Decoding context memories for threat in large-scale neural networks.

Humans are often tasked with determining the degree to which a given situation poses threat. Salient cues present during prior events help bring online memories for context, which plays an informative role in this process. However, it is relatively unknown whether and how individuals use features of the environment to retrieve context memories for threat, enabling accurate inferences about the current level of danger/threat (i.e. retrieve appropriate memory) when there is a degree of ambiguity surrounding the present context. We leveraged computational neuroscience approaches (i.e. independent component analysis and multivariate pattern analyses) to decode large-scale neural network activity patterns engaged during learning and inferring threat context during a novel functional magnetic resonance imaging task. Here, we report that individuals accurately infer threat contexts under ambiguous conditions through neural reinstatement of large-scale network activity patterns (specifically striatum, salience, and frontoparietal networks) that track the signal value of environmental cues, which, in turn, allows reinstatement of a mental representation, primarily within a ventral visual network, of the previously learned threat context. These results provide novel insight into distinct, but overlapping, neural mechanisms by which individuals may utilize prior learning to effectively make decisions about ambiguous threat-related contexts as they navigate the environment.

Decoding neural reactivation of threat during fear learning, extinction, and recall in a randomized clinical trial of L-DOPA among women with PTSD.

BACKGROUND: Laboratory paradigms are widely used to study fear learning in posttraumatic stress disorder (PTSD). Recent basic science models demonstrate that, during fear learning, patterns of activity in large neuronal ensembles for the conditioned stimuli (CS) begin to reinstate neural activity patterns for the unconditioned stimuli (US), suggesting a direct way of quantifying fear memory strength for the CS. Here, we translate this concept to human neuroimaging and test the impact of post-learning dopaminergic neurotransmission on fear memory strength during fear acquisition, extinction, and recall among women with PTSD in a re-analysis of previously reported data. METHODS: Participants (N = 79) completed a context-dependent fear acquisition and extinction task on day 1 and extinction recall tests 24 h later. We decoded activity patterns in large-scale functional networks for the US, then applied this decoder to activity patterns toward the CS on day 1 and day 2. RESULTS: US decoder output for the CS+ increased during acquisition and decreased during extinction in networks traditionally implicated in human fear learning. The strength of US neural reactivation also predicted individuals skin conductance responses. Participants randomized to receive L-DOPA (n = 43) following extinction on day 1 demonstrated less US neural reactivation on day 2 relative to the placebo group (n = 28). CONCLUSION: These results support neural reactivation as a measure of memory strength between competing memories of threat and safety and further demonstrate the role of dopaminergic neurotransmission in the consolidation of fear extinction memories.

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Diminished prospective mental representations of reward mediate reward learning strategies among youth with internalizing symptoms.

BACKGROUND: Adolescent internalizing symptoms and trauma exposure have been linked with altered reward learning processes and decreased ventral striatal responses to rewarding cues. Recent computational work on decision-making highlights an important role for prospective representations of the imagined outcomes of different choices. This study tested whether internalizing symptoms and trauma exposure among youth impact the generation of prospective reward representations during decision-making and potentially mediate altered behavioral strategies during reward learning. METHODS: Sixty-one adolescent females with varying exposure to interpersonal violence exposure (n = 31 with histories of physical or sexual assault) and severity of internalizing symptoms completed a social reward learning task during fMRI. Multivariate pattern analyses (MVPA) were used to decode neural reward representations at the time of choice. RESULTS: MVPA demonstrated that rewarding outcomes could accurately be decoded within several large-scale distributed networks (e.g. frontoparietal and striatum networks), that these reward representations were reactivated prospectively at the time of choice in proportion to the expected probability of receiving reward, and that youth with behavioral strategies that favored exploiting high reward options demonstrated greater prospective generation of reward representations. Youth internalizing symptoms, but not trauma exposure characteristics, were negatively associated with both the behavioral strategy of exploiting high reward options as well as the prospective generation of reward representations in the striatum. CONCLUSIONS: These data suggest diminished prospective mental simulation of reward as a mechanism of altered reward learning strategies among youth with internalizing symptoms.

Large-scale neural network computations and multivariate representations during approach-avoidance conflict decision-making.

Many real-world situations require navigating decisions for both reward and threat. While there has been significant progress in understanding mechanisms of decision-making and mediating neurocircuitry separately for reward and threat, there is limited understanding of situations where reward and threat contingencies compete to create approach-avoidance conflict (AAC). Here, we leverage computational learning models, independent component analysis (ICA), and multivariate pattern analysis (MVPA) approaches to understand decision-making during a novel task that embeds concurrent reward and threat learning and manipulates congruency between reward and threat probabilities. Computational modeling supported a modified reinforcement learning model where participants integrated reward and threat value into a combined total value according to an individually varying policy parameter, which was highly predictive of decisions to approach reward vs avoid threat during trials where the highest reward option was also the highest threat option (i.e., approach-avoidance conflict). ICA analyses demonstrated unique roles for salience, frontoparietal, medial prefrontal, and inferior frontal networks in differential encoding of reward vs threat prediction error and value signals. The left frontoparietal network uniquely encoded degree of conflict between reward and threat value at the time of choice. MVPA demonstrated that delivery of reward and threat could accurately be decoded within salience and inferior frontal networks, respectively, and that decisions to approach reward vs avoid threat were predicted by the relative degree to which these reward vs threat representations were active at the time of choice. This latter result suggests that navigating AAC decisions involves generating mental representations for possible decision outcomes, and relative activation of these representations may bias subsequent decision-making towards approaching reward or avoiding threat accordingly.

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

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

Transcranial direct current stimulation targeting the medial prefrontal cortex modulates functional connectivity and enhances safety learning in obsessive-compulsive disorder: Results from two pilot studies.

BACKGROUND: Exposed-based psychotherapy is a mainstay of treatment for obsessive-compulsive disorder (OCD) and anxious psychopathology. The medial prefrontal cortex (mPFC) and the default mode network (DMN), which is anchored by the mPFC, promote safety learning. Neuromodulation targeting the mPFC might augment therapeutic safety learning and enhance response to exposure-based therapies. METHODS: To characterize the effects of mPFC neuromodulation on functional connectivity, 17 community volunteers completed resting-state functional magnetic resonance imaging scans before and after 20 min of frontopolar anodal multifocal transcranial direct current stimulation (tDCS). To examine the effects of tDCS on therapeutic safety learning, 24 patients with OCD completed a pilot randomized clinical trial; they were randomly assigned (double-blind, 50:50) to receive active or sham frontopolar tDCS before completing an in vivo exposure and response prevention (ERP) challenge. Changes in subjective emotional distress during the ERP challenge were used to index therapeutic safety learning. RESULTS: In community volunteers, frontal pole functional connectivity with the middle and superior frontal gyri increased, while connectivity with the anterior insula and basal ganglia decreased (ps < .001, corrected) after tDCS; functional connectivity between DMN and salience network also decreased after tDCS (ps < .001, corrected). OCD patients who received active tDCS exhibited more rapid therapeutic safety learning (ps < .05) during the ERP challenge than patients who received sham tDCS. CONCLUSIONS: Frontopolar tDCS may modulate mPFC and DMN functional connectivity and can accelerate therapeutic safety learning. Though limited by small samples, these findings motivate further exploration of the effects of frontopolar tDCS on neural and behavioral targets associated with exposure-based psychotherapies.

A flexible and generalizable model of online latent-state learning.

Many models of classical conditioning fail to describe important phenomena, notably the rapid return of fear after extinction. To address this shortfall, evidence converged on the idea that learning agents rely on latent-state inferences, i.e. an ability to index disparate associations from cues to rewards (or penalties) and infer which index (i.e. latent state) is presently active. Our goal was to develop a model of latent-state inferences that uses latent states to predict rewards from cues efficiently and that can describe behavior in a diverse set of experiments. The resulting model combines a Rescorla-Wagner rule, for which updates to associations are proportional to prediction error, with an approximate Bayesian rule, for which beliefs in latent states are proportional to prior beliefs and an approximate likelihood based on current associations. In simulation, we demonstrate the model's ability to reproduce learning effects both famously explained and not explained by the Rescorla-Wagner model, including rapid return of fear after extinction, the Hall-Pearce effect, partial reinforcement extinction effect, backwards blocking, and memory modification. Lastly, we derive our model as an online algorithm to maximum likelihood estimation, demonstrating it is an efficient approach to outcome prediction. Establishing such a framework is a key step towards quantifying normative and pathological ranges of latent-state inferences in various contexts.

Exploring Neural Correlates of Empathy in Juveniles Who Have Sexually Offended.

To effectively address the needs of youth who perpetrate sexual violence and reduce rates of recidivism, a better understanding of the mechanisms of juvenile sexual offending is needed. Current literature identifies various factors that are believed to put youth at risk for sexual offending, two of which are empathy deficits and childhood sexual abuse (CSA). The extent to which empathy deficits contribute to juvenile sexual offending, however, is often debated, though studies have not yet explored a neurobehavioral model of this mechanism. This pilot study used functional magnetic resonance imaging (fMRI) to explore the neural correlates of empathy in juveniles who sexually offend (JSOs), and the possible role of CSA. A total of 38 males (ages 12-20) were enrolled, including 11 healthy control subjects and 27 JSOs, of which, 11 had a history of CSA. Participants underwent clinical assessment and completed an empathy task during fMRI. Using both whole-brain and region-of-interest analysis, results of the fMRI data showed no statistical differences in engagement of brain regions associated with empathy between controls and all JSOs. There were also no significant differences between JSOs with and without a history of CSA. These null findings pose implications for guiding future research studies with larger samples and more statistical power, and may support the need to further explore empathy-related explanatory models and interventions for JSOs. Neuroimaging may demonstrate to be a useful tool to identify individualized risk factors and aid in tailoring interventions for this population.

Exploring Emotion Regulation in Juveniles Who Have Sexually Offended: An fMRI Study.

This exploratory study compared juveniles who sexually offend to nonoffending juveniles in their capacities to behaviorally and neurologically regulate, or reappraise, negative emotions. Participants were 39 juvenile males, including 10 healthy, nonoffending control subjects and 29 juveniles who sexually offend, comprising 12 juveniles who sexually offend with history of child sexual abuse. Participants completed a clinical assessment and a reappraisal task during functional magnetic resonance imaging. Difficulties in Emotional Regulation Scale results showed significantly less difficulties in emotion regulation among controls compared to juveniles who sexually offend, but when self-rating reappraisal abilities during the functional magnetic resonance imaging, all groups obtained comparable results. The imaging results showed no significant differences in fronto-temporal regions between controls and juveniles who sexually offend. Differences were found in other regions indicated in cognitive control, working memory, and emotional processing between controls and juveniles who sexually offend as well as between juveniles who sexually offend and those without history of child sexual abuse. Findings suggest that juveniles who sexually offend are capable of emotion regulation.

A comparison of statistical methods for detecting context-modulated functional connectivity in fMRI.

Many cognitive and clinical neuroscience research studies seek to determine how contextual factors modulate cognitive processes. In fMRI, hypotheses about how context modulates distributed patterns of information processing are often tested by comparing functional connectivity between neural regions A and B as a function of task conditions X and Y, which is termed context-modulated functional connectivity (FC). There exist two exploratory statistical approaches to testing context-modulated FC: the beta-series method and psychophysiological interaction (PPI) analysis methods. While these approaches are commonly used, their relative power for detecting context-modulated FC is unknown, especially with respect to real-world experimental parameters (e.g., number of stimulus repetitions, inter-trial-interval, stimulus duration). Here, we use simulations to compare power for detecting context-modulated FC between the standard PPI formulation (sPPI), generalized PPI formulation (gPPI), and beta series methods. Simulation results demonstrate that gPPI and beta series methods are generally more powerful than sPPI. Whether gPPI or beta series methods performed more powerfully depended on experiment parameters: block designs favor the gPPI, whereas the beta series method was more powerful for designs with more trial repetitions and it also retained more power under conditions of hemodynamic response function variability. On a real dataset of adolescent girls, the PPI methods appeared to have greater sensitivity in detecting task-modulated FC when using a block design and the beta series method appeared to have greater sensitivity when using an event-related design with many trial repetitions. Implications of these performance results are discussed.

Childhood maltreatment is associated with a sex-dependent functional reorganization of a brain inhibitory control network.

Childhood adversity represents a major risk factor for drug addiction and other mental disorders. However, the specific mechanisms by which childhood adversity impacts human brain organization to confer greater vulnerability for negative outcomes in adulthood is largely unknown. As an impaired process in drug addiction, inhibitory control of behavior was investigated as a target of childhood maltreatment (abuse and neglect). Forty adults without Axis-I psychiatric disorders (21 females) completed a Childhood Trauma Questionnaire (CTQ) and underwent functional MRI (fMRI) while performing a stop-signal task. A group independent component analysis identified a putative brain inhibitory control network. Graph theoretical analyses and structural equation modeling investigated the impact of childhood maltreatment on the functional organization of this neural processing network. Graph theory outcomes revealed sex differences in the relationship between network functional connectivity and inhibitory control which were dependent on the severity of childhood maltreatment exposure. A network effective connectivity analysis indicated that a maltreatment dose-related negative modulation of dorsal anterior cingulate (dACC) activity by the left inferior frontal cortex (IFC) predicted better response inhibition and lesser attention deficit hyperactivity disorder (ADHD) symptoms in females, but poorer response inhibition and greater ADHD symptoms in males. Less inhibition of the right IFC by dACC in males with higher CTQ scores improved inhibitory control ability. The childhood maltreatment-related reorganization of a brain inhibitory control network provides sex-dependent mechanisms by which childhood adversity may confer greater risk for drug use and related disorders and by which adaptive brain responses protect individuals from this risk factor.

Latent-state and model-based learning in PTSD.

Post-traumatic stress disorder (PTSD) is characterized by altered emotional and behavioral responding following a traumatic event. In this article, we review the concepts of latent-state and model-based learning (i.e., learning and inferring abstract task representations) and discuss their relevance for clinical and neuroscience models of PTSD. Recent data demonstrate evidence for brain and behavioral biases in these learning processes in PTSD. These new data potentially recast excessive fear towards trauma cues as a problem in learning and updating abstract task representations, as opposed to traditional conceptualizations focused on stimulus-specific learning. Biases in latent-state and model-based learning may also be a common mechanism targeted in common therapies for PTSD. We highlight key knowledge gaps that need to be addressed to further elaborate how latent-state learning and its associated neurocircuitry mechanisms function in PTSD and how to optimize treatments to target these processes.

Neural differentiation of emotional faces as a function of interpersonal violence among adolescent girls.

Interpersonal violence (IV) is associated with altered neural threat processing and risk for psychiatric disorder. Representational similarity analysis (RSA) is a multivariate approach examining the extent to which differences between stimuli correspond to differences in multivoxel activation patterns to these stimuli within each ROI. Using RSA, we examine overlap in neural patterns between threat and neutral faces in youth with IV. Participants were female adolescents aged 11-17 who had a history of IV exposure (n = 77) or no history of IV, psychiatric diagnoses, nor psychiatric medications (n = 37). Participants completed a facial emotion processing task during fMRI. Linear mixed models indicated that increasing hippocampal differentiation of fear and neutral faces was associated with increasing IV severity. Increased neural differentiation of these facial stimuli in the left and right hippocampus was associated with increasing physical abuse severity. Increased differentiation by the dACC correlated with increasing physical assault severity. RSA for most ROIs were not significantly associated with univariate activity, except for a positive association between amygdala RSA and activity to fear faces. Differences in statistically significant ROIs for physical assault and physical abuse may highlight distinct effects of trauma type on encoding of threat vs. neutral faces. Null associations between RSA and univariate activation in most ROIs suggest unique contributions of RSA for understanding IV compared to traditional activation. Implications include understanding mechanisms of risk in IV and trauma-specific treatment selection. Future work should replicate these findings in longitudinal studies and identify sensitive periods for neural alterations in RSA.

The role of recurrent trauma on post-traumatic stress disorder symptoms and substance use among trauma exposed youth.

Comorbidity between post-traumatic stress disorder (PTSD) and substance use disorder may be explained by a prospective trauma risk conferred by both conditions. The current study modeled concurrent and prospective associations of trauma, PTSD symptoms, and substance use (SU) behavior among trauma exposed youth (ages 8-20). Clinical interviews assessed trauma exposure, PTSD symptom severity, and SU behavior at baseline and at six- and 12-month follow up study visits (N = 2,069). Structural equation models assessed the associations of trauma, PTSD symptoms, and SU behavior. Lifetime trauma was associated with more severe PTSD symptoms and SU behaviors, whereas trauma exposure during the study was only associated with PTSD symptoms. PTSD symptom severity was prospectively associated with trauma exposure. PTSD symptom severity and SU behavior at follow-up study visits were prospectively associated. These results highlight the dynamic interplay between trauma, PTSD symptoms, and SU behavior during youth, a developmental period during which complex psychiatric presentations can have longstanding consequences for health.

The role of resilience in the development of depression, anxiety, and post-traumatic stress disorder after trauma in children and adolescents.

This investigation, conducted within the Texas Childhood Trauma Research Network, investigated the prospective relationships between resiliency and emergent internalizing symptoms among trauma-exposed youth. The cohort encompassed 1262 youth, aged 8-20, from twelve health-related institutions across Texas, who completed assessments at baseline and one- and six-month follow-ups for resiliency, symptoms of depression, generalized anxiety, posttraumatic stress disorder (PTSD), and other demographic and clinical characteristics. At baseline, greater resilience was positively associated with older age, male (vs female) sex assigned at birth, and history of mental health treatment. Unadjusted for covariates, higher baseline resilience was associated with greater prospective depression and PTSD symptoms but not anxiety symptoms. Upon adjusting for demographic and clinical factors, higher baseline resilience was no longer associated with depression, PTSD, or anxiety symptoms. Our analyses demonstrate that the predictive value of resilience on psychopathology is relatively small compared to more readily observable clinical and demographic factors. These data suggest a relatively minor prospective role of resilience in protecting against internalizing symptoms among trauma-exposed youth and highlight the importance of controlling for relevant youth characteristics when investigating a protective effect of resilience on internalizing symptoms.

Sadness, suicide, and sexual behavior in Arkansas: results from the youth risk behavior survey 2011.

We used the 2011 Arkansas Youth Risk Behavior Survey to estimate the prevalence of risky sexual behavior and sexual assault and to measure its association with teen suicidality. In Arkansas, 50.3% of students reported ever having sexual intercourse, 26% onset at 14 or younger, 36 % having had more than one partner, and 10.2% having been physically forced to have sex. "Being forced to have sex" was a risk factor for depression and all components of the suicide continuum. Additionally, early onset of sexual activity and having more than one partner increased the risk for depression, suicidal ideation, plan, and attempt. Suicide is a grievous and preventable tragedy, sadly standing among the leading causes of death for teens.' In this series, we examine risk factors for suicidality among Arkansas high school students; in this installment, we examine sexual behavior. A previous study utilizing the Rhode Island Youth Risk Behavior Survey (YRBS) found an association between having forced sexual intercourse and suicide. Furthermore, an association between psychiatric disorders and risky sexual behaviors, including both early onset and number of partners was found in a birth cohort study revealed. We hypothesize that Arkansas' teens reporting risky sexual behavior and sexual assault are at higher risk of depression and suicidality as well.

Circulating endocannabinoids and psychological outcomes in women with PTSD.

BACKGROUND: Recent research has attempted to elucidate the relationship between blood-based biomarkers (e.g., endocannabinoids; eCBs: including N-arachidonoylethanolamine [AEA] and 2-arachidonoylglycerol [2-AG]) and mental health outcomes in psychiatric populations such as posttraumatic stress disorder (PTSD). Prior research suggests that adults with PTSD may have altered circulating eCB tone and a blunted mobilization of eCBs (particularly 2-AG) in response to stress (e.g., aerobic exercise), although our understanding has been limited in part due to heterogenous samples and small sample sizes. METHODS: A subset of data was pooled from five studies in which women with and without PTSD (N = 98) completed questionnaires related to mood states and a blood draw prior to and following a bout of moderate-intensity aerobic exercise in order to determine: 1) whether circulating eCBs differ between groups and whether depressive and PTSD symptom severity are associated with baseline eCBs, 2) whether a bout of aerobic exercise increases circulating eCBs in adult women with PTSD, and 3) whether circulating eCBs are associated with overall mood states and exercise-induced improvements in mood states in women with and without PTSD. RESULTS: PTSD diagnoses were not associated with baseline concentrations of eCBs. Greater depressive symptom severity and PTSD symptom severity within the negative alteration in cognition and mood cluster were associated with lower circulating AEA. Circulating AEA significantly increased following aerobic exercise for both groups, whereas circulating 2-AG only increased in women without PTSD. Greater circulating AEA within the PTSD group was associated with lower depressive mood, confusion, and total mood disturbance. CONCLUSIONS: These findings suggest that greater circulating AEA is associated with better overall mood and lower depressive and PTSD symptom severity, and that an acute bout of moderate-intensity aerobic exercise increases circulating AEA (but not 2-AG) in adult women with PTSD. These findings are consistent with the idea that greater eCB tone (particularly AEA) following pharmacological and/or non-pharmacological manipulations may be beneficial for improving psychological outcomes (e.g., mood, cognition) among PTSD, and possibly other psychiatric populations.

Aerobic exercise in the treatment of PTSD: An examination of preclinical and clinical laboratory findings, potential mechanisms, clinical implications, and future directions.

Posttraumatic stress disorder (PTSD) is associated with heightened emotional responding, avoidance of trauma related stimuli, and physical health concerns (e.g., metabolic syndrome, type 2 diabetes, cardiovascular disease). Existing treatments such as exposure-based therapies (e.g., prolonged exposure) aim to reduce anxiety symptoms triggered by trauma reminders, and are hypothesized to work via mechanisms of extinction learning. However, these conventional gold standard psychotherapies do not address physical health concerns frequently presented in PTSD. In addition to widely documented physical and mental health benefits of exercise, emerging preclinical and clinical evidence supports the hypothesis that precisely timed administration of aerobic exercise can enhance the consolidation and subsequent recall of fear extinction learning. These findings suggest that aerobic exercise may be a promising adjunctive strategy for simultaneously improving physical health while enhancing the effects of exposure therapies, which is desirable given the suboptimal efficacy and remission rates. Accordingly, this review 1) encompasses an overview of preclinical and clinical exercise and fear conditioning studies which form the basis for this claim; 2) discusses several plausible mechanisms for enhanced consolidation of fear extinction memories following exercise, and 3) provides suggestions for future research that could advance the understanding of the potential importance of incorporating exercise into the treatment of PTSD.

The influence of aerobic exercise on model-based decision making in women with posttraumatic stress disorder.

Individuals with PTSD often exhibit deficits in executive functioning. An unexplored aspect of neurocognitive functions associated with PTSD is the type of learning system engaged in during decision-making. A model-free (MF) system is habitual in nature and involves trial-and-error learning that is often updated based on the most recent experience (e.g., repeat action if rewarded). A model-based (MB) system is goal-directed in nature and involves the development of an abstract representation of the environment to facilitate decisions (e.g., choose sequence of actions according to current contextual state and predicted outcomes). The existing neurocognitive literature on PTSD suggests the hypothesis of greater reliance on MF vs MB learning strategies when navigating their environment. While MF systems may be more cognitively efficient, they do not afford flexibility when making prospective predictions about likely outcomes of different decision-tree branches. Emerging research suggests that an acute bout of aerobic exercise improves certain aspects of neurocognition, and thereby could promote the utilization of MB over MF systems during decision making, although prior research has not yet tested this hypothesis. Accordingly, the current study administered a lab-based two-stage Markov decision-making task capable of discriminating MF vs MB decision making, in order to determine if moderate-intensity aerobic exercise (either shortly after or 30-minutes after the exercise bout has ended) promotes greater engagement in MB behavioral strategies compared to light-intensity aerobic exercise in adult women with and without PTSD (N=61). Results revealed that control women generally displayed higher levels of MB behavior that was further increased following immediate exercise, particularly moderate-intensity exercise. By contrast, the PTSD group generally displayed lower levels of MB behavior, and exhibited greater MB behavior when completing the task following moderate-intensity aerobic exercise compared to light-intensity aerobic exercise regardless of whether there was a short or long delay between exercise and the task. Additionally, women with PTSD demonstrated less impairment in MB decision-making compared to controls following moderate-intensity aerobic exercise. These results suggest that an acute bout of moderate-intensity aerobic exercise boosts MB behavior in women with PTSD, and suggests that aerobic exercise may play an important role in enhancing cognitive outcomes for PTSD.