Resting state functional connectivity changes following mindfulness-based stress reduction predict improvements in disease control for patients with asthma.

BACKGROUND: The staggering morbidity associated with chronic inflammatory diseases can be reduced by psychological interventions, including Mindfulness-Based Stress Reduction (MBSR). Proposed mechanisms for MBSR's beneficial effects include changes in salience network function. Salience network perturbations are also associated with chronic inflammation, including airway inflammation in asthma, a chronic inflammatory disease affecting approximately 10% of the population. However, no studies have examined whether MBSR-related improvements in disease control are related to changes in salience network function. METHODS: Adults with asthma were randomized to 8 weeks of MBSR or a waitlist control group. Resting state functional connectivity was measured using fMRI before randomization, immediately post-intervention, and 4 months post-intervention. Using key salience network regions as seeds, we calculated group differences in change in functional connectivity over time and examined whether functional connectivity changes were associated with increased mindfulness, improved asthma control, and decreased inflammatory biomarkers. RESULTS: The MBSR group showed greater increases in functional connectivity between salience network regions relative to the waitlist group. Improvements in asthma control correlated with increased functional connectivity between the salience network and regions important for attention control and emotion regulation. Improvements in inflammatory biomarkers were related to decreased functional connectivity between the salience network and other networks. CONCLUSIONS: Increased resting salience network coherence and connectivity with networks that subserve attention and emotion regulation may contribute to the benefits of MBSR for patients with asthma. Understanding the neural underpinnings of MBSR-related benefits in patients is a critical step towards optimizing brain-targeted interventions for chronic inflammatory disease management.

How often should I meditate? A randomized trial examining the role of meditation frequency when total amount of meditation is held constant.

Meditation apps are the most commonly used mental health apps. However, the optimal dosing of app-delivered meditation practice has not been established. We examined whether the distribution of meditation practices across a day impacted outcomes in a distressed population. We investigated the effects of meditation practice frequency in a 2-week compassion-based meditation intervention delivered via the Healthy Minds Program app. Undergraduates with clinically elevated depression and/or anxiety (N = 351) were randomized to a massed (one 20-min meditation per day) or distributed condition (two 10-min meditations per day). Psychological distress (primary outcome; composite of depression and anxiety), experiential avoidance, fear of missing out, loneliness, and self-compassion were assessed pre- and post-intervention. Psychological distress, loneliness, and informal meditation practice were also assessed daily. Practice time and frequency were assessed using app data. Results support feasibility of the study design, success of the manipulation, and acceptability of the intervention. Pooled across conditions, participants exhibited pre-post improvements on all outcomes (absolute value of ds = 0.12-0.63, p ≤ .010) and trajectories of improvement on daily distress and loneliness (p ≤ .010). No between-group differences were observed on changes in pre-post or daily measures (ps = .158-.729). When total amount of meditation practice per day is held constant, the distribution of practice may not influence outcomes for distressed beginners. Although only a first test of dose frequency effects, findings support flexibility in the distribution of meditation throughout the day, which may increase accessibility. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Long-term Meditation Training Is Associated with Enhanced Subjective Attention and Stronger Posterior Cingulate-Rostrolateral Prefrontal Cortex Resting Connectivity.

Mindfulness meditation has been shown to increase resting-state functional connectivity (rsFC) between the posterior cingulate cortex (PCC) and dorsolateral prefrontal cortex (DLPFC), which is thought to reflect improvements in shifting attention to the present moment. However, prior research in long-term meditation practitioners lacked quantitative measures of attention that would provide a more direct behavioral correlate and interpretational anchor for PCC-DLPFC connectivity and was inherently limited by small sample sizes. Moreover, whether mindfulness meditation primarily impacts brain function locally, or impacts the dynamics of large-scale brain networks, remained unclear. Here, we sought to replicate and extend prior findings of increased PCC-DLPFC rsFC in a sample of 40 long-term meditators (average practice = 3759 hr) who also completed a behavioral assay of attention. In addition, we tested a network-based framework of changes in interregional connectivity by examining network-level connectivity. We found that meditators had stronger PCC-rostrolateral prefrontal cortex (RLPFC) rsFC, lower connector hub strength across the default mode network, and better subjective attention, compared with 124 meditation-naive controls. Orienting attention positively correlated with PCC-RLPFC connectivity and negatively correlated with default mode network connector hub strength. These findings provide novel evidence that PCC-RLPFC rsFC may support attention orienting, consistent with a role for RLPFC in the attention shifting component of metacognitive awareness that is a core component of mindfulness meditation training. Our results further demonstrate that long-term mindfulness meditation may improve attention and strengthen the underlying brain networks.

A Randomized Controlled Trial of a Smartphone-Based Well-Being Training in Public School System Employees During the COVID-19 Pandemic.

While the extraordinary pressures of the COVID-19 pandemic on student mental health have received considerable attention, less attention has been placed on educator well-being. School system employees play a vital role in society, and teacher levels of well-being are associated with the educational outcomes of young people. We extend extant research on the prevalence and correlates of educator distress during the pandemic by reporting on a pragmatic randomized wait-list controlled trial (N=662; 64% teachers) of an innovative mental health promotion strategy implemented during the pandemic; a free four-week smartphone-based meditation app designed to train key constituents of well-being (Healthy Minds Program; HMP). Following our preregistered analysis plan and consistent with hypotheses, assignment to the HMP predicted significantly larger reductions in psychological distress, our primary outcome, at post-intervention (Cohen's d=-0.52, 95% confidence interval [-0.68, -0.37], p<.001) and at the three-month follow-up (d=-0.33 [-0.48, -0.18], p<.001). Also consistent with hypotheses, we observed similar indications of immediate and sustained benefit following the HMP on all six preregistered secondary outcomes selected to tap skills targeted in the app (e.g., perseverative thinking, social connection, well-being; absolute ds=0.19-0.42, all ps<.031 corrected except mindful action at follow-up). We found no evidence for elevated adverse events and the HMP was equally effective among participants with elevated baseline anxiety and depressive symptoms. These data suggest that the HMP may be an effective and scalable approach to supporting the mental health and well-being of teachers and other school system employees, with implications for employee retention and performance, and student outcomes.

BrainAGE and regional volumetric analysis of a Buddhist monk: a longitudinal MRI case study.

Yongey Mingyur Rinpoche (YMR) is a Tibetan Buddhist monk, and renowned meditation practitioner and teacher who has spent an extraordinary number of hours of his life meditating. The brain-aging profile of this expert meditator in comparison to a control population was examined using a machine learning framework, which estimates "brain-age" from brain imaging. YMR's brain-aging rate appeared slower than that of controls suggesting early maturation and delayed aging. At 41 years, his brain resembled that of a 33-year-old. Specific regional changes did not differentiate YMR from controls, suggesting that the brain-aging differences may arise from coordinated changes spread throughout the gray matter.

A multimodal encoding model applied to imaging decision-related neural cascades in the human brain.

Perception and cognition in the brain are naturally characterized as spatiotemporal processes. Decision-making, for example, depends on coordinated patterns of neural activity cascading across the brain, running in time from stimulus to response and in space from primary sensory regions to the frontal lobe. Measuring this cascade is key to developing an understanding of brain function. Here we report on a novel methodology that employs multi-modal imaging for inferring this cascade in humans at unprecedented spatiotemporal resolution. Specifically, we develop an encoding model to link simultaneously measured electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) signals to infer high-resolution spatiotemporal brain dynamics during a perceptual decision. After demonstrating replication of results from the literature, we report previously unobserved sequential reactivation of a substantial fraction of the pre-response network whose magnitude correlates with a proxy for decision confidence. Our encoding model, which temporally tags BOLD activations using time localized EEG variability, identifies a coordinated and spatially distributed neural cascade that is associated with a perceptual decision. In general the methodology illuminates complex brain dynamics that would otherwise be unobservable using fMRI or EEG acquired separately.

Neurobiological correlates of impulsivity in healthy adults: Lower prefrontal gray matter volume and spontaneous eye-blink rate but greater resting-state functional connectivity in basal ganglia-thalamo-cortical circuitry.

Studies consistently implicate aberrance of the brain's reward-processing and decision-making networks in disorders featuring high levels of impulsivity, such as attention-deficit hyperactivity disorder, substance use disorder, and psychopathy. However, less is known about the neurobiological determinants of individual differences in impulsivity in the general population. In this study of 105 healthy adults, we examined relationships between impulsivity and three neurobiological metrics - gray matter volume, resting-state functional connectivity, and spontaneous eye-blink rate, a physiological indicator of central dopaminergic activity. Impulsivity was measured both by performance on a task of behavioral inhibition (go/no-go task) and by self-ratings of attentional, motor, and non-planning impulsivity using the Barratt Impulsiveness Scale (BIS-11). Overall, we found that less gray matter in medial orbitofrontal cortex and paracingulate gyrus, greater resting-state functional connectivity between nodes of the basal ganglia-thalamo-cortical network, and lower spontaneous eye-blink rate were associated with greater impulsivity. Specifically, less prefrontal gray matter was associated with higher BIS-11 motor and non-planning impulsivity scores, but was not related to task performance; greater correlated resting-state functional connectivity between the basal ganglia and thalamus, motor cortices, and prefrontal cortex was associated with worse no-go trial accuracy on the task and with higher BIS-11 motor impulsivity scores; lower spontaneous eye-blink rate was associated with worse no-go trial accuracy and with higher BIS-11 motor impulsivity scores. These data provide evidence that individual differences in impulsivity in the general population are related to variability in multiple neurobiological metrics in the brain's reward-processing and decision-making networks.

Prestimulus EEG alpha oscillations modulate task-related fMRI BOLD responses to auditory stimuli.

EEG alpha-band activity is generally thought to represent an inhibitory state related to decreased attention and play a role in suppression of task-irrelevant stimulus processing, but a competing hypothesis suggests an active role in processing task-relevant information - one in which phase dynamics are involved. Here we used simultaneous EEG-fMRI and a whole-brain analysis to investigate the effects of prestimulus alpha activity on the event-related BOLD response during an auditory oddball task. We separately investigated the effects of the posterior alpha rhythm's power and phase on activity related to task-relevant stimulus processing and also investigated higher-level decision-related processing. We found stronger decision-related BOLD activity in areas late in the processing stream when subjects were in the high alpha power state prior to stimulus onset, but did not detect any effect in primary sensory regions. Our phase analysis revealed correlates in the bilateral thalamus, providing support for a thalamo-cortical loop in attentional modulations and suggesting that the cortical alpha rhythm acts as a cyclic modulator of task-related responses very early in the processing stream. Our results help to reconcile the competing inhibition and active-processing hypotheses for ongoing alpha oscillations and begin to tease apart the distinct roles and mechanisms underlying their power and phase.

Simultaneous EEG-fMRI reveals temporal evolution of coupling between supramodal cortical attention networks and the brainstem.

Cortical and subcortical networks have been identified that are commonly associated with attention and task engagement, along with theories regarding their functional interaction. However, a link between these systems has not yet been demonstrated in healthy humans, primarily because of data acquisition and analysis limitations. We recorded simultaneous EEG-fMRI while subjects performed auditory and visual oddball tasks and used these data to investigate the BOLD correlates of single-trial EEG variability at latencies spanning the trial. We focused on variability along task-relevant dimensions in the EEG for identical stimuli and then combined auditory and visual data at the subject level to spatially and temporally localize brain regions involved in endogenous attentional modulations. Specifically, we found that anterior cingulate cortex (ACC) correlates strongly with both early and late EEG components, whereas brainstem, right middle frontal gyrus (rMFG), and right orbitofrontal cortex (rOFC) correlate significantly only with late components. By orthogonalizing with respect to event-related activity, we found that variability in insula and temporoparietal junction is reflected in reaction time variability, rOFC and brainstem correlate with residual EEG variability, and ACC and rMFG are significantly correlated with both. To investigate interactions between these correlates of temporally specific EEG variability, we performed dynamic causal modeling (DCM) on the fMRI data. We found strong evidence for reciprocal effective connections between the brainstem and cortical regions. Our results support the adaptive gain theory of locus ceruleus-norepinephrine (LC-NE) function and the proposed functional relationship between the LC-NE system, right-hemisphere ventral attention network, and P300 EEG response.

Simultaneous EEG-fMRI reveals a temporal cascade of task-related and default-mode activations during a simple target detection task.

Focused attention continuously and inevitably fluctuates, and to completely understand the mechanisms responsible for these modulations it is necessary to localize the brain regions involved. During a simple visual oddball task, neural responses measured by electroencephalography (EEG) modulate primarily with attention, but source localization of the correlates is a challenge. In this study we use single-trial analysis of simultaneously-acquired scalp EEG and functional magnetic resonance image (fMRI) data to investigate the blood oxygen level dependent (BOLD) correlates of modulations in task-related attention, and we unravel the temporal cascade of these transient activations. We hypothesize that activity in brain regions associated with various task-related cognitive processes modulates with attention, and that their involvements occur transiently in a specific order. We analyze the fMRI BOLD signal by first regressing out the variance linked to observed stimulus and behavioral events. We then correlate the residual variance with the trial-to-trial variation of EEG discriminating components for identical stimuli, estimated at a sequence of times during a trial. Post-stimulus and early in the trial, we find activations in right-lateralized frontal regions and lateral occipital cortex, areas that are often linked to task-dependent processes, such as attentional orienting, and decision certainty. After the behavioral response we see correlates in areas often associated with the default-mode network and introspective processing, including precuneus, angular gyri, and posterior cingulate cortex. Our results demonstrate that during simple tasks both task-dependent and default-mode networks are transiently engaged, with a distinct temporal ordering and millisecond timescale.

Prospective active marker motion correction improves statistical power in BOLD fMRI.

Group level statistical maps of blood oxygenation level dependent (BOLD) signals acquired using functional magnetic resonance imaging (fMRI) have become a basic measurement for much of systems, cognitive and social neuroscience. A challenge in making inferences from these statistical maps is the noise and potential confounds that arise from the head motion that occurs within and between acquisition volumes. This motion results in the scan plane being misaligned during acquisition, ultimately leading to reduced statistical power when maps are constructed at the group level. In most cases, an attempt is made to correct for this motion through the use of retrospective analysis methods. In this paper, we use a prospective active marker motion correction (PRAMMO) system that uses radio frequency markers for real-time tracking of motion, enabling on-line slice plane correction. We show that the statistical power of the activation maps is substantially increased using PRAMMO compared to conventional retrospective correction. Analysis of our results indicates that the PRAMMO acquisition reduces the variance without decreasing the signal component of the BOLD (beta). Using PRAMMO could thus improve the overall statistical power of fMRI based BOLD measurements, leading to stronger inferences of the nature of processing in the human brain.

Slower respiration rate is associated with higher self-reported well-being after wellness training.

Mind-body interventions such as mindfulness-based stress reduction (MBSR) may improve well-being by increasing awareness and regulation of physiological and cognitive states. However, it is unclear how practice may alter long-term, baseline physiological processes, and whether these changes reflect improved well-being. Using respiration rate (RR), which can be sensitive to effects of meditation, and 3 aspects of self-reported well-being (psychological well-being [PWB], distress, and medical symptoms), we tested pre-registered hypotheses that: (1) Lower baseline RR (in a resting, non-meditative state) would be a physiological marker associated with well-being, (2) MBSR would decrease RR, and (3) Training-related decreases in RR would be associated with improved well-being. We recruited 245 adults (age range = 18-65, M = 42.4): experienced meditators (n = 42), and meditation-naïve participants randomized to MBSR (n = 72), active control (n = 41), or waitlist control (n = 66). Data were collected at pre-randomization, post-intervention (or waiting), and long-term follow-up. Lower baseline RR was associated with lower psychological distress among long-term meditators (p* = 0.03, b = 0.02, 95% CI [0.01, 0.03]), though not in non-meditators prior to training. MBSR decreased RR compared to waitlist (p = 0.02, Cohen's d = - 0.41, 95% CI [- 0.78, - 0.06]), but not the active control. Decreased RR related to decreased medical symptoms, across all participants (p* = 0.02, b = 0.57, 95% CI [0.15, 0.98]). Post-training, lower RR was associated with higher PWB across training groups compared to waitlist (p* = 0.01, b = 0.06, 95% CI [0.02, 0.10]), though there were no significant differences in change in PWB between groups. This physiological marker may indicate higher physical and/or psychological well-being in those who engage in wellness practices.

Increased entrainment and decreased excitability predict efficacious treatment of closed-loop phase-locked rTMS for treatment-resistant depression.

Transcranial magnetic stimulation (TMS) is an FDA-approved therapy for major depressive disorder (MDD), specifically for patients who have treatment-resistant depression (TRD). However, TMS produces response or remission in about 50% of patients but is ineffective for the other 50%. Limits on efficacy may be due to individual patient variability, but to date, there are no good biomarkers or measures of target engagement. In addition, TMS efficacy is typically not assessed until a six-week treatment ends, precluding the evaluation of intermediate improvements during the treatment duration. Here, we report on results using a closed-loop phase-locked repetitive TMS (rTMS) treatment that synchronizes the delivery of rTMS based on the timing of the pulses relative to a patient's individual electroencephalographic (EEG) prefrontal alpha oscillation informed by functional magnetic resonance imaging (fMRI). We find that, in responders, synchronized delivery of rTMS produces two systematic changes in brain dynamics. The first change is a decrease in global cortical excitability, and the second is an increase in the phase entrainment of cortical dynamics. These two effects predict clinical outcomes in the synchronized treatment group but not in an active-treatment unsynchronized control group. The systematic decrease in excitability and increase in entrainment correlated with treatment efficacy at the endpoint and intermediate weeks during the synchronized treatment. Specifically, we show that weekly tracking of these biomarkers allows for efficacy prediction and potential of dynamic adjustments through a treatment course, improving the overall response rates.

EEG synchronized left prefrontal transcranial magnetic stimulation (TMS) for treatment resistant depression is feasible and produces an entrainment dependent clinical response: A randomized controlled double blind clinical trial.

BACKGROUND: Synchronizing a TMS pulse with a person's underlying EEG rhythm can modify the brain's response. It is unclear if synchronizing rTMS trains might boost the antidepressant effect of TMS. In this first-in-human trial, we demonstrated that a single TMS pulse over the prefrontal cortex produces larger effects in the anterior cingulate depending on when it is fired relative to the individual's EEG alpha phase. OBJECTIVE/HYPOTHESES: We had three hypotheses. 1) It is feasible to synchronize repetitive TMS (rTMS) delivery to a person's preferred prefrontal alpha phase in each train of every session during a 30-visit TMS depression treatment course. 2) EEG-synchronized rTMS would produce progressive entrainment greater than unsynchronized (UNSYNC) rTMS. And 3) SYNC TMS would have better antidepressant effects than UNSYNC (remission, final Hamilton Depression Rating <10). METHODS: We enrolled (n = 34) and treated (n = 28) adults with treatment resistant depression (TRD) and randomized them to receive six weeks (30 treatments) of left prefrontal rTMS at their individual alpha frequency (IAF) (range 6-13 Hz). Prior to starting the clinical trial, all patients had an interleaved fMRI-EEG-TMS (fET) scan to determine which phase of their alpha rhythm would produce the largest BOLD response in their dorsal anterior cingulate. Our clinical EEG-rTMS system then delivered the first TMS pulse in each train time-locked to this patient-specific 'preferred phase' of each patient's left prefrontal alpha oscillation. We randomized patients (1:1) to SYNC or UNSYNC, and all were treated at their IAF. Only the SYNC patients had the first pulse of each train for all sessions synchronized to their individualized preferred alpha phase (75 trains/session ×30 sessions, 2250 synchronizations per patient over six weeks). The UNSYNC group used a random firing with respect to the alpha wave. All other TMS parameters were balanced between the two groups. The system interfaced with a MagStim Horizon air-cooled Fig. 8 TMS coil. All patients were treated at their IAF, coil in the F3 position, 120 % MT, frequency 6-13 Hz, 40 pulses per train, average 15-s inter-train interval, 3000 pulses per session. All patients, raters, and treaters were blinded. RESULTS: In the intent to treat (ITT) sample, both groups had significant clinical improvement from baseline with no significant between-group differences, with the USYNC group having mathematically more remitters but fewer responders. (ITT -15 SYNC; 13 UNSYNC, response 5 (33 %), 1 (7 %), remission 2 (13 %), 6 (46 %). The same was true with the completer sample - 12 SYNC; 12 UNSYNC, response 4, 4 (both 30 %), remission 2 (17 %), 3 (25 %)). The clinical EEG phase synchronization system performed well with no failures. The average treatment session was approximately 90 min, with 30 min for placing the EEG cap and the actual TMS treatment for 45 min (which included gathering 10 min of resting EEG). Four subjects (1 SYNC) withdrew before six weeks of treatment. All 24 completer patients were treated for six weeks despite the trial occurring during the COVID pandemic. SYNC patients exhibited increased post-stimulation EEG entrainment over the six weeks. A detailed secondary analysis of entrainment data in the SYNC group showed that responders and non-responders in this group could be cleanly separated based on the total number of sessions with entrainment and the session-to-session precision of the entrained phase. For the SYNC group only, depression improvement was greater when more sessions were entrained at similar phases. CONCLUSIONS: Synchronizing prefrontal TMS with a patient's prefrontal alpha frequency in a blinded clinical trial is possible and produces progressive EEG entrainment in synchronized patients only. There was no difference in overall clinical response in this small clinical trial. A secondary analysis showed that the consistency of the entrained phase across sessions was significantly associated with response outcome only in the SYNC group. These effects may not simply be due to how the stimulation is delivered but also whether the patient's brain can reliably entrain to a precise phase. EEG-synchronized clinical delivery of TMS is feasible and requires further study to determine the best method for determining the phase for synchronization.

The timing of transcranial magnetic stimulation relative to the phase of prefrontal alpha EEG modulates downstream target engagement.

BACKGROUND: The communication through coherence model posits that brain rhythms are synchronized across different frequency bands and that effective connectivity strength between interacting regions depends on their phase relation. Evidence to support the model comes mostly from electrophysiological recordings in animals while evidence from human data is limited. METHODS: Here, an fMRI-EEG-TMS (fET) instrument capable of acquiring simultaneous fMRI and EEG during noninvasive single pulse TMS applied to dorsolateral prefrontal cortex (DLPFC) was used to test whether prefrontal EEG alpha phase moderates TMS-evoked top-down influences on subgenual, rostral and dorsal anterior cingulate cortex (ACC). Six runs (276 total trials) were acquired in each participant. Phase at each TMS pulse was determined post-hoc using single-trial sorting. Results were examined in two independent datasets: healthy volunteers (HV) (n = 11) and patients with major depressive disorder (MDD) (n = 17) collected as part of an ongoing clinical trial. RESULTS: In both groups, TMS-evoked functional connectivity between DLPFC and subgenual ACC (sgACC) depended on the EEG alpha phase. TMS-evoked DLPFC to sgACC fMRI-derived effective connectivity (EC) was modulated by EEG alpha phase in healthy volunteers, but not in the MDD patients. Top-down EC was inhibitory for TMS pulses during the upward slope of the alpha wave relative to TMS timed to the downward slope of the alpha wave. Prefrontal EEG alpha phase dependent effects on TMS-evoked fMRI BOLD activation of the rostral anterior cingulate cortex were detected in the MDD patient group, but not in the healthy volunteer group. DISCUSSION: Results demonstrate that TMS-evoked top-down influences vary as a function of the prefrontal alpha rhythm, and suggest potential clinical applications whereby TMS is synchronized to the brain's internal rhythms in order to more efficiently engage deep therapeutic targets.

Biomarkers predict the efficacy of closed-loop rTMS treatment for refractory depression.

Transcranial magnetic stimulation (TMS) is a non-invasive FDA-approved therapy for major depressive disorder (MDD), specifically for treatment-resistant depression (TRD). Though offering promise for those with TRD, its effectiveness is less than one in two patients (i.e., less than 50%). Limits on efficacy may be due to individual patient variability, but to date, there are no established biomarkers or measures of target engagement that can predict efficacy. Additionally, TMS efficacy is typically not assessed until a six-week treatment ends, precluding interim re-evaluations of the treatment. Here, we report results using a closed-loop phase-locked repetitive TMS (rTMS) treatment that synchronizes the delivery of rTMS based on the timing of the pulses relative to a patient's individual electroencephalographic (EEG) prefrontal alpha oscillation indexed by functional magnetic resonance imaging (fMRI). Among responders, synchronized rTMS produces two systematic changes in brain dynamics: a reduction in global cortical excitability and enhanced phase entrainment of cortical dynamics. These effects predict clinical outcomes in the synchronized treatment group but not in an active-treatment unsynchronized control group. The systematic decrease in excitability and increase in entrainment correlated with treatment efficacy at the endpoint and intermediate weeks during the synchronized treatment. Specifically, we show that weekly biomarker tracking enables efficacy prediction and dynamic adjustments through a treatment course, improving the overall response rates. This innovative approach advances the prospects of individualized medicine in MDD and holds potential for application in other neuropsychiatric disorders.

Clinically relevant effects of Mindfulness-Based Stress Reduction in individuals with asthma.

Background: Psychological distress and comorbid psychopathology contribute to exacerbation risk in patients with asthma. Thus, interventions designed to reduce stress and improve emotion regulation, such as Mindfulness-Based Stress Reduction (MBSR), may augment standard care. Few studies have addressed this question and a paucity of data exists to determine the ability of MBSR to impact clinical outcomes in asthma. Methods: This randomized controlled trial investigated effects of MBSR training on asthma control and airway inflammation, in relation to psychological symptoms, in adults with asthma. Participants were randomized to an 8-week MBSR training (n = 35) or wait-list control group (n = 34). Clinically relevant asthma assessments, including Asthma Control Questionnaire and inflammatory biomarkers, were collected at baseline and six approximately-monthly follow-ups. Self-reported mindfulness, distress, depression, and anxiety symptoms were assessed at baseline, post-intervention, and study completion. Chronic stress level was determined at baseline only. Results: Asthma control improved significantly in individuals randomized to MBSR, relative to wait-list controls (p = .01; effect size d = 0.76), which was maintained at 4mo post-intervention. 32% of MBSR participants achieved a clinically significant improvement, based on the ACQ6 Minimally Important Difference, relative to 12% of wait-list participants. Moreover, MBSR-related improvement in asthma control was associated with a reduction in distress (p = .043) and the intervention was most efficacious for those with the highest baseline depressive symptoms (p = .023). Importantly, MBSR also reduced levels of exhaled nitric oxide, a biomarker of airway inflammation, relative to wait-list controls (p < .05). Conclusion: Supporting and extending extant evidence of mind-body relationships in asthma and the benefits of stress reduction for these patients, this is, to the best of our knowledge, the first RCT to demonstrate that training in MBSR improves clinically relevant asthma outcomes. MBSR may thus be a valuable addition to optimal asthma management, particularly for those with comorbid psychopathology. Clinical trial registration: NCT02157766.

Absence of structural brain changes from mindfulness-based stress reduction: Two combined randomized controlled trials.

Studies purporting to show changes in brain structure following the popular, 8-week mindfulness-based stress reduction (MBSR) course are widely referenced despite major methodological limitations. Here, we present findings from a large, combined dataset of two, three-arm randomized controlled trials with active and waitlist (WL) control groups. Meditation-naïve participants (n = 218) completed structural magnetic resonance imaging scans during two visits: baseline and postintervention period. After baseline, participants were randomly assigned to WL (n = 70), an 8-week MBSR program (n = 75), or a validated, matched active control (n = 73). We assessed changes in gray matter volume, gray matter density, and cortical thickness. In the largest and most rigorously controlled study to date, we failed to replicate prior findings and found no evidence that MBSR produced neuroplastic changes compared to either control group, either at the whole-brain level or in regions of interest drawn from prior MBSR studies.

Daily prefrontal closed-loop repetitive transcranial magnetic stimulation (rTMS) produces progressive EEG quasi-alpha phase entrainment in depressed adults.

BACKGROUND: Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation modality that can treat depression, obsessive-compulsive disorder, or help smoking cessation. Research suggests that timing the delivery of TMS relative to an endogenous brain state may affect efficacy and short-term brain dynamics. OBJECTIVE: To investigate whether, for a multi-week daily treatment of repetitive TMS (rTMS), there is an effect on brain dynamics that depends on the timing of the TMS relative to individuals' prefrontal EEG quasi-alpha rhythm (between 6 and 13 Hz). METHOD: We developed a novel closed-loop system that delivers personalized EEG-triggered rTMS to patients undergoing treatment for major depressive disorder. In a double blind study, patients received daily treatments of rTMS over a period of six weeks and were randomly assigned to either a synchronized or unsynchronized treatment group, where synchronization of rTMS was to their prefrontal EEG quasi-alpha rhythm. RESULTS: When rTMS is applied over the dorsal lateral prefrontal cortex (DLPFC) and synchronized to the patient's prefrontal quasi-alpha rhythm, patients develop strong phase entrainment over a period of weeks, both over the stimulation site as well as in a subset of areas distal to the stimulation site. In addition, at the end of the course of treatment, this group's entrainment phase shifts to be closer to the phase that optimally engages the distal target, namely the anterior cingulate cortex (ACC). These entrainment effects are not observed in the group that is given rTMS without initial EEG synchronization of each TMS train. CONCLUSIONS: The entrainment effects build over the course of days/weeks, suggesting that these effects engage neuroplastic changes which may have clinical consequences in depression or other diseases.