Representation of aversive prediction errors in the human periaqueductal gray

Brain representations of affective valence and intensity in sustained pleasure and pain

Pleasure and pain are two fundamental, intertwined aspects of human emotions. Pleasurable sensations can reduce subjective feelings of pain and vice versa, and we often perceive the termination of pain as pleasant and the absence of pleasure as unpleasant. This implies the existence of brain systems that integrate them into modality-general representations of affective experiences. Here, we examined representations of affective valence and intensity in an functional MRI (fMRI) study (n = 58) of sustained pleasure and pain. We found that the distinct subpopulations of voxels within the ventromedial and lateral prefrontal cortices, the orbitofrontal cortex, the anterior insula, and the amygdala were involved in decoding affective valence versus intensity. Affective valence and intensity predictive models showed significant decoding performance in an independent test dataset (n = 62). These models were differentially connected to distinct large-scale brain networks-the intensity model to the ventral attention network and the valence model to the limbic and default mode networks. Overall, this study identified the brain representations of affective valence and intensity across pleasure and pain, promoting a systems-level understanding of human affective experiences.

Pain perception as hierarchical Bayesian inference: A test case for the theory of constructed emotion

An intriguing perspective about human emotion, the theory of constructed emotion considers emotions as generative models according to the Bayesian brain hypothesis. This theory brings fresh insight to existing findings, but its complexity renders it challenging to test experimentally. We argue that laboratory studies of pain could support the theory because although some may not consider pain to be a genuine emotion, the theory must at minimum be able to explain pain perception and its dysfunction in pathology. We review emerging evidence that bear on this question. We cover behavioral and neural laboratory findings, computational models, placebo hyperalgesia, and chronic pain. We conclude that there is substantial evidence for a predictive processing account of painful experience, paving the way for a better understanding of neuronal and computational mechanisms of other emotions.

The neurocomputational link between defensive cardiac states and approach-avoidance arbitration under threat

Avoidance, a hallmark of anxiety-related psychopathology, often comes at a cost; avoiding threat may forgo the possibility of a reward. Theories predict that optimal approach-avoidance arbitration depends on threat-induced psychophysiological states, like freezing-related bradycardia. Here we used model-based fMRI analyses to investigate whether and how bradycardia states are linked to the neurocomputational underpinnings of approach-avoidance arbitration under varying reward and threat magnitudes. We show that bradycardia states are associated with increased threat-induced avoidance and more pronounced reward-threat value comparison (i.e., a stronger tendency to approach vs. avoid when expected reward outweighs threat). An amygdala-striatal-prefrontal circuit supports approach-avoidance arbitration under threat, with specific involvement of the amygdala and dorsal anterior cingulate (dACC) in integrating reward-threat value and bradycardia states. These findings highlight the role of human freezing states in value-based decision making, relevant for optimal threat coping. They point to a specific role for amygdala/dACC in state-value integration under threat.

Pain reflects the informational value of nociceptive inputs

ABSTRACT

Pain perception and its modulation are fundamental to human learning and adaptive behavior. This study investigated the hypothesis that pain perception is tied to pain's learning function. Thirty-one participants performed a threat conditioning task where certain cues were associated with a possibility of receiving a painful electric shock. The cues that signaled potential pain or safety were regularly changed, requiring participants to continually establish new associations. Using computational models, we quantified participants' pain expectations and prediction errors throughout the task and assessed their relationship with pain perception and electrophysiological responses. Our findings suggest that subjective pain perception increases with prediction error, that is, when pain was unexpected. Prediction errors were also related to physiological nociceptive responses, including the amplitude of nociceptive flexion reflex and electroencephalography markers of cortical nociceptive processing (N1-P2-evoked potential and gamma-band power). In addition, higher pain expectations were related to increased late event-related potential responses and alpha/beta decreases in amplitude during cue presentation. These results further strengthen the idea of a crucial link between pain and learning and suggest that understanding the influence of learning mechanisms in pain modulation could help us understand when and why pain perception is modulated in health and disease.

The parieto-occipital cortex is a candidate neural substrate for the human ability to approximate Bayesian inference

Adaptive decision-making often requires one to infer unobservable states based on incomplete information. Bayesian logic prescribes that individuals should do so by estimating the posterior probability by integrating the prior probability with new information, but the neural basis of this integration is incompletely understood. We record fMRI during a task in which participants infer the posterior probability of a hidden state while we independently modulate the prior probability and likelihood of evidence regarding the state; the task incentivizes participants to make accurate inferences and dissociates expected value from posterior probability. Here we show that activation in a region of left parieto-occipital cortex independently tracks the subjective posterior probability, combining its subcomponents of prior probability and evidence likelihood, and reflecting the individual participants' systematic deviations from objective probabilities. The parieto-occipital cortex is thus a candidate neural substrate for humans' ability to approximate Bayesian inference by integrating prior beliefs with new information.

Noncortical cognition: integration of information for close-proximity behavioral problem-solving

Animals face behavioral problems that can be conceptualized in terms of a gradient of spatial and temporal proximity. I propose that solving close-proximity behavioral problems involves integrating disparate types of information in complex and flexible ways. In this framework, the midbrain periaqueductal gray (PAG) is understood as a key region involved in close-proximity motivated cognition. Anatomically, the PAG has access to signals across the neuroaxis via extensive connectivity with cortex, subcortex, and brainstem. However, the flow of signals is not unidirectional, as the PAG projects to the cortex directly, and further ascending signal flow is attained via the midline thalamus. Overall, the anatomical organization of the PAG allows is to be a critical hub engaged in cognition "here and now".

Depth and hierarchies in the predictive brain: From reaction to action

The human brain is a prediction device, a view widely accepted in neuroscience. Prediction is a rational and efficient response that relies on the brain's ability to create and employ generative models to optimize actions over unpredictable time horizons. We argue that extant predictive frameworks while compelling, have not explicitly accounted for the following: (a) The brain's generative models must incorporate predictive depth (i.e., rely on degrees of abstraction to enable predictions over different time horizons); (b) The brain's implementation scheme to account for varying predictive depth relies on dynamic predictive hierarchies formed using the brain's functional networks. We show that these hierarchies incorporate the ascending processes (driven by reaction), and the descending processes (related to prediction), eventually driving action. Because they are dynamically formed, predictive hierarchies allow the brain to address predictive challenges in virtually any domain. By way of application, we explain how this framework can be applied to heretofore poorly understood processes of human behavioral thermoregulation. Although mammalian thermoregulation has been closely tied to deep brain structures engaged in autonomic control such as the hypothalamus, this narrow conception does not translate well to humans. In addition to profound differences in evolutionary history, the human brain is bestowed with substantially increased functional complexity (that itself emerged from evolutionary differences). We argue that behavioral thermoregulation in humans is possible because, (a) ascending signals shaped by homeostatic sub-networks, interject with (b) descending signals related to prediction (implemented in interoceptive and executive sub-networks) and action (implemented in executive sub-networks). These sub-networks cumulatively form a predictive hierarchy for human thermoregulation, potentiating a range of viable responses to known and unknown thermoregulatory challenges. We suggest that our proposed extensions to the predictive framework provide a set of generalizable principles that can further illuminate the many facets of the predictive brain. This article is categorized under: Neuroscience > Behavior Philosophy > Action Psychology > Prediction.

How Do Expectations Modulate Pain? A Motivational Perspective

Expectations can profoundly modulate pain experience, during which the periaqueductal gray (PAG) plays a pivotal role. In this article, we focus on motivationally evoked neural activations in cortical and brainstem regions both before and during stimulus administration, as has been demonstrated by experimental studies on pain-modulatory effects of expectations, in the hope of unraveling how the PAG is involved in descending and ascending nociceptive processes. This motivational perspective on expectancy effects on the perception of noxious stimuli sheds new light on psychological and neuronal substrates of pain and its modulation, thus having important research and clinical implications.

Why is the Rescorla-Wagner model so influential?

The influence of the Rescorla-Wagner model cannot be overestimated, despite that (1) the model does not differ much computationally from its predecessors and competitors, and (2) its shortcomings are well-known in the learning community. Here we discuss the reasons behind its widespread influence in the cognitive and neural sciences, and argue that it is the constant search for general-process theories by learning scholars which eventually produced a model whose application spans many different areas of research to this day. We focus on the theoretical and empirical background of the model, the theoretical connections that it has with later developments across Marr's levels of analysis, as well as the broad variety of research that it has guided and inspired.

Placebo treatment affects brain systems related to affective and cognitive processes, but not nociceptive pain

Placebo analgesia is a replicable and well-studied phenomenon, yet it remains unclear to what degree it includes modulation of nociceptive processes. Some studies find effects consistent with nociceptive effects, but meta-analyses show that these effects are often small. We analyzed placebo analgesia in a large fMRI study (N = 392), including placebo effects on brain responses to noxious stimuli. Placebo treatment caused robust analgesia in both conditioned thermal and unconditioned mechanical pain. Placebo did not decrease fMRI activity in nociceptive pain regions, including the Neurologic Pain Signature (NPS) and pre-registered spinothalamic pathway regions, with strong support from Bayes Factor analyses. However, placebo treatment affected activity in pre-registered analyses of a second neuromarker, the Stimulus Intensity Independent Pain Signature (SIIPS), and several associated a priori brain regions related to motivation and value, in both thermal and mechanical pain. Individual differences in behavioral analgesia were correlated with neural changes in both thermal and mechanical pain. Our results indicate that processes related to affective and cognitive aspects of pain primarily drive placebo analgesia.

Function and biochemistry of the dorsolateral prefrontal cortex during placebo analgesia: how the certainty of prior experiences shapes endogenous pain relief

Prior experiences, conditioning cues, and expectations of improvement are essential for placebo analgesia expression. The dorsolateral prefrontal cortex is considered a key region for converting these factors into placebo responses. Since dorsolateral prefrontal cortex neuromodulation can attenuate or amplify placebo, we sought to investigate dorsolateral prefrontal cortex biochemistry and function in 38 healthy individuals during placebo analgesia. After conditioning participants to expect pain relief from a placebo "lidocaine" cream, we collected baseline magnetic resonance spectroscopy (1H-MRS) at 7 Tesla over the right dorsolateral prefrontal cortex. Following this, functional magnetic resonance imaging scans were collected during which identical noxious heat stimuli were delivered to the control and placebo-treated forearm sites. There was no significant difference in the concentration of gamma-aminobutyric acid, glutamate, Myo-inositol, or N-acetylaspartate at the level of the right dorsolateral prefrontal cortex between placebo responders and nonresponders. However, we identified a significant inverse relationship between the excitatory neurotransmitter glutamate and pain rating variability during conditioning. Moreover, we found placebo-related activation within the right dorsolateral prefrontal cortex and altered functional magnetic resonance imaging coupling between the dorsolateral prefrontal cortex and the midbrain periaqueductal gray, which also correlated with dorsolateral prefrontal cortex glutamate. These data suggest that the dorsolateral prefrontal cortex formulates stimulus-response relationships during conditioning, which are then translated to altered cortico-brainstem functional relationships and placebo analgesia expression.

Brain mediators of negative affect-induced physical symptom reporting in patients with functional somatic syndromes

Functional somatic syndromes (FSS) include fibromyalgia, irritable bowel syndrome (IBS), and others. In FSS patients, merely viewing negative affective pictures can elicit increased physical symptoms. Our aim was to investigate the neural mechanisms underlying such negative affect-induced physical symptoms in FSS patients. Thirty patients with fibromyalgia and/or IBS and 30 healthy controls (all women) watched neutral, positive and negative affective picture blocks during functional MRI scanning and rated negative affect and physical symptoms after every block. We compared brain-wide activation during negative versus neutral picture viewing in FSS patients versus controls using robust general linear model analysis. Further, we compared neurologic pain signature (NPS), stimulus intensity-independent pain signature (SIIPS) and picture-induced negative emotion signature (PINES) responses to the negative versus neutral affect contrast and investigated whether they mediated between-group differences in affective picture-induced physical symptom reporting. More physical symptoms were reported after viewing negative compared to neutral pictures, and this effect was larger in patients than controls (p = 0.025). Accordingly, patients showed stronger activation in somatosensory regions during negative versus neutral picture viewing. NPS, but not SIIPS nor PINES, responses were higher in patients than controls during negative versus neutral pictures (p = 0.026). These differential NPS responses partially mediated between-group differences in physical symptoms. In conclusion, picture-induced negative affect elicits physical symptoms in FSS patients as a result of activation of somatosensory and nociceptive brain patterns, supporting the idea that affect-driven alterations in processing of somatic signals is a critical mechanism underlying FSS.

Orchestration of innate and conditioned defensive actions by the periaqueductal gray

The midbrain periaqueductal gray (PAG) has been recognized for decades as having a central role in the control of a wide variety of defensive responses. Initial discoveries relied primarily on lesions, electrical stimulation and pharmacology. Recent developments in neural activity imaging and in methods to control activity with anatomical and genetic specificity have revealed additional streams of data informing our understanding of PAG function. Here, we discuss both classic and modern studies reporting on how PAG-centered circuits influence innate as well as learned defensive actions in rodents and humans. Though early discoveries emphasized the PAG's role in rapid induction of innate defensive actions, emerging new data indicate a prominent role for the PAG in more complex processes, including representing behavioral states and influencing fear learning and memory. This article is part of the Special Issue on "Fear, Anxiety and PTSD".

A machine learning based approach towards high-dimensional mediation analysis

Mediation analysis is used to investigate the role of intermediate variables (mediators) that lie in the path between an exposure and an outcome variable. While significant research has focused on developing methods for assessing the influence of mediators on the exposure-outcome relationship, current approaches do not easily extend to settings where the mediator is high-dimensional. These situations are becoming increasingly common with the rapid increase of new applications measuring massive numbers of variables, including brain imaging, genomics, and metabolomics. In this work, we introduce a novel machine learning based method for identifying high dimensional mediators. The proposed algorithm iterates between using a machine learning model to map the high-dimensional mediators onto a lower-dimensional space, and using the predicted values as input in a standard three-variable mediation model. Hence, the machine learning model is trained to maximize the likelihood of the mediation model. Importantly, the proposed algorithm is agnostic to the machine learning model that is used, providing significant flexibility in the types of situations where it can be used. We illustrate the proposed methodology using data from two functional Magnetic Resonance Imaging (fMRI) studies. First, using data from a task-based fMRI study of thermal pain, we combine the proposed algorithm with a deep learning model to detect distributed, network-level brain patterns mediating the relationship between stimulus intensity (temperature) and reported pain at the single trial level. Second, using resting-state fMRI data from the Human Connectome Project, we combine the proposed algorithm with a connectome-based predictive modeling approach to determine brain functional connectivity measures that mediate the relationship between fluid intelligence and working memory accuracy. In both cases, our multivariate mediation model links exposure variables (thermal pain or fluid intelligence), high dimensional brain measures (single-trial brain activation maps or resting-state brain connectivity) and behavioral outcomes (pain report or working memory accuracy) into a single unified model. Using the proposed approach, we are able to identify brain-based measures that simultaneously encode the exposure variable and correlate with the behavioral outcome.

Measuring pain and nociception: Through the glasses of a computational scientist. Transdisciplinary overview of methods

In a healthy state, pain plays an important role in natural biofeedback loops and helps to detect and prevent potentially harmful stimuli and situations. However, pain can become chronic and as such a pathological condition, losing its informative and adaptive function. Efficient pain treatment remains a largely unmet clinical need. One promising route to improve the characterization of pain, and with that the potential for more effective pain therapies, is the integration of different data modalities through cutting edge computational methods. Using these methods, multiscale, complex, and network models of pain signaling can be created and utilized for the benefit of patients. Such models require collaborative work of experts from different research domains such as medicine, biology, physiology, psychology as well as mathematics and data science. Efficient work of collaborative teams requires developing of a common language and common level of understanding as a prerequisite. One of ways to meet this need is to provide easy to comprehend overviews of certain topics within the pain research domain. Here, we propose such an overview on the topic of pain assessment in humans for computational researchers. Quantifications related to pain are necessary for building computational models. However, as defined by the International Association of the Study of Pain (IASP), pain is a sensory and emotional experience and thus, it cannot be measured and quantified objectively. This results in a need for clear distinctions between nociception, pain and correlates of pain. Therefore, here we review methods to assess pain as a percept and nociception as a biological basis for this percept in humans, with the goal of creating a roadmap of modelling options.

Computational perspectives on human fear and anxiety

Fear and anxiety are adaptive emotions that serve important defensive functions, yet in excess, they can be debilitating and lead to poor mental health. Computational modelling of behaviour provides a mechanistic framework for understanding the cognitive and neurobiological bases of fear and anxiety, and has seen increasing interest in the field. In this brief review, we discuss recent developments in the computational modelling of human fear and anxiety. Firstly, we describe various reinforcement learning strategies that humans employ when learning to predict or avoid threat, and how these relate to symptoms of fear and anxiety. Secondly, we discuss initial efforts to explore, through a computational lens, approach-avoidance conflict paradigms that are popular in animal research to measure fear- and anxiety-relevant behaviours. Finally, we discuss negative biases in decision-making in the face of uncertainty in anxiety.

Pain, from perception to action: A computational perspective

Pain is driven by sensation and emotion, and in turn, it motivates decisions and actions. To fully appreciate the multidimensional nature of pain, we formulate the study of pain within a closed-loop framework of sensory-motor prediction. In this closed-loop cycle, prediction plays an important role, as the interaction between prediction and actual sensory experience shapes pain perception and subsequently, action. In this Perspective, we describe the roles of two prominent computational theories-Bayesian inference and reinforcement learning-in modeling adaptive pain behaviors. We show that prediction serves as a common theme between these two theories, and that each of these theories can explain unique aspects of the pain perception-action cycle. We discuss how these computational theories and models can improve our mechanistic understandings of pain-centered processes such as anticipation, attention, placebo hypoalgesia, and pain chronification.

Serotonin modulates an inhibitory input to the central amygdala from the ventral periaqueductal gray

Fear is an adaptive state that drives defensive behavioral responses to specific and imminent threats. The central nucleus of the amygdala (CeA) is a critical site of adaptations that are required for the acquisition and expression of fear, in part due to alterations in the activity of inputs to the CeA. Here, we characterize a novel GABAergic input to the CeA from the ventral periaqueductal gray (vPAG) using fiber photometry and ex vivo whole-cell slice electrophysiology combined with optogenetics and pharmacology. GABA transmission from this ascending vPAG-CeA input was enhanced by serotonin via activation of serotonin type 2 C (5HT2C) receptors. Results suggest that these receptors are presynaptic. Interestingly, we found that GABA release from the vPAG-CeA input is enhanced following fear learning via activation of 5HT2C receptors and that this pathway is dynamically engaged in response to aversive stimuli. Additionally, we characterized serotonin release in the CeA during fear learning and recall for the first time using fiber photometry coupled to a serotonin biosensor. Together, these findings describe a mechanism by which serotonin modulates GABA release from ascending vPAG GABA inputs to the CeA and characterize a role for this pathway in fear.

Ventrolateral Periaqueductal Gray Astrocytes Regulate Nociceptive Sensation and Emotional Motivation in Diabetic Neuropathic Pain

Diabetic neuropathic pain (DNP) is a diabetes complication experienced by many patients. Ventrolateral periaqueductal gray (vlPAG) neurons are essential mediators of the descending pain modulation system, yet the role of vlPAG astrocytes in DNP remains unclear. The present study applied a multidimensional approach to elucidate the role of these astrocytes in DNP. We verified the activation of astrocytes in different regions of the PAG in male DNP-model rats. We found that only astrocytes in the vlPAG exhibited increased growth. Furthermore, we described differences in vlPAG astrocyte activity at different time points during DNP progression. After the 14th day of modeling, vlPAG astrocytes exhibited obvious activation and morphologic changes. Furthermore, activation of Gq-designer receptors exclusively activated by a designer drug (Gq-DREADDs) in vlPAG astrocytes in naive male rats induced neuropathic pain-like symptoms and pain-related aversion, whereas activation of Gi-DREADDs in vlPAG astrocytes in male DNP-model rats alleviated sensations of pain and promoted pain-related preference behavior. Thus, bidirectional manipulation of vlPAG astrocytes revealed their potential to regulate pain. Surprisingly, activation of Gi-DREADDs in vlPAG astrocytes also mitigated anxiety-like behavior induced by DNP. Thus, our results provide direct support for the hypothesis that vlPAG astrocytes regulate diabetes-associated neuropathic pain and concomitant anxiety-like behavior.SIGNIFICANCE STATEMENT Many studies examined the association between the ventrolateral periaqueductal gray (vlPAG) and neuropathic pain. However, few studies have focused on the role of vlPAG astrocytes in diabetic neuropathic pain (DNP) and DNP-related emotional changes. This work confirmed the role of vlPAG astrocytes in DNP by applying a more direct and robust approach. We used chemogenetics to bidirectionally manipulate the activity of vlPAG astrocytes and revealed that vlPAG astrocytes regulate DNP and pain-related behavior. In addition, we discovered that activation of Gi-designer receptors exclusively activated by a designer drug in vlPAG astrocytes alleviated anxiety-like behavior induced by DNP. Together, these findings provide new insights into DNP and concomitant anxiety-like behavior and supply new therapeutic targets for treating DNP.

Brainstem networks construct threat probability and prediction error from neuronal building blocks

When faced with potential threat we must estimate its probability, respond advantageously, and leverage experience to update future estimates. Threat estimation is the proposed domain of the forebrain, while behaviour is elicited by the brainstem. Yet, the brainstem is also a source of prediction error, a learning signal to acquire and update threat estimates. Neuropixels probes allowed us to record single-unit activity across a 21-region brainstem axis in rats receiving probabilistic fear discrimination with foot shock outcome. Against a backdrop of diffuse behaviour signaling, a brainstem network with a dorsal hub signaled threat probability. Neuronal function remapping during the outcome period gave rise to brainstem networks signaling prediction error and shock on multiple timescales. The results reveal brainstem networks construct threat probability, behaviour, and prediction error signals from neuronal building blocks.

Functional brain reconfiguration during sustained pain

Pain is constructed through complex interactions among multiple brain systems, but it remains unclear how functional brain networks are reconfigured over time while experiencing pain. Here, we investigated the time-varying changes in the functional brain networks during 20 min capsaicin-induced sustained orofacial pain. In the early stage, the orofacial areas of the primary somatomotor cortex were separated from other areas of the somatosensory cortex and integrated with subcortical and frontoparietal regions, constituting an extended brain network of sustained pain. As pain decreased over time, the subcortical and frontoparietal regions were separated from this brain network and connected to multiple cerebellar regions. Machine-learning models based on these network features showed significant predictions of changes in pain experience across two independent datasets (n = 48 and 74). This study provides new insights into how multiple brain systems dynamically interact to construct and modulate pain experience, advancing our mechanistic understanding of sustained 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.

Reward and loss incentives improve spatial working memory by shaping trial-by-trial posterior frontoparietal signals

Integrating motivational signals with cognition is critical for goal-directed activities. The mechanisms that link neural changes with motivated working memory continue to be understood. Here, we tested how externally cued and non-cued (internally represented) reward and loss impact spatial working memory precision and neural circuits in human subjects using fMRI. We translated the classic delayed-response spatial working memory paradigm from non-human primate studies to take advantage of a continuous numeric measure of working memory precision, and the wealth of translational neuroscience yielded by these studies. Our results demonstrated that both cued and non-cued reward and loss improved spatial working memory precision. Visual association regions of the posterior prefrontal and parietal cortices, specifically the precentral sulcus (PCS) and intraparietal sulcus (IPS), had increased BOLD signal during incentivized spatial working memory. A subset of these regions had trial-by-trial increases in BOLD signal that were associated with better working memory precision, suggesting that these regions may be critical for linking neural signals with motivated working memory. In contrast, regions straddling executive networks, including areas in the dorsolateral prefrontal cortex, anterior parietal cortex and cerebellum displayed decreased BOLD signal during incentivized working memory. While reward and loss similarly impacted working memory processes, they dissociated during feedback when money won or avoided in loss was given based on working memory performance. During feedback, the trial-by-trial amount and valence of reward/loss received was dissociated amongst regions such as the ventral striatum, habenula and periaqueductal gray. Overall, this work suggests motivated spatial working memory is supported by complex sensory processes, and that the IPS and PCS in the posterior frontoparietal cortices may be key regions for integrating motivational signals with spatial working memory precision.

Different brain systems support learning from received and avoided pain during human pain-avoidance learning

Both unexpected pain and unexpected pain absence can drive avoidance learning, but whether they do so via shared or separate neural and neurochemical systems is largely unknown. To address this issue, we combined an instrumental pain-avoidance learning task with computational modeling, functional magnetic resonance imaging (fMRI), and pharmacological manipulations of the dopaminergic (100 mg levodopa) and opioidergic (50 mg naltrexone) systems (N = 83). Computational modeling provided evidence that untreated participants learned more from received than avoided pain. Our dopamine and opioid manipulations negated this learning asymmetry by selectively increasing learning rates for avoided pain. Furthermore, our fMRI analyses revealed that pain prediction errors were encoded in subcortical and limbic brain regions, whereas no-pain prediction errors were encoded in frontal and parietal cortical regions. However, we found no effects of our pharmacological manipulations on the neural encoding of prediction errors. Together, our results suggest that human pain-avoidance learning is supported by separate threat- and safety-learning systems, and that dopamine and endogenous opioids specifically regulate learning from successfully avoided pain.

The neural signature of the decision value of future pain

SignificanceWe often willingly experience pain to reach a goal. However, potential pain can also prevent reckless action. How do we consider future pain when deciding on the best course of action? To date, the precise neural mechanisms underlying the valuation of future pain remain unknown. Using functional MRI, we derive a whole-brain signature of the value of future pain capable of predicting participants' choices to accept pain in exchange for a reward. We show that this signature is characterized by a distributed pattern of activity with clear contributions from structures encoding reward and salience, notably the ventral and dorsal striatum. These findings highlight how the brain assigns value to future pain when choosing the best course of action.

Role of anterior cingulate cortex inputs to periaqueductal gray for pain avoidance

Although pain-related excessive fear is known to be a key factor in chronic pain disability, which involves the anterior cingulate cortex (ACC), little is known about the downstream circuits of the ACC for fear avoidance in pain processing. Using behavioral experiments and functional magnetic resonance imaging with optogenetics at 15.2 T, we demonstrate that the ACC is a part of the abnormal circuit changes in chronic pain and its downstream circuits are closely related to modulating sensorimotor integration and generating active movement rather than carrying sensory information. The projection from the ACC to the dorsolateral and lateral parts of the periaqueductal gray (dl/lPAG) especially enhances both reflexive and active avoidance behavior toward pain. Collectively, our results indicate that increased signals from the ACC to the dl/lPAG might be critical for excessive fear avoidance in chronic pain disability.

A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems

Information is coded in the brain at multiple anatomical scales: locally, distributed across regions and networks, and globally. For pain, the scale of representation has not been formally tested, and quantitative comparisons of pain representations across regions and networks are lacking. In this multistudy analysis of 376 participants across 11 studies, we compared multivariate predictive models to investigate the spatial scale and location of evoked heat pain intensity representation. We compared models based on (a) a single most pain-predictive region or resting-state network; (b) pain-associated cortical-subcortical systems developed from prior literature ("multisystem models"); and (c) a model spanning the full brain. We estimated model accuracy using leave-one-study-out cross-validation (CV; 7 studies) and subsequently validated in 4 independent holdout studies. All spatial scales conveyed information about pain intensity, but distributed, multisystem models predicted pain 20% more accurately than any individual region or network and were more generalizable to multimodal pain (thermal, visceral, and mechanical) and specific to pain. Full brain models showed no predictive advantage over multisystem models. These findings show that multiple cortical and subcortical systems are needed to decode pain intensity, especially heat pain, and that representation of pain experience may not be circumscribed by any elementary region or canonical network. Finally, the learner generalization methods we employ provide a blueprint for evaluating the spatial scale of information in other domains.

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.

Cortico-Brainstem Mechanisms of Biased Perceptual Decision-Making in the Context of Pain

Prior expectations can bias how we perceive pain. Using a drift diffusion model, we recently showed that this influence is primarily based on changes in perceptual decision-making (indexed as shift in starting point). Only during unexpected application of high-intensity noxious stimuli, altered information processing (indexed as increase in drift rate) explained the expectancy effect on pain processing. Here, we employed functional magnetic resonance imaging to investigate the neural basis of both these processes in healthy volunteers. On each trial, visual cues induced the expectation of high- or low-intensity noxious stimulation or signaled equal probability for both intensities. Participants categorized a subsequently applied electrical stimulus as either low- or high-intensity pain. A shift in starting point towards high pain correlated negatively with right dorsolateral prefrontal cortex activity during cue presentation underscoring its proposed role of "keeping pain out of mind". This anticipatory right dorsolateral prefrontal cortex signal increase was positively correlated with periaqueductal gray (PAG) activity when the expected high-intensity stimulation was applied. A drift rate increase during unexpected high-intensity pain was reflected in amygdala engagement and increased functional connectivity between amygdala and PAG. Our findings suggest involvement of the PAG in both decision-making bias and altered information processing to implement expectancy effects on pain. PERSPECTIVE: Modulation of pain through expectations has been linked to changes in perceptual decision-making and altered processing of afferent information. Our results suggest involvement of the dorsolateral prefrontal cortex, amygdala, and periaqueductal gray in these processes.

Cerebellar modulation of memory encoding in the periaqueductal grey and fear behaviour

The pivotal role of the periaqueductal grey (PAG) in fear learning is reinforced by the identification of neurons in male rat ventrolateral PAG (vlPAG) that encode fear memory through signalling the onset and offset of an auditory-conditioned stimulus during presentation of the unreinforced conditioned tone (CS+) during retrieval. Some units only display CS+ onset or offset responses, and the two signals differ in extinction sensitivity, suggesting that they are independent of each other. In addition, understanding cerebellar contributions to survival circuits is advanced by the discovery that (i) reversible inactivation of the medial cerebellar nucleus (MCN) during fear consolidation leads in subsequent retrieval to (a) disruption of the temporal precision of vlPAG offset, but not onset responses to CS+, and (b) an increase in duration of freezing behaviour. And (ii) chemogenetic manipulation of the MCN-vlPAG projection during fear acquisition (a) reduces the occurrence of fear-related ultrasonic vocalisations, and (b) during subsequent retrieval, slows the extinction rate of fear-related freezing. These findings show that the cerebellum is part of the survival network that regulates fear memory processes at multiple timescales and in multiple ways, raising the possibility that dysfunctional interactions in the cerebellar-survival network may underlie fear-related disorders and comorbidities.

Anxiety disorders are a cluster of mental health conditions characterised by persistent and excessive amounts of fear and worry. They affect millions of people worldwide, but treatments can sometimes be ineffective and have unwanted side effects. Understanding which brain regions are involved in fear and anxiety-related behaviours, and how those areas are connected, is the first step towards designing more effective treatments.

A region known as the periaqueductal grey (or PAG) sits at the centre of the brain’s fear and anxiety network, regulating pain, encoding fear memories and responding to threats and stressors. It also controls survival behaviours such as the ‘freeze’ response, when an animal is frightened.

A more recent addition to the fear and anxiety network is the cerebellum, which sits at the base of the brain. Two-way connections between this region and the PAG have been well described, but how the cerebellum might influence fear and anxiety-related behaviours remains unclear.

To explore this role, Lawrenson, Paci et al. investigated whether the cerebellum modulates brain activity within the PAG and if so, how this relates to fear behaviours. Rats had electrodes implanted in their brains to record the activity of nerve cells within the PAG. A common fear-conditioning task was then used to elicit ‘freeze’ responses: a sound was paired with mild foot shocks until the animals learned to fear the auditory signal. In the rats, a subset of neurons within the PAG responded to the tone, consistent with those cells encoding a fear memory. But when a drug blocked the cerebellum’s output during fear conditioning, the timing of the PAG response was less precise and the rats’ freeze response lasted longer.

Lawrenson, Paci et al. concluded that the cerebellum, through its interactions with the brain’s fear and anxiety network, might be responsible for coordinating the most appropriate behavioural response to fear, and how long ‘freezing’ lasts.

In summary, these findings show that the cerebellum is a part of the brain’s survival network which regulates fear-memory processes. It raises the possibility that disruption of the cerebellum might underlie anxiety and other fear-related disorders, thereby providing a new target for future therapies.

Effect sizes and test-retest reliability of the fMRI-based neurologic pain signature

Identifying biomarkers that predict mental states with large effect sizes and high test-retest reliability is a growing priority for fMRI research. We examined a well-established multivariate brain measure that tracks pain induced by nociceptive input, the Neurologic Pain Signature (NPS). In N = 295 participants across eight studies, NPS responses showed a very large effect size in predicting within-person single-trial pain reports (d = 1.45) and medium effect size in predicting individual differences in pain reports (d = 0.49). The NPS showed excellent short-term (within-day) test-retest reliability (ICC = 0.84, with average 69.5 trials/person). Reliability scaled with the number of trials within-person, with ≥60 trials required for excellent test-retest reliability. Reliability was tested in two additional studies across 5-day (N = 29, ICC = 0.74, 30 trials/person) and 1-month (N = 40, ICC = 0.46, 5 trials/person) test-retest intervals. The combination of strong within-person correlations and only modest between-person correlations between the NPS and pain reports indicate that the two measures have different sources of between-person variance. The NPS is not a surrogate for individual differences in pain reports but can serve as a reliable measure of pain-related physiology and mechanistic target for interventions.

The exploration-exploitation dilemma in pain: an experimental investigation

ABSTRACT

Daily life consists of a chain of decisions. Typically, individuals may choose to pursue what they already know (exploitation) or to search for other options (exploration). This exploration-exploitation dilemma is a topic of interest across multiple scientific fields. Here we propose that investigating how individuals solve this dilemma may improve our understanding of how individuals make behavioral decisions (eg, avoidance) when facing pain. To this end, we present the data of 3 experiments in which healthy individuals were given the opportunity to choose between 4 different movements, with each movement being associated with different probabilities of receiving a painful outcome only (experiment 1) or pain and/or a reward (experiment 2). We also investigated whether participants stuck to their decisions when the contingencies between each movement and the painful/rewarding outcome changed during the task (experiment 3). The key findings across all experiments are the following: First, after initial exploration, participants most often exploited the safest option. Second, participants weighted rewards more heavily than receiving pain. Finally, after receiving a painful outcome, participants were more inclined to explore than to exploit a rewarding movement. We argue that by focusing more on how individuals in pain solve the exploration-exploitation dilemma is helpful in understanding behavioral decision making in pain.

Distinct networks of periaqueductal gray columns in pain and threat processing

Noxious events that can cause physical damage to the body are perceived as threats. In the brainstem, the periaqueductal gray (PAG) ensures survival by generating an appropriate response to these threats. Hence, the experience of pain is coupled with threat signaling and interfaces in the dl/l and vlPAG columns. In this study, we triangulate the functional circuits of the dl/l and vlPAG by using static and time-varying functional connectivity (FC) in multiple fMRI scans in healthy participants (n=37, 21 female). The dl/l and vlPAG were activated during cue, heat, and rating periods when the cue signaled a high threat of experiencing heat pain and the incoming intensity of heat pain was low; responses were significantly lower after low threat cues. The two regions responded similarly to the cued conditions but showed prominent distinctions in the extent of FC with other brain regions. Thus, both static and time-varying FC showed significant differences in the functional circuits of dl/l and vlPAG in rest and task scans. The dl/lPAG consistently synchronized with the salience network, suggesting a role in threat detection, while the vlPAG exhibited more widespread synchronization and frequently connected with memory/language and sensory regions. Hence, these two PAG regions process heat pain when stronger pain is expected or when it is uncertain, and preferentially synchronize with distinct brain circuits in a reproducible manner. The dl/lPAG seems more directly involved in salience detection, while the vlPAG seems engaged in contextualizing threats.

Modulation effect of acupuncture treatment on chronic neck and shoulder pain in female patients: Evidence from periaqueductal gray-based functional connectivity

Aims

Chronic neck and shoulder pain (CNSP) is a common neurological disorder, which females are more likely to suffer from. The periaqueductal gray (PAG) plays a key role in the descending modulation of pain. This study aimed to investigate altered PAG‐based functional connectivity (FC) in female patients with CNSP related to healthy controls (HCs) and the effect of acupuncture for female patients with CNSP using PAG‐based FC biomarkers.

Methods

PAG‐based FC value was calculated based on resting‐state functional images and then compared between patients with CNSP at pre‐acupuncture, post‐acupuncture, and HCs. Then, correlational analyses were performed to examine the relationships between increased PAG‐based FC strength and improved clinical parameters in patients after acupuncture treatment.

Results

Before acupuncture treatment, compared to HCs, patients with CSNP showed altered PAG‐based FC with widely distributed brain regions, including the left medial superior frontal gyrus, bilateral posterior insula (pIns), and cingulate gyrus. After treatment, patients with CNSP exhibited specially improved PAG‐pIns FC compared to that before treatment, and no significant difference was observed in the increased PAG‐pIns FC strength between HCs and patients with CNSP after treatment. Furthermore, pain catastrophizing reduction was significantly correlated with the increased PAG‐pIns FC strength in patients after treatment.

Conclusion

The effect of acupuncture treatment may relate to the increased PAG‐pIns FC, which significantly correlated with pain catastrophizing reduction after treatment. These findings shed important mechanistic information on the role of therapeutic approaches in treating chronic neck and shoulder pain.

Influence of periaqueductal gray on other salience network nodes predicts social sensitivity

The intrinsic connectivity of the salience network (SN) plays an important role in social behavior, however the directional influence that individual nodes have on each other has not yet been fully determined. In this study, we used spectral dynamic causal modeling to characterize the effective connectivity patterns in the SN for 44 healthy older adults and for 44 patients with behavioral variant frontotemporal dementia (bvFTD) who have focal SN dysfunction. We examined the relationship of SN effective connections with individuals' socioemotional sensitivity, using the revised self‐monitoring scale, an informant‐facing questionnaire that assesses sensitivity to expressive behavior. Overall, average SN effective connectivity for bvFTD patients differs from healthy older adults in cortical, hypothalamic, and thalamic nodes. For the majority of healthy individuals, strong periaqueductal gray (PAG) output to right cortical (p < .01) and thalamic nodes (p < .05), but not PAG output to other central pattern generators contributed to sensitivity to socioemotional cues. This effect did not exist for the majority of bvFTD patients; PAG output toward other SN nodes was weak, and this lack of output negatively influenced socioemotional sensitivity. Instead, input to the left vAI from other SN nodes supported patients' sensitivity to others' socioemotional behavior (p < .05), though less effectively. The key role of PAG output to cortical and thalamic nodes for socioemotional sensitivity suggests that its core functions, that is, generating autonomic changes in the body, and moreover representing the internal state of the body, is necessary for optimal social responsiveness, and its breakdown is central to bvFTD patients' social behavior deficits.

Effect of Pain Reprocessing Therapy vs Placebo and Usual Care for Patients With Chronic Back Pain: A Randomized Clinical Trial

IMPORTANCE

Chronic back pain (CBP) is a leading cause of disability, and treatment is often ineffective. Approximately 85% of cases are primary CBP, for which peripheral etiology cannot be identified, and maintenance factors include fear, avoidance, and beliefs that pain indicates injury.

OBJECTIVE

To test whether a psychological treatment (pain reprocessing therapy [PRT]) aiming to shift patients' beliefs about the causes and threat value of pain provides substantial and durable pain relief from primary CBP and to investigate treatment mechanisms.

DESIGN, SETTING, AND PARTICIPANTS

This randomized clinical trial with longitudinal functional magnetic resonance imaging (fMRI) and 1-year follow-up assessment was conducted in a university research setting from November 2017 to August 2018, with 1-year follow-up completed by November 2019. Clinical and fMRI data were analyzed from January 2019 to August 2020. The study compared PRT with an open-label placebo treatment and with usual care in a community sample.

INTERVENTIONS

Participants randomized to PRT participated in 1 telehealth session with a physician and 8 psychological treatment sessions over 4 weeks. Treatment aimed to help patients reconceptualize their pain as due to nondangerous brain activity rather than peripheral tissue injury, using a combination of cognitive, somatic, and exposure-based techniques. Participants randomized to placebo received an open-label subcutaneous saline injection in the back; participants randomized to usual care continued their routine, ongoing care.

MAIN OUTCOMES AND MEASURES

One-week mean back pain intensity score (0 to 10) at posttreatment, pain beliefs, and fMRI measures of evoked pain and resting connectivity.

RESULTS

At baseline, 151 adults (54% female; mean [SD] age, 41.1 [15.6] years) reported mean (SD) pain of low to moderate severity (mean [SD] pain intensity, 4.10 [1.26] of 10; mean [SD] disability, 23.34 [10.12] of 100) and mean (SD) pain duration of 10.0 (8.9) years. Large group differences in pain were observed at posttreatment, with a mean (SD) pain score of 1.18 (1.24) in the PRT group, 2.84 (1.64) in the placebo group, and 3.13 (1.45) in the usual care group. Hedges g was -1.14 for PRT vs placebo and -1.74 for PRT vs usual care (P < .001). Of 151 total participants, 33 of 50 participants (66%) randomized to PRT were pain-free or nearly pain-free at posttreatment (reporting a pain intensity score of 0 or 1 of 10), compared with 10 of 51 participants (20%) randomized to placebo and 5 of 50 participants (10%) randomized to usual care. Treatment effects were maintained at 1-year follow-up, with a mean (SD) pain score of 1.51 (1.59) in the PRT group, 2.79 (1.78) in the placebo group, and 3.00 (1.77) in the usual care group. Hedges g was -0.70 for PRT vs placebo (P = .001) and -1.05 for PRT vs usual care (P < .001) at 1-year follow-up. Longitudinal fMRI showed (1) reduced responses to evoked back pain in the anterior midcingulate and the anterior prefrontal cortex for PRT vs placebo; (2) reduced responses in the anterior insula for PRT vs usual care; (3) increased resting connectivity from the anterior prefrontal cortex and the anterior insula to the primary somatosensory cortex for PRT vs both control groups; and (4) increased connectivity from the anterior midcingulate to the precuneus for PRT vs usual care.

CONCLUSIONS AND RELEVANCE

Psychological treatment centered on changing patients' beliefs about the causes and threat value of pain may provide substantial and durable pain relief for people with CBP.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03294148.

Interoception of breathing and its relationship with anxiety

Interoception, the perception of internal bodily states, is thought to be inextricably linked to affective qualities such as anxiety. Although interoception spans sensory to metacognitive processing, it is not clear whether anxiety is differentially related to these processing levels. Here we investigated this question in the domain of breathing, using computational modeling and high-field (7 T) fMRI to assess brain activity relating to dynamic changes in inspiratory resistance of varying predictability. Notably, the anterior insula was associated with both breathing-related prediction certainty and prediction errors, suggesting an important role in representing and updating models of the body. Individuals with low versus moderate anxiety traits showed differential anterior insula activity for prediction certainty. Multi-modal analyses of data from fMRI, computational assessments of breathing-related metacognition, and questionnaires demonstrated that anxiety-interoception links span all levels from perceptual sensitivity to metacognition, with strong effects seen at higher levels of interoceptive processes.

A social affective neuroscience lens on placebo analgesia

Pain is a fundamental experience that promotes survival. In humans, pain stands at the intersection of multiple health crises: chronic pain, the opioid epidemic, and health disparities. The study of placebo analgesia highlights how social, cognitive, and affective processes can directly shape pain, and identifies potential paths for mitigating these crises. This review examines recent progress in the study of placebo analgesia through affective science. It focuses on how placebo effects are shaped by expectations, affect, and the social context surrounding treatment, and discusses neurobiological mechanisms of placebo, highlighting unanswered questions and implications for health. Collaborations between clinicians and social and affective scientists can address outstanding questions and leverage placebo to reduce pain and improve human health.

The Aversion Function of the Limbic Dopaminergic Neurons and Their Roles in Functional Neurological Disorders

The Freudian theory of conversion suggested that the major symptoms of functional neurological disorders (FNDs) are due to internal conflicts at motivation, especially at the sex drive or libido. FND patients might behave properly at rewarding situations, but they do not know how to behave at aversive situations. Sex drive is the major source of dopamine (DA) release in the limbic area; however, the neural mechanism involved in FND is not clear. Dopaminergic (DAergic) neurons have been shown to play a key role in processing motivation-related information. Recently, DAergic neurons are found to be involved in reward-related prediction error, as well as the prediction of aversive information. Therefore, it is suggested that DA might change the rewarding reactions to aversive reactions at internal conflicts of FND. So DAergic neurons in the limbic areas might induce two major motivational functions: reward and aversion at internal conflicts. This article reviewed the recent advances on studies about DAergic neurons involved in aversive stimulus processing at internal conflicts and summarizes several neural pathways, including four limbic system brain regions, which are involved in the processing of aversion. Then the article discussed the vital function of these neural circuits in addictive behavior, depression treatment, and FNDs. In all, this review provided a prospect for future research on the aversion function of limbic system DA neurons and the therapy of FNDs.

Neural and behavioral correlates of human pain avoidance in participants with and without episodic migraine

ABSTRACT

The innate motivation to avoid pain can be disrupted when individuals experience uncontrollable stress, such as pain. This can lead to maladaptive behaviors, including passivity, and negative affect. Despite its importance, motivational aspects of pain avoidance are understudied in humans and their neural mechanisms vastly unknown. Rodent models suggest an important role of the periaqueductal gray, but it is unknown whether it subserves a similar role in humans. Furthermore, it is unclear whether pain avoidance is associated with individual differences in pain coping. Using functional magnetic resonance imaging, networks underlying pain avoidance behavior were examined in 32 participants with and without episodic migraine. Pain avoidance behavior was assessed using an adaptation of the incentive delay task. In each trial of the task, participants tried to avoid a painful stimulus and receive a nonpainful one instead while the difficulty to succeed varied across trials (3 difficulty levels: safe, easy, and difficult). After unsuccessful pain avoidance on the preceding trial, participants showed reduced pain avoidance behavior, especially in the difficult condition. This reduction in behavior was associated with higher helplessness scores only in participants with migraine. Higher helplessness in participants with migraine was further correlated with a stronger decrease in activation of cortical areas associated with motor behavior, attention, and memory after unsuccessful pain avoidance. Of these areas, specifically posterior parietal cortex activation predicted individual's pain avoidance behavior on the next trial. The results link individual pain coping capacity to patterns of neural activation associated with altered pain avoidance in patients with migraine.

Resting state hypothalamic and dorsomedial prefrontal cortical connectivity of the periaqueductal gray in cocaine addiction

Cocaine-dependent (CD) individuals demonstrate significant anxiety and dysphoria during withdrawal, a negative emotional state that may perpetuate drug seeking and consumption. An extensive body of work has focused on characterizing reward circuit dysfunction, but relatively little is known about the pain circuit during cocaine withdrawal. In an earlier study, we highlighted how cue-elicited functional connectivity between the periaqueductal gray (PAG), a subcortical hub of the pain circuit, and ventromedial prefrontal cortex supports tonic craving in recently abstinent CD. The functional organization of the brain can be characterized by intrinsic connectivities, and it is highly likely that the resting state functional connectivity (rsFC) of the PAG may also be altered in association with cocaine use variables. Here, we examined this issue in 52 CD and 52 healthy control (HC) participants. Imaging data were processed with published routines, and the findings were evaluated with a corrected threshold. In a covariance analysis, CD as compared with HC showed higher PAG rsFC with the hypothalamus, dorsomedial prefrontal, and inferior parietal cortices. Further, these connectivities were correlated negatively with tonic cocaine craving and recent cocaine use, respectively. Higher hypothalamic and frontoparietal rsFC with the PAG may reflect a compensatory process to regulate craving and compulsive drug use. The findings provide additional evidence in humans implicating the PAG circuit and may help research of the role of negative reinforcement in sustaining habitual drug use in cocaine addiction.

A human colliculus-pulvinar-amygdala pathway encodes negative emotion

Animals must rapidly respond to threats to survive. In rodents, threat-related signals are processed through a subcortical pathway from the superior colliculus to the amygdala, a putative "low road" to affective behavior. This pathway has not been well characterized in humans. We developed a novel pathway identification framework that uses pattern recognition to identify connected neural populations and optimize measurement of inter-region connectivity. We first verified that the model identifies known thalamocortical pathways with high sensitivity and specificity in 7 T (n = 56) and 3 T (n = 48) fMRI experiments. Then we identified a human functional superior colliculus-pulvinar-amygdala pathway. Activity in this pathway encodes the intensity of normative emotional responses to negative images and sounds but not pleasant images or painful stimuli. These results provide a functional description of a human "low road" pathway selective for negative exteroceptive events and demonstrate a promising method for characterizing human functional brain pathways.

Anatomical dissociation of intracerebral signals for reward and punishment prediction errors in humans

Whether maximizing rewards and minimizing punishments rely on distinct brain systems remains debated, given inconsistent results coming from human neuroimaging and animal electrophysiology studies. Bridging the gap across techniques, we recorded intracerebral activity from twenty participants while they performed an instrumental learning task. We found that both reward and punishment prediction errors (PE), estimated from computational modeling of choice behavior, correlate positively with broadband gamma activity (BGA) in several brain regions. In all cases, BGA scaled positively with the outcome (reward or punishment versus nothing) and negatively with the expectation (predictability of reward or punishment). However, reward PE were better signaled in some regions (such as the ventromedial prefrontal and lateral orbitofrontal cortex), and punishment PE in other regions (such as the anterior insula and dorsolateral prefrontal cortex). These regions might therefore belong to brain systems that differentially contribute to the repetition of rewarded choices and the avoidance of punished choices.

Whether maximizing rewards and minimizing punishments rely on distinct brain learning systems remains debated. Here, using intracerebral recordings in humans, the authors provide evidence for brain regions differentially engaged in signaling reward and punishment prediction errors that prescribe repetition versus avoidance of past choices.

The placebo effect: To explore or to exploit?

How people choose between options with differing outcomes (explore-exploit) is a central question to understanding human behaviour. However, the standard explore-exploit paradigm relies on gamified tasks with low-stake outcomes. Consequently, little is known about decision making for biologically-relevant stimuli. Here, we combined placebo and explore-exploit paradigms to examine detection and selection of the most effective treatment in a pain model. During conditioning, where 'optimal' and 'suboptimal' sham-treatments were paired with a reduction in electrical pain stimulation, participants learnt which treatment most successfully reduced pain. Modelling participant responses revealed three important findings. First, participants' choices reflected both directed and random exploration. Second, expectancy modulated pain - indicative of recursive placebo effects. Third, individual differences in terms of expectancy during conditioning predicted placebo effects during a subsequent test phase. These findings reveal directed and random exploration when the outcome is biologically-relevant. Moreover, this research shows how placebo and explore-exploit literatures can be unified.

Neural substrates of appetitive and aversive prediction error

Prediction error, defined by the discrepancy between real and expected outcomes, lies at the core of associative learning. Behavioural investigations have provided evidence that prediction error up- and down-regulates associative relationships, and allocates attention to stimuli to enable learning. These behavioural advances have recently been followed by investigations into the neurobiological substrates of prediction error. In the present paper, we review neuroscience data obtained using causal and recording neural methods from a variety of key behavioural designs. We explore the neurobiology of both appetitive (reward) and aversive (fear) prediction error with a focus on the mesolimbic dopamine system, the amygdala, ventrolateral periaqueductal gray, hippocampus, cortex and locus coeruleus noradrenaline. New questions and avenues for research are considered.

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.

Retrorubral field is a hub for diverse threat and aversive outcome signals

Adaptive fear scales to the degree of threat and requires diverse neural signals for threat and aversive outcome. We propose that the retrorubral field (RRF), a midbrain region containing A8 dopamine, is a neural origin of such signals. To reveal these signals, we recorded RRF single-unit activity while male rats discriminated danger, uncertainty, and safety. Many RRF neurons showed firing extremes to danger and safety that framed intermediate firing to uncertainty. The remaining neurons showed unique, threat-selective cue firing patterns. Diversity in firing direction, magnitude, and temporal characteristics led to the detection of at least eight functional neuron types. Neuron types defined with respect to threat showed unique firing patterns following aversive outcome. The result was RRF signals for foot shock receipt, positive prediction error, anti-positive prediction error, persistent safety, and persistent threat. The diversity of threat and aversive outcome signals points to a key role for the RRF in adaptive fear.

The Neural Correlates of Cued Reward Omission

Compared to our understanding of positive prediction error signals occurring due to unexpected reward outcomes, less is known about the neural circuitry in humans that drives negative prediction errors during omission of expected rewards. While classical learning theories such as Rescorla-Wagner or temporal difference learning suggest that both types of prediction errors result from a simple subtraction, there has been recent evidence suggesting that different brain regions provide input to dopamine neurons which contributes to specific components of this prediction error computation. Here, we focus on the brain regions responding to negative prediction error signals, which has been well-established in animal studies to involve a distinct pathway through the lateral habenula. We examine the activity of this pathway in humans, using a conditioned inhibition paradigm with high-resolution functional MRI. First, participants learned to associate a sensory stimulus with reward delivery. Then, reward delivery was omitted whenever this stimulus was presented simultaneously with a different sensory stimulus, the conditioned inhibitor (CI). Both reward presentation and the reward-predictive cue activated midbrain dopamine regions, insula and orbitofrontal cortex. While we found significant activity at an uncorrected threshold for the CI in the habenula, consistent with our predictions, it did not survive correction for multiple comparisons and awaits further replication. Additionally, the pallidum and putamen regions of the basal ganglia showed modulations of activity for the inhibitor that did not survive the corrected threshold.

Expecting social punishment facilitates control over a decision under uncertainty by recruiting medial prefrontal cortex

In many decision-making situations, sub-optimal choices are increased by uncertainty. However, when wrong choices could lead to social punishment, such as blame, people might try to improve their performance by minimizing sub-optimal choices, which could be achieved by increasing the subjective cost of errors, thereby globally reducing decision noise or reducing an uncertainty-induced component of decision noise. In this functional magnetic resonance imaging (fMRI) study, 46 participants performed a choice task in which the probability of a correct choice with a given cue and the conditional probability of blame feedback (by making an incorrect choice) changed continuously. By comparing computational models of behaviour, we found that participants optimized their performance by preferentially reducing a component of decision noise associated with uncertainty. Simultaneously, expecting blame significantly deteriorated participants' mood. Model-based fMRI analyses and dynamic causal modelling indicate that the optimization mechanism based on the expectation of being blamed would be controlled by a neural circuit centred on the right medial prefrontal cortex. These results show novel behavioural and neural mechanisms regarding how humans optimize uncertain decisions under the expectation of being blamed.

Hierarchical models of pain: Inference, information-seeking, and adaptive control

Computational models of pain consider how the brain processes nociceptive information and allow mapping neural circuits and networks to cognition and behaviour. To date, they have generally have assumed two largely independent processes: perceptual inference, typically modelled as an approximate Bayesian process, and action control, typically modelled as a reinforcement learning process. However, inference and control are intertwined in complex ways, challenging the clarity of this distinction. Here, we consider how they may comprise a parallel hierarchical architecture that combines inference, information-seeking, and adaptive value-based control. This sheds light on the complex neural architecture of the pain system, and takes us closer to understanding from where pain 'arises' in the brain.