Speaker
Description
Mild Cognitive Impairment (MCI) consists of a cognitive impairment that does not affect a person’s activities of daily living and progresses to dementia at a rate of approximately 12% per year. In cross-sectional studies, the complexity of the cognitive organisation was explored using Network Analysis to evaluate the relationships between cognitive functions. The present study aims to investigate the longitudinal changes in the relationships between cognitive functions.
From the ADNI database, we extracted three cognitive evaluations of two groups of MCI patients who will convert to Alzheimer’s Disease (convMCI; N=128) or not (stabMCI; N=390) and cognitive performances before and after the conversion to AD (MCI/AD; N=203). We used cross-lagged panel network (CLPN) models to investigate the relationship between cognitive performance on different measurement occasions. We assessed node-wise prediction stability via bootstrap (500 samples).
The stabMCI group showed a higher density of connections in the first year (0.322) than in the second year (0.198). In the first year, memory performance predicted almost all other cognitive tests. On the contrary, the convMCI group showed a lower density of connections in the first year (0.165) than in the second year (0.248), when memory performance and executive functions showed predictive power. Predictions were less stable in the convMCI than in the stabMCI group. The MCI/AD group showed sparse connections (density=0.215), with the Trial Making Test and the Boston Naming Test showing higher predictions than the other variables.
These results show different predictive patterns depending on the future evolution of cognitive impairment.
| If you're submitting a symposium talk, what's the symposium title? | Applications of Psychometric Network Analysis in Psychology |
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| If you're submitting a symposium, or a talk that is part of a symposium, is this a junior symposium? | No |
