Details

Autor(en) / Beteiligte

• Poreh, Amir

Titel

A-7 Extending the Quantified Process Approach - Application of Nonlinear Models Toward the Understanding of Neurocognitive Decline Across the Lifespan

Ist Teil von

• Archives of clinical neuropsychology, 2022-08, Vol.37 (6), p.1242-1242

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Oxford Journals 2020 Medicine

Beschreibungen/Notizen

• Abstract Objective: In this presentation, I will extend the Reliability Theory of Cognitive Decline and examine the emergence of infrequent errors on neurocognitive tests following cognitive decline or brain insult. Data Selection: Unpublished, meta norms (Figure 1), data published by Poreh (2020) (Figure 2), and cognitive/genetic data collected by the National Alzheimer’s Coordinating Center (NACC) will be used to illustrate the validity and utility of the model. Data Synthesis: Nonlinear models will be presented to show how performance on various neuropsychological tests declines across the life span and how the threshold and rate of decline are impacted by education and genetics (Figures 3a and 3b). Next, a new theoretical model will be used to explain how task-specific neurocognitive systems (neural networks) fail. The “time to failure” curve-fitting hazard model (Figure 4) will be used to illustrate how this process occurs and how this method can be applied to the development of age-based norms for such errors on neuropsychological tests. Conclusions: This cohesive empirical model extends on the Quantified Process Approach using cross-sectional and longitudinal neuropsychological data. This model allows clinicians to understand the effect of education on cognition decline (also known as “brain reserve capacity”), genetic predisposition, and heuristic biases regarding cognitive aging.