Dementia and Cognitive Impairment Research

Deep learning-based imaging classification identified cingulate island sign in dementia with Lewy bodies

This study uses deep learning to classify dementia with Lewy bodies and Alzheimer's disease using brain perfusion images, identifying the cingulate island sign as a key feature.

Estimation of Brain Age Delta from Brain Imaging

The paper evaluates methods for estimating brain age delta from brain imaging data and identifies variables strongly correlated with it using UK Biobank data.

Genetic risk for coronary heart disease alters the influence of Alzheimer’s genetic risk on mild cognitive impairment

The paper examines how genetic risk for coronary heart disease interacts with Alzheimer’s genetic risk to influence mild cognitive impairment risk in a cohort of 1,209 individuals.

Serial position effects reflect the integrity of distinct brain regions in Major and Minor Neurocognitive Disorder

This study links serial position effects in memory tasks to specific brain regions in neurocognitive disorders, showing correlations with gray matter integrity.

Modeling longitudinal imaging biomarkers with parametric Bayesian multi-task learning

This paper introduces a Bayesian multi-task learning model for longitudinal imaging biomarkers, showing improved trajectory inference and disease effect detection in Alzheimer's disease data.

Distinct effects of amyloid and tau deposition on eigenvector centrality during hippocampal down-regulation: a real-time fMRI virtual reality closed-loop neurofeedback study with CSF biomarkers

The paper investigates how amyloid and tau levels in CSF affect eigenvector centrality during hippocampal down-regulation using real-time fMRI neurofeedback.

The effect of APOE genotype and streamline density volume, on hippocampal CA1 down-regulation: a real-time fMRI virtual reality neurofeedback study

This study links APOE genotype and hippocampal structure to neurofeedback performance in preclinical Alzheimer's disease risk individuals.

Aging-related hypometabolism in the anterior cingulate cortex mediates the relationship between age vs. executive function but not vs. memory in cognitively intact elders

The paper examines the role of anterior cingulate cortex metabolism in mediating the relationship between age and executive function in cognitively intact elders using the ADNI dataset.

Predicting late-onset Alzheimer’s disease from genomic data using deep neural networks

This study uses deep neural networks to predict late-onset Alzheimer’s disease from genetic variants, showing promise for clinical diagnosis.

A highly predictive signature of cognition and brain atrophy for progression to Alzheimer’s dementia

The paper identifies a predictive signature of cognition and brain atrophy for progression to Alzheimer’s dementia using machine learning, validated in two MCI cohorts with high positive predictive value.

Distinct changes in morphometric networks in aging versus Alzheimer’s disease dementia

The paper identifies distinct morphometric network changes in aging and Alzheimer’s disease, showing additive effects of aging and AD on GM loss, with unique whole-brain pattern variability in AD.

Deep Residual Learning for Neuroimaging: An application to Predict Progression to Alzheimer’s Disease

This paper applies deep residual networks to predict Alzheimer’s disease progression from mild cognitive impairment using neuroimaging data, achieving better performance than existing methods.

Serum triglycerides in Alzheimer’s disease: Relation to neuroimaging and CSF biomarkers

The paper investigates the association between triglyceride principal component scores and Alzheimer's disease biomarkers in the ADNI cohort, finding significant links with MCI, AD, and specific brain structures.

Large-scale proteomic analysis of human prefrontal cortex identifies proteins associated with cognitive trajectory in advanced age

The paper identifies 579 proteins associated with cognitive trajectory in aging using proteomic analysis of human prefrontal cortex, highlighting mitochondrial and synaptic processes linked to cognitive stability.

Differentiation of mild cognitive impairment using an entorhinal cortex-based test of VR navigation

This study uses a virtual reality navigation task to differentiate mild cognitive impairment patients with and without Alzheimer's disease biomarkers, showing higher accuracy than standard cognitive tests.

Identifying Changepoints in Biomarkers During the Preclinical Phase of AD

The paper identifies changepoints in AD biomarkers before symptom onset, showing varying timing across different measures.

Lateral ventricle volume trajectories predict response inhibition in older age - a longitudinal brain imaging and machine learning approach

A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer’s disease

This paper develops a parameter-efficient deep learning model to predict conversion from mild cognitive impairment to Alzheimer’s disease using multimodal data, achieving high accuracy and specificity.

A normative study of modified spatial context memory test in middle and older individuals

The paper develops a modified spatial context memory test to assess cognitive function in middle and older adults, finding age-related declines in spatial-context memory performance.

Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important

The paper proposes a framework combining neuroimaging and clinical data for mental health diagnosis using EasyMKL and feature selection, showing improved performance over baseline methods.

A practical computerized decision support system for predicting the severity of Alzheimer’s disease of an individual

This paper develops a computerized decision support system for predicting Alzheimer’s disease severity using cognitive and clinical measures, showing improved accuracy over biomarker-based models.

A blood-based signature of cerebral spinal fluid Aβ1-42 status

This paper develops a blood-based machine learning model to predict cerebral spinal fluid Aβ1-42 levels, showing high accuracy in identifying Alzheimer's disease risk.

Revealing heterogeneity of brain imaging phenotypes in Alzheimer’s disease based on unsupervised clustering of blood marker profiles

The paper uses unsupervised clustering of blood marker profiles to identify subgroups in Alzheimer’s disease and shows differences in brain imaging phenotypes across these subgroups.

Predicting time to dementia using a quantitative template of disease progression

The paper predicts dementia onset age using a Bayesian model of biomarker trajectories in Alzheimer's disease.

Associations between vascular risk factors and brain MRI indices in UK Biobank

This study examines associations between vascular risk factors and brain MRI indices in UK Biobank, finding that higher vascular risk is linked to poorer brain health across macro- and microstructural measures.

Blood and Brain Gene Expression Trajectories Underlying Neuropathology and Cognitive Impairment in Neurodegeneration

This paper introduces a novel GE contrastive trajectory inference method to analyze gene expression patterns in neurodegenerative diseases, showing strong predictive power for neuropathology and cognitive decline using blood and brain data.

Identification of a simple and novel cut-point based CSF and MRI signature for predicting Alzheimer disease progression that reinforces the 2018 NIA-AA research framework

The paper identifies a novel 4-marker CSF and MRI signature for predicting Alzheimer's disease progression, reinforcing the 2018 NIA-AA framework with improved accuracy over conventional markers.

Alzheimer’s environmental and genetic risk scores are differentially associated with ‘g’ and δ

This study examines the association of environmental and genetic risk scores with cognitive performance in older adults, finding the environmental risk index more strongly linked to dementia-related cognitive decline.

SNIPE score can capture prodromal Alzheimer's in cognitively normal subjects

This study compares hippocampal volume and SNIPE score to predict dementia onset in cognitively normal individuals, finding SNIPE score has a larger effect size in distinguishing progressors.

Integrated Cognitive Assessment: Speed and Accuracy of Visual Processing as a Reliable Proxy to Cognitive Performance

The paper develops a 5-minute computerized cognitive assessment tool (ICA) that reliably measures cognitive performance through visual processing speed and accuracy, showing strong correlation with standard tests.