Publication date: Available online 19 September 2017
Source:Journal of Neuroscience Methods
Author(s): Emilia Ambrosini, Simona Ferrante, Mark van de Ruit, Stefano Biguzzi, Vera Colombo, Marco Monticone, Giorgio Ferriero, Alessandra Pedrocchi, Giancarlo Ferrigno, Michael J. Grey
BackgroundDuring Transcranial Magnetic Stimulation (TMS) experiments researchers often use a neuronavigation system to precisely and accurately maintain coil position and orientation.New methodThis study aimed to develop and validate an open-source software for TMS coil navigation. StimTrack uses an optical tracker and an intuitive user interface to facilitate the maintenance of position and orientation of any type of coil within and between sessions. Additionally, online access to navigation data is provided, hereby adding e.g. the ability to start or stop the magnetic stimulator depending on the distance to target or the variation of the orientation angles.ResultsStimTrack allows repeatable repositioning of the coil within 0.7mm for translation and <1° for rotation. Stimulus-response (SR) curves obtained from 19 healthy volunteers were used to demonstrate that StimTrack can be effectively used in a typical experiment. An excellent intra and inter-session reliability (ICC >0.9) was obtained on all parameters computed on SR curves acquired using StimTrack.Comparison with existing methodStimTrack showed a target accuracy similar to that of a commercial neuronavigation system (BrainSight, Rogue Research Inc.). Indeed, small differences both in position (∼0.2mm) and orientation (<1°) were found between the systems. These differences are negligible given the human error involved in landmarks registration.ConclusionsStimTrack, available as supplementary material, is found to be a good alternative for commercial neuronavigation systems facilitating assessment changes in corticospinal excitability using TMS. StimTrack allows researchers to tailor its functionality to their specific needs, providing added value that benefits experimental procedures and improves data quality.
Graphical abstract
from #ORL-AlexandrosSfakianakis via ola Kala on Inoreader http://ift.tt/2wFvJLp
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