ArticleHuman brain mapping2018
Structure-function multi-scale connectomics reveals a major role of the fronto-striato-thalamic circuit in brain aging.
Article in Human brain mapping, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Factors associated with brain ageing - a systematic review.BMC neurology · 2021Pooled it
- Mapping Neuroanatomical Heterogeneity of Brain Aging Within a Clinically Defined Aging Reference Cohort.Bioengineering (Basel, Switzerland) · 2026Article
- Structure-function dynamics in healthy cognitive aging: a graph signal processing approach.Brain structure & function · 2026Article
- Connectivity of the adult human brain with sequential neurogenesis of circuits and transcriptomics signatures.Nature communications · 2025Article
- Senolytics as Modulators of Critical Signaling Pathways: a Promising Strategy to Combat Brain Aging and Neurodegenerative Disorders.Molecular neurobiology · 2025Review
- Aging as an active player in Alzheimer's disease classification: Insights from feature selection in BrainAge models.NeuroImage · 2025Article
- Aging as an active player in Alzheimer's Disease Classification: Insights from feature selection in BrainAge Models.medRxiv : the preprint server for health sciences · 2025Article
- Combining functional, structural, and morphological networks for multimodal classification of developing autistic brains.Brain imaging and behavior · 2025Article
- The negative relationship between brain-age gap and psychological resilience defines the age-related neurocognitive status in older people.GeroScience · 2025Article
- Normative aging results in degradation of gene networks in a zebra finch basal ganglia nucleus dedicated to vocal behavior.Neurobiology of aging · 2025Article
- Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain.Scientific data · 2024Article
- Article
- Quantifying neuroinflammation within deep gray matter in small vessel disease using diffusion tensor based free-water imaging: a longitudinal study.Frontiers in aging neuroscience · 2024Article
- High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model.PLoS computational biology · 2022Article
- Age-related changes in medial septal cholinergic and GABAergic projection neurons and hippocampal neurotransmitter receptors: relationship with memory impairment.Experimental brain research · 2022Article
- Amyloid-β and tau pathologies relate to distinctive brain dysconnectomics in preclinical autosomal-dominant Alzheimer's disease.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- No evidence for a difference in lateralization and distinctiveness level of transcranial magnetic stimulation-derived cortical motor representations over the adult lifespan.Frontiers in aging neuroscience · 2022Article
- Brain age predicts long-term recovery in post-stroke aphasia.Brain communications · 2022Article
- Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis.Frontiers in neuroscience · 2022Article
- Integrating across neuroimaging modalities boosts prediction accuracy of cognitive ability.PLoS computational biology · 2021Article
Corrections and comments
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9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Physiological aging affects brain structure and function impacting morphology, connectivity, and performance. However, whether some brain connectivity metrics might reflect the age of an individual is still unclear. Here, we collected brain images from healthy participants (N = 155) ranging from 10 to 80 years to build functional (resting state) and structural (tractography) connectivity matrices, both data sets combined to obtain different connectivity features. We then calculated the brain connectome age-an age estimator resulting from a multi-scale methodology applied to the structure-function connectome, and compared it to the chronological age (ChA). Our results were twofold. First, we found that aging widely affects the connectivity of multiple structures, such as anterior cingulate and medial prefrontal cortices, basal ganglia, thalamus, insula, cingulum, hippocampus, parahippocampus, occipital cortex, fusiform, precuneus, and temporal pole. Second, we found that the connectivity between basal ganglia and thalamus to frontal areas, also known as the fronto-striato-thalamic (FST) circuit, makes the major contribution to age estimation. In conclusion, our results highlight the key role played by the FST circuit in the process of healthy aging. Notably, the same methodology can be generally applied to identify the structural-functional connectivity patterns correlating to other biomarkers than ChA.
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