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Alpha and Theta Rhythm Abnormality in Alzheimer’s Disease: A Study Using a Computational Model

  • Conference paper
From Brains to Systems

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 718))

Abstract

Electroencephalography (EEG) studies in Alzheimer’s Disease (AD) patients show an attenuation of average power within the alpha band (7.5–13 Hz) and an increase of power in the theta band (4–7 Hz). Significant body of evidence suggest that thalamocortical circuitry underpin the generation and modulation of alpha and theta rhythms. The research presented in this chapter is aimed at gaining a better understanding of the neuronal mechanisms underlying EEG band power changes in AD which may in the future provide useful biomarkers towards early detection of the disease and for neuropharmaceutical investigations. The study is based on a classic computational model of the thalamocortical circuitry which exhibits oscillation within the theta and the alpha bands. We are interested in the change in model oscillatory behaviour corresponding with changes in the connectivity parameters in the thalamocortical as well as sensory input pathways. The synaptic organisation as well as the connectivity parameter values in the model are modified based on recent experimental data from the cat thalamus. We observe that the inhibitory population in the model plays a crucial role in mediating the oscillatory behaviour of the model output. Further, increase in connectivity parameters in the afferent and efferent pathways of the inhibitory population induces a slowing of the output power spectra. These observations may have implications for extending the model for further AD research.

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Notes

  1. 1.

    Neurons that use Acetylcholine (ACh) as the synaptic neurotransmitter are called cholinergic neurons, while the synapse is called a cholinergic synapse (see [23] for a review).

  2. 2.

    Alpha Rhythms are dominant in cortical EEG while a subject is in a relaxed but awake state with eyes closed and thus corresponds to a lack of visual representation from the external world.

  3. 3.

    The set of varying values for each connectivity parameter are different and over a smaller range compared to that in ARm. Preliminary investigation over smaller parameter ranges with ARm are reported elsewhere [4, 6].

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Acknowledgements

This work is supported by the Northern Ireland Department for Education and Learning under the Strengthening the All Island Research Base programme. B. Sen Bhattacharya would like to thank Dr. David Watson for valuable comments and suggestions on the work and several useful discussions from time to time.

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Authors and Affiliations

  1. University of Ulster, Magee Campus, Northland Road, Derry, BT48 7JL, Northern Ireland, UK

    Basabdatta Sen Bhattacharya, Damien Coyle & Liam P. Maguire

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  1. Basabdatta Sen Bhattacharya
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Correspondence to Basabdatta Sen Bhattacharya .

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  1. , Departamento de Automática, Universidad Politécnica de Madrid, Jose Gutierrez Abascal 2, Madrid, 28006, Spain

    Carlos Hernández

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  6. Dipto. Ingegneria Automatica e, Informatica, Università Palermo, Corso Pizasi 106, Palermo, 90144, Italy

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Bhattacharya, B.S., Coyle, D., Maguire, L.P. (2011). Alpha and Theta Rhythm Abnormality in Alzheimer’s Disease: A Study Using a Computational Model. In: Hernández, C., et al. From Brains to Systems. Advances in Experimental Medicine and Biology, vol 718. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0164-3_6

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