Brain communications最新文献

Despite being frequently reported by patients, the prevalence, character and clinical relevance of sensory symptoms in functional neurological disorder (FND) is unknown. This study aimed to (i) estimate the frequency and explore the characteristics of sensory symptoms and signs (excluding the special senses) in patients with motor-FND, (ii) compare these features to patients with recent stroke, and (iii) investigate potential mechanisms underlying functional sensory symptoms. In this prospective observational cohort study, 102 patients with motor-FND and 75 patients with recent stroke were assessed using structured clinical interviews, body maps, validated questionnaires, clinical assessment and quantitative sensory testing. Motor-FND participants were followed up at 12-months. Data were analysed using thematic analysis for symptom description, descriptive statistics for frequency and regression models to explore predictors of symptom severity and change. Sensory symptoms were highly prevalent in motor-FND, reported by 96% compared to 67% of mild to moderate recent stroke. However, 27% of motor-FND and 36% of stroke only endorsed experiencing sensory symptoms after prompting. Motor-FND participants described a broader spectrum of sensory experiences compared to stroke, including numbness, paraesthesia, movement-related perceptions and abstract descriptions. Feelings of limb absence/'feels dead' (19% versus 1%) and areas of complete sensory absence (27% versus 15%) were more commonly reported in individuals with FND than in mild-moderate stroke. The motor-FND group experienced pain more frequently than the stroke group (88% versus 41%) and more frequently endorsed having a high pain tolerance (70% versus 49%). The distribution of sensory symptoms differed from the distribution of pain. Sensory symptoms were often perceived as severe and associated with disability and depression. Conflation of the concepts of weakness and numbness was common in both groups (21% of motor-FND versus 10% of stroke). Only one-third of motor-FND patients reported improvement in sensory symptoms at 12 months. Dissociation, body perceptual disturbance and sensory hypersensitivity were significantly more common in motor-FND. Dense midline splitting of light touch or splitting of vibration sense across the forehead or sternum were uncommon and had poor diagnostic specificity, but asymmetries in vibration sense were more common in motor-FND. Quantitative sensory testing provided no clear added diagnostic value. Sensory symptoms in motor-FND vary in nature, are highly prevalent, persistent, clinically significant and often linked to broader illness burden and psychological distress. Sensory symptoms should be routinely assessed in FND, both for diagnosis and treatment planning. Future research should evaluate targeted interventions to specifically address sensory symptoms within multidisciplinary rehabilitation frameworks.

We describe the case of a participant in a clinical trial investigating intracortical microstimulation of the visual cortex to provide a limited yet functional sense of vision to the profoundly blind. Prior to his formal enrolment, he was completely blind due to bilateral Non-arteritic Anterior Ischemic Optic Neuropathy. Following the initiation of brain electrical microstimulation experiments, he experienced a remarkable recovery of spontaneous vision. The regained sight, after more than 3 years of complete blindness, enabled him to perceive light and motion again and even read large characters and words, enhancing his confidence in mobility and daily activities. We conducted several behavioural and electrophysiological tests to assess and quantify his vision over time.

Mild traumatic brain injury is a risk factor to sustaining future mild traumatic brain injuries and increased symptom severity and duration following a second mild traumatic brain injury. Inflammation during neurobiological recovery is hypothesized to influence susceptibility to poorer outcomes after repetitive mild traumatic brain injury. Here, we investigated whether the inflammatory response during neurobiological recovery is related to susceptibility to increased functional and biological deficits following re-injury. To investigate this, we collected serum 1, 3, 7 or 14 days after mild traumatic brain injury in male Sprague-Dawley rats and measured levels of circulating inflammatory cytokines using the MesoScale Discovery MESO QuickPlex SQ 120MM platform to quantify interferon-gamma, interleukin-1-beta, interleukin-4, interleukin-5, interleukin-6, interleukin-10, interleukin-13, keratinocyte chemoattractant/human growth-related oncogene and tumour necrosis factor-alpha. Immediately following this blood collection, rats were given a second mild traumatic brain injury to assess associations between cytokine levels at time of second mild traumatic brain injury with behavioural outcomes, neurofilament light levels, and ex vivo diffusion tensor imaging in the 28 days following second injury. After a single mild traumatic brain injury, interleukin-10, interleukin-13, interleukin-4 and tumour necrosis factor-alpha were elevated 3 days post-injury while interleukin-10 and tumour necrosis factor-alpha levels were elevated 14-days post-injury. Furthermore, higher levels of interleukin-6 and interleukin-13 at the time of a second mild traumatic brain injury were associated with a reduced number of acute neurological signs of mild traumatic brain injury following the second injury. There were no other significant correlations between circulating cytokine levels and post-injury outcomes following correction for multiple comparisons. These findings provide initial, hypothesis-generating evidence that higher levels of circulating inflammatory cytokines at the time of a second mild traumatic brain injury may be associated with decreased susceptibility to a second mild traumatic brain injury, highlighting the complex role of inflammation in repeated mild traumatic brain injury.

Frontotemporal lobar degeneration is associated with diverse clinical phenotypes underlain by multiple disease pathologies and genetic mutations for which traditional structural magnetic resonance imaging (MRI) analyses lack discriminatory sensitivity and specificity. Here, we use a data-driven multivariate method to extract a concise set of MRI-derived shape morphometric features and cross-sectionally examine the discriminatory capability of their unique combinations in three frontotemporal lobar degeneration clinical phenotypes. Patients with sporadic or familial frontotemporal lobar degeneration clinical syndromes across two cohorts (i.e. behavioral variant (n = 173), non-fluent variant primary progressive aphasia (n = 63), semantic variant primary progressive aphasia (n = 41)) and 158 controls were assessed. Cortical morphometry measures of cortical thickness, surface curvature, and metric distortion were extracted, contrasted with controls using linear models, and additionally entered into a sparse partial least squares discriminatory analysis (sPLS-DA) designed to model multimodal signatures unique to each phenotype. Discriminatory power of partial least squares-derived features was tested on independent, age-matched test data. We found that each cortical morphometric feature significantly differed between clinical syndromes in dissociable spatial patterns. On independent data, the combination of cortical thickness and surface curvature best discriminated between behavioural variant and non-fluent variant primary progressive aphasia patients from controls. For semantic variant primary progressive aphasia, any model including cortical thickness maximized model performance. The sparse partial least squares approach indicated distinctive brain regions contribute to discrimination for each shape feature, suggesting each feature may reflect unique aspects of neurodegeneration across groups. This method could prove invaluable in future studies for early detection of frontotemporal lobar degeneration phenotypes.

Aggressive behaviour is prevalent across neurodevelopmental and neuropsychiatric conditions and is related to poor outcomes. Yet, despite extensive neuroimaging studies, a consistent set of brain networks where dysfunction is consistently related to aggressive behaviour remains unclear. Many studies are correlational in nature, while causal studies, such a lesion-location-based studies, are often limited to injury of the frontal lobes. Here, we analyse 61 focal brain lesions, identified in the current medical literature, that are associated with new-onset aggression and related behaviours. Lesions were traced onto a standardized brain atlas and used as seeds for a functional connectivity analysis, leveraging resting-state data from 1000 healthy individuals. These maps, representing likely pre-injury connectivity, were grouped using a data-driven hierarchical clustering approach. Then, the lesion networks of the identified clusters were separately compared with the connectivity of 716 lesions causing other symptoms. This data-driven approach identified two distinct lesion subgroups that both appear to manifest aggression through the co-occurrence of disrupted functional connectivity to networks involved in emotional expression and cognitive control. Both 'aggression networks' demonstrated sensitivity and specificity when compared with lesions causing a wide variety of other neuropsychiatric symptoms. The first subgroup network involved connectivity to the anterior cingulate cortex and was correlated with the connectivity of lesions causing akinetic mutism. The second subgroup network involved connectivity to the ventromedial prefrontal cortex and contained a notable subset of cases (n = 25) that had reported criminal behaviour, supporting a role of self-control in this subgroup and implying separable influences towards criminality within our identified aggression networks. Alterations within the first group aligned with motivation networks, while the second group aligned with disinhibition networks, indicating these as the potential underlying factors in aggression in the two subgroups, respectively. This characterization was supported by previous work on the atrophy network mapping of behavioural variant frontotemporal dementia. Overall, this study suggests that aggressive behaviour may be more likely after injury to distinct brain networks, which may be related to distinct behavioural factors, and has implications for potential targeted therapeutic interventions such as focused neuromodulation.

Temporal lobe resection for focal, drug-resistant temporal lobe epilepsy (TLE) causes verbal memory deficits in 30% of left hemisphere-operated patients. Structural, functional and computational modelling have shown a widespread structural and functional memory network with hubs in critical brain regions including the hippocampus, subcortical and neocortical regions. We hypothesized that damage to white matter pathways forming a network involving cortical and subcortical regions may be responsible for postoperative memory problems. In this study, we measured verbal memory encoding (immediate recall) and retrieval (delayed recall) outcome at three timepoints (preoperative, 3- and 12-month postoperatively) in 146 left TLE patients who underwent temporal lobe surgery and evaluated the impact of white matter tract section on verbal memory. Outcome was measured by the change in scores from preoperative to 3- and 12-month postoperatively and via the reliable change index. Utilizing resection masks from pre- and postoperative T1 scans, an atlas-based analysis utilizing reconstructions of the ventral cingulum and fornix confirmed these tracts involvement in verbal encoding but not retrieval. Using preoperative diffusion MRI (dMRI) reconstructions with resection masks to estimate the percentage of fibre bundle transection, we found that the ventral cingulum was significantly related to verbal encoding change and the fornix was related to verbal retrieval across both 3- and 12-month timepoints. Investigating volumes of ventral cingulum and fornix from postoperative dMRI reconstruction revealed that greater volume remaining of the ventral cingulum and fornix was related to less decline in verbal encoding but not retrieval. Our results suggest that verbal encoding may be supported by direct and indirect connections between the medial temporal lobe and subcortical regions with memory deficits arising from their transection. Verbal retrieval may rely on a greater neocortical network. These findings may inform a revised surgical approach to minimize damage to the fornix and ventral cingulum to optimize memory outcome, but recognizing the potential for worse seizure outcome with less ventral cingulum resections.

Multiple sclerosis (MS) progressively impairs brain network function, often driving disability even in the absence of overt structural MRI changes. Current clinical and radiological tools frequently fail to capture early, subtle disruptions in cortical activity that may indicate ongoing disease progression. Functional assessment methods capable of detecting these early network alterations are therefore critically needed. This study aimed to determine whether brain responses recorded by combining transcranial magnetic stimulation (TMS) with electroencephalography (EEG) from the primary motor cortex differ in MS, correlate with clinical disability and predict disease activity. Sixty-nine right-handed participants [mean age: MS 38.5 ± 9.1 years, healthy controls (HCs) 36.9 ± 8.8 years; 41 females] were enrolled, including 43 patients with relapsing-remitting MS and 26 HCs matched for age and sex. MS patients were clinically stable and off corticosteroids or CNS-acting medications at least 1 month prior to testing. All underwent single-pulse stimulation over the left primary motor cortex during EEG recording. Transcranial-evoked potentials (TEPs) and spectral perturbations were extracted. Patients were followed for 2 years and classified as active or stable based on 'No Evidence of Disease Activity-3' criteria. Patients showed significantly reduced P60 amplitude compared with controls (P = 0.0098, FDR-corrected P adj. = 0.0491), and a trend-level reduction in gamma-band desynchronization (i.e. less negative values) (P = 0.025, P adj. = 0.075), which correlated inversely with 9-Hole Peg Test times (r _s = -0.504, P = 0.001). A trend towards lower P15 amplitude was observed in patients with active disease (P = 0.0178, P adj. = 0.0891), and P15 amplitude significantly predicted disease stability at 2 years (accuracy = 74.4%, P = 0.023). TMS combined with EEG detects altered motor cortical network dynamics in MS. Less-pronounced (i.e. less negative) gamma-band desynchronization correlated with preserved fine-motor network efficiency, potentially reflecting a compensatory mechanism. The P15-evoked potential amplitude may predict disease activity. This perturbation-based approach provides a privileged window into network dysfunction in MS, with potential to guide early prognosis and treatment.

Meningiomas are histologically and genetically heterogeneous tumors with varying anatomical distributions. While distinct genetic mutations have been associated with specific tumor locations, the spatial distribution of histological subtypes and their relationship to radiogenomic profiles remains poorly defined. Moreover, the predictive value of spatial information for histopathological classification and tumor grading has not yet been systematically explored. This study aimed to systematically analyze the anatomical predilection of histological meningioma subtypes and their concordance with known mutation-specific spatial patterns, and the predictive potential of voxel-based spatial features. We retrospectively analyzed 737 patients undergoing surgical resection of intracranial meningiomas. Preoperative magnetic resonance images were normalized to a common stereotactic space, and tumors were semi-automatically segmented. Voxel-based lesion-symptom mapping (VLSM) was performed to identify subtype-specific spatial clustering. Spatial distributions were compared with mutation maps from current literature using receiver operating characteristic analysis (AUC-ROC). Additionally, multinomial logistic regression models were applied to evaluate whether tumor localization could predict histological subtype and World Health Organization (WHO) grading. Histological subtypes showed distinct spatial preferences. Meningothelial meningiomas clustered in the anterior and middle skull base; fibrous and transitional types predominated in the convexity, falx, and tentorium; secretory tumors localized to the sphenoid wing and petroclival region; and atypical meningiomas were common in the anterior falx and frontal convexity. Psammomatous meningiomas displayed a broader distribution with involvement of the petrous bone and foramen magnum. AUC analysis revealed strong concordance between histological subtypes and mutation maps, confirming known histogenomic associations (e.g. KLF4/TRAF7 with secretory; NF2 with fibrous and transitional; SMO with meningothelial). No associations to any mutation map were observed for angiomatous, microcystic and metaplastic meningiomas. Predictive modeling based solely on spatial features achieved moderate accuracy for subtype classification and higher accuracy for WHO grade prediction. Meningioma subtypes show distinct, statistically robust anatomical predilections that align with known genetic mutation maps. Predictive modeling highlights that spatial features themselves hold diagnostic and prognostic value, linking anatomical localization to tumor biology and aggressiveness. The study introduces anatomically precise voxel-based templates that may improve radiogenomic classification and non-invasive genotype prediction.

While obesity (body mass index ≥ 30) has been consistently associated with white matter diffusion magnetic resonance imaging (MRI) phenotypes, the contributions of common obesity phenotypes on various diffusion metrics, and the moderating effects of sex and age, require further clarification. This study aims to elucidate these body-brain connections to enhance our understanding of the comorbid link between obesity and body anthropometrics and the brain using a large-scale dataset. We analysed cross-sectional data from 40 040 participants from the UK Biobank (52.2% female; ages 44-83 years) using multiple linear regression to evaluate how obesity and body anthropometrics relate to regional white matter diffusion tensor imaging metrics (fractional anisotropy, axial diffusivity, radial diffusivity, mean diffusivity). We also examined interactions with age and sex. Our analyses revealed significant associations between individual obesity phenotypes (i.e. obesity and body anthropometrics) and diffusion tensor imaging metrics of small effects, with partial correlation coefficient |r| effect sizes ranging from 0.02 to 0.20 for most regions of interest with largest effects in brainstem tracts. We observed more widespread sex-by-obesity phenotypes than age-by-obesity phenotypes interaction effects on diffusion tensor imaging metrics. Our results link obesity and body anthropometrics with white matter phenotypes and suggests that shared body fat-related pathways link physical and brain health that may vary based on sex and age. Understanding these body-brain relationships, and the role of age and sex, could enhance the development and evaluation of targeted, personalized, treatment strategies for brain disorders that co-occur with obesity, although further longitudinal and intervention studies are needed to map the causal dynamics of these associations.