Abstract Objective Learning slopes (LS) indicate the learning rate (LR) when individuals are repeatedly exposed to the same information across trials. Traditionally, the LR is calculated by measuring the difference between the last and first trials (formula 1). A novel formula (formula 2) was developed to calculate the LR, where the number of words learned after the first trial is divided by the number of words yet to be learned. This study compared the two methods of calculating changes in cognitive performance with the aim of achieving higher accuracy from Formula 2. Method Participants (N=256) completed the Hopkins Verbal Learning Test (HVLT), an MRI, and PET scan at Mount Sinai Medical Center in Miami Beach as part of the 1Florida ADRC (M=71.59 years, SD = 7.80), and were diagnosed as Cognitively Normal (CN; n=87), Mild Cognitive Impairment (MCI; n=127), or dementia (n=42). A 3 (diagnosis) x 2 (formula type) ANCOVA determined outcomes for LR accuracy from the HVLT. Results Correlations showed associations between the formulas, right and left normalized hippocampal volumes, and beta-amyloid (centiloid) while controlling for covariates. Formula 2 showed larger group differences across all diagnoses (p .001), unlike Formula 1, which demonstrated significant differences between CN and MCI. Formula 2 was significantly negatively correlated with amyloid, r(152) =-.264, p .001, and positively correlated with right and left hippocampal volumes. Conclusion Formula 2 showed greater sensitivity to the underlying biomarkers than formula 1, which contributes to developing more effective diagnostic and intervention tools for MCI and dementia.
Montilla et al. (Fri,) studied this question.