Browsing by Subject "Learning slopes"

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    Learning slopes in early-onset Alzheimer's disease
    (Wiley, 2023) Hammers, Dustin B.; Nemes, Sára; Diedrich, Taylor; Eloyan, Ani; Kirby, Kala; Aisen, Paul; Kramer, Joel; Nudelman, Kelly; Foroud, Tatiana; Rumbaugh, Malia; Atri, Alireza; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Honig, Lawrence S.; Jones, David T.; Masdeu, Joseph C.; Mendez, Mario F.; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily; Salloway, Steve; Sha, Sharon J.; Turner, Raymond Scott; Weintraub, Sandra; Wingo, Thomas S.; Wolk, David A.; Wong, Bonnie; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; LEADS Consortium; Neurology, School of Medicine
    Objective: Investigation of learning slopes in early-onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early-onset dementia with and without β-amyloid positivity. METHOD: Data from 310 participants in the Longitudinal Early-Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determined. RESULTS: Worse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric-the learning ratio (LR)-outperformed other learning slope calculations across analyses. CONCLUSIONS: Learning slopes appear to be sensitive to early-onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses. Highlights: Learning is impaired in amyloid-positive EOAD, beyond cognitive severity scores alone. Amyloid-positive EOAD participants perform worse on learning slopes than amyloid-negative participants. Learning ratio appears to be the learning metric of choice for EOAD participants.
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    The Relationship Between Learning Slopes and Alzheimer’s Disease Biomarkers in Cognitively Unimpaired Participants with and without Subjective Memory Concerns
    (Taylor & Francis, 2023) Hammers, Dustin B.; Pentchev, Julian V.; Kim, Hee Jin; Spencer, Robert J.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
    Objective: Learning slopes represent serial acquisition of information during list-learning tasks. Although several calculations for learning slopes exist, the Learning Ratio (LR) has recently demonstrated the highest sensitivity toward changes in cognition and Alzheimer's disease (AD) biomarkers. However, investigation of learning slopes in cognitively unimpaired individuals with subjective memory concerns (SMC) has been limited. The current study examines the association of learning slopes to SMC, and the role of SMC in the relationship between learning slopes and AD biomarkers in cognitively unimpaired individuals. Method: Data from 950 cognitively unimpaired participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 89) were used to calculate learning slope metrics. Learning slopes among those with and without SMC were compared with demographic correction, and the relationships of learning slopes with AD biomarkers of bilateral hippocampal volume and β-amyloid pathology were determined. Results: Learning slopes were consistently predictive of hippocampal atrophy and β-amyloid deposition. Results were heightened for LR relative to the other learning slopes. Additionally, interaction analyses revealed different associations between learning slopes and hippocampal volume as a function of SMC status. Conclusions: Learning slopes appear to be sensitive to SMC and AD biomarkers, with SMC status influencing the relationship in cognitively unimpaired participants. These findings advance our knowledge of SMC, and suggest that LR - in particular - can be an important tool for the detection of AD pathology in both SMC and in AD clinical trials.