ArticleProceedings of the National Academy of Sciences of the United States of America2018
Genetically defined cellular correlates of the baseline brain MRI signal.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- AI-powered Gradient Echo Plural Contrast Imaging (AI-GEPCI) - a Comprehensive Multiparametric Neurological Protocol from a Single MRI Scan.medRxiv : the preprint server for health sciences · 2026Article
- Automatic design and optimization of MRI-based neurochemical sensors via reinforcement learning.Discover nano · 2025Article
- Unraveling the major role of vascular (R2') contributions to R2* signal relaxation at ultra-high-field MRI: A comprehensive analysis with quantitative gradient recalled echo in mouse brain.Magnetic resonance in medicine · 2025Article
- CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping.Journal of mathematical imaging and vision · 2025Article
- Intrinsic Gene Expression Correlates of the Biophysically Modeled Diffusion Magnetic Resonance Imaging Signal.Biological psychiatry global open science · 2025Article
- Increased periventricular thalamic damage gradient in multiple sclerosis detected by quantitative gradient echo MRI.Multiple sclerosis and related disorders · 2024Article
- Quantitative gradient recalled echo (qGRE) MRI enables in vivo measurement of pre-atrophic neurodegeneration in a mouse model of Alzheimer's disease.NeuroImage · 2024Article
- High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain.NeuroImage · 2024Article
- T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease.Human brain mapping · 2023Observational
- Functional alteration due to structural damage is network dependent: insight from multiple sclerosis.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Quantitative MRI identifies lesional and non-lesional abnormalities in MOGAD.Multiple sclerosis and related disorders · 2023Article
- Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Linking resting-state network fluctuations with systems of coherent synaptic density: A multimodal fMRI andFrontiers in human neuroscience · 2023Article
- Tissue damage detected by quantitative gradient echo MRI correlates with clinical progression in non-relapsing progressive MS.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Article
- Stronger Microstructural Damage Revealed in Multiple Sclerosis Lesions With Central Vein Sign by Quantitative Gradient Echo MRI.Journal of central nervous system disease · 2022Article
- Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tisssue Atrophy in Early Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2022Article
- The Role of the Human Brain Neuron-Glia-Synapse Composition in Forming Resting-State Functional Connectivity Networks.Brain sciences · 2021Article
- Relating quantitative 7T MRI across cortical depths to cytoarchitectonics, gene expression and connectomics.Human brain mapping · 2021Article
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5 authors.
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Abstract
fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease.
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