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Member Research & Reports

Member Research & Reports

Washington: Biostatistician Contributes to New Statistical Approach to More Accurately Assess Brain Function and Health

A recent University of Washington study unveiled a new statistical method that was able to analyze human brain white matter to accurately classify patients with amyotrophic lateral sclerosis (ALS) in one dataset and designate “brain age” in another. The method uses a technique developed by Dr. Noah Simon, an associate professor of biostatistics at the University of Washington School of Public Health, who was also a co-author of the study.

White matter contains long-range connections between different brain regions. The organization of these connections reveals information about brain function and health, providing insight into cognitive skills and predicting clinical symptoms across a variety of psychiatric and neurological disorders.

Prior statistical inference approaches from tractometry, a method that uses diffusion-weighted magnetic resonance, or dMRI, data to quantify brain tissue properties, have been limited in either sensitivity or statistical power. The new method resolves these issues by using a regularization technique developed by Dr. Simon, called Sparse Group Lasso.

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