Clinical Neurophysiology

Genetic deletion or pharmacological blockade of P2X7 receptors (Rs) counteract status epilepticus (SE) in animal models of epilepsy. It is, however, unclear whether P2X7Rs are localized at astrocytes or neurons, and the reason for astrocytic atrophy arising in consequence of SE is also ambiguous. We conducted a combined morphological/electrophysiological study in order to investigate these issues. It has been shown that kainic acid (KA)-induced SE in mice led to the atrophy of hippocampal astrocytes and at the same time to the decrease of ezrin immunoreactivity and its co-expression with mCherry, whose synthesis has been initiated by the injection of a virus complex. mCherry expression in astrocytes enabled us to study changes in cell somata and processes brought about by KA-injection. Ezrin is a plasmalemmal-cytoskeleton linker; its grade of expression indicates changes in the existence/function of small peripheral astrocytic processes. Pretreatment of mice with the blood-brain barrier-permeable P2X7R antagonist JNJ-47965567 prevented the SE-induced damage of astrocytes. KA caused a potentiation of dibenzoyl-ATP (Bz-ATP) currents in astrocytes but not neurons of the hippocampus. This effect was also abolished by pre-treatment of mice with JNJ-47965567 before applying KA, although no similar changes occurred in hippocampal CA1 neurons. The measurement of spontaneous postsynaptic currents (sPSCs) and spontaneous excitatory postsynaptic currents (sEPSCs) indicated a presynaptic facilitation of neurotransmitter release by Bz-ATP. In conclusion, we suggest that astrocytic P2X7Rs are the primary target of ATP release from damaged CNS cells in the hippocampus which simultaneously causes damage to astrocytic somata and processes.

Short-interval intracortical inhibition (SICI) is the most widely used neurophysiological index of GABAergic inhibition in the human cortex. However, it is an indirect measure, inferring synaptic inhibition from suppression of peripherally recorded motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS). In the standard protocol, a subthreshold conditioning pulse suppresses the MEP evoked by a suprathreshold test pulse delivered 1-5 ms later. Interpretation is further complicated by temporal overlap with short-interval intracortical facilitation (SICF), reflecting excitatory interactions at interstimulus intervals of [~]1.5 and 2.7 ms. To overcome these limitations, we recorded immediate TMS-evoked EEG potentials (iTEPs; 1-10 ms post-stimulus) as a more direct measure of motor cortical activity in 16 healthy volunteers (20-35 years; 7 male). The conventional SICI protocol suppressed only later components of the iTEP, likely corresponding to late corticospinal volleys previously identified in epidural spinal recordings after suprathreshold TMS, while the earliest iTEP component was unaffected. Importantly, later iTEPs were suppressed to a similar extent whether conditioning-test intervals coincided with SICF peaks or troughs, and the magnitude of iTEP suppression correlated with concurrently recorded paired-pulse MEP suppression. SICI also reduced an early TEP component (N15; 10-20 ms), but paired-pulse N15 suppression showed a different dependence on stimulus intensity and did not correlate with MEP suppression. These findings demonstrate that SICI measured via MEPs does not reflect a global index of cortical GABAergic motor cortical inhibition but instead reflects inhibition within specific cortical circuits that can be investigated directly with iTEPs.

Parkinson's Disease (PD) is a complex neurodegenerative disorder that manifests through systemic, large-scale physiological reorganizations. While research often focuses on region-specific neural changes, there is a growing need for multidomain approaches to capture the complexity of the disease and its clinical heterogeneity. This study proposes an analytical pipeline to evaluate Brain-Heart Interplay (BHI) as a novel systemic biomarker for neurodegeneration and healthy ageing. In this study we assessed BHI across three open-source datasets (EEG and ECG signals). We compared Healthy Young, Healthy Elderly, and PD patients in resting state to investigate the effects of ageing and cognitive performance. Additionally, we studied BHI trends in PD patients in the moment of freezing of gait (FOG). Methodologically, brain network organization was quantified using coherence-based EEG connectivity and graph theory, while heart activity was analyzed through Poincare plot-derived measures of cardiac autonomic activity. The coupling between these two systems was measured using the Maximal Information Coefficient to capture linear and non-linear dependencies between global cortical organization and cardiac autonomic outflow. The results demonstrate that BHI is a sensitive biomarker for detecting early multisystem dysfunction in both neurodegeneration and ageing. Furthermore, the identification of specific BHI trends during FOG onset suggests new opportunities for understanding the physiological mechanisms driving motor complications in PD. Our proposed pipeline provides a guiding tool for large-scale physiological assessment in clinical research.

1.PurposeSYNGAP1-related developmental and epileptic encephalopathy (SYNGAP1-DEE) is characterized by high rates of both epilepsy and autism spectrum disorder (ASD). While the clinical spectrum is well-documented, the link between specific seizure semiologies and caregiver-reported autistic behaviors is not well understood. This study analyzed the correlation between ten distinct seizure types, their frequencies, and a caregiver-reported autistic behavior score. MethodClinical data were extracted from the PATRE (PATient-based phenotyping and evaluation of therapy for Rare Epilepsies) Registry for SYNGAP1, in the framework of the EURAS project (Grant No. 101080580, Horizon Europe). This study employed a retrospective cross-sectional analysis of caregiver-reported registry data. Analysis was restricted to an analytic cohort of N=337 participants with complete data for both the epilepsy questionnaire (including epilepsy status, seizure semiology, and peak seizure frequency items) and the behavior questionnaire (from a total N=522 registry participants). Caregiver-reported autistic behaviors were quantified using a standardized caregiver-reported scale (Likert 1-5). Statistical associations were evaluated using the Wilcoxon rank-sum test to compare caregiver-reported autistic behavior scores across different seizure semiologies and Spearmans rank correlation to assess the impact of seizure frequency (9-point scale). ResultsWithin the analytic cohort (N=337), epilepsy was reported in 259 patients. Eyelid myoclonia was the most prevalent semiology, affecting 64.9% (n=168) of the epilepsy-positive group. Atypical absences (n=77) demonstrated the most profound and statistically robust association with higher caregiver-reported autistic behavior scores (FDR-adjusted p = 0.001). Significant associations were also observed for typical absences (n=70, FDR-adjusted p = 0.018), eyelid myoclonia (FDR-adjusted p = 0.018), myoclonic-atonic seizures (n=40, FDR-adjusted p = 0.019), and atonic seizures (n=72, FDR-adjusted p = 0.025). Focal and tonic-clonic seizures showed weaker associations (FDR-adjusted p = 0.026 and p = 0.047, respectively). Crucially, quantitative analysis revealed no significant correlation between ordinal caregiver-reported peak seizure frequency ratings and caregiver-reported autistic behavior scores across all semiologies (e.g., Eyelid Myoclonia: p=0.096; Atypical Absences: p=0.744), indicating no detectable association between peak-frequency ratings and caregiver-reported autistic behavior scores. ConclusionHigher caregiver-reported autistic behavior scores in SYNGAP1-DEE were most strongly associated with the presence of atypical absences, representing a generalized, thalamocortical seizure network dysfunction. In contrast, no detectable association was observed between caregiver-reported autistic behavior scores and the ordinal caregiver-reported peak seizure frequency metric. Atypical absences and related semiologies may serve as clinical "red flags" for increased neurodevelopmental comorbidity severity, regardless of reported peak seizure frequency. Abstract SummaryThis study investigates the relationship between ten seizure semiologies, seizure frequency, and severity of caregiver-reported autistic behaviors in a large-scale international cohort of N=337 patients with SYNGAP1-DEE. We identify a robust association between elevated caregiverreported autistic behavior scores and specific thalamocortical seizure patterns, most prominently atypical absences. Notably, our analysis reveals that this association is independent of seizure frequency, demonstrating no detectable association between this ordinal, caregiver-reported seizure frequency metric and caregiver-reported autistic behaviors.

BackgroundGlobal cerebral anoxia is a leading cause of death and resuscitated patients often remained persistently affected by neurological deficits. While previous studies suggest that brain-heart electrophysiological interactions may predict severity and prognosis after hypoxic brain injury coma, little is known about the brain-heart dynamics at near-death. Gaining insight into these mechanisms is crucial for developing targeted interventions in critical conditions. ResultsUsing a rodent model of reversible systemic anoxia (n=29, male and female rats), we investigated whether brain-heart interactions during the asphyxia onset could predict the return of brain electrical activities after resuscitation. Electrophysiological recordings confirmed that cerebral activity declines following asphyxia, coinciding with increased heart rate variability. Notably, the strong coupling between cardiac parasympathetic activity and high-frequency brain activity in the somatosensory cortex and hippocampus serves as a key predictor of a favorable outcome. ConclusionOur study underscores the involvement of the brain-heart axis mechanisms in the physiology of dying and the potential prognostic significance of these mechanisms, paving the way for translational research into critical care, based on new characterizations of cardiac reflexes and brain-heart interactions.

ObjectiveIn individuals with drug-resistant epilepsy, accurately identifying the brain regions where seizures originate is a critical prerequisite to guide surgical treatment and achieve seizure freedom. To accomplish this, intracranial EEG is considered the gold standard, providing the spatiotemporal high-resolution data necessary to pinpoint epileptogenic activity. However, this precision is achieved through an invasive procedure with significant patient burden, which is fundamentally limited by the electrode placement and spatial coverage. MethodsIn this study, we investigated the potential utility of preoperative resting-state fMRI to non-invasively map alterations in brain dynamics at the whole brain level. Region-wise brain dynamics were quantified with complementary measures of local autocorrelation decay rates. We assessed the capacity of these derived features to effectively identify intracranial EEG confirmed seizure onset zones in 18 individuals with drug-resistant medial temporal lobe epilepsy. Overall, the study cohort contained 3867 implanted electrodes of which 159 classified as seizure onset zones by two independent board-certified epileptologists. ResultsOverall, our findings reveal more constrained temporal dynamics for brain regions associated with seizure onsets compared to non-seizure onset zones. Individual-level prediction showed a performance better than chance in 15 of the 18 patients. The overall predictive performance across all patients yielded a median AUC of 0.81, a median true positive rate of 0.75, and a median true negative rate of 0.83. Furthermore, in a subset of 13 patients, those with negative seizure outcomes showed higher probabilities of seizure onset zone predictions outside the resection area compared to those with good outcomes. SignificanceOverall, our findings suggest that altered temporal dynamics derived from preoperative resting-state fMRI represent a promising non-invasive approach for delineating epileptogenic tissue, potentially informing intervention strategies and guiding electrode placement.

ObjectiveVagus nerve stimulation (VNS) is an established neuromodulation therapy used in the management of drug-resistant epilepsy (DRE), or when other intracranial surgical modalities have not reduced seizure burden. We evaluated whether prior intracranial surgery for epilepsy influences safety and effectiveness outcomes with adjunctive VNS, using real-world data from the CORE-VNS study. MethodsCORE-VNS (NCT03529045), a prospective, multicenter, international observational study, was designed to collect data on seizure and non-seizure outcomes in patients with DRE treated with VNS. Participants were identified as having or not having undergone prior intracranial brain surgery for epilepsy (ICSE) and received an initial VNS implant. Baseline seizure frequency data and patient-reported outcome measures were collected at 3, 6, 12, 24, and 36 months. This analysis compared the baseline data for VNS therapy and safety outcomes at 36 months. ResultsAmong 531 participants implanted with VNS, prior ICSE was performed in 84. Median percentage seizure reductions at 36 months for all seizures (76.6% and 76.3%), all focal seizures (83.3% and 71.8%), and all generalized seizures (77.8% and 76.2%) were found to be similar between those without and with a history of ICSE, respectively. The 50% responder rate for all seizures reported at baseline was similar, 64.8% and 61.8%, in both groups and complete seizure freedom was reported by 17.9% and 8.8%, respectively. Implant-related adverse events (AE) and serious AE rates were similar between groups. ConclusionVNS was associated with clinically meaningful seizure reductions and showed a consistent safety profile irrespective of the history of ICSE. Prior ICSE should not be a contraindication to the consideration of VNS.

PurposeColonic motility disorders, including diarrhea-predominant irritable bowel syndrome and slow-transit constipation, impose a major clinical burden. Although high-resolution colonic manometry reveals characteristic spatiotemporal motor patterns, such as high-amplitude propagating contractions and cyclic motor pattern in healthy individuals, these patterns are often altered or absent in disease. Understanding how these patterns arise from underlying pacemaker, neural, and mechanical mechanisms is essential for improving treatment strategies. MethodsWe developed a biophysical whole-colon model that integrates an Interstitial Cells of Cajal-inspired oscillator network, enteric nervous system reflexes, a pressure-gated modulation element motivated by rectosigmoid brake behavior, and a nonlinear tube law describing colon wall mechanics. The model simulates spatiotemporal pressure patterns along the colon and allows systematic variation of physiological parameters associated with pacemaker activity, neural reflex control, and distal gating. ResultsA small set of parameters reproduces three illustrative motility patterns corresponding to healthy motility, diarrhea-predominant irritable bowel syndrome, and slow-transit constipation. The simulated pressure maps recapitulate key features observed in high-resolution manometry, including propagation direction, regional patterning of contractions, and case-specific changes in amplitude and coordination. Sensitivity analysis suggests that proximal excitation strength and waveform morphology strongly influence global motility metrics. ConclusionOur study presents a simple, biophysical framework for reproducing clinically observed colonic motor patterns and exploring their disruption in disease. More broadly, the model may help interpret clinical manometry in mechanistic terms and support hypothesis-driven in silico studies of colonic motility disorders.

BackgroundTheory of Mind (ToM) deficits are well-documented in right-hemisphere stroke but remain understudied in post-stroke aphasia. Prior work suggests that performance on tasks assessing ToM may be relatively preserved in aphasia and dissociable from language impairment, but these findings are based largely on small studies. This study examined performance on nonverbal false-belief tasks in post-stroke aphasia, its relationship with aphasia severity, and whether vascular brain health, operationalized using cerebral small vessel disease (CSVD) markers, contributed to variability in performance. MethodsForty-four individuals with aphasia completed two nonverbal belief-reasoning tasks assessing spontaneous perspective-taking and self-perspective inhibition. Task accuracy served as the primary outcome. Linear regression models examined associations between task performance, aphasia severity (Western Aphasia Battery-Revised Aphasia Quotient), and CSVD markers, including white matter hyperintensities, cerebral microbleeds, lacunes and enlarged perivascular spaces in the basal ganglia and centrum semiovale. ResultsPerformance was heterogeneous across tasks, with reduced performance observed in 23% of participants on the Reality-Unknown task and 36% on the Reality-Known task. Aphasia severity was not associated with task accuracy. Greater cerebral microbleed count was associated with lower accuracy on both tasks, while greater basal ganglia enlarged perivascular spaces burden showed a more selective association with lower performance. ConclusionsPerformance on nonverbal false-belief tasks in aphasia is variable and not explained by aphasia severity alone. These findings suggest that apparent ToM-related difficulties in aphasia may be shaped by broader vascular brain health, supporting a more multidimensional framework for interpreting social-cognitive task performance after stroke.

Electroencephalography (EEG) preprocessing is a critical yet time-consuming step that often relies on expert-driven, semi-automatic pipelines, limiting scalability and reproducibility across large datasets. In this work, we present sEEGnal, a fully automated and modular pipeline for EEG preprocessing designed to produce outputs comparable to expert-driven analyses while ensuring consistency and computational efficiency. The pipeline integrates three main modules: data standardization following the EEG extension of the Brain Imaging Data Structure (BIDS), bad channel detection, and artifact identification, combining physiologically grounded criteria with independent component analysis and ICLabel-based classification. Performance was evaluated against manual preprocessing performed by EEG experts at two complementary levels: preprocessing metadata (bad channels, artifact duration, and rejected components) and EEG-derived measures. In addition, test-retest analyses were conducted to assess the stability of the pipeline across repeated recordings. Results show that sEEGnal achieves performance comparable to expert-driven preprocessing while preserving key neurophysiological features. Furthermore, the pipeline demonstrates reduced variability and increased consistency compared to human experts. These findings support sEEGnal as a robust and scalable solution for automated EEG preprocessing in both research and large-scale applications. HighlightsFully automated and modular EEG preprocessing pipeline. Benchmarked against expert-driven preprocessing. Comparable performance in metadata and EEG-derived measures. Demonstrates stable performance in test-retest recordings. BIDS-based framework for reproducible EEG data handling.

AbstractO_ST_ABSBackgroundC_ST_ABSLeft ventricular (LV) remodeling in chronic Chagas cardiomyopathy (CCC) is progressive, but whether population-level LV mass dynamics follow nonlinear patterns and whether the loss of dynamic complexity tracks mortality is unknown. MethodsFifty outpatients from SEARCH-Rio cohort were followed-up for 10 years. Serial echocardiography provided paired LV mass measurements fitted to the logistic equation x = {middle dot}x{middle dot}(1-{gamma}{middle dot}x). Lyapunov exponents (LE) were computed from consecutive inter-patient derivatives. A clinical risk score was developed using Firth penalized logistic regression with bootstrap validation (B = 1,000) and Cox-Firth sensitivity analysis. ResultsLV mass remodeling adjusted the logistic equation with = 3.91 {+/-} 0.18 and {gamma} = 1.27 {+/-} 0.06, which was compatible with dynamics near the complexity threshold ( {approx} 3.57). Survivors showed positive LE (+0.339 {+/-} 0.543), and nonsurvivors showed negative LE (-0.825 {+/-} 0.972; p = 0.015). The fixed-point equilibrium of {approx} 280 g was approached by 63 % of patients at follow-up (p = 0.0003), a pattern indistinguishable from regression to the mean in the present design. Firth regression identified EF < 51.7 % and maximum heart rate < 109 bpm as independent predictors (optimism-corrected AUC = 0.959); the derived score showed a monotonic mortality gradient accompanied by lower LE across strata (Spearman {rho} = -0.369, p = 0.004). ConclusionsThese exploratory findings are compatible with nonlinear LV mass remodeling in Chagas disease and the association between loss of dynamic complexity and mortality. Replication in larger cohorts, formal model comparisons, and prospective validation of the score are warranted. Nonstandard Abbreviations and AcronymsASE, American Society of Echocardiography; AUC, area under the receiver operating characteristic curve; CCC, chronic Chagas cardiomyopathy; CHF, congestive heart failure; CI, confidence interval; EF, ejection fraction; HRV, heart rate variability; IQR, interquartile range; IVS, interventricular septum; LA, left atrial; LAHB, left anterior hemiblock; LBBB, left bundle branch block; LE, Lyapunov exponent; LV, left ventricular; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; NSVT, nonsustained ventricular tachycardia; NYHA, New York Heart Association; OR, odds ratio; PSVT, paroxysmal supraventricular tachycardia; PVC, premature ventricular complex; PW, posterior wall; RBBB, right bundle branch block; ROC, receiver operating characteristic; SAECG, signal-averaged electrocardiogram; SD, standard deviation; SDNN, standard deviation of normal-to-normal intervals; SEM, standard error of the mean; SVE, supraventricular ectopy

Individuals with autism spectrum disorder (ASD) often exhibit atypical auditory processing, yet it remains unclear whether and how the integration of simple acoustic features and contextual information is impacted in ASD. One real-world example of this integration is the auditory looming bias, the prioritized processing and perception of approaching auditory stimuli. We designed a paradigm that presents intensity-rising (looming) and intensity-falling (receding) auditory stimuli to 3-4-year-old children with ASD (n = 21), children with sensory processing concerns who do not have ASD (SPC; n = 16) and children with typical development (TD; n = 30). We recorded neural responses using electroencephalography (EEG) and found evidence of looming bias in the SPC and TD groups, as indexed by greater P1 peak amplitude during the looming than receding stimuli (TD: t(64) = 6.87, p < .001; SPC: t(64) = 4.07, p < .001). But this finding was not present in the ASD group (p = .194). Additionally, the ASD group showed reduced differentiation between looming and receding stimuli, as indicated by significantly lower Rise-Fall Difference Score (RFDS) in comparison to the TD group (Z = -3.00, padj = .008). These findings suggested altered context-dependent modulation of sensory input in ASD.

Background: Rett Syndrome (RTT) is a severe neurodevelopmental disorder affecting approximately 1 in 10,000 live female births worldwide. The Rett Syndrome Behaviour Questionnaire (RSBQ), remains one of the most widely used standardized behavioral assessment tools for RTT. However, the RSBQ was originally validated only in British English, limiting its applicability for Spanish-speaking caregivers and clinical centers across Latin America and Spain. Objective: The primary aim of this study was to develop and validate the comprehension of the Spanish translation of the RSBQ to ensure cultural and linguistic equivalence, enhance data reliability, and facilitate earlier, more accurate clinical assessments among Spanish-speaking RTT populations. Methods: Surveys were administered in two phases to Spanish-speaking caregivers between November 2023 and September 2025. Phase I consisted of 12 guided survey administrations with participants being able to ask clarifying questions and offer linguistic modifications of RSBQ questions. Phase II consisted of independent online administration of the refined Spanish RSBQ and a retest at least 7 days later. Participants were recruited through direct outreach and supported virtually during questionnaire completion. Results: Following data cleaning and quality control, a total of 51 caregivers successfully completed both surveys. The Spanish RSBQ demonstrated high caregiver comprehension and strong engagement across multiple Latin American countries, including Argentina, Mexico, and Peru. Responses were highly correlated between test and retest timepoints, and no question showed biased response distributions. A slight effect of response interval on test-retest correlation was observed, potentially indicating the impact of natural disease progression confounding retest evaluation for long (>80 day) intervals; however this effect did not impact the overall linguistic validation results as analysis of only <21 day test-retest responders confirmed the findings. Conclusions: This linguistic validation study represents the first formal step toward the clinical validation of the Spanish RSBQ, enabling broader inclusion of Spanish-speaking populations in RTT research. The collaborative, bilingual data collection strategy proved both feasible and effective, paving the way for multinational trials and expanding therapeutic accessibility through localized, patient-centered innovation.

BackgroundAlthough neurogenic orthostatic hypotension (nOH) is a common and debilitating feature of multiple system atrophy (MSA), little is known about the burden of symptoms in the real world. ObjectivesTo design and conduct a cross-sectional community-based research survey targeting patients with MSA, with and without nOH. MethodsWe recruited patients with MSA to complete an anonymous online survey covering three core themes: 1) timely diagnosis, 2) nOH pharmacotherapy and refractory symptoms, and 3) confidence in physician knowledge. Responses were grouped by pre-specified diagnostic certainty levels. Relationships between symptoms, function, and pharmacotherapy were assessed using univariate and multivariate methods. ResultsWe analyzed 259 respondents with a self-reported diagnosis of MSA (age: M=64.38, SD=8.09 years; 44% female). In total, 42% also had a diagnosis nOH; 40% had symptoms highly suspicious of nOH, but no diagnosis; and 21% reported having never had their blood pressure measured in the standing position at a clinical visit. Treatment with a pressor agent was independently associated with the presence of other symptoms of autonomic failure. Each additional nOH symptom reported increased the odds of requiring pharmacotherapy by 18%. Yet, despite anti-hypotensive medication use, 97% of patients reported limitations in their ability to bathe, cook, or arise from a chair/bed with 76% needing caregiver support for refractory nOH symptoms. ConclusionsThis cross-sectional representative sample shows nOH is underrecognized and undertreated in MSA patients, leading to substantial functional limitations. It is our hope that these findings are leveraged for planning future trials and advocating for better treatments.

ObjectiveTo describe the design, feasibility, and baseline characteristics of the Migraine Impact on Neurocognitive Dynamics (MIND) study, a 30-day smartphone-based cohort for high-frequency assessment of cognition and symptoms in adults with migraine. BackgroundCognitive symptoms are an important component of migraine burden, but they are difficult to measure using single-visit testing or retrospective questionnaires. Repeated smartphone-based assessment may better capture real-world variability in cognition and symptoms. MethodsAdults meeting International Classification of Headache Disorders, 3rd edition, criteria for migraine were enrolled remotely and completed 30 days of once-daily ecological momentary assessments and mobile cognitive tasks delivered through the Mobile Monitoring of Cognitive Change platform. Baseline measures assessed demographics, migraine characteristics, disability, mood, stress, and treatment patterns. Feasibility was evaluated using enrollment, completion, and retention metrics. ResultsA total of 177 participants enrolled (mean age 38.8 {+/-} 11.9 years; 79.7% female), including 80/177 (45.2%) with chronic migraine. Across the 30-day protocol, 3688 daily assessments were completed, representing 70.8% of all possible study days, and 70.6% of participants completed at least 20 days of monitoring. Completion remained above 60% across study days. At baseline, chronic migraine was associated with greater burden than low-frequency and high-frequency episodic migraine, including higher MIDAS scores (98.6 vs. 38.7 and 70.3), more days with concentration difficulty (16.0 vs. 7.9 and 11.5), and more days with functional interference (18.5 vs. 7.6 and 13.0). ConclusionsThe MIND study demonstrates the feasibility of high-frequency smartphone-based assessment of cognition and symptoms in migraine and provides a methodological foundation for future analyses of within-person cognitive and symptom dynamics across the migraine cycle.

Disability worsening is the critical long-term outcome in multiple sclerosis, yet the Expanded Disability Status Scale incompletely captures neurological deterioration and has limited sensitivity in the short time windows of clinical trials. Composite endpoints incorporating functional measures have been proposed to address these limitations, but whether they reliably improve detection of treatment effects has not been established across trials. We conducted a post-hoc analysis of individual patient data from ten phase III randomised controlled trials (ASCEND, BRAVO, CONFIRM, DEFINE, EXPAND, INFORMS, OLYMPUS, OPERA I/II, and ORATORIO; n = 9,369), spanning relapsing-remitting and progressive multiple sclerosis. Confirmed disability worsening was defined using harmonised criteria with the msprog package and confirmed at 24 weeks. Treatment effects were estimated using Cox proportional hazards models and combined across trials in a one-stage individual patient data framework. Composite endpoints were constructed from the Expanded Disability Status Scale, the timed 25-foot walk test, and the nine-hole peg test using logical unions (OR-type), intersections (AND-type), and majority-vote structures. Sensitivity to treatment effect was quantified using Z-scores (the ratio of the pooled log-hazard ratio to its standard error) and compared to the Expanded Disability Status Scale reference using interaction tests. Event rates varied across components: the timed walk test generated the highest rates (up to 46.8%) while the nine-hole peg test generated the lowest (as low as 2.1%). OR-type composite endpoints showed weaker treatment effects than the Expanded Disability Status Scale alone, with the largest reductions in sensitivity observed for endpoints incorporating the timed walk test ({Delta}Z up to +2.26; interaction p = 0.004). These findings were confirmed across disease subtypes and were pronounced in relapsing-remitting trials, where no composite endpoint outperformed the Expanded Disability Status Scale. In progressive multiple sclerosis, the combination of the Expanded Disability Status Scale and the nine-hole peg test showed numerically stronger treatment effects ({Delta}Z = -1.65), though interaction tests did not reach statistical significance (p = 0.051). Composite endpoints do not systematically improve treatment effect detection in multiple sclerosis trials. Increased event capture driven by the timed walk test introduces noise that dilutes the treatment signal rather than amplifying it, highlighting that event rate and endpoint quality are not interchangeable. Upper limb function assessed by the nine-hole peg test provides complementary and specific information, particularly in progressive disease. The combination of global disability and upper limb measures represents a promising direction for future endpoint development in progressive multiple sclerosis trials, warranting validation.

Post-stroke cognitive recovery is difficult to predict using focal lesion characteristics alone. The brain's capacity to maintain cognitive function depends also on structural integrity of the whole brain. One way to measure brain health is through the severity of cerebral small vessel disease (CSVD) markers, which reflect aging-related pathologies that erode structural integrity. Here, we propose a composite measure of CSVD (cCSVD) integrating three independently validated biomarkers automatically quantified using T1-weighted MRIs: white matter hyperintensity volume (WMH; representing vascular injury), perivascular space count (PVS; putative glymphatic clearance), and brain-predicted age difference (brain-PAD; structural atrophy). We hypothesize that cCSVD, which captures the shared variance across these CSVD biomarkers, will be a robust indicator of whole-brain structural integrity and predict cognitive changes 3 months after stroke. We analyzed 65 early subacute stroke survivors with assessments within 21 days (baseline) and at 90 days (follow-up) post-stroke. WMH volume, PVS count, and brain-PAD were quantified from baseline T1-weighted MRIs, and then residualized for age, sex, days since stroke, and intracranial volume. Principal component analysis (PCA) of the residualized biomarkers was used to derive cCSVD. Beta regression with stability selection using LASSO was used to model three outcomes: baseline Montreal Cognitive Assessment (MoCA) scores, follow-up MoCA scores, and longitudinal change (follow-up score adjusted for baseline score). Logistic regression was used to test if baseline cCSVD predicted improvement in those with baseline cognitive impairment (MoCA < 26). The PCA revealed that the first principal component (PC1) explained 43.1% of the total variance among WMH volume, PVS count, and brain-PAD. The three biomarkers contributed nearly equally to PC1, which was subsequently used as the baseline cCSVD score. Lower baseline cCSVD was significantly associated with better MoCA scores at follow-up ({beta} = -0.19, p = 0.009), even after adjusting for baseline MoCA ({beta} = -0.12, p = 0.042), and, importantly, outperformed all individual biomarkers. Furthermore, lower cCSVD at baseline significantly increased the likelihood of improving to cognitively unimpaired status at three months (OR = 0.34, p = 0.036), independent of age and education. The composite CSVD captures the additive impact of vascular injury, glymphatic dysfunction, and structural atrophy on recovery in a way that individual measures do not. cCSVD accounts for shared variance across these domains, reflecting a patient's latent capacity for cognitive recovery, where relative integrity in one CSVD domain may mitigate effects of another. This automated, T1-based framework offers a scalable tool for predicting post-stroke recovery.

BackgroundAccelerated long-term forgetting (ALF), defined as an increased rate of memory loss over extended intervals, has so far been detected in a pilot study of patients with mild multiple sclerosis (MS). This study aimed to (I) confirm the presence of ALF in a larger, heterogeneous MS sample, (II) explore associations with patient-reported outcomes, and (III) assess the diagnostic performance of ALF tests for subjective memory impairment. MethodsThis study compared 62 MS patients and 65 age-, sex-, and education-matched healthy controls using standardized memory tests (RAVLT, WMS-IV Logical Memory subtest). Recall was assessed immediately, after 30 minutes, and after 7 days. Seven-day/30-minute recall ratios (QRAVLT, QWMS) served as primary outcomes. Self-report measures included memory complaints, fatigue, depression, and sleep disturbances. Linear regression and Receiver operating characteristic (ROC) analyses assessed predictors and diagnostic accuracy. ResultsALF was observed in multiple sclerosis since QRAVLT was lower in patients than in controls (0.64 [95% CI 0.59-0.69] vs. 0.78 [0.73-0.82], p < 0.001), as was QWMS (0.79 [95% CI 0.74-0.84] vs. 0.95 [0.90-1.00], p < 0.001), despite comparable initial learning. Greater fatigue, higher memory complaints, longer disease duration, older age, and greater disability were associated with lower ALF scores. The combined ALF score moderately discriminated subjective memory impairment (AUC 0.74; sensitivity 0.73; specificity 0.73). ConclusionMS patients showed ALF despite normal initial learning, indicating a specific memory deficit undetected by standard tests. Long-delay recall using RAVLT and WMS-IV Logical Memory subtest may improve cognitive impairment detection in MS.

ObjectivePathological beta-band oscillations (13 to 30 Hz) in the subthalamic nucleus (STN) are a hallmark of Parkinsons disease and a primary target for deep brain stimulation therapy, yet the specific pattern of synaptic reorganization that drives their emergence remains incompletely understood. We developed a GPU-accelerated computational framework to systematically investigate combinations of synaptic changes across basal ganglia pathways that produce Parkinsonian beta oscillations while satisfying literature-based electrophysiology constraints. ApproachWe implemented a biophysically detailed spiking network model of the STN, external globus pallidus (GPe), and internal globus pallidus (GPi) in JAX (a high-performance numerical computing Python library), achieving a 490-fold speedup over conventional CPU-based simulation. Using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) we optimized 10 network parameters across two stages: first establishing a healthy baseline matching primate electrophysiology data, then searching within biologically motivated bounds for synaptic modifications that reproduce Parkinsonian firing rates and beta power. Fixed in-degree connectivity ensured optimized parameters produced scale-invariant dynamics from 450 to 45000 neurons. All simulations ran on a single cloud GPU instance at 84 cents per hour. Main ResultsThe optimizer converged on a coordinated pattern of synaptic reorganization dominated by asymmetric changes within the STN-GPe reciprocal loop: STN to GPe excitation increased 2.21-fold while GPe to STN inhibition collapsed to 0.11-fold of its healthy value. STN to GPi and GPe to GPi pathways changed minimally (1.06-fold and 1.45-fold respectively). This configuration transformed asynchronous firing (beta: 0.4 percent of spectral power) into synchronized bursting with prominent beta oscillations (49.4 percent), with firing rate changes matching experimental observations. Network dynamics were invariant across a 100-fold range of network sizes (firing rate deviation less than 2.4 Hz; all metrics p less than 0.001 across 10 random seeds at 45000 neurons). We implemented a simplified deep brain stimulation model for validation purposes, which achieved complete beta suppression (49.4 percent to 0.0 percent) and restored GPi output to healthy levels. SignificanceThese results suggest that pathological beta oscillations emerge from a specific pattern of synaptic reorganization, namely the reduction of GPe inhibitory feedback to STN. The GPU-accelerated optimization framework, running on commodity cloud infrastructure, demonstrates an accessible platform for parameter exploration in neural circuit models and a foundation for generating synthetic training data for adaptive deep brain stimulation algorithms.

Chronotype reflects individual circadian preference for timing of sleep, wakefulness, and peak performance and has been linked to variability in prefrontal cognitive function across the day. Whether chronotype independently relates to dual-task gait cost (DTC) and whether this relationship differs by cognitive task domain is unclear. Sixty-nine healthy young adults (37 female; mean age 21.3 years) completed the Morningness-Eveningness Questionnaire (MEQ). Spatiotemporal gait parameters were recorded with three-dimensional motion capture during single-task walking and three dual-task conditions: backward word spelling (5LWB; phonological), serial subtraction by seven (SS7; arithmetic), and reverse month recitation (RMR; sequential). DTC was calculated for eight gait parameters. Condition differences were assessed with nonparametric tests and post-hoc comparisons. Multiple linear regression, adjusting for age, sex, BMI, and baseline gait velocity, tested the independent association between MEQ score and mean velocity DTC; exploratory Spearman correlations examined other parameters. SS7 produced the largest mean velocity DTC (-12.76%), significantly greater than 5LWB (-7.95%; p = 0.002) and RMR (-9.57%; p = 0.021). MEQ score independently predicted mean velocity DTC in 5LWB ({beta} = -0.51, p < 0.001, R{superscript 2} = 0.269) and RMR ({beta} = -0.55, p = 0.004, R{superscript 2} = 0.222), indicating greater morningness associated with better gait-speed preservation under cognitive load; the SS7 association was not significant ({beta} = -0.33, p = 0.071). Exploratory correlations showed MEQ-DTC associations across 7/8 parameters in 5LWB, 4/8 in RMR, and 3/8 in SS7. Chronotype is independently associated with dual-task gait cost in a task-domain-specific manner, with stronger effects for phonological and sequential tasks than for arithmetic processing. The SS7 condition yielded the largest interference but weakest chronotype modulation, suggesting arithmetic dual-task disruption may be less sensitive to circadian arousal. Fixed testing time and cross-sectional design warrant within-subject, multi-timepoint studies to confirm chronotype effects separate from time-of-day confounds.