One of the primary steps in exploring resting-state functional connectivity MRI is to identify and remove the global signal (GS). Plenty of methods have been proposed for this. However, the majority of them are based on an averaging approach known to produce spurious connectivity values. In this work, we used a nonlinear adaptive method to construct voxel-specific GS. The method is tested for task-positive, task-negative and reference ROIs by computing the Pearson correlation coefficient. Our results show a high level of precision for the proposed approach, while the conventional method could not provide an accurate brain functional mapping.
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