Bhattacharya, Basab, Coyle, Damien and Maguire, LP (2012) Assessing Alpha Band Event-related Synchronisation/Desynchronisation Using a Bio-Inspired Computational Model. Journal of Universal Computer Science, 18 (13). pp. 1888-1904. [Journal article]
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URL: http://www.jucs.org/jucs_18_13/assessing_alpha_band_event
Abstract
This paper describes a study of the effects of variation of synaptic connectivity in a thalamo-cortical circuitry using a neural mass model. The oscillatory behaviour of the model output is assessed within the alpha frequency band. The model presented here is a modification of an existing model involving the introduction of biologically plausible synaptic connectivities as well as synaptic structure. Our goal is to study altered event related desynchronisation/synchronisation (ERD/ERS) patterns within the alpha band in Alzheimers disease as observed in experimental studies. ERD is an amplitude attenuation of certain EEG rhythms when an event is initiated or while a certain event is taking place in the brain. ERS is an amplitude enhancement of a certain EEG rhythm when cortical areas are not specifically engaged in a given mode of activity at a certain instant of time. EEG desynchronisation normally blocks alpha rhythms in the EEG due to sensory processing or behaviour. The results show that a decrease in synaptic connectivity induces a time lag in both ERD and ERS peaks in the model output. Furthermore, a deficiency induced in the inhibitory cholinergic pathway results in a distinct effect on time to peak in the ERD/ERS response. These observations are consistent with experimental findings in AD. Variation of the level of interconnectivity has a pronounced effect on the ERS behaviour of the model whilethe excitatory connectivity in the retino-geniculate pathway during the resting state is more influential on the ERD behaviour.
| Item Type: | Journal article |
|---|---|
| Keywords: | Alpha rhythm, Event-related-(de)synchronisation, Alzheimer’s disease, thalamo-cortical model |
| 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: | 23752 |
| Deposited By: | Dr Damien Coyle |
| Deposited On: | 29 Oct 2012 11:19 |
| Last Modified: | 29 Oct 2012 11:19 |
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