ArticleHuman brain mapping2020
Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.
Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 58 citations in OpenAlex.
- Macroscale Gradient Dysfunction in Alzheimer's Disease: Patterns With Cognition Terms and Gene Expression Profiles.Human brain mapping · 2024Pooled it
- Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review.Human brain mapping · 2021Pooled it
- Human brain connectome profiles mediate the relationship between pathology burden and clinical phenotypes in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Propofol and dexmedetomidine sedation share the similar functional activity but distinct functional synchronization.Scientific reports · 2026Article
- Multimodal Classification of Alzheimer's Disease Using Longitudinal Data Analysis and Hypergraph Regularized Multi-Task Feature Selection.Bioengineering (Basel, Switzerland) · 2025Article
- Structure-function coupling reveals the brain hierarchical structure dysfunction in Alzheimer's disease: A multicenter study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- fMRI-based Alzheimer's disease detection via functional connectivity analysis: a systematic review.PeerJ. Computer science · 2024Article
- Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks.Brain : a journal of neurology · 2023Article
- Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease.Neuroscience bulletin · 2023Article
- Altered large-scale dynamic connectivity patterns in Alzheimer's disease and mild cognitive impairment patients: A machine learning study.Human brain mapping · 2023Article
- Neuropsychiatric Symptoms and Commonly Used Biomarkers of Alzheimer's Disease: A Literature Review from a Machine Learning Perspective.Journal of Alzheimer's disease : JAD · 2023Review
- BNLoop-GAN: a multi-loop generative adversarial model on brain network learning to classify Alzheimer's disease.Frontiers in neuroscience · 2023Review
- Brain disease research based on functional magnetic resonance imaging data and machine learning: a review.Frontiers in neuroscience · 2023Review
- Neuroimaging modalities in the detection of Alzheimer's disease-associated biomarkers.Psychoradiology · 2023Review
- Altered Functional Connectivity of Basal Ganglia in Mild Cognitive Impairment and Alzheimer's Disease.Brain sciences · 2022Article
- Classification of Parkinson's disease using a region-of-interest- and resting-state functional magnetic resonance imaging-based radiomics approach.Brain imaging and behavior · 2022Article
- Impaired time-distance reconfiguration patterns in Alzheimer's disease: a dynamic functional connectivity study with 809 individuals from 7 sites.BMC bioinformatics · 2022Article
- Machine Learning for Detecting Parkinson's Disease by Resting-State Functional Magnetic Resonance Imaging: A Multicenter Radiomics Analysis.Frontiers in aging neuroscience · 2022Article
- Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2021Review
- Machine Learning of Schizophrenia Detection with Structural and Functional Neuroimaging.Disease markers · 2021Article
Corrections and comments
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Authors and funding
22 authors at 8 institutions in 2 countries.
Funding
Abstract
Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to elucidate the core disease mechanisms. In this study, we aim to comprehensively characterize AD-associated functional brain alterations using one of the world's largest resting-state functional MRI (fMRI) biobank for the disorder. The biobank includes fMRI data from six neuroimaging centers, with a total of 252 AD patients, 221 mild cognitive impairment (MCI) patients and 215 healthy comparison individuals. Meta-analytic techniques were used to unveil reliable differences in brain function among the three groups. Relative to the healthy comparison group, AD was associated with significantly reduced functional connectivity and local activity in the default-mode network, basal ganglia and cingulate gyrus, along with increased connectivity or local activity in the prefrontal lobe and hippocampus (p < .05, Bonferroni corrected). Moreover, these functional alterations were significantly correlated with the degree of cognitive impairment (AD and MCI groups) and amyloid-β burden. Machine learning models were trained to recognize key fMRI features to predict individual diagnostic status and clinical score. Leave-one-site-out cross-validation established that diagnostic status (mean area under the receiver operating characteristic curve: 0.85) and clinical score (mean correlation coefficient between predicted and actual Mini-Mental State Examination scores: 0.56, p < .0001) could be predicted with high accuracy. Collectively, our findings highlight the potential for a reproducible and generalizable functional brain imaging biomarker to aid the early diagnosis of AD and track its progression.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.