Brain communications最新文献

Perivascular space (PVS) dysfunction may potentially contribute to the development and progression of amyotrophic lateral sclerosis (ALS). This study investigated the clinical relevance of PVS dysfunction in ALS. Two PVS parameters were quantified in patients with ALS: (i) the enlarged perivascular space (ePVS) score and (ii) the diffusion tensor image analysis along the perivascular space (DTI-ALPS) index. These parameters were analysed in relation to the clinical, structural and prognostic features of ALS. The study included 55 patients with ALS (33 men; mean age, 61.38 ± 10.95 years). The DTI-ALPS index was markedly reduced in the patients compared to age- and gender-matched controls, and there were no differences in ePVS scores between the two groups. The ePVS total score was positively correlated with the ALS progression, as measured by the monthly change in the revised ALS functional rating scale. The ePVS basal ganglia regional score was inversely correlated with muscle strength. Additionally, both the ePVS score and the DTI-ALPS index were associated with regional grey matter volumes of the superior frontal gyrus and middle frontal gyrus, and the DTI-ALPS index was associated with diffusion parameters of the corticostriatal and corticothalamic tracts. This study underscores the importance of PVS dysfunction in ALS according to the ePVS and a reduced DTI-ALPS index, which were respectively associated with disease progression, neurological deficits, including reduced muscle strength, and cortical and subcortical structural changes.

Early stages of Alzheimer's disease are marked by brain hyperexcitability, evidenced by subclinical epileptiform features suggesting an excitation-inhibition imbalance. Clinically translatable biomarkers for early detection of excitation-inhibition changes at the network level, however, are lacking. We investigated the functional excitation-inhibition ratio, theta-gamma phase-amplitude coupling and epileptiform features in hippocampal and cortical local field potentials recorded weekly in freely behaving male APPswe/PS1dE9 (APP/PS1) mice (n = 10) and wild-type controls (n = 10) between 3 and up to and including 11 months of age. APP/PS1 mice exhibited a shift towards increased excitation, reflected in the elevated functional excitation-inhibition ratio emerging most prominently in the hippocampus at 6 months. Additionally, elevated population spiking activity and age-related impairments in theta-gamma phase-amplitude coupling were observed in the local field potentials of APP/PS1 mice in both the hippocampus and the cortex. Importantly, the functional excitation-inhibition ratio correlated positively with elevated population spiking activity in both brain regions in APP/PS1 mice. Our findings highlight the functional excitation-inhibition ratio as a promising biomarker of hippocampal and cortical network disinhibition and hyperexcitability in APP/PS1 mice, with potential value as an early disease marker in Alzheimer's disease.

Sarcopenia, a common geriatric condition characterized by the loss of skeletal muscle mass and function, can negatively affect functional outcomes in acute ischaemic stroke; however, the underlying mechanisms remain unclear. We hypothesized that sarcopenia affects post-stroke outcomes, mediated through its impact on dysphagia, early neurological deterioration, or post-stroke recovery, particularly in patients with motor deficits. To explore this hypothesis, we included 600 consecutive elderly (≥65 years) patients with acute (<1 week) ischaemic stroke and assessed: (i) the relationships sarcopenia has with dysphagia, early neurological deterioration and various phases of recovery after stroke (in-hospital, post-discharge [up to 3 months], and chronic [3 months to 1 year]) and (ii) whether either presenting symptoms or lesion locations modify the impact of sarcopenia on stroke outcomes. Temporal muscle thickness, a marker of sarcopenia, was measured by brain magnetic resonance imaging and dichotomized into low versus high temporal muscle thickness at the 25th percentile cut-off point. Logistic regression analysis, mediation analysis and statistical brain mapping were conducted. Mean age was 75.3 ± 6.1 years and 303 (50.5%) were male. Low temporal muscle thickness (<5.1 mm) was independently associated with dysphagia (adjusted odds ratio 1.89 [95% confidence interval 1.06-3.37], P = 0.03), early neurological deterioration (adjusted odds ratio 2.75 [95% confidence interval 1.61-4.71], P < 0.001) and post-discharge recovery (adjusted odds ratio 0.56 [95% confidence interval 0.34-0.94], P = 0.03) but not with in-hospital or chronic recovery. In addition, dysphagia, early neurological deterioration and post-discharge recovery were shown to mediate the association between low temporal muscle thickness and poor functional outcome (modified Rankin scale score ≥ 3) at 3 months, accounting for ∼45% of the total effect. Low temporal muscle thickness had a greater impact on stroke outcomes in patients with motor deficit, facial palsy, dysarthria, or pontine lesions. Furthermore, brain mapping revealed that low temporal muscle thickness had a stronger impact on functional outcomes in infarctions involving brain regions responsible for motor strength, planning, execution, and control: i.e. pallidum, fronto-pontine tract, parieto-occipito-temporo-pontine tract, middle cerebellar peduncle, and corticospinal tract. Sarcopenia leads to poor functional outcomes, probably due to its association with dysphagia, early neurological deterioration, and limited post-discharge recovery in elderly acute ischaemic stroke patients, particularly those with motor deficit, bulbar symptoms, or lesions involving pons and motor pathways. Understanding and identifying the mechanisms underlying sarcopenia-related effects on post-stroke outcomes may inform comprehensive, time-specific approaches to personalised management for this patient population.

Hemispheric lateralization has been central to developmental dyslexia research for over a century, yet its role in the aetiology of reading and language deficits remains elusive. While altered asymmetries have long been implicated, evidence is inconsistent, with limited consideration given to individual variability in lateralization patterns. This study investigated hemispheric lateralization in 35 adults with dyslexia and 35 matched controls using functional MRI across three language tasks: word generation, rhyming decision and lexical decision. Laterality indices were calculated to comprehensively assess the strength, direction, and consistency of activation across global and regional task-specific brain areas. Significant group differences were not found in the absolute strength of lateralization for global measures or any regional measures, except in the fusiform gyrus, where people with dyslexia showed lower asymmetry. Directional asymmetry was similar across the two groups, except in the fusiform gyrus during the reading task, where dyslexic individuals showed a higher prevalence of right hemisphere lateralization compared to controls. Interestingly, we found that dyslexic participants demonstrated greater inconsistency in regional lateralization during reading and rhyming tasks. Among individuals with dyslexia, those with inconsistent lateralization in the reading task had weaker fusiform lateralization, although fusiform lateralization strength itself did not predict reading outcomes. Our findings suggest that dyslexia is characterized by inconsistent, rather than universally weaker, lateralization patterns. Inconsistencies in task-related and regional lateralization may disrupt the efficiency of language networks, contributing to observed reading deficits. By highlighting the role of regional and task-specific inconsistencies, this study provides new insights into the neural mechanisms underlying dyslexia and underscores the importance of considering individual variability in hemispheric lateralization when investigating language disorders.

Microstructural alterations in brain tissue play a crucial role in the pathophysiology of frontotemporal dementia (FTD). This study assessed brain white matter (WM) and grey-matter (GM) microstructure in FTD variants using neurite orientation dispersion and density imaging (NODDI) diffusion MRI model and developed an exploratory machine-learning algorithm to classify FTD subtypes according to diffusion MRI metrics. Brain MRI including multi-shell diffusion sequences and neuropsychological assessment were obtained in controls and participants with FTD: 35 behavioural variant of FTD (bvFTD), 20 semantic-variant primary progressive aphasia (svPPA), 14 nonfluent-variant primary progressive aphasia (nfvPPA), 9 semantic-bvFTD (sbvFTD). Fractional anisotropy (FA), mean diffusivity (MD), intracellular-volume fraction (ICVF), and orientation-dispersion index (ODI) were analysed using tract-based and GM-based spatial statistic at the voxel-wise level, with nonparametric and permutation-based methods. Support vector machine (SVM) models were trained on different combinations of diffusion MRI and neuropsychological features to classify FTD subtypes. FA and MD showed widespread WM alterations in all variants. ICVF showed reductions in both WM and GM (bilateral frontotemporal for bvFTD, left temporal-frontal for svPPA and nfvPPA and right temporal for sbvFTD). GM ODI reduction exhibited a similar but more diffuse pattern compared with ICVF. WM ODI alterations were also observed, with specific WM alterations in the corpus callosum and long-range WM tracts when comparing FTD syndromes. SVM algorithm, trained on mean FA, ICVF and ODI values from different brain lobes and neuropsychological scores, achieved 98.6% accuracy in classifying different clinical syndromes, outperforming standard diffusion tensor (DT) imaging-based models. NODDI capture subtle microstructural alterations in brain GM and WM, demonstrating advantages over standard DT imaging in capturing disease-relevant alterations. By integrating NODDI with cognitive data, machine-learning models can learn complex patterns and relationships facilitating the differentiation of FTD subtypes.

Long COVID is a complex condition characterized by persistent symptoms, including cognitive difficulties and fatigue, which significantly impact daily functioning. Although various intervention strategies inspired by approaches used in the rehabilitation of other neurological conditions have been developed to address these issues, evidence of their efficacy in Long COVID populations remains limited. This study aimed to compare the effectiveness for cognitive complaints of two psychoeducational interventions-one focused on cognitive difficulties and the other on affective symptoms in Long COVID patients with cognitive problems. COVCOG (Long COVID: treatment of cognitive difficulties) is a randomized controlled trial using a parallel two-group design. Long COVID patients underwent neuropsychological assessments at pre-, 2- and 8-month post-intervention. The intervention comprised four 90-min sessions of either a cognitive-focused or an affective-focused psychoeducational programme. The effects were measured on cognitive complaints (primary outcome), cognitive performance, fatigue, sleep difficulties, quality of life, psychological distress, and impact on work and daily activities (secondary outcomes). Linear mixed models (LMMs) were used. One hundred and thirty Long COVID patients were randomized. One hundred and twenty-two (mean age: 47 ± 10; 69.7% female) were included (63 in the cognitive group and 59 in the affective group). The low dropout rate (12% at 2 months and 9% at 8 months post-intervention) and the patients' substantial active engagement-92% attended all intervention sessions-assured the feasibility of both interventions. LMM analysis revealed a statistically significant improvement with time in subjective cognitive complaints, objective cognitive performance (attention, working memory and long-term memory), quality of life, fatigue, sleep, some psychological distress subscales and work impairment (all Ps < 0.03, with small to moderate effect sizes), but no group-by-time interaction, suggesting that trajectories did not differ between arms. However, some improvements are specific to one intervention or the other. Designed specifically for this population, both psychoeducative interventions provide insights into improving the management of Long COVID patients with cognitive problems. Longer treatment may be needed for more meaningful improvements. Clinicaltrials.gov: NCT05167266.

Most foundational frameworks for understanding disorders of consciousness are based on common aetiologies such as traumatic brain injury, stroke or hypoxic-ischemic insult. From these, the mesocircuit hypothesis has emerged as a leading model, proposing that consciousness depends on a distributed network of brainstem arousal systems, central thalamic hubs and cortico-subcortical loops. However, rare and underrecognized causes of coma and prolonged disorders of consciousness offer a unique opportunity to test, refine and expand these models. In this review, we analyse a wide array of rare aetiologies-including genetic syndromes, parasitic and fungal infections, autoimmune encephalitides, amyloid and tau pathologies, toxic-metabolic states and haematological disorders-that are often excluded from mainstream consciousness research. Despite their diverse mechanisms, these conditions converge on a consistent set of anatomical targets: the central thalamus, brainstem reticular activating system, deep white matter 'bridging zones', basal ganglia and distributed cortical networks. This convergence not only provides powerful external validation of network-based frameworks such as the mesocircuit hypothesis but also underscores the clinical need for therapeutic approaches that address both aetiology-specific pathology and distributed circuit-level dysfunction. However, evidence quality varies considerably across these rare conditions, with many findings based on limited case reports or small series, necessitating cautious interpretation of proposed anatomical frameworks.

The association of genetic variants in the Human Leukocyte Antigen (HLA) locus with late-onset Alzheimer's disease has been stringently replicated across several, powerful genome-wide association studies. However, no clear picture has yet emerged of the mechanistic relationship between Alzheimer's disease and this top genetic hit, despite the fact that the HLA locus is one of the most influential gene loci of the immune system, known to influence antigen presentation, T cell responses and brain plasticity. In this review, we explore this association by outlining five research questions, namely: (i) the association of HLA Class I and Class II genes with Alzheimer's disease at the allelic and haplotypic levels, (ii) the unconventional role of HLA Class I in the brain, (iii) the infection hypothesis of Alzheimer's disease in the context of the known role HLA proteins play in immunity, (iv) the possible antigen presentation of Alzheimer's disease relevant self-antigens and in turn (v) the possibility of T cells existing that are specific for these antigens. Identifying the functional mechanisms underlying this important genetic association with Alzheimer's disease may hold the key to unravelling new avenues of Alzheimer's disease immunotherapeutics.

Repetitive head impacts are common in contact and collision sports and are linked to structural brain changes and an elevated risk of neurodegenerative diseases such as Chronic Traumatic Encephalopathy. Identifying early in vivo structural markers remains challenging. Although diagnosis currently requires post-mortem confirmation, clinical symptoms, including cognitive impairment and behavioural changes, are reflected in the diagnosis of Traumatic Encephalopathy Syndrome. These symptoms align with dysfunction in key brain regions-amygdala, hippocampus and thalamus-which support memory, emotion and behaviour and commonly show tau pathology in Chronic Traumatic Encephalopathy. This study uses shape analysis to examine structural differences in these regions between former American football players and unexposed asymptomatic controls and evaluates the influence of age, head impact exposure and clinical diagnosis on brain structure. We analyzed brain morphology in former American football players (n = 163) and unexposed, asymptomatic controls (n = 53). Structural segmentation was performed with FreeSurfer 7.1, and the shape analysis pipeline was used to generate subregional reconstructions. Vertex-level morphometry, based on the logarithm of the Jacobian determinant and radial distance, quantified local surface area dilation and thickness. Group differences were examined with covariate-adjusted linear regression models contrasting football players and controls, as well as participants with and without a Traumatic Encephalopathy Syndrome diagnosis. Partial correlations examined the influence of age, age of first football exposure and cumulative head impact index metrics, including frequency, linear acceleration and rotational force. Models were adjusted accordingly for age, body mass index, education, race, imaging site, apolipoprotein $ϵ4$ status and total intracranial volume. Former football players exhibited bilateral surface area contractions in the hippocampus and amygdala, along with reduced amygdala thickness, compared to controls. Older age was associated with widespread surface contractions and thinning across all regions, except for preserved thickness in the left hippocampus. An earlier age of first exposure to football correlated with surface contractions in the thalamus and left hippocampus. Greater cumulative linear acceleration was linked to bilateral hippocampal surface contractions and reduced thickness in the left thalamus, while greater rotational force exposure was associated with hippocampal thinning. No significant structural differences were found between players with and without a diagnosis of Traumatic Encephalopathy Syndrome. These findings extend volume-based research by revealing localized alterations in surface area dilation and thickness and emphasize the roles of age and repetitive head impact exposure in long-term brain changes.

Astrocytes are key regulators of sleep and neuroinflammatory responses. However, the relationship between objective sleep parameters and astrocytic fluid biomarkers in cognitively unimpaired individuals remains unclear. We examined how sleep architecture relates to astrocytic, neuroaxonal and Alzheimer's disease-related fluid biomarkers in cognitively unimpaired adults and whether age, sex and APOE ε4 moderate these associations. This cross-sectional study included 51 cognitively unimpaired participants from the Sant Pau Initiative on Neurodegeneration cohort. One-night in-lab polysomnography was used to quantify sleep architecture, fragmentation, slow-wave activity and respiratory parameters. CSF biomarkers included glial fibrillary acidic protein (GFAP), chitinase-like-3 protein 1 (YKL-40), Aβ42, Aβ40, pTau181 and tTau; plasma biomarkers included GFAP and neurofilament light chain (NfL). Associations were analysed using Spearman correlations, multiple linear regression, and moderation models, adjusting for age, sex, body mass index, APOE ε4 status and sleep apnoea. Lighter and more fragmented sleep, characterized by longer N1 duration, increased wake after sleep onset, frequent stage transitions and elevated cortical arousal, was associated with higher CSF YKL-40, Aβ40, pTau181 and tTau (ρ = 0.32-0.62, all P < 0.05). In contrast, deeper, more consolidated sleep, indicated by longer total time of sleep, greater N3 duration and higher slow-wave activity, was associated with lower CSF GFAP and YKL-40 (ρ = -0.35 to -0.44, all P < 0.05). These associations remained significant in adjusted regression models. Plasma GFAP and NfL exhibited an inverse profile, with positive associations with deeper sleep (β: 0.16-0.18, P < 0.05) and negative associations with lighter sleep stages (β: -0.23 to -0.29, P < 0.01). Rapid eye movement (REM) sleep was also associated with astrocytic fluid biomarkers, with negative correlations for CSF and plasma GFAP (ρ = -0.49 and ρ = -0.28, respectively, all P < 0.05), while in regression models, REM duration remained a negative predictor of plasma GFAP (β = -0.23, P = 0.003) and a positive predictor of CSF YKL-40 (β = 0.12, P = 0.037). Notably, APOE ε4 consistently moderated associations between sleep and CSF YKL-40 and GFAP, while age and sex influenced plasma GFAP and CSF YKL-40, respectively (all P < 0.05). In cognitively unimpaired adults, sleep architecture is differentially associated with central and peripheral biomarkers of astrocytic activation, neuroaxonal integrity and Alzheimer's disease-related proteins. These findings support the importance of considering sleep as a key factor in the early pathophysiology of neurodegenerative disease.