Machine learning-based prediction of post-stroke cognitive status using electroencephalography-derived brain network attributes.

Objectives: More than half of patients with acute ischemic stroke develop post-stroke cognitive impairment (PSCI), a significant barrier to future neurological recovery. Thus, predicting cognitive trajectories post-AIS is crucial. Our primary objective is to determine whether brain network properties from electroencephalography (EEG) can predict post-stroke cognitive function using machine learning approach.

Stress cardiomyopathy associated with area postrema syndrome as a presentation of neuromyelitis optica: case report.

Background: Stress cardiomyopathy (Takotsubo cardiomyopathy) is very rare in the central nervous system (CNS) demyelinating disorders. Although this dysfunction of the heart-brain axis has been reported in several case series related to multiple sclerosis (MS), stress cardiomyopathy by neuromyelitis optica (NMO), which is rarer CNS demyelinating disorder than MS, is extremely rare. Herein, we report a case of stress cardiomyopathy associated with a medullary lesion as a presentation of NMO.

Early Impairment of Chopsticks Skills in Parkinsonism Suggests Progressive Supranuclear Palsy.

Background And Purpose: Chopsticks are a primary eating utensil in East Asia, but systematic assessments of chopsticks skills in parkinsonian disorders is lacking. We aimed to identify any differences in chopsticks skills in the early stages of Parkinson's disease (PD) and atypical parkinsonism (AP), including progressive supranuclear palsy (PSP), multiple system atrophy (MSA), and corticobasal syndrome (CBS).

Methods: We consecutively recruited 111 patients with PD and 74 with AP (40 with PSP, 30 with MSA, and 4 with CBS) who were in a drug-naïve state.