Brain and Behavior

Transcranial magnetic stimulation (TMS) is widely used in both clinical and research settings to study and treat neurological and neuropsychiatric disorders, yet its underlying neural mechanisms remain unclear; particularly how stimulation influences both local and distant regional activity in relation to behavior. In this study, we combined single-pulse TMS with concurrent whole-head functional near-infrared spectroscopy (fNIRS) to examine hemodynamic and behavioral responses during a working memory task, with a focus on behavioral variability. Single TMS pulses were delivered to the left dorsolateral prefrontal cortex (DLPFC) while healthy participants rested; additionally, single pulses were delivered online to the left DLPFC while participants performed the working memory task. Across all participants, we observed a reliable load-dependent increase in hemodynamic activity associated with task. However, behavioral responses to TMS varied during the task. When participants were stratified into subgroups based on performance, a distinct topographic pattern emerged. During the task, TMS systematically modulated hemodynamic responses in regions including DLPFC, superior medial gyrus, precuneus, and parietal lobule, which are areas belonging to the default mode network. Moreover, the hemodynamic response during the single pulse alone sessions without any task was also found to be associated with the behavioral responses in a coherent pattern involving DLPFC, precuneus and parietal lobules. These findings suggest that variable behavioral outcomes during online TMS task are linked to distinct hemodynamic responses in a topographic pattern of local and distant regional areas.

Chemotherapy is a common treatment for women with ovarian cancer, and many women treated with chemotherapy experience cognitive dysfunction. However, few studies have investigated the mechanisms of chemotherapy-related cognitive impairment in women with ovarian cancer. The goal of this study was to assess the relationships among neurovascular coupling, iron levels and cognitive functions in women with ovarian cancer after first-line chemotherapy. Simultaneous fNIRS and EEG data were collected in women diagnosed with advanced stage ovarian cancer at baseline (N = 13) and after 3-9 rounds of chemotherapy (N = 8). The attentional network task (ANT) was administered for neurocognitive evaluation. Blood iron levels were measured using standard clinical assays. In parallel, similar concurrent fNIRS-EEG data were acquired in a group of 10 healthy participants in a test-retest design. Cognitive performance declined, as indicated by decreases in ANT sub scores after chemotherapy. Blood iron biomarkers indexing oxygen transport also declined and were related to decreases in the ANT sub scores. Both fNIRS and EEG data responses were shown to have excellent reliability in the healthy subjects, while cancer patients showed significant decreases in oxygenated hemoglobin response in fNIRS, despite no changes in EEG responses after chemotherapy. A significant dose relationship was also found in the changes of fNIRS responses. Our data indicate that chemotherapy produced cognitive deficits and decreases in the oxygenated hemoglobin response and that these may be related to reduced oxygen transport capacity. Results also suggest the utility of using fNIRS-EEG to monitor the progression of cognitive impairment and characterize those mechanisms.

Dietary iron deficiency in the absence of anemia (IDNA) affects numerous people worldwide, with a wide range of negative effects on brain functioning and cognition. Although studies employing electroencephalography (EEG) have revealed a number of negative effects of IDNA in both the time- and frequency domains, to date there have been no attempts to characterize the effects of IDNA on the temporal dynamics of whole brain interactions. To address this issue, we applied multiscale entropy (MSE) analysis to resting-state EEG data collected from IDNA (n = 21) and iron sufficient (IS, n = 21) women. The MSE analysis on this data revealed that entropy was higher overall for the IS than the IDNA group, with significant differences appearing primarily at longer time scales and under right frontal and left and right parietal electrodes. These results suggest that IDNA may negatively affect long-distance interactions among brain regions and that this could conceivably be a source of diminished cognitive function and neural resilience in IDNA.

Depression and treatment-resistant depression (TRD) are significant public health issues, but the associated network-level neurobiological mechanisms remain poorly understood. This study used magnetoencephalography (MEG) to identify altered resting-state connectivity within the default mode (DMN), executive control (ECN), salience (SN), dorsal attention (DAN), motor (MN), and visual (VN) networks as potential biomarkers of depression and treatment resistance. The study recruited 168 participants (80 healthy volunteers (HVs) and 88 currently experiencing a major depressive episode (74 with TRD and 14 without TRD (noTRD))). Data Integration Analysis for Biomarker Discovery using Latent Variable Approaches for Omics Studies (DIABLO) was used to differentiate the depression, TRD, and HV subgroups and identify neural markers of depression and treatment resistance. For differentiating the depression and HV groups, the triple network model (area under the receiver operating curve (AUROC): 0.759-0.787) - which includes the DMN, ECN, and SN - outperformed the six-network model (AUROC: 0.747-0.762) across different bandwidths. For differentiating the TRD and HV groups, the triple network model demonstrated reasonable prediction across different bandwidths (AUROC: 0.737-0.807); potential within-network connectivity differences distinguished those with TRD from HVs, especially DMN within-network connectivity between the inferior parietal lobule and precuneus in the beta band (FDR-corrected p<.05). Hyperconnectivity within the SN (superior parietal lobule and frontal operculum in the alpha band) and DMN (inferior parietal lobule and lateral prefrontal cortex in the beta band) was associated with number of treatment failures (ps<.05). These findings highlight key brain regions and connectivity patterns, advancing our understanding of neural mechanisms underlying depression and treatment resistance.

Abstract Objectives To evaluate and compare the neuro-behavioural safety profiles of piroxicam and nitroglycerine by investigating their differential effects on cognitive function, spatial and recognition memory, and hippocampal neurochemistry in a di-oestrous female Wistar rat model. Methods Female Wistar rats at di-oestrous were randomly assigned to receive distilled water, piroxicam, or nitroglycerine orally for four consecutive days. Following treatment, spatial and recognition memory were evaluated using standard behavioural paradigms. Hippocampal tissues were analysed for acetylcholinesterase and glutamate activity, oxidative stress markers, and neuroinflammatory indices. Results Piroxicam improved recognition memory and was associated with increased glutamatergic activity and a compensatory rise in superoxide dismutase. However, it also elicited elevated nitric oxide signaling, lipid peroxidation, and localized neuroinflammatory markers in the hippocampus. In contrast, nitroglycerine impaired non-spatial memory during di-oestrous. Although both treatments preserved working memory, they produced distinct effects on object recognition, memory discrimination, oxidative stress parameters, and neuroinflammatory mediators. Conclusions Piroxicam and nitroglycerine exert differential effects on cognition and hippocampal neurochemistry during di-oestrous. Piroxicam improved recognition memory and produced distinct hippocampal neurochemical alterations, whereas nitroglycerine impaired recognition memory. These findings highlight the influence of menstrual pain therapeutics on cognitive function and hippocampal physiology under hormonally sensitive conditions. Keywords: cognitive function; cognitive impairment; cyclooxygenase inhibitors; neuroinflammation; neurochemistry

BACKGROUND: Cognitive flexibility represents a crucial function in adapting to new environments. In this study we examined the ecological validity of a cognitive flexibility task by studying its relationship with individual traits (dogmatism, dependence on routines and perspective taking). Second, we investigated whether global and local structural brain connectivity properties were related to cognitive flexibility as well as associated traits and their possible age-related differences. METHOD: Thirty-eight young (18-35 years) and thirty-seven older (60-85 years) healthy participants took part in an MRI protocol including a Diffusion Weighted Imaging (DWI) sequence. Participants also performed a Rule-Switching task to measure cognitive flexibility performance and filled in questionnaires assessing dogmatism, dependence on routines and perspective taking. RESULTS: A higher cognitive flexibility was related to lower dogmatism and lower dependence on routines only in young adults. In relation to structural connectivity, we found that: a) global and local connectivity properties negatively predicted dogmatism levels in the full sample, b) local connectivity properties of the inferior frontal gyrus (IFG) positively predicted performance in cognitive flexibility performance in the full sample and in older adults, and c) connectivity between left inferior parietal lobule (IPL) and left putamen negatively predicted dogmatism in older adults. DISCUSSION: A deeper understanding of the shaping of structural networks supports a better understanding of cognitive flexibility and dogmatism in a highly dynamic world.

Background Chemotherapy-related cognitive impairment is a well-documented concern among cancer survivors, yet the neural mechanisms underlying deficits in cognitive control remain poorly understood. This study examined group differences in brain activation during a flanker task using functional MRI (fMRI) between chemotherapy-exposed participants and healthy controls. Methods Participants (21 survivors (24.9 years old; 71.4 % female; 15 years from diagnosis) and 21 healthy controls (26.7 years old; 61.9 % female) completed a flanker task during fMRI, with congruent and incongruent conditions. Reaction time, accuracy, and Flanker scores were collected. Whole-brain group comparisons were performed for congruent, incongruent, and incongruent > congruent contrasts. Associations between the incongruent > congruent contrast and cognitive performance were examined. Results Compared to controls, the Chemo group had longer reaction times in both congruent and incongruent conditions (p < .001) and lower NIH Flanker scores (p = .01), with no differences in accuracy. They showed reduced activation in the bilateral inferior frontal gyri, supplementary motor area, and bilateral caudate, but greater activation in the right inferior temporal and cerebellar regions. The incongruent > congruent contrast correlated with increased activation in the orbitofrontal cortex, inferior temporal gyri, and fusiform gyrus with cognitive performance. Conclusions Chemotherapy-exposed participants showed cognitive control deficits and altered neural activation during a flanker task, indicating disrupted recruitment of frontoparietal and subcortical regions key for conflict processing. These findings improve understanding of neural causes of chemotherapy-related cognitive impairment and may help identify at-risk survivors and guide personalized rehabilitation.

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.

Introduction: Functional Neurological Disorder (FND) affects women approximately three times more often than men. This disparity has largely been attributed to higher trauma prevalence and diagnostic bias, while the potential contribution of hormonal influences has received little attention. Methods: An online questionnaire was distributed through FND clinics in thirteen countries, assessing self-reported symptom change across five hormonal events: hormonal contraception, pregnancy, the menstrual cycle, menopause, and gender-affirming hormone therapy. Eligible participants were cisgender women with a diagnosis of FND, or gender minority individuals (transgender or non-binary). Perceived symptom change was rated on a five-point scale ranging from large improvement to large worsening. Results: Among 262 respondents (96% female; mean age 39 years), several hormonal contexts were associated with self-reported symptom changes. Overall, hormonal contraception and pregnancy were frequently associated with worsening of motor and cognitive symptoms, and menopause with worsening across all symptom domains. Menstrual cycle analysis revealed a phase-dependent pattern: worsening was most frequently reported during menstruation and the luteal phase, whereas improvement was most frequent during the follicular phase. Reported changes were not uniform, with a substantial proportion of participants describing no change or improvement. Conclusion: Self-reported FND symptom severity appears to vary with hormonal context, with motor and cognitive symptoms most consistently affected. Given the retrospective, self-report design, these findings are hypothesis-generating and support prospective research into the role of hormonal transitions in FND.

Psychosis as a symptom manifests in schizophenia and bipolar disorder, two highly heterogeneous psychiatric illnesses with overlapping clinical manifestations. Resting-state functional Magnetic Resonance Imaging (rsfMRI), represents a promising tool for identifying objective biomarkers of functional brain alterations to aid differential diagnosis. In this work, we comparatively evaluate multiple rs-fMRI representations for differentiating schizophrenia and bipolar disorder using intrinsic connectivity network (ICN) temporal profiles and several functional network connectivity (FNC) approaches, including static, dynamic, and high-order connectivity analyses. The study was conducted on a cohort of 371 subjects with psychosis, while evaluation was performed using a separate held-out cohort of 315 subjects. We investigated convolutional neural network architectures applied to ICN temporal profiles, spectrograms, and scalograms, alongside classical machine learning models trained on connectivity-derived features. Across the evaluated approaches, ICN temporal profiles provided the most consistent discriminative performance, with a 1D convolutional neural network achieving the strongest overall results under the benchmark protocol. Among connectivity-based methods, static functional connectivity generally outperformed dynamic and high-order representations, suggesting that increased representational complexity did not necessarily translate into improved generalization. Although the obtained classification performance remained modest, the results highlight the challenges of robust psychosis differentiation using rs-fMRI while emphasizing the relative stability of low-order connectivity representations and temporal ICN features. These findings contribute to ongoing efforts toward reproducible and interpretable neuroimaging biomarkers for psychiatric disorders.

Abstract: Objective: Post-traumatic epilepsy (PTE) is a common sequela of traumatic brain injury (TBI). Research indicates that individuals with PTE tend to experience greater cognitive difficulties compared to those with TBI alone. However, it is plausible that a distinct cognitive profile exists that distinguishes between TBI cases with and without PTE. We aimed to identify longitudinal changes in cognitive measures among TBI patients to better assess the changes associated with developing PTE. Setting: Outpatient. Participants: Prospective subjects who had suffered TBI within 6 months post-injury (TBI-6M, n=32), retrospective subjects with pre-existing PTE diagnoses (PTE, n=20), and healthy control subjects (HC, n=41). Design: We examined cognitive performance for TBI patients within 6 months post-injury, then again within 12 months (TBI-12M, n=26), and within 18-months (TBI-18M, n=25), and compared this with cognitive performance among HC and PTE. Main Measures: Cognitive tests administered yielded 15 test components for analysis. We utilized linear mixed effects modeling to examine cohort-level differences cognitive function. Results: 11/15 tests showed a significant performance deficit in the PTE subjects compared to HC. TBI-6M was not significantly different from the PTE subjects; with time, 9/15 tests showed some degree of recovery in TBI subjects. Tests for information processing speed/working memory and executive function showed strong recovery (TBI-6M vs. TBI-18M, SDMT written: p<0.0001, SDMT oral and COWAT: p<0.001). Tests for visual attention/working memory also showed a smaller but significant recovery (TBI-18M vs. PTE, p<0.05). By contrast, tests for verbal memory [HVLT-R Delayed Recall] showed chronic impairment in TBI (TBI-18M vs HC, p<0.0001). TBI subjects generally trend towards recovery in cognitive performance post-TBI. Conclusions: Information processing speed/working memory are strong indicators for TBI recovery, while auditory learning/memory shows chronic impairment. The stagnation of recovery in cognitive domains typically characterized by robust recovery may correlate with an elevated risk of developing PTE.

Reading comprehension is a complex cognitive task that involves dynamic interactions between the brain and external information. Previous studies on reading development primarily focused on localized or static brain activities. However, it remains an enigma how brain state dynamics evolve with development underlying reading comprehension. This study aims to address this issue by combining functional magnetic resonance imaging (fMRI) with Hidden Markov Model (HMM) to explore brain state dynamics. A total of 35 typically developing children and 31 adults were scanned while reading a story. Our results demonstrated a tripartite brain state organization, characterized respectively by high activities in the visual (State #1), language (State #2), and default mode network (DMN, State #3) regions. Children exhibited significantly longer dwell time in the DMN state (State #3) compared to adults, along with a higher probability of transitioning from the language state (State #2) to the DMN state (State #3). In addition, adults exhibited greater flexibility in state transitions during reading comprehension. Finally, the alignment between the dynamic states of children and the average states of adults was a significant positive predictor of their reading comprehension performance. This study provides a novel, intuitive perspective on how brain state dynamics evolve during the development of reading comprehension.

Background: Opioid use disorder (OUD) is associated with a wide range of cognitive, affective, and motivational impairments, suggesting a disruption of large-scale brain systems that support diverse domains of functioning. Resting-state brain network segregation quantifies the degree of functional specialization within brain networks, is age-related, has been linked to brain glucose metabolism, and has been shown to be reduced in substance use disorders. We examined brain network segregation in individuals with OUD and non-OUD controls and tested associations with the duration of opioid use. Methods: Resting-state functional MRI data were collected from 149 individuals with OUD and 126 non-OUD controls. Functional connectivity was computed between brain regions assigned to functionally specialized networks supporting higher-order "association" or "sensorimotor" processes. For each network, segregation was quantified as the extent to which within-network connectivity exceeded between-network connectivity. Results: Individuals with OUD demonstrated lower segregation of the association and sensorimotor networks than non-OUD controls. Within the OUD group, more years of opioid use was associated with lower segregation of the association network, but not the sensorimotor network. Conclusions: OUD is characterized by overall lower resting-state brain network segregation. More years of opioid exposure was associated with lower association-network segregation, consistent with there being cumulative effects of chronic opioid use on large-scale brain organization, though causation could not be examined in this cross-sectional dataset. These findings identify altered network segregation as a potential neurobiological marker of OUD and suggest that restoration of brain network specialization is a measurable target of OUD treatment and potentially recovery.

Background: Bipolar disorder is associated with persistent social, cognitive, and functional impairment during euthymia, yet the neural mechanisms underlying these deficits remain unclear. Alterations to self-referential processing are a candidate mechanism, but existing electrophysiological studies rely on emotionally valenced paradigms that potentially confound self-processing with emotional biases. Methods: We analysed electroencephalography from 28 patients with bipolar disorder (type I or II) and 28 age- and sex-matched healthy controls during an emotionally neutral colour judgment task with self-related (preference) and non-self-related (similarity) conditions. Late positive potentials, temporal generalisation decoding, and frequency band decoding (theta, alpha, beta) were used to characterise the temporal dynamics and oscillatory correlates of self versus non-self processing. Results: Controls showed higher overall event-related potential amplitudes and greater self versus non-self differentiation than patients (condition by group interaction, 337 to 946 ms). Broadband temporal generalisation decoding revealed extensive cross-temporal generalisation of the self versus non-self representation in controls, spanning most of the trial, but no significant generalisation in patients. Frequency analyses showed that alpha and beta carried self versus non-self information in both groups, with broader extent in controls, and that anterior theta carried this information in patients but not controls. Exploratory correlations linked decoding measures to rumination and anxiety but not to manic symptoms. Conclusions: The neural representation distinguishing self-referential from externally guided processing was both smaller in amplitude and less temporally sustained in bipolar disorder. Reduced persistence is not detectable by conventional amplitude analyses, and may bear on the self-related and social cognitive difficulties reported in this population.

Objective: Disruption of the excitation/inhibition balance may contribute to the pathophysiology of bipolar disorder, with post-mortem studies reporting abnormalities in GABA-receptors, interneurons and inhibitory signaling in prefrontal areas. Transcranial magnetic stimulation with electroencephalography (TMS-EEG) enables in vivo assessment of cortical excitability/inhibition. This study examined short-latency intracortical inhibition (SICI) after left- and right-dorsolateral prefrontal cortex (DLPFC) stimulation in bipolar depression (BDep, n=10) and healthy controls (HC, n=22). Methods: SICI (paired-pulse TMS) and excitability (single-pulse TMS) were quantified using local- and global-mean-field-power. Associations with lithium use and between-group differences in TMS-evoked potential amplitudes were also explored. Results: For left-DLPFC stimulation, BDep showed weaker SICI than HC (local: 3.7%{+/-}12.5 vs 9.0%{+/-}20.3, p=0.05; global: 1.5%{+/-}11.7 vs 8.8%{+/-}20.6, p=0.10), driven by larger ppTMS responses (weaker inhibition). For right-DLPFC stimulation, BDep showed stronger SICI than HC (local: 17.3%{+/-}16.1 vs 0.75%{+/-}27.1, p=0.36; global: 16.2%{+/-}14.6 vs -1.0%{+/-}21.8, p=0.03), driven by a larger spTMS response (enlarged excitability). Stronger right-hemispheric global-SICI was most pronounced in BDep patients not using lithium (17.9%{+/-}7.0) vs lithium users (3.9%{+/-}11.9) and HC (pFDR=0.03). Conclusions: BDep is characterized by reduced cortical inhibition after left DLPFC stimulation and enlarged cortical excitability after right DLPFC stimulation; the latter partly normalized by lithium. Significance: To our knowledge, this is the first study to apply TMS-EEG to the bilateral DLPFC in BDep, revealing distinct patterns of hemispheric dysfunction. These findings warrant replication in larger samples, to further elucidate the underlying pathophysiology and inform the mechanisms of action of neuromodulation treatments, such as rTMS.

Background: MRI has increasingly been explored as a biomarker for detecting structural and functional brain changes. For clinical decision-making, it is crucial to validate observed changes in MRI indices at the individual level. The uncertainty in longitudinal MRI indices can be quantified using the repeatability coefficient (RC). Methods: Twenty healthy controls (10 males, 10 females) underwent two test-retest sessions of structural magnetic resonance imaging (MRI) and resting-state functional MRI (rs-fMRI) on the same day, separated by a 30-minute interval. RC values and their 95% confidence intervals (CI) were estimated for subcortical volumes, cortical thickness, and within-network functional connectivity. Additionally, 33 patients with mental health disorders underwent MRI before and after 20 sessions of transcranial magnetic stimulation (TMS). Percentage changes in MRI-derived indices were assessed at the individual level, with changes exceeding the RC threshold considered indicative of true change beyond measurement uncertainty. Results: The RC showed measurement variability in subcortical volumetric in the range of 8% to 17.5% for caudate and left amygdala, respectively. For cortical thickness, the RC was measured between 3.5% and 16.5% for the left occipital pole and the left temporal pole, respectively. The RC% for fractional anisotropy (FA) measures were variable between 11.3% (the left middle cingulum) and 62.9% (the right anterior cingulum). For within-network connectivity, the RC was measured in a range of 9.7% and 29.4% for sensorimotor and visual networks, respectively. TMS-treated patients exhibited no changes beyond the RC in almost all subcortical volumes and within-network connectivity. The most frequent changes beyond the uncertainty were observed in FA measures, particularly in the posterior cingulum, where 17 out of 23 patients exhibited clinically meaningful alterations. Conclusion: Structural brain features extracted from MRI demonstrated high reliability. Among all measures, FA, reflecting white matter integrity, was most sensitive in detecting neural changes following TMS, highlighting its potential utility as a treatment-responsive biomarker.

ObjectiveDescribe and compare the biomechanical severity of head acceleration events (HAEs) associated with diagnosed concussion in elite mens and womens rugby league using instrumented mouthguards (iMGs) and evaluate the diagnostic accuracy and screening performance of severity metrics within the current Head Injury Assessment (HIA) process. MethodsA prospective cohort of 398 men and 252 women from Super League teams wore iMGs across 515 matches. Following a matching and data quality screening procedure, 123 HIAs (106 men, 17 women) were matched to HAEs, 52 of which were diagnosed concussions (44 men, 8 women). High-magnitude asymptomatic control HAEs (22,676 men, 3,200 women) were sampled proportionally to the number of HIAs. A range of biomechanical severity metrics were calculated for HAEs. Statistical comparisons between outcomes were made. Receiver operating characteristic (ROC) analysis evaluated diagnostic accuracy (ability to predict diagnosed concussions within the HIA). Precision-recall analysis evaluated screening performance (ability to discriminate observable concussion signs from asymptomatic events). ResultsDiagnosed concussions had greater severity than asymptomatic HAEs across all metrics in both sexes. For diagnostic accuracy, area under the ROC curve ranged from 0.61 to 0.72 in men and 0.53 to 0.86 in women. For screening performance, optimal thresholds in several metrics provided theoretical improvements to precision over current thresholds used in rugby, but recall remained <0.20. ConclusionThese findings support integrating iMG-derived severity metrics into a multimodal, clinician-led HIA pathway as objective adjuncts for diagnosis and screening, while reinforcing that they cannot replace clinical judgement or other assessment modalities. What is already known on this topicInstrumented mouthguards are increasingly used in rugby to quantify head acceleration events and trigger Head Injury Assessment (HIA) alerts, but current screening thresholds based on simple peak kinematics have low sensitivity for identifying HAEs linked with visible concussion signs, and very few iMG-measured concussions, particularly in women, have been reported in current research. What this study addsThis study provides the largest dataset of iMG-measured concussions in any sport, shows that concussive HAEs are more severe than asymptomatic events across multiple biomechanical metrics in both sexes, and identifies several severity metrics with diagnostic accuracy comparable to existing HIA sub-tests and modest theoretical improvements over current screening thresholds. How this study might affect research, practice or policyThese findings support incorporating iMG-derived severity metrics as objective adjuncts within clinician-led HIA pathways, highlight the need for sex-inclusive iMG datasets and multimodal concussion identification, and may inform future refinement of iMG screening thresholds in elite rugby and other contact sports.

Abstract Background: Long COVID frequently includes post-exertional malaise, neuromuscular fatigue, internal vibrations, tremor-like symptoms, orthostatic intolerance, sleep disturbance, cognitive dysfunction, and autonomic instability. Neuroimaging studies in Long COVID and post-infectious ME/CFS have identified abnormalities across limbic, thalamic, mesiotemporal, brainstem, cerebellar, and white-matter systems, but no single established circuit accounts for this clinical phenotype. We examined whether abnormalities cluster at the mammillary body-fornix-superior tuberal hypothalamic interface and within connected brainstem-cerebellar pathways. Methods: Structural MRI and diffusion tensor imaging were analysed in 88 participants with clinician-diagnosed Long COVID and 34 healthy controls (total N = 122). Thirty-three patients were classified as bedridden. Volumetric and diffusion analyses focused on the mammillary bodies, superior tuberal hypothalamic region, fornix, dorsal and median raphe, midbrain reticular formation, and cerebellar peduncles. Fractional anisotropy was used as an index of white-matter microstructural organisation. Exploratory clinical associations included motor impairment, proprioceptive dysfunction, autonomic symptoms, fatigue, internal vibrations, and tremor-like symptoms. Results: Three mammillary-body volume phenotypes were identified: reduced, enlarged, and control-range. Left and right mammillary-body volumes differed across groups, with large effect estimates. Segmentation showed narrowing or loss of a visible internal passage at the superior tuberal-mammillary interface, while the fornix showed altered diffusion measures and reduced tract coherence in the hypothesised gate region. Additional findings included lower superior cerebellar peduncle volume, lower middle cerebellar peduncle fractional anisotropy, and lower dorsal raphe and midbrain reticular formation volumes in Long COVID. Conclusions: The findings support an exploratory mammillary body-fornix gate model in which a vulnerable periventricular hypothalamic-limbic interface may contribute to network dysfunction in a subgroup of patients with severe Long COVID. The data do not establish direct viral invasion, a coronavirus entry route, axonal destruction, or a single causal pathway. Prospective replication with standardised acquisition, preregistered regions of interest, correction for multiple comparisons, objective movement and autonomic measures, and longitudinal follow-up is required. Keywords: Long COVID; post-COVID condition; ME/CFS; mammillary body; fornix; hypothalamus; diffusion tensor imaging; internal vibrations; tremor-like symptoms; neuromuscular fatigue; dysautonomia; brainstem

Background: Anxiety-spectrum disorders (ANSD) are highly prevalent, yet the underlying neurovascular mechanisms remain unclear. Functional near-infrared spectroscopy (fNIRS) comprises a non-invasive method to assess cortical hemodynamics, neurovascular coupling, and network organization during cognitive processing. Methods: We investigated healthy controls (HC), generalized anxiety disorder (GAD), anxious depression (AD), and anxiety-depression comorbidity (CO) using multichannel fNIRS during a verbal fluency task. Multiple hemodynamic features were extracted, including peak response, temporal hemodynamic variability, {beta}activation, and HbO, HbR, and HbT signals. Functional connectivity, graph-theoretical network measures, machine-learning classification, and associations with depressive, anxiety and psychosomatic scores were examined. Results: Compared to controls, ANSD patients showed reduced task-evoked HbO and HbT responses, preserved HbR levels, increased temporal hemodynamic variability, and reduced {beta}activation. Activation deficits were most prominent in bilateral frontopolar and medial prefrontal cortices and followed a gradient, with the CO group exhibiting highest abnormalities. Functional connectivity was increased, whereas clustering coefficient, nodal local efficiency, and nodal efficiency were reduced, indicating maladaptive hyperconnectivity accompanied by inefficient network organization. The AD and CO groups showed the greatest network disintegration. Temporal hemodynamic variability emerged as the strongest predictor of anxiety, depressive, and physiosomatic symptom severity. Reduced prefrontal activation was significantly associated with higher symptom domain scores. Machine-learning analyses demonstrated adequate discrimination between HC and ANSD. Conclusions: ANSD are characterized by impaired neurovascular recruitment, increased hemodynamic instability, maladaptive hyperconnectivity, and disrupted cortical network topology. These abnormalities appear to represent transdiagnostic neurovascular processes underlying anxiety, depressive, and physiosomatic symptoms across the anxiety spectrum.

Background: On-call clinicians frequently report the anecdotal impression of 'theme shifts' during which specific acute neurological diagnoses appear to cluster. Whether such clustering reflects a statistically true and reproducible phenomenon has not been systematically investigated; the present paper examines seasonality and temporal clustering within six different acute neurological conditions. Methods: In this retrospective, single-center cohort study, we identified all patients admitted to a tertiary neurological department between July 2016 and June 2026 with acute unilateral vestibulopathy, cerebral artery dissection, generalized epileptic seizures, primary intracerebral hemorrhage, peripheral facial nerve palsy, or transient global amnesia (TGA) (n = 2,140). Monthly and seasonal distributions were assessed using chi-squared goodness-of-fit and cosinor analysis. Short-term temporal clustering was tested by Monte Carlo permutation across time windows from 24 hours to 90 days, and endogenous cluster dynamics were characterized using Hawkes self-exciting point process modeling. Results: Admissions for generalized epileptic seizures showed a statistically significant deviation from a uniform monthly distribution with a winter distribution (p<0.001 and q = 0.002), and a significant temporal clustering across time windows from 72 hours to 90 days (all q < 0.05). Peripheral facial nerve palsy presented significant clustering at the 90-day window (q = 0.029) and TGA at 60-day time window (q = 0.041) without seasonality; the diagnostic groups of acute unilateral vestibulopathy, cerebral artery dissection and primary intracerebral hemorrhage showed neither seasonality nor clustering after correction for multiple comparison. No diagnostic group showed clustering within a 24-hour window, statistically significant self-excitation in Hawkes process modelling, or a significant linear trend in monthly case counts over the study period. Conclusion: The anecdotal impression of diagnostic 'theme shifts' among on-call neurologists appears to have a measurable basis, although clustering is confined to specific conditions and rather on a time scale of weeks to months. Generalized epileptic seizures were the only diagnostic group that uniquely combined seasonality with temporal clustering, suggesting a shared trigger, while facial palsy and TGA showed episodic, yet non-seasonal clustering.