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Matsuda RH, Souza VH, Marchetti TC, Soto AM, Kahilakoski OP, Zhdanov A, Malheiro VHE, Laine M, Nyrhinen M, Sinisalo H, Kicic D, Lioumis P, Ilmoniemi RJ, Baffa O. Robotic-electronic platform for autonomous and accurate transcranial magnetic stimulation targeting. Brain Stimul 2024; 17:469-472. [PMID: 38582491 DOI: 10.1016/j.brs.2024.03.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 03/15/2024] [Accepted: 03/31/2024] [Indexed: 04/08/2024] Open
Affiliation(s)
- Renan H Matsuda
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, 3900, 14040-901, Ribeirão Preto, SP, Brazil; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland.
| | - Victor H Souza
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, 3900, 14040-901, Ribeirão Preto, SP, Brazil; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland; School of Physiotherapy, Federal University of Juiz de Fora, Juiz de Fora, MG, Brazil
| | - Thais C Marchetti
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, 3900, 14040-901, Ribeirão Preto, SP, Brazil
| | - Ana M Soto
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Olli-Pekka Kahilakoski
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Andrey Zhdanov
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Victor H E Malheiro
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, 3900, 14040-901, Ribeirão Preto, SP, Brazil
| | - Mikael Laine
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Mikko Nyrhinen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Heikki Sinisalo
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Dubravko Kicic
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, 02150, Espoo, Finland
| | - Oswaldo Baffa
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, 3900, 14040-901, Ribeirão Preto, SP, Brazil
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Agboada D, Osnabruegge M, Rethwilm R, Kanig C, Schwitzgebel F, Mack W, Schecklmann M, Seiberl W, Schoisswohl S. Semi-automated motor hotspot search (SAMHS): a framework toward an optimised approach for motor hotspot identification. Front Hum Neurosci 2023; 17:1228859. [PMID: 38164193 PMCID: PMC10757939 DOI: 10.3389/fnhum.2023.1228859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 11/23/2023] [Indexed: 01/03/2024] Open
Abstract
Background Motor hotspot identification represents the first step in the determination of the motor threshold and is the basis for the specification of stimulation intensity used for various Transcranial Magnetic Stimulation (TMS) applications. The level of experimenters' experience and the methodology of motor hotspot identification differ between laboratories. The need for an optimized and time-efficient technique for motor hotspot identification is therefore substantial. Objective With the current work, we present a framework for an optimized and time-efficient semi-automated motor hotspot search (SAMHS) technique utilizing a neuronavigated robot-assisted TMS system (TMS-cobot). Furthermore, we aim to test its practicality and accuracy by a comparison with a manual motor hotspot identification method. Method A total of 32 participants took part in this dual-center study. At both study centers, participants underwent manual hotspot search (MHS) with an experienced TMS researcher, and the novel SAMHS procedure with a TMS-cobot (hereafter, called cobot hotspot search, CHS) in a randomized order. Resting motor threshold (RMT), and stimulus intensity to produce 1 mV (SI1mV) peak-to-peak of motor-evoked potential (MEP), as well as MEPs with 120% RMT and SI1mV were recorded as outcome measures for comparison. Results Compared to the MHS method, the CHS produced lower RMT, lower SI1mV and a trend-wise higher peak-to-peak MEP amplitude in stimulations with SI1mV. The duration of the CHS procedure was longer than that of the MHS (15.60 vs. 2.43 min on average). However, accuracy of the hotspot was higher for the CHS compared to the MHS. Conclusions The SAMHS procedure introduces an optimized motor hotspot determination system that is easy to use, and strikes a fairly good balance between accuracy and speed. This new procedure can thus be deplored by experienced as well as beginner-level TMS researchers.
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Affiliation(s)
- Desmond Agboada
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Mirja Osnabruegge
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Roman Rethwilm
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Carolina Kanig
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Florian Schwitzgebel
- Department of Electrical Engineering, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Wolfgang Mack
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Martin Schecklmann
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Wolfgang Seiberl
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Stefan Schoisswohl
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
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Passera B, Harquel S, Chauvin A, Gérard P, Lai L, Moro E, Meoni S, Fraix V, David O, Raffin E. Multi-scale and cross-dimensional TMS mapping: A proof of principle in patients with Parkinson's disease and deep brain stimulation. Front Neurosci 2023; 17:1004763. [PMID: 37214390 PMCID: PMC10192635 DOI: 10.3389/fnins.2023.1004763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 03/29/2023] [Indexed: 05/24/2023] Open
Abstract
Introduction Transcranial magnetic stimulation (TMS) mapping has become a critical tool for exploratory studies of the human corticomotor (M1) organization. Here, we propose to gather existing cutting-edge TMS-EMG and TMS-EEG approaches into a combined multi-dimensional TMS mapping that considers local and whole-brain excitability changes as well as state and time-specific changes in cortical activity. We applied this multi-dimensional TMS mapping approach to patients with Parkinson's disease (PD) with Deep brain stimulation (DBS) of the sub-thalamic nucleus (STN) ON and OFF. Our goal was to identifying one or several TMS mapping-derived markers that could provide unprecedent new insights onto the mechanisms of DBS in movement disorders. Methods Six PD patients (1 female, mean age: 62.5 yo [59-65]) implanted with DBS-STN for 1 year, underwent a robotized sulcus-shaped TMS motor mapping to measure changes in muscle-specific corticomotor representations and a movement initiation task to probe state-dependent modulations of corticospinal excitability in the ON (using clinically relevant DBS parameters) and OFF DBS states. Cortical excitability and evoked dynamics of three cortical areas involved in the neural control of voluntary movements (M1, pre-supplementary motor area - preSMA and inferior frontal gyrus - IFG) were then mapped using TMS-EEG coupling in the ON and OFF state. Lastly, we investigated the timing and nature of the STN-to-M1 inputs using a paired pulse DBS-TMS-EEG protocol. Results In our sample of patients, DBS appeared to induce fast within-area somatotopic re-arrangements of motor finger representations in M1, as revealed by mediolateral shifts of corticomuscle representations. STN-DBS improved reaction times while up-regulating corticospinal excitability, especially during endogenous motor preparation. Evoked dynamics revealed marked increases in inhibitory circuits in the IFG and M1 with DBS ON. Finally, inhibitory conditioning effects of STN single pulses on corticomotor activity were found at timings relevant for the activation of inhibitory GABAergic receptors (4 and 20 ms). Conclusion Taken together, these results suggest a predominant role of some markers in explaining beneficial DBS effects, such as a context-dependent modulation of corticospinal excitability and the recruitment of distinct inhibitory circuits, involving long-range projections from higher level motor centers and local GABAergic neuronal populations. These combined measures might help to identify discriminative features of DBS mechanisms towards deep clinical phenotyping of DBS effects in Parkinson's Disease and in other pathological conditions.
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Affiliation(s)
- Brice Passera
- CNRS UMR 5105, Laboratoire Psychologie et Neurocognition, LPNC, Grenoble, France
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, United States
| | - Sylvain Harquel
- CNRS UMR 5105, Laboratoire Psychologie et Neurocognition, LPNC, Grenoble, France
- CNRS, INSERM, IRMaGe, Grenoble, France
- Defitech Chair in Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, EPFL, Geneva, Switzerland
| | - Alan Chauvin
- CNRS UMR 5105, Laboratoire Psychologie et Neurocognition, LPNC, Grenoble, France
| | - Pauline Gérard
- CNRS UMR 5105, Laboratoire Psychologie et Neurocognition, LPNC, Grenoble, France
| | - Lisa Lai
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
| | - Elena Moro
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
| | - Sara Meoni
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
| | - Valerie Fraix
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
| | - Olivier David
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
- Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Estelle Raffin
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut Neurosciences, Grenoble, France
- Defitech Chair in Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, EPFL, Geneva, Switzerland
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Nieminen AE, Nieminen JO, Stenroos M, Novikov P, Nazarova M, Vaalto S, Nikulin V, Ilmoniemi RJ. Accuracy and precision of navigated transcranial magnetic stimulation. J Neural Eng 2022; 19. [PMID: 36541458 DOI: 10.1088/1741-2552/aca71a] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/29/2022] [Indexed: 12/02/2022]
Abstract
Objective.Transcranial magnetic stimulation (TMS) induces an electric field (E-field) in the cortex. To facilitate stimulation targeting, image-guided neuronavigation systems have been introduced. Such systems track the placement of the coil with respect to the head and visualize the estimated cortical stimulation location on an anatomical brain image in real time. The accuracy and precision of the neuronavigation is affected by multiple factors. Our aim was to analyze how different factors in TMS neuronavigation affect the accuracy and precision of the coil-head coregistration and the estimated E-field.Approach.By performing simulations, we estimated navigation errors due to distortions in magnetic resonance images (MRIs), head-to-MRI registration (landmark- and surface-based registrations), localization and movement of the head tracker, and localization of the coil tracker. We analyzed the effect of these errors on coil and head coregistration and on the induced E-field as determined with simplistic and realistic head models.Main results.Average total coregistration accuracies were in the range of 2.2-3.6 mm and 1°; precision values were about half of the accuracy values. The coregistration errors were mainly due to head-to-MRI registration with average accuracies 1.5-1.9 mm/0.2-0.4° and precisions 0.5-0.8 mm/0.1-0.2° better with surface-based registration. The other major source of error was the movement of the head tracker with average accuracy of 1.5 mm and precision of 1.1 mm. When assessed within an E-field method, the average accuracies of the peak E-field location, orientation, and magnitude ranged between 1.5 and 5.0 mm, 0.9 and 4.8°, and 4.4 and 8.5% across the E-field models studied. The largest errors were obtained with the landmark-based registration. When computing another accuracy measure with the most realistic E-field model as a reference, the accuracies tended to improve from about 10 mm/15°/25% to about 2 mm/2°/5% when increasing realism of the E-field model.Significance.The results of this comprehensive analysis help TMS operators to recognize the main sources of error in TMS navigation and that the coregistration errors and their effect in the E-field estimation depend on the methods applied. To ensure reliable TMS navigation, we recommend surface-based head-to-MRI registration and realistic models for E-field computations.
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Affiliation(s)
- Aino E Nieminen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,AMI Centre, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland
| | - Jaakko O Nieminen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Pavel Novikov
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Maria Nazarova
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States of America
| | - Selja Vaalto
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,HUS Diagnostic Center, Clinical Neurophysiology, Clinical Neurosciences, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Vadim Nikulin
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia.,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
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Passera B, Chauvin A, Raffin E, Bougerol T, David O, Harquel S. Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region. Neuroimage 2022; 259:119419. [PMID: 35777633 DOI: 10.1016/j.neuroimage.2022.119419] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 04/12/2022] [Accepted: 06/27/2022] [Indexed: 02/06/2023] Open
Abstract
The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this study, we explored the spatial resolution of TMS-EEG coupling by evaluating the minimal distance between two stimulated cortical sites that would significantly evoke different response dynamics. TMS evoked responses were mapped on the sensorimotor region in twenty participants. The stimulation grid was composed of nine targets separated between 10 and 15 mm on average. The dynamical signatures of TMS evoked activity were extracted and compared between sites using both local and remote linear regression scores and spatial generalized mixed models. We found a significant effect of the distance between stimulated sites on their dynamical signatures, neighboring sites showing differentiable response dynamics. Besides, common dynamical signatures were also found between sites up to 25-30 mm from each other. This overlap in dynamical properties decreased with distance and was stronger between sites within the same Brodmann area. Our results suggest that the spatial resolution of TMS-EEG coupling might be at least as high as 10 mm. Furthermore, our results reveal an anisotropic spatial resolution that was higher across than within the same Brodmann areas, in accordance with the TMS induced E-field modeling. Common cytoarchitectonic leading to shared dynamical properties within the same Brodmann area could also explain this anisotropy. Overall, these findings suggest that TMS-EEG benefits from the spatial resolution of TMS, which makes it an accurate technique for meso-scale brain mapping.
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Affiliation(s)
- Brice Passera
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; Univ. Grenoble Alpes, CNRS, UMR5105, Laboratoire Psychologie et NeuroCognition, LPNC, F-38000 Grenoble, France; Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Alan Chauvin
- Univ. Grenoble Alpes, CNRS, UMR5105, Laboratoire Psychologie et NeuroCognition, LPNC, F-38000 Grenoble, France
| | - Estelle Raffin
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland; Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Thierry Bougerol
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; Centre Hospitalier Univ. Grenoble Alpes, Service de Psychiatrie, F-38000 Grenoble, France
| | - Olivier David
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; Aix Marseille Univ, Inserm, U1106, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Sylvain Harquel
- Univ. Grenoble Alpes, CNRS, UMR5105, Laboratoire Psychologie et NeuroCognition, LPNC, F-38000 Grenoble, France; Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland; Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland.
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Nazarova M, Asmolova A. Towards more reliable TMS studies - How fast can we probe cortical excitability? Clin Neurophysiol Pract 2021; 7:21-22. [PMID: 35036660 PMCID: PMC8752992 DOI: 10.1016/j.cnp.2021.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 11/23/2021] [Indexed: 11/30/2022] Open
Affiliation(s)
- Maria Nazarova
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, 101000, Krivokolenny per. 3 Entrance 2, Moscow, Russian Federation
- Federal State Budgetary Institution Federal Center for Brain Research and Neurotechnologies of the Federal Medical Biological Agency, 117513 Ostrovityanova Street 1/10, Russian Federation
| | - Anastasia Asmolova
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, 101000, Krivokolenny per. 3 Entrance 2, Moscow, Russian Federation
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Ramalho BL, Moly J, Raffin E, Bouet R, Harquel S, Farnè A, Reilly KT. Face-hand sensorimotor interactions revealed by afferent inhibition. Eur J Neurosci 2021; 55:189-200. [PMID: 34796553 DOI: 10.1111/ejn.15536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 11/12/2021] [Indexed: 11/29/2022]
Abstract
Reorganization of the sensorimotor cortex following permanent (e.g., amputation) or temporary (e.g., local anaesthesia) deafferentation of the hand has revealed large-scale plastic changes between the hand and face representations that are accompanied by perceptual correlates. The physiological mechanisms underlying this reorganization remain poorly understood. The aim of this study was to investigate sensorimotor interactions between the face and hand using an afferent inhibition transcranial magnetic stimulation protocol in which the motor evoked potential elicited by the magnetic pulse is inhibited when it is preceded by an afferent stimulus. We hypothesized that if face and hand representations in the sensorimotor cortex are functionally coupled, then electrocutaneous stimulation of the face would inhibit hand muscle motor responses. In two separate experiments, we delivered an electrocutaneous stimulus to either the skin over the right upper lip (Experiment 1) or right cheek (Experiment 2) and recorded muscular activity from the right first dorsal interosseous. Both lip and cheek stimulation inhibited right first dorsal interosseous motor evoked potentials. To investigate the specificity of this effect, we conducted two additional experiments in which electrocutaneous stimulation was applied to either the right forearm (Experiment 3) or right upper arm (Experiment 4). Forearm and upper arm stimulation also significantly inhibited the right first dorsal interosseous motor evoked potentials, but this inhibition was less robust than the inhibition associated with face stimulation. These findings provide the first evidence for face-to-hand afferent inhibition.
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Affiliation(s)
- Bia Lima Ramalho
- IMPACT and Trajectoires Teams, INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), Lyon, France.,University UCBL Lyon 1, University of Lyon, Lyon, France.,Laboratory of Neurobiology II, Institute of Biophysics Carlos Chagas Filho, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.,Research Division, National Institute of Traumatology and Orthopedics Jamil Haddad, Rio de Janeiro, Brazil
| | - Julien Moly
- IMPACT and Trajectoires Teams, INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), Lyon, France.,University UCBL Lyon 1, University of Lyon, Lyon, France
| | - Estelle Raffin
- University Grenoble Alpes, Grenoble Institute of Neuroscience, INSERM U1216, Grenoble, France
| | - Romain Bouet
- University UCBL Lyon 1, University of Lyon, Lyon, France.,Brain Dynamics and Cognition Team - DyCog, Lyon Neuroscience Research Center, INSERM U1028, CRNS-UMR5292, Lyon, France
| | - Sylvain Harquel
- University Grenoble Alpes, Grenoble Institute of Neuroscience, INSERM U1216, Grenoble, France.,Laboratoire de Psychologie et NeuroCognition - LPNC, University Grenoble Alpes, CNRS UMR5105, Grenoble, France.,IRMaGe, University Grenoble-Alpes, CHU Grenoble Alpes, INSERM US17, CNRS UMS3552, Grenoble, France
| | - Alessandro Farnè
- IMPACT and Trajectoires Teams, INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), Lyon, France.,University UCBL Lyon 1, University of Lyon, Lyon, France.,Hospices Civils de Lyon, Neuro-immersion, Mouvement and Handicap, Lyon, France.,Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | - Karen T Reilly
- IMPACT and Trajectoires Teams, INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), Lyon, France.,University UCBL Lyon 1, University of Lyon, Lyon, France
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Abstract
Spatial documentation is exponentially increasing given the availability of Big Data in the Internet of Things, enabled by device miniaturization and data storage capacity. Bayesian spatial statistics is a useful statistical tool to determine the dependence structure and hidden patterns in space through prior knowledge and data likelihood. However, this class of modeling is not yet well explored when compared to adopting classification and regression in machine-learning models, in which the assumption of the spatiotemporal independence of the data is often made, that is an inexistent or very weak dependence. Thus, this systematic review aims to address the main models presented in the literature over the past 20 years, identifying the gaps and research opportunities. Elements such as random fields, spatial domains, prior specification, the covariance function, and numerical approximations are discussed. This work explores the two subclasses of spatial smoothing: global and local.
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Noccaro A, Mioli A, D'Alonzo M, Pinardi M, Pino GD, Formica D. Development and Validation of a Novel Calibration Methodology and Control Approach for Robot-Aided Transcranial Magnetic Stimulation (TMS). IEEE Trans Biomed Eng 2021; 68:1589-1600. [PMID: 33513096 DOI: 10.1109/tbme.2021.3055434] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
OBJECTIVE This article presents the development and validation of a new robotic system for Transcranial Magnetic Stimulation (TMS), characterized by a new control approach, and an ad-hoc calibration methodology, specifically devised for the TMS application. METHODS The robotic TMS platform is composed of a 7 dof manipulator, controlled by an impedance control, and a camera-based neuronavigation system. The proposed calibration method was optimized on the workspace useful for the specific TMS application (spherical shell around the subject's head), and tested on three different hand-eye and robot-world calibration algorithms. The platform functionality was tested on six healthy subjects during a real TMS procedure, over the left primary motor cortex. RESULTS employing our method significantly decreases ( ) the calibration error by 34% for the position and 19% for the orientation. The robotic TMS platform achieved greater orientation accuracy than the expert operators, significantly reducing orientation errors by 46% ( ). No significant differences were found in the position errors and in the amplitude of the motor evoked potentials (MEPs) between the robot-aided TMS and the expert operators. CONCLUSION The proposed calibration represents a valid method to significantly reduce the calibration errors in robot-aided TMS applications. Results showed the efficacy of the proposed platform (including the control algorithm) in administering a real TMS procedure, achieving better coil positioning than expert operators, and similar results in terms of MEPs. SIGNIFICANCE This article spotlights how to improve the performance of a robotic TMS platform, providing a reproducible and low-cost alternative to the few devices commercially available.
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Rossi S, Antal A, Bestmann S, Bikson M, Brewer C, Brockmöller J, Carpenter LL, Cincotta M, Chen R, Daskalakis JD, Di Lazzaro V, Fox MD, George MS, Gilbert D, Kimiskidis VK, Koch G, Ilmoniemi RJ, Lefaucheur JP, Leocani L, Lisanby SH, Miniussi C, Padberg F, Pascual-Leone A, Paulus W, Peterchev AV, Quartarone A, Rotenberg A, Rothwell J, Rossini PM, Santarnecchi E, Shafi MM, Siebner HR, Ugawa Y, Wassermann EM, Zangen A, Ziemann U, Hallett M. Safety and recommendations for TMS use in healthy subjects and patient populations, with updates on training, ethical and regulatory issues: Expert Guidelines. Clin Neurophysiol 2021; 132:269-306. [PMID: 33243615 PMCID: PMC9094636 DOI: 10.1016/j.clinph.2020.10.003] [Citation(s) in RCA: 505] [Impact Index Per Article: 168.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 10/12/2020] [Accepted: 10/13/2020] [Indexed: 12/11/2022]
Abstract
This article is based on a consensus conference, promoted and supported by the International Federation of Clinical Neurophysiology (IFCN), which took place in Siena (Italy) in October 2018. The meeting intended to update the ten-year-old safety guidelines for the application of transcranial magnetic stimulation (TMS) in research and clinical settings (Rossi et al., 2009). Therefore, only emerging and new issues are covered in detail, leaving still valid the 2009 recommendations regarding the description of conventional or patterned TMS protocols, the screening of subjects/patients, the need of neurophysiological monitoring for new protocols, the utilization of reference thresholds of stimulation, the managing of seizures and the list of minor side effects. New issues discussed in detail from the meeting up to April 2020 are safety issues of recently developed stimulation devices and pulse configurations; duties and responsibility of device makers; novel scenarios of TMS applications such as in the neuroimaging context or imaging-guided and robot-guided TMS; TMS interleaved with transcranial electrical stimulation; safety during paired associative stimulation interventions; and risks of using TMS to induce therapeutic seizures (magnetic seizure therapy). An update on the possible induction of seizures, theoretically the most serious risk of TMS, is provided. It has become apparent that such a risk is low, even in patients taking drugs acting on the central nervous system, at least with the use of traditional stimulation parameters and focal coils for which large data sets are available. Finally, new operational guidelines are provided for safety in planning future trials based on traditional and patterned TMS protocols, as well as a summary of the minimal training requirements for operators, and a note on ethics of neuroenhancement.
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Affiliation(s)
- Simone Rossi
- Department of Scienze Mediche, Chirurgiche e Neuroscienze, Unit of Neurology and Clinical Neurophysiology, Brain Investigation and Neuromodulation Lab (SI-BIN Lab), University of Siena, Italy.
| | - Andrea Antal
- Department of Clinical Neurophysiology, University Medical Center, Georg-August University of Goettingen, Germany; Institue of Medical Psychology, Otto-Guericke University Magdeburg, Germany
| | - Sven Bestmann
- Department of Movement and Clinical Neurosciences, UCL Queen Square Institute of Neurology, London, UK and Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York, New York, NY, USA
| | - Carmen Brewer
- National Institute on Deafness and Other Communication Disorders, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Jürgen Brockmöller
- Department of Clinical Pharmacology, University Medical Center, Georg-August University of Goettingen, Germany
| | - Linda L Carpenter
- Butler Hospital, Brown University Department of Psychiatry and Human Behavior, Providence, RI, USA
| | - Massimo Cincotta
- Unit of Neurology of Florence - Central Tuscany Local Health Authority, Florence, Italy
| | - Robert Chen
- Krembil Research Institute and Division of Neurology, Department of Medicine, University of Toronto, Canada
| | - Jeff D Daskalakis
- Center for Addiction and Mental Health (CAMH), University of Toronto, Canada
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico, Roma, Italy
| | - Michael D Fox
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Mark S George
- Medical University of South Carolina, Charleston, SC, USA
| | - Donald Gilbert
- Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Vasilios K Kimiskidis
- Laboratory of Clinical Neurophysiology, Aristotle University of Thessaloniki, AHEPA University Hospital, Greece
| | | | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering (NBE), Aalto University School of Science, Aalto, Finland
| | - Jean Pascal Lefaucheur
- EA 4391, ENT Team, Faculty of Medicine, Paris Est Creteil University (UPEC), Créteil, France; Clinical Neurophysiology Unit, Henri Mondor Hospital, Assistance Publique Hôpitaux de Paris, (APHP), Créteil, France
| | - Letizia Leocani
- Department of Neurology, Institute of Experimental Neurology (INSPE), IRCCS-San Raffaele Hospital, Vita-Salute San Raffaele University, Milano, Italy
| | - Sarah H Lisanby
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Carlo Miniussi
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Center for Memory Health, Hebrew SeniorLife, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; Guttmann Brain Health Institut, Institut Guttmann, Universitat Autonoma Barcelona, Spain
| | - Walter Paulus
- Department of Clinical Neurophysiology, University Medical Center, Georg-August University of Goettingen, Germany
| | - Angel V Peterchev
- Departments of Psychiatry & Behavioral Sciences, Biomedical Engineering, Electrical & Computer Engineering, and Neurosurgery, Duke University, Durham, NC, USA
| | - Angelo Quartarone
- Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
| | - Alexander Rotenberg
- Department of Neurology, Division of Epilepsy and Clinical Neurophysiology, Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - John Rothwell
- Department of Movement and Clinical Neurosciences, UCL Queen Square Institute of Neurology, London, UK and Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
| | - Paolo M Rossini
- Department of Neuroscience and Rehabilitation, IRCCS San Raffaele-Pisana, Roma, Italy
| | - Emiliano Santarnecchi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark; Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yoshikatzu Ugawa
- Department of Human Neurophysiology, School of Medicine, Fukushima Medical University, Fukushima, Japan
| | - Eric M Wassermann
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Abraham Zangen
- Zlotowski Center of Neuroscience, Ben Gurion University, Beer Sheva, Israel
| | - Ulf Ziemann
- Department of Neurology & Stroke, and Hertie-Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA.
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Tervo AE, Metsomaa J, Nieminen JO, Sarvas J, Ilmoniemi RJ. Automated search of stimulation targets with closed-loop transcranial magnetic stimulation. Neuroimage 2020; 220:117082. [PMID: 32593801 DOI: 10.1016/j.neuroimage.2020.117082] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 06/15/2020] [Accepted: 06/22/2020] [Indexed: 12/21/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) protocols often include a manual search of an optimal location and orientation of the coil or peak stimulating electric field to elicit motor responses in a target muscle. This target search is laborious, and the result is user-dependent. Here, we present a closed-loop search method that utilizes automatic electronic adjustment of the stimulation based on the previous responses. The electronic adjustment is achieved by multi-locus TMS, and the adaptive guiding of the stimulation is based on the principles of Bayesian optimization to minimize the number of stimuli (and time) needed in the search. We compared our target-search method with other methods, such as systematic sampling in a predefined cortical grid. Validation experiments on five healthy volunteers and further offline simulations showed that our adaptively guided search method needs only a relatively small number of stimuli to provide outcomes with good accuracy and precision. The automated method enables fast and user-independent optimization of stimulation parameters in research and clinical applications of TMS.
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Affiliation(s)
- Aino E Tervo
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Johanna Metsomaa
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Neurology & Stroke and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Jaakko O Nieminen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
| | - Jukka Sarvas
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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12
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Passera B, Harquel S, Vercueil L, Dojat M, Attye A, David O, Chauvin A. Modulation of visual hallucinations originating from deafferented occipital cortex by robotized transcranial magnetic stimulation. Clin Neurophysiol 2020; 131:1728-1730. [PMID: 32504933 DOI: 10.1016/j.clinph.2020.04.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 04/06/2020] [Accepted: 04/15/2020] [Indexed: 10/24/2022]
Affiliation(s)
- Brice Passera
- Univ. Grenoble Alpes, Inserm, CHU Grenoble Alpes, GIN, Grenoble, France; Univ. Grenoble-Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, F-38000 Grenoble, France.
| | - Sylvain Harquel
- Univ. Grenoble-Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, F-38000 Grenoble, France; Univ. Grenoble-Alpes, CNRS, CHU Grenoble Alpes, INSERM, CNRS, IRMaGe, F-38000 Grenoble, France
| | - Laurent Vercueil
- Univ. Grenoble Alpes, Inserm, CHU Grenoble Alpes, GIN, Grenoble, France; Neurophysiology Unit, Neurology Department, CHU Grenoble Alpes, F-38000 Grenoble, France
| | - Michel Dojat
- Univ. Grenoble Alpes, Inserm, CHU Grenoble Alpes, GIN, Grenoble, France
| | - Arnaud Attye
- Univ. Grenoble-Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, F-38000 Grenoble, France
| | - Olivier David
- Univ. Grenoble Alpes, Inserm, CHU Grenoble Alpes, GIN, Grenoble, France
| | - Alan Chauvin
- Univ. Grenoble-Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, F-38000 Grenoble, France
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Affiliation(s)
- Til O Bergmann
- Department of Neurology and Stroke, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,Deutsches Resilienz Zentrum, University Medical Center Mainz, Mainz, Germany
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14
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Valero-Cabré A, Amengual JL, Stengel C, Pascual-Leone A, Coubard OA. Transcranial magnetic stimulation in basic and clinical neuroscience: A comprehensive review of fundamental principles and novel insights. Neurosci Biobehav Rev 2017; 83:381-404. [DOI: 10.1016/j.neubiorev.2017.10.006] [Citation(s) in RCA: 190] [Impact Index Per Article: 27.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2017] [Revised: 09/29/2017] [Accepted: 10/06/2017] [Indexed: 01/13/2023]
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