A computational modelling approach to investigate alpha rhythm slowing associated with Alzheimer’s Disease

Attenuation of power in the alpha band (8–13 Hz) of Electroencephalograhy (EEG) is identified as a hallmark symptom of Alzheimer’s Disease (AD). There is general agreement in existing literature that the thalamocortical circuitry play a key role in generation of alpha rhythms. Our research is to gain a better understanding of the cause of alpha rhythm slowing in the thalamocortical circuitry, which in turn might help in early detection of Alzheimer’s Disease. We adopt a computational approach and base our work on a classic computational model of the thalamocortical circuitry associated with the generation of alpha rhythms proposed by Lopes Da Silva. In this work, we use the model to do a preliminary study on the power spectrum of the alpha rhythms by varying model parameters corresponding to inhibitory and excitatory synaptic activity. We observe that an increased inhibitory synaptic activity in the network leads to a decrease in the power of the upper alpha frequency band (11–13 Hz) and an increase in that of the lower alpha frequency band (8–10 Hz). Thus we observe an overall slowing of alpha rhythm corresponding to an increase in the inhibitory synaptic activity in the thalamocortical circuitry.