Brain communications最新文献

This scientific commentary refers to 'The sixth sense: how much does interictal intracranial EEG add to determining the focality of epileptic networks?', by Gallagher et al. (https://doi.org/10.1093/braincomms/fcae320).

Encephalitis lethargica, an epidemic neurological illness, typically involved a severe sleep disorder and progressive parkinsonism. A century later, our understanding relies on seminal descriptions, more recent historical research and the study of small numbers of possible sporadic cases. Theories around infection, environmental toxins, catatonia and autoimmune encephalitis have been proposed. We aimed to describe the presentation of encephalitis lethargica and test these diagnostic and aetiological theories. Subjects with encephalitis lethargica were identified in the archives of the National Hospital for Neurology and Neurosurgery, UK between 1918 and 1946. Case notes were examined to establish illness temporality, clinical features and cerebrospinal fluid results. Controls from the archives were identified for 10% of cases, matching on discharge year, sex and neurologist. Clinical presentation was compared to modern diagnostic criteria for encephalitis lethargica, catatonia and autoimmune encephalitis. In a case-control design, a multilevel logistic regression was conducted to ascertain whether cases of encephalitis lethargica were associated with febrile illnesses and with environmental exposures. Six hundred and fourteen cases of encephalitis lethargica and 65 controls were identified. Cases had a median age of 29 years (interquartile range 18) and a median time since symptomatic onset of 3.00 years (interquartile range 3.52). Motor features were present in 97.6%, cranial nerve findings in 91.0%, ophthalmological features in 77.4%, sleep disorders in 66.1%, gastrointestinal or nutritional features in 62.1%, speech disorders in 60.8% and psychiatric features in 53.9%. Of the 167 cases who underwent lumbar puncture, 20 (12.0%) had a pleocytosis. The Howard and Lees criteria for encephalitis lethargica had a sensitivity of 28.5% and specificity of 96.9%. Among the cases, 195 (31.8%, 95% confidence interval 28.1-35.6%) had a history of febrile illness within one calendar year prior to illness onset, which was more common than among the controls (odds ratio 2.70, 95% confidence interval 1.02-7.20, P = 0.05), but there was substantial reporting bias. There was no evidence that occupational exposure to solvents or heavy metals was associated with encephalitis lethargica. Two hundred and seventy-six (45.0%) of the cases might meet criteria for possible autoimmune encephalitis, but only 3 (0.5%) might meet criteria for probable NMDA receptor encephalitis. Only 11 cases (1.8%) met criteria for catatonia. Encephalitis lethargica has a distinct identity as a neuropsychiatric condition with a wide range of clinical features. Evidence for a relationship with infectious or occupational exposures was weak. Autoimmune encephalitis may be an explanation, but typical cases were inconsistent with NMDA receptor encephalitis.

Obesity and its metabolic complications are associated with lower grey matter and white matter densities, whereas weight loss after bariatric surgery leads to an increase in both measures. These increases in grey and white matter density are significantly associated with post-operative weight loss and improvement of the metabolic/inflammatory profiles. While our recent studies demonstrated widespread increases in white matter density 4 and 12 months after bariatric surgery, it is not clear if these changes persist over time. The underlying mechanisms also remain unknown. In this regard, numerous studies demonstrate that the enlargement or hypertrophy of mature adipocytes, particularly in the visceral fat compartment, is an important marker of adipose tissue dysfunction and obesity-related cardiometabolic abnormalities. We aimed (i) to assess whether the increases in grey and white matter densities previously observed at 12 months are maintained 24 months after bariatric surgery; (ii) to examine the association between these structural brain changes and adiposity and metabolic markers 24 months after bariatric surgery; and (iii) to examine the association between abdominal adipocyte diameter at the time of surgery and post-surgery grey and white matter densities changes. Thirty-three participants undergoing bariatric surgery were recruited. Grey and white matter densities were assessed from T1-weighted magnetic resonance imaging scans acquired prior to and 4, 12 and 24 months post-surgery using voxel-based morphometry. Omental and subcutaneous adipose tissue samples were collected during the surgical procedure. Omental and subcutaneous adipocyte diameters were measured by microscopy of fixed adipose tissue samples. Linear mixed-effects models were performed controlling for age, sex, surgery type, initial body mass index, and initial diabetic status. The average weight loss at 24 months was 33.6 ± 7.6%. A widespread increase in white matter density was observed 24 months post-surgery mainly in the cerebellum, brainstem and corpus callosum (P < 0.05, false discovery rate) as well as some regions in grey matter density. Greater omental adipocyte diameter at the time of surgery was associated with greater changes in total white matter density at 24 months (P = 0.008). A positive trend was observed between subcutaneous adipocyte diameter at the time of surgery and changes in total white matter density at 24 months (P = 0.05). Our results show prolonged increases in grey and white matter densities up to 24 months post-bariatric surgery. Greater preoperative omental adipocyte diameter is associated with greater increases in white matter density at 24 months, suggesting that individuals with excess visceral adiposity might benefit the most from surgery.

[¹⁸F]FE-PE2I PET is a promising alternative to single positron emission computed tomography-based dopamine transporter (DAT) imaging in Parkinson's disease. While the excellent discriminative power of [¹⁸F]FE-PE2I PET has been established, so far only one study has reported meaningful associations between motor severity scores and DAT availability. In this study, we use high-resolution (∼3 mm isotropic) PET to provide an independent validation for the clinical correlates of [¹⁸F]FE-PE2I imaging in separate cross-sectional (28 participants with Parkinson's disease, Hoehn-Yahr: 2 and 14 healthy individuals) and longitudinal (initial results from 6 participants with Parkinson's disease with 2-year follow-up) cohorts. In the cross-sectional cohort, DAT availability in the putamen and substantia nigra of patients with Parkinson's disease showed a significant negative association with total motor severity (r = -0.59, P = 0.002 for putamen; r = -0.46, P = 0.018 for substantia nigra), but not tremor severity. To our knowledge, this is the first observed association between motor severity in Parkinson's disease and DAT availability in the substantia nigra. The associations with motor severity in most nigrostriatal regions improved if tremor scores were excluded from motor scores. Further, we found significant asymmetry in DAT availability in the putamen (∼28% lower DAT availability within the more-affected side of the putamen), and DAT-based asymmetry index for the putamen was correlated with asymmetry in motor severity (r = -0.60, P = 0.001). In the longitudinal study, [¹⁸F]FE-PE2I PET detected significant annual percentage reduction of DAT availability at the individual level in the putamen (9.7 ± 2.6%), caudate (10.5 ± 3.8%) and ventral striatum (5.5 ± 2.7%), but not the substantia nigra. Longitudinal per cent reduction in DAT availability within the putamen was strongly associated with increase in motor severity (r = 0.91, P = 0.011) at follow-up, demonstrating the high sensitivity of [¹⁸F]FE-PE2I PET in tracking longitudinal changes. These results provide further evidence for the utility of [¹⁸F]FE-PE2I as an important in vivo PET biomarker in future clinical trials of Parkinson's disease.

People with epilepsy are at risk of premature death, of which sudden unexpected death in epilepsy (SUDEP), sudden cardiac death (SCD) and sudden arrhythmic death syndrome (SADS) are the primary, partly overlapping, clinical scenarios. We discuss the epidemiologies, risk factors and pathophysiological mechanisms for these sudden death events. We reviewed the existing evidence on sudden death in epilepsy. Classification of sudden death depends on the presence of autopsy and expertise of the clinician determining aetiology. The definitions of SUDEP, SCD and SADS lead to substantial openings for overlap. Seizure-induced arrhythmias constitute a minority of SUDEP cases. Comorbid cardiovascular conditions are the primary determinants of increased SCD risk in chronic epilepsy. Genetic mutations overlap between the states, yet whether these are causative, associated or incidentally present is often unclear. Risk stratification for sudden death in people with epilepsy requires a multidisciplinary approach, including a review of clinical history, toxicological analysis and complete autopsy with histologic and, preferably, genetic examination. We recommend pursuing genetic testing of relatives of people with epilepsy who died suddenly, mainly if a post-mortem genetic test contained a Class IV/V (pathogenic/likely pathogenic) gene variant. Further research may allow more precise differentiation of SUDEP, SCD and SADS and the development of algorithms for risk stratification and preventative strategies.

This scientific commentary refers to 'Noradrenergic modulation of saccades in Parkinson's disease', by  Orlando et al. (https://doi.org/10.1093/braincomms/fcae297).

This study investigates the efficacy of deep-learning models in expediting the generation of disconnectomes for individualized prediction of neuropsychological outcomes one year after stroke. Utilising a 3D U-Net network, we trained a model on a dataset of N = 1333 synthetic lesions and corresponding disconnectomes, subsequently applying it to N = 1333 real stroke lesions. The model-generated disconnection patterns were then projected into a two-dimensional 'morphospace' via uniform manifold approximation and projection for dimension reduction dimensionality reduction. We correlated the positioning within this morphospace with one-year neuropsychological scores across 86 metrics in a novel cohort of 119 stroke patients, employing multiple regression models and validating the findings in an out-of-sample group of 20 patients. Our results demonstrate that the 3D U-Net model captures the critical information of conventional disconnectomes with a notable increase in efficiency, generating deep-disconnectomes 720 times faster than current state-of-the-art software. The predictive accuracy of neuropsychological outcomes by deep-disconnectomes averaged 85.2% (R ² = 0.208), which significantly surpassed the conventional disconnectome approach (P = 0.009). These findings mark a substantial advancement in the production of disconnectome maps via deep learning, suggesting that this method could greatly enhance the prognostic assessment and clinical management of stroke survivors by incorporating disconnection patterns as a predictive tool.

Patients with visual snow syndrome (VSS) experience uncountable flickering tiny dots in the entire visual field. Symptoms often persist over the years. Very little is known about altered perception in VSS. VSS is diagnosed based on subjective reports because there is no manual with objective measures. In this study, 20 patients with VSS and 17 healthy controls performed a battery of tests assessing visual acuity, contrast sensitivity, illusion perception, spatial-temporal vision, motion perception, visual attention, and selective attention. Surprisingly, except for one test, which is the honeycomb illusion, patients performed at the same level as controls. Patients reporting black and white visual snow performed better in the Stroop test compared to patients reporting other visual snow colours. In addition to a clinical visit, the 30-day clinical diary was administered to patients to broadly measure their symptom severity. We found that better performance in the tests, in particular in the contrast and coherent motion tests, was correlated with lower VSS symptoms, weaker VS characteristics (e.g. density and size) and lower VS severity. Our results suggest that, even if visual abilities are not deteriorated by VSS, they can determine how severe symptoms are, and show that VSS is an heterogenous disorder where symptoms and visual abilities vary between patients, for instance depending on the VS colour. The study was primarily designed to identify tests where performance differs between controls and patients. In addition, exploratory analyses were conducted to initiate an understanding of the overall pattern of relationships between patients' visual abilities and symptoms, which is of clinical relevance. Future studies with more power are necessary to validate our findings.

This scientific commentary refers to 'Brain network changes after the first seizure: an insight into medication response?', by Pedersen et al. (https://doi.org/10.1093/braincomms/fcae328).