Poster Session 02 Program Schedule
02/15/2024
08:00 am - 09:15 am
Room: Shubert Complex (Posters 1-60)
Poster Session 02: Aging | MCI | Neurodegenerative Disease - PART 1
Final Abstract #22
Using the Drift Diffusion Model to Investigate the Relationship of Alzheimer's Disease Biomarkers with Impaired Older Adults' Performance on a Paired Associates Task
Madelyn Eckel, University of Michigan, Ann Arbor, United States
Alexander Weigard, University of Michigan, Ann Arbor, United States
Benjamin Hampstead, University of Michigan, Ann Arbor, United States
Category: Dementia (Alzheimer's Disease)
Keyword 1: dementia - Alzheimer's disease
Keyword 2: mild cognitive impairment
Keyword 3: positron emission tomography
Objective:
Paired associates tasks are a measure of episodic memory and are typically used to evaluate the accuracy of a binary decision (i.e., correct vs. incorrectly recalled/rejected), and response time (RT). Mathematical models of choice response time that estimate mechanistic parameters that determine task performance may improve our understanding about the cognitive mechanisms underlying performance. The Drift Diffusion Model (DDM) allows researchers to estimate participant’s drift rate, or their efficiency of evidence accumulation (EEA) during PA choices. EEA reflects the quality of individuals’ memory representations as separate from confounding variables such as response strategy, early perceptual processes, and motor speed (Voss et al., 2013). Previous research has established that participants with family history of Alzheimer’s Disease (AD), tend to have more impaired EEA compared to those without, even when accounting for the apolipoprotein E (APOE) ε4 allele, suggesting drift rate can help identify the presence of AD before the emergence of cognitive decline (Aschenbrenner et al., 2015). AD is typically identified by increased concentration of the biomarker proteins amyloid (Aβ) and tau. In this study we evaluated EEA as a function of amyloid and tau status (i.e., positive vs. negative) in patients with amnestic mild cognitive impairment (aMCI) and dementia of the Alzheimer’s type (DAT).
Participants and Methods:
Participants (age≥55) with a diagnosis of aMCI or DAT were enrolled as part of a larger treatment study. At their baseline visit they completed our paired associates task, which required them to encode and subsequently identify 60 unique word pairs. 99 Participants completed positron emission tomography scans for Aβ and the other for tau. We estimated DDM parameters using trial-level data from PA task performance. We compared average EEA using an ANOVA based on dichotomous biomarker status: amyloid and tau negative (A-T-)(n=27), amyloid positive and tau negative (A+T-)(n=29), and amyloid and tau positive (A+T+)(n=43).
Results:
Biomarker status has a significant main effect on EEA (F(2, 96) = 4.23, p = 0.02). A post hoc Tukey test revealed that A+T+ participants had significantly lower EEA compared to A+T- participants; but had no significant difference from A-T- participants. There was no statistically significant difference found between A+T- and A-T- participants.
Conclusions:
Our findings reflect the larger literature showing cognitive decline once tau becomes elevated. The A-T- group performed in between the other two groups and raises the possibility that the cognitive deficits were due to a non-Alzheimer’s disease etiology. Future work will evaluate this possibility using blood-based biomarkers and brain volume measures of neurodegeneration. We also plan to compare the sensitivity of EEA with traditional memory test performances.
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