Dementia and Cognitive Impairment Research

The paper harmonizes CSF and amyloid imaging biomarkers using a Z-score approach and compares it to existing methods in GWAS analyses.

This study identifies a latent clinical-anatomical dimension linking metabolic syndrome severity to brain morphology and cognition in 40,087 individuals.

This study integrates multi-omic data from brain and blood to identify AD subtypes and proposes LDLR as a blood biomarker linked to brain gene expression changes.

The paper uses metabolic covariance analysis on PET imaging data from a mouse model of Alzheimer's disease to show age-related metabolic network changes and their alignment with clinical AD stages.

The paper shows that high-risk individuals for Alzheimer's show stronger implicit interference with practice compared to low-risk individuals, indicating early cognitive differences.

This study uses MRI data to show reduced gray matter in the nucleus basalis of Meynert in Alzheimer's Disease but limited evidence in mild cognitive impairment, with amygdala and hippocampus effects also observed.

The paper examines how AD risk factors relate to hippocampal excitation-inhibition balance in cognitively normal individuals, finding sex-specific differences and effects of APOE-ε4.

This paper introduces PentaMind, a deep learning model that extracts cognitive features from hand-drawn intersecting pentagons, improving detection of cognitive decline in older adults.

The paper maps sleep oscillatory events as biomarkers for early Alzheimer's disease by analyzing EEG and CSF biomarkers in aging adults.

The paper correlates rs-fMRI complexity, measured by entropy, with tau-PET in Alzheimer's disease, showing associations with cognitive decline mediated through tau accumulation.

The paper demonstrates the feasibility of conducting clinical recall studies from the FinnGen biobank to collect customized clinical data from participants with Alzheimer's disease or mild cognitive disorder.

This study shows hippocampal sclerosis of aging (HS) causes detectable hippocampal volume changes on MRI more than a decade before death, independent of age and Alzheimer's Disease burden.

The paper finds that higher plasma Reelin levels in AUD patients expressing APOE4 predict greater cognitive decline, particularly in memory and executive function.

This study examines how resting EEG power spectra relate to age, cognition, APOE-4 status, and cardiometabolic factors in adults aged 50-80.

This paper introduces two deep learning models, PPAD and PPAD-AE, to predict Alzheimer's disease progression from mild cognitive impairment using EHR data, achieving better performance than baselines in F2 and sensitivity.

This study evaluates Brain Age as a biomarker for fluid cognition in older adults and finds it only marginally improves prediction over chronological age.

This study compares three brain age algorithms to assess their reliability, demographic correlations, and predictive power for cognitive disorders.

This study investigates the association between cerebellar and subcortical atrophy and neuropsychiatric symptoms in genetic frontotemporal dementia, finding significant differences across genetic mutations.

This paper evaluates transfer learning methods for Alzheimer's disease classification using brain MRI, finding that contrastive learning improves performance, especially with limited data.

This paper uses deep 3D CNNs combining anatomical and diffusion MRI to predict dementia severity and brain age, finding that diffusion MRI improves performance over anatomical MRI alone.

The paper uses deep learning to extract neuroimaging features from MRI data for Alzheimer's disease GWAS, identifying associated SNPs linked to neurodegenerative disorders.

The paper develops an automatic pipeline for analyzing skull thickness and scalp-to-cortex distance from MRI data and shows age and sex-related changes in these metrics in elderly individuals.

The paper examines the association between retinal neuronal layer thickness and brain structural integrity in midlife, finding thinner retinal layers correlate with reduced brain structural measures.

This study finds that preserved aerobic glycolysis in the brain is linked to resilience against Alzheimer's disease pathology, while white matter hyperintensity burden is associated with reduced youthful AG patterns.

This paper introduces OViTAD, an optimized vision transformer that predicts Alzheimer's disease stages using resting-state fMRI and structural MRI data, achieving high accuracy with fewer parameters.

The paper examines the link between social isolation and Alzheimer's disease-related dementias risk using large population cohorts.

The paper develops a histological staging system for hippocampal sclerosis (HS) and shows its correlation with disease duration, cognitive performance, and MRI findings.

This study examines how brain age estimates from different MRI modalities relate to Alzheimer's disease biomarkers and cognition in early stages.

This study examines the relationship between white matter hyperintensities, medial temporal lobe volumes, and memory in older adults, finding that occipital hyperintensities are linked to reduced subregional volumes and worse memory performance.

This study performs a GWAS of dementia in African-ancestry individuals, identifying risk loci and highlighting differences in gene expression.