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10.1007/978-3-030-45623-8_7

http://scihub22266oqcxt.onion/10.1007/978-3-030-45623-8_7
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suck abstract from ncbi


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pmid32966022      Brain+and+Human+Body+Modeling+2020:+Computational+Human+Models+Presented+at+EMBC++2019+and+the+BRAIN+Initiative(R)+2019+Meeting-/-ä 2021 ; ä (ä): 119-35
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  • Personalization of Multi-electrode Setups in tCS/tES: Methods and Advantages #MMPMID32966022
  • Salvador R; Biagi MC; Puonti O; Splittgerber M; Moliadze V; Siniatchkin M; Thielscher A; Ruffini G
  • Brain and Human Body Modeling 2020: Computational Human Models Presented at EMBC 2019 and the BRAIN Initiative(R) 2019 Meeting-/-ä 2021[]; ä (ä): 119-35 PMID32966022show ga
  • Transcranial current stimulation (tCS or tES) protocols yield results that are highly variable across individuals. Part of this variability results from differences in the electric field (E-field) induced in subjects' brains during stimulation. The E-field determines how neurons respond to stimulation, and it can be used as a proxy for predicting the concurrent effects of stimulation, like changes in cortical excitability, and, ultimately, its plastic effects. While the use of multichannel systems with small electrodes has provided a more precise tool for delivering tCS, individually variable anatomical parameters like the shape and thickness of tissues affect the E-field distribution for a specific electrode montage. Therefore, using the same montage parameters across subjects does not lead to the homogeneity of E-field amplitude over the desired targets. Here we describe a pipeline that leverages individualized head models combined with montage optimization algorithms to reduce the variability of the E-field distributions over subjects in tCS. We will describe the different steps of the pipeline - namely, MRI segmentation and head model creation, target specification, and montage optimization - and discuss their main advantages and limitations.
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