Alpha and theta rhythm abnormality in Alzheimer's disease: a study using a computational model

Sen Bhattacharya, Basabdatta and Coyle, Damien and Maguire, Liam (2011) Alpha and theta rhythm abnormality in Alzheimer's disease: a study using a computational model. In: From brains to systems. Advances in Experimental Medicine and Biology, 718 . Springer, New York, pp. 57-73. ISBN 9781461401643

Full content URL: http://dx.doi.org/10.1007/978-1-4614-0164-3_6

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Item Type:Book Section
Item Status:Live Archive

Abstract

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 gener-
ation 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 com-
putational 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 thala-
mus. We observe that the inhibitory population in the model plays a crucial
role in mediating the oscillatory behaviour of the model output. Further, in-
crease 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.

Keywords:Neural mass models, Alpha rhythms, theta rhythms, Alzheimer's Disease, Electroencephalogram
Subjects:G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Engineering
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ID Code:9364
Deposited On:09 May 2013 11:10

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