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Depression is characterized by altered neurobiological responses to threat and inflammation may be involved in the development and maintenance of symptoms. However, the mechanistic pathways underlying the relationship between the neural underpinnings of threat, inflammation and depressive symptoms remain unknown.Twenty participants with major depressive disorder (MDD) and 17 healthy controls (HCs) completed this study. Peripheral blood mononuclear cells (PBMCs) were collected and stimulated ex vivo with lipopolysaccharide (LPS). We then measured a broad array of secreted proteins and performed principal component analysis to compute an aggregated immune reactivity score. Subjects completed a well-validated emotional face processing task during functional magnetic resonance imaging (fMRI). Amygdala activation was measured during perception of threat for the main contrast of interest: fearhappy face. Participants completed the Mood and Anxiety Symptom Questionnaire (MASQ) and the Perceived Stress Scale (PSS). Correlation analyses between amygdala activation, the aggregate immune score, and symptom were computed across groups. A mediation analysis was also performed across groups to further explore the relationship between these three variables.In line with our hypotheses and with prior work, the MDD group showed greater amygdala activation in response to threat compared to the HC group [tThese data highlight the potential importance of threat circuitry hyperactivation in MDD, consistent with prior reports. We found that higher levels of inflammatory biomarkers were associated with higher amygdala activation, which in turn was associated with anxious arousal. Future research utilizing larger sample sizes are needed to replicate these preliminary results.

Motivational processes underlie behaviors that enrich the human experience, and impairments in motivation are commonly observed in psychiatric illness. While motivated behavior is often examined with respect to extrinsic reinforcers, not all actions are driven by reactions to external stimuli; some are driven by ‘intrinsic’ motivation. Intrinsically motivated behaviors are computationally similar to extrinsically motivated behaviors, in that they strive to maximize reward value and minimize punishment. However, our understanding of the neurocognitive mechanisms that underlie intrinsically motivated behavior remains limited. Dysfunction in intrinsic motivation represents an important trans-diagnostic facet of psychiatric symptomology, but due to a lack of clear consensus, the contribution of intrinsic motivation to psychopathology remains poorly understood. This review aims to provide an overview of the conceptualization, measurement, and neurobiology of intrinsic motivation, providing a framework for understanding its potential contributions to psychopathology and its treatment. Distinctions between intrinsic and extrinsic motivation are discussed, including divergence in the types of associated rewards or outcomes that drive behavioral action and choice. A useful framework for understanding intrinsic motivation, and thus separating it from extrinsic motivation, is developed and suggestions for optimization of paradigms to measure intrinsic motivation are proposed.

BackgroundThe sense of agency, or the belief in action causality, is an elusive construct that impacts day-to-day experience and decision-making. Despite its relevance in a range of neuropsychiatric disorders, it is widely under-studied and remains difficult to measure objectively in patient populations. We developed and tested a novel cognitive measure of valence-modulated agency perception in an in-person and online cohort.MethodsThe in-person cohort consisted of 52 healthy control subjects and 20 subjects with depression and anxiety disorders (DA), including major depressive disorder and generalized anxiety disorder. The online sample consisted of 254 participants. The task consisted of an effort task for monetary rewards with computerized visual feedback interference and trial-by-trial ratings of self versus other agency.ResultsAll subjects across both cohorts demonstrated higher self-agency after receiving positive-win feedback, compared to negative-loss feedback when the level of computer inference was kept constant. Patients with DA showed reduced positive valence-dependent agency compared to healthy controls. Finally, in both cohorts, lower self-agency following negative-loss feedback was associated with worse anhedonia symptoms.ConclusionTogether this work suggests how positive and negative environmental information impacts the sense of self-agency in healthy subjects, and how it is perturbed in patients with depression and anxiety.

The hippocampus and amygdala limbic structures are critical to the etiology of major depressive disorder (MDD). However, there are no high-resolution characterizations of the role of their subregions in the whole brain network (connectome). Connectomic examination of these subregions can uncover disorder-related patterns that are otherwise missed when treated as single structures. 38 MDD patients and 40 healthy controls (HC) underwent anatomical and diffusion imaging using 7-Tesla MRI. Whole-brain segmentation was performed along with hippocampus and amygdala subregion segmentation, each representing a node in the connectome. Graph theory analysis was applied to examine the importance of the limbic subregions within the brain network using centrality features measured by node strength (sum of weights of the node’s connections), Betweenness (number of shortest paths that traverse the node), and clustering coefficient (how connected the node’s neighbors are to one another and forming a cluster). Compared to HC, MDD patients showed decreased node strength of the right hippocampus cornu ammonis (CA) 3/4, indicating decreased connectivity to the rest of the brain, and decreased clustering coefficient of the right dentate gyrus, implying it is less embedded in a cluster. Additionally, within the MDD group, the greater the embedding of the right amygdala central nucleus (CeA) in a cluster, the greater the severity of depressive symptoms. The altered role of these limbic subregions in the whole-brain connectome is related to diagnosis and depression severity, contributing to our understanding of the limbic system involvement in MDD and may elucidate the underlying mechanisms of depression.

While COVID-19 is primarily considered a respiratory disease, it has been shown to affect the central nervous system. Mounting evidence shows that COVID-19 is associated with neurological complications as well as effects thought to be related to neuroinflammatory processes. Due to the novelty of COVID-19, there is a need to better understand the possible long-term effects it may have on patients, particularly linkage to neuroinflammatory processes. Perivascular spaces (PVS) are small fluid-filled spaces in the brain that appear on MRI scans near blood vessels and are believed to play a role in modulation of the immune response, leukocyte trafficking, and glymphatic drainage. Some studies have suggested that increased number or presence of PVS could be considered a marker of increased blood-brain barrier permeability or dysfunction and may be involved in or precede cascades leading to neuroinflammatory processes. Due to their size, PVS are better detected on MRI at ultrahigh magnetic field strengths such as 7 Tesla, with improved sensitivity and resolution to quantify both concentration and size. As such, the objective of this prospective study was to leverage a semi-automated detection tool to identify and quantify differences in perivascular spaces between a group of 10 COVID-19 patients and a similar subset of controls to determine whether PVS might be biomarkers of COVID-19-mediated neuroinflammation. Results demonstrate a detectable difference in neuroinflammatory measures in the patient group compared to controls. PVS count and white matter volume were significantly different in the patient group compared to controls, yet there was no significant association between PVS count and symptom measures. Our findings suggest that the PVS count may be a viable marker for neuroinflammation in COVID-19, and other diseases which may be linked to neuroinflammatory processes.

Increased levels of peripheral cytokines have been previously associated with depression in preclinical and clinical research. Although the precise nature of peripheral immune dysfunction in depression remains unclear, evidence from animal studies points towards a dysregulated response of peripheral leukocytes as a risk factor for stress susceptibility. This study examined dynamic release of inflammatory blood factors from peripheral blood mononuclear cells (PBMC) in depressed patients and associations with neural and behavioral measures of reward processing. Thirty unmedicated patients meeting criteria for unipolar depressive disorder and 21 healthy control volunteers were enrolled. PBMCs were isolated from whole blood and stimulated ex vivo with lipopolysaccharide (LPS). Olink multiplex assay was used to analyze a large panel of inflammatory proteins. Participants completed functional magnetic resonance imaging with an incentive flanker task to probe neural responses to reward anticipation, as well as clinical measures of anhedonia and pleasure including the Temporal Experience of Pleasure Scale (TEPS) and the Snaith-Hamilton Pleasure Scale (SHAPS). LPS stimulation revealed larger increases in immune factors in depressed compared to healthy subjects using an aggregate immune score (t49 = 2.83, p = 0.007). Higher peripheral immune score was associated with reduced neural responses to reward anticipation within the ventral striatum (VS) (r = −0.39, p = 0.01), and with reduced anticipation of pleasure as measured with the TEPS anticipatory sub-score (r = −0.318, p = 0.023). Our study provides new evidence suggesting that dynamic hyper-reactivity of peripheral leukocytes in depressed patients is associated with blunted activation of the brain reward system and lower subjective anticipation of pleasure.

SummaryObjectiveIn this study, we validate and describe a user-friendly tool for PVS tracing that uses a Frangi-based detection algorithm; which will be made freely available to aid in future clinical and research applications. All PVS detected by the semi-automated method had a match with the manual dataset and 94% of the manual PVS had a match within the semi-automated dataset.MethodsWe deployed a Frangi-based filter using a pre-existing Matlab toolbox. The PVSSAS tool pre-processes the images and is optimized for maximum effectiveness in this application. A user-friendly GUI was developed to aid the speed and ease in marking large numbers of PVS across the entire brain at once.ResultsUsing a tolerance of 0.7 cm, 83% of all PVSs detected by the semi-automated method had a match with the manual dataset and 94% of the manual PVS had a match within the semi-automated dataset. As shown in figure 3, there was generally excellent agreement between the manual and semi-automated markings in any given slice.SignificanceThe primary benefit of PVSSAS will be time saved marking PVS. Clinical MRI use is likely to become more widespread in the diagnosis, treatment, and study of MS and other degenerative neurological conditions in the coming years. Tools like the one presented here will be invaluable in ensuring that the tracing and quantitative analysis of these PVS does not act as a bottle neck to treatment and further research.

This review aims to synthesise a large pre-clinical and clinical literature related to a hypothesised role of the locus coeruleus norepinephrine system in responses to acute and chronic threat, as well as the emergence of pathological anxiety. The locus coeruleus has widespread norepinephrine projections throughout the central nervous system, which act to globally modulate arousal states and adaptive behavior, crucially positioned to play a significant role in modulating both ascending visceral and descending cortical neurocognitive information. In response to threat or a stressor, the locus coeruleus–norepinephrine system globally modulates arousal, alerting and orienting functions and can have a powerful effect on the regulation of multiple memory systems. Chronic stress leads to amplification of locus coeruleus reactivity to subsequent stressors, which is coupled with the emergence of pathological anxiety-like behaviors in rodents. While direct in vivo evidence for locus coeruleus dysfunction in humans with pathological anxiety remains limited, recent advances in high-resolution 7-T magnetic resonance imaging and computational modeling approaches are starting to provide new insights into locus coeruleus characteristics.

Alcohol misuse and addiction are major international public health issues. Addiction can be characterized as a disorder of aberrant neurocircuitry interacting with environmental, genetic and social factors. Neuroimaging in alcohol misuse can thus provide a critical window into underlying neural mechanisms, highlighting possible treatment targets and acting as clinical biomarkers for predicting risk and treatment outcomes. This neuroimaging review on alcohol misuse in humans follows the Addictions Neuroclinical Assessment (ANA) that proposes incorporating three functional neuroscience domains integral to the neurocircuitry of addiction: incentive salience and habits, negative emotional states, and executive function within the context of the addiction cycle. Here we review and integrate multiple imaging modalities focusing on underlying cognitive processes such as reward anticipation, negative emotionality, cue reactivity, impulsivity, compulsivity and executive function. We highlight limitations in the literature and propose a model forward in the use of neuroimaging as a tool to understanding underlying mechanisms and potential clinical applicability for phenotyping of heterogeneity and predicting risk and treatment outcomes.

Epilepsy patients exhibit morphological differences on neuroimaging compared to age-matched healthy controls, including cortical and sub-cortical volume loss and altered gray-white matter ratios. The objective was to develop a model of normal aging using the 7T MRIs of healthy controls. This model can then be used to determine if the changes in epilepsy patients resemble the changes seen in aging, and potentially give a marker for the severity of those changes.Sixty-nine healthy controls (24F/45M, mean age 36.5 ± 10.5 years) and forty-four epilepsy patients (24F/20M, 33.2 ± 9.9 years) non-lesional at 3T were scanned with volumetric T1-MPRAGE at 7T. These images were segmented and quantified using FreeSurfer. A linear regression-based model trained on healthy controls was developed to predict ages using derived imaging features among the epilepsy patient cohort. The model used 114 features with significant linear correlation with age.The regression-based model estimated brain age with mean absolute error (MAE) of 6.6 years among controls. Comparable prediction accuracy of 6.9 years MAE was seen epilepsy patients. T-test of mean absolute error showed no difference in the prediction accuracy with controls and epilepsy patients (Morphological patterns suggestive of premature aging were observed in non-lesional epilepsy patients vs. controls and in high seizure frequency patients vs. low frequency patients. Modeling brain age with 7T MRI may provide a sensitive imaging marker to assess the differential effects of the aging process in diseases such as epilepsy.

Background Functional neurological disorder (FND) is an elusive disorder characterized by unexplained neurological symptoms alongside aberrant cognitive processing and negative affect, often associated with amygdala reactivity. Methods We examined the effect of negative conditioning on cognitive function and amygdala reactivity in 25 FND patients and 20 healthy volunteers (HV). Participants were first conditioned to stimuli paired with negative affective or neutral (CS +/CS −) information. During functional MRI, subjects then performed an instrumental associative learning task to avoid monetary losses in the context of the previously conditioned stimuli. We expected that FND patients would be better at learning to avoid losses when faced with negatively conditioned stimuli (increased harm avoidance). Multi-echo resting state fMRI was also collected from the same subjects and a robust denoising method was employed, important for removing motion and physiological artifacts. Results FND subjects were more sensitive to the negative CS + compared to HV, demonstrated by a reinforcement learning model. Contrary to expectation, FND patients were generally more impaired at learning to avoid losses under both contexts (CS +/CS −), persisting to choose the option that resulted in a negative outcome demonstrated by both behavioural and computational analyses. FND patients showed enhanced amygdala but reduced dorsolateral prefrontal cortex responses when they received negative feedback. Patients also had increased resting state functional connectivity between these two regions. Conclusions FND patients had impaired instrumental avoidance learning, findings that parallel previous observations of impaired action-outcome binding. FND patients further show enhanced behavioural and neural sensitivity to negative information. However, this did not translate to improved avoidance learning. Put together, our findings do not support the theory of harm avoidance in FND. We highlight a potential mechanism by which negative contexts interfere with adaptive behaviours in this under-explored disorder., Highlights • Functional neurological disorder (FND) is a relatively common but elusive disorder characterized by unexplained neurological symptoms and negative affect. • One theory of FND symptomology is related to unconscious harm avoidance, in which symptom expression occurs to avoid a stressful situation. • We show that FND patients were more sensitive to negative information. However, this did not translate to increased harm avoidance as patients were impaired at goal-directed avoidance learning. • This study suggests that excessive negative conditioning in this group may engender deficient, rather than increased, goal-directed cognitive ability and loss avoidance.

Insight into motivational processes may be gained by examining measures of willingness to exert effort for rewards, which have been linked to neuropsychiatric symptoms of anhedonia and apathy. However, while much work has focused on the development of models of motivation based on classic tasks of externally-generated levels of effort for reward, there has been less focus on the question of self-generated motivation or volition. We developed a task that aims to capture separate measures of self-generated and externally-generated motivation, with two task variants for physical and cognitive effort, and sought to test and validate this measure in two populations of healthy volunteers (N = 27 and N = 28). Similar to previous reports, a sigmoid function represented a better overall fit to the effort-reward data than a linear or Weibull model. Individual sigmoid function shapes were governed by two free parameters: bias (the amount of reward needed for effort initiation) and reward insensitivity (the amount of increase in reward needed to accelerate effort expenditure). For both physical and cognitive effort, bias was higher in the self-generated condition, indicating reduced self-generated volitional effort initiation, compared to externally-generated effort initiation, across effort domains. Bias against initial effort initiation in the self-generated condition was related to a specific dimensional measure of anticipatory anhedonia. For physical effort only, reward insensitivity was also higher in the self-generated condition compared to the externally-generated motivation condition, indicating lower self-generated effort acceleration. This work provides a novel objective measure of self-generated motivation that may provide insights into mechanisms of anhedonia and related symptoms.

Highlights • We combined ultra-high field 7-Tesla and 0.4 × 0.4 × 0.5 mm quantitative MR imaging with a computational LC localization and segmentation algorithm. • LC was delineated in 29 human subjects including subjects with and without an anxiety or stress-related disorder. • Patients with an anxiety or stress-related disorder had larger LC compared to controls (Cohen's d = 1.08, p = 0.024). • Larger LC was additionally associated with poorer attentional and inhibitory control and higher anxious arousal (FDR-corrected p's, The locus coeruleus (LC) has a long-established role in the attentional and arousal response to threat, and in the emergence of pathological anxiety in pre-clinical models. However, human evidence of links between LC function and pathological anxiety has been restricted by limitations in discerning LC with current neuroimaging techniques. We combined ultra-high field 7-Tesla and 0.4 × 0.4 × 0.5 mm quantitative MR imaging with a computational LC localization and segmentation algorithm to delineate the LC in 29 human subjects including subjects with and without an anxiety or stress-related disorder. Our automated, data-driven LC segmentation algorithm provided LC delineations that corresponded well with postmortem anatomic definitions of the LC. There was variation of LC size in healthy subjects (125.7 +/- 59.3 mm3), which recapitulates histological reports. Patients with an anxiety or stress-related disorder had larger LC compared to controls (Cohen's d = 1.08, p = 0.024). Larger LC was additionally associated with poorer attentional and inhibitory control and higher anxious arousal (FDR-corrected p's

Ultra-high field 7-Tesla (7 T) MRI has the potential to advance our understanding of neuropsychiatric disorders, including major depressive disorder (MDD). To date, few studies have quantified the advantage of resting state functional MRI (fMRI) at 7 T compared to 3-Tesla (3 T). We conducted a series of experiments that demonstrate the improvement in temporal signal-to-noise ratio (TSNR) of a multi-echo multi-band fMRI protocol with ultra-high field 7 T MRI, compared to a similar protocol using 3 T MRI in healthy controls (HC). We also directly tested the enhancement in ultra-high field 7 T fMRI signal power by examining the ventral tegmental area (VTA), a small midbrain structure that is critical to the expected neuropathology of MDD but difficult to discern with standard 3 T MRI. We demonstrate up to 300% improvement in TSNR and resting state functional connectivity coefficients provided by ultra-high field 7 T fMRI compared to 3 T, indicating enhanced power for detection of functional neural architecture. A multi-echo based acquisition protocol and signal denoising pipeline afforded greater gain in signal power compared to classic acquisition and denoising pipelines. Furthermore, ultra-high field fMRI revealed mood-related neurocircuit disturbances in patients with MDD compared to HC, which were not detectable with 3 T fMRI. Ultra-high field 7 T fMRI may provide an effective tool for studying functional neural architecture relevant to MDD and other neuropsychiatric disorders.

Major depressive disorder (MDD) is a leading cause of disability worldwide, yet current treatment strategies remain limited in their mechanistic diversity. Recent evidence has highlighted a promising novel pharmaceutical target-the KCNQ-type potassium channel-for the treatment of depressive disorders, which may exert a therapeutic effect via functional changes within the brain reward system, including the ventral striatum. The current study assessed the effects of the KCNQ channel opener ezogabine (also known as retigabine) on reward circuitry and clinical symptoms in patients with MDD. Eighteen medication-free individuals with MDD currently in a major depressive episode were enrolled in an open-label study and received ezogabine up to 900 mg/day orally over the course of 10 weeks. Resting-state functional magnetic resonance imaging data were collected at baseline and posttreatment to examine brain reward circuitry. Reward learning was measured using a computerized probabilistic reward task. After treatment with ezogabine, subjects exhibited a significant reduction of depressive symptoms (Montgomery-Asberg Depression Rating Scale score change: -13.7 ± 9.7, p

Since its discovery, the gut hormone, ghrelin, has been implicated in diverse functional roles in the central nervous system. Central and peripheral interactions between ghrelin and other hormones, including the stress-response hormone cortisol, govern complex behavioral responses to external cues and internal states. By acting at ventral tegmental area dopaminergic projections and other areas involved in reward processing, ghrelin can induce both general and directed motivation for rewards, including craving for alcohol and other alcohol-seeking behaviors. Stress-induced increases in cortisol seem to increase ghrelin in the periphery, suggesting a pathway by which ghrelin influences how stressful life events trigger motivation for rewards. However, in some states, ghrelin may be protective against the anxiogenic effects of stressors. This critical review brings together a dynamic and growing literature, that is, at times inconsistent, on the relationships between ghrelin, central reward-motivation pathways, and central and peripheral stress responses, with a special focus on its emerging role in the context of alcohol use disorder.

A cardinal feature of persistent pain that follows injury is a general suppression of behavior, in which motivation is inhibited in a way that promotes energy conservation and recuperation. Across species, the anterior cingulate cortex (ACC) is associated with the motivational aspects of phasic pain, but whether it mediates motivational functions in persistent pain is less clear. Using burrowing behavior as an marker of non-specific motivated behavior in rodents, we studied the suppression of burrowing following painful CFA or control injection into the right knee-joint of 30 rats (14 with pain), and examined associated neural connectivity with ultra-high-field resting state functional MRI. We found that connectivity between ACC and subcortical structures including hypothalamic/preoptic nuclei and the bed nucleus of the stria terminalis correlated with the reduction in burrowing behavior observed following the pain manipulation. In summary, the findings implicate ACC connectivity as a correlate of the motivational aspect of persistent pain in rodents., Shionogi Corp

Pathological behaviors toward drugs and food rewards have underlying commonalities. Risk-taking has a fourfold pattern varying as a function of probability and valence leading to the nonlinearity of probability weighting with overweighting of small probabilities and underweighting of large probabilities. Here we assess these influences on risk-taking in patients with pathological behaviors toward drug and food rewards and examine structural neural correlates of nonlinearity of probability weighting in healthy volunteers. In the anticipation of rewards, subjects with binge eating disorder show greater risk-taking, similar to substance-use disorders.\ud Methamphetamine-dependent subjects had greater onlinearity of probability weighting along with impaired subjective discrimination of probability and reward magnitude. Ex-smokers also had lower risk-taking to rewards compared with non-smokers. In the anticipation of losses, obesity without binge eating had a similar pattern to other substance-use disorders. Obese subjects with binge eating also have impaired discrimination of subjective value similar to that of the methamphetamine-dependent subjects. Nonlinearity of probability weighting was associated with lower gray matter volume in dorsolateral and ventromedial prefrontal cortex and orbitofrontal cortex in healthy volunteers. Our findings support a distinct subtype of binge eating disorder in obesity with similarities in risk-taking in the reward domain to substance use disorders. The results dovetail with the current approach of defining mechanistically based dimensional approaches rather than categorical approaches to psychiatric disorders. The relationship to risk probability and valence may underlie the propensity toward pathological behaviors toward different types of rewards

Naltrexone, an opioid receptor antagonist, is commonly used as a relapse prevention medication in alcohol and opiate addiction, but its efficacy and the mechanisms underpinning its clinical usefulness are not well characterized. In the current study, we examined the effects of 50‐mg naltrexone compared with placebo on neural network changes associated with substance dependence in 21 alcohol and 36 poly‐drug‐dependent individuals compared with 36 healthy volunteers. Graph theoretic and network‐based statistical analysis of resting‐state functional magnetic resonance imaging (MRI) data revealed that alcohol‐dependent subjects had reduced functional connectivity of a dispersed network compared with both poly‐drug‐dependent and healthy subjects. Higher local efficiency was observed in both patient groups, indicating clustered and segregated network topology and information processing. Naltrexone normalized heightened local efficiency of the neural network in alcohol‐dependent individuals, to the same levels as healthy volunteers. Naltrexone failed to have an effect on the local efficiency in abstinent poly‐substance‐dependent individuals. Across groups, local efficiency was associated with substance, but no alcohol exposure implicating local efficiency as a potential premorbid risk factor in alcohol use disorders that can be ameliorated by naltrexone. These findings suggest one possible mechanism for the clinical effects of naltrexone, namely, the amelioration of disrupted network topology.

The capacity to flexibly respond to contextual changes is crucial to adapting to a dynamic environment. Compulsivity, or behavioural inflexibility, consists of heterogeneous subtypes with overlapping yet discrete neural substrates. The subthalamic nucleus (STN) mediates the switch from automatic to controlled processing to slow, break or stop behaviour when necessary. Rodent STN lesions or inactivation are linked with perseveration or repetitive, compulsive responding. However, there are few studies examining the role of latent STN-centric neural networks and compulsive behaviour in healthy individuals. We therefore aimed to characterize the relationship between measures of compulsivity (goal-directed and habit learning, perseveration, and self-reported obsessive – compulsive symptoms) and the intrinsic resting state network of the STN. We scanned 77 healthy controls using a multi-echo resting state functional MRI sequence analyzed using independent components analysis (ME-ICA) with enhanced signal-to-noise ratio to examine small subcortical structures. Goal directed model-based behaviour was associated with higher connectivity of STN with medial orbitofrontal cortex (mOFC) and ventral striatum (VS) and more habitual model-free learning was associated with STN connectivity with hippocampus and dorsal anterior cingulate cortex (ACC). Perseveration was associated with reduced connectivity between STN and premotor cortex and finally, higher obsessive –compulsive inventory scores were associated with reduced STN connectivity with dorsolateral prefrontal cortex (PF). We highlight unique contributions of diffuse cortico-striatal functional connections with STN in dissociable measures of compulsivity. These findings are relevant to the development of potential biomarkers of treatment response in neurosurgical procedures targeting the STN for neurological and psychiatric disorders.

We focus on exploratory decisions across disorders of compulsivity, a potential dimensional construct for the classification of mental disorders. Behaviors associated with the pathological use of alcohol or food, in alcohol use disorders (AUD) or binge-eating disorder (BED), suggest a disturbance in explore–exploit decision-making, whereby strategic exploratory decisions in an attempt to improve long-term outcomes may diminish in favor of more repetitive or exploitatory choices. We compare exploration vs exploitation across disorders of natural (obesity with and without BED) and drug rewards (AUD). We separately acquired resting state functional MRI data using a novel multi-echo planar imaging sequence and independent components analysis from healthy individuals to assess the neural correlates underlying exploration. Participants with AUD showed reduced exploratory behavior across gain and loss environments, leading to lower-yielding exploitatory choices. Obese subjects with and without BED did not differ from healthy volunteers but when compared with each other or to AUD subjects, BED had enhanced exploratory behaviors particularly in the loss domain. All subject groups had decreased exploration or greater uncertainty avoidance to losses compared with rewards. More exploratory decisions in the context of reward were associated with frontal polar and ventral striatal connectivity. For losses, exploration was associated with frontal polar and precuneus connectivity. We further implicate the relevance and dimensionality of constructs of compulsivity across disorders of both natural and drug rewards.

Parallel decisional systems constantly compete for control of our day-to-day choices. Recent computational models propose two distinct forms of reinforcement learning, model-based and model free, which drive goal-directed and habitual behaviours, respectively. Although most of us seem to effortlessly alternate between the two systems, several pathological disorders have been associated with their imbalance. Thus the need to further characterize such systems is clear. To examine the neural networks of these parallel processes, we employ a two-step sequential learning task used previously to show simultaneous engagement of model-based and model-free learning in healthy volunteers [1] and their imbalance in pathological states [2] . We separately acquired fMRI data from 66 healthy volunteers during rest using a novel multi-echo planar sequence that greatly boosts signal-to-noise ratios compared to traditional single-echo sequences thus allowing higher spatial resolution of subcortical structures [3] . We quantified the connectivity between regions of interest (ROI’s) by calculating Pearson correlations coefficients (R) between a priori hypothesized regions (henceforth referred to as ‘connectivity’). These connectivity values were then correlated with behavioural measures. Higher model-based learning was positively correlated with medial orbitofrontal cortex and ventral striatum connectivity (R=0.32, p=0.01). Model-based scores also positively correlated with connectivity between dorsolateral prefrontal cortex and ventral striatum (R=0.27, p=0.03). In contrast, model-free learning was positively correlated with posterior putamen and supplementary motor area connectivity (R=0.266, p=0.033); and negatively with medial orbitofrontal cortex and left amygdala connectivity (R=-0.255, p=0.042). Model-free learning was also positively correlated with right ventral striatum and amygdala connectivity (R=0.274, p=0.028). We finally show that cognitive flexibility in the form of attention set shifting is associated with functional connectivity between dorsolateral prefrontal cortex and ventral striatum (R=-0.298, p=0.021). These findings suggest a neural network for model-based learning involving: integration of instrumental performance (ventral striatum); flexible, computationally-driven updating of outcome value based on changing internal motivational states and external feedback (medial orbitofrontal cortex); and computation of the relative advantage of alternative action values (dorsolateral prefrontal cortex). The current findings provide a more integrative network model of how previously implicated cortical regions organize to drive goal-directed model-based learning. Whereas most previous findings have focused on the neural correlates of model-based learning, we highlight a motoric frontal-striatal network associated with model-free learning. Together, we illustrate the sensitivity of the multi-echo sequence for the distinguishment of such elusive behavioural control systems.

Background Why do we jump the gun or speak out of turn? Waiting impulsivity has a preclinical basis as a predictor for the development of addiction. Here, we mapped the intrinsic neural correlates of waiting and dissociated it from stopping, both fundamental mechanisms of behavioral control. Methods We used a recently developed translational task to assess premature responding and assess response inhibition using the stop signal task. We mapped the neural correlates in 55 healthy volunteers using a novel multi-echo resting-state functional magnetic resonance imaging sequence and analysis, which robustly boosts signal-to-noise ratio. We further assessed 32 young binge drinkers and 36 abstinent subjects with alcohol use disorders. Results Connectivity of limbic and motor cortical and striatal nodes mapped onto a mesial-lateral axis of the subthalamic nucleus. Waiting impulsivity was associated with lower connectivity of the subthalamic nucleus with ventral striatum and subgenual cingulate, regions similarly implicated in rodent lesion studies. This network was dissociable from fast reactive stopping involving hyperdirect connections of the pre-supplementary area and subthalamic nucleus. We further showed that binge drinkers, like those with alcohol use disorders, had elevated premature responding and emphasized the relevance of this subthalamic network across alcohol misuse. Using machine learning techniques we showed that subthalamic connectivity differentiates binge drinkers and individuals with alcohol use disorders from healthy volunteers. Conclusions We highlight the translational and clinical relevance of dissociable functional systems of cortical, striatal, and hyperdirect connections with the subthalamic nucleus in modulating waiting and stopping and their importance across dimensions of alcohol misuse.

Objective Functional neurological disorder (FND) is characterised by unexplained neurological symptoms, including movement, seizures or sensory symptoms that are unrelated to an underlying neurological disorder. As FND presents as ∼16% cases in neurology clinics (Stone et al, 2010) and the current understanding of its aetiology is limited, research into the neural disturbances present in this group is critical. FND subjects have been shown to display enhanced amygdala activity to arousing stimuli (Voon et al, 2010), however delineation of the roles of each subnuclei have not yet been achieved. In this study, we examined the response of FND subjects to fear conditioning and their sensitivity to loss. Method 25 FND and 20 healthy volunteers (HV) were conditioned to aversive/negative affective (CS+) or neutral (CS-) stimuli. During functional MRI, subjects performed a two-choice learning task to avoid monetary loss. The stimuli used in the two-choice task included the previously conditioned stimuli and were associated with a greater likelihood of a loss outcome. Results FND patients were more impaired at learning to avoid losses. Using reinforcement learning modelling, we show that FND subjects had a more negative valuation of the CS+ and greater noisy choice behaviours in the context of the CS+. Compared to HV, FND patients showed enhanced Centromedial amygdala responses to loss compared to neutral feedback in the context of the negative/aversive CS+, which correlated with greater impairments in avoidance learning. Conclusion The findings show that although FND patients have enhanced sensitivity to negative outcomes, this fails to be adaptive, and is not used to guide avoidance learning. We show no evidence for greater harm avoidance but rather a generalised impairment in the capacity to use negative outcomes to guide behaviours. Furthermore, fearful learned contexts enhance the randomness of choice behaviours, thus highlighting a potential mechanism by which negative contexts interfere with adaptive behaviours. Our findings further detail the aetiology of a common but elusive disorder and highlight the potential utility of interventions targeting the salience of negative stimuli.