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Project

Cognitive brain circuits and the spread of amyloid and tau in vivo in humans

Alzheimer’s disease (AD) is the most common cause of dementia among older adults. The neuropathological hallmarks of Alzheimer’s disease are the accumulation of extracellular amyloid beta plaques and the deposition of tau aggregates as intraneuronal neurofibrillary tangles. An important endeavor of contemporary research is to examine the relationship between these different components in vivo in humans and how they relate to cognitive function. We hypothesize that a critical intermediary level between the protein aggregates and cognitive dysfunction is the re-organization of functional brain circuits.

The discovery of PET tracers is very useful to quantify the amount and to map the distribution of amyloid and tau. Amyloid PET has been validated against a neuropathological ground truth in end-of-life studies, where visual reads of amyloid PET scans had a high diagnostic accuracy for predicting the presence of neuritic amyloid plaques. Training and testing a classifier for binary classification against a neuropathological ground truth may provide us with a more data-driven way of defining the most discriminative features, rather than an expert- or consensus-based definition based on visual read rules. Once the classifier has been trained and tested using post-mortem verification, and has proven to be accurate, it may be applicable to different datasets without the need for laborious and time-intensive visual reads.

Functional changes in brain networks can be studied in vivo by measuring the brain’s hemodynamic response during cognitive processing using fMRI. Many fMRI studies in Alzheimer’s disease have used episodic memory tasks, as episodic memory impairment is a hallmark of Alzheimer’s disease. Besides memory problems, language deficits, predominantly word finding problems, occur already early in the progression of Alzheimer’s disease. Therefore, it is interesting to study the functional circuitry of the language and the associative-semantic network in Alzheimer’s disease.

There are two separate objectives:
1. To examine if a support vector machine is able to classify 18F-Flutemetamol PET images as normal or abnormal based on neuropathological ground truths and to investigate how the performance of the classifiers related to the Centiloid scale and visual reads in an independent asymptomatic cohort.
2. To determine how the spread of amyloid beta plaques and tau aggregates affects the functional organization of the language network in different stages of Alzheimer’s disease: the preclinical and early Alzheimer’s disease stage.

Date:16 Oct 2018 →  13 Dec 2023
Keywords:Alzheimer's Disease
Disciplines:Neurosciences, Biological and physiological psychology, Cognitive science and intelligent systems, Developmental psychology and ageing
Project type:PhD project