98 papers
Neurology explores the intricate workings of the brain and nervous system, tackling everything from memory and movement to complex conditions like epilepsy and Alzheimer's. This field seeks to understand how our minds function and what happens when that delicate machinery falters, aiming to improve lives through better diagnosis and treatment.
At Gist.Science, we make the latest research from medRxiv accessible to everyone. We process every new preprint in this category, offering both straightforward plain-language explanations and detailed technical summaries so you can grasp the science at your own pace. Below are the latest papers in neurology, ready for you to explore.
This study demonstrates that intraindividual cognitive variability, specifically measured by the coefficient of variation, serves as a sensitive marker that distinguishes prodromal neuronal synuclein disease from healthy controls and independently predicts short-term progression to more advanced stages.
This resting-state fMRI study reveals that migraine patients, particularly those with chronic migraine, exhibit widespread reductions in brain entropy reflecting impaired neural adaptability, which are associated with greater clinical burden but show partial restoration during attacks through weakly chaotic dynamics in multisensory integration regions.
This paper introduces DBSgram, a multimodal framework that integrates subthalamic nucleus local field potentials and wearable kinematic data to enable objective, data-driven Deep Brain Stimulation programming for Parkinson's disease by visualizing the relationship between stimulation parameters, neural activity, and motor symptom improvement.
This study demonstrates that longitudinal analysis of urinary astrocyte-derived extracellular vesicles can non-invasively track real-time dynamics of brain GluN1 receptor concentrations in anti-NMDAR encephalitis, revealing both a treatment-associated decline and drug-induced oscillations that mirror cerebrospinal fluid changes.
This study utilized a longitudinal cohort of autosomal dominant Alzheimer's disease mutation carriers to identify a sequential cascade of nine plasma protein biomarkers that diverge from non-carriers between 26 and 6 years prior to expected symptom onset, offering a refined framework for staging presymptomatic disease and optimizing clinical trial design.
This study demonstrates a causal modeling approach that translates short-term changes in Parkinson's disease rating scales into long-term predictions of clinically meaningful outcomes, showing that a 30% reduction in disease progression could significantly lower the 10-year risk of dementia, falls, and mortality.
This study suggests that bilingualism may support cognitive reserve in both amnestic Alzheimer's disease and logopenic variant primary progressive aphasia, allowing bilinguals to maintain comparable cognitive performance to monolinguals despite exhibiting reduced gray matter volume in specific regions, with bilinguals in the logopenic variant additionally showing preserved volume in disease-epicenter areas.
This bibliometric analysis of 403 publications from the past two decades reveals that neuroendoscopy for intracranial hemorrhage has evolved from a focus on operative feasibility and safety to a precision-based, minimally invasive cornerstone of treatment, driven primarily by Chinese and American research and increasingly integrated with emerging technologies like augmented reality and robotics.
The Global Parkinson's Genetics Program (GP2) identifies a significant global population of 9,019 potentially trial-eligible carriers of pathogenic *GBA1* and *LRRK2* variants among 65,509 Parkinson's disease patients, highlighting a critical disparity between these genetic carriers and the availability of gene-targeted clinical trials while advocating for a unified framework to enable equitable precision medicine recruitment.
By applying computational modeling to intracranial EEG data, this study reveals that distinct, preconfigured excitation-inhibition dynamics underlie clinically defined seizure onset patterns, offering a mechanism-informed classification that correlates with patient characteristics and surgical outcomes.