| dc.description.abstract | Background: Mnemonic discrimination (MD) involves distinguishing new stimuli
from memories of highly similar “lure” items or events, and is a putative indirect
probe of dentate gyrus functioning. MD is impaired in the elderly and in individuals
with hippocampal lesions, schizophrenia, major depressive disorder, and Alzheimer’s
disease. The gold-standard MD test, called the mnemonic similarity task (MST), is
rarely used in clinical research. We thus aimed to demonstrate convergent validity
between the MST’s MD measure and a novel analysis method that extracts informa-
tion about MD that could be used in widely clinically used recognition memory tests
that do not have categorical distinctions between “lures” and “foils.”
Methods: By fitting a logistic function to the relationship between stimulus inter-
ference and the probability of classifying a stimulus as novel, at the single participant
level, we derived participant-level indices of MD (λ) and overall recognition memory
performance (∆). We applied the novel measures to MST data from two indepen-
dent datasets (N=18; N=67), and to synthetic MST data. Using linear mixed-effects
modelling, we sought to confirm that λ predicts the MST’s lure discrimination index
(LDI), while ∆ predicts the MST’s overall recognition memory index (REC).
Results: Across all datasets, λ predicted LDI (β=0.76, 95% CI [0.62-0.91], p<0.001),
but not REC (β=0.06, 95% CI [-0.03-0.15], p=0197), while ∆ predicted REC (β=0.93,
95% CI [0.83-1.02], p<0.001), but not LDI (β=-0.06, 95% CI [-0.20-0.09], p=0.438).
The λ and ∆ indices were not correlated. Simulations suggest that λ may be more
robustly estimated in participants with stronger overall recognition performance.
Conclusion: Our novel measure accurately indexes MD, without correlating with
overall recognition memory performance. Future studies should apply it to large
clinical datasets with widely used recognition memory tests. | en_US |
