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 utilizes autopsy-confirmed Lewy body disease cohorts to demonstrate that while major genetic susceptibility loci are shared with clinically diagnosed cases, the APOE4 variant uniquely influences both disease risk and the neocortical extent of Lewy pathology, independent of Alzheimer's disease co-pathology.
This study introduces the Route Concordance Index (RCI), a diffusion MRI-based graph-theoretic biomarker of periventricular white-matter routing that effectively tracks Alzheimer's disease progression from preclinical stages to clinical conversion, offering predictive accuracy comparable to established structural markers while providing a cleaner, monotonic decline across the disease trajectory.
This study demonstrates that apparent cross-cohort differences in tau-positivity prediction between ADNI and OASIS3 are largely artifacts of variable availability and disease-stage composition rather than genuine biological divergence, highlighting the critical need for strict feature harmonization and stage-aware modeling in Alzheimer's biomarker research.
This study identifies reproducible cerebrospinal fluid proteomic signatures across early neuronal α-synuclein disease stages, revealing distinct synaptic and neurosecretory protein patterns that differentiate disease progression and predict phenoconversion, thereby offering potential biomarkers to optimize cohort enrichment for Parkinson's disease prevention trials.
This retrospective study of 35 patients characterizes pseudo-orthostatic tremor as a condition predominantly associated with essential tremor or functional neurological disorders, highlighting distinct surface electromyography features that differentiate organic and functional subtypes and informing treatment outcomes.
In the HUNT Study, plasma pTau217 emerged as a strong predictor of 11-year dementia risk, with eight modifiable risk scores providing statistically significant but marginal improvements in discrimination and complementary value for risk stratification, while NfL offered no additional predictive benefit.
This prospective ecological momentary assessment study of 143 adults with migraine reveals that daily cognitive symptoms (brain fog and forgetfulness) and mood disturbance, rather than demographic factors, are the primary independent predictors of headache-related interference with activity and concentration.
This study prospectively validates a conformal prediction-enabled random forest model that outperforms the Lorscheider criteria in classifying secondary progressive multiple sclerosis with calibrated uncertainty, demonstrating high sensitivity and supporting its potential for clinical decision support.
This study demonstrates that an unsupervised, home-based screening toolkit consisting of an 11-item questionnaire and an 8-scent smell test effectively identifies adults with Parkinson's disease with high sensitivity (0.98) and specificity (0.83), outperforming a more complex original version.
This study demonstrates that a longitudinal XGBoost model utilizing non-imaging clinical features from over 15,000 individuals can accurately predict Alzheimer's disease progression from cognitively normal or mild cognitive impairment states, successfully identifying future decline months before clinical diagnosis with high sensitivity and manageable false alarm rates.