Anatomy and Cell Biology Publications

Document Type

Article

Publication Date

3-12-2019

Issue

11

Journal

Frontiers in Aging Neuroscience

Volume

11

First Page

1

Last Page

9

URL with Digital Object Identifier

https://doi.org/10.3389/fnagi.2019.00046

Abstract

The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or "BOLDSD", is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan.

Notes

First published in Frontiers Media.

Pur, Daiana R., Eagleson, Roy A., de Ribaupierre, Anik, Mella, Nathalie, de Ribaupierre, Sandrine (2019). Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes. Frontiers in Aging Neuroscience vol11, pp1-9.https://doi.org/10.3389/fnagi.2019.00046.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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