Changes in functional connectivity after theta-burst transcranial magnetic stimulation for post-traumatic stress disorder: a machine-learning study.

Intermittent theta burst stimulation (iTBS) is a novel treatment approach for post-traumatic stress disorder (PTSD), and recent neuroimaging work indicates that functional connectivity profiles may be able to identify those most likely to respond. However, prior work has relied on functional magnetic resonance imaging, which is expensive and difficult to scale. Alternatively, electroencephalography (EEG) represents a different approach that may be easier to implement in clinical practice. To this end, we acquired an 8-channel resting-state EEG signal on participants before (n = 47) and after (n = 43) randomized controlled trial of iTBS for PTSD (ten sessions, delivered at 80% of motor threshold, 1,800 pulses, to the right dorsolateral prefrontal cortex). We used a cross-validated support vector machine (SVM) to track changes in EEG functional connectivity after verum iTBS stimulation. We found that an SVM classifier was able to successfully separate patients who received active treatment vs. sham treatment, with statistically significant findings in the Delta band (1-4 Hz, p = 0.002). Using Delta coherence, the classifier was 75.0% accurate in detecting sham vs. active iTBS, and observed changes represented an increase in functional connectivity between midline central/occipital and a decrease between frontal and central regions. The primary limitations of this work are the sparse electrode system and a modest sample size. Our findings raise the possibility that EEG and machine learning may be combined to provide a window into mechanisms of action of TMS, with the potential that these approaches can inform the development of individualized treatment methods.

Multimodal Elements of Suicidality Reduction After Transcranial Magnetic Stimulation.

OBJECTIVES: Repetitive transcranial magnetic stimulation (TMS) is a promising treatment for suicidality, but it is underlying neural mechanisms remain poorly understood. Our prior findings indicated that frontostriatal functional connectivity correlates with the severity of suicidal thoughts and behaviors. In this secondary analysis of data from an open label trial, we evaluated whether changes in frontostriatal functional connectivity would accompany suicidality reductions following TMS. We also explored the relationship between frontostriatal connectivity change and underlying white matter (WM) organization. MATERIALS AND METHODS: We conducted seed-based functional connectivity analysis on participants (N = 25) with comorbid post-traumatic stress disorder and depression who received eight weeks of 5 Hz TMS to left dorsolateral prefrontal cortex. We measured clinical symptoms with the Inventory of Depressive Symptomatology-Self Report (IDS-SR) and the PTSD Checklist for DSM-5 (PCL-5). We derived suicidality from IDS-SR item 18. Magnetic resonance imaging data were collected before TMS, and at treatment end point. These data were entered into analyses of covariance, evaluating the effect of suicidality change across treatment on striatal and thalamic functional connectivity. Changes in other PTSD and depression symptoms were included as covariates and results were corrected for multiple comparisons. Diffusion connectometry in a participant subsample (N = 17) explored the relationship between frontal WM integrity at treatment baseline and subsequent functional connectivity changes correlated with differences in suicidality. RESULTS: Suicidal ideation decreased in 65% of participants. Reductions in suicidality and functional connectivity between the dorsal striatum and frontopolar cortex were correlated (p-False Discover Rate-corrected < 0.001), after covariance for clinical symptom change. All other results were nonsignificant. Our connectometry results indicated that the integrity of frontostriatal WM may circumscribe functional connectivity response to TMS for suicide. CONCLUSIONS: Targeted reduction of fronto-striatal connectivity with TMS may be a promising treatment for suicidality. Future research can build on this multimodal approach to advance individualized stimulation approaches in high-risk patients.

A Brief Report on an 8-Week Course of Mindfulness-based Care for Chronic Pain in the Treatment of Veterans With Back Pain: Barriers Encountered to Treatment Engagement and Lessons Learned.

BACKGROUND: Chronic pain and associated symptoms are debilitating for veterans. Medical costs of treatments are high and current treatment options, most notably with opioid medications, have been associated with significant risk. Mindfulness-based interventions appear promising for chronic pain, but require additional testing in veteran care settings. OBJECTIVE: This project was designed to test the feasibility of engaging and retaining veterans with chronic lower back pain in a new mindfulness protocol tailored for veterans, mindfulness-based care for chronic pain (MBCP). Clinical outcomes were also assessed. DESIGN: An open pilot trial of an 8-week MBCP course that included meditation, gentle yoga, and psychoeducation. SUBJECTS: Twenty-two veterans (mean age=49.77; 18% women) were recruited from a VA Medical Center in the Northeastern US. After screening for inclusion/exclusion criteria, 20 were eligible at baseline. MEASURES: Veterans were assessed at baseline and postintervention for functional impairment, pain intensity and bothersomeness, depression, and mindfulness. RESULTS: The average number of sessions completed was 5; only 4 (20%) attended all sessions. Eleven of the 20 participants (55%) attended 5 or more sessions and had complete preintervention and postintervention visits. Five of the 11 had a clinically meaningful decrease in pain intensity and in depressive symptoms, while 6 of 11 had a meaningful decrease in pain bothersomeness and functional impairment. CONCLUSIONS: It was challenging to enroll and retain participants in this study, even with our intervention designed for veterans. We discuss possible adaptations and refinements in MBCP for veterans with chronic pain to enhance feasibility and improve upon these interventions.

Suicidal thoughts and behaviours among military veterans: protocol for a prospective, observational, neuroimaging study.

INTRODUCTION: This study's overarching goal is to examine the relationship between brain circuits and suicidal thoughts and behaviours (STBs) in a transdiagnostic sample of US military veterans. Because STBs have been linked with maladaptive decision-making and disorders linked to impulsivity, this investigation focuses on valence and inhibitory control circuits. METHODS AND ANALYSIS: In this prospective, observational study, we will collect functional MRI (fMRI), cognitive and clinical data from 136 veterans (target sample size) recruited from the Providence VA Health System (PVAHS): 68 with STBs and 68 matched controls. Behavioural data will be collected using standardised measures of STBs, psychiatric symptoms, cognition, functioning and medical history. Neuroimaging data will include structural, task and resting fMRI. We will conduct follow-up interviews and assessments at 6, 12 and 24 months post-enrolment. Primary analyses will compare data from veterans with and without STBs and will also evaluate whether activation and connectivity within circuits of valence and inhibition covary with historical and prospective patterns of suicidal ideation and behaviour. ETHICS AND DISSEMINATION: The PVAHS Institutional Review Board approved this study (2018-051). Written informed consent will be obtained from all participants. Findings from this study will be published in peer-reviewed journals and presented at local, regional, national and international conferences.Nauder Namaky, Ph.D.* nauder_namaky@brown.edu.

Combined transcranial magnetic stimulation and brief cognitive behavioral therapy for suicide: study protocol for a randomized controlled trial in veterans.

BACKGROUND: At least 17 veterans die every day from suicide. Although existing treatments such as brief cognitive behavioral therapy (BCBT) have been found to reduce suicide attempts in military personnel, a number of patients go on to attempt suicide after completing therapy. Thus, finding ways to enhance treatment efficacy to reduce suicide is critical. Repetitive transcranial magnetic stimulation (TMS) is a noninvasive technique that can be used to stimulate brain regions that are impaired in suicidal patients, that has been successfully used to augment treatments for psychiatric disorders implicated in suicide. The goal of this study is to test whether augmenting BCBT with TMS in suicidal veterans reduces rates of suicidal ideation, attempts, and other deleterious treatment outcomes. METHODS: One hundred thirty veterans with a suicide plan or suicidal behavior in the prior 2 weeks will be recruited from inpatient and outpatient settings at the Providence VA Medical Center in the USA. Veterans will be randomly assigned to receive 30 daily sessions of active or sham TMS in concert with a 12-week BCBT protocol in a parallel group design. Veterans will complete interviews and questionnaires related to psychiatric symptoms, suicidal ideation and behavior, treatment utilization, and functioning during a baseline assessment prior to treatment, at treatment endpoint, and 6- and 12-month follow-ups. Primary analyses will use mixed effect regressions to examine effects of treatment condition on suicidal behaviors, improvements in psychosocial functioning, and psychiatric hospitalization. Similar models as well as exploratory latent growth curve analyses will examine mediators and moderators of treatment effects. DISCUSSION: This protocol provides a framework for designing multilayered treatment studies for suicide. When completed, this study will be the first clinical trial evaluating the efficacy of augmenting BCBT for suicide with TMS. The results of this trial will have implications for treatment of suicide ideation and behaviors and implementation of augmented treatment designs. If positive, results from this study can be rapidly implemented across the VA system and will have a direct and meaningful impact on veteran suicide. TRIAL REGISTRATION: This study was registered prior to participant enrollment with ClinicalTrials.gov NCT03952468 . Registered on May 16, 2019. TRIAL SPONSOR CONTACT: Robert O'Brien (VA Health Services R&D), robert.obrien7@va.gov.

One-year clinical outcomes following theta burst stimulation for post-traumatic stress disorder.

Theta burst transcranial magnetic stimulation (TBS) is a potential new treatment for post-traumatic stress disorder (PTSD). We previously reported active intermittent TBS (iTBS) was associated with superior clinical outcomes for up to 1-month, in a sample of fifty veterans with PTSD, using a crossover design. In that study, participants randomized to the active group received a total of 4-weeks of active iTBS, or 2-weeks if randomized to sham. Results were superior with greater exposure to active iTBS, which raised the question of whether observed effects persisted over the longer-term. This study reviewed naturalistic outcomes up to 1-year from study endpoint, to test the hypothesis that greater exposure to active iTBS would be associated with superior outcomes. The primary outcome measure was clinical relapse, defined as any serious adverse event (e.g., suicide, psychiatric hospitalization, etc.,) or need for retreatment with repetitive transcranial magnetic stimulation (rTMS). Forty-six (92%) of the initial study's intent-to-treat participants were included. Mean age was 51.0 ± 12.3 years and seven (15.2%) were female. The group originally randomized to active iTBS (4-weeks active iTBS) demonstrated superior outcomes at one year compared to those originally randomized to sham (2-weeks active iTBS); log-rank ChiSq = 5.871, df = 1, p = 0.015; OR = 3.50, 95% CI = 1.04-11.79. Mean days to relapse were 296.0 ± 22.1 in the 4-week group, and 182.0 ± 31.9 in the 2-week group. When used, rTMS retreatment was generally effective. Exploratory neuroimaging revealed default mode network connectivity was predictive of 1-year outcomes (corrected p < 0.05). In summary, greater accumulated exposure to active iTBS demonstrated clinically meaningful improvements in the year following stimulation, and default mode connectivity could be used to predict longer-term outcomes.

Mapping PTSD symptoms to brain networks: a machine learning study.

Posttraumatic Stress Disorder (PTSD) is a prevalent and debilitating condition with complex and variable presentation. While PTSD symptom domains (intrusion, avoidance, cognition/mood, and arousal/reactivity) correlate highly, the relative importance of these symptom subsets often differs across patients. In this study, we used machine learning to derive how PTSD symptom subsets differ based upon brain functional connectivity. We acquired resting-state magnetic resonance imaging in a sample (N = 50) of PTSD patients and characterized clinical features using the PTSD Checklist for DSM-5 (PCL-5). We compared connectivity among 100 cortical and subcortical regions within the default mode, salience, executive, and affective networks. We then used principal component analysis and least-angle regression (LARS) to identify relationships between symptom domain severity and brain networks. We found connectivity predicted PTSD symptom profiles. The goodness of fit (R2) for total PCL-5 score was 0.29 and the R2 for intrusion, avoidance, cognition/mood, and arousal/reactivity symptoms was 0.33, 0.23, -0.01, and 0.06, respectively. The model performed significantly better than chance in predicting total PCL-5 score (p = 0.030) as well as intrusion and avoidance scores (p = 0.002 and p = 0.034). It was not able to predict cognition and arousal scores (p = 0.412 and p = 0.164). While this work requires replication, these findings demonstrate that this computational approach can directly link PTSD symptom domains with neural network connectivity patterns. This line of research provides an important step toward data-driven diagnostic assessments in PTSD, and the use of computational methods to identify individual patterns of network pathology that can be leveraged toward individualized treatment.