Aprinda Indahlastari1, Alejandro Albizu2, Nicole R Nissim2, Kelsey R Traeger2, Andrew O'Shea2, Adam J Woods2. 1. Department of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA. Electronic address: aprinda.indahlas@phhp.ufl.edu. 2. Department of Clinical and Health Psychology, Department of Neuroscience, Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
Abstract
BACKGROUND: Inaccurate electrode placement and electrode drift during a transcranial electrical stimulation (tES) session have been shown to alter predicted field distributions in the brain and thus may contribute to a large variation in tES study outcomes. Currently, there is no objective and independent measure to quantify electrode placement accuracy/drift in tES clinical studies. OBJECTIVE/HYPOTHESIS: We proposed and tested novel methods to quantify accurate and consistent electrode placements in tES using models generated from a 3D scanner. METHODS: Accurate electrode placements were quantified as Discrepancy in eight tES participants by comparing landmark distances of physical electrode locations F3/F4 to their model counterparts. Distances in models were computed using curve and linear based methods. Variability of landmark locations in a single subject was computed for multiple stimulation sessions to determine consistent electrode placements across four experimenters. MAIN RESULTS: We obtained an average of 0.4 cm in Discrepancy, which was within the placement accuracy/drift threshold (1 cm) for conventional tES electrodes (∼35 cm2) to achieve reliable tES sessions suggested in the literature. Averaged Variability was 5.2%, with F4 electrode location as the least consistent placement. CONCLUSIONS: These methods provide objective feedback for experimenters on their performance in placing tES electrodes. Applications of these methods can be used to monitor electrode locations in tES studies of a larger cohort using F3/F4 montage and other conventional electrode arrangements. Future studies may include co-registering the landmark locations with imaging-derived head models to quantify the effects of electrode accuracy/drift on predicted field distributions in the brain.
BACKGROUND: Inaccurate electrode placement and electrode drift during a transcranial electrical stimulation (tES) session have been shown to alter predicted field distributions in the brain and thus may contribute to a large variation in tES study outcomes. Currently, there is no objective and independent measure to quantify electrode placement accuracy/drift in tES clinical studies. OBJECTIVE/HYPOTHESIS: We proposed and tested novel methods to quantify accurate and consistent electrode placements in tES using models generated from a 3D scanner. METHODS: Accurate electrode placements were quantified as Discrepancy in eight tES participants by comparing landmark distances of physical electrode locations F3/F4 to their model counterparts. Distances in models were computed using curve and linear based methods. Variability of landmark locations in a single subject was computed for multiple stimulation sessions to determine consistent electrode placements across four experimenters. MAIN RESULTS: We obtained an average of 0.4 cm in Discrepancy, which was within the placement accuracy/drift threshold (1 cm) for conventional tES electrodes (∼35 cm2) to achieve reliable tES sessions suggested in the literature. Averaged Variability was 5.2%, with F4 electrode location as the least consistent placement. CONCLUSIONS: These methods provide objective feedback for experimenters on their performance in placing tES electrodes. Applications of these methods can be used to monitor electrode locations in tES studies of a larger cohort using F3/F4 montage and other conventional electrode arrangements. Future studies may include co-registering the landmark locations with imaging-derived head models to quantify the effects of electrode accuracy/drift on predicted field distributions in the brain.
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