Blunted Frontostriatal Blood Oxygen Level-Dependent Signals Predict Stimulant and Marijuana Use

BACKGROUND

Occasional recreational stimulant (amphetamine and cocaine) use is an important public health problem among young adults because 16% of those who experiment develop stimulant use disorder. This study aimed to determine whether behavioral and/or neural processing measures can forecast the transition from occasional to problematic stimulant use.

METHODS

Occasional stimulant users completed a Risky Gains Task during functional magnetic resonance imaging and were followed up 3 years later. Categorical analyses tested whether blood oxygen level-dependent (BOLD) responses differentiated occasional stimulant users who became problem stimulant users (n = 35) from those who desisted from stimulant use (n = 75) at follow-up. Dimensional analyses (regardless of problem stimulant user or desisted stimulant use status; n = 144) tested whether BOLD responses predicted baseline and follow-up stimulant and marijuana use.

RESULTS

Categorical results indicated that relative to those who desisted from stimulant use, problem stimulant users 1) made riskier decisions after winning feedback; 2) exhibited lower frontal, insular, and striatal BOLD responses to win/loss feedback after making risky decisions; and 3) displayed lower thalamic but greater temporo-occipital BOLD responses to risky losses than to risky wins. In comparison, dimensional results indicated that lower BOLD signals to risky choices than to safe choices in frontal, striatal, and additional regions predicted greater marijuana use at follow-up.

CONCLUSIONS

Taken together, blunted frontostriatal signals during risky choices may quantify vulnerability to future marijuana consumption, whereas blunted frontostriatal signals to risky outcomes mark risk for future stimulant use disorder. These behavioral and neural processing measures may prove to be useful for identifying ultra-high risk individuals prior to onset of problem drug use.

A Nonlinear Simulation Framework Supports Adjusting for Age When Analyzing BrainAGE

Several imaging modalities, including T1-weighted structural imaging, diffusion tensor imaging, and functional MRI can show chronological age related changes. Employing machine learning algorithms, an individual's imaging data can predict their age with reasonable accuracy. While details vary according to modality, the general strategy is to: (1) extract image-related features, (2) build a model on a training set that uses those features to predict an individual's age, (3) validate the model on a test dataset, producing a predicted age for each individual, (4) define the "Brain Age Gap Estimate" (BrainAGE) as the difference between an individual's predicted age and his/her chronological age, (5) estimate the relationship between BrainAGE and other variables of interest, and (6) make inferences about those variables and accelerated or delayed brain aging. For example, a group of individuals with overall positive BrainAGE may show signs of accelerated aging in other variables as well. There is inevitably an overestimation of the age of younger individuals and an underestimation of the age of older individuals due to "regression to the mean." The correlation between chronological age and BrainAGE may significantly impact the relationship between BrainAGE and other variables of interest when they are also related to age. In this study, we examine the detectability of variable effects under different assumptions. We use empirical results from two separate datasets [training = 475 healthy volunteers, aged 18-60 years (259 female); testing = 489 participants including people with mood/anxiety, substance use, eating disorders and healthy controls, aged 18-56 years (312 female)] to inform simulation parameter selection. Outcomes in simulated and empirical data strongly support the proposal that models incorporating BrainAGE should include chronological age as a covariate. We propose either including age as a covariate in step 5 of the above framework, or employing a multistep procedure where age is regressed on BrainAGE prior to step 5, producing BrainAGE Residualized (BrainAGER) scores.

Empirical evidence of mental health risks posed by climate change

Sound mental health-a critical facet of human wellbeing-has the potential to be undermined by climate change. Few large-scale studies have empirically examined this hypothesis. Here, we show that short-term exposure to more extreme weather, multiyear warming, and tropical cyclone exposure each associate with worsened mental health. To do so, we couple meteorological and climatic data with reported mental health difficulties drawn from nearly 2 million randomly sampled US residents between 2002 and 2012. We find that shifting from monthly temperatures between 25 °C and 30 °C to >30 °C increases the probability of mental health difficulties by 0.5% points, that 1°C of 5-year warming associates with a 2% point increase in the prevalence of mental health issues, and that exposure to Hurricane Katrina associates with a 4% point increase in this metric. Our analyses provide added quantitative support for the conclusion that environmental stressors produced by climate change pose threats to human mental health.

Effect of Ibuprofen on BrainAGE: A Randomized, Placebo-Controlled, Dose-Response Exploratory Study

BACKGROUND

The age of a person's brain can be estimated from structural brain images using an aggregate measure of variation in morphology across the whole brain. The brain age gap estimation (BrainAGE) score is computed as the difference between kernel-estimated brain age and chronological age. In this exploratory study, we investigated the application of the BrainAGE measure to identify potential novel effects of pharmacological agents on brain morphology.

METHODS

Twenty healthy participants (23-47 years of age) completed three structural magnetic resonance imaging scans 45 minutes after administration of placebo or 200 or 600 mg of ibuprofen in a double-blind, crossover study. An externally derived BrainAGE model from a sample of 480 healthy participants was used to examine the acute effect of ibuprofen on temporary neuroanatomical changes in healthy individuals.

RESULTS

The BrainAGE model produced age prediction for each participant with a mean absolute error of 6.7 years between the estimated and chronological age. The intraclass correlation coefficient for BrainAGE was 0.96. Relative to placebo, 200 and 600 mg of ibuprofen significantly decreased BrainAGE by 1.18 and 1.15 years, respectively (p < .05). The trained BrainAGE model identified the medial prefrontal cortex to be the strongest age predictor.

CONCLUSIONS

BrainAGE is a potentially useful construct to examine neurological effects of therapeutic drugs. Ibuprofen temporarily reduces BrainAGE by approximately 1 year, which is likely due to its acute anti-inflammatory effects.

Neural hypersensitivity to pleasant touch in women remitted from anorexia nervosa

Interoception, or the sensing and integration of bodily state signals, has been implicated in anorexia nervosa (AN), given that the hallmark symptoms involve food restriction and body image disturbance. Here we focus on brain response to the anticipation and experience of affective interoceptive stimuli. Women remitted from AN (RAN; N = 18) and healthy comparison women (CW; N = 26) underwent a pleasant affective touch paradigm consisting of gentle strokes with a soft brush administered to the forearm or palm during functional neuroimaging. RAN had a lower brain response relative to CW during anticipation of touch, but a greater response when experiencing touch in the right ventral mid-insula. In RAN, this reduced anticipatory response was associated with higher levels of harm avoidance. Exploratory analyses in RAN also suggested that lower response during touch anticipation was associated with greater body dissatisfaction and higher perceived touch intensity ratings. This reduced responsivity to the anticipation of pleasant affective interoceptive stimuli in association with higher harm avoidance, along with an elevated response to the experience of touch, suggests an impaired ability in AN to predict and interpret incoming physiological stimuli. Impaired interoception may thus impact one's sense of self, thereby supporting observations of disturbed body image and avoidance of affective and social stimuli. Therapeutic approaches that help AN to better anticipate and interpret salient affective stimuli or improve tolerance of interoceptive experiences may be an important addition to current interventions.

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Interoception and Mental Health: A Roadmap

Interoception refers to the process by which the nervous system senses, interprets, and integrates signals originating from within the body, providing a moment-by-moment mapping of the body's internal landscape across conscious and unconscious levels. Interoceptive signaling has been considered a component process of reflexes, urges, feelings, drives, adaptive responses, and cognitive and emotional experiences, highlighting its contributions to the maintenance of homeostatic functioning, body regulation, and survival. Dysfunction of interoception is increasingly recognized as an important component of different mental health conditions, including anxiety disorders, mood disorders, eating disorders, addictive disorders, and somatic symptom disorders. However, a number of conceptual and methodological challenges have made it difficult for interoceptive constructs to be broadly applied in mental health research and treatment settings. In November 2016, the Laureate Institute for Brain Research organized the first Interoception Summit, a gathering of interoception experts from around the world, with the goal of accelerating progress in understanding the role of interoception in mental health. The discussions at the meeting were organized around four themes: interoceptive assessment, interoceptive integration, interoceptive psychopathology, and the generation of a roadmap that could serve as a guide for future endeavors. This review article presents an overview of the emerging consensus generated by the meeting.

The Neural Bases of Interoceptive Encoding and Recall in Healthy Adults and Adults With Depression

BACKGROUND

Theoretical models assert that the brain's interoceptive network links external stimuli with their interoceptive consequences, thereby supporting later recall of these associations to guide the selection of healthy behaviors. If these accounts are correct, previously reported interoceptive abnormalities in major depressive disorder (MDD) should lead to altered recall of associations between external stimuli and their interoceptive (somatic) consequences. To date, the processes underlying interoceptive recall have never been experimentally investigated.

METHODS

We designed and implemented the Interoceptive Encoding and Recall task to compare interoceptive and exteroceptive recall among subjects with MDD (n = 24) and healthy comparison subjects (n = 21). During the encoding phase, subjects learned to pair neutral visual cues (geometric shapes) with aversive interoceptive and exteroceptive stimuli. Later, while undergoing functional magnetic resonance imaging, subjects were prompted to recall the stimulus associated with each shape.

RESULTS

Interoceptive recall, relative to exteroceptive recall, was associated with bilateral mid-to-posterior insula activation. Relative to the healthy control participants, participants with depression exhibited marked hypoactivation of the right dorsal mid-insula during interoceptive recall.

CONCLUSIONS

In healthy control subjects, simply recalling a stimulus associated with a previous interoceptive challenge activated a key region in the brain's interoceptive network. Although previous research has linked MDD with aberrant processing of interoceptive stimuli, the current study is the first to demonstrate that individuals with MDD exhibit decreased insula activity while recalling interoceptive memories. It is possible that insula hypoactivation during interoceptive recall may affect the representation of prior interoceptive experiences in ways that contribute to depressive symptomology and the relationship between depression and systemic health.

Assessment of culture and environment in the Adolescent Brain and Cognitive Development Study: Rationale, description of measures, and early data

Neurodevelopmental maturation takes place in a social environment in addition to a neurobiological one. Characterization of social environmental factors that influence this process is therefore an essential component in developing an accurate model of adolescent brain and neurocognitive development, as well as susceptibility to change with the use of marijuana and other drugs. The creation of the Culture and Environment (CE) measurement component of the ABCD protocol was guided by this understanding. Three areas were identified by the CE Work Group as central to this process: influences relating to CE Group membership, influences created by the proximal social environment, influences stemming from social interactions. Eleven measures assess these influences, and by time of publication, will have been administered to well over 7,000 9-10 year-old children and one of their parents. Our report presents baseline data on psychometric characteristics (mean, standard deviation, range, skewness, coefficient alpha) of all measures within the battery. Effectiveness of the battery in differentiating 9-10 year olds who were classified as at higher and lower risk for marijuana use in adolescence was also evaluated. Psychometric characteristics on all measures were good to excellent; higher vs. lower risk contrasts were significant in areas where risk differentiation would be anticipated.

The Elicitation of Relaxation and Interoceptive Awareness Using Floatation Therapy in Individuals With High Anxiety Sensitivity

BACKGROUND

Floatation-REST (Reduced Environmental Stimulation Therapy), an intervention that attenuates exteroceptive sensory input to the nervous system, has recently been found to reduce state anxiety across a diverse clinical sample with high levels of anxiety sensitivity (AS). To further examine this anxiolytic effect, the present study investigated the affective and physiological changes induced by Floatation-REST and assessed whether individuals with high AS experienced any alterations in their awareness for interoceptive sensation while immersed in an environment lacking exteroceptive sensation.

METHODS

Using a within-subject crossover design, 31 participants with high AS were randomly assigned to undergo a 90-minute session of Floatation-REST or an exteroceptive comparison condition. Measures of self-reported affect and interoceptive awareness were collected before and after each session, and blood pressure was measured during each session.

RESULTS

Relative to the comparison condition, Floatation-REST generated a significant anxiolytic effect characterized by reductions in state anxiety and muscle tension and increases in feelings of relaxation and serenity (p < .001 for all variables). Significant blood pressure reductions were evident throughout the float session and reached the lowest point during the diastole phase (average reduction >12 mm Hg). The float environment also significantly enhanced awareness and attention for cardiorespiratory sensations.

CONCLUSIONS

Floatation-REST induced a state of relaxation and heightened interoceptive awareness in a clinical sample with high AS. The paradoxical nature of the anxiolytic effect in this sample is discussed in relation to Wolpe’s theory of reciprocal inhibition and the regulation of distress via sustained attention to present moment visceral sensations such as the breath.

Single-Subject Anxiety Treatment Outcome Prediction using Functional Neuroimaging

This corrects the article DOI: 10.1038/npp.2013.328.

Cardiorespiratory noise correction improves the ASL signal

Cardiorespiratory fluctuations such as changes in heart rate or respiration volume influence the temporal dynamics of cerebral blood flow (CBF) measurements during arterial spin labeling (ASL) fMRI. This "physiological noise" can confound estimates of resting state network activity, and it may lower the signal-to-noise ratio of ASL during task-related experiments. In this study we examined several methods for minimizing the contributions of both synchronized and non-synchronized physiological noise in ASL measures of CBF, by combining the RETROICOR approach with different linear deconvolution models. We evaluated the amount of variance in CBF that could be explained by each method during physiological rest, in both resting state and task performance conditions. To further demonstrate the feasibility of this approach, we induced low-frequency cardiorespiratory deviations via peripheral adrenergic stimulation with isoproterenol, and determined how these fluctuations influenced CBF, before and after applying noise correction. By suppressing physiological noise, we observed substantial improvements in the signal-to-noise ratio at the individual and group activation levels. Our results suggest that variations in cardiac and respiratory parameters can account for a large proportion of the variance in resting and task-based CBF, and indicate that regressing out these non-neuronal signal variations improves the intrinsically low signal-to-noise ratio of ASL. This approach may help to better identify and control physiologically driven activations in ASL resting state and task-based analyses.

Tulsa 1000: a naturalistic study protocol for multilevel assessment and outcome prediction in a large psychiatric sample

INTRODUCTION

Although neuroscience has made tremendous progress towards understanding the basic neural circuitry underlying important processes such as attention, memory and emotion, little progress has been made in applying these insights to psychiatric populations to make clinically meaningful treatment predictions. The overall aim of the Tulsa 1000 (T-1000) study is to use the NIMH Research Domain Criteria framework in order to establish a robust and reliable dimensional set of variables that quantifies the positive and negative valence, cognition and arousal domains, including interoception, to generate clinically useful treatment predictions.

METHODS AND ANALYSIS

The T-1000 is a naturalistic study that will recruit, assess and longitudinally follow 1000 participants, including healthy controls and treatment-seeking individuals with mood, anxiety, substance use and eating disorders. Each participant will undergo interview, behavioural, biomarker and neuroimaging assessments over the course of 1 year. The study goal is to determine how disorders of affect, substance use and eating behaviour organise across different levels of analysis (molecules, genes, cells, neural circuits, physiology, behaviour and self-report) to predict symptom severity, treatment outcome and long-term prognosis. The data will be used to generate computational models based on Bayesian statistics. The final end point of this multilevel latent variable analysis will be standardised assessments that can be developed into clinical tools to help clinicians predict outcomes and select the best intervention for each individual, thereby reducing the burden of mental disorders, and taking psychiatry a step closer towards personalised medicine.

ETHICS AND DISSEMINATION

Ethical approval was obtained from Western Institutional Review Board screening protocol #20101611. The dissemination plan includes informing health professionals of results for clinical practice, submitting results to journals for peer-reviewed publication, presenting results at national and international conferences and making the dataset available to researchers and mental health professionals.

TRIAL REGISTRATION NUMBER

NCT02450240; Pre-results.

Altered interoceptive activation before, during, and after aversive breathing load in women remitted from anorexia nervosa

BACKGROUND

The neural mechanisms of anorexia nervosa (AN), a severe and chronic psychiatric illness, are still poorly understood. Altered body state processing, or interoception, has been documented in AN, and disturbances in aversive interoception may contribute to distorted body perception, extreme dietary restriction, and anxiety. As prior data implicate a potential mismatch between interoceptive expectation and experience in AN, we examined whether AN is associated with altered brain activation before, during, and after an unpleasant interoceptive state change.

METHODS

Adult women remitted from AN (RAN; n = 17) and healthy control women (CW; n = 25) underwent functional magnetic resonance imaging during an inspiratory breathing load paradigm.

RESULTS

During stimulus anticipation, the RAN group, relative to CW, showed reduced activation in right mid-insula. In contrast, during the aversive breathing load, the RAN group showed increased activation compared with CW in striatum and cingulate and prefrontal cortices (PFC). The RAN group also showed increased activation in PFC, bilateral insula, striatum, and amygdala after stimulus offset. Time course analyses indicated that RAN responses in interoceptive processing regions during breathing load increased more steeply than those of CW. Exploratory analyses revealed that hyperactivation after breathing load was associated with markers of past AN severity.

CONCLUSIONS

Anticipatory deactivation with a subsequent exaggerated brain response during and after an aversive body state may contribute to difficulty predicting and adapting to internal state fluctuation. Because eating changes our interoceptive state, restriction may be one method of avoiding aversive, unpredictable internal change in AN.

The Insular Cortex Dynamically Maps Changes in Cardiorespiratory Interoception

Palpitations and dyspnea are fundamental to the human experience of panic anxiety, but it remains unclear how the brain dynamically represents changes in these interoceptive sensations. We used isoproterenol, a rapidly acting peripheral beta-adrenergic agonist similar to adrenaline, to induce sensations of palpitation and dyspnea in healthy individuals (n=23) during arterial spin labeling functional magnetic resonance imaging (fMRI). We hypothesized that the right mid-insular cortex, a central recipient of viscerosensory input, would preferentially respond during the peak period of cardiorespiratory stimulation. Bolus infusions of saline and isoproterenol (1 or 2 μg) were administered in a blinded manner while participants continuously rated the intensity of their cardiorespiratory sensation using a dial. Isoproterenol elicited dose-dependent increases in cardiorespiratory sensation, with all participants reporting palpitations and dyspnea at the 2 μg dose. Consistent with our hypothesis, the right mid-insula was maximally responsive during the peak period of sympathetic arousal, heart rate increase, and cardiorespiratory sensation. Furthermore, a shift in insula activity occurred during the recovery period, after the heart rate had largely returned to baseline levels, with an expansion of activation into anterior and posterior sectors of the right insula, as well as bilateral regions of the mid-insula. These results confirm the right mid-insula is a key node in the interoceptive network, and inform computational models proposing specific processing roles for insula subregions during homeostatic inference. The combination of isoproterenol and fMRI offers a powerful approach for evaluating insula function, and could be a useful probe for examining interoceptive dysfunction in psychiatric disorders.

The effect of single-dose methylphenidate on the rate of error-driven learning in healthy males: a randomized controlled trial

RATIONALE AND OBJECTIVES

Norepinephrine mediates the adjustment of error-driven learning to match the rate of change of the environment, while phasic dopamine signals prediction errors. We tested the hypothesis that pharmacologic manipulation may modulate this process.

METHODS

We administered a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, or placebo in double-blind randomized fashion to 20 healthy human males, who then performed a probabilistic learning task. Each subject was tested in two sessions, receiving methylphenidate in one session and placebo in the other, in randomized order. Task performance was quantified by the percentage of trials on which subjects chose the most likely option, while learning rate was measured using a computational model-based parameter as well as with a behavioral analogue of this parameter.

RESULTS

There was a substance-by-session interaction effect on behavioral learning rate and model-based learning rate, such that subjects receiving methylphenidate exhibited higher learning rates than those receiving placebo in session 1, with no difference observed in session 2, suggesting that subjects retained the increased learning rate across sessions. Higher behavioral learning rate was associated with both higher task performance and with the model-based learning rate. Higher learning rates were advantageous given the high rate of change on the task. Subjects receiving methylphenidate and placebo began the task in session 1 with a similar behavioral learning rate, but those receiving methylphenidate rapidly increased learning rate toward the optimal value, suggesting that methylphenidate accelerated the adaptation of learning rate based on the environment.

CONCLUSIONS

The results suggest that methylphenidate may improve disrupted probabilistic learning in disorders involving noradrenergic or dopaminergic dysfunction.

Anhedonia and anxiety underlying depressive symptomatology have distinct effects on reward-based decision-making

Depressive pathology, which includes both heightened negative affect (e.g., anxiety) and reduced positive affect (e.g., anhedonia), is known to be associated with sub-optimal decision-making, particularly in uncertain environments. Here, we use a computational approach to quantify and disambiguate how individual differences in these affective measures specifically relate to different aspects of learning and decision-making in reward-based choice behavior. Fifty-three individuals with a range of depressed mood completed a two-armed bandit task, in which they choose between two arms with fixed but unknown reward rates. The decision-making component, which chooses among options based on current expectations about reward rates, is modeled by two different decision policies: a learning-independent Win-stay/Lose-shift (WSLS) policy that ignores all previous experiences except the last trial, and Softmax, which prefers the arm with the higher expected reward. To model the learning component for the Softmax choice policy, we use a Bayesian inference model, which updates estimated reward rates based on the observed history of trial outcomes. Softmax with Bayesian learning better fits the behavior of 55% of the participants, while the others are better fit by a learning-independent WSLS strategy. Among Softmax “users”, those with higher anhedonia are less likely to choose the option estimated to be most rewarding. Moreover, the Softmax parameter mediates the inverse relationship between anhedonia and overall monetary gains. On the other hand, among WSLS “users”, higher state anxiety correlates with increasingly better ability of WSLS, relative to Softmax, to explain subjects’ trial-by-trial choices. In summary, there is significant variability among individuals in their reward-based, exploratory decision-making, and this variability is at least partly mediated in a very specific manner by affective attributes, such as hedonic tone and state anxiety.

Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior.

Neuroscience-informed psychoeducation for addiction medicine: A neurocognitive perspective

Psychoeducation (PE) is defined as an intervention with systematic, structured, and didactic knowledge transfer for an illness and its treatment, integrating emotional and motivational aspects to enable patients to cope with the illness and to improve its treatment adherence and efficacy. PE is considered an important component of treatment in both medical and psychiatric disorders, especially for mental health disorders associated with lack of insight, such as alcohol and substance use disorders (ASUDs). New advancements in neuroscience have shed light on how various aspects of ASUDs may relate to neural processes. However, the actual impact of neuroscience in the real-life clinical practice of addiction medicine is minimal. In this chapter, we provide a perspective on how PE in addiction medicine can be informed by neuroscience in two dimensions: content (knowledge we transfer in PE) and structure (methods we use to deliver PE). The content of conventional PE targets knowledge about etiology of illness, treatment process, adverse effects of prescribed medications, coping strategies, family education, and life skill training. Adding neuroscience evidence to the content of PE could be helpful in communicating not only the impact of drug use but also the beneficial impact of various treatments (i.e., on brain function), thus enhancing motivation for compliance and further destigmatizing their symptoms. PE can also be optimized in its "structure" by implicitly and explicitly engaging different neurocognitive processes, including salience/attention, memory, and self-awareness. There are many interactions between these two dimensions, structure and content, in the delivery of neuroscience-informed psychoeducation (NIPE). We explore these interactions in the development of a cartoon-based NIPE to promote brain recovery during addiction treatment as a part of the brain awareness for addiction recovery initiative.

Computational Dysfunctions in Anxiety: Failure to Differentiate Signal From Noise

BACKGROUND

Differentiating whether an action leads to an outcome by chance or by an underlying statistical regularity that signals environmental change profoundly affects adaptive behavior. Previous studies have shown that anxious individuals may not appropriately differentiate between these situations. This investigation aims to precisely quantify the process deficit in anxious individuals and determine the degree to which these process dysfunctions are specific to anxiety.

METHODS

One hundred twenty-two subjects recruited as part of an ongoing large clinical population study completed a change point detection task. Reinforcement learning models were used to explicate observed behavioral differences in low anxiety (Overall Anxiety Severity and Impairment Scale score ≤ 8) and high anxiety (Overall Anxiety Severity and Impairment Scale score ≥ 9) groups.

RESULTS

High anxiety individuals used a suboptimal decision strategy characterized by a higher lose-shift rate. Computational models and simulations revealed that this difference was related to a higher base learning rate. These findings are better explained in a context-dependent reinforcement learning model.

CONCLUSIONS

Anxious subjects' exaggerated response to uncertainty leads to a suboptimal decision strategy that makes it difficult for these individuals to determine whether an action is associated with an outcome by chance or by some statistical regularity. These findings have important implications for developing new behavioral intervention strategies using learning models.

Insular and cingulate attenuation during decision making is associated with future transition to stimulant use disorder

AIMS

To understand processes placing individuals at risk for stimulant (amphetamine and cocaine) use disorder.

DESIGN

Longitudinal study.

SETTING

University of California, San Diego Department of Psychiatry, CA, USA.

PARTICIPANTS

Occasional stimulant users (OSU; n = 184) underwent a baseline clinical interview and a functional magnetic resonance imaging (fMRI) session. On the basis of a follow-up clinical interview completed 3 years later, OSU (n = 147) were then categorized as problem stimulant users (PSU: n = 36; those who developed stimulant use disorders in the interim) or desisted stimulant users (DSU: n = 74; those who stopped using). OSU who did not meet criteria for PSU or DSU (n = 37) were included in dimensional analyses.

MEASUREMENTS

fMRI blood oxygen level-dependent (BOLD) contrast percentage signal change from baseline collected during a Paper-Scissors-Rock task was examined during three decision-making conditions, those resulting in: (1) wins, (2) ties and (3) losses. These data were used as dependent variables in categorical analyses comparing PSU and DSU, as well as dimensional analyses including interim drug use as predictors, controlling for baseline drug use.

FINDINGS

PSU exhibited lower anterior cingulate, middle insula, superior temporal, inferior parietal, precuneus and cerebellum activation than DSU across all three conditions (significant brain clusters required > 19 neighboring voxels to exceed F_(1,108)  = 5.58, P < 0.01 two-tailed; all Cohen's d > 0.83). Higher interim marijuana use was linked to lower pre-central and superior temporal activation during choices resulting in wins (> 19 neighboring voxels to exceed t = 2.61, P < 0.01 two-tailed; R² change > 0.11).

CONCLUSIONS

Individuals who transition from stimulant use to stimulant use disorder appear to show alterations in neural processing of stimulus valuation and outcome monitoring, patterns also evident in chronic stimulant use disorder. Attenuated anterior cingulate and insular processing may constitute a high-risk neural processing profile, which could be used to calculate risk scores for individuals experimenting with stimulants.

Latent variable analysis of positive and negative valence processing focused on symptom and behavioral units of analysis in mood and anxiety disorders

BACKGROUND

Mood and anxiety disorders are highly heterogeneous and their underlying pathology is complex. The Research Domain Criteria (RDoC) approach seeks to establish dimensionally and neuroscience-based descriptions of psychopathology that may inform better classification and treatment approaches. The current investigation sought to determine the latent variables underlying positive and negative valence processing in terms of symptoms and behavioral units of analysis.

METHOD

As part of an ongoing study, individuals with mood and anxiety problems were recruited largely from primary care clinics at UCLA (n=62) and UCSD (n=58). These participants underwent a comprehensive symptomatic and behavioral assessment. An implicit approach avoidance task and a modified dot probe detection task were used to measure positive and negative valence processing.

RESULTS

Principal components analysis with varimax rotation identified four symptom components, three behavioral components for the dot probe task, and two behavioral components for the implicit approach avoidance task. These components yielded two meta-components consisting of: negative valence symptoms, negative approach bias, and high sustained, selective attention; and positive valence symptoms, positive approach bias, and slow selective or sustained attention. The components did not differ between males and females, nor by age or medication status.

LIMITATIONS

The limitations are: (1) relatively small sample, (2) exploratory analysis strategy, (3) no test/re-test data, (4) no neural circuit analysis, and (5) limited reliability of behavioral data.

CONCLUSIONS

These preliminary data show that positive and negative valence processing domains load on independent dimensions. Taken together, multi-level assessment approaches combined with advanced statistical analyses may help to identify distinct positive and negative valence processes within a clinical population that cut across traditional diagnostic categories.

Response in taste circuitry is not modulated by hunger and satiety in women remitted from bulimia nervosa

Individuals with bulimia nervosa (BN) engage in episodes of binge eating, marked by loss of control and eating despite fullness. Does altered reward and metabolic state contribute to BN pathophysiology? Normally, hunger increases (and satiety decreases) reward salience to regulate eating. We investigated whether BN is associated with an abnormal response in a neural circuit involved in translating taste signals into motivated behavior, when hungry and fed. Twenty-six women remitted from BN (RBN) and 22 control women (CW) were administered water and sucrose during 2 counterbalanced fMRI visits, following a 16-hr fast or a standardized breakfast. Significant Group × Condition interactions were found in the left putamen, insula, and amygdala. Post hoc analyses revealed CW were significantly more responsive to taste stimuli when hungry versus fed in the left putamen and amygdala. In contrast, RBN response did not differ between conditions. Further, RBN had greater activation in the left amygdala compared with CW when fed. Findings suggest that RBN neural response to rewarding stimuli may not be modulated by metabolic state. Data raise the possibility that disinhibited eating in BN could result from a failure to devalue food reward when fed, resulting in an exaggerated response. (PsycINFO Database Record

Comparison of two different analysis approaches for DTI free-water corrected and uncorrected maps in the study of white matter microstructural integrity in individuals with depression

Diffusion tensor imaging (DTI) has often been used to examine white matter (WM) tract abnormalities in depressed subjects, but these studies have yielded inconsistent results, probably, due to gender composition or small sample size. In this study, we applied different analysis pipelines to a relatively large sample of individuals with depression to determine whether previous findings in depression can be replicated with these pipelines. We used a "standard" DTI algorithm and maps computed through a free-water (FW) corrected DTI. This latter algorithm is able to identify and separate the effects of extracellular FW on DTI metrics. Additionally, skeletonized and WM voxel-based analysis (VBA) methods were used. Using the skeletonized method, DTI maps showed lower fractional anisotropy (FA) in depressed subjects in the left brain hemisphere, including the anterior thalamic radiation (ATR L), cortical spinal tract (CST L), inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, and superior longitudinal fasciculus (SLF L). Differences in radial diffusivity (RD) were also found. For the VBA using RD, we found different results when we used FW uncorrected and corrected DTI metrics. Relative to the VBA approach, the skeletonized analysis was able to identify more clusters where WM integrity was altered in depressed individuals. Different significant correlations were found between RD and the Patient Health Questionnaire in the CST L, and SLF L. In conclusion, the skeletonized method revealed more clusters than the VBA and individuals with depression showed multiple WM abnormalities, some of which were correlated with disease severity Hum Brain Mapp 38:4690-4702, 2017. © 2017 Wiley Periodicals, Inc.