OBJECTIVE: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique to modify neural excitability. Using multi-array tDCS, we investigate the influence of inter-individually varying head tissue conductivity profiles on optimal electrode configurations for an auditory cortex stimulation. APPROACH: In order to quantify the uncertainty of the optimal electrode configurations, multi-variate generalized polynomial chaos expansions of the model solutions are used based on uncertain conductivity profiles of the compartments skin, skull, gray matter, and white matter. Stochastic measures, probability density functions, and sensitivity of the quantities of interest are investigated for each electrode and the current density at the target with the resulting stimulation protocols visualized on the head surface. MAIN RESULTS: We demonstrate that the optimized stimulation protocols are only comprised of a few active electrodes, with tolerable deviations in the stimulation amplitude of the anode. However, large deviations in the order of the uncertainty in the conductivity profiles could be noted in the stimulation protocol of the compensating cathodes. Regarding these main stimulation electrodes, the stimulation protocol was most sensitive to uncertainty in skull conductivity. Finally, the probability that the current density amplitude in the auditory cortex target region is supra-threshold was below 50%. SIGNIFICANCE: The results suggest that an uncertain conductivity profile in computational models of tDCS can have a substantial influence on the prediction of optimal stimulation protocols for stimulation of the auditory cortex. The investigations carried out in this study present a possibility to predict the probability of providing a therapeutic effect with an optimized electrode system for future auditory clinical and experimental procedures of tDCS applications.
OBJECTIVE: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique to modify neural excitability. Using multi-array tDCS, we investigate the influence of inter-individually varying head tissue conductivity profiles on optimal electrode configurations for an auditory cortex stimulation. APPROACH: In order to quantify the uncertainty of the optimal electrode configurations, multi-variate generalized polynomial chaos expansions of the model solutions are used based on uncertain conductivity profiles of the compartments skin, skull, gray matter, and white matter. Stochastic measures, probability density functions, and sensitivity of the quantities of interest are investigated for each electrode and the current density at the target with the resulting stimulation protocols visualized on the head surface. MAIN RESULTS: We demonstrate that the optimized stimulation protocols are only comprised of a few active electrodes, with tolerable deviations in the stimulation amplitude of the anode. However, large deviations in the order of the uncertainty in the conductivity profiles could be noted in the stimulation protocol of the compensating cathodes. Regarding these main stimulation electrodes, the stimulation protocol was most sensitive to uncertainty in skull conductivity. Finally, the probability that the current density amplitude in the auditory cortex target region is supra-threshold was below 50%. SIGNIFICANCE: The results suggest that an uncertain conductivity profile in computational models of tDCS can have a substantial influence on the prediction of optimal stimulation protocols for stimulation of the auditory cortex. The investigations carried out in this study present a possibility to predict the probability of providing a therapeutic effect with an optimized electrode system for future auditory clinical and experimental procedures of tDCS applications.
Authors: S Wagner; S M Rampersad; Ü Aydin; J Vorwerk; T F Oostendorp; T Neuling; C S Herrmann; D F Stegeman; C H Wolters Journal: J Neural Eng Date: 2013-12-05 Impact factor: 5.379
Authors: F Fregni; R Marcondes; P S Boggio; M A Marcolin; S P Rigonatti; T G Sanchez; M A Nitsche; A Pascual-Leone Journal: Eur J Neurol Date: 2006-09 Impact factor: 6.089
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Authors: Leon Morales-Quezada; Mirret M El-Hagrassy; Beatriz Costa; R Andy McKinley; Pengcheng Lv; Felipe Fregni Journal: Front Hum Neurosci Date: 2019-10-31 Impact factor: 3.169
Authors: Mohd Faizal Mohd Zulkifly; Albert Lehr; Daniel van de Velden; Asad Khan; Niels K Focke; Carsten H Wolters; Walter Paulus Journal: PLoS One Date: 2022-03-24 Impact factor: 3.240