What Correlates with Your Connectome?
Jessica S. Damoiseaux1

1Wayne State University

Synopsis

Since the introduction of functional and structural connectivity approaches, MRI has been used to assess age-related differences on a brain network level. A systems-level or network approach of brain structure and function provides an intuitive framework for understanding a complex dynamic system. In this talk I will discuss previous research that used MRI to study the effect of aging on brain networks in vivo, through functional connectivity measures derived from resting-state functional MRI and structural connectivity measures derived from diffusion MRI.

Purpose

To discuss the application of functional and structural brain connectivity measures to assess the effects of aging on the brain.

Background

The observed connectivity differences/changes seem to particularly affect the default mode network, resulting in lower within-network connectivity in older adults. Furthermore, this decreased functional connectivity in older adults appears to be related to cognitive decline. Results from whole brain analyses suggest a central role for default mode regions in our brain system, as key members of the brain's “rich club”. This “rich club” organization appears lower in older adults, possibly reflecting lower network efficiency and differences in brain dynamics. Network approaches also indicate a whole brain network-wide pattern of age-related functional and structural connectivity differences/changes, revealing lower within- and higher between-network connectivity and less system segregation in older adults. Overall, structural and functional connectivity seem to be strongly associated and similarly affected by older age.

Network analyses have contributed to an increased understanding of age-related brain changes, but some important inconsistencies and challenges remain. Future research can address some of these issues by increasing the number of longitudinal studies, examining the effect of network definition on network measures, and comparing multiple brain indices within the same dataset.

Acknowledgements

References

Proc. Intl. Soc. Mag. Reson. Med. 25 (2017)