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This work updates an existing, simplistic computational model of Alzheimer'sDisease (AD) to investigate the behaviour of synaptic compensatory mechanismsin neural networks with small-world connectivity, and varying methods ofcalculating compensation. It additionally introduces a method for simulatingtau 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 moreeasily-obtained remote memories rather than recent memories for synapticcompensation is found to lead to rapid network damage.

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