BACKGROUND:Repetitive transcranial magnetic stimulation (rTMS) may have an analgesic effect in neuropathic pain. However, clinical application is notably limited by a variable rate of responders. We aimed to (i) assess the analgesic efficacy of prolonged continuous theta burst stimulation (pcTBS) delivered to M1, (ii) study the analgesic effect of maintenance treatment in responders., and (iii) examine the analgesic efficacy of switching to the left dorsolateral prefrontal cortex (DLPFC) in nonresponders. METHODS:We conducted a randomized, sham-controlled, and double-blind study in chronic neuropathic pain participants (n = 94). In part 1, participants were randomized to receive 5 days of either pcTBS, 10-Hz rTMS, or sham stimulation over the left M1. In the subsequent parts, responders to either active treatment in part 1 continued with biweekly sessions for four weeks (part 2), while nonresponders in part 1 received 5 days of stimulation on the left DLPFC (part 3). Corticospinal excitability was assessed via measurements of motor-evoked potential (MEP) and cortical silent period (CSP) recorded from the right first dorsal interosseous (FDI) muscle. RESULTS:Among the 94 participants randomized into treatment groups, 5 days of M1 stimulation with either pcTBS or 10-Hz rTMS showed significant analgesia compared to baseline (mean [standard deviation {SD}]: 10-Hz 37.9 ± 17.5 vs 48.5 ± 16.0, P < .001; pcTBS 35.1 ± 15.3 vs 47.1 ± 15.1, P < .001), but the two active groups did not differ from each other (P = .16). However, pcTBS induced more rapid corticospinal excitability changes (MEP pcTBS versus Sham: 188.5 ± 39.8 vs 102.2 ± 6.9, P = .044; CSP pcTBS versus Sham: 113.9 ± 3.8 vs 101.7 ± 3.3, P = .039), whereas no significant changes were observed in the 10-Hz group during the same period (MEP 10-Hz versus Sham:115.7 ± 9.3 vs 102.2 ± 6.9, Pcorrected = 1.000; CSP 10-Hz versus Sham: 103.6 ± 2.9 vs 101.7 ± 3.3, Pcorrected = 1.000). In the responder group, additional maintenance sessions further increased analgesia (time effect: Post2 versus Post1: 21.3 ± 2.1 vs 27.1 ± 2.3, P = .006) and maintained analgesic effect for 1 month in both the pcTBS and 10-Hz rTMS treatment groups (follow-up versus Post1: 29.9 ± 2.7 vs 27.1 ± 2.3, P = .74). Additional sessions also increased corticospinal excitability, and this was associated with less pain during the follow-up period (r = -0.48, P = .037). Pain symptoms were improved more by pcTBS (post versus pre: 11.3 ± 5.5 vs 13.1 ± 5.3, P = .020) than by 10-Hz rTMS (post versus pre: 15.9 ± 7.2 vs 15.5 ± 6.4, P = .978) when both were applied to the left DLPFC in initial nonresponders. CONCLUSIONS:This study demonstrates that pcTBS applied to M1 is an effective treatment for chronic neuropathic pain, with analgesic efficacy comparable to conventional 10-Hz rTMS. The protocol offers a substantial reduction in treatment time, opening perspectives for more efficient clinical application.

Traumatic brain injury (TBI) is linked to persistent cognitive and functional impairment, yet its long-term effects on the spatiotemporal organization of brain activity remain unclear. Electroencephalography (EEG) studies have reported spectral power and functional connectivity (FC) abnormalities following TBI, but little is known about whether injury also disrupts propagating oscillatory activity such as travelling waves. Resting-state EEG was analysed from a large clinical dataset (Temple University Hospital EEG Corpus) including 174 individuals with TBI and 174 age- and sex-matched non-TBI clinical controls. FC was estimated using the debiased weighted phase lag index and tested using network-based statistic. Spectral power differences were computed with cluster-based permutation. Travelling waves were quantified along left- and right-lateral electrode lines using two-dimensional Fast Fourier Transforms to extract forward (posterior-to-anterior) and backward (anterior-to-posterior) propagation in theta and alpha bands. TBI participants exhibited lower alpha-band connectivity (p < 0.001) and higher theta-band connectivity (p = 0.011) relative to controls. Spectral analyses revealed stronger theta power (p = 4.6 × 10-4) and weaker posterior alpha power (p = 0.008). Critically, travelling-wave analyses showed weaker backward theta waves in TBI across hemispheres, surviving multiple comparison correction in the left (p = 0.007), but not right (p = 0.018). These findings link TBI to altered oscillatory power, disrupted FC, and weaker backward travelling theta waves, consistent with impaired top-down coordination. The opposing pattern of theta hyperconnectivity alongside alpha hypoconnectivity may reflect compensatory but inefficient large-scale communication. Travelling-wave analysis thus provides a novel complement to conventional EEG measures for characterising electrophysiological alterations following TBI in a heterogenous clinical sample with limited clinical metadata.

Mindfulness meditation has been linked to differences in attention and executive function, which may be related to differences in neural activity patterns. To explore this, we used an electroencephalography (EEG)-based event-related potential (ERP) paradigm to examine brain responses associated with conflict monitoring and attention in experienced meditators, compared to non-meditators. We measured N2 and P3 ERPs associated with conflict monitoring and attention processes from 35 meditators and 29 non-meditators across both an easy and a hard Go/Nogo task (50 η_p^2 = 0.11). The fronto-midline N2 ERP was also larger following Nogo trials than Go trials in the harder task condition and was associated with correct responses. Meditators also exhibited a more frontally distributed P3 ERP in the easy task compared to the hard task, while non-meditators showed a more frontally distributed P3 ERP in the hard task (pFDR = 0.015, η_p^2 = 0.08). Meditation experience was associated with distinct topographical patterns of neural activity, without corresponding differences in global amplitudes. Exploratory analyses of relationships between task parameters, behavioural performance, and the neural activities of interest indicated these meditation-related effects appear to be more closely associated with attentional processes than with processes specific to conflict monitoring or stimulus expectancy, although we acknowledge that the ERP components examined reflect multiple overlapping cognitive processes. This study was not preregistered.

Social cognition, particularly theory of mind (ToM) is important for understanding and engaging with the social environment. The continual development and improvement of these skills can be of broad benefit. However, current social cognitive training methods are time intensive and have limited ecological validity. Virtual reality (VR) combined with transcranial alternating current stimulation (tACS) may provide a more ecologically valid and efficient alternative. The current study investigated the effects of theta tACS to the right temporoparietal junction (rTPJ) on VR social cognition training in a group of 21 healthy adults. Outcome measures were behavioural (attribution of intentions ToM task) and neurophysiological (spectral power and event related potentials). Participants completed two identical lab sessions each. One session included VR training concurrent with active theta tACS and the other, with sham theta tACS. Participants completed resting state electroencephalography (EEG) and ToM tasks with concurrent EEG pre and post VR-tACS in each session. tACS condition was randomised and all assessments were double-blinded. VR and active tACS, but not VR and sham tACS, improved ToM task accuracy. ToM task response times improved pre versus post VR-tACS regardless of tACS condition (active vs sham). Resting state theta power increased significantly across the cortex post VR-tACS regardless of tACS condition. This study provides the first evidence for the feasibility of a combined VR-tACS protocol for social cognition. Future research in larger samples, and with multiple sessions, in both healthy and clinical populations are recommended. ### Competing Interest Statement KEH was a past founder of Resonance Therapeutics. PBF has received reimbursement for educational activities from Otsuka Australia Pharmaceutical Pty Ltd and equipment for research from Brainsway Ltd. ### Clinical Trial ACTRN12621001649808 ### Funding Statement KG was supported by a Monash University Departmental Scholarship, an Australian Government Research Training Program (RTP) Scholarship and an Epworth HealthCare Capacity Building Grant. KEH was supported by a National Health and Medical Research Council (NHMRC) fellowship (1135558). PBF is supported by an MHMRC Leadership Award. ATH was supported by and Alfred Deakin Postdoctoral Research Fellowship. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Monash Health Human Research Ethics Committee gave ethical approval for this work. Monash University Human Research Ethics Committee, Alfred Health and Epworth HealthCare provided governance approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Mindfulness-based interventions (MBIs) show promise in managing chronic pain but often require substantial time commitments, leading to high attrition and concerns about acceptability. This meta-analysis evaluated attrition rates in MBIs for chronic pain and examined moderators contributing to participant withdrawal. Following PRISMA guidelines, we searched relevant databases for studies of MBIs for pain. Eligible studies included randomised controlled trials, controlled trials, and quasi-experimental designs that reported attrition data for adults (≥18 y) with chronic pain lasting over 3 months. Data extraction covered attrition metrics, program characteristics, and participant demographics. Statistical analyses included random-effects meta-analyses of proportions, sensitivity analyses, meta-regression, and publication bias assessments. Forty-four studies (45 intervention conditions) were included. The pooled attrition rate was 30.1% (95% CI: 24.5% to 37.3%) with substantial heterogeneity (I²=89.0%). Attrition increased with stricter completion thresholds (minimum sessions required for programme completion status) (P<0.001, R²=28.1%): 18.0% (≥3–4 sessions), 31.6% (≥5–6 sessions), and 49.7% (>6 sessions). Online delivery showed higher attrition (51.0%) than in-person delivery (25.6%, P=0.002, R²=17.1%). Individually delivered MBIs were also associated with higher attrition than group formats (β=0.216, P=0.039, R²=5.5%). Publication bias analyses suggested minor influence on the pooled effect, which remained robust after adjustment. Attrition rates for MBIs in chronic pain vary widely. Higher attrition is associated with stricter completion criteria, online delivery, and individual formats. These findings highlight the need to optimise MBI programme structure for management of pain.

OBJECTIVE:Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression, but not for all patients. Accurate treatment response prediction could lower treatment burden. Research suggests machine learning trained with electroencephalography (EEG) data may predict response, but a limited range of features have been tested. We tested whether a combination of > 7000 time-series features were predictive of response in training and test and independent datasets. METHODS:Pre-treatment EEG from 188 patients with depression treated with rTMS were decomposed into five principal components (PCs). The highly comparative time-series analysis toolbox was used to extract 7304 time-series features from each participant and PC. A classification algorithm was trained to predict responders from these features separately for each PC. The classifier was applied to an independent dataset (N = 58) to test generalizability. RESULTS:Within the training and test dataset, the third PC showed above-chance classification accuracy (69.4 %, pFDR = 0.005). The model generalized to the independent dataset with above-chance accuracy (60 %, p = 0.046). Analysis of feature-clusters suggested responders showed more high frequency relative power relative, and a more negative skew in the distribution of time-series values. CONCLUSIONS:Results suggest our methods could be used to inform treatment selection. SIGNIFICANCE:Our methods may enable better outcomes than 'one-size-fits-all' treatment approaches.

OBJECTIVE:Electroencephalography (EEG) data are contaminated by a range of non-neural artifacts. The confounding influence of artifacts is often addressed by using independent component analysis (ICA) to decompose data into components, subtracting artifactual components, then reconstructing data into the electrode space. Due to imperfect component separation, this common approach can remove neural signals as well as artifacts. Here, we demonstrate the counterintuitive finding that this can artificially inflate event-related potential and connectivity effect sizes and bias source localisation estimates, while also removing neural signals. METHODS:We developed a novel method that targets cleaning to artifact periods of eye movement components and artifact frequencies of muscle components, and tested our method across different EEG systems and cognitive tasks. RESULTS:Our targeted artifact reduction method was effective in cleaning artifacts while also reducing the artificial inflation of effect sizes and minimizing source localisation biases. CONCLUSIONS:EEG pre-processing of Go/No-go and N400 task data is better when targeted cleaning is applied, which better preserves neural signals and mitigates effect size inflation and source localisation biases that result from subtracting artifact components. SIGNIFICANCE:These improvements enhance the reliability and validity of EEG analyses. Our method is provided in the RELAX pipeline, which is freely available as an EEGLAB plugin (https://github.com/NeilwBailey/RELAX).

Mindfulness meditation involves training attention, commonly toward sensory experiences, with nonjudgmental awareness. Theoretical perspectives propose that meditation increases the precision of sensory processing and reduces the generation/elaboration of top-down expectations. Research suggests forward traveling cortical alpha waves may reflect bottom-up inhibition to enhance signal-to-noise ratios of sensory processing, while backward traveling alpha waves may reflect top-down inhibition based on expectations. We used electroencephalography to test whether the strength of forward and backward traveling cortical alpha waves differed between meditators and a matched sample of nonmeditators during eyes-closed resting (N = 97) and during a visual cognitive (Go/No-go) task (N = 126). Our results showed meditators produced stronger forward traveling waves compared to nonmeditators while resting with their eyes closed and during task performance. Meditators also exhibited weaker backward traveling waves while resting with their eyes closed. These results may indicate a neural mechanism underpinning enhanced attention associated with meditation, as well as a potential neural marker of reductions in mind-wandering, suggested to be associated with meditation. The results also support models of brain function that suggest attention modification is achievable through mental training to increase sensory awareness, which might be indexed by the greater strength of forward traveling cortical waves.

Accelerated intermittent and continuous theta burst stimulation (a-iTBS and a-cTBS) show strong efficacy for treatment-resistant depression (TRD), yet their neural mechanisms remain unclear. This study uses concurrent transcranial magnetic stimulation (TMS) and electroencephalography (TMS-EEG) to examine these mechanisms in 40 TRD patients and 40 healthy controls (HCs). TRD individuals demonstrate abnormal local cortical excitability at baseline, characterized by left hypoactivity and right disinhibition. A-iTBS increases left excitability, and a-cTBS increases right inhibition, and both normalize it to the level of HCs. Network analyses reveal that a-iTBS improves current propagation to the left inferior parietal lobule (IPL), correlating with a better antidepressant effect. Contrastingly, a-cTBS induces a widespread inhibition as indicated by current propagation over parietal cortices, with the left IPL being most prominent, and this also correlates with a better antidepressant effect. These findings outline the frontoparietal circuitry in TMS antidepressant effects and provide insights for optimizing treatment efficacy. This study was registered at the Chinese Clinical Trial Registry (ChiCTR2200055320).

Social cognition is significantly impacted in people with schizophrenia and can be assessed using various methods including traditional (paper-and-pencil) tasks, computer tasks, and Virtual Reality (VR) assessments. The current study investigated whether these different approaches to social cognitive assessment, with a particular focus on theory of mind (ToM), could consistently and sensitively identify differences between individuals with schizophrenia and controls within the same sample. We hypothesised that participants with schizophrenia would perform less well than controls across all assessment methods. We additionally measured brain changes associated with social cognition during the ToM computer task using electroencephalography (EEG). Our results revealed that the schizophrenia group performed less well than the control group in ToM across all assessment approaches. They also performed less well on traditional measures of social knowledge and on VR measures of emotion recognition. Additionally, event-related potential (ERP) amplitudes were reduced in people with schizophrenia compared to controls across brain regions linked to ToM. Our findings suggest that these different modes of social cognitive assessment are all sensitive to detecting differences in ToM abilities, with VR in particular showing strongest effect sizes. Implications of the findings on future protocol development are discussed. ### Competing Interest Statement KEH was a past founder of Resonance Therapeutics. PBF has received reimbursement for educational activities from Otsuka Australia Pharmaceutical Pty Ltd and equipment for research from Brainsway Ltd. ### Clinical Trial ACTRN12621001649808 ### Funding Statement KG was supported by a Monash University Departmental Scholarship, an Australian Government Research Training Program (RTP) Scholarship and an Epworth HealthCare Capacity Building Grant. KEH was supported by a National Health and Medical Research Council (NHMRC) fellowship (1135558). PBF is supported by an MHMRC Leadership Award. ATH was supported by and Alfred Deakin Postdoctoral Research Fellowship. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Monash Health Human Research Ethics Committee gave ethical approval for this work. Monash University Human Research Ethics Committee, Alfred Health and Epworth HealthCare provided governance approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors.

Objectives: Mindfulness meditation has been linked to enhanced attention and executive function, likely resulting from practice-related effects on neural activity patterns. In this study, we used an event-related potential (ERP) paradigm to examine brain responses related to conflict monitoring and attention in experienced mindfulness meditators to better understand key factors driving meditation-related effects. Methods: We measured electroencephalography-derived N2 and P3 ERPs reflecting conflict monitoring and attention processes from 35 meditators and 29 non-meditators across both an easy and a hard Go/Nogo task (50% Nogo and 25% Nogo stimuli, respectively). Results: Meditators displayed distinct neural activity patterns compared to non-meditators, with enhanced N2 responses in fronto-midline electrodes following hard Nogo trials (pFDR = 0.011, np2 = 0.111). The fronto-midline N2 ERP was also larger following Nogo trials than Go trials, in the harder task condition, and was related to correct responses. Meditators also exhibited a more frontally distributed P3 ERP in the easy task compared to the hard task, while non-meditators showed a more frontally distributed P3 ERP in the hard task (pFDR = 0.015, np2 = 0.079). Conclusions: Mindfulness meditation was associated with distinct topographical patterns of neural activity in the attention task, without corresponding increases in global neural activity amplitudes. These meditation-related effects appear to be driven by attention-specific mechanisms, despite the examined neural activity being associated with conflict monitoring and stimulus expectancy. Our findings suggest that the cognitive benefits of meditation may only emerge in tasks that actively engage targeted cognitive processes, such as sustained attention. ### Competing Interest Statement In the last 3 years PBF has received equipment for research from Neurosoft, Nexstim and Brainsway Ltd. He has served on scientific advisory boards for Magstim and LivaNova and received speaker fees from Otsuka. He has also acted as a founder and board member for TMS Clinics Australia and Resonance Therapeutics. PBF is supported by a National Health and Medical Research Council of Australia Investigator grant (1193596). The other authors declare that they have no conflicts of interest.

Introduction: Psilocybin, a classical psychedelic, has been rescheduled for use in psilocybin-assisted psychotherapy for treatment-resistant depression in Australia. While evidence for its use is promising, understanding the associated risks is crucial. Accordingly, this review aims to collate adverse event data from psilocybin-assisted psychotherapy clinical trials and evaluate its definition, way of measurement and reporting. Methods: A systematic method was employed to identify clinical trials related to the use of psilocybin-assisted psychotherapy in clinical populations that reported on adverse events. The quality assessment focused on relevant criteria related to adverse event definition, monitoring and reporting methods. Results: A total of 24 articles were included. The studies reported heterogeneous psilocybin doses, study designs and indications. Physical and psychological adverse events during and after psilocybin sessions were examined, revealing variations in measuring, reporting methods and occurrences. The most common adverse events during and after sessions included elevated blood pressure, headaches, nausea, vomiting, fatigue and anxiety. In addition, both suicidal ideation and behaviour were observed infrequently and mainly in participants with a history of suicidal ideation or suicide attempt(s). Conclusion: The review highlights the need to standardise the defintion of an adverse event, including how they are measured and reported, in psychedelic clinical trials to ensure consistent reporting across studies. In addition, screening participants for suicidality history and ongoing monitoring remains important, given the potential risk identified in the literature. However, based on the available data, the safety of psilocybin-assisted psychotherapy is generally supported, and no deaths were attributed to psilocybin. Nevertheless, cautious optimism is needed due to the preliminary nature and heterogeneity of the safety data.

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators' brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.

Opioidergic mechanisms of repetitive transcranial magnetic stimulation (rTMS) analgesia are shaped by rTMS dose and different endogenous opioids: a randomised controlled trial. Repetitive transcranial magnetic stimulation (rTMS) is a promising technology to reduce chronic pain. Investigating the mechanisms of rTMS analgesia holds the potential to improve treatment efficacy. Using a double-blind and placebo-controlled design at both stimulation and pharmacologic ends, this study investigated the opioidergic mechanisms of rTMS analgesia by abolishing and recovering analgesia in 2 separate stages across brain regions and TMS doses. A group of 45 healthy participants were equally randomized to the primary motor cortex (M1), the dorsolateral prefrontal cortex (DLPFC), and the Sham group. In each session, participants received an intravenous infusion of naloxone or saline before the first rTMS session. Participants then received a second dose of rTMS session after the drugs were metabolized at 90 minutes. M1-rTMS-induced analgesia was abolished by naloxone compared with saline and was recovered by the second rTMS run when naloxone was metabolized. In the DLPFC, double but not the first TMS session induced significant pain reduction in the saline condition, resulting in less pain compared with the naloxone condition. In addition, TMS over the M1 or DLPFC selectively increased plasma concentrations of beta-endorphin or encephalin, respectively. Overall, we present causal evidence that opioidergic mechanisms are involved in both M1-induced and DLPFC-rTMS-induced analgesia; however, these are shaped by rTMS dosage and the release of different endogenous opioids.

Regulation of the heart by the brain is a vital function of the autonomic nervous system (ANS), and healthy ANS function has been linked to a wide range of well-being measures. Although there is evidence of mindfulness-meditation-related changes to brain functioning and heart functioning independently, few studies have examined the interaction between brain and heart functions in experienced meditators. This study compared measures of the brain–heart relationship between 37 experienced meditators and 35 non-meditators (healthy controls) using three different analysis methods: (1) the heartbeat evoked potential (HEP; thought to reflect neural sensitivity to interoceptive feedback); (2) the relationship between fronto-midline theta neural oscillations (fm-theta) and the root mean square of successive differences (RMSSD) in electrocardiogram activity (an estimate of vagally mediated heart rate variability); and (3) the correlation between heart rate wavelet entropy and electroencephalographic wavelet entropy—a measure of signal complexity. The HEP analysis indicated that meditators showed a more central-posterior distribution of neural activity time-locked to the heartbeat (p < 0.001, partial η2 = 0.06) than controls. A significant positive relationship was also found between fm-theta and RMSSD in meditators (F(2,34) = 4.18, p = 0.02, R2 = 0.20) but not controls. No significant relationship was found between EEG entropy and ECG entropy in either group. The altered distribution of evoked neural activity, and the correlation between brain and heart biomarkers of vagal activity suggests greater neural regulation and perhaps greater sensitivity to interoceptive signals in experienced meditators.

Biopsychosocial factors are associated with pain, but they can be difficult to compare. One way of comparing them is to use standardized mean differences. Previously, these effects sizes have been termed as small, medium, or large, if they are bigger than or equal to, respectively, .2, .5, or .8. These cut-offs are arbitrary and recent evidence showed that they need to be reconsidered. We argue it is necessary to determine cut-offs for each biopsychosocial factor. To achieve this, we propose 3 potential approaches: 1) examining, for each factor, how the effect size differs depending upon disease severity; 2) using an existing minimum clinically important difference to anchor the large effect size; and 3) define cut-offs by comparing data from people with and without pain. This is important for pain research, as exploring these methodologies has potential to improve comparability of biopsychosocial factors and lead to more directed treatments. We note assumptions and limitations of these methods that should also be considered. Perspective Standardized mean differences can estimate effect sizes between groups and could theoretically allow for comparison of biopsychosocial factors. However, common thresholds to define effect sizes are arbitrary and likely differ based on outcome. We propose methods that could overcome this and be used to derive biopsychosocial outcome-specific effect sizes.

Background Our previous study synthesized the analgesic effects of repetitive Transcranial Magnetic Stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) trials up to 2019. There has been a significant increase in pain trials in the past few years, along with methodological variabilities such as sample size, stimulation intensity, and rTMS paradigms. Objectives/Methods: This study therefore updated the effects of DLPFC-rTMS on chronic pain and quantified the impact of methodological differences across studies. Results A total of 36 studies were included. Among them, 26 studies were clinical trials (update = 9, 307/711 patients), and 10 (update = 1, 34/249 participants) were provoked pain studies. The updated meta-analysis does not support an effect on neuropathic pain after including the additional trials (pshort-term = 0.20, pmid-term = 0.50). However, there is medium-to-large analgesic effect in migraine trials extending up to six weeks follow-up (SMDmid-term = −0.80, SMDlong-term = −0.51), that was not previously reported. Methodological differences wthine the studies were considered. DLPFC-rTMS also induces potential improvement in the emotional aspects of pain (SMDshort-term = −0.28). Conclusions The updated systematic meta-analysis continues to support analgesic effects for chronic pain overall. However, the updated results no longer support DLPFC-rTMS for pain relief in neuropathic pain, and do supports DLPFC-rTMS in the management of migraine. There is also evidence for DLPFC-rTMS to improve emotional aspects of pain.