![]() In a fMRI experiment, subjects are put inside a scanner that measures the dynamics of blood oxygenation in a 3D representation of the brain, divided into around 10,000 volume elements (voxels). This coarse-grained picture can be anatomical – a map of the large-scale wiring diagram between parts of the brain – or functional, indicating which parts of the brain tend to become active together under a given task.īut how should this coarse-graining be done in practice? How to define the nodes of a brain network –– what should brain nodes represent? In functional magnetic resonance imaging (fMRI), the highest level of detail is determined by the imaging technology. Therefore, one needs to zoom out and look at the coarse-grained picture. The problem is that there are about 10^12 of them with ~10^5 outgoing connections each mapping out a network of this scale is not possible. The human brain is a complex network of neurons. Here, we show that this averaging of voxel time series is problematic. Summary: Nodes in brain networks from fMRI are usually defined using ROI’s (Regions of Interest) so that each ROI node has a time series that is the average of the BOLD time series of the ROI’s voxels and links represent correlations between nodes.
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