Related Experiment Video
Updated: Jan 21, 2026
06:44
Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
Published on: September 23, 2025
513
Distributed fMRI Patterns Coupled to Low-Frequency Cardiorespiratory Dynamics Provide Markers of Aging
Shiyu Wang1, Richard Song2,3, Laurent M Lochard4
1Departments of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee 37240 shiyu.wang.1@vanderbilt.edu catie.chang@vanderbilt.edu.
Summary
Aging impacts brain-body connections. Functional magnetic resonance imaging (fMRI) patterns coupled with physiological signals reliably predict age, highlighting autonomic regulation
Area of Science:
- Neuroscience
- Aging Research
- Physiology
Background:
- Aging alters brain-body connections, measurable via functional magnetic resonance imaging (fMRI) and autonomic processes.
- Previous studies noted age-related changes in associations between specific brain regions and physiological activity.
- The interplay between brain activity and physiological signals is increasingly recognized as significant, moving beyond 'noise' interpretation.
Purpose of the Study:
- To investigate age-related changes in whole-brain spatial fMRI patterns linked to low-frequency physiological processes.
- To determine if these fMRI-physiology coupling patterns can predict chronological age across the adult lifespan.
- To identify brain regions most influential in predicting age based on fMRI-physiology coupling.
Main Methods:
- Analysis of functional magnetic resonance imaging (fMRI) data from human participants across the adult lifespan.
- Examination of whole-brain spatial patterns of fMRI-physiology coupling, focusing on low-frequency heart rate and respiratory volume fluctuations.
- Statistical prediction of chronological age from fMRI-physiology coupling patterns, controlling for physiological signal characteristics and brain anatomy.
Main Results:
- Chronological age was statistically predictable from low-frequency fMRI-physiology coupling patterns.
- Brain regions involved in central autonomic regulation (e.g., insula, middle cingulate cortex) were key predictors of age.
- Residual blood oxygen level-dependent (BOLD) signal variability, even after accounting for physiological effects, remained a reliable age indicator.
Conclusions:
- fMRI-physiology coupling patterns reveal generalizable age-related changes in brain-body integration.
- This coupling serves as a potential biomarker for the aging process, reflecting changes in autonomic function and brain vascular health.
- The findings emphasize the significance of brain-body interactions in understanding aging and potential disease-related disruptions.
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