• J. Neurosci. Methods · Apr 2010

    Evaluating the impact of the deep brain stimulation induced electric field on subthalamic neurons: a computational modelling study.

    • Nada Yousif, Nuri Purswani, Richard Bayford, Dipankar Nandi, Peter Bain, and Xuguang Liu.
    • Department of Clinical Neuroscience, Imperial College London, London, UK. n.yousif@imperial.ac.uk
    • J. Neurosci. Methods. 2010 Apr 30; 188 (1): 105-12.

    AbstractDeep brain stimulation (DBS) is an effective surgical treatment used to alleviate the symptoms of neurological disorders, most commonly movement disorders. However, the mechanism of how the applied stimulus pulses interact with the surrounding neuronal elements is not yet clearly understood, slowing progress and development of this promising therapeutic technology. To extend previous approaches of using isolated, myelinated axon models used to estimate the effect of DBS, we propose that taking into account entire neurons will reveal stimulation induced effects overlooked by previous studies. We compared the DBS induced volume of tissue activated (VTA) using arrays of whole cell models of subthalamic nucleus (STN) excitatory neurons consisting of a cell body and an anatomically accurate dendritic tree, to the common models of axon arrays. Our results demonstrate that STN neurons have a higher excitation threshold than axons, as stimulus amplitudes 10 times as large elicit a VTA range a fifth of the distance from the electrode surface. However, the STN neurons do show a change in background firing rate in response to stimulation, even when they are classified as sub-threshold by the VTA definition. Furthermore the whole neuron models are sensitive to regions of high current density, as the distribution of firing is centred on the electrode contact edges These results demonstrate the importance of accurate neuron models for fully appreciating the spatial effects of DBS on the immediate surrounding brain volume within small distances of the electrode, which are overlooked by previous models of isolated axons and individual neurons.Copyright 2010 Elsevier B.V. All rights reserved.

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