Brain Communications

Lesion anatomy has been widely used to study post stroke cognitive outcomes, but it is unclear whether lesion-based measures provide clinically meaningful prognostic information beyond established predictors. Stroke survivors (n = 408) completed the Oxford Cognitive Screen (OCS) during acute hospitalisation and at chronic (6-month) follow-up. Lesion characteristics and structural disconnection profiles associated with chronic OCS scores were identified using ROI-level, voxel-level and structural network disconnection lesion mapping approaches. The incremental predictive value of these measures, relative to acute behaviour and pre-morbid brain health, was evaluated using regression analyses, receiver operating curve (ROC) and support vector regression (SVR) models predicting continuous chronic scores. Significant lesion and disconnection correlates of chronic cognitive impairment were identified for 9/10 OCS subtests. The extent of damage to these correlates was significantly associated with chronic cognitive scores, but their diagnostic utility for identifying persistent impairment was low under conventional thresholds (AUC mean = 0.59, range= 0.46-0.66). Acute cognitive task performance was the single best predictor of chronic cognition (AUC mean = 0.66, range = 0.4-0.95). In multivariate analyses, SVR models trained on acute cognitive performance and regional atrophy severity scores both outperformed models trained on lesion anatomy or structural disconnection across most cognitive domains. SVR models combining anatomical, disconnection and behavioural predictors did not improve predictions accuracy relative to behaviour or atrophy-only models. Together, these findings demonstrate that statistically significant lesion-outcome relationships do not necessarily translate into clinically useful prognostic indicators. In a large, clinically representative stroke cohort, detailed lesion-based measures provided limited incremental prognostic value beyond acute cognitive assessment and coarse brain health markers. These results highlight the importance of explicitly evaluating predictive utility when developing prognostic models for post-stroke cognitive outcomes.

BACKGROUND: Dementia with Lewy bodies shares clinical and pathological features with both Parkinson's disease and Alzheimer's disease, but the local biological factors that render specific cortical regions vulnerable to atrophy remain poorly defined. In particular, it is unclear whether cortical thinning in dementia with Lewy bodies reflects generic neurodegenerative mechanisms, processes shared with Parkinson's disease and Alzheimer's disease, or dementia with Lewy bodies-specific molecular and network susceptibilities. METHODS: A total of 89 patients with dementia with Lewy bodies and 89 matched controls underwent T1-weighted brain MRI. Scans were processed to generate surface-based cortical thickness maps. Regional cortical thickness estimates, after slice-by-slice manual correction, were mapped to gene expression data from healthy postmortem human brains to identify transcriptomic signatures associated with decreased thickness in dementia with Lewy bodies. We assessed whether genes whose expression was increased with regional thinning converged onto established Parkinson's disease- and Alzheimer's disease-related pathways and isolated genes uniquely implicated in dementia with Lewy bodies. Spatial annotation mapping was then used to test whether patterns of cortical thinning overlapped with in vivo neurotransmitter system distributions and whether the observed thickness pattern was constrained by large-scale structural connectivity, consistent with a network-based propagation process. RESULTS: Cortical thinning predominated in regions that, in the healthy brain, show higher expression of genes involved in mitochondrial function and synaptic transmission. The transcriptomic profile associated with thinning significantly overlapped with genes belonging to Parkinson's disease and Alzheimer's disease pathways, supporting shared pathogenic mechanisms across Lewy body and Alzheimer-type neurodegeneration. However, 90 genes associated with cortical thinning did not overlap with Parkinson's disease or Alzheimer's disease pathways and were enriched for GABAergic signalling. Spatial mapping analyses showed that regions with greatest thickness reductions colocalized with GABAA, serotoninergic 5-HT1A, 5-HT1B, 5-HT4, and dopaminergic D2 receptor distributions, and that the thickness pattern followed structural connectivity. CONCLUSIONS: MRI-derived cortical thickness changes in dementia with Lewy bodies reflect selective molecular and network vulnerabilities rather than a non-specific degenerative process. Mitochondrial and synaptic genes, together with a distinct GABAergic association and connectivity constraints, delineate mechanisms explaining why some cortical territories are more affected in dementia with Lewy bodies.

Repurposed noradrenergic drugs have been proposed to treat neuropsychiatric symptoms in Parkinsons disease and related conditions. While there is evidence that these drugs can be beneficial for cognition in selected patients, questions remain about their cardiovascular effects. Here we tested whether heart rate variability (HRV) is altered in people with Parkinsons disease, following a single-dose challenge with the noradrenaline reuptake inhibitor atomoxetine (40 mg, oral). Consistent with previous work, our cohort of people with idiopathic Parkinsons disease (n=15) had lower HRV than healthy controls (n=22). Decreased HRV in people with Parkinsons disease was associated with reduced integrity of the caudal locus coeruleus, measured using neuromelanin-sensitive ultra-high field 7T magnetic resonance imaging. Following a randomised double-blind placebo-controlled crossover challenge in the Parkinsons disease group, short-term resting HRV was not significantly altered following atomoxetine. Using Bayesian statistical inference, we demonstrated confidence in the preservation of HRV across measures in the time, frequency, and non-linear domains. Our findings are in favour of a safe cardiovascular profile for atomoxetine in Parkinsons disease, further supporting noradrenergic modulation as a viable treatment strategy for neuropsychiatric symptoms in Parkinsons disease and related disorders.

The mechanisms of aphasia recovery following left-hemisphere stroke remain debated. Two broad hypotheses have been proposed for how recovery occurs when specialized systems, such as the language system, are affected by brain damage: i) recovery depends on the remaining components of the language system; and ii) recovery depends on functional remapping in brain areas outside of the language system. A key candidate for such takeover of language function is the Multiple Demand (MD) system--an extensive bilateral network that supports executive functions and is associated with the ability to flexibly adapt to task goals. The theoretical premise is that this system is capable of a wide range of cognitive tasks and can potentially be repurposed for language when specialized resources are no longer sufficient. We used precision functional MRI to evaluate these two hypotheses about aphasia recovery in 37 individuals (mean age = 58.3, SD = 8.4) with chronic aphasia due to a single left-hemisphere stroke, along with 38 age-matched controls (mean age = 61.6, SD = 9.2). Participants performed extensively validated functional localizers to identify the language network and the MD network within individuals. Participants with aphasia additionally completed extensive behavioral assessments that evaluated linguistic and executive skills. We first examined responses during language processing--audio-visual speech comprehension and reading--in each of the two networks, and then we related activity and functional connectivity measures from the two networks to linguistic ability. Our results do not support the hypothesis of drastic reorganization of the language system in the form of co-opting parts of the MD system in chronic aphasia. First, the language network and the MD network remain robustly dissociated: the language network responds strongly and selectively to language across modalities (left-hemisphere language regions: pFDR < 0.003), and no MD region shows increased activation during language comprehension relative to controls (pFDR > 0.24). Second, functional connectivity analyses reveal no evidence for increased integration between the two networks during language processing. Third, linguistic ability, as measured by an extensive behavioral battery of tests, is associated with the strength of activity and functional connectivity within the language network, but not within the MD network. Although we cannot rule out a role for the MD network in aphasia recovery during the acute and subacute phases or in more severely impaired patients, it appears that during the chronic phase, language comprehension relies on the same specialized network as prior to the injury.

Background and Objectives: Converging evidence hints at neurodevelopmental effects in genetic frontotemporal degeneration (FTD). In cross-sectional studies, for some genes, young adult FTD variant carriers show differences in brain volumes and cognition compared to familial non-carriers. However, longitudinal trajectories may more sensitively capture FTD-related neurodevelopmental vs. neurodegenerative changes than cross-sectional approaches. This study examined longitudinal trajectories of brain volumes, executive function, and plasma biomarkers in young adult carriers compared to familial non-carriers, as measures of neurodevelopmental and neurodegenerative outcomes of FTD-causing variants. Methods: This longitudinal cohort study comprised participants, aged 18-30 years, from the FTD Prevention Initiative across Europe, Canada, and the USA. Genetic groups included C9orf72 (47%), MAPT (30%), and GRN (23%). Linear mixed-effects models were computed to assess longitudinal outcomes across age between groups, controlling for sex, scanner (for brain volumes), and education (for executive function); random effects accounted for between-subject variability nested within family membership. Results: Variant carriers (n=147) and familial non-carriers (n=113) did not differ in age (mean{+/-}SD, 25.9{+/-}3.2 years), sex (53% female), or number of visits (2.1{+/-}1.7). Young adult C9orf72 repeat expansion carriers exhibited smaller thalamic volumes than non-carriers at the reference age of 26 years (b=-982.8mm3, SE=317.0, p=0.0046, f2=0.32), with relatively stable trajectories across ages 18-30 (i.e., no change over time). Trajectories of rostral anterior cingulate volumes differed in C9orf72 carriers and non-carriers across age, where carriers showed relatively stable trajectories and non-carriers showed age-appropriate declines (b=64.4mm3, SE=29.9, p=0.035, f2=0.07). For MAPT and GRN, there were little to no differences in total brain, cortical, or subcortical volumes between groups and over time. No longitudinal differences were observed between carriers and non-carriers in executive function, or plasma NfL or GFAP for any genetic group. Discussion: C9orf72 repeat expansions were linked to smaller average thalamic volumes and stable trajectories between ages 18 to 30, supporting potential neurodevelopmental origins. The modest evidence supporting an absence of difference in neurodegenerative biomarkers and executive function suggests minimal early neurodegeneration and functional preservation in young adulthood.

Cerebellar ataxias are a rare group of disorders manifesting with motor incoordination and cognitive-affective deficits of variable severity. Although neurogenetic has revealed multiple mutations, the study of ataxias still relies on clinical evaluation, while the underlying neural network changes remain unclear. It has been argued that the less severe symptoms in congenital (like Joubert syndrome, JS) than in slowly progressive (SP) ataxias reflect a different interplay of alteration and compensation but direct evidence is still lacking. Moreover, it is unclear why, in front of a wide heterogeneity of molecular alterations, SPs show common clinical symptoms. To address these questions, we created brain digital twins for each participant by combining volumetry, graph theory analysis of structural and functional connectivity, and dynamical simulations using the virtual brain. We studied 8 JS (3 females, 21{+/-}6years), 8 SP (3 females, 20{+/-}5years) and 11 healthy controls (HC; 5 females, 21{+/-}2years).Volumetry quantified atrophy, graph metrics (centrality, segregation and integration) characterized topology, and neural dynamical simulations estimated excitation/inhibition balance, providing anatomo-physiological parameters within the somatomotor (SMN) and ventral attention (VAN) networks. Anatomo-physiological parameters were correlated with clinical/neuropsychological scores, and unsupervised clustering was applied to assess whether network features can discriminate between JS and SP beyond clinical classification. MRI morphometry confirmed selective vermis reduction in JS and a widespread cerebellar atrophy in SP compared to HC. In both ataxia groups, SMN and VAN showed reduced volume and structural connectivity but with different patterns of topological and dynamical alterations. In the SMN of SP, reduced centrality and excitation/inhibition balance depressed information transfer through the network. In the VAN of JS, reduced centrality, segregation, and integration, were detrimental but coexisted with a higher number of functional core nodes and an increased large-scale excitatory coupling, supporting compensatory reorganisation in extracerebellar nodes. Clustering confirmed that SMN better differentiates SP, whereas VAN better clusters JS. Importantly, anatomo-physiological parameters of network volume, topology, and dynamics correlated with patients motor and cognitive performance. In conclusion, primary cerebellar damage secondarily impacts large-scale brain networks, altered in both ataxia groups but compensated only in JS. Similar clinical symptoms in SP reflects the similarity of network changes, while differential involvement of SMN and VAN in JS and SP reflects the connectivity pattern of the lesioned areas inside these large-scale brain circuits. Importantly, anatomo-physiological parameters are sufficient to explain individual motor and cognitive performance, offering a basis for improved patient profiling and personalized therapies.

ObjectivePostoperative pain outcomes following spinal fusion surgery remain difficult to predict, as structural and surgical indicators alone offer limited insight into who will experience meaningful relief. A substantial proportion of patients continue to report persistent pain after surgery, underscoring the need for objective markers that can help identify those at risk of poor recovery. Peak alpha frequency (PAF) has emerged as a promising trait-like neural signature of pain sensitivity in experimental models, where individuals with slower PAF tend to exhibit heightened pain sensitivity. Yet despite this link, its ability to forecast longer-term postoperative pain trajectories remains unclear. MethodsSeventeen adults undergoing cervical or lumbar fusion surgery were included. Resting-state, eyes-closed EEG was recorded preoperatively and at multiple visits after surgery. PAF was extracted from central electrodes using the centre-of-mass method. Pain intensity was assessed longitudinally on standardised self-report pain scales. Associations between PAF measures and postoperative pain change were examined using correlation analyses, and receiver operating characteristic (ROC) analyses evaluated discrimination of pain responders ([&ge;]50% improvement). ResultsPreoperative peak alpha frequency (PAF) was positively associated with longer-term pain reduction at the 3-month follow-up, but showed no consistent relationship with early postoperative pain. Across pain measures, a consistent pattern emerged across the Brief Pain Inventory (BPI), visual analogue scale (VAS), and numerical rating scale (NRS), but not the verbal rating scale (VRS) or Short-Form McGill (SF-MPQ). At the 3-month follow-up, associations reached statistical significance for BPI-Worst ({rho} = 0.67, p = 0.017), and BPI-Average Pain ({rho} = 0.62, p = 0.033). VAS and NRS showed moderate-to-strong effects that approached significance in non-parametric analyses and were significant for VAS when treated as an approximately interval measure (Pearson r = 0.63, p = 0.022). ROC analyses using BPI-Worst pain improvement demonstrated good discriminative ability of preoperative PAF for identifying treatment responders at 3 months (AUC = 0.84; 95% CI: 0.61-1.00), with high specificity and moderate sensitivity at the Youden-optimal threshold of 10.11 Hz. By contrast, changes in PAF over time were not reliably related to changes in pain scores, suggesting that PAF functions more as a stable, trait-like predictor than a dynamic biomarker in this context. ConclusionThis study demonstrates the feasibility and potential clinical value of preoperative EEG for characterising individual differences in postoperative pain recovery following spinal fusion. The results identify faster preoperative PAF as a stable neural signal that captures meaningful variability in longer-term pain reduction, with convergent support across multiple patient-reported measures. While replication in a larger cohort is required, these findings establish a clear foundation for evaluating PAF as a candidate neurophysiological marker to inform preoperative risk profiling and potentially personalised perioperative pain-management strategies in spinal fusion patients.

BackgroundFunctional motor disorder (FMD) is a common and disabling condition with incompletely understood pathophysiology. Eye-tracking offers a method to objectively examine cognitive and motor control processes and their underlying neural pathways. We aimed to quantify saccade, blink and pupil responses in FMD and healthy controls performing an interleaved pro-/anti-saccade task, and to investigate the relationships between oculomotor measures and motor and non-motor symptom severity. MethodsWe conducted video-based eye-tracking in 104 patients with clinically definite FMD and 115 age- and sex-matched healthy controls performing the saccade task. Patients completed questionnaires on depressive, pain-related, dissociative, non-motor somatic symptoms. Clinician-rated motor severity and centrally acting medication was recorded in FMD patients. ResultsCompared to controls, FMD patients showed increased anti-saccade error rates (p < 0.001), anticipatory saccades (p [&le;] 0.003), altered blink distribution (p < 0.001), and reduced pupil dilation velocity (p < 0.001). However, reduced pupil dilation velocity was not significant in subsample of unmedicated patients. Higher anti-saccade error rates were significantly associated with depressive symptoms, pain severity, dissociative symptoms, non-motor somatic symptom burden, and motor severity (all p < 0.05). ConclusionsWe hypothesize that the altered saccade and blink responses result from altered processing in the frontal cortex and basal ganglia which provide critical input to brainstem oculomotor control areas in FMD. These results support neurobiological models proposing altered predictive and attentional processing underlying FMD. Association between oculomotor measures and symptom severity suggests that specific cognitive abnormalities may play a role in the pathophysiology of these symptoms in FMD. WHAT IS ALREADY KNOWN ON THIS TOPICFMD is increasingly interpreted through predictive coding models suggesting abnormalities in predictions about motor and sensory states driven by abnormally focused attention. Yet the underlying neurobiology remains poorly defined. Empirical studies directly probing basic predictive processes in FMD are scarce, and implicit cognitive-motor interactions, particularly those involving motor learning and adaptation, have been insufficiently explored. WHAT THIS STUDY ADDSOnly two previous studies have used eye-tracking in FMD, focusing mainly on diagnostic saccadic markers. Using time-series analyses of saccadic, blink, and pupillary data, we show abnormalities in inhibitory control, predictive processing, and implicit learning. Due to strong homology between human and primate neurophysiology and neuroimaging findings in oculomotor control, the findings can be linked to dysfunction within cortico-basal ganglia circuits. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYOculomotor abnormalities correlated with motor and non-motor symptom severity, indicating mechanistic relevance. The findings provide empirical support for predictive coding accounts and point to involvement of subcortical structures including projections from the frontal cortex to the basal ganglia. This highlights the value of studying cortico-basal ganglia circuits with implications for treatment and of developing oculomotor measures as potential biomarkers in FMD.

Background: Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a genetic disease characterized by spasticity and ataxia which reflects involvement of the corticospinal tracts (CST) and cerebellum. The primary involvement of the middle cerebellar peduncles (MCP) and transverse pontine fibers (TPF) at the crossing with the CST, and their role in the pathophysiology of the disease, is currently debated. Objectives: Advanced MRI techniques capable of isolating sub-voxel microstructural parameters can test the hypothesis that the MCP and TPF are abnormally large, compressing the CST at their crossing, and potentially impairing CST development. Methods: Tract macro- and micro-structural properties, including axon and tract caliber, axon density and geometry, and myelin content were estimated from diffusion-relaxometry and magnetization transfer imaging. These features were analyzed along segments of the CST, MCP, and TPF of 9 patients and 9 age-matched controls. Results: While the CST showed significant decreases in tract size, axon caliber, and myelination throughout its length compared to controls (p<0.01), the MCP and TPF were relatively unaffected. In our group, neither the MCP nor the pons were enlarged. The proximal MCP showed an increase in axon caliber. Conclusions: The increase in fractional anisotropy and axon density towards the center of the TPF could be driven by geometric confounds related to differences in the relative sizes of the CST and TPF compared to controls. This highlights the importance of investigating tract-specific microstructural profiles, particularly in regions of geometric complexity. The findings confirm the involvement of the CST, with a relatively limited involvement of the MCP and TPF.

Rationale: Reliable electroencephalography (EEG) biomarkers of cortical excitability could improve diagnosis and longitudinal monitoring in epilepsy, yet it remains unclear which metrics best balance sensitivity across individuals with intra-individual stability over time. Methods: We analyzed scalp EEG recordings from the open-access Temple University Hospital EEG Epilepsy Corpus, comprising 1,404 recordings from 96 individuals with neurologist-confirmed epilepsy and 85 healthy controls across multiple sessions. Eight global measures were computed: aperiodic exponent and offset, sample entropy, detrended fluctuation analysis exponent and derived index, spatial gamma-band phase consistency, and absolute and relative alpha power. Group differences were assessed by permutation tests with false discovery rate correction at recording, session, and subject levels. Associations with antiseizure medication burden, temporal stability, and cross-metric correlation structure were evaluated as secondary analyses. Results: Aperiodic parameters showed the most robust case-control separation, remaining significant after subject-level averaging (exponent: median difference = 0.20, q = 0.010; offset: median difference = 0.25, q = 0.011). Entropy and alpha power distinguished groups at the recording and session levels, while gamma-band phase consistency was significant at the session level only; none of these survived subject-level averaging, suggesting greater state-dependency. Higher medication burden was associated with reductions in alpha power and detrended fluctuation analysis, and adjusting for it substantially attenuated group differences, though residual effects in the aperiodic exponent persisted. Cross-metric correlation structure was preserved between groups but modestly reorganized by medication burden. Conclusions: Aperiodic spectral parameters are the most robust EEG markers of epilepsy, reflecting stable trait-like network properties. Complexity and synchrony measures capture complementary, state-sensitive dimensions. Medication burden substantially influences multiple metrics, underscoring the need to account for pharmacological effects when interpreting EEG biomarkers in epilepsy.

Background and ObjectivesFunctional neurological disorder (FND) is one of the most common causes of neurological symptoms and disability, but much remains unknown about its pathophysiology. In both clinical conversations and research publications, clinicians and researchers imply a variety of models for onset of the condition with respect to both the process culminating in its onset, and the distribution of susceptibility to the condition across the population. Here we used population-level data as evidence to arbitrate between these generative models of the condition. MethodsWe identified six hazard distributions corresponding to different pathophysiological processes, and four distributions of population susceptibility, as the assumptions underlying the range of plausible generative models resulting in the observed distribution of age of onset of FND. We combined these model families into 24 parametric proportional hazards models, and fitted each to the observed distribution of reported age at onset in two large FND datasets, one for functional movement disorders (FMD) and one for functional seizures (FS). Out-of-sample predictive accuracy for these models was compared using Bayesian model comparison. ResultsStrong trends were seen across model families with different distributions of population susceptibility to FND. For both datasets, the best-fitting model family overall was the mixture-cure family, which represents susceptibility as binary, with a susceptible and an unsusceptible proportion of the population. For the FMD dataset, some models in the log-normal frailty family had comparable fits to the mixture-cure models, and for the FS dataset, a number of the gamma frailty family had comparable fits. The variance parameters for each of these frailty distributions were so large as to imply binary risk, approximating mixture-cure models. Models with exponential hazard distributions--which correspond to a generative process where a single trigger in a susceptible person brings about the condition--were universally poor fits for the observed data. Other hazard distributions were insufficiently distinguished by their out-of-sample predictive accuracy to make further inference as to the underlying process resulting in onset of FND in susceptible individuals. InterpretationOur results suggest that susceptibility to FND is approximately binary, with the susceptible proportion of the population extremely likely to develop FND in their lifetime. The results also argue strongly against a generative model where a single trigger is sufficient to cause the onset of FND in a susceptible person.

High placebo response is an obstacle in developing drugs to treat agitation in Alzheimer's disease (AAD), a prevalent and burdensome symptom. However, it has proved challenging to develop actionable models of placebo response that 1) can be applied prospectively, requiring only information available at screening or baseline, 2) yield strategies for reducing placebo response without equally depressing drug response, and 3) show generalizability across trials. Here, we first investigated placebo response in AAD at the trial level using meta-regression applied to 23 clinical trials. Meta-regression identified several factors associated with increased placebo response, but most of these factors were non-specific such that they predicted improvements in drug response as well. We therefore turned to individual level clinical trial datasets and applied causal modeling to predict which participants would have high placebo response relative to predicted drug response. We successfully built and validated the causal model across two independent clinical trials of risperidone and haloperidol at the level of individual patients (ability to predict subsequent improvement on drug or placebo). Crucially, we also found efficacy improvements in the overall trial through in silico exclusion/screen failing of high placebo-predicted subjects. We further characterized features most associated with placebo response to improve explainability and, lastly, validated the effect of these features at the trial level in clinical trials of galantamine, an acetylcholinesterase inhibitor (hence in a different class of drugs than those in the other two trials used). Taken together, we have developed and applied a causal modeling framework for reducing placebo response and increasing trial-level efficacy in neuropsychiatry clinical trials using historical trial datasets.

Background: Anomia is common in frontotemporal dementia (FTD), although its clinical prominence varies by subtype, with the most marked impairment typically observed in primary progressive aphasia (PPA). It remains unclear whether naming impairment reflects language-specific impairment or broader cognitive severity, and how it relates to other cognitive domains across FTD syndromes. Methods: Fifteen healthy controls and twenty-two individuals across the FTD spectrum, including variant-specified and unclassifiable (NOS) presentations, completed two confrontation naming tasks (Boston Naming Test and Multilingual Naming Test) and a global cognitive screening measure (Montreal Cognitive Assessment, MoCA). Patient participants additionally completed a standardized language battery (Western Aphasia Battery Revised) and a comprehensive neuropsychological assessment (Uniform Data Set). Naming performance was compared between groups and associations with language severity, global cognition, and domain-specific cognitive functions were examined using regression analyses. Results: Naming was impaired in patients relative to healthy controls but did not differ between patient groups. Naming was strongly associated with language severity, but not global cognition. A significant group-by-MoCA interaction indicated that MoCA was positively associated with naming only in the unclassifiable group. In addition, naming was associated with episodic memory across both verbal and non-verbal domains. Conclusions: Naming in FTD primarily reflects language severity rather than global cognitive impairment. A robust association between naming and episodic memory suggests potential contributions from semantic cognition, shared frontally mediated retrieval processes, or parallel cognitive decline. These findings support the use of naming as a marker of language dysfunction while highlighting its relevance to broader cognitive systems in FTD.

The temporal coupling between cortical blood-oxygen-level-dependent (BOLD) activity and CSF inflow has recently been proposed as a non-invasive marker of glymphatic function, a brain-wide clearance system closely linked to sleep, neuromodulatory regulation and neurodegeneration. Reduced BOLD-CSF coupling has been previously reported in Parkinsons disease but its characterization in dementia with Lewy bodies, regional specificity and relevance to shared neuropsychiatric symptoms remain unclear. Using resting-state functional MRI, we quantified global and regional BOLD-CSF coupling in 39 participants, including 17 with Parkinsons disease (mean age 61.4 years), 10 with dementia with Lewy bodies (mean age 72.8 years) and 12 healthy controls (mean age 66.2 years), and examined the relationship with clinical and cognitive measures, as well as volumetric measures of the subcortical ascending arousal network. Parkinsons disease and dementia with Lewy bodies patients both demonstrated weaker global BOLD-CSF coupling compared to controls, with no detectable difference between patient groups. Coupling reductions were most pronounced within the unimodal and attentional networks, encompassing regions that are particularly vulnerable in Lewy body disease. Weaker coupling was associated with the severity of hallucinations and cognitive fluctuations, poorer nocturnal sleep quality and impaired attentional working memory, but not overall motor symptom burden. Associations between BOLD-CSF coupling and basal forebrain and brainstem volumes were observed, though partially age-dependent, suggesting a complex interaction between neuromodulatory system degeneration, ageing and brain-fluid dynamics. Our results provide preliminary evidence that disrupted temporal coordination between cerebrovascular activity and CSF inflow may contribute to the fluctuating neuropsychiatric features of Lewy body disease and highlight the utility of BOLD-CSF coupling as a dynamic in vivo proxy of glymphatic function. Replication in larger cohorts incorporating multimodal imaging and biomarkers of pathology will be essential to validate these findings and determine whether brain-fluid dysregulation represents a potentially modifiable therapeutic target.

Objective: To determine whether absolute ictal energy on intracranial EEG identifies brain regions whose epileptogenic involvement is attenuated under existing baseline-normalized, dynamic-systems, and event-based frameworks. Approach: Intracranial EEG from 56 patients (five centers; 21 SEEG, 35 ECoG) was analyzed using the Teager-Kaiser Energy Operator computed as z-scored and raw envelopes; energy-dominant network regions (EDNRs) were defined as electrodes whose raw-energy rank exceeded their z-score rank by at least 2 positions. Hilbert decomposition characterized instantaneous amplitude and frequency. Main results: EDNRs were identified in 51 of 56 patients (91%; mean 3.4). Hilbert decomposition revealed elevated baseline amplitude in EDNRs relative to both non-involved regions (p < 0.001) and potential seizure onset zones (PSOZs, the top-ranked electrodes under both metrics; p = 0.029), with EDNRs participating in seizure-frequency dynamics comparable to PSOZs (mean ictal frequency shift +3.7 versus +4.1 Hz). EDNR detectability correlated directly with electrode count (Spearman r = 0.899, p < 0.001) without plateau. Significance: Absolute ictal energy identifies an epileptogenic network component with elevated baseline amplitude attenuated under baseline-normalized metrics. The dual-metric framework defines a complementary energy-based axis and establishes the second layer of a two-layer approach with seizure onset and propagation mapping as the first layer. EDNR detectability scales with electrode count, directly relevant to SEEG implantation strategy and to network-level inferences from heterogeneously covered cohorts.

Migraine is a common and disabling neurological disorder linked to alterations in neuronal activity and waste clearance in the brain. MRI-visible perivascular spaces (PVS) are key components of the glymphatic system which may serve as imaging biomarker of such disorder. We hypothesised that higher frequency of migraine episodes would be associated with increased PVS burden, reflecting greater levels of impaired glymphatic clearance. In this retrospective case-control study of 90 participants (20 episodic migraineurs, 18 chronic migraineurs, and 52 age- and sex-matched healthy controls; 58 females, median [Q1, Q3] age=28.6 [25.1, 39.4] years) we investigated PVS alterations in episodic migraineurs (n=20) and 18 chronic migraineurs (n=18). PVS volumes and cluster counts were quantified in the white matter (WM), basal ganglia (BG), midbrain, and hippocampus. We stratified PVS metrics by white matter lobes and arterial vascular territories. After adjusting for age, sex, and total brain volume, episodic migraineurs exhibited significantly lower BG-PVS volumes (exp({beta})=0.76, 95%CI [0.61, 0.94], p=0.01) compared to controls. Chronic migraineurs exhibited significantly lower PVS cluster counts in the parietal (exp({beta})=0.8, 95%CI [0.68, 0.94], p=0.01) and temporal lobes (exp({beta})=0.72, 95%CI [0.53, 0.96], p=0.03) and middle cerebral artery territory (exp({beta})=0.82, 95%CI [0.68, 0.97], p=0.03) compared to healthy controls. Within migraineurs, those with aura (n=20) exhibited significantly lower PVS burden in all brain regions, vascular territories, and across the frontal, parietal, and temporal lobes (all pFDR<0.05). Our findings suggest that the aura symptom, rather than the migraine disorder itself, may primarily drive changes in perivascular spaces, with effects varying across brain regions.

Young onset Parkinson's disease may be caused by biallelic mutations in PRKN or other autosomal recessive Parkinson's disease genes, but the majority of patients do not carry known monogenic variants. Previous studies have found an increased cumulative burden of common genetic risk variants for Parkinson's disease in young onset patients, but the specific genetic architecture of non-monogenic young onset Parkinson's disease is not well characterized. We conducted a genome-wide association study of 1,528 Parkinson's disease patients with symptom onset between 18 and 40 years and 20,408 controls of European ancestry using data from The Global Parkinson's Genetic Program, the International Parkinson's Disease Genomics Consortium, and the NeuroGenetics Research Consortium. We performed meta-analyses of additive and recessive regression models and investigated associations between age at onset groups and different polygenic risk scores. An additive model meta-analysis identified six independent loci passing a genome-wide significance threshold, including three loci identified in previous genome-wide association studies (near SNCA, GBA1, and HIP1R) and two loci not previously associated with Parkinson's disease (rs74950462, P = 1.24e-8 and rs72848817, P = 4.89e-8). Furthermore, we identified a significant signal at the PRKN locus, prompting a follow-up analysis employing a recessive model. The recessive genome-wide association meta-analysis identified nine loci passing a genome-wide significance threshold, including SNCA, PRKN, and seven novel variants. Patients with onset between 18 and 40 years had significantly higher polygenic risk scores than later onset patients when the score was modelled specifically on genome-wide association statistics from independent young onset Parkinson's disease participants versus healthy controls. This increased polygenic burden was driven in part by loci harbouring mitochondrial pathway genes. Our results indicate that previously unidentified common and low-frequency variants contribute specifically to the young onset subgroup of Parkinson's disease. Association signals detected uniquely with a recessive model suggest that genetic susceptibility to young onset Parkinson's disease may be partially driven by homozygous variation, in line with previous reports of increased runs of homozygosity in this particular group of patients and may be consistent with a loss of function mechanism. The findings support the notion of young onset Parkinson's disease as a partly distinct subphenotype and highlight the mitochondrial pathway. These results may have implications for future precision medicine but should be interpreted with caution pending independent replication.

BackgroundFunctional neurological disorder (FND) is one of the most common, but least researched, conditions in neurology. Debate exists as to whether the clinical entity referred to as FND is truly a single disorder or is in fact multiple entities which have been erroneously amalgamated into the same condition. We sought to provide empirical evidence on this question by treating it as a problem of model comparison. MethodsWe formulated statistical models equivalent to: (1) FND being a single entity with variation in phenotype, represented by latent trait (binary factor/item response theory) models, and (2) FND being multiple discrete entities, represented by latent class analysis (LCA) models. We fitted these models to data on the symptoms experienced by 697 people with FND from the FND Research Connect database (fnd-research.org) and used Bayesian model comparison methods to compare them. ResultsAll but one of the latent trait models, representing FND as a single entity with heterogeneous phenotype, fit the data better than all the LCA models. Secondary analysis of the LCA models showed results compatible with the models capturing discretisation of continuous variation rather than true discrete categories. DiscussionOur results suggest that the symptom structure of FND is the result of a single pathophysiological process, either as a single entity, or a common pathway preceded by multiple causative processes where the common pathway is solely responsible for the phenotype of the condition.

Background and ObjectivesElectrical stimulation mapping (ESM) is the clinical gold standard for identifying eloquent cortex during presurgical evaluation but is time-intensive, constrained by incomplete cortical sampling, and limited by patient tolerance. We investigated whether features derived from electrocorticography (ECoG), including functional connectivity measures, can provide complementary information for identifying functionally critical cortex and examined how predictive performance varies across functional domains, behavioral tasks, and data quantity. MethodsFourteen patients undergoing intracranial monitoring for epilepsy surgery performed speech production tasks while ECoG was recorded independently of stimulation mapping. Graph-theoretic functional connectivity features derived from high-gamma activity (70-150 Hz), combined with anatomical region encoding, were used to train machine learning classifiers, and predictive performance was evaluated using leave-one-subject-out validation with ESM-defined functional deficits used as ground-truth outcomes. ResultsFourteen patients were included. Performance differed across functional domains, with motor-critical electrodes identified with the highest accuracy (ROC-AUC 0.929 {+/-} 0.061; PR-AUC 0.755 {+/-} 0.191), followed by speech arrest (ROC-AUC 0.793 {+/-} 0.103; PR-AUC 0.550 {+/-} 0.196), whereas language-critical electrodes were more difficult to robustly predict (ROC-AUC 0.761 {+/-} 0.160; PR-AUC 0.385 {+/-} 0.167). Additional signal-derived features provided limited benefit beyond anatomical and connectivity features. Performance also varied across tasks and with the number of available trials, with motor prediction remaining stable across trial counts and speech arrest prediction improving with increasing trial counts up to approximately 10 trials before plateauing. In addition, evaluation at the level of stimulation pairs increased sensitivity, with only modest changes in overall performance. DiscussionGraph-theoretic connectivity analysis of ECoG provides complementary information for identifying stimulation-defined functional criticality and supports presurgical mapping. Differences in predictive performance across functional domains likely reflect underlying neuro-physiologic organization, with connectivity providing the clearest improvement for speech arrest prediction. Combined-label prediction strategies increased sensitivity at the expense of specificity, reflecting a clinically relevant tradeoff between broad detection of critical cortex and precise localization. These findings suggest that connectivity-informed approaches may help guide task selection and improve mapping efficiency while complementing electrical stimulation mapping.

There is substantial interest in understanding neurological impact and recovery over time, but there is a dearth of longitudinal assessment extending from minutes to months surrounding neural system impact. We compared rare intraoperative recordings in three patients, obtained immediately before and after anterior temporal lobe (ATL) resection during a semantic prediction task, with longitudinal source-localized electroencephalography (EEG) obtained 2-6 weeks before and 2 and 6-14 months after surgery. Relative to controls (n = 20), task performance showed sustained impairment in the two left-hemisphere patients and delayed impact in the right-hemisphere patient. Consistent with theory on ipsilateral and contralateral hemisphere compensation, all three patients exhibited bilateral EEG alterations in speech responses and effective connectivity that did not recover to pre-operative levels. Direct comparison of the datasets for intrinsic neurophysiological biomarkers associated with timescales of processing ({tau}INT) and excitatory-inhibitory balance (aperiodic slope, {chi}SPEC) showed a striking months-long reduction in rapid timescale processing and gradually increasing aperiodic slope (e.g., putatively increased cortical inhibition) in the ipsilateral hemisphere of all three patients. Amidst these neurophysiological alterations, task performance did not return to pre-operative levels. These rare longitudinal patient data advance a framework to broadly evaluate neurological impact over multiple timeframes.