Multivariate pattern analysis techniques have been increasingly used over the past decade
to derive highly sensitive and specific biomarkers of diseases on an individual basis. The
driving assumption behind the vast majority of the existing methodologies is that a single
imaging pattern can distinguish between healthy and diseased populations, or between two
subgroups of patients (eg, progressors vs. non-progressors). This assumption effectively
ignores the ample evidence for the heterogeneous nature of brain diseases …