Effects of Compensation, Connectivity and Tau in a Computational Model of Alzheimer's Disease

Abstract

This work updates an existing, simplistic computational model of Alzheimer's Disease (AD) to investigate the behaviour of synaptic compensatory mechanisms in neural networks with small-world connectivity, and varying methods of calculating compensation. It additionally introduces a method for simulating tau neurofibrillary pathology, resulting in a more dramatic damage profile. Small-world connectivity is shown to have contrasting effects on capacity, retrieval time, and robustness to damage, whilst the use of more easily-obtained remote memories rather than recent memories for synaptic compensation is found to lead to rapid network damage.