Onerva Korhonen (Aalto)
Thursday 2017-11-09 12.15 – 13.00
Seminar room T5, T-building
Regions of Interest as nodes of dynamic functional brain networks
The properties of functional brain networks strongly depend on how their nodes are chosen. Commonly, nodes are defined by Regions of Interest (ROIs), pre-determined groupings of fMRI measurement voxels. Earlier, we have demonstrated that the functional homogeneity of ROIs, captured by their spatial consistency, varies widely across ROIS in commonly-used brain atlases. Here, we ask how ROIs behave as nodes of dynamic brain networks. To this end, we use two measures: spatiotemporal consistency measures changes in spatial consistency across time and network turnover quantifies the changes in the local network structure around a ROI. We find that spatial consistency varies non-uniformly in space and time, which is reflected in the variation of spatiotemporal consistency across ROIs. Further, we see time-dependent changes in the ROIs’ network neighborhoods, resulting in high network turnover. This turnover is nonuniformly distributed across ROIs: ROIs with high spatiotemporal consistency have low network turnover. Finally, we reveal rich internal, voxel-level correlation structure inside ROIs.Because the internal structure and connectivity of ROIs vary in time, the common approach of using static node definitions may be surprisingly inaccurate. Therefore, network neuroscience would greatly benefit from node definition strategies tailored for dynamical networks.
Article in arXiv: https://arxiv.org/abs/1710.04056