Biomedical Engineering - Research Publications

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Author: Cook, Mark × Author: Grayden, David × Author: Nesic, Dragan × End date: 2018 × Start date: 2011 × Type: Journal Article ×

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    Electrical probing of cortical excitability in patients with epilepsy
    Freestone, DR ; Kuhlmann, L ; Grayden, DB ; Burkitt, AN ; Lai, A ; Nelson, TS ; Vogrin, S ; Murphy, M ; D'Souza, W ; Badawy, R ; Nesic, D ; Cook, MJ (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2011-12)
    Standard methods for seizure prediction involve passive monitoring of intracranial electroencephalography (iEEG) in order to track the 'state' of the brain. This paper introduces a new method for measuring cortical excitability using an electrical probing stimulus. Electrical probing enables feature extraction in a more robust and controlled manner compared to passively tracking features of iEEG signals. The probing stimuli consist of 100 bi-phasic pulses, delivered every 10 min. Features representing neural excitability are estimated from the iEEG responses to the stimuli. These features include the amplitude of the electrically evoked potential, the mean phase variance (univariate), and the phase-locking value (bivariate). In one patient, it is shown how the features vary over time in relation to the sleep-wake cycle and an epileptic seizure. For a second patient, it is demonstrated how the features vary with the rate of interictal discharges. In addition, the spatial pattern of increases and decreases in phase synchrony is explored when comparing periods of low and high interictal discharge rates, or sleep and awake states. The results demonstrate a proof-of-principle for the method to be applied in a seizure anticipation framework. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction.
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    Bifurcation analysis of two coupled Jansen-Rit neural mass models
    Ahmadizadeh, S ; Karoly, PJ ; Nesic, D ; Grayden, DB ; Cook, MJ ; Soudry, D ; Freestone, DR ; Cymbalyuk, G (PUBLIC LIBRARY SCIENCE, 2018-03-27)
    We investigate how changes in network structure can lead to pathological oscillations similar to those observed in epileptic brain. Specifically, we conduct a bifurcation analysis of a network of two Jansen-Rit neural mass models, representing two cortical regions, to investigate different aspects of its behavior with respect to changes in the input and interconnection gains. The bifurcation diagrams, along with simulated EEG time series, exhibit diverse behaviors when varying the input, coupling strength, and network structure. We show that this simple network of neural mass models can generate various oscillatory activities, including delta wave activity, which has not been previously reported through analysis of a single Jansen-Rit neural mass model. Our analysis shows that spike-wave discharges can occur in a cortical region as a result of input changes in the other region, which may have important implications for epilepsy treatment. The bifurcation analysis is related to clinical data in two case studies.