Resting-state global brain activity induces bias in fMRI motion estimates

Area of Science:

• Neuroimaging
• Functional Magnetic Resonance Imaging (fMRI)
• Brain Activity Analysis

Background:

• Head motion is a primary artifact source in resting-state fMRI (rsfMRI), impacting functional connectivity (rsFC) measurements.
• Motion parameters are commonly used to correct rsfMRI data, but neural influences on these parameters are not well understood.

Purpose of the Study:

• To investigate and characterize neural-related bias in rsfMRI motion estimates.
• To assess the impact of this bias on rsFC measurements and group comparisons.

Main Methods:

• Utilized a public multi-echo rsfMRI dataset.
• Quantified neural-induced bias by comparing motion estimates between the first and second echo data.
• Analyzed the influence of global signal (GS) on motion estimates and rsFC.

Main Results:

• Demonstrated that resting-state global brain activity (GS) introduces bias in translational motion estimates (y- and z-axes).
• Showed GS-related bias correlates with asymmetries in the GS beta coefficient map.
• Confirmed that regression using biased motion estimates negatively impacts rsFC and reduces age-related differences.

Conclusions:

• Neural activity, specifically the global signal, introduces bias into rsfMRI motion estimates.
• This bias can distort rsFC results, potentially leading to erroneous conclusions, especially in group studies comparing different age demographics.