Decreased spatial correspondence of individualized networks with group networks in older adults
Poster No:
904
Submission Type:
Abstract Submission
Authors:
Diana Perez1, Ashley Jaimes2, Mackenzie Mitchell2, Gretchen Wulfekuhle3, Joanna Hernandez4, Caterina Gratton5,6
Institutions:
1Northwestern University, Chicago, IL, 2Florida State University, Tallahassee, FL, 3University of North Carolina, Chapel Hill, NC, 4Harvard University, Cambridge, MA, 5University of Illinois, Urbana-Champaign, Champaign, IL, 6Northwestern University, Evanston, IL
First Author:
Co-Author(s):
Caterina Gratton
University of Illinois, Urbana-Champaign|Northwestern University
Champaign, IL|Evanston, IL
University of Illinois, Urbana-Champaign|Northwestern University
Champaign, IL|Evanston, IL
Introduction:
The brain is organized into multiple large-scale distributed networks. The interactions within and across networks give rise to cognition and behavior. Recent findings have shown that individuals vary widely in the topology of brain networks, particularly of higher-order association systems (Gordon et al., 2017). Similarly, past research has suggested that large-scale networks change with aging, with networks becoming relatively desegregated from one another, even in the absence of disease (Chan et al., 2014). Despite this, most research examining age-related differences in the brain uses group-derived network partitions (typically based on young adult data) to extract measures of functional networks. This approach, while convenient, can introduce further noise by combining signals from different networks when the individual networks deviate from the group average. Age-related changes to the spatial organization of networks may lead to systematic differences in the "goodness of fit" of group-based network representations in older adults, exacerbating these issues. Here, we compare measures of spatial correspondence (via dice coefficient) between individualized networks in young and older adults with the Power group average networks (Power et al., 2011), a commonly used atlas based on data from younger adults.
Methods:
We used two precision fMRI datasets of younger (n = 46; ages 18-30) and older (n=8; ages 65-75) adults with >90 min. of high-quality rs-FC data per subject. Networks were defined based on each individual's rs-FC patterns. The large amount of data per individual allowed us to produce highly reliable representations of individual-specific networks. For each participant and for each network, we calculated the dice coefficient between the individualized network and the group-average network. We used two-sample t-tests to determine statistical significance. Results were replicated with two additional datasets of younger (n=43; ages 18-35) and older (n=22; ages 60-75) adults with >90 min. of high-quality rs-FC data per subject.
Results:
Our results indicate that on average older adults show lower dice coefficients between individualized and group-average networks (p(FDR)<0.001) compared to younger adults (Figure 1), indicating lower spatial correspondence with the group-average networks. This result also arose in the replication datasets (p(FDR)<0.0001). Multiple networks showed significant differences between young and older adults in their individualized and group-average networks: the visual (p(FDR)<0.01), cingulo-opercular (p(FDR)<0.001), somatomotor lateral (p(FDR)<0.02) and dorsal (p(FDR)<0.005), and auditory (p(FDR)<0.005) networks showed significantly decreased spatial correspondence in older adults compared to young adults (Figure 2). These results were replicated in the replication datasets. The dorsal attention and language networks also showed differences across age-groups, but these comparisons did not survive FDR correction in either the original or replication comparisons.
·Figure 1
·Figure 2
Conclusions:
Our results suggest that the spatial organization of networks changes across the lifespan, with older adults showing decreased spatial correspondence with a group-average network representation. This result has implications for research examining age-related changes in the functional connectivity of the brain: an age-related difference in the fit of a group-average network atlas could lead to biased results due to the use of group-average network templates that systematically fit older participants more poorly compared to younger ones. This suggests that the use of group-average networks based on participants of similar ages, or individual-specific networks, may be more appropriate.
Lifespan Development:
Aging 1
Modeling and Analysis Methods:
fMRI Connectivity and Network Modeling 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Aging
FUNCTIONAL MRI
Other - Functional Networks
1|2Indicates the priority used for review
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Provide references using APA citation style.
Gordon, E. M., Laumann, T. O., Adeyemo, B., & Petersen, S. E. (2017). Individual Variability of the System-Level Organization of the Human Brain. 14. https://doi.org/10.1093/cercor/bhv239
Power, J. D., Cohen, A. L., Nelson, S. M., Wig, G. S., Barnes, K. A., Church, J. A., Vogel, A. C., Laumann, T. O., Miezin, F. M., Schlaggar, B. L., & Petersen, S. E. (2011). Functional Network Organization of the Human Brain. Neuron, 72(4), 665–678. https://doi.org/10.1016/j.neuron.2011.09.006