fMRI Findings Reveal Impact of Head Movement in Multiple Sclerosis Patients

Neglecting data from individuals with multiple sclerosis (MS) who exhibit head movement during functional magnetic resonance imaging (fMRI) scanning may bias sampling away from individuals with lower cognitive ability.

Because head movement during fMRI degrades data quality, data tied to severe movement are frequently ignored as a source of random error, and these authors noted that it is important for researchers to be aware of this potential preconception.

Researchers have shown that discarding data from subjects with MS who exhibit head movement during fMRI scanning may bias sampling away from study subjects with lower cognitive ability. The study’s findings were published in the January 2014 issue of the journal Human Brain Mapping. Glenn Wylie, D.Phil., is associate director of neuroscience in neuropsychology and neuroscience research at the Kessler Foundation (West Orange, NJ, USA). He is also associate director of the Neuroimaging Center at Kessler Foundation, and an associate professor at Rutgers—New Jersey Medical School (Newark, USA).

Because head movement during fMRI degrades data quality, data associated with severe movement is frequently discarded as a source of random error. Kessler Foundation scientists tested this supposition in 34 individual with MS by exploring whether head movement was related to task difficulty and cognitive status. Cognitive status was evaluated by combining performance on a working memory and processing speed task.

“We found an interaction between task difficulty and cognitive status,” explained Dr. Wylie. “As task difficulty increased, there was a linear increase in movement that was larger among subjects with lower cognitive ability.”

Healthy control subjects revealed comparable, although much smaller, effects. This finding indicates that ignoring data with severe movement artifact may bias MS samples so that only individuals with less-severe cognitive deficiency are included in the study. However, even if such data are not discarded outright, subjects who move more will add less to the group-level findings because of the poor quality of their data.

It is important for researchers to be aware of this potential bias. “Some newer scanners can correct for motion,” noted Dr. Wylie. “Another approach is to monitor each subject’s motion parameters and ensure that an adequate number of subjects with low cognition are included. Recruiting a large number of subjects may ensure inclusion of a sufficient number of people with low cognition/low movement. It is however, a costly option.”

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Rutgers--New Jersey Medical School