Journal
ALZHEIMER DISEASE & ASSOCIATED DISORDERS
Volume 27, Issue 1, Pages 16-22Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/WAD.0b013e31824d5668
Keywords
neuropsychological testing; wordlist memory; recognition memory; functional assessment staging test; clinical dementia rating
Categories
Funding
- Alzheimer's Association [NIRG-08-90460]
- US Department of Health and Human Services [AG03051, AG08051]
- Fisher Center for Alzheimer's Research Foundation
- Litwin Fund for Alzheimer's Disease Research
- Woodbourne Foundation
- Louis J. Kay and June E. Kay Foundation
- Stringer Foundation
- Hagedorn Fund
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Determining how cognition affects functional abilities is important in Alzheimer disease and related disorders. A total of 280 patients (normal or Alzheimer disease and related disorders) received a total of 1514 assessments using the functional assessment staging test (FAST) procedure and the MCI Screen. A hierarchical Bayesian cognitive processing model was created by embedding a signal detection theory model of the MCI Screen-delayed recognition memory task into a hierarchical Bayesian framework. The signal detection theory model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the 6 FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. Hierarchical Bayesian cognitive processing models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition into a continuous measure of functional severity for both individuals and FAST groups. Such a translation links 2 levels of brain information processing and may enable more accurate correlations with other levels, such as those characterized by biomarkers.
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