228 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 integrating instantaneous frequency and amplitude into EEG microstate analysis reveals distinct alterations in brain state prevalence and network organization in Alzheimer's disease patients compared to healthy controls, offering a complementary approach to characterizing neurodegenerative dysfunction.
In a pilot randomized crossover trial involving nine Parkinson's disease patients, chronic adaptive and conventional deep brain stimulation demonstrated comparable population-level efficacy, though exploratory analyses suggest that individual baseline disease characteristics may influence specific treatment advantages, highlighting the need for larger studies to identify optimal patient subgroups.
This paper presents and validates a novel implantable device platform that utilizes secure large language models to enable bidirectional, real-time conversation between patients and an AI agent, allowing the system to co-manage epilepsy by detecting biomarkers, personalizing interactions, and rapidly adapting seizure detection algorithms without extensive expert intervention.
This study introduces MELD-PostOp, a deep learning tool trained on a large, multi-center cohort that achieves accurate, generalizable, and rapid (17-second) automated segmentation of post-surgical resection cavities on MRI, significantly outperforming existing methods in both accuracy and efficiency.
This study utilizes patient and family-reported data from 32 individuals to characterize the heterogeneous clinical spectrum of IRF2BPL-related disorders and provides evidence that missense variants are associated with a less severe phenotype compared to truncating variants.
This study demonstrates that a multi-session hierarchical Bayesian model (MS-HBM) can reliably map individual-specific resting-state networks in drug-resistant epilepsy patients using short fMRI sessions, enabling accurate prediction of task-based language dominance for presurgical planning.
This study utilizes three-dimensional gait analysis to characterize the heterogeneous gait deviations in STXBP1-related disorder, identifying externally rotated foot progression as the most common pattern and demonstrating that the age of independent walking onset predicts future community mobility while validating observational scoring as a practical alternative to instrumental analysis.
This study demonstrates that targeted long-read RNA sequencing (Amp-LRS) is a sensitive, cost-effective, and versatile method for functionally validating non-coding variants predicted to alter splicing in rare neurological disorders, successfully confirming pathogenic mechanisms in all five tested patients using accessible tissues.
This prospective longitudinal study of 450 Parkinson's disease patients demonstrates that poor visual function, particularly when combined with specific genetic risk factors such as GBA1 variants and polygenic risk scores for Parkinson's and Alzheimer's diseases, significantly predicts progression to cognitive impairment, offering a strategy to enrich clinical trials for more efficient dementia intervention studies.
This study utilized a Bayesian multimodal subtyping framework on over 121,000 cognitively unimpaired adults to identify four distinct risk profiles, revealing that those with cardiometabolic-depressive multimorbidity face the highest risk of developing mild cognitive impairment and derive the greatest protective benefit from antihypertensive and specific antidiabetic treatments.