2015
DOI: 10.1088/1741-2560/12/4/046030
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Design andin vivoevaluation of more efficient and selective deep brain stimulation electrodes

Abstract: Objective Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, the efficiency and selectivity of DBS can be improved. Our objective was to design electrode geometries that increased the efficiency and selectivity of DBS. Approach We coupled computational models of electrodes in brain tissue with cable models of axons of passage (AOPs), terminating axons (TAs), and local neurons (LNs… Show more

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Cited by 34 publications
(40 citation statements)
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References 79 publications
(111 reference statements)
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“…This can be explained with the second spatial derivative of the electric potential, so that the electric field potential of a long electrode is more homogeneous parallel to the electrode orientation leading to a smaller second spatial derivative as compared to the perpendicular direction, and vice versa for the short electrodes. Selectivity to parallel axons was also achieved with an asymmetric bipolar electrode and a cathodic electrode surrounded by anodes [32]. Although those results are very encouraging, the control of orientational selectivity of the lead is restricted by the orientation in which the lead is implanted.…”
Section: Discussionmentioning
confidence: 99%
“…This can be explained with the second spatial derivative of the electric potential, so that the electric field potential of a long electrode is more homogeneous parallel to the electrode orientation leading to a smaller second spatial derivative as compared to the perpendicular direction, and vice versa for the short electrodes. Selectivity to parallel axons was also achieved with an asymmetric bipolar electrode and a cathodic electrode surrounded by anodes [32]. Although those results are very encouraging, the control of orientational selectivity of the lead is restricted by the orientation in which the lead is implanted.…”
Section: Discussionmentioning
confidence: 99%
“…As well, computational models provide the foundation for model-based design of electrode geometries and stimulation parameters intended to improve the ability control the neural response to stimulation. For example, computational models have been used to analyze and design electrode configurations for spinal cord stimulation (Holsheimer et al 2005, Howell et al 2014), deep brain stimulation (Butson and McIntyre 2006, Keane et al 2012, Howell et al 2015), epidural cortical stimulation (Manola et al 2005, Wongsarnpigoon and Grill 2012), and peripheral nerve stimulation (Veltink et al 1989, Choi et al 2001, Kent and Grill 2013). As well, such computational models can be used to guide the selection or optimization of stimulation parameters.…”
Section: Introductionmentioning
confidence: 99%
“…As important as it is to assay the perceptual properties of artificial sensations using classical psychophysical measures, it is as important to assay their functional utility using standardized tests. Many behavioral tests are designed to provide a quantitative evaluation of sensory motor performance to assess the consequences of injury or disease (Jebsen et al, 1969;Penta et al, 1998). Again, standardized functional tests can draw on decades of data from healthy subjects to provide a baseline index of performance.…”
Section: Neuroprosthetics Research Needs To Generalizementioning
confidence: 99%
“…However, they offer very limited selectivity given the low number of contacts and the relatively large contact area of the electrodes. Optimization of electrode design and stimulation parameters can improve selectivity (Howell et al, 2015), but current DBS technology is probably not well suited for prosthetics.…”
Section: Hardware Considerationsmentioning
confidence: 99%