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

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Bhattacharya, Basab, Coyle, Damien and Maguire, Liam (2010) A computational modelling approach to investigate alpha rhythm slowing associated with Alzheimer’s Disease. In: the Brain-inspired Cognitive Systems Conference, Spain. Online. 11 pp. [Conference contribution]

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URL: http://tierra.aslab.upm.es/events/BICS2010/BICS2010online-preprints/CognitiveNeuroscience/56.pdf

Abstract

Attenuation of power in the alpha band (8–13 Hz) of Electroencephalo-grahy (EEG) is identified as a hallmark symptom of Alzheimer’s Disease (AD).There is general agreement in existing literature that the thalamocortical circuitryplay a key role in generation of alpha rhythms. Our research is to gain a better un-derstanding 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 acomputational approach and base our work on a classic computational model of thethalamocortical circuitry associated with the generation of alpha rhythms proposedby Lopes Da Silva. In this work, we use the model to do a preliminary study on thepower spectrum of the alpha rhythms by varying model parameters corresponding toinhibitory and excitatory synaptic activity. We observe that an increased inhibitorysynaptic activity in the network leads to a decrease in the power of the upper al-pha frequency band (11–13 Hz) and an increase in that of the lower alpha frequencyband (8–10 Hz). Thus we observe an overall slowing of alpha rhythm correspondingto an increase in the inhibitory synaptic activity in the thalamocortical circuitry.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Intelligent Systems Research Centre
ID Code:17642
Deposited By:Dr Damien Coyle
Deposited On:30 Mar 2011 16:01
Last Modified:15 Jun 2011 11:09

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