Age-related Differences in Default-mode Network Connectivity

Abstract

In recent decades, one of the focuses of interest in Neuroscience has been studying the patterns of neuronal activity and identifying networks within the brain. A well-known example of such a network is the Default Mode Network (DMN). Its subnetworks are involved in higher-order cognition which allows for theorizing about the role of the DMN in cognitive processes [1]. The activity of the DMN has been linked to a wide range of functions, such as memory, decision-making, social cognition, daydreaming, and creativity [2]. Research on age-related differences in the functional connectivity (FC) of the DMN has shown a significant decrease in connectivity between anterior and posterior regions [3]. However, the correlation can be both linear and non-linear. Studying these changes in FC as people age could provide insight into brain disorders and disruptions in cognitive functions. This research intends to investigate how FC within the DMN changes with age using the graph topology analysis to measure how the regions of the DMN assemble in space. It is hypothesized that these measures will differ between the young and elderly adults.

This study uses resting state fMRI (rs-fMRI) data acquired on 3 Tesla scanner equipped with a 32-channel head coil. Two hundred and twenty-seven healthy participants formed two groups: young adults (N=153, 25.1±3.1 years, range 20–35 years, 45 female) and elderly adults (N=74, 67.6±4.7 years, range 59–77 years, 37 female). The total time of rs-fMRI was 15 min 30 s. The participants were instructed to remain awake during that time. This dataset is publicly available as a part of the MPI-Leipzig Mind-Brain-Body database.

The goal of this study is to better understand changes in functional connectivity within the DMN as a function of age, and to investigate potential implications for cognitive functions and disorders. The topological data analysis will be implemented as the main method. The study will involve defining network nodes and links between them, generating a graph, and analyzing the graph's topology for two different age groups. Each node will represent a voxel, and the links between nodes will be defined. The analysis will evaluate various characteristics, including node degree, number of nodes, clustering coefficient, path length, global efficiency, and small-world index.

References

[1] J. M. Kernbach et al., “Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants,” Proceedings of the National Academy of Sciences, vol. 115, no. 48, pp. 12295–12300, 2018. doi:10.1073/pnas.1804876115

[2] J. Smallwood et al., “The default mode network in Cognition: A Topographical Perspective,” Nature Reviews Neuroscience, vol. 22, no. 8, pp. 503–513, 2021. doi:10.1038/s41583-021-00474-4

[3] M. De Marco, S. Ourselin, and A. Venneri, “Age and hippocampal volume predict distinct parts of default mode network activity,” Scientific Reports, vol. 9, no. 1, 2019. doi:10.1038/s41598-019-52488-9