Functional connectivity networks with and without global signal correction.
1Department of Biostatistical Sciences, Wake Forest School of Medicine Winston-Salem, NC, USA ; Department of Radiology, Wake Forest School of Medicine Winston-Salem, NC, USA.
Frontiers in Human Neuroscience
|January 4, 2014
Summary
Global signal correction in blood oxygen-level dependent (BOLD) functional MRI (fMRI) data significantly impacts network analysis. Uncorrected data shows biased correlations and altered network connectivity, affecting brain network interpretations.
Area of Science:
- Neuroimaging
- Cognitive Neuroscience
- Data Analysis
Background:
- Functional connectivity analysis of BOLD fMRI data is widely used.
- A long-standing debate exists regarding global signal correction in fMRI time series.
- Recent growth in network analysis has intensified this discussion.
Purpose of the Study:
- To systematically investigate the impact of global signal correction on fMRI network analysis.
- To compare functional connectivity networks constructed with and without global signal correction.
Main Methods:
- Voxel-based resting-state fMRI networks were constructed.
- Networks were analyzed both with and without global signal correction.
- Functional connectivity networks were compared.
Main Results:
- Without global signal correction, correlation coefficients showed a positive bias.
- Interhemispheric fissure nodes were hyperconnected in uncorrected data.
- Subgraphs near white-matter tracts became disconnected in uncorrected data.
Conclusions:
- Global signal correction substantially alters functional connectivity network properties.
- Differences observed highlight the importance of considering global signal correction for accurate fMRI network interpretation.
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