Brain Stimulation

Background: Low-intensity focused ultrasound (LIFU) is an emerging noninvasive neuromodulation technique capable of targeting deep cortical and subcortical structures with high spatial precision. In healthy human volunteers, LIFU has demonstrated a favorable safety and tolerability profile across multiple studies. However, its safety and tolerability in clinical populations remains poorly characterized, representing a critical barrier to clinical translation. Here, we prospectively evaluate the safety and tolerability of LIFU targeting the left dorsal anterior insula (dAI) in patients with fibromyalgia (FM). Methods: In a single-blind, sham-controlled, within-subjects crossover design, 13 individuals with FM (43.1 +/- 13.2 years; 12 female) received 10 minutes of active LIFU (500 kHz, 1 kHz PRF, 36% duty cycle, 4.2 W/cm2 Isppa; 100 x 1-second pulse trains with a 5-second inter-train interval) targeting the left dorsal anterior insula (dAI) or sham on separate visits. Safety was evaluated through neuroradiological review of post vs. pre LIFU FLAIR MRI, quantitative voxel-wise FLAIR analysis, and patient report of symptoms (ROS). Tolerability was assessed using an experience assessment. Efficacy of the LIFU intervention was assessed using quantitative sensory testing (QST) including temporal summation of pain (TSP) and conditioned pain modulation (CPM). Results: Neuroradiological review identified no new evidence of edema, microhemorrhage, acute ischemia, or white matter injury on post-LIFU structural imaging. Quantitative FLAIR analysis using contralateral-mirror-referenced relative FLAIR (rFLAIR) showed no significant within-subject change in the stimulated beam volume (delta rFLAIR = 0.002 +/- 0.025, t(12) = 0.30, P = 0.769, Cohen's dz = 0.08). No serious adverse events were documented and ROS indicated no change due to LIFU sonication. Participants rated the procedure as comfortable and could not distinguish active from sham LIFU. LIFU did not result in statistically significant changes for TSP (p = 0.797) or CPM (p = 0.465). Conclusions: Ten minutes of LIFU targeting the left dAI was safe and well tolerated in individuals with FM, with no neuroradiological or quantitative MRI evidence of tissue effects and no serious adverse events. Blinding was preserved, and participants rated the procedure as comfortable. Although no significant changes were observed in experimental pain measures, these findings support the feasibility of targeting deep salience and pain amplification circuitry with LIFU in patients with FM and provide a foundation for adequately powered efficacy trials.

Background: Post-stroke apathy (PSA) is a common, disabling syndrome with few evidence-based treatment options. We evaluated the safety, feasibility, acceptability, and evidence of effects of a three-day accelerated intermittent theta burst stimulation-repetitive transcranial magnetic stimulation (iTBS-rTMS) protocol targeting the left dorsomedial prefrontal cortex (dmPFC) in chronic stroke survivors with apathy. Methods: Stroke survivors with symptomatic apathy received open-label iTBS-rTMS at the left dmPFC (21,600 pulses across 36 sessions; 3 treatment days; 12 sessions/day within one week). Safety endpoints included adverse events, neuroradiological findings, and objective cognitive performance. Secondary outcomes included measures of apathy and other neuropsychiatric symptoms as well as psychosocial functioning, including quality of life and caregiver burden. Participants were followed up for one month. Results: Fourteen participants (mean age = 61.8 {+/-} 14.0 years; mean time since stroke = 55.6 {+/-} 31.6 months) completed the iTBS-rTMS treatment course. No serious adverse events occurred. Participants rated the treatment as highly acceptable, and cognitive performance was stable from pre- to post-rTMS with no treatment-related changes on structural MRI. Regarding apathy, participants had significant improvements with moderate to large effect sizes on the Lille Apathy Rating Scale (LARS), on both self (d = 0.78) and caregiver-rated versions (d = 1.28), p<0.05 pretreatment-to-one-month follow-up. In addition, secondary measures of psychosocial function also showed improvement with moderate to large effect sizes (Stroke Specific Quality of Life Scale: d = 0.62; Zarit Burden Interview: d = 0.72), and the Brief Inventory of Psychosocial Function: d = 0.89). Conclusions: In chronic stroke survivors with PSA, accelerated iTBS-rTMS targeting the left dmPFC appears to be safe, feasible, tolerable, and highly acceptable, with preliminary evidence suggesting a potential role in reducing apathy and secondarily promoting improvements in quality of life, caregiver burden, and broader psychosocial function.

Normal emotional experience depends on dynamic modulation of neural excitability across limbic and prefrontal circuits, yet the spectral markers that reflect these shifts in humans remain incompletely understood. In this study, we combined a validated video-based emotion induction paradigm with stereotactic electroencephalography (SEEG) in 31 patients with drug-resistant epilepsy to investigate how positive and negative affective states modulate oscillatory and aperiodic (asynchronous) neural activity. Using spectral parameterization to dissociate oscillatory power from the aperiodic 1/f component, we found that emotional valence robustly altered the aperiodic slope in a regionally specific manner: negative valence flattened the slope in thalamus, posterior insula, and posterior cingulate cortex, whereas positive valence produced flattening in dorsolateral prefrontal cortex. Simultaneous oscillatory changes included increased high-frequency activity and decreased alpha/beta power during negative affect, and reduced alpha power during positive affect, which were elucidated after adjusting for broadband aperiodic spectral shifts. These effects persisted after controlling for audiovisual stimulus or physiological features and were not evident in simultaneously recorded scalp EEG, underscoring their localization to intracranial sites. Together, these results provide the first direct evidence that active induction of emotional states modulates the aperiodic slope of human intracranial field potentials, reflecting valence-dependent shifts in local circuit excitability. The findings highlight the 1/f slope as a sensitive neural marker of affective brain states and for mood dysregulation.

Background: Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising treatment across addictive disorders including Cannabis Use Disorder (CUD). Stimulation of two rTMS-targets, the ventromedial prefrontal cortex (vmPFC) and the left dorsolateral prefrontal cortex (LDLPFC), limbic and executive control network hubs respectively, may yield differential effects. In this pilot trial, we explored the differential effects of 36-sessions of rTMS applied to either the vmPFC or LDLPFC. Methods: Treatment-seeking participants with moderate or severe CUD (n=20, 10F, age=33.3+9.8SD) were randomized to 36-sessions of open-label rTMS (two sessions-per-visit, two or three visits-per-week) to either the LDLPFC (3000-pulses; 10Hz) or vmPFC (900-pulses; 1Hz) using personalized functional Magnetic Resonance Imaging (fMRI) targets along with three-sessions of Motivational Enhancement Therapy. At baseline and following rTMS, the Time-Line Follow-Back was used to measure Days-per-week of cannabis use and the fMRI Regulation of Craving (ROC) task was used to measure network activation to cues associated with long-term negative ('Later') and short-term positive ('Now') consequences of cannabis use. Results: Eighty percent of participants completed study-rTMS. There was a significant decrease in days-per-week of cannabis use in both groups (vmPFC: d=7.9; DLPFC, d=3.1) between the four-weeks of baseline and seven-weeks of follow-up. LDPFC-rTMS reduced fMRI BOLD signal magnitude and increased LDLPFC functional connectivity in response to cues, while vmPFC-TMS reduced functional connectivity. Conclusions: Treatment-seeking participants with CUD reduced the number of days-per-week they used cannabis when receiving rTMS applied to either the LDPFC or vmPFC, while fMRI effects differed by treatment target. Future larger sham-controlled trials are needed for efficacy and biomarker determination.

Background: Repetitive Transcranial Magnetic Stimulation (rTMS) is a promising treatment across addictive disorders including Cannabis Use Disorder (CUD). Targeting incentive-salience circuitry via the ventromedial prefrontal cortex (vmPFC) and central-executive circuitry via the left dorsolateral prefrontal cortex (LDLPFC) are both promising treatment approaches; however, to date structural targets have predominated whereas functional targeting may allow for more precision. In this pilot trial we adapted a functional Magnetic Resonance Imaging (fMRI) Regulation of Craving (ROC) task to generate fMRI-based rTMS targets in the vmPFC and LDLPFC. Methods: We recruited treatment-seeking participants with moderate or severe CUD as a part of an open-label trial and administered an adapted ROC-task during fMRI following 24-hours of cannabis abstinence. We identified sub-portions of maximal activation of the LDLPFC when participants thought of long-term consequences of cannabis use (Later) and of the vmPFC when participants thought of short-term positive aspects of cannabis use (Now). We hypothesized that our task would generate acceptable rTMS targets in >66% of baseline fMRI scans. Results: A total of 20-participants enrolled in the trial (50%F, age=33.3+9.8) and completed the baseline fMRI. The adapted ROC-task elicited group level activation in the LDLPFC and precuneus in the Later>Now and in the bilateral vmPFC, ACC, and striatum in the Now>Later contrast. Acceptable functional targets resolved in both the vmPFC and LDLPFC in 19 of 20 participants (one participant did not tolerate MRI). Conclusions: The adapted ROC-task elicits activation in incentive salience and central executive circuitry and can feasibly generate rTMS targets when using a cluster selection algorithm.

Adapting ongoing gait patterns to environmental challenges is essential for safe navigation through the environment. Impairment of gait adaptation is common in many neurodegenerative disorders, such as Parkinson's disease (PD), where it hampers mobility and limits quality of life. The neural control of gait adaptation remains largely unclear, thereby limiting the development of targeted treatments, such as deep brain stimulation of the subthalamic nucleus (STN-DBS). We integrated clinical, kinematic, brain metabolic imaging, and electrophysiological data, obtained during a fully immersive virtual reality overground walking task, to characterize the neural underpinnings of gait adaptation performance during dynamic obstacle avoidance and its improvement with STN-DBS. Movement kinematics, brain oscillatory activity, and metabolic activation were simultaneously acquired in 12 patients with PD during rest and gait adaptation, under active or paused STN-DBS, using inertial measurement units, electroencephalography, and three separate [18F]fluorodeoxyglucose positron emission tomography scans. Eight age-matched healthy subjects completed the same task for comparative kinematic analyses. All patients showed significant clinical improvement with STN-DBS. During the gait adaptation task with paused stimulation, patients exhibited increased metabolic activity in the cerebellum and sensorimotor cortex. Active STN-DBS selectively enhanced thalamic and superior frontal gyrus (SFG) metabolism, while concomitantly reducing cerebellar uptake. Right-lateralized SFG metabolism correlated with gait adaptation performance, with DBS-driven shifts toward greater right SFG activity predicting the magnitude of gait adaptation improvement. This correlation was independent of baseline asymmetry in clinical impairment, electrode placement, or structural connectivity to the SFG. Of note, STN-DBS amplitude asymmetry emerged as an independent predictor of right-lateralization of SFG metabolism. EEG recordings confirmed this lateralized network modulation, with theta-band asymmetry paralleling PET findings. Our findings identify a lateralized thalamo-cortical network supporting gait adaptation in PD and highlight a distinctive role for the SFG. We further show that effective STN-DBS acts as a lateralized regulator, dynamically rebalancing cortico-thalamic circuits to support context-appropriate gait control. The observed right-hemispheric lateralization may foster novel image-guided programming strategies to enhance the consistency and effectiveness of gait control in PD.

Background: Obsessive-compulsive disorder (OCD) is characterized by disturbing thoughts (obsessions) that initiate anxiety-reducing thoughts or behaviors (compulsions). For patients with treatment-resistant OCD (tr-OCD), neuromodulation techniques, like capsulotomy (a lesion in the anterior limb of the internal capsule) and deep brain stimulation (DBS), have emerged as interventions that likely regulate connectivity between the prefrontal cortex (PFC) and subcortical targets. Three patients (Cap-DBS1-3) underwent a failed capsulotomy followed by successful DBS. Here, we aimed to understand the brain connections disrupted by failed capsulotomy vs modulated by successful DBS. Methods: We used diffusion-weighted magnetic resonance imaging (dMRI) tractography in a control cohort with tr-OCD (n=12) and in two of the Cap-DBS patients themselves to determine connectivity profiles of the capsulotomy, volume of tissue activated (VTA), and potentially necessary tracts (VTA minus capsulotomy tracts). We used whole-brain, PFC-focused, and subcortically-focused tractography algorithms to fully explore the space of possible connections. Results: Capsulotomy regions-of-interest (ROIs) connected with a variety of PFC and subcortical regions. VTA ROIs and potentially necessary tracts had limited and inconsistent PFC connectivity but substantial subcortical connectivity. While correlated to the average OCD connectome (r = 0.214, 95% CI [0.177, 0.251]; r = 0.756, 95% CI [0.739, 0.772]), the Cap-DBS connectomes had many edges that were stronger (z-score > 3). Conclusions: The connectivity profile of potentially necessary tracts for successful DBS treatment after failed capsulotomy revealed a surprising proportion of subcortical regions and inconsistent PFC involvement, highlighting an often-ignored set of connections that may be critical to effective DBS.

Introduction: Reduced or lost sensation and movement after a spinal cord injury (SCI) impairs the brain s ability to accurately localize paralyzed body parts, causing deficits in its internal body map, or mental body representations (MBR). These deficits hinder functional recovery and contribute to neuropathic pain. Medications for neuropathic pain are often ineffective and carry side effects. Our pilot trials found that in-person Cognitive Multisensory Rehabilitation (CMR), a physical therapy restoring MBR, led to prolonged pain reduction, improved sensorimotor function, and enhanced brain function, to greater extent than adaptive fitness. To explore more accessible interventions for those in rural areas or with transportation challenges, we examined whether 12 weeks of remotely delivered CMR or exercise would (1) improve function and reduce pain; (2) increase brain activity and connectivity related to sensorimotor function and MBR in adults with SCI. Methods: Of 19 adults with SCI who consented, 15 (51+/-15 years old, 8+/-10 years post-SCI) were randomized to 12 weeks of remotely delivered CMR or exercise (45min, 3x/week). Eight reported neuropathic pain equal or greater than 3/10. The Numeric Pain Rating Scale (NPRS), ASIA Impairment Scale (AIS), and Neuromuscular Recovery Scale (NRS) assessed pain and sensorimotor function at baseline, post-intervention, and 6-month follow-up. Functional MRI included resting-state and four tasks: imagining feeling the left leg, imagining moving the left leg, whole-body movement imagery, and a sensation task. Results: After CMR (n=8), participants improved on AIS (large effect sizes: touch: d=1.30; pinprick: d=1.21; lower limb motor function: d=1.83). Exercise (n=7) produced smaller improvements (touch: d=0.35; pinprick: d=0.36; lower limb motor function: d=0.80). CMR showed greater NRS effect sizes (core: d=1.48; upper limb: d=0.69; lower limb: d=1.25) than exercise (core: d=0.31; upper limb: d=0.74; lower limb: d=0.83). Benefits persisted at follow-up for both AIS and NRS, especially in the CMR group. Highest neuropathic pain intensity decreased in both groups post-intervention (CMR: d=-0.61; exercise: d=-0.73) and at 6-month follow-up (CMR: d=-0.55; exercise: d=-0.55). Unlike previous studies, group effects for CMR were not found due to high heterogeneity. Increased task-based activation, including in the lateral occipital cortex involved in visual body perception and spatial awareness, was seen for the exercise group (n=5). Discussion: These preliminary results support the potential of remotely delivered CMR and exercise to improve function and reduce neuropathic pain in adults with SCI, highlighting the need for larger trials. Clinicaltrial.gov: NCT05870189

Background: Understanding how transcranial direct current stimulation (tDCS) affects brain activity critically benefits from the use of functional magnetic resonance imaging (fMRI) to measure the related BOLD (blood-oxygenation-level-dependent) signal changes. However, the small magnetic fields induced by the stimulation currents can cause artifacts in the fMRI images that can compromise findings from concurrent tDCS-fMRI studies. Objective: To identify how the current-induced magnetic fields affect fMRI data and establish a quantitative framework for evaluating their impact on concurrent tDCS-fMRI measurements. Methods: Magnetic fields induced by currents inside the head and electrode cables were calculated for a standard motor cortex montage. Their effects on echo-planar images (EPI) were simulated based on a framework derived from MR physics first principles and validated using phantom experiments. The framework was applied to artificially induce artifacts related to the tDCS current flow in current-free fMRI time series from 5 participants. These were compared to active runs from the same participants where tDCS intensity was varied in a block design. Results: Currents in the electrode cables were the main contributors to the current flow-related artifacts in the EPI images, which occurred both locally by causing geometric distortions and remotely by affecting the dynamic update of the scanner demodulation frequency. The artificially induced fMRI activations corresponded well to those measured during real tDCS on the single-subject level for intensities of 2 mA and higher. Conclusion: The current-induced magnetic fields can cause intensity changes comparable to typical BOLD responses. Their impact on the statistical results depends on the chosen experimental design (electrode locations, cable paths, imaging parameters, fMRI paradigm). The simulation framework provides a principled approach to evaluate the impact of these artifacts during the design and data analyses of concurrent tDCS-fMRI studies.

Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) frequently co-occur in Veterans, producing overlapping symptoms and shared autonomic dysregulation. Heart rate variability (HRV) offers a noninvasive measure of autonomic function. Univariate HRV analyses often fail to capture complex, multivariate patterns associated with comorbidity. This study applied machine learning to HRV features extracted from MEG-derived electrocardiogram (M-ECG) signals to differentiate Veterans with TBI alone (TBI-alone; n = 42) from those with comorbid PTSD (TBI+PTSD; n = 40). Time-domain, frequency-domain, geometric, and nonlinear HRV metrics were analyzed using nested cross-validated Random Forest and XGBoost classifiers, with Boruta-based feature selection and SHapley Additive exPlanations for model interpretability. Both classifiers achieved above-chance discrimination (Random Forest AUC = 0.663; XGBoost AUC = 0.635). Multivariate models identified distributed autonomic signatures in TBI+PTSD, including altered sympathovagal balance, increased low-frequency proportion, and greater heart rate complexity. In contrast, univariate HRV differences were subtle and did not survive correction for multiple comparisons. These findings demonstrate how using multivariate machine learning HRV analysis could help with detecting comorbidity-specific autonomic patterns, suggesting that HRV-derived signatures may serve as exploratory biomarkers for risk assessment and targeted interventions in Veterans with TBI and PTSD.

Background: Parkinson's disease (PD) is the second most common progressive neurological disorder that is pathologically characterized by the loss of dopaminergic neurons within the substantia nigra (SN). However, disease progression probably involves coordinated changes across both neuronal and glial cell populations. Although single-nucleus RNA-seq resolved cell-type-specific transcriptional profiling, differential expression and regulatory interpretation are commonly reported separately; however, they may limit the mechanistic prioritization to uncover novel therapeutic targets. Methods: Here, we performed sample-aware pseudobulk framework analysis on single-nucleus transcriptomes obtained SN of PD and control donors. Cell-type-specific differential expression for PD vs. control was identified using edgeR quasi-likelihood modeling (FDR < 0.05; |log2FC| > 0.5). Further, to quantify disease-specific remodelling, we computed one-vs-rest cell-type specificity scores in each condition and defined delta-specificity as the PD-control shift. We further prioritized the gene-set for dopaminergic neurons and microglia based on edge R significance and delta-specificity shifts, followed by upstream regulatory assessment using transcription factor enrichment and subnetwork visualization using ChEA-KG. Moreover, we used Cellchat to identify altered cell-cell communication networks to infer differences between both conditions. Results: Dopaminergic neurons demonstrated upregulation of neuronal-state remodeling transcriptional programs related gene sets in PD group, including receptor signaling and contact/guidance pathways (e.g., CHRM3, ROBO1, PLXNA4, UNC5D, EFNA5), neuronal excitability homeostatsis, RNA components, cellular traffickings and proteostasis, suggesting coordinated remodeling in surviving neuronal population. Microglia exhibited a compact PD-associated signature enriched for regulatory and activation state-related genes. TF networks analysis revealed distinct regulatory subnetwork in each population,including BNC2-centered network in microglia and an NPAS3-centered network in dopaminergic neurons with embedded ZNF804A and chromatin-associated components. Conclusions: In summary, integrating pseudobulk, delta-specificity scoring and TF-network enrichment analysis provides coherent dopaminergic and microglial programs in PD substantia nigra. This framework prioritizes cell-type-specific potential candidate mechanisms for downstream validation. The inferred regulatory networks and interactions are hypothesis generating and need orthogonal validation, such as spatial or proteomics approaches and independent cohorts.

Background Children in low- and middle-income countries (LMICs) face an elevated risk of developmental delay, yet scalable neuroimaging tools to study early brain development in these contexts remain limited. Children who are HIV-exposed but uninfected (CHEU) represent a growing population with evidence of language and motor delays and altered brain development compared with children who are HIV-unexposed (CHU). Ultra-low-field (ULF) MRI offers a more affordable alternative to conventional high-field (HF) MRI, but its application in early childhood remains underexplored. Methods We compared brain volumes derived from ULF (64mT) and HF (3T) MRI in South African CHEU and CHU as part of the DolPHIN-2 PLUS study. Volumetric segmentation was performed using FreeSurfer v7.4.1 and SynthSeg on the Flywheel platform. Agreement between modalities was assessed using Pearsons and Lins concordance correlation coefficients across global and subcortical regions. Associations between ULF-derived brain volumes and developmental outcomes, measured by the Bayley Scales of Infant Development, Third Edition, were evaluated using partial correlations adjusted for sex and age. Results Forty-five children (9 CHEU, 36 CHU; mean age 45.6 months) had paired ULF and HF scans of usable quality. Strong correlations were observed between ULF and HF volumes for global white and grey matter regions (r > 0.92) and larger subcortical grey matter structures such as the thalamus, caudate, and putamen (r = 0.86-0.89). Moderate-to-weak correlations were evident in smaller structures (hippocampus, pallidum, amygdala). ULF underestimated most grey matter volumes, and overestimated total white matter volume relative to HF. ULF-derived global and subcortical volumes were associated with receptive and expressive communication (r = 0.34-0.59, all p < 0.05). Conclusions ULF MRI produces brain volume estimates comparable to HF MRI and captures meaningful associations with early language development. These findings support ULF MRI as a feasible and scalable tool for studying neurodevelopment in vulnerable paediatric populations in LMICs.

Objective To verify the reliability of a self developed bowel sound monitoring device under real biological tissue acoustic propagation conditions using a controllable sound source, and to establish quantitative evidence for its translational applicability. Methods Freshly euthanized six month old Bama miniature pigs were used as an experimental model. A high fidelity Bluetooth audio playback device was implanted into the abdominal cavity to deliver manually annotated bowel sound recordings as controllable acoustic stimuli. A self developed bowel sound monitoring device was fixed on the abdominal surface for continuous signal acquisition. Playback timestamps were defined as the ground truth, and event level matching was performed within a predefined temporal tolerance window. Four performance indicators were evaluated: (1) bowel sound acquisition and energy amplification, (2) event matching accuracy, (3) acoustic feature consistency, and (4) subjective agreement assessed by blinded auscultation from gastroenterologists with different levels of clinical experience. Results The monitoring device exhibited stable detection capability and effectively covered the full spectral range of the original signals. It significantly enhanced bowel sound energy while preserving temporal and spectral characteristics, demonstrating high consistency in time and frequency domain features. Blinded clinician assessments showed a subjective agreement rate of 88.9% between original and surface recorded bowel sound events. Conclusions Under real tissue acoustic propagation conditions, the self-developed bowel sound monitoring device reliably captures bowel sound events with high temporal accuracy, acoustic fidelity, and clinical perceptual consistency. This controllable sound source based validation provides robust technical evidence for subsequent in vivo studies and clinical translation, supporting the development of objective and continuous gastrointestinal function monitoring.

Although language acquisition delays are frequently observed in children with autism spectrum disorder (autism), our current understanding of the neurobiological mechanisms underlying language development in autism is sparse. Previous studies have found resting-state electroencephalography (EEG) power to be associated with language abilities in autistic children. However, longitudinal studies examining resting-state EEG phase coherence in relation to language development in preschool-aged children with autism are limited. This study aimed to characterize age- and group-related changes in whole-brain coherence in neurotypical children and in autistic children with and without language delay. Resting-state EEG and language data were collected at 2, 3, and 4 years of age. Peak phase coherence within the alpha band (6-11 Hz) was calculated at each timepoint and differences in the developmental trajectory of peak alpha coherence (PAC) were analyzed. In neurotypical children, PAC increased between 2 and 4 years of age. In contrast, PAC did not significantly change with age in children with autism. However, when examining autistic children based on language delay status, PAC increased with age in autistic children without language delay, but not in children with language delay. Exploratory analysis revealed evidence for an interaction between PAC and age, suggesting that the direction of the association between PAC and VDQ varied across age. Overall, these results support previous findings of altered oscillatory connectivity in autism and suggest that differences become apparent early in development. Importantly, phase coherence may not only differentiate diagnostic groups but also capture meaningful variability within the autism group. Future research should further investigate the use of EEG coherence as a biomarker of language development in autism.

Chronic pelvic pain (CPP) affects up to 26% of women worldwide. While its pathophysiology is poorly understood, disturbances in body perception have been identified in various similar chronic musculoskeletal disorders. The Fremantle Perineal Awareness Questionnaire (FrePAQ) is a novel tool designed to specifically assess disturbed body perception in the pelvic region, but its structural validity and reliability require formal evaluation. Methods: Patient partners with lived experience contributed to study design. Participants with (n=417 and without (n=277) chronic pelvic pain completed the FrePAQ at baseline, as well as one week later. We assessed the validity and reliability of the FrePAQ following COSMIN guidelines for Classical Test Theory. Results: The validated FrePAQ comprises a two factor model, with a six item Distress & Disconnection (D&D) subscale and a two item Size & Shape (S&S) subscale. Confirmatory analysis showed excellent fit (CFI = .988; RMSEA = .048) and measurement invariance between diagnostic groups. Internal consistency was high (cronbach alpha = .838 CPP, .819 controls). Test retest reliability was high for D&D (ICC = .863) and acceptable for S&S (ICC = .695). FrePAQ scores showed a weak to moderate correlation with pain scores (r = .234 to .255), psychological distress (r = .226 to .443), and functional impact (r = .172 to .295), particularly for the D&D subscale. Conclusion: The FrePAQ is a reliable and valid instrument to measure perineal perceptual disturbances in CPP. Future research will evaluate the tools potential to support phenotyping and guide individualised interventions. Improved understanding of body perception disturbance in CPP can enhance diagnosis and treatment precision.

Introduction Dysmenorrhoea is highly prevalent globally and interferes with engagement in education, work, social participation, and quality of life. Although evidence suggests that sociocultural beliefs influence how menstrual pain is understood and managed, relatively little research has explored dysmenorrhoea-related knowledge and beliefs within South Africa. This study aimed to (1) determine the frequency of dysmenorrhoea, (2) assess dysmenorrhoea-related knowledge and compare knowledge between menstruating and non-menstruating individuals, and (3) explore commonly held generational, cultural, and religious beliefs related to dysmenorrhoea in a South African university cohort. Methods We analysed data collected as part of a cross-sectional survey conducted among staff and students at a South African university. Participants completed demographic questions, items assessing dysmenorrhoea-related knowledge, and an adapted Working Ability, Location, Intensity, Days of Pain, Dysmenorrhoea (WaLIDD) questionnaire. Participants were also invited to provide free-text responses describing generational, cultural, and religious beliefs about dysmenorrhoea. Quantitative data were analysed descriptively and compared between menstruating and non-menstruating participants. Free-text responses were analysed using reflexive thematic analysis. Results A total of 863 participants completed the survey, including 578 current or past menstruators. The frequency (95%CI) of dysmenorrhoea was 75.4% (71.7-78.9). Most participants were classified as having moderate (53%) or severe (31%) dysmenorrhoea on the WaLIDD scale. Awareness of dysmenorrhoea was higher among participants who had menstruated than among those who had never menstruated (80.4% vs 55.3%, p<0.001). Most participants (85.1%) reported wanting more education about dysmenorrhoea and its impact. Reflexive thematic analysis of 246 free-text responses identified five themes: (1) menstrual pain is normalised, dismissed, and expected to endure, (2) reproductive meanings attached to menstrual pain, (3) moral, spiritual, and cultural interpretations of menstrual pain, (4) negotiating competing explanations for menstrual pain, and (5) managing and controlling menstrual pain symptoms. Across themes, dysmenorrhoea was interpreted through social, cultural, reproductive, spiritual, and biomedical frameworks that shaped how pain was understood, communicated, and managed. Conclusion Dysmenorrhoea is common in this South African university cohort, and is rarely understood as a purely biological symptom. Instead, menstrual pain is understood and managed through broader social, cultural, reproductive, moral, and biomedical narratives, which shape how pain is recognised, disclosed, legitimised, and treated. These findings highlight the importance of considering sociocultural beliefs alongside clinical factors when developing menstrual health education, support strategies, and healthcare services.

Amyotrophic lateral sclerosis (ALS) is increasingly recognized as a multisystem neurodegenerative disorder in which motor-neuron degeneration is accompanied by widespread alterations in cortical dynamics. Among its most reproducible neurophysiological signatures is cortical hyperexcitability, yet how this local excitability imbalance shapes distributed whole-brain activity remains poorly understood. Here, we combined source-reconstructed resting-state MEG data, tractography-informed whole-brain modeling, and simulation-based inference to investigate whether ALS-related alterations in large-scale brain dynamics can be mechanistically explained by changes in cortical excitability. First, we characterized empirical brain dynamics using complementary features spanning regional activity amplitude and variability, functional connectivity, and avalanche-based metrics. These analyses revealed significant alterations in ALS patients relative to healthy controls, as well as associations with clinical impairment and disease staging. To mechanistically interpret these changes, we employed a reduced Wong-Wang whole-brain model in which local recurrent excitation modulates emergent large-scale neural dynamics. Simulations showed that increasing excitability systematically reproduced the empirical dynamical signatures observed in ALS. We then applied a simulation-based inference framework to estimate latent excitability parameters directly from empirical observations. Whole-brain model inversion revealed increased excitability in ALS patients compared with controls. The recovered excitability parameter was associated with disease staging, supporting its clinical relevance as a model-derived descriptor of ALS progression. Finally, by extending the model to estimate frontal and non-frontal excitability separately, we found that ALS-related alterations were predominantly associated with increased frontal excitability, whereas non-frontal regions appeared comparatively less affected. The recovered parameters related to disease staging. Together, these findings provide a mechanistic framework linking altered large-scale brain dynamics in ALS to selective cortical hyperexcitability, explaining how local excitability changes can give rise to global network reorganization. More broadly, they show how computational model inversion can recover latent multiscale pathophysiological processes from empirical neural recordings, offering a non-perturbative alternative to complex experimental paradigms typically required to causally probe local-to-global mechanisms.

The objective assessment of patients with disorders of consciousness (DOC) remains a significant clinical challenge. Behavioral scales like the Coma Recovery Scale-Revised (CRS-R) are susceptible to rater subjectivity and have difficulty in detecting patients with cognitive-motor dissociation (CMD), while existing electrophysiological paradigms typically evaluate isolated processing levels, especially in visual functions. To address these limitations, we developed a novel, hierarchical visual EEG framework that evaluates three progressive tiers of visual processing--sensory input, selective attention, and object discrimination--within a single, unified paradigm. This framework uses steady-state and event-related potentials, analyzed with statistical testing and machine learning, to provide objective detection. In a cohort of 85 participants, the framework demonstrated a robust alignment with behavioral CRS-R levels and successfully identified CMD patients missed by bedside behavioral examinations. Notably, model predictions derived from this framework showed a significant correlation with 3-month clinical outcomes. This prognostic utility generalized effectively and remained consistent across distinct EEG acquisition systems in an independent validation cohort of 17 patients. In summary, this work offers electrophysiological validation for the hierarchical design of the CRS-R and provides a practical tool for bedside objective assessment of DOC.

Introduction: Acute low back pain is a leading cause of disability worldwide. Clinical guidelines recommend non-pharmacological therapies as first-line treatment and advise caution with opioid prescribing. However pharmacological therapies, including opioids and gabapentinoids, remain commonly used. The comparative risks of subsequent opioid use disorder (OUD) and overdose diagnosis associated with initial treatment modality in large, real-world populations is not well characterized. We estimated the incidence of new-onset OUD and overdose diagnosis among opioid-naive, Medicaid-insured adults with newly diagnosed acute low back pain and estimated the association between initial treatment modalities and subsequent OUD and overdose diagnosis risk. Methods: We conducted a retrospective cohort study using Medicaid T-MSIS Analytic files from 25 states (2016-2019). We identified opioid-naive adults with a new diagnosis of acute low back pain who initiated pharmacologic or non-pharmacologic treatment within 1 month of diagnosis. The primary outcome was incident OUD and overdose diagnosis (based on diagnosis codes in claims) during follow-up. Associations between initial treatment modality and OUD and overdose diagnosis risk were estimated using a non-parametric, doubly robust estimator to adjust for measured confounding. Results: The cohort included 525,002 opioid-naive adults initiating treatment for low back pain. The cumulative incidence of OUD and overdose diagnosis was 1.5% and 2.4% at 7 and 13 months, respectively. Compared to non-use, use of gabapentinoids during the first month of treatment was associated with the highest relative risk (increasing risk) by 130.1%, 95% confidence interval (CI): 117.8%, 142.3%), the second-highest relative risk was estimated for higher-dose opioids, defined as > 50 daily Morphine Milligram Equivalents (MME) (118.1%, 95% CI: 99.2%, 137.0%). Lower-dose, short-duration opioids ([&le;] 50 MME, [&le;] 7 days) were also associated with elevated risk, though substantially smaller in magnitude (20.8%, 95% CI: 13.8%, 27.9%). In contrast, non-pharmacologic, non-interventional therapies were associated with reduced OUD and overdose diagnosis risk, with physical therapy demonstrating the largest relative reduction of 34.0% (95% CI: -40.9%, -27.1%). Discussion: In opioid-naive Medicaid patients with acute low back pain, initial non-pharmacologic treatment was associated with reduced OUD and overdose diagnosis risk. Gabapentinoids and opioids were each associated with increased risk; for opioids, the degree of risk increased with higher doses and durations. These results support guideline recommendations favoring non-pharmacologic treatment as first-line therapy and indicate the importance of cautious prescribing when pharmacologic treatment is considered.

Background: Major depressive disorder (MDD) is clinically heterogeneous, hindering identification of reproducible biomarkers. Using a semi-supervised machine learning approach, HYDRA, we previously identified two neuroanatomical dimensions from structural MRI in medication-free MDD from COORDINATE-MDD consortium. These dimensions (D1, D2) showed differential responses to selective serotonin reuptake inhibitor (SSRI) antidepressants and placebo. External replication in UK Biobank linked D2, characterized by widespread subtle neuroanatomical reductions, to an immuno-metabolic profile. Here, we examined whether these dimensions are detectable early in the course of illness. Methods: We applied the pre-trained model to structural MRI data from the multisite PRONIA cohort, comprising individuals with recent-onset depression (ROD; n = 377; mean age 25.8 years, SD 6.0; 51.3% female) and healthy controls (n = 267; mean age 25.5 years, SD 6.4; 61.0% female). Participants were assigned to clusters (C1, C2) corresponding to the previously identified dimensions (D1, D2). Clusters were compared on clinical symptom profiles, peripheral inflammatory markers, and in a subset (n = 107), proteomic ageing indices. Results: Two neuroanatomical clusters were identified in PRONIA. C1 (n = 265) showed higher negative symptom severity and elevated interleukin-2 levels. C2 (n = 140) was associated with higher residual proteomic age. Overall depressive symptom severity did not differ significantly between clusters. Conclusions: Neuroanatomical dimensions of MDD are reproducible and detectable at illness onset. Associations with negative symptom severity, inflammatory signalling, and proteomic ageing suggest these dimensions capture biologically meaningful heterogeneity early in depression. These findings support a biologically informed framework for stratified treatment approaches in MDD.