Electrical and Electronic Engineering - Research Publications

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Author: Grayden, David × Author: Nesic, Dragan × End date: 2014 × Start date: 2013 × Type: Journal Article ×

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    A comparison of open-loop and closed-loop stimulation strategies to control excitation of retinal ganglion cells
    Kameneva, T ; Zarelli, D ; Nesic, D ; Grayden, DB ; Burkitt, AN ; Meffin, H (Elsevier, 2014-11-01)
    Currently, open-loop stimulation strategies are prevalent in medical bionic devices. These strategies involve setting electrical stimulation that does not change in response to neural activity. We investigate through simulation the advantages of using a closed-loop strategy that sets stimulation level based on continuous measurement of the level of neural activity. We propose a model-based controller design to control activation of retinal neurons. To deal with the lack of controllability and observability of the whole system, we use Kalman decomposition and control only the controllable and observable part. We show that the closed-loop controller performs better than the open-loop controller when perturbations are introduced into the system. We envisage that our work will give rise to more investigations of the closed-loop techniques in basic neuroscience research and in clinical applications of medical bionics.
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    Estimation of effective connectivity via data-driven neural modeling
    Freestone, DR ; Karoly, PJ ; Nesic, D ; Aram, P ; Cook, MJ ; Grayden, DB (FRONTIERS MEDIA SA, 2014-11-28)
    This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination.