Abstract
The differences in how our brain is connected are often thought to reflect the differences in our individual personalities and cognitive abilities. Individual differences in brain connectivity has long been recognized in the neuroscience community however it has yet to manifest itself in the methodology of resting state analysis. This is evident as previous studies use the same region of interest (ROIs) for all subjects. In this paper we demonstrate that the use of ROIs which are standardized across individuals leads to inaccurate calculations of functional connectivity. We also show that this problem can be addressed by taking an individualized approach by using subject-specific ROIs. Finally we show that ROI selection can affect the way we interpret our data by showing different changes in functional connectivity with aging.
Highlights
An important aspect of network analysis and graph theory in brain imaging is node definition (Smith et al, 2011; Shen et al, 2013)
We found that average calculated connectivity is lower when region of interest (ROIs) fell outside the anterior default mode network (aDMN) and high when the ROIs are inside the aDMN (Figure 2B)
We found that by using subject-specific ROIs, we were able to obtain higher correlations and lower variance compared to using ROIs that were based on group averages or previous research (Figure 2A, Supplementary Figure 2)
Summary
An important aspect of network analysis and graph theory in brain imaging is node definition (Smith et al, 2011; Shen et al, 2013). These nodes represent neural populations in the brain which have shared structural or functional relevance (Sporns et al, 2004; Bullmore and Sporns, 2009). The human lifespan is characterized by the initial development and later decline of cognitive abilities from adolescence through aging These changes in our cognitive abilities are thought to be representative of changes in the functional organization of our brains
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