanced for a positive ORP but suppressed for a negative ORP. These interactions occurred in beta and gamma frequency bands depending on the area contributing the spikes, exhibited a specific directionality of information flow associated with a positive ORP and could be used to decode social decisions. These findings suggest that specialized coordination in the medial prefrontal–amygdala network underlies social-decision preferences.
Multiple lines of evidence link economic choices to the orbitofrontal cortex (OFC), but other brain regions may contribute to the computation and comparison of economic values. A particularly strong candidate is the basolateral amygdala (BLA). Amygdala lesions impair performance in reinforcer devaluation tasks, suggesting that BLA contributes to value computation. Furthermore, previous studies of BLA found neuronal activity consistent with a value representation. Here we recorded from the BLA of two male rhesus macaques choosing between different juices. Offered quantities varied from trial to trial and relative values were inferred from choices. Roughly one third of BLA cells were task-related. Our analyses revealed the presence of three groups of neurons encoding variables offer value, chosen value and chosen juice. In this respect, BLA appeared similar to OFC. The two areas differed for the proportion of neurons in each group, as the fraction of chosen value cells was significantly higher in BLA. Importantly, the activity of these neurons reflected the subjective nature of value. Firing rates in BLA were sustained throughout the trial and maximal after juice delivery. In contrast, firing rates in OFC were phasic and maximal shortly after offer presentation. Our results suggest that BLA supports economic choice and reward expectation.
The explore-exploit dilemma refers to the challenge of deciding when to forego immediate rewards and explore new opportunities that could lead to greater rewards in the future. While motivational neural circuits facilitate learning based on past choices and outcomes, it is unclear whether they also support computations relevant for deciding when to explore. We recorded neural activity in the amygdala and ventral striatum of rhesus macaques as they solved a task that required them to balance novelty-driven exploration with exploitation of what they had already learned. Using a partially observable Markov decision process (POMDP) model to quantify explore-exploit trade-offs, we identified that the ventral striatum and amygdala differ in how they represent the immediate value of exploitative choices and the future value of exploratory choices. These findings show that subcortical motivational circuits are important in guiding explore-exploit decisions.
By observing their social partners, primates learn about reward values of objects. Here, we show that monkeys’ amygdala neurons derive object values from observation and use these values to simulate a
partner monkey’s decision process. While monkeys alternated making reward-based choices, amygdala neurons encoded object-specific values learned from observation. Dynamic activities converted these
values to representations of the recorded monkey’s own choices. Surprisingly, the same activity patterns unfolded spontaneously before partner’s choices in separate neurons, as if these neurons simulated the partner’s decision-making. These ‘‘simulation neurons’’ encoded signatures of mutual-inhibitory decision computation, including value comparisons and value-to-choice conversions, resulting in accurate
predictions of partner’s choices. Population decoding identified differential contributions of amygdala subnuclei. Biophysical modeling of amygdala circuits showed that simulation neurons emerge naturally
from convergence between object-value neurons and self-other
neurons. By simulating decision computations during observation, these neurons could allow primates to reconstruct their social partners’ mental states.
The social brain hypothesis posits that dedicated neural systems process social information. In support of this, neurophysiological data have shown that some brain regions are specialized for representing faces. It remains unknown, however, whether distinct anatomical substrates also represent more complex social variables, such as the hierarchical rank of individuals within a social group. Here we show that the primate amygdala encodes the hierarchical rank of individuals in the same neuronal ensembles that encode the rewards associated with nonsocial stimuli. By contrast, orbitofrontal and anterior cingulate cortices lack strong representations of hierarchical rank while still representing reward values. These results challenge the conventional view that dedicated neural systems process social information. Instead, information about hierarchical rank-which contributes to the assessment of the social value of individuals within a group-is linked in the amygdala to representations of rewards associated with nonsocial stimuli.
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
Significance statement:
Dysfunctional interactions between orbitofrontal cortex (OFC) and the amygdala underlie several mental health disorders, often related to value-based decision making. Understanding the underlying neural circuitry may help to develop therapies for those suffering from mood and anxiety disorders and provide insight into addiction. Here we investigated whether the amygdala must interact with OFC to make adaptive choices. Monkeys learned to perform two different actions: 'tap' for one kind of food reward, 'hold' for another. Then one of the two foods was devalued temporarily. Intact monkeys shifted their choice to whichever action produced the higher-value food; monkeys with crossed surgical disconnection of OFC and the amygdala did not. Thus, OFC and the amygdala must functionally interact to mediate adaptive choices.
Significance statement:
Altered functional interactions among orbital frontal cortex (OFC), medial frontal cortex (MFC), and amygdala are thought to underlie several psychiatric conditions, many related to reward learning. Here we investigated the causal contribution of the amygdala to the development of neuronal activity in macaque OFC and MFC related to rewards and the stimuli that predict them during learning. Without amygdala inputs, neurons in both OFC and MFC showed decreased encoding of stimulus-reward associations. MFC also showed increased encoding of the instrumental responses that monkeys' made on each trial. Behaviorally, changes in neural activity were accompanied by slower stimulus-reward learning. Taken together, the findings suggest that interactions among amygdala, OFC, and MFC contribute to learning about stimuli that predict rewards.
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.
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.
Significance
Making social decisions requires evaluation of benefits and costs to self and others. Long associated with emotion and vigilance, neurons in primate amygdala also signal reward and punishment as well as information about the faces and eyes of others. Here we show that neurons in the basolateral amygdala signal the value of rewards for self and others when monkeys make social decisions. These value-mirroring neurons reflected monkeys’ tendency to make prosocial decisions on a momentary as well as long-term basis. We also found that delivering the social peptide oxytocin into basolateral amygdala enhances both prosocial tendencies and attention to the recipients of prosocial decisions. Our findings endorse the amygdala as a critical neural nexus regulating social decisions.
Despite widespread interest in social dominance, little is known of its neural correlates in primates. We hypothesized that social status in primates might be related to individual variation in subcortical brain regions implicated in other aspects of social and emotional behavior in other mammals. To examine this possibility we used magnetic resonance imaging (MRI), which affords the taking of quantitative measurements noninvasively, both of brain structure and of brain function, across many regions simultaneously. We carried out a series of tests of structural and functional MRI (fMRI) data in 25 group-living macaques. First, a deformation-based morphometric (DBM) approach was used to show that gray matter in the amygdala, brainstem in the vicinity of the raphe nucleus, and reticular formation, hypothalamus, and septum/striatum of the left hemisphere was correlated with social status. Second, similar correlations were found in the same areas in the other hemisphere. Third, similar correlations were found in a second data set acquired several months later from a subset of the same animals. Fourth, the strength of coupling between fMRI-measured activity in the same areas was correlated with social status. The network of subcortical areas, however, had no relationship with the sizes of individuals' social networks, suggesting the areas had a simple and direct relationship with social status. By contrast a second circuit in cortex, comprising the midsuperior temporal sulcus and anterior and dorsal prefrontal cortex, covaried with both individuals' social statuses and the social network sizes they experienced. This cortical circuit may be linked to the social cognitive processes that are taxed by life in more complex social networks and that must also be used if an animal is to achieve a high social status.
Hungry animals are influenced by a multitude of different factors when foraging for sustenance. Much of the work on animal foraging has focused on factors relating to the amount of time and energy animals expend searching for and harvesting foods. Models that emphasize such factors have been invaluable in determining when it is beneficial for an animal to search for pastures new. When foraging, however, animals also have to determine how to direct their search. For what food should they forage? There is no point searching for more of a particular food when you are sated from eating it. Here we review work in macaques and humans that has sought to reveal the neural circuits critical for determining the subjective value of different foods and associated objects in our environment and tracking this value over time. There is mounting evidence that a network composed of the orbitofrontal cortex (OFC), amygdala, and medial thalamus is critical for linking objects in the environment with food value and adjusting those valuations in real time based on current biological needs. Studies using temporary inactivation methods have revealed that the amygdala and OFC play distinct yet complementary roles in this valuation process. Such a network for determining the subjective value of different foods and, by extension, associated objects, must interact with systems that determine where and for how long to forage. Only by efficiently incorporating these two factors into their decisions will animals be able to achieve maximal fitness.
A stimulus predicting reinforcement can trigger emotional responses, such as arousal, and cognitive ones, such as increased attention toward the stimulus. Neuroscientists have long appreciated that the amygdala mediates spatially nonspecific emotional responses, but it remains unclear whether the amygdala links motivational and spatial representations. To test whether amygdala neurons encode spatial and motivational information, we presented reward-predictive cues in different spatial configurations to monkeys and assessed how these cues influenced spatial attention. Cue configuration and predicted reward magnitude modulated amygdala neural activity in a coordinated fashion. Moreover, fluctuations in activity were correlated with trial-to-trial variability in spatial attention. Thus, the amygdala integrates spatial and motivational information, which may influence the spatial allocation of cognitive resources. These results suggest that amygdala dysfunction may contribute to deficits in cognitive processes normally coordinated with emotional responses, such as the directing of attention toward the location of emotionally relevant stimuli.
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.
The time of reward and the temporal structure of reward occurrence fundamentally influence behavioral reinforcement and decision processes [1-11]. However, despite knowledge about timing in sensory and motor systems [12-17], we know little about temporal mechanisms of neuronal reward processing. In this experiment, visual stimuli predicted different instantaneous probabilities of reward occurrence that resulted in specific temporal reward structures. Licking behavior demonstrated that the animals had developed expectations for the time of reward that reflected the instantaneous reward probabilities. Neurons in the amygdala, a major component of the brain's reward system [18-29], showed two types of reward signal, both of which were sensitive to the expected time of reward. First, the time courses of anticipatory activity preceding reward delivery followed the specific instantaneous reward probabilities and thus paralleled the temporal reward structures. Second, the magnitudes of responses following reward delivery covaried with the instantaneous reward probabilities, reflecting the influence of temporal reward structures at the moment of reward delivery. In being sensitive to temporal reward structure, the reward signals of amygdala neurons reflected the temporally specific expectations of reward. The data demonstrate an active involvement of amygdala neurons in timing processes that are crucial for reward function.
The outcome-selective effects of presenting intertrial unconditioned stimuli (USs) in a rat appetitive conditioning paradigm
were examined in two experiments. In both experiments, two stimuli were paired with different outcomes, while one of these
outcomes was also presented in the intertrial interval (A+, B*, +). Two measures of learning, stimulus-elicited magazine approach
and Pavlovian-to-instrumental transfer, were used to examine these effects. The presence of freely occurring outcomes in the
intertrial interval (ITI) was observed to interfere more with the learning of a new association (Experiment 1) and to degrade
more an already established association (Experiment 2) when the conditioned stimulus had been paired with the same outcome
as that occurring in the ITI. An outcome-selective effect of ITI USs distinguishes among accounts of contingency based on
general performance, attentional, and motivational mechanisms from those based on more specific associative mechanisms. Overall,
the data highlight the importance of specific encoding processes in the analysis of associative learning.
The orbitofrontal cortex (OFC) and its interactions with the basolateral amygdala (BLA) are critical for goal-directed behavior, especially for adapting to changes in reward value. Here we used a reinforcer devaluation paradigm to investigate the contribution of OFC to this behavior in four macaques. Subjects that had formed associations between objects and two different primary reinforcers (foods) were presented with choices of objects overlying the two different foods. When one of the two foods was devalued by selective satiation, the subjects shifted their choices toward the objects that represented the nonsated food reward (devaluation effect). Transient inactivation of OFC by infusions of the GABA(A) receptor agonist muscimol into area 13 blocked the devaluation effect: the monkeys did not reduce their selection of objects associated with the devalued food. This effect was observed when OFC was inactivated during both satiation and the choice test, and during the choice test only. This supports our hypothesis that OFC activity is required during the postsatiety object choice period to guide the selection of objects. This finding sharply contrasts with the role of BLA in the same devaluation process (Wellman et al., 2005). Whereas activity in BLA was required during the selective satiation procedure, it was not necessary for guiding the subsequent object choice. Our results are the first to demonstrate that transient inactivation of OFC is sufficient to disrupt the devaluation effect, and to document a role for OFC distinct from that of BLA for the conditioned reinforcer devaluation process in monkeys.
Animals assess the values of rewards to learn and choose the best possible outcomes. We studied how single neurons in the primate amygdala coded reward magnitude, an important variable determining the value of rewards. A single, Pavlovian-conditioned visual stimulus predicted fruit juice to be delivered with one of three equiprobable volumes (P = 1/3). A population of amygdala neurons showed increased activity after reward delivery, and almost one half of these responses covaried with reward magnitude in a monotonically increasing or decreasing fashion. A subset of the reward responding neurons were tested with two different probability distributions of reward magnitude; the reward responses in almost one half of them adapted to the predicted distribution and thus showed reference-dependent coding. These data suggest parametric reward value coding in the amygdala as a characteristic component of its function in reinforcement learning and economic decision making.
Prediction about outcomes constitutes a basic mechanism underlying informed economic decision making. A stimulus constitutes a reward predictor when it provides more information about the reward than the environmental background. Reward prediction can be manipulated in two ways, by varying the reward paired with the stimulus, as done traditionally in neurophysiological studies, and by varying the background reward while holding stimulus-reward pairing constant. Neuronal mechanisms involved in reward prediction should also be sensitive to changes in background reward independently of stimulus-reward pairing. We tested this assumption on a major brain structure involved in reward processing, the central and basolateral amygdala. In a 2 x 2 design, we examined the influence of rewarded and unrewarded backgrounds on neuronal responses to rewarded and unrewarded visual stimuli. Indeed, responses to the unchanged rewarded stimulus depended crucially on background reward in a population of amygdala neurons. Elevating background reward to the level of the rewarded stimulus extinguished these responses, and lowering background reward again reinstated the responses without changes in stimulus-reward pairing. None of these neurons responded specifically to an inhibitory stimulus predicting less reward compared with background (negative contingency). A smaller group of amygdala neurons maintained stimulus responses irrespective of background reward, possibly reflecting stimulus-reward pairing or visual sensory processes without reward prediction. Thus in being sensitive to background reward, the responses of a population of amygdala neurons to phasic stimuli appeared to follow the full criteria for excitatory reward prediction (positive contingency) rather than reflecting simple stimulus-reward pairing (contiguity).
This review begins with a brief historical overview of attempts in the first half of the 20th century to discern brain systems that underlie emotion and emotional behavior. These early studies identified the amygdala, hippocampus, and other parts of what was termed the 'limbic' system as central parts of the emotional brain. Detailed connectional data on this system began to be obtained in the 1970s and 1980s, as more effective neuroanatomical techniques based on axonal transport became available. In the last 15 years these methods have been applied extensively to the limbic system and prefrontal cortex of monkeys, and much more specific circuits have been defined. In particular, a system has been described that links the medial prefrontal cortex and a few related cortical areas to the amygdala, the ventral striatum and pallidum, the medial thalamus, the hypothalamus, and the periaqueductal gray and other parts of the brainstem. A large body of human data from functional and structural imaging, as well as analysis of lesions and histological material indicates that this system is centrally involved in mood disorders.
The palatability and pleasantness of the sensory properties of foods drive food selection and intake and may contribute to overeating and obesity. Oral fat texture can make food palatable and pleasant. To analyze its neural basis, we correlated humans' subjective reports of the pleasantness of the texture and flavor of a high- and low-fat food with a vanilla or strawberry flavor, with neural activations measured with functional magnetic resonance imaging. Activity in the midorbitofrontal and anterior cingulate cortex was correlated with the pleasantness of oral fat texture and in nearby locations with the pleasantness of flavor. The pregenual cingulate cortex showed a supralinear response to the combination of high fat and pleasant, sweet flavor, implicating it in the convergence of fat texture and flavor to produce a representation of highly pleasant stimuli. The subjective reports of oral fattiness were correlated with activations in the midorbitofrontal cortex and ventral striatum. The lateral hypothalamus and amygdala were more strongly activated by high- versus low-fat stimuli. This discovery of which brain regions track the subjective hedonic experience of fat texture will help to unravel possible differences in the neural responses in obese versus lean people to oral fat, a driver of food intake.
As an organism interacts with the world, how good or bad things are at the moment, the value of the current state of the organism, is an important parameter that is likely to be encoded in the brain. As the environment changes and new stimuli appear, estimates of state value must be updated to support appropriate responses and learning. Indeed, many models of reinforcement learning posit representations of state value. We examined how the brain mediates this process by recording amygdala neural activity while monkeys performed a trace-conditioning task requiring fixation. The presentation of different stimuli induced state transitions; these stimuli included unconditioned stimuli (USs) (liquid rewards and aversive air puffs), newly learned reinforcement-predictive visual stimuli [conditioned stimuli (CSs)], and familiar stimuli long associated with reinforcement [fixation point (FP)]. The FP had a positive value to monkeys, because they chose to foveate it to initiate trials. Different populations of amygdala neurons tracked the positive or negative value of the current state, regardless of whether state transitions were caused by the FP, CSs, or USs. Positive value-coding neurons increased their firing during the fixation interval and fired more strongly after rewarded CSs and rewards than after punished CSs and air puffs. Negative value-coding neurons did the opposite, decreasing their firing during the fixation interval and firing more strongly after punished CSs and air puffs than after rewarded CSs and rewards. This representation of state value could underlie how the amygdala helps coordinate cognitive, emotional, and behavioral responses depending on the value of one's state.
Neuronal activity in the amygdala (AM) was recorded from alert monkeys during performance of tasks that led to presentation of rewarding or aversive stimuli. The tasks had 3 phases: (1) discrimination (visual, auditory), (2) operant response (bar pressing), and (3) ingestion (reward) or avoidance (aversion). Neuronal activity was analyzed and compared during each of these phases. Of 585 AM neurons tested, 312 (53.3%) responded to at least one stimulus in one or more of 5 major groups: vision related, audition related, ingestion related, multimodal, and selective. Forty neurons (6.8%) in the anterior dorsolateral capsule of the basolateral nuclei responded exclusively to visual stimuli (vision related). Twenty-six neurons (4.4%) further posterior in the basolateral group responded only to auditory stimuli (audition related). During ingestion an additional 41 neurons (7.0%) increased their activity (ingestion related). These were in the corticomedial group and at the boundaries between the nuclei of the basolateral group. Of these, 27 responded only in the ingestion phase, 11 during ingestion and at the sight of food, and 3 during ingestion and to certain sounds. Throughout the AM other neurons (n = 117, 20.0%) responded to visual, auditory, and somesthetic stimuli and, when tested, to involuntary ingestion of liquid (multimodal). Of these, 40 responded transiently (phasic; 36 excited, 4 inhibited). The remaining 77 maintained their altered activity into the subsequent phases of the task (tonic; 69 excited, 8 inhibited). In each of these 4 categories, most cells were activated primarily by novel or unfamiliar stimuli, and their responses habituated during repeated stimulation. A small number of cells in the basolateral and the basomedial nuclei (n = 14, 2.4%) were highly selective in that they responded specifically to one biologically significant object or sound more than to any other stimuli (selective). Some of these neurons responded to both sight and ingestion of a specific food. In summary, most AM neurons responded vigorously to novel stimuli, and some of the neurons had multimodal responsiveness. These results suggest the AM is related to processing of new environmental stimuli and to those cross-modal association.
THE TRADITIONAL CONTROL PROCEDURES FOR PAVLOVIAN CONDITIONING ARE EXAMINED AND EACH IS FOUND WANTING. SOME PROCEDURES INTRODUCE NONASSOCIATIVE FACTORS NOT PRESENT IN THE EXPERIMENTAL PROCEDURE WHILE OTHERS TRANSFORM THE EXCITATORY, EXPERIMENTAL CS-UCS CONTINGENCY INTO AN INHIBITORY CONTINGENCY. AN ALTERNATIVE CONTROL PROCEDURE IS SUGGESTED IN WHICH THERE IS NO CONTINGENCY WHATSOEVER BETWEEN CS AND UCS. THIS "TRULY RANDOM" CONTROL PROCEDURE LEADS TO A NEW CONCEPTION OF PAVLOVIAN CONDITIONING POSTULATING THAT THE CONTINGENCY BETWEEN CS AND UCS, RATHER THAN THE PAIRING OF CS AND UCS, IS THE IMPORTANT EVENT IN CONDITIONING. THE FRUITFULNESS OF THIS NEW CONCEPTION OF PAVLOVIAN CONDITIONING IS ILLUSTRATED BY 2 EXPERIMENTAL RESULTS. (15 REF.)
The sixth edition of the foundational reference on cognitive neuroscience, with entirely new material that covers the latest research, experimental approaches, and measurement methodologies. Each edition of this classic reference has proved to be a benchmark in the developing field of cognitive neuroscience. The sixth edition of The Cognitive Neurosciences continues to chart new directions in the study of the biological underpinnings of complex cognition—the relationship between the structural and physiological mechanisms of the nervous system and the psychological reality of the mind. It offers entirely new material, reflecting recent advances in the field, covering the latest research, experimental approaches, and measurement methodologies.
This sixth edition treats such foundational topics as memory, attention, and language, as well as other areas, including computational models of cognition, reward and decision making, social neuroscience, scientific ethics, and methods advances. Over the last twenty-five years, the cognitive neurosciences have seen the development of sophisticated tools and methods, including computational approaches that generate enormous data sets. This volume deploys these exciting new instruments but also emphasizes the value of theory, behavior, observation, and other time-tested scientific habits.
Section editorsSarah-Jayne Blakemore and Ulman Lindenberger, Kalanit Grill-Spector and Maria Chait, Tomás Ryan and Charan Ranganath, Sabine Kastner and Steven Luck, Stanislas Dehaene and Josh McDermott, Rich Ivry and John Krakauer, Daphna Shohamy and Wolfram Schultz, Danielle Bassett and Nikolaus Kriegeskorte, Marina Bedny and Alfonso Caramazza, Liina Pylkkänen and Karen Emmorey, Mauricio Delgado and Elizabeth Phelps, Anjan Chatterjee and Adina Roskies
We recorded the activity of single neurons in the posterior parietal cortex (area LIP) of two rhesus monkeys while they discriminated the direction of motion in random-dot visual stimuli. The visual task was similar to a motion discrimination task that has been used in previous investigations of motion-sensitive regions of the extrastriate cortex. The monkeys were trained to decide whether the direction of motion was toward one of two choice targets that appeared on either side of the random-dot stimulus. At the end of the trial, the monkeys reported their direction judgment by making an eye movement to the appropriate target. We studied neurons in LIP that exhibited spatially selective persistent activity during delayed saccadic eye movement tasks. These neurons are thought to carry high-level signals appropriate for identifying salient visual targets and for guiding saccadic eye movements. We arranged the motion discrimination task so that one of the choice targets was in the LIP neuron's response field (RF) while the other target was positioned well away from the RF. During motion viewing, neurons in LIP altered their firing rate in a manner that predicted the saccadic eye movement that the monkey would make at the end of the trial. The activity thus predicted the monkey's judgment of motion direction. This predictive activity began early in the motion-viewing period and became increasingly reliable as the monkey viewed the random-dot motion. The neural activity predicted the monkey's direction judgment on both easy and difficult trials (strong and weak motion), whether or not the judgment was correct. In addition, the timing and magnitude of the response was affected by the strength of the motion signal in the stimulus. When the direction of motion was toward the RF, stronger motion led to larger neural responses earlier in the motion-viewing period. When motion was away from the RF, stronger motion led to greater suppression of ongoing activity. Thus the activity of single neurons in area LIP reflects both the direction of an impending gaze shift and the quality of the sensory information that instructs such a response. The time course of the neural response suggests that LIP accumulates sensory signals relevant to the selection of a target for an eye movement.
The same reward can possess different motivational meaning depending upon its magnitude relative to other rewards. To study the neurophysiological mechanisms mediating assignment of motivational meaning, we recorded the activity of neurons in the amygdala and orbitofrontal cortex (OFC) of monkeys during a Pavlovian task in which the relative amount of liquid reward associated with one conditioned stimulus (CS) was manipulated by changing the reward amount associated with a second CS. Anticipatory licking tracked relative reward magnitude, implying that monkeys integrated information about recent rewards to adjust the motivational meaning of a CS. Upon changes in relative reward magnitude, neural responses to reward-predictive cues updated more rapidly in OFC than amygdala, and activity in OFC but not the amygdala was modulated by recent reward history. These results highlight a distinction between the amygdala and OFC in assessing reward history to support the flexible assignment of motivational meaning to sensory cues.
Neurons in prefrontal cortex (PFC) encode rules, goals, and other abstract information thought to underlie cognitive, emotional, and behavioral flexibility. Here we show that the amygdala, a brain area traditionally thought to mediate emotions, also encodes abstract information that could underlie this flexibility. Monkeys performed a task in which stimulus-reinforcement contingencies varied between two sets of associations, each defining a context. Reinforcement prediction required identifying a stimulus and knowing the current context. Behavioral evidence indicated that monkeys utilized this information to perform inference and adjust their behavior. Neural representations in both amygdala and PFC reflected the linked sets of associations implicitly defining each context, a process requiring a level of abstraction characteristic of cognitive operations. Surprisingly, when errors were made, the context signal weakened substantially in the amygdala. These data emphasize the importance of maintaining abstract cognitive information in the amygdala to support flexible behavior.
Copyright © 2015 Elsevier Inc. All rights reserved.
A cornerstone of successful social interchange is the ability to anticipate each other's intentions or actions. While generating these internal predictions is essential for constructive social behavior, their single neuronal basis and causal underpinnings are unknown. Here, we discover specific neurons in the primate dorsal anterior cingulate that selectively predict an opponent's yet unknown decision to invest in their common good or defect and distinct neurons that encode the monkey's own current decision based on prior outcomes. Mixed population predictions of the other was remarkably near optimal compared to behavioral decoders. Moreover, disrupting cingulate activity selectively biased mutually beneficial interactions between the monkeys but, surprisingly, had no influence on their decisions when no net-positive outcome was possible. These findings identify a group of other-predictive neurons in the primate anterior cingulate essential for enacting cooperative interactions and may pave a way toward the targeted treatment of social behavioral disorders. VIDEO ABSTRACT:
Copyright © 2015 Elsevier Inc. All rights reserved.
The best rewards are often distant and can only be achieved by planning and decision-making over several steps. We designed a multi-step choice task in which monkeys followed internal plans to save rewards toward self-defined goals. During this self-controlled behavior, amygdala neurons showed future-oriented activity that reflected the animal's plan to obtain specific rewards several trials ahead. This prospective activity encoded crucial components of the animal's plan, including value and length of the planned choice sequence. It began on initial trials when a plan would be formed, reappeared step by step until reward receipt, and readily updated with a new sequence. It predicted performance, including errors, and typically disappeared during instructed behavior. Such prospective activity could underlie the formation and pursuit of internal plans characteristic of goal-directed behavior. The existence of neuronal planning activity in the amygdala suggests that this structure is important in guiding behavior toward internally generated, distant goals.
The amygdala has long been associated with emotion and motivation, playing an essential part in processing both fearful and rewarding environmental stimuli. How can a single structure be crucial for such different functions? With recent technological advances that allow for causal investigations of specific neural circuit elements, we can now begin to map the complex anatomical connections of the amygdala onto behavioural function. Understanding how the amygdala contributes to a wide array of behaviours requires the study of distinct amygdala circuits.
Primates explore the visual world through eye-movement sequences. Saccades bring details of interest into the fovea, while fixations stabilize the image [1]. During natural vision, social primates direct their gaze at the eyes of others to communicate their own emotions and intentions and to gather information about the mental states of others [2]. Direct gaze is an integral part of facial expressions that signals cooperation or conflict over resources and social status [3-6]. Despite the great importance of making and breaking eye contact in the behavioral repertoire of primates, little is known about the neural substrates that support these behaviors. Here we show that the monkey amygdala contains neurons that respond selectively to fixations on the eyes of others and to eye contact. These "eye cells" share several features with the canonical, visually responsive neurons in the monkey amygdala; however, they respond to the eyes only when they fall within the fovea of the viewer, either as a result of a deliberate saccade or as eyes move into the fovea of the viewer during a fixation intended to explore a different feature. The presence of eyes in peripheral vision fails to activate the eye cells. These findings link the primate amygdala to eye movements involved in the exploration and selection of details in visual scenes that contain socially and emotionally salient features.
We examined the contribution of the amygdala to value signals within orbital prefrontal cortex (OFC) and medial prefrontal cortex (MFC). On each trial, monkeys chose between two stimuli that were associated with different quantities of reward. In intact monkeys, as expected, neurons in both OFC and MFC signaled the reward quantity associated with stimuli. Contrasted with MFC, OFC contained a larger proportion of neurons encoding reward quantity and did so with faster response latencies. Removing the amygdala eliminated these differences, mainly by decreasing value coding in OFC. Similar decreases occurred in OFC immediately before and after reward delivery. Although the amygdala projects to both OFC and MFC, we found that it has its greatest influence over reward-value coding in OFC. Notably, amygdala lesions did not abolish value coding in OFC, which shows that OFC's representations of the value of objects, choices, and outcomes depends, in large part, on other sources.
People with autism spectrum disorder (ASD) show abnormal processing of faces. A range of morphometric, histological, and neuroimaging studies suggest the hypothesis that this abnormality may be linked to the amygdala. We recorded data from single neurons within the amygdalae of two rare neurosurgical patients with ASD. While basic electrophysiological response parameters were normal, there were specific and striking abnormalities in how individual facial features drove neuronal response. Compared to control patients, a population of neurons in the two ASD patients responded significantly more to the mouth, but less to the eyes. Moreover, we found a second class of face-responsive neurons for which responses to faces appeared normal. The findings confirm the amygdala's pivotal role in abnormal face processing by people with ASD at the cellular level and suggest that dysfunction may be traced to a specific subpopulation of neurons with altered selectivity for the features of faces.
Each of us has felt afraid, and we can all recognize fear in many animal species. Yet there is no consensus in the scientific study of fear. Some argue that 'fear' is a psychological construct rather than something discoverable through scientific investigation. Others argue that the term 'fear' cannot properly be applied to animals because we cannot know whether they feel afraid. Studies in rodents show that there are highly specific brain circuits for fear, whereas findings from human neuroimaging seem to make the opposite claim. Here, I review the field and urge three approaches that could reconcile the debates. For one, we need a broadly comparative approach that would identify core components of fear conserved across phylogeny. This also pushes us towards the second point of emphasis: an ecological theory of fear that is essentially functional. Finally, we should aim even to incorporate the conscious experience of being afraid, reinvigorating the study of feelings across species.
consider the functions of the primate amygdala in the light of the responsiveness of single neurons within the structure / the neuronal responsiveness is most informative when activity is recorded while the amygdala is functioning normally, and in situations in which the amygdala is required / the neurophysiology must thus proceed closely with lesion studies which help assess the functions of the amygdala / it is important to analyse the information processing being performed by neurons in the amygdala, and for this reason some evidence on the input and output connections of the amygdala, and on the neuronal activity in these input and output regions, is considered / this helps to provide an understanding of how the amygdala operates at the systems level of brain function, and in particular how it transforms the inputs it receives, and what effects the results of its computations have on output regions / particular attention is paid to research in nonhuman primates (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Neuroscientists have often described cognition and emotion as separable processes implemented by different regions of the brain, such as the amygdala for emotion and the prefrontal cortex for cognition. In this framework, functional interactions between the amygdala and prefrontal cortex mediate emotional influences on cognitive processes such as decision-making, as well as the cognitive regulation of emotion. However, neurons in these structures often have entangled representations, whereby single neurons encode multiple cognitive and emotional variables. Here we review studies using anatomical, lesion, and neurophysiological approaches to investigate the representation and utilization of cognitive and emotional parameters. We propose that these mental state parameters are inextricably linked and represented in dynamic neural networks composed of interconnected prefrontal and limbic brain structures. Future theoretical and experimental work is required to understand how these mental state representations form and how shifts between mental states occur, a critical feature of adaptive cognitive and emotional behavior.
In the two-choice situation, the Wald sequential probability ratio decision procedure is applied to relate the mean and variance of the decision times, for each alternative separately, to the error rates and the ratio of the frequencies of presentation of the alternatives. For situations involving more than two choices, a fixed sample decision procedure (selection of the alternative with highest likelihood) is examined, and the relation is found between the decision time (or size of sample), the error rate, and the number of alternatives.
There is evidence that the inferotemporal visual cortex in the monkey projects to the amygdala, and evidence that damage to this region impairs the learning of associations between visual stimuli and reward or punishment. In recordings made in the amygdala to determine whether or not visual responses were found, and if so how they were affected by the significance of the visual stimuli, neurons were found in the dorsolateral part of the amygdala with visual responses which in most cases were sustained while the animal looked at effective visual stimuli. The latency of the responses was 100 to 140 ms or more. The majority (85%) of these neurons responded more strongly to some stimuli than to others, but physical factors which accounted for the responses of the neurons, such as shape, size, orientation, color, or texture, could not usually be identified. Although 22 (19.5%) of these neurons responded primarily to food objects, the responses were not uniquely food-related. Furthermore, although some neurons responded in a visual discrimination test to a visual stimulus which indicated reward, and not to a visual stimulus which indicated saline, only minor modifications of the magnitude of the neuronal responses to the stimuli were obtained when the reward-related significance of the stimuli was reversed. The visual responses of these amygdaloid neurons were thus intermediate in some respects between those of neurons in the inferotemporal cortex, which are not affected by the significance of visual stimuli, and those of neurons in a region to which the amygdala projects, the lateral hypothalamus and substantia innominata, where neurons respond to visual stimuli associated with food reward.
To investigate the functions of the amygdala in visual information processing and in emotional and social responses, recordings were made from single neurons in the amygdala of the monkey. A population of neurons (40 of more than 1000 recorded in 4 monkeys) was investigated which responded primarily to faces. These neurons typically (1) responded to some human or monkey faces, which were presented to the monkey through a large aperture shutter so that response latencies could be measured, or were simply shown to the monkey, (2) responded to 2-dimensional representations of these faces, as well as to real 3-dimensional faces, (3) had no responses or only small (less than half maximum) responses to gratings, simple geometrical, other complex 3-D stimuli, or to arousing and aversive stimuli, (4) had response latencies of 110-200 ms, (5) were located in the basal accessory nucleus of the amygdala, (6) responded differently to different faces, as shown by measures of d', and could thus over a population of such neurons code information useful for making different responses to different individuals, (7) could in some cases (9/11 tested) respond to parts of faces, and (8) in a few cases (4/19 tested) responded more to a face which produced an emotional response. A comparison made in three monkeys of the responses of these neurons with the responses of 77 neurons with face-selective responses recorded in the cortex of the superior temporal sulcus (STS) showed that the amygdaloid neurons had longer response latencies (110-200 compared to 90-140 ms), and were in some respects more selective in their responses to different faces. It is suggested that the deficits in social and emotional behavior produced by amygdala lesions could be due in part to damage to a neuronal system specialized in utilizing information from faces so that appropriate social and emotional responses can be made to different individuals.
Recent theoretical approaches to the problem of psychophysical discrimination have produced what may be classified as ‘ statistical decision ’ or ‘ data accumulation ’ models. While the former have received much attention their application to judgment and choice meets with some difficulties. Among the latter, the two types which have received most attention are a ‘ runs ’ and a ‘ recruitment ’ model, but neither seems able to account for all of the relevant data. It is suggested instead that an ‘ accumulator ’ model, in which sampled events may vary in magnitude as well as probability, can be developed to give a good account of much of the available data on psychophysical discrimination. Two experiments are reported, in which the subject presses one of two keys as soon as he has decided whether the longer of two simultaneously presented lines is on the left or right. Results are found to be inconsistent with a runs or recruitment process, but to accord well with predictions from the accumulator model. Other evidence consistent with such a mechanism is briefly reviewed
Amygdalo-cortical projections were analyzed in the macaque monkey (Macaca fascicularis) in a series of experiments in which 3H-amino acids were injected into each of the major divisions of the amygdaloid complex and the anterogradely transported label was demonstrated autoradiographically. Projections to widespread regions of frontal, insular, temporal, and occipital cortices have been observed. The heaviest projections to frontal cortex terminated in medial and orbital regions which included areas 24, 25, and 32 on the medial surface and areas 14, 13a, and 12 on the orbital surface. Lighter projections were also seen in areas 45, 46, 6, 9, and 10. The heaviest projection to the insula terminated in the agranular insular cortex with a decreasing gradient of innervation to the more caudally placed dysgranular and granular insular areas. The projection to this region continues around the dorsal limiting sulcus to terminate in the somatosensory fields 3, 1-2, and SII. Essentially all major divisions of the temporal neocortex receive a projection from the amygdaloid complex with the most prominent projections ending in the cortex of the temporal pole (area TG) and the perirhinal cortex. The entire rostrocaudal extent of the inferotemporal cortex (areas TE and TEO) is also in receipt of an amygdaloid projection. While the rostral superior temporal gyrus (area TA) is heavily labeled in several of the experiments (with light labeling continuing into AI and adjacent auditory association regions) there was little indication of labeling in the caudal reaches of area TA. There was a surprisingly strong projection to prestriate regions of the occipital lobe and, in at least one case, clear-cut labeling in areas OB and 17. Labeling in the parietal cortex was primarily observed in the depths of the intraparietal sulcus. In all cortical fields, label was heaviest at the border between layers I and II and in some regions layers V and VI also had above background levels of silver grains.