Towards a consensus regarding global signal regression for resting state functional connectivity MRI

Area of Science:

• Neuroimaging
• Cognitive Neuroscience
• Data Science

Background:

• Resting state functional connectivity MRI studies are rapidly increasing.
• Global signal regression (GSR) is a controversial data processing technique.
• GSR has led to debate and confusion regarding negative correlations (anti-correlations).

Purpose of the Study:

• To work towards a consensus on global signal regression in resting state fMRI.
• To clarify the impact of different processing strategies on brain functional organization.
• To address confusion and contradictory guidelines surrounding GSR.

Main Methods:

• Review and synthesis of current literature on resting state fMRI processing.
• Analysis of the implications of global signal regression.
• Discussion of various data processing strategies and their outcomes.

Main Results:

• There is agreement that no single processing method reveals the "true" nature of the brain.
• Different processing approaches, including GSR, can reveal complementary insights.
• The debate has spurred advancements in processing strategies.

Conclusions:

• A consensus is emerging regarding the interpretation of global signal regression.
• Understanding the brain's functional organization requires considering multiple processing perspectives.
• Further research is needed to fully elucidate the impact of various processing choices.