Neuroimaging predictors of treatment response in anxiety disorders

Association between resting-state connectivity patterns in the defensive system network and treatment response in spider phobia-a replication approach

Although highly effective on average, exposure-based treatments do not work equally well for all patients with anxiety disorders. The identification of pre-treatment response-predicting patient characteristics may enable patient stratification. Preliminary research highlights the relevance of inhibitory fronto-limbic networks as such. We aimed to identify pre-treatment neural signatures differing between exposure treatment responders and non-responders in spider phobia and to validate results through rigorous replication. Data of a bi-centric intervention study comprised clinical phenotyping and pre-treatment resting-state functional connectivity (rsFC) data of n = 79 patients with spider phobia (discovery sample) and n = 69 patients (replication sample). RsFC data analyses were accomplished using the Matlab-based CONN-toolbox with harmonized analyses protocols at both sites. Treatment response was defined by a reduction of >30% symptom severity from pre- to post-treatment (Spider Phobia Questionnaire Score, primary outcome). Secondary outcome was defined by a reduction of >50% in a Behavioral Avoidance Test (BAT). Mean within-session fear reduction functioned as a process measure for exposure. Compared to non-responders and pre-treatment, results in the discovery sample seemed to indicate that responders exhibited stronger negative connectivity between frontal and limbic structures and were characterized by heightened connectivity between the amygdala and ventral visual pathway regions. Patients exhibiting high within-session fear reduction showed stronger excitatory connectivity within the prefrontal cortex than patients with low within-session fear reduction. Whereas these results could be replicated by another team using the same data (cross-team replication), cross-site replication of the discovery sample findings in the independent replication sample was unsuccessful. Results seem to support negative fronto-limbic connectivity as promising ingredient to enhance response rates in specific phobia but lack sufficient replication. Further research is needed to obtain a valid basis for clinical decision-making and the development of individually tailored treatment options. Notably, future studies should regularly include replication approaches in their protocols.

An exploration of neural predictors of treatment compliance in cognitive-behavioral group therapy for hoarding disorder

A persistent and influential barrier to effective cognitive-behavioral therapy (CBT) for patients with hoarding disorder (HD) is treatment retention and compliance. Recent research has suggested that HD patients have abnormal brain activity identified by functional magnetic resonance (fMRI) in regions often engaged for executive functioning (e.g., right superior frontal gyrus, anterior insula, and anterior cingulate), which raises questions about whether these abnormalities could relate to patients' ability to attend, understand, and engage in HD treatment. We examined data from 74 HD-diagnosed adults who completed fMRI-measured brain activity during a discarding task designed to elicit symptom-related brain dysfunction, exploring which regions' activity might predict treatment compliance variables, including treatment engagement (within-session compliance), homework completion (between-session compliance), and treatment attendance. Brain activity that was significantly related to within- and between-session compliance was found largely in insula, parietal, and premotor areas. No brain regions were associated with treatment attendance. The results add to findings from prior research that have found prefrontal, cingulate, and insula activity abnormalities in HD by suggesting that some aspects of HD brain dysfunction might play a role in preventing the engagement needed for therapeutic benefit.

How a transdiagnostic approach can improve the treatment of emotional disorders: Insights from clinical psychology and neuroimaging

Multiple psychological treatments for emotional disorders have been developed and implemented, improving the quality of life of individuals. Nevertheless, relapse and poor response to psychotherapy are common. This article argues that a greater understanding of both the psychological and neurobiological mechanisms of change in psychotherapy is essential to improve treatment for emotional disorders. It aims to demonstrate how an understanding of these mechanisms provides a basis for (i) reconceptualizing some mental disorders, (ii) refining and establishing the evidence for existing therapeutic techniques and (iii) designing new techniques that precisely target the processes that maintain these disorders. Possible future directions for researchers and practitioners working at the intersection of neuropsychology and clinical psychology are discussed.

Measurement of Post-Treatment Changes in Brain Metabolites in Patients with Generalized Anxiety Disorder using Magnetic Resonance Spectroscopy

BACKGROUND

From previous studies, we know the correlations of some brain metabolites with a generalized anxiety disorder (GAD) and its symptoms. The response of GAD patients to various treatments is not the same and finding the best treatment option for each patient takes a long period of time.

OBJECTIVE

In this study, we try to examine if there is any relationship between a special treatment option and GAD patients' response and brain metabolite correlation with anxiety level change.

MATERIAL AND METHODS

This study is a clinical trial type of studies. We have used proton MRS (1H-MRS) with field strength of 3 Tesla to assess whether a different treatment option makes different responses based on metabolite changes. We chose 16 patients based on Hamilton's anxiety rate and a psychiatrist diagnosis. Patients were divided into two groups randomly. Each group took different treatments. Before treatment started, patients underwent MRS imaging and 8 weeks after treatment as well. Our study lacked a control group, and the results were analyzed by comparing the measured values of metabolites and clinical scores before and after treatment.

RESULTS

The NAA and Cho concentration increased after treatments and Cr concentration remained constant in both groups. Both groups showed improvements in their symptoms of anxiety and also in their clinical score rates. Sertraline group showed a more increase in NAA concentration than CBT and also a more decrease in HAMA and HAMD-17 scores.

CONCLUSION

A simultaneously increase in NAA and Cho in both groups and a decrease in clinical anxiety levels demonstrate that NAA and Cho concentration are associated negatively with anxiety levels. In addition, both CBT and sertraline are effective in the improvement of anxiety symptoms.

Identifying individual predictive factors for treatment efficacy

Given the heterogeneous responses to therapy and the high cost of treatments, there is an increasing interest in identifying pretreatment predictors of therapeutic effect. Clearly, the success of such an endeavor will depend on the amount of information that the patient-specific variables convey about the individual causal treatment effect on the response of interest. In the present work, using causal inference and information theory, a strategy is proposed to evaluate individual predictive factors for cancer immunotherapy efficacy. In a first step, the methodology proposes a causal inference model to describe the joint distribution of the pretreatment predictors and the individual causal treatment effect. Further, in a second step, the so-called predictive causal information (PCI), a metric that quantifies the amount of information the pretreatment predictors convey on the individual causal treatment effects, is introduced and its properties are studied. The methodology is applied to identify predictors of therapeutic success for a therapeutic vaccine in advanced lung cancer. A user-friendly R library EffectTreat is provided to carry out the necessary calculations.

Enriching CBT by Neuroscience: Novel Avenues to Achieve Personalized Treatments

Although cognitive behavioral therapy (CBT) is an established and efficient treatment for a variety of common mental disorders, a considerable number of patients do not respond to treatment or relapse after successful CBT. Recent findings and approaches from neuroscience could pave the way for clinical developments to enhance the outcome of CBT. Herein, we will present how neuroscience can offer novel perspectives to better understand (a) the biological underpinnings of CBT, (b) how we can enrich CBT with neuroscience-informed techniques (augmentation of CBT), and (c) why some patients may respond better to CBT than others (predictors of therapy outcomes), thus paving the way for more personalized and effective treatments. We will introduce some key topics and describe a selection of findings from CBT-related research using tools from neuroscience, with the hope that this will provide clinicians and clinical researchers with a brief and comprehensible overview of the field.

Neuroimaging, genetic, clinical, and demographic predictors of treatment response in patients with social anxiety disorder

BACKGROUND

Correct prediction of treatment response is a central goal of precision psychiatry. Here, we tested the predictive accuracy of a variety of pre-treatment patient characteristics, including clinical, demographic, molecular genetic, and neuroimaging markers, for treatment response in patients with social anxiety disorder (SAD).

METHODS

Forty-seven SAD patients (mean±SD age 33.9 ± 9.4 years, 24 women) were randomized and commenced 9 weeks' Internet-delivered cognitive behavior therapy (CBT) combined either with the selective serotonin reuptake inhibitor (SSRI) escitalopram (20 mg daily [10 mg first week], SSRI+CBT, n = 24) or placebo (placebo+CBT, n = 23). Treatment responders were defined from the Clinical Global Impression-Improvement scale (CGI-I ≤ 2). Before treatment, patients underwent functional magnetic resonance imaging and the Multi-Source Interference Task taxing cognitive interference. Support vector machines (SVMs) were trained to separate responders from nonresponders based on pre-treatment neural reactivity in the dorsal anterior cingulate cortex (dACC), amygdala, and occipital cortex, as well as molecular genetic, demographic, and clinical data. SVM models were tested using leave-one-subject-out cross-validation.

RESULTS

The best model separated treatment responders (n = 24) from nonresponders based on pre-treatment dACC reactivity (83% accuracy, P = 0.001). Responders had greater pre-treatment dACC reactivity than nonresponders especially in the SSRI+CBT group. No other variable was associated with clinical response or added predictive accuracy to the dACC SVM model.

LIMITATIONS

Small sample size, especially for genetic analyses. No replication or validation samples were available.

CONCLUSIONS

The findings demonstrate that treatment outcome predictions based on neural cingulate activity, at the individual level, outperform genetic, demographic, and clinical variables for medication-assisted Internet-delivered CBT, supporting the use of neuroimaging in precision psychiatry.

Resting-state connectivity of the bed nucleus of the stria terminalis and the central nucleus of the amygdala in clinical anxiety

Background

The central nucleus of the amygdala and bed nucleus of the stria terminalis are involved primarily in phasic and sustained aversive states. Although both structures have been implicated in pathological anxiety, few studies with a clinical population have specifically focused on them, partly because of their small size. Previous work in our group used high-resolution imaging to map the restingstate functional connectivity of the bed nucleus of the stria terminalis and the central nucleus of the amygdala in healthy subjects at 7 T, confirming and extending structural findings in humans and animals, while providing additional insight into cortical connectivity that is potentially unique to humans.

Methods

In the current follow-up study, we contrasted resting-state functional connectivity in the bed nucleus of the stria terminalis and central nucleus of the amygdala at 7 T between healthy volunteers (n = 30) and patients with generalized and/or social anxiety disorder (n = 30).

Results

Results revealed significant voxel-level group differences. Compared with healthy volunteers, patients showed stronger resting-state functional connectivity between the central nucleus of the amygdala and the lateral orbitofrontal cortex and superior temporal sulcus. They also showed weaker resting-state functional connectivity between the bed nucleus of the stria terminalis and the dorsolateral prefrontal cortex and occipital cortex.

Limitations

These findings depart from a previous report of resting-state functional connectivity in the central nucleus of the amygdala and bed nucleus of the stria terminalis under sustained threat of shock in healthy volunteers.

Conclusion

This study provides functional MRI proxies of the functional dissociation of the bed nucleus of the stria terminalis and central nucleus of the amygdala, and suggests that resting-state functional connectivity of key structures in the processing of defensive responses do not recapitulate changes related to induced state anxiety. Future work needs to replicate and further probe the clinical significance of these findings.

Posttraumatic stress disorder: a model of the longitudinal course and the role of risk factors

Posttraumatic stress disorder (PTSD) differs from other anxiety disorders in that experience of a traumatic event is necessary for the onset of the disorder. The condition runs a longitudinal course, involving a series of transitional states, with progressive modification occurring with time. Notably, only a small percentage of people that experience trauma will develop PTSD. Risk factors, such as prior trauma, prior psychiatric history, family psychiatric history, peritraumatic dissociation, acute stress symptoms, the nature of the biological response, and autonomic hyperarousal, need to be considered when setting up models to predict the course of the condition. These risk factors influence vulnerability to the onset of PTSD and its spontaneous remission. In the majority of cases, PTSD is accompanied by another condition, such as major depression, an anxiety disorder, or substance abuse. This comorbidity can also complicate the course of the disorder and raises questions about the role of PTSD in other psychiatric conditions. This article reviews what is known about the emergence of PTSD following exposure to a traumatic event using data from clinical studies.

Predictors of Pharmacotherapy Response in Generalized Anxiety Disorder: A Systematic Review

BACKGROUND

Pharmacotherapy for generalized anxiety disorder (GAD) may be effective in reducing symptoms in the majority of patients. The study of moderators and predictors of treatment response may help clinicians both to select appropriate interventions to maximize the probability of response and to inform the general prognosis.

METHODS

A systematic literature search of electronic databases, selected authors, and reference lists was used to identify articles that reported trials of drug monotherapy in GAD. Data on predictors and moderators were extracted. Quality of evidence was determined by the presence of a priori hypotheses, number of variables investigated, adequate quality of the measurement, and use of interaction-effects testing.

RESULTS

From the 98 articles meeting inclusion criteria, 24 reported a total of 22 factors associated with treatment response. The reported results were heterogeneous, ranging over sociodemographic, clinical, comorbidity, genetic, and functional-imaging studies. Major depressive symptoms were found to moderate treatment outcome in favor of antidepressants versus benzodiazepines. Neuroticism, previous treatment, genetic polymorphisms (including serotonin receptor gene 2A), and functional activation of the anterior cingulate cortex and amygdala were identified as potential predictors of treatment response.

CONCLUSIONS

Correlates of poor emotion regulation predicted poor treatment response, but subclinical depression was the only variable capable of informing treatment selection in this review. Future research should focus on further exploring the value of depression as a moderator and on a narrower list of potential genetic, brain-imaging, and temperament predictors of response to pharmacotherapy in GAD.

Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder

Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited. Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier. Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%. Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis.

Basolateral amygdala-ventromedial prefrontal cortex connectivity predicts cognitive behavioural therapy outcome in adults with obsessive-compulsive disorder

BACKGROUND

Cognitive behavioural therapy (CBT), including exposure and ritual prevention, is a first-line treatment for obsessive-compulsive disorder (OCD), but few reliable predictors of CBT outcome have been identified. Based on research in animal models, we hypothesized that individual differences in basolateral amygdala-ventromedial prefrontal cortex (BLA-vmPFC) communication would predict CBT outcome in patients with OCD.

METHODS

We investigated whether BLA-vmPFC resting-state functional connectivity (rs-fc) predicts CBT outcome in patients with OCD. We assessed BLA-vmPFC rs-fc in patients with OCD on a stable dose of a selective serotonin reuptake inhibitor who then received CBT and in healthy control participants.

RESULTS

We included 73 patients with OCD and 84 healthy controls in our study. Decreased BLA-vmPFC rs-fc predicted a better CBT outcome in patients with OCD and was also detected in those with OCD compared with healthy participants. Additional analyses revealed that decreased BLA-vmPFC rs-fc uniquely characterized the patients with OCD who responded to CBT.

LIMITATIONS

We used a sample of convenience, and all patients were receiving pharmacological treatment for OCD.

CONCLUSION

In this large sample of patients with OCD, BLA-vmPFC functional connectivity predicted CBT outcome. These results suggest that future research should investigate the potential of BLA-vmPFC pathways to inform treatment selection for CBT across patients with OCD and anxiety disorders.

Reward-related neural activity and structure predict future substance use in dysregulated youth

BACKGROUND

Identifying youth who may engage in future substance use could facilitate early identification of substance use disorder vulnerability. We aimed to identify biomarkers that predicted future substance use in psychiatrically un-well youth.

METHOD

LASSO regression for variable selection was used to predict substance use 24.3 months after neuroimaging assessment in 73 behaviorally and emotionally dysregulated youth aged 13.9 (s.d. = 2.0) years, 30 female, from three clinical sites in the Longitudinal Assessment of Manic Symptoms (LAMS) study. Predictor variables included neural activity during a reward task, cortical thickness, and clinical and demographic variables.

RESULTS

Future substance use was associated with higher left middle prefrontal cortex activity, lower left ventral anterior insula activity, thicker caudal anterior cingulate cortex, higher depression and lower mania scores, not using antipsychotic medication, more parental stress, older age. This combination of variables explained 60.4% of the variance in future substance use, and accurately classified 83.6%.

CONCLUSIONS

These variables explained a large proportion of the variance, were useful classifiers of future substance use, and showed the value of combining multiple domains to provide a comprehensive understanding of substance use development. This may be a step toward identifying neural measures that can identify future substance use disorder risk, and act as targets for therapeutic interventions.

A longitudinal fMRI investigation in acute post-traumatic stress disorder (PTSD)

Background Neuroimaging studies have implicated limbic, paralimbic, and prefrontal cortex in the pathophysiology of chronic post-traumatic stress disorder (PTSD). However, little is known about the neural substrates of acute PTSD and how they change with symptom improvement. Purpose To examine the neural circuitry underlying acute PTSD and brain function changes during clinical recovery from this disorder. Material and Methods Nineteen acute PTSD patients and nine non-PTSD subjects who all experienced a devastating mining accident underwent clinical assessment as well as functional magnetic resonance imaging (fMRI) scanning while viewing trauma-related and neutral pictures. Two years after the accident, a subgroup of 17 patients completed a second clinical evaluation, of which 13 were given an identical follow-up scan. Results Acute PTSD patients demonstrated greater activation in the vermis and right posterior cingulate, and greater deactivation in the bilateral medial prefrontal cortex and inferior parietal lobules than controls in the traumatic versus neutral condition. At follow-up, PTSD patients showed symptom reduction and decreased activation in the right middle frontal gyrus, bilateral posterior cingulate/precuneus, and cerebellum. Correlation results confirmed these findings and indicated that brain activation in the posterior cingulate/precuneus and vermis was predictive of PTSD symptom improvement. Conclusion The findings support the involvement of the medial prefrontal cortex, inferior parietal lobule, posterior cingulate, and vermis in the pathogenesis of acute PTSD. Brain activation in the vermis and posterior cingulate/precuneus appears to be a biological marker of recovery potential from PTSD. Furthermore, decreased activation of the middle frontal gyrus, posterior cingulate/precuneus, and cerebellum may reflect symptom improvement.

Amygdala-Cortical Connectivity: Associations with Anxiety, Development, and Threat

BACKGROUND

Amygdala-prefrontal cortex (PFC) functional connectivity may be influenced by anxiety and development. A prior study on anxiety found age-specific dysfunction in the ventromedial PFC (vmPFC), but not amygdala, associated with threat-safety discrimination during extinction recall (Britton et al.). However, translational research suggests that amygdala-PFC circuitry mediates responses following learned extinction. Anxiety-related perturbations may emerge in functional connectivity within this circuit during extinction recall tasks. The current report uses data from the prior study to examine how anxiety and development relate to task-dependent amygdala-PFC connectivity.

METHODS

Eighty-two subjects (14 anxious youths, 15 anxious adults, 25 healthy youths, 28 healthy adults) completed an extinction recall task, which directed attention to different aspects of stimuli. Generalized psychophysiological interaction analysis tested whether task-dependent functional connectivity with anatomically defined amygdala seed regions differed across anxiety and age groups.

RESULTS

Whole-brain analyses showed significant interactions of anxiety, age, and attention task (i.e., threat appraisal, explicit threat memory, physical discrimination) on left amygdala functional connectivity with the vmPFC and ventral anterior cingulate cortex (Talairach XYZ coordinates: -16, 31, -6 and 1, 36, -4). During threat appraisal and explicit threat memory (vs. physical discrimination), anxious youth showed more negative amygdala-PFC coupling, whereas anxious adults showed more positive coupling.

CONCLUSIONS

In the context of extinction recall, anxious youths and adults manifested opposite directions of amygdala-vmPFC coupling, specifically when appraising and explicitly remembering previously learned threat. Future research on anxiety should consider associations of both development and attention to threat with functional connectivity perturbations.

Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth

Behavioral and emotional dysregulation in childhood may be understood as prodromal to adult psychopathology. Additionally, there is a critical need to identify biomarkers reflecting underlying neuropathological processes that predict clinical/behavioral outcomes in youth. We aimed to identify such biomarkers in youth with behavioral and emotional dysregulation in the Longitudinal Assessment of Manic Symptoms (LAMS) study. We examined neuroimaging measures of function and white matter in the whole brain using 80 youth aged 14.0 (s.d.=2.0) from three clinical sites. Linear regression using the LASSO (Least Absolute Shrinkage and Selection Operator) method for variable selection was used to predict severity of future behavioral and emotional dysregulation measured by the Parent General Behavior Inventory-10 Item Mania Scale (PGBI-10M)) at a mean of 14.2 months follow-up after neuroimaging assessment. Neuroimaging measures, together with near-scan PGBI-10M, a score of manic behaviors, depressive behaviors and sex, explained 28% of the variance in follow-up PGBI-10M. Neuroimaging measures alone, after accounting for other identified predictors, explained ~1/3 of the explained variance, in follow-up PGBI-10M. Specifically, greater bilateral cingulum length predicted lower PGBI-10M at follow-up. Greater functional connectivity in parietal-subcortical reward circuitry predicted greater PGBI-10M at follow-up. For the first time, data suggest that multimodal neuroimaging measures of underlying neuropathologic processes account for over a third of the explained variance in clinical outcome in a large sample of behaviorally and emotionally dysregulated youth. This may be an important first step toward identifying neurobiological measures with the potential to act as novel targets for early detection and future therapeutic interventions.

Long-Term Pharmacological Treatments of Anxiety Disorders: An Updated Systematic Review

Many aspects of long-term pharmacological treatments for anxiety disorders (AnxDs) are still debated. We undertook an updated systematic review of long-term pharmacological studies on panic disorder (PD), generalized anxiety disorder (GAD), and social anxiety disorder (SAD). Relevant studies dating from January 1, 2012 to August 31, 2015 were identified using the PubMed database and a review of bibliographies. Of 372 records identified in the search, five studies on PD and 15 on GAD were included in the review. No studies on SAD were found. Our review confirms the usefulness of long-term pharmacological treatments for PD and GAD and suggests that they can provide further improvement over that obtained during short-term therapy. Paroxetine, escitalopram, and clonazepam can be effective for long-term treatment of PD. However, further studies are needed to draw conclusions about the long-term benzodiazepine use in PD, particularly for the possible cognitive side-effects over time. Pregabalin and quetiapine can be effective for long-term treatment of GAD, while preliminary suggestions emerged for agomelatine and vortioxetine. We did not find any evidence for determining the optimal length and/or dosage of medications to minimize the relapse risk. Few investigations have attempted to identify potential predictors of long-term treatment response. Personalized treatments for AnxDs can be implemented using predictive tools to explore those factors affecting treatment response/tolerability heterogeneity, including neurobiological functions/clinical profiles, comorbidity, biomarkers, and genetic features, and to tailor medications according to each patient's unique features.

Dissociation predicts treatment response in eye-movement desensitization and reprocessing for posttraumatic stress disorder

Using clinical data from a specialized trauma clinic, this study investigated pretreatment clinical factors predicting response to eye-movement desensitization and reprocessing (EMDR) among adult patients diagnosed with posttraumatic stress disorder (PTSD). Participants were evaluated using the Clinician-Administered PTSD Scale (CAPS), the Symptom Checklist-90-Revised, the Beck Depression Inventory, and the Dissociative Experiences Scale before treatment and were reassessed using the CAPS after treatment and at 6-month follow-up. A total of 69 patients underwent an average of 4 sessions of EMDR, and 60 (87%) completed the posttreatment evaluation, including 8 participants who terminated treatment prematurely. Intent-to-treat analysis revealed that 39 (65%) of the 60 patients were classified as responders and 21 (35%) as nonresponders when response was defined as more than a 30% decrease in total CAPS score. The nonresponders had higher levels of dissociation (depersonalization and derealization) and numbing symptoms, but other PTSD symptoms, such as avoidance, hyperarousal, and intrusion, were not significantly different. The number of psychiatric comorbidities was also associated with treatment nonresponse. The final logistic regression model yielded 2 significant variables: dissociation (p < .001) and more than 2 comorbidities compared to none (p < .05). These results indicate that complex symptom patterns in PTSD may predict treatment response and support the inclusion of the dissociative subtype of PTSD in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

Neuroimaging of psychotherapy for obsessive-compulsive disorder: A systematic review

The symptoms of obsessive-compulsive disorder (OCD) include intrusive thoughts, compulsive behavior, anxiety, and cognitive inflexibility, which are associated with dysfunction in dorsal and ventral corticostriato-thalamocortical (CSTC) circuits. Psychotherapy involving exposure and response prevention has been established as an effective treatment for the affective symptoms, but the impact on the underlying neural circuits is not clear. This systematic review used the Medline, Embase, and PsychINFO databases to investigate how successful therapy may affect neural substrates of OCD. Sixteen studies measuring neural changes after therapy were included in the review. The studies indicate that dysfunctions in neural function and structure are partly reversible and state-dependent for affective symptoms, which may also apply to cognitive symptoms. This is supported by post-treatment decreases of symptoms and activity in the ventral circuits during symptom provocation, as well as mainly increased activity in dorsal circuits during cognitive processing. These effects appear to be common to both psychotherapy and medication approaches. Although neural findings were not consistent across all studies, these findings indicate that people with OCD may experience functional, symptomatic, and neural recovery after successful treatment.

Clinical and Neurobiological Perspectives of Empowering Pediatric Cancer Patients Using Videogames

Pediatric oncology patients often experience fatigue and physical and mental deconditioning during and following chemotherapy treatments, contributing to diminished quality of life. Patient empowerment is a core principle of patient-centered care and reflects one's ability to positively affect his or her own health behavior and health status. Empowerment interventions may enhance patients' internal locus of control, resilience, coping skills, and self-management of symptoms related to disease and therapy. Clinical and technological advancements in therapeutic videogames and mobile medical applications (mobile health) can facilitate delivery of the empowerment interventions for medical purposes. This review summarizes clinical strategies for empowering pediatric cancer patients, as well as their relationship with developing a “fighting spirit” in physical and mental health. To better understand physiological aspects of empowerment and to elucidate videogame-based intervention strategies, brain neuronal circuits and neurotransmitters during stress, fear, and resilience are also discussed. Neuroimaging studies point to the role of the reward system pathways in resilience and empowerment in patients. Taken together, videogames and mobile health applications open translational research opportunities to develop and deliver empowerment interventions to pediatric cancer patients and also to those with other chronic diseases.

Validating predictors of therapeutic success: A causal inference approach

In personalized medicine medical decisions, practices and/or products are tailored to the individual patient. The idea is to provide the right patient with the right drug at the right dose at the right time. However, our current lack of ability to predict an individual patient's treatment success for most diseases and conditions is a major challenge to achieve the goal of personalized medicine. In the present work, we argue that many of the techniques often used to evaluate predictors of therapeutic success may not be able to answer the relevant scientific questions and we propose a new validation strategy based on causal inference. The methodology is illustrated using data from a clinical trial in opiate/heroin addiction. The user-friendly R library EffectTreat is provided to carry out the necessary calculations.

Predicting long-term outcome of Internet-delivered cognitive behavior therapy for social anxiety disorder using fMRI and support vector machine learning

Cognitive behavior therapy (CBT) is an effective treatment for social anxiety disorder (SAD), but many patients do not respond sufficiently and a substantial proportion relapse after treatment has ended. Predicting an individual's long-term clinical response therefore remains an important challenge. This study aimed at assessing neural predictors of long-term treatment outcome in participants with SAD 1 year after completion of Internet-delivered CBT (iCBT). Twenty-six participants diagnosed with SAD underwent iCBT including attention bias modification for a total of 13 weeks. Support vector machines (SVMs), a supervised pattern recognition method allowing predictions at the individual level, were trained to separate long-term treatment responders from nonresponders based on blood oxygen level-dependent (BOLD) responses to self-referential criticism. The Clinical Global Impression-Improvement scale was the main instrument to determine treatment response at the 1-year follow-up. Results showed that the proportion of long-term responders was 52% (12/23). From multivariate BOLD responses in the dorsal anterior cingulate cortex (dACC) together with the amygdala, we were able to predict long-term response rate of iCBT with an accuracy of 92% (confidence interval 95% 73.2-97.6). This activation pattern was, however, not predictive of improvement in the continuous Liebowitz Social Anxiety Scale-Self-report version. Follow-up psychophysiological interaction analyses revealed that lower dACC-amygdala coupling was associated with better long-term treatment response. Thus, BOLD response patterns in the fear-expressing dACC-amygdala regions were highly predictive of long-term treatment outcome of iCBT, and the initial coupling between these regions differentiated long-term responders from nonresponders. The SVM-neuroimaging approach could be of particular clinical value as it allows for accurate prediction of treatment outcome at the level of the individual.

Neural circuits in anxiety and stress disorders: a focused review

Anxiety and stress disorders are among the most prevalent neuropsychiatric disorders. In recent years, multiple studies have examined brain regions and networks involved in anxiety symptomatology in an effort to better understand the mechanisms involved and to develop more effective treatments. However, much remains unknown regarding the specific abnormalities and interactions between networks of regions underlying anxiety disorder presentations. We examined recent neuroimaging literature that aims to identify neural mechanisms underlying anxiety, searching for patterns of neural dysfunction that might be specific to different anxiety disorder categories. Across different anxiety and stress disorders, patterns of hyperactivation in emotion-generating regions and hypoactivation in prefrontal/regulatory regions are common in the literature. Interestingly, evidence of differential patterns is also emerging, such that within a spectrum of disorders ranging from more fear-based to more anxiety-based, greater involvement of emotion-generating regions is reported in panic disorder and specific phobia, and greater involvement of prefrontal regions is reported in generalized anxiety disorder and posttraumatic stress disorder. We summarize the pertinent literature and suggest areas for continued investigation.

Toward the application of functional neuroimaging to individualized treatment for anxiety and depression

Functional neuroimaging has led to significant gains in understanding the biological bases of anxiety and depressive disorders. However, the ability of functional neuroimaging to directly impact clinical practice is unclear. One important method by which neuroimaging could impact clinical care is to generate single patient level predictions that can guide clinical decision-making. The present review summarizes published functional neuroimaging studies of predictors of medication or psychotherapy outcome in major depressive disorder, obsessive-compulsive disorder (OCD), posttraumatic stress disorder, generalized anxiety disorder, panic disorder, and social anxiety disorder. In major depressive disorder and OCD, there is converging evidence of specific brain circuitry that has both been implicated in the disordered state itself, and where pretreatment activation levels have been predictive of treatment response. Specifically, in major depressive disorder, greater pretreatment ventral and pregenual anterior cingulate cortex (ACC) activation may predict better antidepressant medication outcome but poorer psychotherapy outcome. In OCD, activation in the ACC and orbitofrontal cortex has been inversely associated with pharmacological treatment response. In other anxiety disorders, research in this area is just beginning, with the ACC potentially implicated. However, the question of whether these results can directly translate to clinical practice remains open. In order to achieve the goal of single patient level prediction and individualized treatment, future research should strive to establish replicable models with good predictive performance and clear incremental validity.

Neural response during attentional control and emotion processing predicts improvement after cognitive behavioral therapy in generalized social anxiety disorder

BACKGROUND

Individuals with generalized social anxiety disorder (gSAD) exhibit attentional bias to salient stimuli, which is reduced in patients whose symptoms improve after treatment, indicating that mechanisms of bias mediate treatment success. Therefore, pre-treatment activity in regions implicated in attentional control over socio-emotional signals (e.g. anterior cingulate cortex, dorsolateral prefrontal cortex) may predict response to cognitive behavioral therapy (CBT), evidence-based psychotherapy for gSAD.

METHOD

During functional magnetic resonance imaging, 21 participants with gSAD viewed images comprising a trio of geometric shapes (circles, rectangles or triangles) alongside a trio of faces (angry, fearful or happy) within the same field of view. Attentional control was evaluated with the instruction to 'match shapes', directing attention away from faces, which was contrasted with 'match faces', whereby attention was directed to emotional faces.

RESULTS

Whole-brain voxel-wise analyses showed that symptom improvement was predicted by enhanced pre-treatment activity in the presence of emotional face distractors in the dorsal anterior cingulate cortex and dorsal medial prefrontal cortex. Additionally, CBT success was foretold by less activity in the amygdala and/or increased activity in the medial orbitofrontal gyrus during emotion processing.

CONCLUSIONS

CBT response was predicted by pre-treatment activity in prefrontal regions and the amygdala. The direction of activity suggests that individuals with intact attentional control in the presence of emotional distractors, regulatory capacity over emotional faces and/or less reactivity to such faces are more likely to benefit from CBT. Findings indicate that baseline neural activity in the context of attentional control and emotion processing may serve as a step towards delineating mechanisms by which CBT exerts its effects.