Anne-Mari Vitikainen1, Elina Mäkelä2, Pantelis Lioumis3, Veikko Jousmäki4, Jyrki P Mäkelä5. 1. BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland; Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 University of Helsinki, Helsinki, Finland. Electronic address: anne-mari.vitikainen@hus.fi. 2. BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland. Electronic address: elina.makela@aalto.fi. 3. BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland; Neuroscience Center, University of Helsinki, P.O. Box 56, FI-00014 University of Helsinki, Helsinki, Finland. Electronic address: pantelis.lioumis@helsinki.fi. 4. Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O. Box 15100, FI-00076 Aalto, Espoo, Finland; Aalto NeuroImaging, Aalto University School of Science, P.O. Box 15100, FI-00076 Aalto, Espoo, Finland. Electronic address: veikko.jousmaki@aalto.fi. 5. BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland. Electronic address: jyrki.makela@hus.fi.
Abstract
BACKGROUND: The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. NEW METHOD: We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. COMPARISON WITH EXISTING METHOD(S): The results produced by the automatic routine were compared with the manually reviewed video-recordings. RESULTS: The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. CONCLUSION: The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results.
BACKGROUND: The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumorpatients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. NEW METHOD: We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. COMPARISON WITH EXISTING METHOD(S): The results produced by the automatic routine were compared with the manually reviewed video-recordings. RESULTS: The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. CONCLUSION: The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results.
Authors: Henri Lehtinen; Jyrki P Mäkelä; Teemu Mäkelä; Pantelis Lioumis; Liisa Metsähonkala; Laura Hokkanen; Juha Wilenius; Eija Gaily Journal: Epilepsia Open Date: 2018-04-06
Authors: Shalini Narayana; Savannah K Gibbs; Stephen P Fulton; Amy Lee McGregor; Basanagoud Mudigoudar; Sarah E Weatherspoon; Frederick A Boop; James W Wheless Journal: Front Neurol Date: 2021-05-19 Impact factor: 4.003
Authors: Charlotte Nettekoven; Julia Pieczewski; Volker Neuschmelting; Kristina Jonas; Roland Goldbrunner; Christian Grefkes; Carolin Weiss Lucas Journal: Hum Brain Mapp Date: 2021-08-13 Impact factor: 5.038