The impact of in-scanner head motion on structural connectivity derived from diffusion MRI

Area of Science:

• Neuroimaging
• Developmental Neuroscience
• Network Science

Background:

• Data quality is crucial for brain network construction from MRI.
• Head motion is a known confounder in functional MRI studies, especially in developing brains.
• The impact of head motion on structural connectivity from diffusion MRI is less understood.

Purpose of the Study:

• To evaluate how in-scanner head motion affects structural connectivity estimates.
• To investigate if head motion confounds developmental inferences in structural brain networks.
• To characterize the motion-dependent biases in structural connectivity.

Main Methods:

• Analyzed diffusion MRI data from 949 participants (ages 8-23) from the Philadelphia Neurodevelopmental Cohort.
• Constructed structural brain networks using deterministic and probabilistic tractography.
• Assessed the impact of head motion on network edge strength, consistency, and length.

Main Results:

• In-scanner head motion significantly altered structural connectivity strength, even after quality assurance and corrections.
• Increased motion reduced connectivity estimates for high-consistency edges (short and long-range).
• Motion inflated connectivity estimates for low-consistency, shorter-range edges, and confounded age-related developmental findings.

Conclusions:

• Head motion systematically biases structural connectivity estimates in a consistency- and length-dependent manner.
• Age-related motion differences can obscure or inflate developmental trajectories of brain networks.
• These findings highlight the need to carefully consider motion artifacts in diffusion MRI studies of brain development.