Relating memory to functional performance in normal aging to dementia using hierarchical bayesian cognitive processing models.

Relating memory to functional performance in normal aging to dementia using hierarchical bayesian cognitive processing models. Alzheimer Dis Assoc Disord. 2013 Jan;27(1):16-22 Authors: Shankle WR, Pooley JP, Steyvers M, Hara J, Mangrola T, Reisberg B, Lee MD Abstract 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 la...
Source: Alzheimer Disease and Associated Disorders - Category: Psychiatry Tags: Alzheimer Dis Assoc Disord Source Type: research