Separate amygdala subregions signal surprise and predictiveness during associative fear learning in humans

Distributed neural representations of conditioned threat in the human brain

Detecting and responding to threat engages several neural nodes including the amygdala, hippocampus, insular cortex, and medial prefrontal cortices. Recent propositions call for the integration of more distributed neural nodes that process sensory and cognitive facets related to threat. Integrative, sensitive, and reproducible distributed neural decoders for the detection and response to threat and safety have yet to be established. We combine functional MRI data across varying threat conditioning and negative affect paradigms from 1465 participants with multivariate pattern analysis to investigate distributed neural representations of threat and safety. The trained decoders sensitively and specifically distinguish between threat and safety cues across multiple datasets. We further show that many neural nodes dynamically shift representations between threat and safety. Our results establish reproducible decoders that integrate neural circuits, merging the well-characterized 'threat circuit' with sensory and cognitive nodes, discriminating threat from safety regardless of experimental designs or data acquisition parameters.

Emotional recognition across the adult lifespan: Effects of age, sex, cognitive empathy, alexithymia traits, and amygdala subnuclei volumes

The ability to recognize others' emotions is vital to everyday life. The goal of this study was to assess which emotions show age-related decline in recognition accuracy of facial emotional expressions across the entire adult lifespan and how this process is related to cognitive empathy (Theory of Mind [ToM]), alexithymia traits, and amygdala subnuclei volumes in a large cohort of healthy individuals. We recruited 140 healthy participants 18-85 years old. Facial affect processing was assessed with the Penn Emotion Recognition task (ER40) that contains images of the five basic emotions: Neutral, Happy, Sad, Angry, and Fearful. Structural magnetic resonance imaging (MRI) datasets were acquired on a 4.7T MRI system. Structural equation modeling was used to test the relationship between studied variables. We found that while both sexes demonstrated age-related reduction in recognition of happy emotions and preserved recognition of sadness, male participants showed age-related reduction in recognition of fear, while in female participants, age-related decline was linked to recognition of neutral and angry facial expressions. In both sexes, accurate recognition of sadness negatively correlated with alexithymia traits. On the other hand, better ToM capabilities in male participants were associated with improvement in recognition of positive and neutral emotions. Finally, none of the observed age-related reductions in emotional recognition were related to amygdala and its subnuclei volumes. In contrast, both global volume of amygdala and its cortical and centromedial subnuclei had significant direct effects on recognition of sad images.

Neuroimaging of Fear Extinction

Extinguishing fear and defensive responses to environmental threats when they are no longer warranted is a critical learning ability that can promote healthy self-regulation and, ultimately, reduce susceptibility to or maintenance of affective-, trauma-, stressor-,and anxiety-related disorders. Neuroimaging tools provide an important means to uncover the neural mechanisms of effective extinction learning that, in turn, can abate the return of fear. Here I review the promises and pitfalls of functional neuroimaging as a method to investigate fear extinction circuitry in the healthy human brain. I discuss the extent to which neuroimaging has validated the core circuits implicated in rodent models and has expanded the scope of the brain regions implicated in extinction processes. Finally, I present new advances made possible by multivariate data analysis tools that yield more refined insights into the brain-behavior relationships involved.

Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder

Background

The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus-amygdala complex in medication-naïve patients with first-episode MDD.

Methods

High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups.

Results

Compared with HCs, the SCN within the hippocampus-amygdala complex in patients with MDD showed a shortened mean characteristic path length, reduced modularity, and reduced small-worldness index. At the nodal level, the left hippocampal tail showed increased measures of centrality, segregation, and integration, while nodes in the left amygdala showed decreased measures of centrality, segregation, and integration in patients with MDD compared with HCs.

Conclusion

Our results provide the first evidence of atypical topologic characteristics within the hippocampus-amygdala complex in patients with MDD using structure network analysis. It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.

Instructions and experiential learning have similar impacts on pain and pain-related brain responses but produce dissociations in value-based reversal learning

Recent data suggest that interactions between systems involved in higher order knowledge and associative learning drive responses during value-based learning. However, it is unknown how these systems impact subjective responses, such as pain. We tested how instructions and reversal learning influence pain and pain-evoked brain activation. Healthy volunteers (n=40) were either instructed about contingencies between cues and aversive outcomes or learned through experience in a paradigm where contingencies reversed three times. We measured predictive cue effects on pain and heat-evoked brain responses using functional magnetic resonance imaging. Predictive cues dynamically modulated pain perception as contingencies changed, regardless of whether participants received contingency instructions. Heat-evoked responses in the insula, anterior cingulate, and other regions updated as contingencies changed, and responses in the prefrontal cortex mediated dynamic cue effects on pain, whereas responses in the brainstem's rostroventral medulla (RVM) were shaped by initial contingencies throughout the task. Quantitative modeling revealed that expected value was shaped purely by instructions in the Instructed Group, whereas expected value updated dynamically in the Uninstructed Group as a function of error-based learning. These differences were accompanied by dissociations in the neural correlates of value-based learning in the rostral anterior cingulate, thalamus, and posterior insula, among other regions. These results show how predictions dynamically impact subjective pain. Moreover, imaging data delineate three types of networks involved in pain generation and value-based learning: those that respond to initial contingencies, those that update dynamically during feedback-driven learning as contingencies change, and those that are sensitive to instruction. Together, these findings provide multiple points of entry for therapies designs to impact pain.

Asymmetric representation of aversive prediction errors in Pavlovian threat conditioning

Survival in biological environments requires learning associations between predictive sensory cues and threatening outcomes. Such aversive learning may be implemented through reinforcement learning algorithms that are driven by the signed difference between expected and encountered outcomes, termed prediction errors (PEs). While PE-based learning is well established for reward learning, the role of putative PE signals in aversive learning is less clear. Here, we used functional magnetic resonance imaging in humans (21 healthy men and women) to investigate the neural representation of PEs during maintenance of learned aversive associations. Four visual cues, each with a different probability (0, 33, 66, 100%) of being followed by an aversive outcome (electric shock), were repeatedly presented to participants. We found that neural activity at omission (US-) but not occurrence of the aversive outcome (US+) encoded PEs in the medial prefrontal cortex. More expected omission of aversive outcome was associated with lower neural activity. No neural signals fulfilled axiomatic criteria, which specify necessary and sufficient components of PE signals, for signed PE representation in a whole-brain search or in a-priori regions of interest. Our results might suggest that, different from reward learning, aversive learning does not involve signed PE signals that are represented within the same brain region for all conditions.

The computational relationship between reinforcement learning, social inference, and paranoia

Theoretical accounts suggest heightened uncertainty about the state of the world underpin aberrant belief updates, which in turn increase the risk of developing a persecutory delusion. However, this raises the question as to how an agent's uncertainty may relate to the precise phenomenology of paranoia, as opposed to other qualitatively different forms of belief. We tested whether the same population (n = 693) responded similarly to non-social and social contingency changes in a probabilistic reversal learning task and a modified repeated reversal Dictator game, and the impact of paranoia on both. We fitted computational models that included closely related parameters that quantified the rigidity across contingency reversals and the uncertainty about the environment/partner. Consistent with prior work we show that paranoia was associated with uncertainty around a partner's behavioural policy and rigidity in harmful intent attributions in the social task. In the non-social task we found that pre-existing paranoia was associated with larger decision temperatures and commitment to suboptimal cards. We show relationships between decision temperature in the non-social task and priors over harmful intent attributions and uncertainty over beliefs about partners in the social task. Our results converge across both classes of model, suggesting paranoia is associated with a general uncertainty over the state of the world (and agents within it) that takes longer to resolve, although we demonstrate that this uncertainty is expressed asymmetrically in social contexts. Our model and data allow the representation of sociocognitive mechanisms that explain persecutory delusions and provide testable, phenomenologically relevant predictions for causal experiments.

Temporally and anatomically specific contributions of the human amygdala to threat and safety learning

Neural plasticity in subareas of the rodent amygdala is widely known to be essential for Pavlovian threat conditioning and safety learning. However, less consistent results have been observed in human neuroimaging studies. Here, we identify and test three important factors that may contribute to these discrepancies: the temporal profile of amygdala response in threat conditioning, the anatomical specificity of amygdala responses during threat conditioning and safety learning, and insufficient power to identify these responses. We combined data across multiple studies using a well-validated human threat conditioning paradigm to examine amygdala involvement during threat conditioning and safety learning. In 601 humans, we show that two amygdala subregions tracked the conditioned stimulus with aversive shock during early conditioning while only one demonstrated delayed responding to a stimulus not paired with shock. Our findings identify cross-species similarities in temporal- and anatomical-specific amygdala contributions to threat and safety learning, affirm human amygdala involvement in associative learning and highlight important factors for future associative learning research in humans.

The human insula processes both modality-independent and pain-selective learning signals

Prediction errors (PEs) are generated when there are differences between an expected and an actual event or sensory input. The insula is a key brain region involved in pain processing, and studies have shown that the insula encodes the magnitude of an unexpected outcome (unsigned PEs). In addition to signaling this general magnitude information, PEs can give specific information on the direction of this deviation-i.e., whether an event is better or worse than expected. It is unclear whether the unsigned PE responses in the insula are selective for pain or reflective of a more general processing of aversive events irrespective of modality. It is also unknown whether the insula can process signed PEs at all. Understanding these specific mechanisms has implications for understanding how pain is processed in the brain in both health and in chronic pain conditions. In this study, 47 participants learned associations between 2 conditioned stimuli (CS) with 4 unconditioned stimuli (US; painful heat or loud sound, of one low and one high intensity each) while undergoing functional magnetic resonance imaging (fMRI) and skin conductance response (SCR) measurements. We demonstrate that activation in the anterior insula correlated with unsigned intensity PEs, irrespective of modality, indicating an unspecific aversive surprise signal. Conversely, signed intensity PE signals were modality specific, with signed PEs following pain but not sound located in the dorsal posterior insula, an area implicated in pain intensity processing. Previous studies have identified abnormal insula function and abnormal learning as potential causes of pain chronification. Our findings link these results and suggest that a misrepresentation of learning relevant PEs in the insular cortex may serve as an underlying factor in chronic pain.

Value estimation and latent-state update-related neural activity during fear conditioning predict posttraumatic stress disorder symptom severity

Learning theories of posttraumatic stress disorder (PTSD) purport that fear-learning processes, such as those that support fear acquisition and extinction, are impaired. Computational models designed to capture specific processes involved in fear learning have primarily assessed model-free, or trial-and-error, reinforcement learning (RL). Although previous studies indicated that aspects of model-free RL are disrupted among individuals with PTSD, research has yet to identify whether model-based RL, which is inferential and contextually driven, is impaired. Given empirical evidence of aberrant contextual modulation of fear in PTSD, the present study sought to identify whether model-based RL processes are altered during fear conditioning among women with interpersonal violence (IPV)-related PTSD (n = 85) using computational modeling. Model-free, hybrid, and model-based RL models were applied to skin conductance responses (SCR) collected during fear acquisition and extinction, and the model-based RL model was found to provide the best fit to the SCR data. Parameters from the model-based RL model were carried forward to neuroimaging analyses (voxel-wise and independent component analysis). Results revealed that reduced activity within visual processing regions during model-based updating uniquely predicted higher PTSD symptoms. Additionally, after controlling for model-based updating, greater value estimation encoding within the left frontoparietal network during fear acquisition and reduced value estimation encoding within the dorsomedial prefrontal cortex during fear extinction predicted greater PTSD symptoms. Results provide evidence of disrupted RL processes in women with assault-related PTSD, which may contribute to impaired fear and safety learning, and, furthermore, may relate to treatment response (e.g., poorer response to exposure therapy).

L-DOPA modulates activity in the vmPFC, nucleus accumbens, and VTA during threat extinction learning in humans

Learning to be safe is central for adaptive behaviour when threats are no longer present. Detecting the absence of an expected threat is key for threat extinction learning and an essential process for the behavioural treatment of anxiety-related disorders. One possible mechanism underlying extinction learning is a dopaminergic mismatch signal that encodes the absence of an expected threat. Here we show that such a dopamine-related pathway underlies extinction learning in humans. Dopaminergic enhancement via administration of L-DOPA (vs. Placebo) was associated with reduced retention of differential psychophysiological threat responses at later test, which was mediated by activity in the ventromedial prefrontal cortex that was specific to extinction learning. L-DOPA administration enhanced signals at the time-point of an expected, but omitted threat in extinction learning within the nucleus accumbens, which were functionally coupled with the ventral tegmental area and the amygdala. Computational modelling of threat expectancies further revealed prediction error encoding in nucleus accumbens that was reduced when L-DOPA was administered. Our results thereby provide evidence that extinction learning is influenced by L-DOPA and provide a mechanistic perspective to augment extinction learning by dopaminergic enhancement in humans.

Approach-Avoidance Decisions Under Threat: The Role of Autonomic Psychophysiological States

Acutely challenging or threatening situations frequently require approach-avoidance decisions. Acute threat triggers fast autonomic changes that prepare the body to freeze, fight or flee. However, such autonomic changes may also influence subsequent instrumental approach-avoidance decisions. Since defensive bodily states are often not considered in value-based decision-making models, it remains unclear how they influence the decision-making process. Here, we aim to bridge this gap by discussing the existing literature on the potential role of threat-induced bodily states on decision making and provide a new neurocomputational framework explaining how these effects can facilitate or bias approach-avoid decisions under threat. Theoretical accounts have stated that threat-induced parasympathetic activity is involved in information gathering and decision making. Parasympathetic dominance over sympathetic activity is particularly seen during threat-anticipatory freezing, an evolutionarily conserved response to threat demonstrated across species and characterized by immobility and bradycardia. Although this state of freezing has been linked to altered information processing and action preparation, a full theoretical treatment of the interactions with value-based decision making has not yet been achieved. Our neural framework, which we term the Threat State/Value Integration (TSI) Model, will illustrate how threat-induced bodily states may impact valuation of competing incentives at three stages of the decision-making process, namely at threat evaluation, integration of rewards and threats, and action initiation. Additionally, because altered parasympathetic activity and decision biases have been shown in anxious populations, we will end with discussing how biases in this system can lead to characteristic patterns of avoidance seen in anxiety-related disorders, motivating future pre-clinical and clinical research.

Volumetric trajectories of hippocampal subfields and amygdala nuclei influenced by adolescent alcohol use and lifetime trauma

Alcohol use and exposure to psychological trauma frequently co-occur in adolescence and share many risk factors. Both exposures have deleterious effects on the brain during this sensitive developmental period, particularly on the hippocampus and amygdala. However, very little is known about the individual and interactive effects of trauma and alcohol exposure and their specific effects on functionally distinct substructures within the adolescent hippocampus and amygdala. Adolescents from a large longitudinal sample (N = 803, 2684 scans, 51% female, and 75% White/Caucasian) ranging in age from 12 to 21 years were interviewed about exposure to traumatic events at their baseline evaluation. Assessments for alcohol use and structural magnetic resonance imaging scans were completed at baseline and repeated annually to examine neurodevelopmental trajectories. Hippocampal and amygdala subregions were segmented using Freesurfer v6.0 tools, followed by volumetric analysis with generalized additive mixed models. Longitudinal statistical models examined the effects of cumulative lifetime trauma measured at baseline and alcohol use measured annually on trajectories of hippocampal and amygdala subregions, while controlling for covariates known to impact brain development. Greater alcohol use, quantified using the Cahalan scale and measured annually, was associated with smaller whole hippocampus (β = -12.0, p_FDR = 0.009) and left hippocampus tail volumes (β = -1.2, p_FDR = 0.048), and larger right CA3 head (β = 0.4, p_FDR = 0.027) and left subiculum (β = 0.7, p_FDR = 0.046) volumes of the hippocampus. In the amygdala, greater alcohol use was associated with larger right basal nucleus volume (β = 1.3, p_FDR = 0.040). The effect of traumatic life events measured at baseline was associated with larger right CA3 head volume (β = 1.3, p_FDR = 0.041) in the hippocampus. We observed an interaction between baseline trauma and within-person age change where younger adolescents with greater trauma exposure at baseline had smaller left hippocampal subfield volumes in the subiculum (β = 0.3, p_FDR = 0.029) and molecular layer HP head (β = 0.3, p_FDR = 0.041). The interaction also revealed that older adolescents with greater trauma exposure at baseline had larger right amygdala nucleus volume in the paralaminar nucleus (β = 0.1, p_FDR = 0.045), yet smaller whole amygdala volume overall (β = -3.7, p_FDR = 0.003). Lastly, we observed an interaction between alcohol use and baseline trauma such that adolescents who reported greater alcohol use with greater baseline trauma showed smaller right hippocampal subfield volumes in the CA1 head (β = -1.1, p_FDR = 0.011) and hippocampal head (β = -2.6, p_FDR = 0.025), yet larger whole hippocampus volume overall (β = 10.0, p_FDR = 0.032). Cumulative lifetime trauma measured at baseline and alcohol use measured annually interact to affect the volume and trajectory of hippocampal and amygdala substructures (measured via structural MRI annually), regions that are essential for emotion regulation and memory. Our findings demonstrate the value of examining these substructures and support the hypothesis that the amygdala and hippocampus are not homogeneous brain regions.

Bilateral amygdala damage linked to impaired ability to predict others' fear but preserved moral judgements about causing others fear

The amygdala is a subcortical structure implicated in both the expression of conditioned fear and social fear recognition. Social fear recognition deficits following amygdala lesions are often interpreted as reflecting perceptual deficits, or the amygdala's role in coordinating responses to threats. But these explanations fail to capture why amygdala lesions impair both physiological and behavioural responses to multimodal fear cues and the ability to identify them. We hypothesized that social fear recognition deficits following amygdala damage reflect impaired conceptual understanding of fear. Supporting this prediction, we found specific impairments in the ability to predict others' fear (but not other emotions) from written scenarios following bilateral amygdala lesions. This finding is consistent with the suggestion that social fear recognition, much like social recognition of states like pain, relies on shared internal representations. Preserved judgements about the permissibility of causing others fear confirms suggestions that social emotion recognition and morality are dissociable.

Fear-induced brain activations distinguish anxious and trauma-exposed brains

Translational models of fear conditioning and extinction have elucidated a core neural network involved in the learning, consolidation, and expression of conditioned fear and its extinction. Anxious or trauma-exposed brains are characterized by dysregulated neural activations within regions of this fear network. In this study, we examined how the functional MRI activations of 10 brain regions commonly activated during fear conditioning and extinction might distinguish anxious or trauma-exposed brains from controls. To achieve this, activations during four phases of a fear conditioning and extinction paradigm in 304 participants with or without a psychiatric diagnosis were studied. By training convolutional neural networks (CNNs) using task-specific brain activations, we reliably distinguished the anxious and trauma-exposed brains from controls. The performance of models decreased significantly when we trained our CNN using activations from task-irrelevant brain regions or from a brain network that is irrelevant to fear. Our results suggest that neuroimaging data analytics of task-induced brain activations within the fear network might provide novel prospects for development of brain-based psychiatric diagnosis.

Uncertainty-driven regulation of learning and exploration in adolescents: A computational account

Healthy adults flexibly adapt their learning strategies to ongoing changes in uncertainty, a key feature of adaptive behaviour. However, the developmental trajectory of this ability is yet unknown, as developmental studies have not incorporated trial-to-trial variation in uncertainty in their analyses or models. To address this issue, we compared adolescents’ and adults’ trial-to-trial dynamics of uncertainty, learning rate, and exploration in two tasks that assess learning in noisy but otherwise stable environments. In an estimation task—which provides direct indices of trial-specific learning rate—both age groups reduced their learning rate over time, as self-reported uncertainty decreased. Accordingly, the estimation data in both groups was better explained by a Bayesian model with dynamic learning rate (Kalman filter) than by conventional reinforcement-learning models. Furthermore, adolescents’ learning rates asymptoted at a higher level, reflecting an over-weighting of the most recent outcome, and the estimated Kalman-filter parameters suggested that this was due to an overestimation of environmental volatility. In a choice task, both age groups became more likely to choose the higher-valued option over time, but this increase in choice accuracy was smaller in the adolescents. In contrast to the estimation task, we found no evidence for a Bayesian expectation-updating process in the choice task, suggesting that estimation and choice tasks engage different learning processes. However, our modeling results of the choice task suggested that both age groups reduced their degree of exploration over time, and that the adolescents explored overall more than the adults. Finally, age-related differences in exploration parameters from fits to the choice data were mediated by participants’ volatility parameter from fits to the estimation data. Together, these results suggest that adolescents overestimate the rate of environmental change, resulting in elevated learning rates and increased exploration, which may help understand developmental changes in learning and decision-making.

To successfully learn the value of stimuli and actions, people should take into account their current (un)certainty about these values: Learning rates and exploration should be high when one’s value estimates are highly uncertain (in the beginning of learning), and decrease over time as evidence accumulates and uncertainty decreases. Recent studies have shown that healthy adults flexibly adapt their learning strategies based on ongoing changes in uncertainty, consistent with normative learning. However, the development of this ability prior to adulthood is yet unknown, as developmental learning studies have not considered trial-to-trial changes in uncertainty. Here, we show that adolescents, as compared to adults, showed a smaller decrease in both learning rate and exploration over time. Computational modeling revealed that both of these effects were due to adolescents overestimating the amount of environmental volatility, which made them more sensitive to recent relative to older evidence. The overestimation of volatility during adolescence may represent the rapidly changing environmental demands during this developmental period, and can help understand the surge in real-life risk taking and exploratory behaviours characteristic of adolescents.

Anatomic alterations across amygdala subnuclei in medication-free patients with obsessive-compulsive disorder

BACKGROUND

The amygdala has been implicated in obsessive-compulsive disorder (OCD), a common, disabling illness. However, the regional distribution of anatomic alterations in this structure and their association with the symptoms of OCD remains to be established.

METHODS

We collected high-resolution 3D T1-weighted images from 81 untreated patients with OCD and no lifetime history of comorbid psychotic, affective or anxiety disorders, and from 95 age- and sex-matched healthy controls. We extracted the volume of the central nucleus of the amygdala (CeA) and the basolateral complex of the amygdala (BLA) and compared them across groups using FreeSurfer 6.0. In exploratory analyses, we evaluated other subnuclei, including the cortical medial nuclei, the anterior amygdaloid area, and the corticoamygdaloid transition area.

RESULTS

Patients with OCD had reduced amygdala volume bilaterally compared with healthy controls (left, p = 0.034; right, p = 0.002). Volume reductions were greater in the CeA (left: -11.9%, p = 0.002; right: -13.3%, p < 0.001) than in the BLA (left lateral nucleus: -3.3%, p = 0.029; right lateral nucleus: -3.9%, p = 0.018; right basal nucleus: -4.1%, p = 0.017; left accessory basal nucleus: -6.5%, p = 0.001; right accessory basal nucleus: -9.3%, p < 0.001). Volume reductions in the CeA were associated with illness duration. Exploratory analysis revealed smaller medial (left: -15.4%, p < 0.001, η2 = 0.101) and cortical (left: -9.1%, p = 0.001, η2 = 0.058; right: -15.4%, p < 0.001, η2 = 0.175) nuclei in patients with OCD compared with healthy controls.

LIMITATIONS

Although the strict exclusion criteria used in the study helped us to identify OCD-specific alterations, they may have limited generalizability to the broader OCD population.

CONCLUSION

Our results provide a comprehensive anatomic profile of alterations in the amygdala subnuclei in untreated patients with OCD and highlight a distinctive pattern of volume reductions across subnuclei in OCD. Based on the functional properties of the amygdala subnuclei established from preclinical research, CeA impairment may contribute to behavioural inflexibility, and BLA disruption may be responsible for altered fear conditioning and the affective components of OCD.

Acute and Post-Traumatic Stress Disorders: A biased nervous system

Acute stress disorder and post-traumatic stress disorder are generally triggered by an exceptionally intense threat. The consequences of this traumatogenic situation are explored here in chronological order, from exposure to the threat to development of symptoms. Such a situation may disrupt the equilibrium between two fundamental brain circuits, referred to as the "defensive" and "cognitive". The defensive circuit triggers the stress response as well as the formation of implicit memory. The cognitive circuit triggers the voluntary response and the formation of explicit autobiographical memory. During a traumatogenic situation, the defensive circuit could be over-activated while cognitive circuit is under-activated. In the most severe cases, overactivation of the defensive circuit may cause its brutal deactivation, resulting in dissociation. Here, we address the underlying neurobiological mechanisms at every scale: from neurons to behaviors, providing a detailed explanatory model of trauma.

A learning theory of attachment: Unraveling the black box of attachment development

Attachment is an inborn behavioral system that is biologically driven and essential for survival. During child development, individual differences in (in)secure attachment emerge. The development of different attachment behaviors has been traditionally explained as a process during which experiences with (lack of) responsive and supportive care are internalized into working models of attachment. However, this idea has been criticized for being vague and even untestable. With the aim of unraveling this black box, we propose to integrate evidence from conditioning research with attachment theory to formulate a Learning Theory of Attachment. In this review, we explain how the development of individual differences in attachment security at least partly follows the principles of classical and operant conditioning. We combine observed associations between attachment and neurocognitive and endocrinological (cortisol, oxytocin, and dopamine) processes with insights in conditioning dynamics to explain the development of attachment. This may contribute to the explanation of empirical observations in attachment research that are insufficiently accounted for by traditional attachment theory.

Reduced safety processing during aversive social conditioning in psychosis and clinical risk

Social impairment occurs across the psychosis spectrum, but its pathophysiology remains poorly understood. Here we tested the hypothesis that reduced differential responses (aversive vs. neutral) in neural circuitry underpinning aversive conditioning of social stimuli characterizes the psychosis spectrum. Participants age 10-30 included a healthy control group (HC, analyzed n = 36) and a psychosis spectrum group (PSY, n = 71), including 49 at clinical risk for psychosis and 22 with a frank psychotic disorder. 3T fMRI utilized a passive aversive conditioning paradigm, with neutral faces as conditioned stimuli (CS) and a scream as the unconditioned stimulus. fMRI conditioning was indexed as the activation difference between aversive and neutral trials. Analysis focused on amygdala, ventromedial prefrontal cortex, and anterior insula, regions previously implicated in aversive and social-emotional processing. Ventromedial prefrontal cortex activated more to neutral than aversive CS; this "safety effect" was driven by HC and reduced in PSY, and correlated with subjective emotional ratings following conditioning. Insula showed the expected aversive conditioning effect, and although no group differences were found, its activation in PSY correlated with anxiety severity. Unexpectedly, amygdala did not show aversive conditioning; its activation trended greater for neutral than aversive CS, and did not differ significantly based on group or symptom severity. We conclude that abnormalities in social aversive conditioning are present across the psychosis spectrum including clinical risk, linked to a failure of safety processing. Aversive and safety learning provide translational paradigms yielding insight into pathophysiology of psychosis risk, and providing potential targets for therapeutic and preventative interventions.

Pain: A Precision Signal for Reinforcement Learning and Control

Since noxious stimulation usually leads to the perception of pain, pain has traditionally been considered sensory nociception. But its variability and sensitivity to a broad array of cognitive and motivational factors have meant it is commonly viewed as inherently imprecise and intangibly subjective. However, the core function of pain is motivational-to direct both short- and long-term behavior away from harm. Here, we illustrate that a reinforcement learning model of pain offers a mechanistic understanding of how the brain supports this, illustrating the underlying computational architecture of the pain system. Importantly, it explains why pain is tuned by multiple factors and necessarily supported by a distributed network of brain regions, recasting pain as a precise and objectifiable control signal.

A computational account of threat-related attentional bias

Visual selective attention acts as a filter on perceptual information, facilitating learning and inference about important events in an agent's environment. A role for visual attention in reward-based decisions has previously been demonstrated, but it remains unclear how visual attention is recruited during aversive learning, particularly when learning about multiple stimuli concurrently. This question is of particular importance in psychopathology, where enhanced attention to threat is a putative feature of pathological anxiety. Using an aversive reversal learning task that required subjects to learn, and exploit, predictions about multiple stimuli, we show that the allocation of visual attention is influenced significantly by aversive value but not by uncertainty. Moreover, this relationship is bidirectional in that attention biases value updates for attended stimuli, resulting in heightened value estimates. Our findings have implications for understanding biased attention in psychopathology and support a role for learning in the expression of threat-related attentional biases in anxiety.

The cerebellum is involved in processing of predictions and prediction errors in a fear conditioning paradigm

Prediction errors are thought to drive associative fear learning. Surprisingly little is known about the possible contribution of the cerebellum. To address this question, healthy participants underwent a differential fear conditioning paradigm during 7T magnetic resonance imaging. An event-related design allowed us to separate cerebellar fMRI signals related to the visual conditioned stimulus (CS) from signals related to the subsequent unconditioned stimulus (US; an aversive electric shock). We found significant activation of cerebellar lobules Crus I and VI bilaterally related to the CS+ compared to the CS-. Most importantly, significant activation of lobules Crus I and VI was also present during the unexpected omission of the US in unreinforced CS+ acquisition trials. This activation disappeared during extinction when US omission became expected. These findings provide evidence that the cerebellum has to be added to the neural network processing predictions and prediction errors in the emotional domain.

Distinct Processing of Aversive Experience in Amygdala Subregions

Background

The amygdala is an anatomically complex medial temporal brain structure whose subregions are considered to serve distinct functions. However, their precise role in mediating human aversive experience remains ill understood.

Methods

We used functional magnetic resonance imaging in 39 healthy volunteers with varying levels of trait anxiety to assess distinct contributions of the basolateral amygdala (BLA) and centromedial amygdala to anticipation and experience of aversive events. Additionally, we examined the relationship between any identified functional subspecialization and measures of subjective reported aversion and trait anxiety.

Results

Our results show that the centromedial amygdala is responsive to aversive outcomes but insensitive to predictive aversive cues. In contrast, the BLA encodes an aversive prediction error that quantifies whether cues and outcomes are worse than expected. A neural representation within the BLA for distinct threat levels was mirrored in self-reported subjective anxiety across individuals. Furthermore, high trait-anxious individuals were characterized by indiscriminately heightened BLA activity in response to aversive cues, regardless of actual threat level.

Conclusions

Our results demonstrate that amygdala subregions are distinctly engaged in processing of aversive experience, with elevated and undifferentiated BLA responses to threat emerging as a potential neurobiological mediator of vulnerability to anxiety disorders.

An Integrative Way for Studying Neural Basis of Basic Emotions With fMRI

How emotions are represented in the nervous system is a crucial unsolved problem in the affective neuroscience. Many studies are striving to find the localization of basic emotions in the brain but failed. Thus, many psychologists suspect the specific neural loci for basic emotions, but instead, some proposed that there are specific neural structures for the core affects, such as arousal and hedonic value. The reason for this widespread difference might be that basic emotions used previously can be further divided into more “basic” emotions. Here we review brain imaging data and neuropsychological data, and try to address this question with an integrative model. In this model, we argue that basic emotions are not contrary to the dimensional studies of emotions (core affects). We propose that basic emotion should locate on the axis in the dimensions of emotion, and only represent one typical core affect (arousal or valence). Therefore, we propose four basic emotions: joy-on positive axis of hedonic dimension, sadness-on negative axis of hedonic dimension, fear, and anger-on the top of vertical dimensions. This new model about basic emotions and construction model of emotions is promising to improve and reformulate neurobiological models of basic emotions.

Role of Human Ventromedial Prefrontal Cortex in Learning and Recall of Enhanced Extinction

Standard fear extinction relies on the ventromedial prefrontal cortex (vmPFC) to form a new memory given the omission of threat. Using fMRI in humans, we investigated whether replacing threat with novel neutral outcomes (instead of just omitting threat) facilitates extinction by engaging the vmPFC more effectively than standard extinction. Computational modeling of associability (indexing surprise strength and dynamically modulating learning rates) characterized skin conductance responses and vmPFC activity during novelty-facilitated but not standard extinction. Subjects who showed faster within-session updating of associability during novelty-facilitated extinction also expressed better extinction retention the next day, as expressed through skin conductance responses. Finally, separable patterns of connectivity between the amygdala and ventral versus dorsal mPFC characterized retrieval of novelty-facilitated versus standard extinction memories, respectively. These results indicate that replacing threat with novel outcomes stimulates vmPFC involvement on extinction trials, leading to a more durable long-term extinction memory.SIGNIFICANCE STATEMENT Psychiatric disorders characterized be excessive fear are a major public health concern. Popular clinical treatments, such as exposure therapy, are informed by principles of Pavlovian extinction. Thus, there is motivation to optimize extinction strategies in the laboratory so as to ultimately develop more effective clinical treatments. Here, we used functional neuroimaging in humans and found that replacing (rather than just omitting) expected aversive events with novel and neutral outcomes engages the ventromedial prefrontal cortex during extinction learning. Enhanced extinction also diminished activity in threat-related networks (e.g., the insula, thalamus) during immediate extinction and a 24 h extinction retention test. This is new evidence for how behavioral protocols designed to enhance extinction affects neurocircuitry underlying the learning and retention of extinction memories.

Financial gain- and loss-related BOLD signals in the human ventral tegmental area and substantia nigra pars compacta

Neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNC) play central roles in reward-related behaviours. Nonhuman animal studies suggest that these neurons also process aversive events. However, our understanding of how the human VTA and SNC responds to such events is limited and has been hindered by the technical challenge of using functional magnetic resonance imaging (fMRI) to investigate a small structure where the signal is particularly vulnerable to physiological noise. Here we show, using methods optimized specifically for the midbrain (including high-resolution imaging, a novel registration protocol, and physiological noise modelling), a BOLD (blood-oxygen-level dependent) signal to both financial gain and loss in the VTA and SNC, along with a response to nil outcomes that are better or worse than expected in the VTA. Taken together, these findings suggest that the human VTA and SNC are involved in the processing of both appetitive and aversive financial outcomes in humans.

Human Pavlovian fear conditioning conforms to probabilistic learning

Learning to predict threat from environmental cues is a fundamental skill in changing environments. This aversive learning process is exemplified by Pavlovian threat conditioning. Despite a plethora of studies on the neural mechanisms supporting the formation of associations between neutral and aversive events, our computational understanding of this process is fragmented. Importantly, different computational models give rise to different and partly opposing predictions for the trial-by-trial dynamics of learning, for example expressed in the activity of the autonomic nervous system (ANS). Here, we investigate human ANS responses to conditioned stimuli during Pavlovian fear conditioning. To obtain precise, trial-by-trial, single-subject estimates of ANS responses, we build on a statistical framework for psychophysiological modelling. We then consider previously proposed non-probabilistic models, a simple probabilistic model, and non-learning models, as well as different observation functions to link learning models with ANS activity. Across three experiments, and both for skin conductance (SCR) and pupil size responses (PSR), a probabilistic learning model best explains ANS responses. Notably, SCR and PSR reflect different quantities of the same model: SCR track a mixture of expected outcome and uncertainty, while PSR track expected outcome alone. In summary, by combining psychophysiological modelling with computational learning theory, we provide systematic evidence that the formation and maintenance of Pavlovian threat predictions in humans may rely on probabilistic inference and includes estimation of uncertainty. This could inform theories of neural implementation of aversive learning.

Memory Beliefs Drive the Memory Bias on Value-based Decisions

For many value-based decisions, people need to retrieve relevant information from their memory. In our previous work, we have shown that memory biases decisions in the sense that better-memorized choice options are preferred, even if these options are comparatively unattractive. However, the cognitive mechanisms that drive this memory bias remain unclear. In the current pre-registered study, we tested the hypothesis that the memory bias arises because people believe they remember better options more often than worse options. Specifically, we predicted a positive correlation between the memory bias on value-based decisions and the belief in value-dependent memory performance. This prediction was confirmed. Additional exploratory analyses revealed that memory performance was indeed higher for more attractive options, indicating that letting decisions be influenced by memory can be an adaptive strategy. However, the memory bias persisted after correcting for this effect, suggesting that it is not simply an artifact of unequal memory performance. Our results highlight a critical influence of beliefs on behavior and add to an emerging understanding of the role of memory in shaping value-based decisions.

Pain-Related Expectation and Prediction Error Signals in the Anterior Insula Are Not Related to Aversiveness

The anterior insula has repeatedly been linked to the experience of aversive stimuli, such as pain. Previously, we showed that the anterior insula is involved in the integration of pain intensity and its prior expectation. However, it is unclear whether this integration occurs by a pain-specific expectation or a more general expectation of an aversive event. To dissociate these possibilities, we conducted an experiment using painful stimuli and aversive pictures with three levels of aversiveness on human male volunteers. Stimuli were preceded by a probabilistic, combined modality and intensity cue in a full factorial design. Subjective ratings of pain intensity and skin conductance responses were best explained by a combination of actual pain intensity and expected pain intensity. In addition, using fMRI, we investigated the neuronal implementation of the integration of prior expectation and pain intensity. Similar to subjective ratings and autonomic responses, the dorsal anterior insula represented pain intensity and expectations. The ventral anterior insula additionally represented the absolute difference of the two terms (i.e., the prediction error). The posterior insula only represented pain intensity. Importantly, the pattern observed in the anterior insula was only present if the cued modality was correct (i.e., expect pain); in case of an incorrect modality cue (i.e., expect aversive picture), the ventral anterior insula simply represented pain intensity. The stimulus expectation and prediction error specificity in the ventral anterior insula indicates the integration of expectation with painful stimuli in this area. Importantly, this pattern cannot be explained by aversiveness.SIGNIFICANCE STATEMENT The anterior insula has been shown to integrate pain intensity and their expectation. However, it is unclear whether this integration is pain-specific or related more generally to an aversive event. To address this, we combined painful stimuli and aversive pictures with three levels of aversiveness. The ventral anterior insula represented pain intensity, expectation, and their absolute difference (i.e., the prediction error). Importantly, this pattern was only observed if the cued modality was correct. In case of an incorrect modality cue, this area simply represented as pain intensity. The stimulus expectation and prediction error specificity in the ventral anterior insula indicates the integration of expectation with painful stimuli in this area. Importantly, this pattern cannot be explained by aversiveness.

Hypervigilance during anxiety and selective attention during fear: Using steady-state visual evoked potentials (ssVEPs) to disentangle attention mechanisms during predictable and unpredictable threat

Anxiety is induced by unpredictable threat, and presumably characterized by enhanced vigilance. In contrast, fear is elicited by imminent threat, and leads to phasic responses with selective attention. In order to investigate attention mechanisms and defensive responding during fear and anxiety, we employed an adaptation of the NPU-threat test and measured cortical (steady-state visual evoked potentials, ssVEPs), physiological (heart rate, HR), and subjective responses (ratings) to predictable (fear-related) and unpredictable (anxiety-related) threat in 42 healthy participants. An aversive unconditioned stimulus (US, loud noise) was 100% predicted by a cue (predictable P-cue) in one context (predictable P-context), but appeared unpredictably within a different context (unpredictable U-context, U-cue), while it was never delivered in a neutral safe context (N-cue, N- context). In response to predictable threat (P-cue), increased ssVEP amplitudes and accelerated HR were found. Both predictable and unpredictable contexts yielded increased ssVEP amplitudes compared to the safe context. Interestingly, in the unpredictable context participants showed longer-lasting visuocortical activation than in the predictable context, supporting the notion of heightened vigilance during anxiety. In parallel, HR decelerated to both threat contexts indicating fear bradycardia to these threatening contexts as compared to the safe context. These results support the idea of hypervigilance in anxiety-like situations reflected in a long-lasting facilitated processing of sensory information, in contrast to increased selective attention to specific imminent threat during fear. Thus, this study further supports the defense-cascade model with vigilance and orienting in the post-encounter phase of threat (anxiety), while selective attention and defensive mobilization in the circa-strike phase of threat (fear).

Learned expectations and uncertainty facilitate pain during classical conditioning

Pain spontaneously activates adaptive and dynamic learning processes affecting the anticipation of, and the responses to, future pain. Computational models of associative learning effectively capture the production and ongoing changes in conditioned anticipatory responses (eg, skin conductance response), but the impact of this dynamic process on unconditional pain responses remains poorly understood. Here, we investigated the dynamic modulation of pain and the nociceptive flexion reflex by fear learning in healthy human adult participants undergoing a classical conditioning procedure involving an acquisition, reversal and extinction phase. Conditioned visual stimuli (CS+) coterminated with a noxious transcutaneous stimulation applied to the sural nerve on 50% of trials (unconditioned stimuli). Expected pain probabilities and cue associability were estimated using computational modeling by fitting a hybrid learning model to skin conductance response elicited by the CS+. Multilevel linear regression analyses confirmed that trial-by-trial changes in expected pain and associability positively predict ongoing fluctuations in pain outcomes. Mediation analysis further demonstrated that both expected probability and associability affect pain perception through a direct effect and an indirect effect mediated by descending modulatory mechanisms affecting spinal nociceptive activity. Moderation analyses further showed that hyperalgesic effects of associability were larger in individuals reporting more harm vigilance and less emotional detachment. Higher harm vigilance was also associated with a stronger mediation of hyperalgesic effects by spinal processes. These results demonstrate how dynamic changes in pain can be explained by associative learning theory and that resilient attitudes towards fear/pain can attenuate the adverse impact of adaptive aversive learning processes on pain.

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

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

The control of tonic pain by active relief learning

Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty ('associability') signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief.

Associability-modulated loss learning is increased in posttraumatic stress disorder

Disproportionate reactions to unexpected stimuli in the environment are a cardinal symptom of posttraumatic stress disorder (PTSD). Here, we test whether these heightened responses are associated with disruptions in distinct components of reinforcement learning. Specifically, using functional neuroimaging, a loss-learning task, and a computational model-based approach, we assessed the mechanistic hypothesis that overreactions to stimuli in PTSD arise from anomalous gating of attention during learning (i.e., associability). Behavioral choices of combat-deployed veterans with and without PTSD were fit to a reinforcement learning model, generating trial-by-trial prediction errors (signaling unexpected outcomes) and associability values (signaling attention allocation to the unexpected outcomes). Neural substrates of associability value and behavioral parameter estimates of associability updating, but not prediction error, increased with PTSD during loss learning. Moreover, the interaction of PTSD severity with neural markers of associability value predicted behavioral choices. These results indicate that increased attention-based learning may underlie aspects of PTSD and suggest potential neuromechanistic treatment targets.

A common neural network differentially mediates direct and social fear learning

Across species, fears often spread between individuals through social learning. Yet, little is known about the neural and computational mechanisms underlying social learning. Addressing this question, we compared social and direct (Pavlovian) fear learning showing that they showed indistinguishable behavioral effects, and involved the same cross-modal (self/other) aversive learning network, centered on the amygdala, the anterior insula (AI), and the anterior cingulate cortex (ACC). Crucially, the information flow within this network differed between social and direct fear learning. Dynamic causal modeling combined with reinforcement learning modeling revealed that the amygdala and AI provided input to this network during direct and social learning, respectively. Furthermore, the AI gated learning signals based on surprise (associability), which were conveyed to the ACC, in both learning modalities. Our findings provide insights into the mechanisms underlying social fear learning, with implications for understanding common psychological dysfunctions, such as phobias and other anxiety disorders.

Functional dissociation of stimulus intensity encoding and predictive coding of pain in the insula

The computational principles by which the brain creates a painful experience from nociception are still unknown. Classic theories suggest that cortical regions either reflect stimulus intensity or additive effects of intensity and expectations, respectively. By contrast, predictive coding theories provide a unified framework explaining how perception is shaped by the integration of beliefs about the world with mismatches resulting from the comparison of these beliefs against sensory input. Using functional magnetic resonance imaging during a probabilistic heat pain paradigm, we investigated which computations underlie pain perception. Skin conductance, pupil dilation, and anterior insula responses to cued pain stimuli strictly followed the response patterns hypothesized by the predictive coding model, whereas posterior insula encoded stimulus intensity. This novel functional dissociation of pain processing within the insula together with previously observed alterations in chronic pain offer a novel interpretation of aberrant pain processing as disturbed weighting of predictions and prediction errors.

In vivo quantification of amygdala subnuclei using 4.7 T fast spin echo imaging

The amygdala (AG) is an almond-shaped heterogeneous structure located in the medial temporal lobe. The majority of previous structural Magnetic Resonance Imaging (MRI) volumetric methods for AG measurement have so far only been able to examine this region as a whole. In order to understand the role of the AG in different neuropsychiatric disorders, it is necessary to understand the functional role of its subnuclei. The main goal of the present study was to develop a reliable volumetric method to delineate major AG subnuclei groups using ultra-high resolution high field MRI. 38 healthy volunteers (15 males and 23 females, 21-60 years of age) without any history of medical or neuropsychiatric disorders were recruited for this study. Structural MRI datasets were acquired at 4.7 T Varian Inova MRI system using a fast spin echo (FSE) sequence. The AG was manually segmented into its five major anatomical subdivisions: lateral (La), basal (B), accessory basal (AB) nuclei, and cortical (Co) and centromedial (CeM) groups. Inter-(intra-) rater reliability of our novel volumetric method was assessed using intra-class correlation coefficient (ICC) and Dice's Kappa. Our results suggest that reliable measurements of the AG subnuclei can be obtained by image analysts with experience in AG anatomy. We provided a step-by-step segmentation protocol and reported absolute and relative volumes for the AG subnuclei. Our results showed that the basolateral (BLA) complex occupies seventy-eight percent of the total AG volume, while CeM and Co groups occupy twenty-two percent of the total AG volume. Finally, we observed no hemispheric effects and no gender differences in the total AG volume and the volumes of its subnuclei. Future applications of this method will help to understand the selective vulnerability of the AG subnuclei in neurological and psychiatric disorders.

Connectivity between the central nucleus of the amygdala and the bed nucleus of the stria terminalis in the non-human primate: neuronal tract tracing and developmental neuroimaging studies

The lateral division of the bed nucleus of the stria terminalis (BSTL) and central nucleus of the amygdala (Ce) form the two poles of the 'central extended amygdala', a theorized subcortical macrostructure important in threat-related processing. Our previous work in nonhuman primates, and humans, demonstrating strong resting fMRI connectivity between the Ce and BSTL regions, provides evidence for the integrated activity of these structures. To further understand the anatomical substrates that underlie this coordinated function, and to investigate the integrity of the central extended amygdala early in life, we examined the intrinsic connectivity between the Ce and BSTL in non-human primates using ex vivo neuronal tract tracing, and in vivo diffusion-weighted imaging and resting fMRI techniques. The tracing studies revealed that BSTL receives strong input from Ce; however, the reciprocal pathway is less robust, implying that the primate Ce is a major modulator of BSTL function. The sublenticular extended amygdala (SLEAc) is strongly and reciprocally connected to both Ce and BSTL, potentially allowing the SLEAc to modulate information flow between the two structures. Longitudinal early-life structural imaging in a separate cohort of monkeys revealed that extended amygdala white matter pathways are in place as early as 3 weeks of age. Interestingly, resting functional connectivity between Ce and BSTL regions increases in coherence from 3 to 7 weeks of age. Taken together, these findings demonstrate a time period during which information flow between Ce and BSTL undergoes postnatal developmental changes likely via direct Ce → BSTL and/or Ce ↔ SLEAc ↔ BSTL projections.

Neural Activities Underlying the Feedback Express Salience Prediction Errors for Appetitive and Aversive Stimuli

Feedback information is essential for us to adapt appropriately to the environment. The feedback-related negativity (FRN), a frontocentral negative deflection after the delivery of feedback, has been found to be larger for outcomes that are worse than expected, and it reflects a reward prediction error derived from the midbrain dopaminergic projections to the anterior cingulate cortex (ACC), as stated in reinforcement learning theory. In contrast, the prediction of response-outcome (PRO) model claims that the neural activity in the mediofrontal cortex (mPFC), especially the ACC, is sensitive to the violation of expectancy, irrespective of the valence of feedback. Additionally, increasing evidence has demonstrated significant activities in the striatum, anterior insula and occipital lobe for unexpected outcomes independently of their valence. Thus, the neural mechanism of the feedback remains under dispute. Here, we investigated the feedback with monetary reward and electrical pain shock in one task via functional magnetic resonance imaging. The results revealed significant prediction-error-related activities in the bilateral fusiform gyrus, right middle frontal gyrus and left cingulate gyrus for both money and pain. This implies that some regions underlying the feedback may signal a salience prediction error rather than a reward prediction error.

Racial stereotypes impair flexibility of emotional learning

Flexibility of associative learning can be revealed by establishing and then reversing cue-outcome discriminations. Here, we used functional MRI to examine whether neurobehavioral correlates of reversal-learning are impaired in White and Asian volunteers when initial learning involves fear-conditioning to a racial out-group. For one group, the picture of a Black male was initially paired with shock (threat) and a White male was unpaired (safe). For another group, the White male was a threat and the Black male was safe. These associations reversed midway through the task. Both groups initially discriminated threat from safety, as expressed through skin conductance responses (SCR) and activity in the insula, thalamus, midbrain and striatum. After reversal, the group initially conditioned to a Black male exhibited impaired reversal of SCRs to the new threat stimulus (White male), and impaired reversals in the striatum, anterior cingulate cortex, midbrain and thalamus. In contrast, the group initially conditioned to a White male showed successful reversal of SCRs and successful reversal in these brain regions toward the new threat. These findings provide new evidence that an aversive experience with a racial out-group member impairs the ability to flexibly and appropriately adjust fear expression towards a new threat in the environment.

Striatal structure and function predict individual biases in learning to avoid pain

Pain is an elemental inducer of avoidance. Here, we demonstrate that people differ in how they learn to avoid pain, with some individuals refraining from actions that resulted in painful outcomes, whereas others favor actions that helped prevent pain. These individual biases were best explained by differences in learning from outcome prediction errors and were associated with distinct forms of striatal responses to painful outcomes. Specifically, striatal responses to pain were modulated in a manner consistent with an aversive prediction error in individuals who learned predominantly from pain, whereas in individuals who learned predominantly from success in preventing pain, modulation was consistent with an appetitive prediction error. In contrast, striatal responses to success in preventing pain were consistent with an appetitive prediction error in both groups. Furthermore, variation in striatal structure, encompassing the region where pain prediction errors were expressed, predicted participants' predominant mode of learning, suggesting the observed learning biases may reflect stable individual traits. These results reveal functional and structural neural components underlying individual differences in avoidance learning, which may be important contributors to psychiatric disorders involving pathological harm avoidance behavior.

Abnormal brain activation and connectivity to standardized disorder-related visual scenes in social anxiety disorder

Our understanding of altered emotional processing in social anxiety disorder (SAD) is hampered by a heterogeneity of findings, which is probably due to the vastly different methods and materials used so far. This is why the present functional magnetic resonance imaging (fMRI) study investigated immediate disorder-related threat processing in 30 SAD patients and 30 healthy controls (HC) with a novel, standardized set of highly ecologically valid, disorder-related complex visual scenes. SAD patients rated disorder-related as compared with neutral scenes as more unpleasant, arousing and anxiety-inducing than HC. On the neural level, disorder-related as compared with neutral scenes evoked differential responses in SAD patients in a widespread emotion processing network including (para-)limbic structures (e.g. amygdala, insula, thalamus, globus pallidus) and cortical regions (e.g. dorsomedial prefrontal cortex (dmPFC), posterior cingulate cortex (PCC), and precuneus). Functional connectivity analysis yielded an altered interplay between PCC/precuneus and paralimbic (insula) as well as cortical regions (dmPFC, precuneus) in SAD patients, which emphasizes a central role for PCC/precuneus in disorder-related scene processing. Hyperconnectivity of globus pallidus with amygdala, anterior cingulate cortex (ACC) and medial prefrontal cortex (mPFC) additionally underlines the relevance of this region in socially anxious threat processing. Our findings stress the importance of specific disorder-related stimuli for the investigation of altered emotion processing in SAD. Disorder-related threat processing in SAD reveals anomalies at multiple stages of emotion processing which may be linked to increased anxiety and to dysfunctionally elevated levels of self-referential processing reported in previous studies.

Amygdala subnuclei response and connectivity during emotional processing

The involvement of the human amygdala in emotion-related processing has been studied using functional magnetic resonance imaging (fMRI) for many years. However, despite the amygdala being comprised of several subnuclei, most studies investigated the role of the entire amygdala in processing of emotions. Here we combined a novel anatomical tracing protocol with event-related high-resolution fMRI acquisition to study the responsiveness of the amygdala subnuclei to negative emotional stimuli and to examine intra-amygdala functional connectivity. The greatest sensitivity to the negative emotional stimuli was observed in the centromedial amygdala, where the hemodynamic response amplitude elicited by the negative emotional stimuli was greater and peaked later than for neutral stimuli. Connectivity patterns converge with extant findings in animals, such that the centromedial amygdala was more connected with the nuclei of the basal amygdala than with the lateral amygdala. Current findings provide evidence of functional specialization within the human amygdala.