A longitudinal resource for mapping interindividual variation in the aging connectome

Area of Science:

• Neuroscience
• Aging Research
• Cognitive Science

Background:

• Neurocognitive decline trajectories vary and are influenced by environmental and physiological factors.
• Midlife represents a critical transition period with increasing individual variability in functioning.
• Existing neuroimaging data resources underrepresent this crucial midlife period.

Purpose of the Study:

• To introduce the Mapping Interindividual Variation in the Aging Connectome (MIVAC) dataset.
• To facilitate the study of brain aging trajectories starting in midlife.
• To assess the impact of modifiable factors (cardiorespiratory fitness, sleep, mood) on dementia prevention.

Main Methods:

• Longitudinal study of 348 community-ascertained participants (aged 38-71 at baseline).
• 219 participants completed 3 annual timepoints.
• Deep phenotyping including cognitive, behavioral, medical, and cardiorespiratory fitness assessments.
• Multimodal neuroimaging (rs-fMRI, dMRI, morphometric MRI, ASL) and biospecimen collection.
• Data harmonization with prior NKI-RS studies for lifespan analyses.

Main Results:

• The MIVAC dataset provides a comprehensive, openly available resource.
• It enables mapping of brain aging trajectories beginning in midlife.
• It allows investigation into factors influencing cognitive and neural aging.

Conclusions:

• The MIVAC dataset addresses a critical gap in midlife neuroimaging research.
• It supports research into dementia prevention by examining modifiable factors.
• The open-access nature promotes further investigation into interindividual variation in aging.