Brain Research Bulletin

Objective: To evaluate the efficacy, engagement, and usability of Tune Out, an unguided, self-paced online tinnitus management program, for reducing tinnitus severity in adults with tinnitus. Design: A two-arm, parallel-group randomised controlled trial was conducted with Australian adults reporting diagnosed or self-reported tinnitus. Participants were randomised to immediate access to Tune Out or a waitlist control group. Outcomes were assessed at baseline, 6 weeks, and 12 weeks. The primary outcome was tinnitus severity measured using the Tinnitus Functional Index (TFI). Secondary outcomes included tinnitus handicap, psychological symptoms, program engagement, self-efficacy, and usability. Results: Eighty-eight participants were randomised: 43 to the intervention group and 45 to the waitlist control group. The primary outcome analysis included 63 participants at 12 weeks. A significant Group x Time interaction was observed for TFI total score, indicating greater reductions in tinnitus severity over time in the intervention group compared with waitlist control, F(2, 102.57) = 5.95, p = .004, partial 2= .104. Significant effects were also observed for tinnitus handicap, F(2, 106.76) = 4.12, p = .019, partial 2 = .072. Effects on psychological symptoms were less consistent, although anxiety showed a significant Group x Time interaction, F(2, 116.85) = 3.63, p = .030, partial 2 = .059. At 12 weeks, 23.1% of intervention participants achieved a clinically meaningful reduction in tinnitus severity compared with 5.4% of controls. Program use was highly variable, with a median use of 1.10 hours, and 25.6% of intervention participants recording no use. Usability ratings were favourable among respondents, with a mean System Usability Scale score of 73.13. Conclusions: Tune Out demonstrated preliminary efficacy for reducing tinnitus severity and tinnitus handicap compared with waitlist control. Effects on broader psychological symptoms were less consistent. Although usability was rated positively, low and variable engagement highlights the need for strategies to support uptake and sustained use in unguided digital tinnitus interventions.

Myofascial pain syndrome (MPS) is a major cause of chronic neck pain, with tissue ischemia implicated as a contributing factor. This prospective, single-arm interventional study evaluated the analgesic effect of ultrasound-guided fascia hydrorelease (US-FHR) performed around arteries supplying the neck in patients with chronic neck MPS. Thirteen adults (median age 53.0 years; 38.5% female) underwent US-FHR targeting the perivascular fascia of either the transverse cervical or dorsal scapular artery using 2 mL of normal saline. Pain intensity was assessed by visual analog scale (VAS) at rest and during movement; disability by the 5-item Pain Disability Index, Japanese version (PDI-5-J); and arterial blood flow volume before and after the procedure. The primary outcome, pain VAS during movement, decreased from 49.0 mm (interquartile range [IQR], 44.5-64.0) at baseline to 22.0 mm (IQR, 14.5-31.5) at 15 min and 22.0 mm (IQR, 14.0-34.0) at 1 week (Hodges&-Lehmann median difference, 30.5 mm [95% CI, 24.5 to 36.5] and 28.5 mm [95% CI, 18.5 to 37.0]; both P < 0.001). Pain VAS at rest improved from 21.0 mm (IQR, 13.0-43.5) to 8.0 mm at 15 min and 1 week (median difference, 14.5 mm [95% CI, 9.0 to 24.0; P = 0.001] and 13.5 mm [95% CI, 6.0 to 21.0; P = 0.007]). PDI-5-J decreased from 17.0 (IQR, 10.5-23.0) to 13.0 (IQR, 4.0-17.5) at 1 week (median difference, 5 [95% CI, 2 to 8; P = 0.004]). Blood flow volume increased from 11.2 mL/min (IQR, 4.5-14.4) to 17.2 mL/min (IQR, 6.1-23.7) immediately after US-FHR (median difference, +4.1 mL/min [95% CI, +2.5 to +8.9; P = 0.001]), although transient. One patient experienced transient bleeding that was promptly controlled. In this single-arm feasibility study, US-FHR around the target artery was simple and safe to perform and was associated with reduced neck pain. Because the study lacked a control group, these preliminary findings should be regarded as hypothesis-generating and require confirmation in controlled trials; they may also inform the future evaluation of MPS in other anatomical regions. Trial registration: UMIN Clinical Trials Registry, UMIN000053612.

Background: Chronic pain is associated with impaired muscle health, but whether these changes reflect site-specific factors, broader systemic factors, or both remains unclear. The purpose of this study is to determine whether normative markers of muscle health derived from MRI show site-specific patterns in chronic pain. Methods: UK Biobank participants who underwent whole-body MRI from 2006 to 2010 were included in this retrospective cross-sectional study. The MuscleMap Toolbox quantified volume and intramuscular fat (IMF) in 42 muscles of the abdomen, pelvis, and thigh. Normative models trained on a no pain group generated muscle-specific deviations from normal (i.e., Z-scores) for single- and multi-site chronic and acute pain. Results: Of 17,843 participants, the primary site-specific analysis included 9,704 no pain, 885 single-site chronic back pain (CBP), 438 single-site chronic hip pain (CHP), and 1,315 single-site chronic knee pain (CKP) participants (n=12,342; mean age 63.7{+/-}7.5 years; 52.7% female). Additional analyses included single-site chronic neck/shoulder pain, acute pain, and multi-site chronic pain groups. In CBP, deviations were localized to abdominal muscles, with decreased volume in 6/8 and increased IMF in 6/8. In CHP, deviations were broad, with decreased volume in 3/8 of the abdominal and 14/26 of the thigh muscles, and increased IMF in 6/8 of the abdominal, 5/8 of the pelvic, and 4/26 of the thigh muscles. In CKP, deviations were localized to thigh muscles, with decreased volume in 8/26 and increased IMF in 6/26. Acute pain groups showed no significant differences except for decreased volume in one thigh muscle in acute knee pain. With each additional chronic pain site, volume decreased ({beta}=-.078;IQR:-0.100-0.051), and IMF increased ({beta}=.085;IQR:0.066-0.101). Combined Z-scores classified chronic pain groups better than chance (accuracy: 48.6%;p<.001), but not acute pain groups (accuracy: 39.0%;p=.20). Conclusions: Whole-body MRI combined with AI-driven muscle segmentation and normative modeling revealed site-specific patterns of muscle health in single-site chronic pain.

Moderate-to-severe traumatic brain injury (msTBI) is recognized as a chronic and evolving neurological condition characterized by progressive structural brain changes and persistent cognitive impairment. While prior studies have demonstrated widespread atrophy following msTBI, less is known regarding the longitudinal trajectory of gray matter (GM) changes during recovery and post-rehabilitation. The current study used longitudinal voxel-based morphometry (VBM) to characterize GM volume changes over a period of 9 months, in individuals with msTBI relative to healthy controls (HC). Associations between regional GM volume and neuropsychological functioning were examined. Twenty-eight participants (14 msTBI, 14 HC) completed MRI and neuropsychological assessments across three timepoints spanning outpatient rehabilitation and follow-up. Longitudinal VBM analyses revealed significant group and time interactions within subcortical and limbic regions. Relative to HC, individuals with msTBI showed lower GM volume in these regions at baseline, with trajectories that converged toward HC values (right hippocampus) or increased relative to HC over the rehabilitation period (bilateral pulvinar), whereas the right amygdala and inferior cerebellar vermis remained persistently reduced. Significant longitudinal improvements in memory and psychomotor speed during the rehabilitation period were demonstrated in msTBI. Greater (preserved) GM volume within the right hippocampus, thalamus, and bilateral pulvinar was associated with better performance across measures of verbal memory, processing speed, executive functioning, and cognitive flexibility. These findings suggest that msTBI is associated with dynamic structural brain changes involving subcortical, limbic, and cerebellar networks, and that the rehabilitation period was accompanied by relative volumetric stabilization in these regions and by meaningful cognitive improvement.

In recent decades, the psychedelic psilocybin has been studied as a potential treatment for major depressive disorder (MDD), offering an alternative to traditional antidepressants. However, the brain changes underlying the clinical effects of different interventions remain unclear. Here, we investigated the effects of psilocybin and a conventional antidepressant, escitalopram, from the double-blind randomised controlled trial (DB-RCT) -NCT03429075- on the brains hierarchical organisation. Using pre- and post-treatment resting-state functional magnetic resonance imaging (fMRI) we built whole-brain models and obtained a generative effective connectivity (GEC) matrix for each patient. Based on the GEC, we measured the level of non-equilibrium brain dynamics by quantifying the deviation from the fluctuation-dissipation theorem (FDT) and performed complementary analysis on brain segregation and asymmetry. Our results showed opposite reconfigurations of the hierarchical non-equilibrium brain dynamics following each treatment. Additionally, baseline measures effectively distinguished responders from non-responders within each treatment. These findings suggest that the deviation of the FDT may serve as a marker for differentiating the effects of psilocybin and escitalopram in MDD treatment, overall, contributing to the understanding of therapeutic mechanisms of depression.

Abstract Background: Non-specific chronic low back pain (NSCLBP) is associated with persistent pain, reduced health-related quality of life (HRQoL), and low-grade systemic inflammation. This study examined associations among changes in inflammatory biomarkers, pain intensity, and HRQoL following a 12-week aerobic exercise programme. Methods: This secondary analysis used data from a randomized controlled trial involving 41 participants with NSCLBP (intervention, n = 21; control, n = 20). Participants received either supervised aerobic exercise plus health education or health education alone for 12 weeks. Change scores for tumour necrosis factor-alpha (TNF-), interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), pain intensity, and HRQoL domains were analysed using correlation and multiple regression analyses. Results: Improvements in IL-6 (r = 0.434, p = 0.005) and hs-CRP (r = 0.444, p = 0.004) were significantly associated with improvements in pain intensity. No significant associations were observed between biomarker changes and HRQoL domains. Treatment allocation was the strongest independent predictor of improvement in physical HRQoL ({beta} = 0.492, p = 0.017) and pain intensity ({beta} = -0.512, p = 0.006). Conclusions: Improvements in IL-6 and hs-CRP were associated with reductions in pain intensity but not with improvements in HRQoL. Treatment allocation was the strongest predictor of clinical improvement, suggesting that mechanisms beyond systemic inflammation may contribute to the benefits of aerobic exercise in NSCLBP. Keywords: non-specific chronic low back pain; aerobic exercise; inflammation; interleukin-6; high-sensitivity C-reactive protein; pain intensity; health-related quality of life.

Introduction: Pain catastrophizing and pain self-efficacy are well-established predictors of health outcomes in chronic pain. Higher pain catastrophizing, a maladaptive cognitive process, predicts worse health outcomes, whereas higher pain self-efficacy, an adaptive cognitive process, predicts better health outcomes. This study examined whether pain catastrophizing and pain self-efficacy interactions predict physical and psychosocial health outcomes at 3 months and their change over 3-months among patients with chronic pain who sought care at a tertiary pain clinic. Methods: Adults with chronic pain (N = 181; 66.7% female; Mage = 58.7) completed baseline assessments of the Pain Catastrophizing Scale (PCS), Chronic Pain Self-Efficacy Scale (CPSS), and PROMIS measures of physical (pain intensity, pain interference, physical function) and psychosocial health (depression, anxiety, anger, loneliness). PROMIS measures were repeated at 3 months. Hierarchical multiple regression analyses tested PCS, CPSS, and their interaction as predictors of outcomes at 3 months and change scores from baseline to 3 months. Results: The PCS by CPSS interaction significantly improved prediction for physical function (Change in R2 = 0.02, p = .02). Higher baseline self-efficacy predicted better physical function (Beta = 0.65, p < .001), but this effect weakened with higher levels of pain catastrophizing. The interaction also predicted change scores in physical function (p = .025) but was marginal after false discovery rate correction (p = .059). Additionally, a significant interaction emerged for loneliness change scores (p = .01): higher self-efficacy predicted greater reductions in loneliness, attenuated by higher catastrophizing. Conclusion: Pain self-efficacy interacted with pain catastrophizing to predict physical function and loneliness at 3 months. Greater self-efficacy was associated with better outcomes, with associations diminished with higher levels of pain catastrophizing. Findings highlight the moderating role of adaptive and maladaptive cognitions and suggest interventions should address both processes to optimize recovery in physical and social functioning.

Background: Chronic pain is a multidimensional condition that often persists despite conventional treatment and adversely affects multiple domains of daily life. Music listening has emerged as a promising non-pharmacological intervention, with accumulating evidence supporting its beneficial effects on pain and associated psychological outcomes. However, despite growing evidence of efficacy, the translation of music listening into routine clinical practice remains limited, partly because intervention reporting has received comparatively little attention. Objective: To evaluate the effectiveness of music listening interventions for chronic pain and systematically assess the methodological quality and completeness of intervention reporting to identify barriers to reproducibility and clinical implementation. Methods: Systematic searches were conducted in PubMed, Cochrane Library, CINAHL, and Web of Science through June 2025, with no date restrictions on publication. Randomized controlled trials involving adults with chronic pain receiving music listening interventions were included. Two independent reviewers screened studies, extracted data, and assessed risk of bias. Intervention reporting was evaluated using the TIDieR checklist, and a random-effects meta-analysis was performed for pain intensity outcomes. Results: Ten RCTs involving 538 participants were included. Music listening interventions varied substantially in delivery, duration, and music selection procedures, reflecting considerable heterogeneity in intervention design. Most studies reported significant improvements in pain and psychological outcomes. Meta-analysis of eight trials (10 effect estimates), demonstrated a moderate reduction in pain intensity (SMD = -0.53, 95% CI: -0.96 to -0.11, p = 0.014; I2 = 76.2%). Although intervention rationale and procedures were generally well described, reporting of intervention modifications, treatment fidelity, and adherence was frequently incomplete. These reporting deficiencies may compromise reproducibility and limit translation into clinical practice. Conclusions: Music listening appears to be a safe, accessible, and scalable non-pharmacological intervention for chronic pain management, with benefits extending beyond pain reduction to psychological wellbeing, quality of life, and functioning. However, incomplete reporting of key intervention components may limit reproducibility and hinder clinical implementation. Future trials should adopt standardized and transparent reporting standards to facilitate implementation into clinical practice.

The mechanisms driving interstitial fluid flow through brain parenchyma remain unresolved, limiting our understanding of how fluid transport contributes to glymphatic waste clearance and broader aspects of brain metabolism and neuronal activity. Existing theories based on diffusion or pressure gradients fail to explain sustained, directional flow through the tortuous extracellular space (ECS), particularly under normal physiologic conditions. Here we propose that electroosmosis, fluid motion driven by endogenous electric fields acting on charged brain tissue, provides a biophysically consistent mechanism for intraparenchymal interstitial fluid transport while generating pressure distributions favorable for periarterial influx and perivenous efflux. Using computational modeling informed by anatomical reconstructions of ECS microstructure and local field potential (LFP) recordings, we show that electroosmotic flow generates physiologically realistic velocities and reproduces brain state dependent differences in glymphatic transport, including the enhanced glymphatic flow observed during sleep compared to wakefulness. A physics-informed reduced-order model (ROM) further demonstrates that these microstructure-resolved results upscale consistently to tissue-level transport. Moreover, electroosmotic flow can induce directional pressure gradients across perivascular interfaces, facilitating both influx and efflux. This mechanism provides a unifying framework linking neuronal activity, parenchymal flow, and compartmental pressure regulation. In contrast, pressure gradients substantially larger than physiological estimates generated much smaller velocities and failed to account for the observed transport rates. These findings address a major gap in glymphatic physiology and suggest that modulation of electric field properties, via endogenous activity or external neuromodulation, could serve as a therapeutic strategy to enhance solute clearance in neurological disorders. Significance StatementA major challenge in brain physiology is the lack of a unifying physical model that explains how fluid moves through the narrow and tortuous extracellular space; a process essential for nutrient distribution and waste clearance. Existing frameworks cannot account for sustained, directional transport under normal physiological conditions. We show that electroosmosis (fluid motion generated when endogenous neuronal electric fields act on charged cellular surfaces) provides a biophysically consistent mechanism for this transport. Using realistic extracellular microstructures and a validated tissue scale reduced order model, our model reproduces experimentally observed brain state dependent transport. Establishing electroosmosis as a possible contributor to interstitial fluid movement offers a new conceptual basis for linking neuronal activity to fluid circulation and for guiding strategies to enhance brain clearance.

A central challenge in neuroscience is understanding how the human brain is organised to support optimal functioning and adaptability. One approach to characterise complex brain dynamics is by artificially perturbing whole-brain models. Here, we asked whether whole-brain organisation under perturbation in major depressive disorder (MDD) changes after intervention with psilocybin and escitalopram. First, we built whole-brain models of pre- and post-treatment resting-state functional magnetic resonance imaging (fMRI) and obtained an initial generative effective connectivity (GEC) matrix for each individual. Then, we employed systematic and local artificial perturbations across intensities, re-optimised each model to create a response GEC (GECr), and assessed the extent of brain reorganisation by quantifying the brain network reconfiguration index (NRI). Our results showed that the global brain NRI increases with psilocybin and decreases with escitalopram. Across sessions and interventions, higher global NRI was related with localised perturbations in brain areas orchestrating the brain's hierarchical dynamics. Traditional approaches complemented our investigation. Our findings suggest distinct neural changes following each treatment for MDD. The increase in brain reorganisation under perturbation following psilocybin is consistent with greater brain flexibility and changeability, whereas the decrease following escitalopram suggests more stabilised brain dynamics. Overall, perturbation-induced brain NRI may represent a useful approach for uncovering neural changes following different interventions for depression.

Objective: The COVID-19 pandemic markedly altered social activity patterns, healthcare utilization, and the epidemiology of infectious diseases. However, its long-term impact on emergency otolaryngologic conditions remains incompletely understood. This study investigated long-term trends in emergency otolaryngologic conditions before, during, and after the COVID-19 pandemic using comprehensive data from a large urban emergency clinic in Osaka, Japan. Methods: All new otolaryngologic outpatients who visited the Chuo Emergency Medical Clinic (CEMC) in Osaka City between 2019 and 2024were retrospectively analyzed. Annual trends in absolute numbers and relative proportions of emergency otolaryngologic conditions were examined by anatomical region and disease category, using 2019 as the pre-pandemic baseline. Results: A total of 99,324 new otolaryngologic outpatients were analyzed. Overall emergency visits declined sharply to approximately half of baseline in 2020, followed by a gradual but incomplete recovery toward pre-pandemic levels by 2024. Most anatomical categories declined to 45-61% of baseline in 2020 and exhibited gradual yet incomplete recovery through 2023; in stark contrast, laryngeal conditions diverged sharply, surging beyond pre-pandemic levels after 2022. Acute infectious otorhinolaryngologic diseases fell to 23-50% of baseline in 2020 and showed variable recovery (69-103%) by 2024. Notably, laryngitis exceeded the baseline, reaching 132% in 2023, whereas epiglottic edema exhibited only a transient increase approaching the baseline in 2021. Non-infectious emergency conditions generally showed only a marginal decrease in 2020 and remained relatively stable throughout the study period, except for sudden sensorineural hearing loss (SSNHL), which dropped sharply to 39% of the baseline in 2020 and remained persistently reduced through 2024. Traumatic emergencies declined variably to 53-81% of the baseline in 2020, followed by an incomplete recovery, reaching only 55-69% by 2024. Conclusion: Emergency otolaryngologic conditions demonstrated heterogeneous recovery trajectories following the COVID-19 pandemic. While most infectious and traumatic conditions gradually but incompletely normalized, laryngeal conditions showed a distinct post-pandemic surge, and SSNHL remained persistently suppressed. These findings reveal heterogeneous, condition-specific recovery trajectories that reflect both genuine shifts in community pathogen burden, true traumatic incidence, and persistent alterations in healthcare-seeking behaviors, insights essential for resource allocation during future public health emergencies.

Background. A filum diameter >2 mm is the conventional MRI threshold for a thickened filum, but it derives from small, mostly adult series showing no age dependence; whether one cutoff suits all of childhood is untested. Objective. To build an age-specific filum-diameter reference on routine pediatric MRI and test, adjusting for image resolution, whether the 2-mm threshold is age-stationary. Materials and methods. In this retrospective study an nnU-Net tracer measured the maximal filum diameter on consecutive lumbosacral MRI; versus manual tracing it showed negligible bias but moderate single-measure agreement. After excluding report-confirmed fatty filum, lipoma, or tethered cord, the proportion >2 mm was analysed within one acquisition protocol and by logistic regression adjusting for voxel size and slice thickness. Results. Of 7,245 examinations, 3,869 (53%) were traceable; untraced ones were younger (median 0.75 vs 2.0 years). The presumed-normal cohort had median diameter 1.48 mm. At matched resolution, 2 mm marked the 94th percentile in infants (5.6% exceeded it) but the 83rd by 3-6 years (17.4%); the age effect persisted after adjusting for voxel size and slice thickness (3-6 years vs infants, adjusted OR 4.7; P < .001). Conclusion. Filum diameter clusters near 1.5 mm, and the fixed 2-mm cutoff flags ~5% of infants but ~17% of preschoolers. Caliber should be judged against an age-specific clinical reference, not one fixed cutoff; a thick filum is not itself a diagnosis of tethered cord.

Task-based precision mapping has become a promising technique in functional MRI (fMRI) to robustly characterize and map an individuals unique activity patterns. These experiments consist of acquiring extensive imaging data in one participant, ultimately improving the sensitivity and specificity of individual-specific functional localization. Despite its advantages, studies have primarily focused on understanding individual-specific cortical activation, preventing a holistic view of a systems-level functional response, and to date, best approaches for the statistical analysis of controlled task-based, densely sampled, whole-brain data have not yet been fully established. Therefore, in this study, we collected whole-brain (i.e. covering cortex, cerebellum, and brainstem) multi-echo densely sampled data of the auditory system, a system with major subcortical components, and evaluated activation sensitivity as well as activation stability across data subsets of commonly-used whole-brain and region-specific inference testing approaches. The whole-brain approaches involved standard voxel-level and cluster-level inference schemes with varying statistical thresholds and a non-parametric permutation inference approach. The region-specific approaches involved an exploratory top % t-statistics methods and non-parametric permutation inference approaches. We found that a whole-brain voxel-level approach with a false discovery rate (FDR) correction (p<0.05) presented highest sensitivity across regions and subjects as well as most consistent detection of expected auditory regions, even with lower scan duration. In addition, we found that a region-specific top % t-statistic approach may be a useful exploratory functional localization tool and a complementary method to standard inference testing approaches.

Amyotrophic lateral sclerosis (ALS) is increasingly understood as a progressive neurodegenerative disorder with distributed cortical and subcortical involvement, but in vivo metabolic mapping has been limited by the spatial coverage of single-voxel proton magnetic resonance spectroscopy (MRS). We acquired high-resolution whole-brain 7T 3D-CRT-FID-MRSI alongside motor-cortex single-voxel sLASER in five rapidly progressing people living with ALS (plALS) and seven non-neurodegenerative controls (NCs), with up to three sessions per participant. Regional metabolite ratios (N-Acetylaspartate [tNAA], glutamate [Glu], glutamine [Gln] to creatine [tCr], and Glu+Gln [Glx] to tNAA) were modelled with Bayesian hierarchical mixed-effects models, and the primary motor cortex was subdivided along its dorsoventral somatotopic axis (bulbar/face, hand/upper-limb, foot/lower-limb). At baseline, plALS showed a motor-cortex-selective tNAA/tCr deficit (motor composite -8.7%, 95% credible Interval [CrI] -16.1 to -1.1, posterior probability=0.99) accompanied by cortically diffuse glutamatergic elevation (Gln/tCr +25.6%, posterior probability=0.96; Glx/tNAA +10.4%, posterior probability=0.95). Reliable separation of the J-coupled glutamine and glutamate resonances at 7T revealed Gln/tCr as a more sensitive marker of glutamatergic dysregulation than Glu/tCr alone in this cohort. Within the somatotopic subdivision, all five plALS showed their peak Gln/tCr increase in the bulbar/face zone irrespective of clinical onset, including three lower-limb-onset patients. Annualised metabolite slope by zone correlated with the matched ALSFRS-R domain decline (Glx/tNAA r=0.82, p<0.001). Group-level longitudinal interactions were modest. Bayesian assurance simulations indicated Glx/tNAA as the most efficient candidate primary endpoint for a confirmatory cross-sectional study. These findings demonstrate that 7T whole-brain MRSI can resolve a metabolic dissociation between motor-selective neuronal compromised and somatotopically patterned glutamatergic dysregulation in ALS and provide design-ready endpoint and sample-size guidance for utility as a structural biomarker of brain function in clinical trials.

PURPOSE: The UK7T travelling head dataset was used to characterise the reproducibility of 7T measurements of the susceptibility of the hippocampal subfields, focusing on the Cornu Ammonis (CA1, CA2 and CA3), dentate gyrus (DG), subiculum (SUB), tail of the hippocampus (TAIL) and entorhinal cortex (ERC). METHODS: Susceptibility maps were created from whole-brain 3D single-echo GRE data (TE=20 ms; 0.7 mm isotropic resolution) using Multi-Scale Dipole Inversion. Automatic Segmentation of Hippocampal Subfields (ASHS) was applied to high resolution T1- and T2-weighted images for segmentation. The mean magnetic susceptibility and volume of hippocampal subfields was evaluated in 50 data sets, comprising 5 repeat acquisitions on 10 healthy participants (age 32 + or -6 years; 3 female). RESULTS: Averaging over subjects, susceptibility values spanned an 18ppb range over the hippocampus (ranging from -13.3ppb in DG to 4.7ppb in ERC). Susceptibility values in the larger hippocampal subfields showed a consistent pattern of variation across subjects, being generally more positive in ERC and SUB than in CA1 and more positive in CA1 than in DG and TAIL. The standard deviation of subfield susceptibilities over subjects ranged from 8.2ppb in the TAIL to 1.7ppb in CA1, and the average standard deviation across repeated measurements, which ranges from 1.7 to 4 ppb, was less than half of the inter-participant standard deviation in all subfields. Susceptibility values in the smaller subfields (CA2 and CA3) were more variable, but ICC(2,k) values for all subfields were >0.82. CONCLUSION: The reported data characterises the variation and reproducibility of hippocampal subfield susceptibility measurements at 7T.

Low back pain is a prevalent issue with few reliable treatments. Although there is great variation in clinical presentation within the low back pain population, little is known about the neurobiological mechanisms underlying these differences. In this study, we sought to stratify chronic low back pain patients (N = 275) into phenotypes characterized by correlated patterns of resting-state brain activity and sensory abnormalities (pain, numbness, and pins and needles) indicated on hand-drawn body maps. Our cross-decomposition analysis yielded phenotypes that resemble previously documented mechanistic pain types, revealing distinct brain connectivity patterns associated with different clinical presentations. Our model was then used to predict pain body maps from fMRI data in a small novel dataset of chronic pain subjects, suggesting that these relationships may generalize to other chronic pain conditions. Our results support the utility of resting-state fMRI in understanding the heterogeneity of chronic pain, which may be leveraged to develop more targeted pain treatments.

Objective: Attention-deficit/hyperactivity disorder (ADHD) is clinically and etiologically heterogeneous, and diagnostic decisions may benefit from integrating multiple sources of information. We developed an explainable deep learning approach to test whether genetic, environmental, cognitive, demographic, and temperament data could classify ADHD diagnosis and identify features contributing to model decisions. Method: We analyzed participants from the Oregon ADHD-1000 cohort split into training, validation, and test subsets. We trained modular neural network models classifying ADHD case-control status using SNP-level genotype data with biological annotations, polygenic scores, demographics, parenting and family conflict, stress and trauma, geocoded measures, cognitive task measures, temperament factor scores, and missingness indicators. Hyperparameter optimization selected model architecture and feature block inclusion. We evaluated model performance using AUC, precision-recall curves, calibration analyses, prediction certainty analyses, and decision curve analysis. We used integrated gradients to quantify block-level, feature-level, and individualized feature importance. Results: The best model using temperament features had an AUC of 0.97 in the held-out test subset, with high accuracy, sensitivity, and specificity and a Brier score of 0.06. The best model excluding temperament had an AUC of 0.75. Feature importance analyses highlighted temperament, demographic, and cognitive domains in the temperament-inclusive model. Individualized explanations showed that prediction drivers varied across participants and could help reveal conflicting or supporting evidence across domains. Conclusion: Explainable, multi-modal classification models can integrate heterogeneous ADHD-relevant information and identify features that contribute to individual predictions. These types of models may advance ADHD risk modeling research and clinician-led decision support, especially in complex or diagnostically uncertain cases.

Acoustic cues such as pitch and spatial location allow listeners to attend to a target speaker and ignore competing talkers, aiding speech recognition in background noise. Diminished ability to utilize acoustic cues for speech stream segregation may thus contribute to older adults' challenges hearing in noise. Adults aged 18-74 completed a speech-in-speech identification task with three conditions containing 1) only pitch cues (fundamental frequency), 2) only spatial cues (interaural time differences; ITDs), and 3) both pitch and spatial cues for segregating a target talker from competing talkers. Hearing thresholds at standard and extended high frequencies (EHFs), auditory brainstem responses (ABRs), and digit span scores were acquired to examine the influence of sensory and cognitive factors on use of each acoustic cue for speech-in-speech recognition. Significant differences were observed between cue condition scores indicating that use of the available cue(s) drove performance. ABR metrics were not a significant predictor but digit span scores significantly predicted scores on all three cue conditions. Working memory abilities therefore set a baseline for participants' speech-in-speech recognition regardless of the acoustic content. Hearing thresholds at standard frequencies significantly predicted scores on the Pitch condition. EHF hearing thresholds better predicted Spatial and Both Cue condition performance, suggesting that EHF thresholds represent auditory processing important for coding ITDs. Age group analysis revealed that older adults (aged 40+) performed significantly more poorly on all cue conditions of the speech-in-speech recognition task relative to younger adults. Age-related changes in auditory sensory processing may therefore impair older adults' speech-in-noise perception by reducing their ability to use acoustic cues for segregating target and competing speech.

Background: Mu-opioid receptors (MORs) are expressed throughout the body including in the brain and gastrointestinal (GI) tract. Total-body PET imaging of the brain and GI tract offers a promising approach for cross-sectional in vivo evaluation of the MOR brain-GI axis. However, intestinal motility and bladder filling introduce motion throughout the GI tract over the scan window. Here we establish analysis methodology to account for motion for dynamic imaging of the brain-GI axis, to further characterize peripheral MORs throughout the body and provide a framework for semi-automatic total-body PET modeling. Methods: 4 subjects underwent 90-min dynamic [11C]-carfentanil (cfn) total-body PET acquisitions at baseline, after intravenous naloxone (central antagonist) administration, and after orally administered loperamide (peripheral agonist and P-glycoprotein substrate). Thalamic MOR availability was measured using the Logan reference tissue model. Using CT-based segmentation, the GI tract was subdivided into anatomical segments, in addition to other peripheral organs (e.g., liver, psoas muscle). Frame-by-frame semi-automatic motion correction was performed with three distinct reference frames (11-14 min post-injection, p.i., 35-40 min p.i., and 85-90 min p.i.). The performance of these three were compared to manual correction. Compartment modeling and Logan graphical analysis were performed to estimate relevant kinetic parameters (K1, VT, VTLogan). Results: Across the 4 subjects and regions, kinetic parameter estimates were highly correlated (r>0.7) for K1, VT and VT Logan when comparing semi-automatic (reference frame at 35-40 min p.i.) and manual correction. With semi-automatic motion correction, graphical-based estimation of VTLogan in the gastrointestinal tract was significantly decreased with loperamide relative to baseline (p<0.05). As expected, naloxone decreased brain thalamic MOR availability but loperamide did not. Conclusions: With semi-automatic motion correction and [11C]-cfn total-body PET, pharmacologic perturbations of MOR brain-GI axis can be quantitatively characterized, reducing the burden of image analysis for these studies.

Early detection of schizophrenia (SZ) remains challenging due to the subtlety of early-stage brain alterations and reliance on subjective clinical assessment. We propose a frequency-aware 3D convolutional neural network (CNN) pipeline that integrates NeuroMark-HiFi high-pass spatial filtering with a modified VGGNet3D architecture featuring 3D Laplacian kernel initialization and dilated convolutions. Using the FBIRN dataset (N=311; 150 healthy controls, 161 SZ) with all 53 intrinsic connectivity networks (ICNs) per subject, we evaluate four experimental conditions across two hyperparameter configurations to isolate the contributions of enhanced input representations and frequency-aware model design. Under the optimized configuration, Condition 3 (HiFi + Laplacian initialization) achieved the best mean test accuracy of 75.54% with a peak single-fold accuracy of 87.10%, representing a 5.44% absolute gain over the optimized baseline. These results demonstrate that high-frequency spatial features are more discriminative for SZ classification than raw intensities, and that aligning Laplacian-initialized kernels with HiFi-filtered input creates a beneficial inductive bias--even with a compact model of approximately 1.4M parameters.