Due to its non-invasive nature, magnetic resonance spectroscopy is a promising tool for investigating neurochemical disease processes, monitoring potential therapy responses, and diagnosis of Alzheimer’s disease (AD). Changes of γ-amino-butyric acid (GABA) and glutamate (Glu) concentrations have been associated with AD, however, their relationship to other disease parameters is still unknown. This work aims to investigate the relationship of GABA and Glu with cognitive measures and demonstrates that the application of Rasch transformation to cognitive assessment data yields more reliable descriptions of cognitive outcome using metabolite concentrations as explanatory variables.
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