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Tan B, Chen J, Liu Y, Lin Q, Wang Y, Shi S, Ye Y, Che X. Differential analgesic effects of high-frequency or accelerated intermittent theta burst stimulation of M1 on experimental tonic pain: Correlations with cortical activity changes assessed by TMS-EEG. Neurotherapeutics 2024:e00451. [PMID: 39304439 DOI: 10.1016/j.neurot.2024.e00451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Revised: 09/08/2024] [Accepted: 09/08/2024] [Indexed: 09/22/2024] Open
Abstract
Accelerated intermittent theta burst stimulation (AiTBS) has attracted much attention in the past few years as a new form of brain stimulation paradigm. However, it is unclear the relative efficacy of AiTBS on cortical excitability compared to conventional high-frequency rTMS. Using concurrent TMS and electroencephalogram (TMS-EEG), this study systematically compared the efficacy on cortical excitability and a typical clinical application (i.e. pain), between AiTBS with different intersession interval (ISIs) and 10-Hz rTMS. Participants received 10-Hz rTMS, AiTBS-15 (3 iTBS sessions with a 15-min ISI), AiTBS-50 (3 iTBS sessions with a 50-min ISI), or Sham stimulation over the primary motor cortex on four separate days. All four protocols included a total of 1800 pulses but with different session durations (10-Hz rTMS = 18, AiTBS-15 = 40, and AiTBS-50 = 110 min). AiTBS-50 and 10-Hz rTMS were more effective in pain reduction compared to AiTBS-15. Using single-pulse TMS-induced oscillation, our data revealed low gamma oscillation as a shared cortical excitability change across all three active rTMS protocols but demonstrated completely opposite directions. Changes in low gamma oscillation were further associated with changes in pain perception across the three active conditions. In contrast, a distinct pattern of TMS-evoked potentials (TEPs) was revealed, with 10-Hz rTMS decreasing inhibitory N100 amplitude and AiTBS-15 reducing excitatory P60 amplitude. These changes in TEPs were also covarying with low gamma power changes. Sham stimulation indicated no significant effect on either cortical excitability or pain perception. These results are relevant only for provoked experimental pain, without being predictive for chronic pain, and revealed a change in low gamma oscillation, particularly around the very particular frequency of 40 Hz, shared between AiTBS and high-frequency rTMS. Conversely, cortical excitability (balance between excitation and inhibition) assessed by TEP recording was modulated differently by AiTBS and high-frequency rTMS paradigms.
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Affiliation(s)
- Bolin Tan
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Jielin Chen
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Ying Liu
- Department of Anesthesiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qiuye Lin
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Ying Wang
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Shuyan Shi
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Yang Ye
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Xianwei Che
- Centre for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.
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Harquel S, Cadic-Melchior A, Morishita T, Fleury L, Witon A, Ceroni M, Brügger J, Meyer NH, Evangelista GG, Egger P, Beanato E, Menoud P, Van de Ville D, Micera S, Blanke O, Léger B, Adolphsen J, Jagella C, Constantin C, Alvarez V, Vuadens P, Turlan JL, Mühl A, Bonvin C, Koch PJ, Wessel MJ, Hummel FC. Stroke Recovery-Related Changes in Cortical Reactivity Based on Modulation of Intracortical Inhibition. Stroke 2024; 55:1629-1640. [PMID: 38639087 DOI: 10.1161/strokeaha.123.045174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 02/29/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Cortical excitation/inhibition dynamics have been suggested as a key mechanism occurring after stroke. Their supportive or maladaptive role in the course of recovery is still not completely understood. Here, we used transcranial magnetic stimulation (TMS)-electroencephalography coupling to study cortical reactivity and intracortical GABAergic inhibition, as well as their relationship to residual motor function and recovery longitudinally in patients with stroke. METHODS Electroencephalography responses evoked by TMS applied to the ipsilesional motor cortex were acquired in patients with stroke with upper limb motor deficit in the acute (1 week), early (3 weeks), and late subacute (3 months) stages. Readouts of cortical reactivity, intracortical inhibition, and complexity of the evoked dynamics were drawn from TMS-evoked potentials induced by single-pulse and paired-pulse TMS (short-interval intracortical inhibition). Residual motor function was quantified through a detailed motor evaluation. RESULTS From 76 patients enrolled, 66 were included (68.2±13.2 years old, 18 females), with a Fugl-Meyer score of the upper extremity of 46.8±19. The comparison with TMS-evoked potentials of healthy older revealed that most affected patients exhibited larger and simpler brain reactivity patterns (Pcluster<0.05). Bayesian ANCOVA statistical evidence for a link between abnormally high motor cortical excitability and impairment level. A decrease in excitability in the following months was significantly correlated with better motor recovery in the whole cohort and the subgroup of recovering patients. Investigation of the intracortical GABAergic inhibitory system revealed the presence of beneficial disinhibition in the acute stage, followed by a normalization of inhibitory activity. This was supported by significant correlations between motor scores and the contrast of local mean field power and readouts of signal dynamics. CONCLUSIONS The present results revealed an abnormal motor cortical reactivity in patients with stroke, which was driven by perturbations and longitudinal changes within the intracortical inhibition system. They support the view that disinhibition in the ipsilesional motor cortex during the first-week poststroke is beneficial and promotes neuronal plasticity and recovery.
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Affiliation(s)
- Sylvain Harquel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Andéol Cadic-Melchior
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Takuya Morishita
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Lisa Fleury
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Adrien Witon
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Health-IT, Centre de Service, Hôpital du Valais, Switzerland (A.W.)
| | - Martino Ceroni
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Julia Brügger
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Nathalie H Meyer
- Laboratory of Cognitive Neuroscience, INX and BMI, EPFL, Geneva, Switzerland (N.H.M., O.B.)
| | - Giorgia G Evangelista
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Philip Egger
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Elena Beanato
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Pauline Menoud
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Dimitri Van de Ville
- Medical Image Processing Laboratory, INX, EPFL, Geneva, Switzerland (D.V.V.)
- Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Switzerland (D.V.d.V.)
| | - Silvestro Micera
- The Biorobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy (S.M.)
- Bertarelli Foundation Chair in Translational Neuroengineering, INX and Institute of Bioengineering, School of Engineering, Ecole Polytechnique Fédérale de Lausanne (S.M.)
| | - Olaf Blanke
- Laboratory of Cognitive Neuroscience, INX and BMI, EPFL, Geneva, Switzerland (N.H.M., O.B.)
- Department of Neurology, Geneva University Hospital (HUG), Switzerland (O.B.)
| | - Bertrand Léger
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | | | | | | | - Vincent Alvarez
- Department of Neurology, Hôpital du Valais, Sion, Switzerland (C.C., V.A., C.B.)
| | - Philippes Vuadens
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | - Jean-Luc Turlan
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | - Andreas Mühl
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | - Christophe Bonvin
- Department of Neurology, Hôpital du Valais, Sion, Switzerland (C.C., V.A., C.B.)
| | - Philipp J Koch
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Department of Neurology, University of Lübeck, Germany (P.J.K.)
| | - Maximilian J Wessel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Department of Neurology, Julius-Maximilians-University Würzburg, Germany (M.J.W.)
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Clinical Neuroscience, Geneva University Hospital, Switzerland (F.C.H.)
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3
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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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Harquel S, Cian C, Torlay L, Cousin E, Barraud PA, Bougerol T, Guerraz M. Modulation of Visually Induced Self-motion Illusions by α Transcranial Electric Stimulation over the Superior Parietal Cortex. J Cogn Neurosci 2024; 36:143-154. [PMID: 37870524 DOI: 10.1162/jocn_a_02074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2023]
Abstract
The growing popularity of virtual reality systems has led to a renewed interest in understanding the neurophysiological correlates of the illusion of self-motion (vection), a phenomenon that can be both intentionally induced or avoided in such systems, depending on the application. Recent research has highlighted the modulation of α power oscillations over the superior parietal cortex during vection, suggesting the occurrence of inhibitory mechanisms in the sensorimotor and vestibular functional networks to resolve the inherent visuo-vestibular conflict. The present study aims to further explore this relationship and investigate whether neuromodulating these waves could causally affect the quality of vection. In a crossover design, 22 healthy volunteers received high amplitude and focused α-tACS (transcranial alternating current stimulation) over the superior parietal cortex while experiencing visually induced vection triggered by optokinetic stimulation. The tACS was tuned to each participant's individual α peak frequency, with θ-tACS and sham stimulation serving as controls. Overall, participants experienced better quality vection during α-tACS compared with control θ-tACS and sham stimulations, as quantified by the intensity of vection. The observed neuromodulation supports a causal relationship between parietal α oscillations and visually induced self-motion illusions, with their entrainment triggering overinhibition of the conflict within the sensorimotor and vestibular functional networks. These results confirm the potential of noninvasive brain stimulation for modulating visuo-vestibular conflicts, which could help to enhance the sense of presence in virtual reality environments.
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Affiliation(s)
- Sylvain Harquel
- Université Grenoble-Alpes, Université Savoie Mont Blanc, CNRS, UMR5105, LPNC, Grenoble, France
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology Lausanne (EPFL), Campus Biotech, Geneva, Switzerland
| | - Corinne Cian
- Université Grenoble-Alpes, Université Savoie Mont Blanc, CNRS, UMR5105, LPNC, Grenoble, France
- Institut de Recherche Biomédicale des Armées, Brétigny sur Orge, France
| | - Laurent Torlay
- Université Grenoble-Alpes, Université Savoie Mont Blanc, CNRS, UMR5105, LPNC, Grenoble, France
| | - Emilie Cousin
- Université Grenoble-Alpes, Université Savoie Mont Blanc, CNRS, UMR5105, LPNC, Grenoble, France
| | - Pierre-Alain Barraud
- Université Grenoble-Alpes, CNRS, CHU Grenoble-Alpes, Grenoble INP, TIMC-IMAG, Grenoble, France
| | - Thierry Bougerol
- Centre Hospitalier Université Grenoble-Alpes, Pôle Psychiatrie, Grenoble, France
- Université Grenoble-Alpes, Inserm, U1216, Grenoble Institut des Neurosciences, Grenoble, France
| | - Michel Guerraz
- Université Grenoble-Alpes, Université Savoie Mont Blanc, CNRS, UMR5105, LPNC, Grenoble, France
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5
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Al E, Stephani T, Engelhardt M, Haegens S, Villringer A, Nikulin VV. Cardiac activity impacts cortical motor excitability. PLoS Biol 2023; 21:e3002393. [PMID: 38015826 PMCID: PMC10684011 DOI: 10.1371/journal.pbio.3002393] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 10/19/2023] [Indexed: 11/30/2023] Open
Abstract
Human cognition and action can be influenced by internal bodily processes such as heartbeats. For instance, somatosensory perception is impaired both during the systolic phase of the cardiac cycle and when heartbeats evoke stronger cortical responses. Here, we test whether these cardiac effects originate from overall changes in cortical excitability. Cortical and corticospinal excitability were assessed using electroencephalographic and electromyographic responses to transcranial magnetic stimulation while concurrently monitoring cardiac activity with electrocardiography. Cortical and corticospinal excitability were found to be highest during systole and following stronger neural responses to heartbeats. Furthermore, in a motor task, hand-muscle activity and the associated desynchronization of sensorimotor oscillations were stronger during systole. These results suggest that systolic cardiac signals have a facilitatory effect on motor excitability-in contrast to sensory attenuation that was previously reported for somatosensory perception. Thus, it is possible that distinct time windows exist across the cardiac cycle, optimizing either perception or action.
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Affiliation(s)
- Esra Al
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Center for Stroke Research Berlin (CSB), Charité–Universitätsmedizin Berlin, Berlin, Germany
- Department of Psychiatry, Columbia University, New York, New York, United States of America
- Division of Systems Neuroscience, New York State Psychiatric Institute, New York, New York, United States of America
| | - Tilman Stephani
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- International Max Planck Research School NeuroCom, Leipzig, Germany
| | - Melina Engelhardt
- Charité–Universitätsmedizin Berlin, Klinik für Neurochirurgie, Berlin, Germany
- Charité–Universitätsmedizin Berlin, Einstein Center for Neurosciences, Berlin, Germany
| | - Saskia Haegens
- Department of Psychiatry, Columbia University, New York, New York, United States of America
- Division of Systems Neuroscience, New York State Psychiatric Institute, New York, New York, United States of America
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- MindBrainBody Institute, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Center for Stroke Research Berlin (CSB), Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Vadim V. Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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Vucic S, Stanley Chen KH, Kiernan MC, Hallett M, Benninger DH, Di Lazzaro V, Rossini PM, Benussi A, Berardelli A, Currà A, Krieg SM, Lefaucheur JP, Long Lo Y, Macdonell RA, Massimini M, Rosanova M, Picht T, Stinear CM, Paulus W, Ugawa Y, Ziemann U, Chen R. Clinical diagnostic utility of transcranial magnetic stimulation in neurological disorders. Updated report of an IFCN committee. Clin Neurophysiol 2023; 150:131-175. [PMID: 37068329 PMCID: PMC10192339 DOI: 10.1016/j.clinph.2023.03.010] [Citation(s) in RCA: 55] [Impact Index Per Article: 55.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/28/2023] [Accepted: 03/09/2023] [Indexed: 03/31/2023]
Abstract
The review provides a comprehensive update (previous report: Chen R, Cros D, Curra A, Di Lazzaro V, Lefaucheur JP, Magistris MR, et al. The clinical diagnostic utility of transcranial magnetic stimulation: report of an IFCN committee. Clin Neurophysiol 2008;119(3):504-32) on clinical diagnostic utility of transcranial magnetic stimulation (TMS) in neurological diseases. Most TMS measures rely on stimulation of motor cortex and recording of motor evoked potentials. Paired-pulse TMS techniques, incorporating conventional amplitude-based and threshold tracking, have established clinical utility in neurodegenerative, movement, episodic (epilepsy, migraines), chronic pain and functional diseases. Cortical hyperexcitability has emerged as a diagnostic aid in amyotrophic lateral sclerosis. Single-pulse TMS measures are of utility in stroke, and myelopathy even in the absence of radiological changes. Short-latency afferent inhibition, related to central cholinergic transmission, is reduced in Alzheimer's disease. The triple stimulation technique (TST) may enhance diagnostic utility of conventional TMS measures to detect upper motor neuron involvement. The recording of motor evoked potentials can be used to perform functional mapping of the motor cortex or in preoperative assessment of eloquent brain regions before surgical resection of brain tumors. TMS exhibits utility in assessing lumbosacral/cervical nerve root function, especially in demyelinating neuropathies, and may be of utility in localizing the site of facial nerve palsies. TMS measures also have high sensitivity in detecting subclinical corticospinal lesions in multiple sclerosis. Abnormalities in central motor conduction time or TST correlate with motor impairment and disability in MS. Cerebellar stimulation may detect lesions in the cerebellum or cerebello-dentato-thalamo-motor cortical pathways. Combining TMS with electroencephalography, provides a novel method to measure parameters altered in neurological disorders, including cortical excitability, effective connectivity, and response complexity.
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Affiliation(s)
- Steve Vucic
- Brain, Nerve Research Center, The University of Sydney, Sydney, Australia.
| | - Kai-Hsiang Stanley Chen
- Department of Neurology, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
| | - Matthew C Kiernan
- Brain and Mind Centre, The University of Sydney; and Department of Neurology, Royal Prince Alfred Hospital, Australia
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, Maryland, United States
| | - David H Benninger
- Department of Neurology, University Hospital of Lausanne (CHUV), Switzerland
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, University Campus Bio-Medico of Rome, Rome, Italy
| | - Paolo M Rossini
- Department of Neurosci & Neurorehab IRCCS San Raffaele-Rome, Italy
| | - Alberto Benussi
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alfredo Berardelli
- IRCCS Neuromed, Pozzilli; Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Antonio Currà
- Department of Medico-Surgical Sciences and Biotechnologies, Alfredo Fiorini Hospital, Sapienza University of Rome, Terracina, LT, Italy
| | - Sandro M Krieg
- Department of Neurosurgery, Technical University Munich, School of Medicine, Klinikum rechts der Isar, Munich, Germany
| | - Jean-Pascal Lefaucheur
- Univ Paris Est Creteil, EA4391, ENT, Créteil, France; Clinical Neurophysiology Unit, Henri Mondor Hospital, AP-HP, Créteil, France
| | - Yew Long Lo
- Department of Neurology, National Neuroscience Institute, Singapore General Hospital, Singapore, and Duke-NUS Medical School, Singapore
| | | | - Marcello Massimini
- Dipartimento di Scienze Biomediche e Cliniche, Università degli Studi di Milano, Milan, Italy; Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences University of Milan, Milan, Italy
| | - Thomas Picht
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Cluster of Excellence: "Matters of Activity. Image Space Material," Humboldt University, Berlin Simulation and Training Center (BeST), Charité-Universitätsmedizin Berlin, Germany
| | - Cathy M Stinear
- Department of Medicine Waipapa Taumata Rau, University of Auckland, Auckland, Aotearoa, New Zealand
| | - Walter Paulus
- Department of Neurology, Ludwig-Maximilians-Universität München, München, Germany
| | - Yoshikazu Ugawa
- Department of Human Neurophysiology, School of Medicine, Fukushima Medical University, Japan
| | - Ulf Ziemann
- Department of Neurology and Stroke, Eberhard Karls University of Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany; Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Otfried-Müller-Straße 27, 72076 Tübingen, Germany
| | - Robert Chen
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital-UHN, Division of Neurology-University of Toronto, Toronto Canada
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7
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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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8
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Hernandez-Pavon JC, Veniero D, Bergmann TO, Belardinelli P, Bortoletto M, Casarotto S, Casula EP, Farzan F, Fecchio M, Julkunen P, Kallioniemi E, Lioumis P, Metsomaa J, Miniussi C, Mutanen TP, Rocchi L, Rogasch NC, Shafi MM, Siebner HR, Thut G, Zrenner C, Ziemann U, Ilmoniemi RJ. TMS combined with EEG: Recommendations and open issues for data collection and analysis. Brain Stimul 2023; 16:567-593. [PMID: 36828303 DOI: 10.1016/j.brs.2023.02.009] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 02/10/2023] [Accepted: 02/19/2023] [Indexed: 02/25/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS-EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS-EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS-EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS-EEG covered all aspects that should be considered in TMS-EEG experiments, providing methodological recommendations (when possible) for effective TMS-EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS-EEG methodology and thus may promote standardization of experimental and computational procedures across groups.
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Affiliation(s)
- Julio C Hernandez-Pavon
- Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Legs + Walking Lab, Shirley Ryan AbilityLab, Chicago, IL, USA; Center for Brain Stimulation, Shirley Ryan AbilityLab, Chicago, IL, USA.
| | | | - Til Ole Bergmann
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Germany; Leibniz Institute for Resilience Research (LIR), Mainz, Germany
| | - Paolo Belardinelli
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, TN, Italy; Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany
| | - Marta Bortoletto
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy; IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Elias P Casula
- Department of Systems Medicine, University of Tor Vergata, Rome, Italy
| | - Faranak Farzan
- Simon Fraser University, School of Mechatronic Systems Engineering, Surrey, British Columbia, Canada
| | - Matteo Fecchio
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Petro Julkunen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
| | - Elisa Kallioniemi
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Johanna Metsomaa
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Carlo Miniussi
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, TN, Italy
| | - Tuomas P Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Lorenzo Rocchi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Nigel C Rogasch
- University of Adelaide, Adelaide, Australia; South Australian Health and Medical Research Institute, Adelaide, Australia; Monash University, Melbourne, Australia
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gregor Thut
- School of Psychology and Neuroscience, University of Glasgow, United Kingdom
| | - Christoph Zrenner
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
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9
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Lioumis P, Rosanova M. The role of neuronavigation in TMS-EEG studies: current applications and future perspectives. J Neurosci Methods 2022; 380:109677. [PMID: 35872153 DOI: 10.1016/j.jneumeth.2022.109677] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 07/12/2022] [Accepted: 07/19/2022] [Indexed: 11/28/2022]
Abstract
Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) allows measuring non-invasively the electrical response of the human cerebral cortex to a direct perturbation. Complementing TMS-EEG with a structural neuronavigation tool (nTMS-EEG) is key for accurately selecting cortical areas, targeting them, and adjusting the stimulation parameters based on some relevant anatomical priors. This step, together with the employment of visualization tools designed to perform a quality check of TMS-evoked potentials (TEPs) in real-time during acquisition, is key for maximizing the impact of the TMS pulse on the cortex and in ensuring highly reproducible measurements within sessions and across subjects. Moreover, storing stimulation parameters in the neuronavigation system can help in reproducing the stimulation parameters within and across experimental sessions and sharing them across research centers. Finally, the systematic employment of neuronavigation in TMS-EEG studies is also key to standardize measurements in clinical populations in search for reliable diagnostic and prognostic TMS-EEG-based biomarkers for neurological and psychiatric disorders.
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Affiliation(s)
- Pantelis Lioumis
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; BioMag Laboratory, HUS Diagnostic Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy
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10
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Rostami M, Zomorrodi R, Rostami R, Hosseinzadeh GA. Impact of methodological variability on EEG responses evoked by transcranial magnetic stimulation: a meta-analysis. Clin Neurophysiol 2022; 142:154-180. [DOI: 10.1016/j.clinph.2022.07.495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 07/12/2022] [Accepted: 07/15/2022] [Indexed: 12/01/2022]
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11
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Ross JM, Sarkar M, Keller CJ. Experimental suppression of transcranial magnetic stimulation-electroencephalography sensory potentials. Hum Brain Mapp 2022; 43:5141-5153. [PMID: 35770956 PMCID: PMC9812254 DOI: 10.1002/hbm.25990] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/13/2022] [Accepted: 06/10/2022] [Indexed: 01/15/2023] Open
Abstract
The sensory experience of transcranial magnetic stimulation (TMS) evokes cortical responses measured in electroencephalography (EEG) that confound interpretation of TMS-evoked potentials (TEPs). Methods for sensory masking have been proposed to minimize sensory contributions to the TEP, but the most effective combination for suprathreshold TMS to dorsolateral prefrontal cortex (dlPFC) is unknown. We applied sensory suppression techniques and quantified electrophysiology and perception from suprathreshold dlPFC TMS to identify the best combination to minimize the sensory TEP. In 21 healthy adults, we applied single pulse TMS at 120% resting motor threshold (rMT) to the left dlPFC and compared EEG vertex N100-P200 and perception. Conditions included three protocols: No masking (no auditory masking, no foam, and jittered interstimulus interval [ISI]), Standard masking (auditory noise, foam, and jittered ISI), and our ATTENUATE protocol (auditory noise, foam, over-the-ear protection, and unjittered ISI). ATTENUATE reduced vertex N100-P200 by 56%, "click" loudness perception by 50%, and scalp sensation by 36%. We show that sensory prediction, induced with predictable ISI, has a suppressive effect on vertex N100-P200, and that combining standard suppression protocols with sensory prediction provides the best N100-P200 suppression. ATTENUATE was more effective than Standard masking, which only reduced vertex N100-P200 by 22%, loudness by 27%, and scalp sensation by 24%. We introduce a sensory suppression protocol superior to Standard masking and demonstrate that using an unjittered ISI can contribute to minimizing sensory confounds. ATTENUATE provides superior sensory suppression to increase TEP signal-to-noise and contributes to a growing understanding of TMS-EEG sensory neuroscience.
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Affiliation(s)
- Jessica M. Ross
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental IllnessResearch, Education, and Clinical Center (MIRECC)Palo AltoCaliforniaUSA,Department of Psychiatry and Behavioral SciencesStanford University Medical CenterStanfordCaliforniaUSA
| | - Manjima Sarkar
- Department of Psychiatry and Behavioral SciencesStanford University Medical CenterStanfordCaliforniaUSA
| | - Corey J. Keller
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental IllnessResearch, Education, and Clinical Center (MIRECC)Palo AltoCaliforniaUSA,Department of Psychiatry and Behavioral SciencesStanford University Medical CenterStanfordCaliforniaUSA
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12
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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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13
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Tervo AE, Nieminen JO, Lioumis P, Metsomaa J, Souza VH, Sinisalo H, Stenroos M, Sarvas J, Ilmoniemi RJ. Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback. Brain Stimul 2022; 15:523-531. [PMID: 35337598 PMCID: PMC8940636 DOI: 10.1016/j.brs.2022.01.016] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/17/2021] [Accepted: 01/28/2022] [Indexed: 12/16/2022] Open
Abstract
Background Transcranial magnetic stimulation (TMS) is widely used in brain research and treatment of various brain dysfunctions. However, the optimal way to target stimulation and administer TMS therapies, for example, where and in which electric field direction the stimuli should be given, is yet to be determined. Objective To develop an automated closed-loop system for adjusting TMS parameters (in this work, the stimulus orientation) online based on TMS-evoked brain activity measured with electroencephalography (EEG). Methods We developed an automated closed-loop TMS–EEG set-up. In this set-up, the stimulus parameters are electronically adjusted with multi-locus TMS. As a proof of concept, we developed an algorithm that automatically optimizes the stimulation orientation based on single-trial EEG responses. We applied the algorithm to determine the electric field orientation that maximizes the amplitude of the TMS–EEG responses. The validation of the algorithm was performed with six healthy volunteers, repeating the search twenty times for each subject. Results The validation demonstrated that the closed-loop control worked as desired despite the large variation in the single-trial EEG responses. We were often able to get close to the orientation that maximizes the EEG amplitude with only a few tens of pulses. Conclusion Optimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity. Closed-loop set-up for guiding TMS with brain activity feedback. Automatic stimulus orientation optimization based on TMS-evoked EEG responses. Adjusting TMS parameters electronically allows fast and effortless procedures. TMS-evoked EEG responses depend on the stimulus orientation.
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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; 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; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
| | - Pantelis Lioumis
- 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; Cognitive Brain Research Unit, Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johanna Metsomaa
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; Department of Neurology & Stroke and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Victor H Souza
- 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
| | - Heikki Sinisalo
- 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
| | - Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Jukka Sarvas
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, 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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14
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Ross JM, Ozdemir RA, Lian SJ, Fried PJ, Schmitt EM, Inouye SK, Pascual-Leone A, Shafi MM. A structured ICA-based process for removing auditory evoked potentials. Sci Rep 2022; 12:1391. [PMID: 35082350 PMCID: PMC8791940 DOI: 10.1038/s41598-022-05397-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 12/22/2021] [Indexed: 12/13/2022] Open
Abstract
Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs), recorded using electroencephalography (EEG), reflect a combination of TMS-induced cortical activity and multi-sensory responses to TMS. The auditory evoked potential (AEP) is a high-amplitude sensory potential-evoked by the "click" sound produced by every TMS pulse-that can dominate the TEP and obscure observation of other neural components. The AEP is peripherally evoked and therefore should not be stimulation site specific. We address the problem of disentangling the peripherally evoked AEP of the TEP from components evoked by cortical stimulation and ask whether removal of AEP enables more accurate isolation of TEP. We hypothesized that isolation of the AEP using Independent Components Analysis (ICA) would reveal features that are stimulation site specific and unique individual features. In order to improve the effectiveness of ICA for removal of AEP from the TEP, and thus more clearly separate the transcranial-evoked and non-specific TMS-modulated potentials, we merged sham and active TMS datasets representing multiple stimulation conditions, removed the resulting AEP component, and evaluated performance across different sham protocols and clinical populations using reduction in Global and Local Mean Field Power (GMFP/LMFP) and cosine similarity analysis. We show that removing AEPs significantly reduced GMFP and LMFP in the post-stimulation TEP (14 to 400 ms), driven by time windows consistent with the N100 and P200 temporal characteristics of AEPs. Cosine similarity analysis supports that removing AEPs reduces TEP similarity between subjects and reduces TEP similarity between stimulation conditions. Similarity is reduced most in a mid-latency window consistent with the N100 time-course, but nevertheless remains high in this time window. Residual TEP in this window has a time-course and topography unique from AEPs, which follow-up exploratory analyses suggest could be a modulation in the alpha band that is not stimulation site specific but is unique to individual subject. We show, using two datasets and two implementations of sham, evidence in cortical topography, TEP time-course, GMFP/LMFP and cosine similarity analyses that this procedure is effective and conservative in removing the AEP from TEP, and may thus better isolate TMS-evoked activity. We show TEP remaining in early, mid and late latencies. The early response is site and subject specific. Later response may be consistent with TMS-modulated alpha activity that is not site specific but is unique to the individual. TEP remaining after removal of AEP is unique and can provide insight into TMS-evoked potentials and other modulated oscillatory dynamics.
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Affiliation(s)
- Jessica M Ross
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, KS-423, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Recep A Ozdemir
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, KS-423, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Shu Jing Lian
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, KS-423, Boston, MA, USA
| | - Peter J Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, KS-423, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Eva M Schmitt
- Hinda and Arthur Marcus Institute for Aging Research, and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
| | - Sharon K Inouye
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Hinda and Arthur Marcus Institute for Aging Research, and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Hinda and Arthur Marcus Institute for Aging Research, and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
- Guttmann Brain Health Institute, Institut Guttmann, Institut Universitari de Neurorehabilitació adscrit a la UAB, Badalona, Barcelona, Spain
| | - Mouhsin M Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, KS-423, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
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15
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Gordon PC, Jovellar DB, Song Y, Zrenner C, Belardinelli P, Siebner HR, Ziemann U. Recording brain responses to TMS of primary motor cortex by EEG - utility of an optimized sham procedure. Neuroimage 2021; 245:118708. [PMID: 34743050 PMCID: PMC8752966 DOI: 10.1016/j.neuroimage.2021.118708] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 10/31/2021] [Accepted: 11/02/2021] [Indexed: 11/30/2022] Open
Abstract
Optimized sham TMS-EEG is introduced and tested. Sham combined auditory and supramaximal electrical somatosensory stimulation. Subjects reported equal sensory perception during sham and real TMS. Subtraction revealed evoked EEG potentials and beta-band power specific to real TMS. The optimized sham procedure is relevant in research and therapeutic settings.
Introduction Electroencephalography (EEG) is increasingly used to investigate brain responses to transcranial magnetic stimulation (TMS). A relevant issue is that TMS is associated with considerable auditory and somatosensory stimulation, causing peripherally evoked potentials (PEPs) in the EEG, which contaminate the direct cortical responses to TMS (TEPs). All previous attempts to control for PEPs suffer from significant limitations. Objective/Hypothesis To design an optimized sham procedure to control all sensory input generated by subthreshold real TMS targeting the hand area of the primary motor cortex (M1), enabling reliable separation of TEPs from PEPs. Methods In 23 healthy (16 female) subjects, we recorded EEG activity evoked by an optimized sham TMS condition which masks and matches auditory and somatosensory co-stimulation during the real TMS condition: auditory control was achieved by noise masking and by using a second TMS coil that was placed on top of the real TMS coil and produced a calibrated sound pressure level. Somatosensory control was obtained by electric stimulation (ES) of the scalp with intensities sufficient to saturate somatosensory input. ES was applied in both the sham and real TMS conditions. Perception of auditory and somatosensory inputs in the sham and real TMS conditions were compared by psychophysical testing. Transcranially evoked EEG signal changes were identified by subtraction of EEG activity in the sham condition from EEG activity in the real TMS condition. Results Perception of auditory and somatosensory inputs in the sham vs. real TMS conditions was comparable. Both sham and real TMS evoked a series of similar EEG signal deflections and induced broadband power increase in oscillatory activity. Notably, the present procedure revealed EEG potentials and a transient increase in beta band power at the site of stimulation that were only present in the real TMS condition. Discussion The results validate the effectiveness of our optimized sham approach. Despite the presence of typical responses attributable to sensory input, the procedure provided evidence for direct cortical activation by subthreshold TMS of M1. The findings are relevant for future TMS-EEG experiments that aim at measuring regional brain target engagement controlled by an optimized sham procedure.
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Affiliation(s)
- Pedro C Gordon
- Department of Neurology & Stroke, University of Tübingen, Hoppe-Seyler-Straße 3, Tübingen 72076, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - D Blair Jovellar
- Department of Neurology & Stroke, University of Tübingen, Hoppe-Seyler-Straße 3, Tübingen 72076, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - YuFei Song
- Department of Neurology & Stroke, University of Tübingen, Hoppe-Seyler-Straße 3, Tübingen 72076, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Christoph Zrenner
- Department of Neurology & Stroke, University of Tübingen, Hoppe-Seyler-Straße 3, Tübingen 72076, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Paolo Belardinelli
- Department of Neurology & Stroke, University of Tübingen, Hoppe-Seyler-Straße 3, Tübingen 72076, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; CIMeC, Center for Mind/Brain Sciences, University of Trento, Italy
| | - Hartwig Roman Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Department of Neurology, Copenhagen University Hospital - Bispebjerg and Fredriksberg, Copenhagen, Denmark
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Hoppe-Seyler-Straße 3, Tübingen 72076, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany.
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16
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Nicolas G, Castet E, Rabier A, Kristensen E, Dojat M, Guérin-Dugué A. Neural correlates of intra-saccadic motion perception. J Vis 2021; 21:19. [PMID: 34698810 PMCID: PMC8556557 DOI: 10.1167/jov.21.11.19] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Retinal motion of the visual scene is not consciously perceived during ocular saccades in normal everyday conditions. It has been suggested that extra-retinal signals actively suppress intra-saccadic motion perception to preserve stable perception of the visual world. However, using stimuli optimized to preferentially activate the M-pathway, Castet and Masson (2000) demonstrated that motion can be perceived during a saccade. Based on this psychophysical paradigm, we used electroencephalography and eye-tracking recordings to investigate the neural correlates related to the conscious perception of intra-saccadic motion. We demonstrated the effective involvement during saccades of the cortical areas V1-V2 and MT-V5, which convey motion information along the M-pathway. We also showed that individual motion perception was related to retinal temporal frequency.
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Affiliation(s)
- Gaëlle Nicolas
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, 38000 Grenoble, France.,
| | - Eric Castet
- LPC, Laboratoire de Psychologie Cognitive (UMR 7290), Aix-Marseille Univ, CNRS, LPC, Marseille, France.,
| | - Adrien Rabier
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, 38000 Grenoble, France.,
| | | | - Michel Dojat
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, GIN, 38000 Grenoble, France.,
| | - Anne Guérin-Dugué
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, 38000 Grenoble, France.,
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17
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Yu K, Niu X, He B. Neuromodulation Management of Chronic Neuropathic Pain in The Central Nervous system. ADVANCED FUNCTIONAL MATERIALS 2020; 30:1908999. [PMID: 34335132 PMCID: PMC8323399 DOI: 10.1002/adfm.201908999] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Indexed: 05/05/2023]
Abstract
Neuromodulation is becoming one of the clinical tools for treating chronic neuropathic pain by transmitting controlled physical energy to the pre-identified neural targets in the central nervous system. Its nature of drug-free, non-addictive and improved targeting have attracted increasing attention among neuroscience research and clinical practices. This article provides a brief overview of the neuropathic pain and pharmacological routines for treatment, summarizes both the invasive and non-invasive neuromodulation modalities for pain management, and highlights an emerging brain stimulation technology, transcranial focused ultrasound (tFUS) with a focus on ultrasound transducer devices and the achieved neuromodulation effects and applications on pain management. Practical considerations of spatial guidance for tFUS are discussed for clinical applications. The safety of transcranial ultrasound neuromodulation and its future prospectives on pain management are also discussed.
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Affiliation(s)
| | | | - Bin He
- Department of Biomedical Engineering, Carnegie Mellon University
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18
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Raffin E, Harquel S, Passera B, Chauvin A, Bougerol T, David O. Probing regional cortical excitability via input-output properties using transcranial magnetic stimulation and electroencephalography coupling. Hum Brain Mapp 2020; 41:2741-2761. [PMID: 32379389 PMCID: PMC7294059 DOI: 10.1002/hbm.24975] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Revised: 02/04/2020] [Accepted: 02/23/2020] [Indexed: 01/28/2023] Open
Abstract
The modular organization of the cortex refers to subsets of highly interconnected nodes, sharing specific cytoarchitectural and dynamical properties. These properties condition the level of excitability of local pools of neurons. In this study, we described TMS evoked potentials (TEP) input-output properties to provide new insights into regional cortical excitability. We combined robotized TMS with EEG to disentangle region-specific TEP from threshold to saturation and describe their oscillatory contents. Twenty-two young healthy participants received robotized TMS pulses over the right primary motor cortex (M1), the right dorsolateral prefrontal cortex (DLPFC) and the right superior occipital lobe (SOL) at five stimulation intensities (40, 60, 80, 100, and 120% resting motor threshold) and one short-interval intracortical inhibition condition during EEG recordings. Ten additional subjects underwent the same experiment with a realistic sham TMS procedure. The results revealed interregional differences in the TEPs input-output functions as well as in the responses to paired-pulse conditioning protocols, when considering early local components (<80 ms). Each intensity in the three regions was associated with complex patterns of oscillatory activities. The quality of the regression of TEPs over stimulation intensity was used to derive a new readout for cortical excitability and dynamical properties, revealing lower excitability in the DLPFC, followed by SOL and M1. The realistic sham experiment confirmed that these early local components were not contaminated by multisensory stimulations. This study provides an entirely new analytic framework to characterize input-output relations throughout the cortex, paving the way to a more accurate definition of local cortical excitability.
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Affiliation(s)
- Estelle Raffin
- University of Grenoble Alpes, Inserm, U1216, Grenoble Institut NeurosciencesGrenobleFrance
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL)GenevaSwitzerland
- Defitech Chair of Clinical Neuroengineering, Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL Valais), Clinique Romande de RéadaptationSionSwitzerland
| | - Sylvain Harquel
- CNRS, UMR5105, Laboratoire Psychologie et NeuroCognition, LPNCUniversity of Grenoble AlpesGrenobleFrance
- University of Grenoble‐Alpes, CNRS, CHU Grenoble Alpes, INSERM, CNRS, IRMaGeGrenobleFrance
| | - Brice Passera
- University of Grenoble Alpes, Inserm, U1216, Grenoble Institut NeurosciencesGrenobleFrance
- CNRS, UMR5105, Laboratoire Psychologie et NeuroCognition, LPNCUniversity of Grenoble AlpesGrenobleFrance
| | - Alan Chauvin
- CNRS, UMR5105, Laboratoire Psychologie et NeuroCognition, LPNCUniversity of Grenoble AlpesGrenobleFrance
- University of Grenoble‐Alpes, CNRS, CHU Grenoble Alpes, INSERM, CNRS, IRMaGeGrenobleFrance
| | - Thierry Bougerol
- University of Grenoble Alpes, Inserm, U1216, Grenoble Institut NeurosciencesGrenobleFrance
- CNRS, UMR5105, Laboratoire Psychologie et NeuroCognition, LPNCUniversity of Grenoble AlpesGrenobleFrance
| | - Olivier David
- University of Grenoble Alpes, Inserm, U1216, Grenoble Institut NeurosciencesGrenobleFrance
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19
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Bergmann TO, Hartwigsen G. Inferring Causality from Noninvasive Brain Stimulation in Cognitive Neuroscience. J Cogn Neurosci 2020; 33:195-225. [PMID: 32530381 DOI: 10.1162/jocn_a_01591] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Noninvasive brain stimulation (NIBS) techniques, such as transcranial magnetic stimulation or transcranial direct and alternating current stimulation, are advocated as measures to enable causal inference in cognitive neuroscience experiments. Transcending the limitations of purely correlative neuroimaging measures and experimental sensory stimulation, they allow to experimentally manipulate brain activity and study its consequences for perception, cognition, and eventually, behavior. Although this is true in principle, particular caution is advised when interpreting brain stimulation experiments in a causal manner. Research hypotheses are often oversimplified, disregarding the underlying (implicitly assumed) complex chain of causation, namely, that the stimulation technique has to generate an electric field in the brain tissue, which then evokes or modulates neuronal activity both locally in the target region and in connected remote sites of the network, which in consequence affects the cognitive function of interest and eventually results in a change of the behavioral measure. Importantly, every link in this causal chain of effects can be confounded by several factors that have to be experimentally eliminated or controlled to attribute the observed results to their assumed cause. This is complicated by the fact that many of the mediating and confounding variables are not directly observable and dose-response relationships are often nonlinear. We will walk the reader through the chain of causation for a generic cognitive neuroscience NIBS study, discuss possible confounds, and advise appropriate control conditions. If crucial assumptions are explicitly tested (where possible) and confounds are experimentally well controlled, NIBS can indeed reveal cause-effect relationships in cognitive neuroscience studies.
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Affiliation(s)
| | - Gesa Hartwigsen
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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20
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Giroud J, Trébuchon A, Schön D, Marquis P, Liegeois-Chauvel C, Poeppel D, Morillon B. Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy. PLoS Biol 2020; 18:e3000207. [PMID: 32119667 PMCID: PMC7067489 DOI: 10.1371/journal.pbio.3000207] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 03/12/2020] [Accepted: 02/13/2020] [Indexed: 11/18/2022] Open
Abstract
Speech perception is mediated by both left and right auditory cortices but with differential sensitivity to specific acoustic information contained in the speech signal. A detailed description of this functional asymmetry is missing, and the underlying models are widely debated. We analyzed cortical responses from 96 epilepsy patients with electrode implantation in left or right primary, secondary, and/or association auditory cortex (AAC). We presented short acoustic transients to noninvasively estimate the dynamical properties of multiple functional regions along the auditory cortical hierarchy. We show remarkably similar bimodal spectral response profiles in left and right primary and secondary regions, with evoked activity composed of dynamics in the theta (around 4–8 Hz) and beta–gamma (around 15–40 Hz) ranges. Beyond these first cortical levels of auditory processing, a hemispheric asymmetry emerged, with delta and beta band (3/15 Hz) responsivity prevailing in the right hemisphere and theta and gamma band (6/40 Hz) activity prevailing in the left. This asymmetry is also present during syllables presentation, but the evoked responses in AAC are more heterogeneous, with the co-occurrence of alpha (around 10 Hz) and gamma (>25 Hz) activity bilaterally. These intracranial data provide a more fine-grained and nuanced characterization of cortical auditory processing in the 2 hemispheres, shedding light on the neural dynamics that potentially shape auditory and speech processing at different levels of the cortical hierarchy. Capitalizing on intracranial data from 96 epileptic patients, this study precisely estimates the processing timescales along the cortical auditory hierarchy and reveals that an asymmetric sampling emerges in associative areas.
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Affiliation(s)
- Jérémy Giroud
- Aix Marseille University, Inserm, INS, Inst Neurosci Syst, Marseille, France
| | - Agnès Trébuchon
- Aix Marseille University, Inserm, INS, Inst Neurosci Syst, Marseille, France
- APHM, Hôpital de la Timone, Service de Neurophysiologie Clinique, Marseille, France
| | - Daniele Schön
- Aix Marseille University, Inserm, INS, Inst Neurosci Syst, Marseille, France
| | - Patrick Marquis
- Aix Marseille University, Inserm, INS, Inst Neurosci Syst, Marseille, France
| | - Catherine Liegeois-Chauvel
- Aix Marseille University, Inserm, INS, Inst Neurosci Syst, Marseille, France
- Cleveland Clinic Neurological Institute, Epilepsy Center, Cleveland, Ohio, United States of America
| | - David Poeppel
- Department of Neuroscience, Max-Planck-Institute for Empirical Aesthetics, Frankfurt am Main, Germany
- Department of Psychology and Center for Neural Science, New York University, New York, New York, United States of America
| | - Benjamin Morillon
- Aix Marseille University, Inserm, INS, Inst Neurosci Syst, Marseille, France
- * E-mail:
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21
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Freedberg M, Reeves JA, Hussain SJ, Zaghloul KA, Wassermann EM. Identifying site- and stimulation-specific TMS-evoked EEG potentials using a quantitative cosine similarity metric. PLoS One 2020; 15:e0216185. [PMID: 31929531 PMCID: PMC6957143 DOI: 10.1371/journal.pone.0216185] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Accepted: 12/20/2019] [Indexed: 11/19/2022] Open
Abstract
The ability to interpret transcranial magnetic stimulation (TMS)-evoked electroencephalography (EEG) potentials (TEPs) is limited by artifacts, such as auditory evoked responses produced by discharge of the TMS coil. TEPs generated from direct cortical stimulation should vary in their topographical activity pattern according to stimulation site and differ from responses to sham stimulation. Responses that do not show these effects are likely to be artifactual. In 20 healthy volunteers, we delivered active and sham TMS to the right prefrontal, left primary motor, and left posterior parietal cortex and compared the waveform similarity of TEPs between stimulation sites and active and sham TMS using a cosine similarity-based analysis method. We identified epochs after the stimulus when the spatial pattern of TMS-evoked activation showed greater than random similarity between stimulation sites and sham vs. active TMS, indicating the presence of a dominant artifact. To do this, we binarized the derivatives of the TEPs recorded from 30 EEG channels and calculated cosine similarity between conditions at each time point with millisecond resolution. Only TEP components occurring before approximately 80 ms differed across stimulation sites and between active and sham, indicating site and condition-specific responses. We therefore conclude that, in the absence of noise masking or other measures to decrease neural artifact, TEP components before about 80 ms can be safely interpreted as stimulation location-specific responses to TMS, but components beyond this latency should be interpreted with caution due to high similarity in their topographical activity pattern.
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Affiliation(s)
- Michael Freedberg
- Behavioral Neurology Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States of America
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States of America
- * E-mail:
| | - Jack A. Reeves
- Behavioral Neurology Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States of America
| | - Sara J. Hussain
- Human Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States of America
| | - Kareem A. Zaghloul
- Functional and Restorative Neurosurgery Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States of America
| | - Eric M. Wassermann
- Behavioral Neurology Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States of America
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22
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Noda Y. Toward the establishment of neurophysiological indicators for neuropsychiatric disorders using transcranial magnetic stimulation-evoked potentials: A systematic review. Psychiatry Clin Neurosci 2020; 74:12-34. [PMID: 31587446 DOI: 10.1111/pcn.12936] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2019] [Revised: 08/14/2019] [Accepted: 09/23/2019] [Indexed: 12/24/2022]
Abstract
Transcranial magnetic stimulation (TMS) can depolarize the neurons directly under the coil when applied to the cerebral cortex, and modulate the neural circuit associated with the stimulation site, which makes it possible to measure the neurophysiological index to evaluate excitability and inhibitory functions. Concurrent TMS and electroencephalography (TMS-EEG) has been developed to assess the neurophysiological characteristics of cortical regions other than the motor cortical region noninvasively. The aim of this review is to comprehensively discuss TMS-EEG research in the healthy brain focused on excitability, inhibition, and plasticity following neuromodulatory TMS paradigms from a neurophysiological perspective. A search was conducted in PubMed to identify articles that examined humans and that were written in English and published by September 2018. The search terms were as follows: (TMS OR 'transcranial magnetic stimulation') AND (EEG OR electroencephalog*) NOT (rTMS OR 'repetitive transcranial magnetic stimulation' OR TBS OR 'theta burst stimulation') AND (healthy). The study presents an overview of TMS-EEG methodology and neurophysiological indices and reviews previous findings from TMS-EEG in healthy individuals. Furthermore, this review discusses the potential application of TMS-EEG neurophysiology in the clinical setting to study healthy and diseased brain conditions in the future. Combined TMS-EEG is a powerful tool to probe and map neural circuits in the human brain noninvasively and represents a promising approach for determining the underlying pathophysiology of neuropsychiatric disorders.
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Affiliation(s)
- Yoshihiro Noda
- Multidisciplinary Translational Research Lab, Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
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23
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Beynel L, Appelbaum LG, Luber B, Crowell CA, Hilbig SA, Lim W, Nguyen D, Chrapliwy NA, Davis SW, Cabeza R, Lisanby SH, Deng ZD. Effects of online repetitive transcranial magnetic stimulation (rTMS) on cognitive processing: A meta-analysis and recommendations for future studies. Neurosci Biobehav Rev 2019; 107:47-58. [PMID: 31473301 PMCID: PMC7654714 DOI: 10.1016/j.neubiorev.2019.08.018] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 06/28/2019] [Accepted: 08/22/2019] [Indexed: 01/03/2023]
Abstract
Online repetitive transcranial magnetic stimulation (rTMS), applied while subjects are performing a task, is widely used to disrupt brain regions underlying cognition. However, online rTMS has also induced "paradoxical enhancement". Given the rapid proliferation of this approach, it is crucial to develop a better understanding of how online stimulation influences cognition, and the optimal parameters to achieve desired effects. To accomplish this goal, a quantitative meta-analysis was performed with random-effects models fitted to reaction time (RT) and accuracy data. The final dataset included 126 studies published between 1998 and 2016, with 244 total effects for reaction times, and 202 for accuracy. Meta-analytically, rTMS at 10 Hz and 20 Hz disrupted accuracy for attention, executive, language, memory, motor, and perception domains, while no effects were found with 1 Hz or 5 Hz. Stimulation applied at and 10 and 20 Hz slowed down RTs in attention and perception tasks. No performance enhancement was found. Meta-regression analysis showed that fMRI-guided targeting and short inter-trial intervals are associated with increased disruptive effects with rTMS.
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Affiliation(s)
- Lysianne Beynel
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Lawrence G Appelbaum
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Bruce Luber
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Courtney A Crowell
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Susan A Hilbig
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Wesley Lim
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Duy Nguyen
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Nicolas A Chrapliwy
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Simon W Davis
- Department of Neurology, Duke University School of Medicine, Durham, NC, United States
| | - Roberto Cabeza
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
| | - Sarah H Lisanby
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States; Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Zhi-De Deng
- Departments of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, United States; Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
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24
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Rossini P, Di Iorio R, Bentivoglio M, Bertini G, Ferreri F, Gerloff C, Ilmoniemi R, Miraglia F, Nitsche M, Pestilli F, Rosanova M, Shirota Y, Tesoriero C, Ugawa Y, Vecchio F, Ziemann U, Hallett M. Methods for analysis of brain connectivity: An IFCN-sponsored review. Clin Neurophysiol 2019; 130:1833-1858. [DOI: 10.1016/j.clinph.2019.06.006] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 05/08/2019] [Accepted: 06/18/2019] [Indexed: 01/05/2023]
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25
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Reproducibility in TMS–EEG studies: A call for data sharing, standard procedures and effective experimental control. Brain Stimul 2019; 12:787-790. [DOI: 10.1016/j.brs.2019.01.010] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 01/14/2019] [Accepted: 01/17/2019] [Indexed: 11/21/2022] Open
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26
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Tremblay S, Rogasch NC, Premoli I, Blumberger DM, Casarotto S, Chen R, Di Lazzaro V, Farzan F, Ferrarelli F, Fitzgerald PB, Hui J, Ilmoniemi RJ, Kimiskidis VK, Kugiumtzis D, Lioumis P, Pascual-Leone A, Pellicciari MC, Rajji T, Thut G, Zomorrodi R, Ziemann U, Daskalakis ZJ. Clinical utility and prospective of TMS–EEG. Clin Neurophysiol 2019; 130:802-844. [DOI: 10.1016/j.clinph.2019.01.001] [Citation(s) in RCA: 117] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 01/07/2019] [Accepted: 01/08/2019] [Indexed: 12/15/2022]
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27
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A quantitative physical model of the TMS-induced discharge artifacts in EEG. PLoS Comput Biol 2018; 14:e1006177. [PMID: 30016315 PMCID: PMC6063435 DOI: 10.1371/journal.pcbi.1006177] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 07/27/2018] [Accepted: 05/04/2018] [Indexed: 11/22/2022] Open
Abstract
The combination of Transcranial Magnetic Stimulation (TMS) with Electroencephalography (EEG) exposes the brain’s global response to localized and abrupt stimulations. However, large electric artifacts are induced in the EEG by the TMS, obscuring crucial stages of the brain’s response. Artifact removal is commonly performed by data processing techniques. However, an experimentally verified physical model for the origin and structure of the TMS-induced discharge artifacts, by which these methods can be justified or evaluated, is still lacking. We re-examine the known contribution of the skin in creating the artifacts, and outline a detailed model for the relaxation of the charge accumulated at the electrode-gel-skin interface due to the TMS pulse. We then experimentally validate implications set forth by the model. We find that the artifacts decay like a power law in time rather than the commonly assumed exponential. In fact, the skin creates a power-law decay of order 1 at each electrode, which is turned into a power law of order 2 by the reference electrode. We suggest an artifact removal method based on the model which can be applied from times after the pulse as short as 2 milliseconds onwards to expose the full EEG from the brain. The method can separate the capacitive discharge artifacts from those resulting from cranial muscle activation, demonstrating that the capacitive effect dominates at short times. Overall, our insight into the physical process allows us to accurately access TMS-evoked EEG responses that directly follow the TMS pulse, possibly opening new opportunities in TMS-EEG research. The combined use of transcranial magnetic stimulation (TMS) with electroencephalography (EEG) is rapidly becoming a useful diagnostic and research tool for measuring the brain’s global response to localized and abrupt stimulations. However, large electric artifacts that are induced in the EEG by the TMS must be removed from the EEG signal, since they are unrelated to brain activity and obscure crucial stages of the brain’s response. Here we show that a simple physical model of skin impedance explains the observed artifact decay, and enables the efficient removal of the artifact signal in an automatable manner. We thus discern the EEG response precisely from about 2 milliseconds after the TMS pulse, showing that the artifact is dominated by capacitive rather than muscular effects.
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28
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Wu W, Keller CJ, Rogasch NC, Longwell P, Shpigel E, Rolle CE, Etkin A. ARTIST: A fully automated artifact rejection algorithm for single-pulse TMS-EEG data. Hum Brain Mapp 2018; 39:1607-1625. [PMID: 29331054 DOI: 10.1002/hbm.23938] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Revised: 10/29/2017] [Accepted: 12/14/2017] [Indexed: 11/08/2022] Open
Abstract
Concurrent single-pulse TMS-EEG (spTMS-EEG) is an emerging noninvasive tool for probing causal brain dynamics in humans. However, in addition to the common artifacts in standard EEG data, spTMS-EEG data suffer from enormous stimulation-induced artifacts, posing significant challenges to the extraction of neural information. Typically, neural signals are analyzed after a manual time-intensive and often subjective process of artifact rejection. Here we describe a fully automated algorithm for spTMS-EEG artifact rejection. A key step of this algorithm is to decompose the spTMS-EEG data into statistically independent components (ICs), and then train a pattern classifier to automatically identify artifact components based on knowledge of the spatio-temporal profile of both neural and artefactual activities. The autocleaned and hand-cleaned data yield qualitatively similar group evoked potential waveforms. The algorithm achieves a 95% IC classification accuracy referenced to expert artifact rejection performance, and does so across a large number of spTMS-EEG data sets (n = 90 stimulation sites), retains high accuracy across stimulation sites/subjects/populations/montages, and outperforms current automated algorithms. Moreover, the algorithm was superior to the artifact rejection performance of relatively novice individuals, who would be the likely users of spTMS-EEG as the technique becomes more broadly disseminated. In summary, our algorithm provides an automated, fast, objective, and accurate method for cleaning spTMS-EEG data, which can increase the utility of TMS-EEG in both clinical and basic neuroscience settings.
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Affiliation(s)
- Wei Wu
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, 94305.,Stanford Neuroscience Institute, Stanford University, Stanford, California, 94305.,Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304.,School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, 510640, China
| | - Corey J Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, 94305.,Stanford Neuroscience Institute, Stanford University, Stanford, California, 94305.,Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304
| | - Nigel C Rogasch
- Brain and Mental Health Laboratory, School of Psychological Sciences and Monash Biomedical Imaging, Monash Institute of Cognitive and Clinical Neuroscience, Monash University, Victoria, Australia
| | - Parker Longwell
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, 94305.,Stanford Neuroscience Institute, Stanford University, Stanford, California, 94305.,Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304
| | - Emmanuel Shpigel
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, 94305.,Stanford Neuroscience Institute, Stanford University, Stanford, California, 94305.,Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304
| | - Camarin E Rolle
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, 94305.,Stanford Neuroscience Institute, Stanford University, Stanford, California, 94305.,Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, 94305.,Stanford Neuroscience Institute, Stanford University, Stanford, California, 94305.,Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304
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29
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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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30
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Fecchio M, Pigorini A, Comanducci A, Sarasso S, Casarotto S, Premoli I, Derchi CC, Mazza A, Russo S, Resta F, Ferrarelli F, Mariotti M, Ziemann U, Massimini M, Rosanova M. The spectral features of EEG responses to transcranial magnetic stimulation of the primary motor cortex depend on the amplitude of the motor evoked potentials. PLoS One 2017; 12:e0184910. [PMID: 28910407 PMCID: PMC5599017 DOI: 10.1371/journal.pone.0184910] [Citation(s) in RCA: 79] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 09/01/2017] [Indexed: 01/05/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) of the primary motor cortex (M1) can excite both cortico-cortical and cortico-spinal axons resulting in TMS-evoked potentials (TEPs) and motor-evoked potentials (MEPs), respectively. Despite this remarkable difference with other cortical areas, the influence of motor output and its amplitude on TEPs is largely unknown. Here we studied TEPs resulting from M1 stimulation and assessed whether their waveform and spectral features depend on the MEP amplitude. To this aim, we performed two separate experiments. In experiment 1, single-pulse TMS was applied at the same supra-threshold intensity on primary motor, prefrontal, premotor and parietal cortices and the corresponding TEPs were compared by means of local mean field power and time-frequency spectral analysis. In experiment 2 we stimulated M1 at resting motor threshold in order to elicit MEPs characterized by a wide range of amplitudes. TEPs computed from high-MEP and low-MEP trials were then compared using the same methods applied in experiment 1. In line with previous studies, TMS of M1 produced larger TEPs compared to other cortical stimulations. Notably, we found that only TEPs produced by M1 stimulation were accompanied by a late event-related desynchronization (ERD-peaking at ~300 ms after TMS), whose magnitude was strongly dependent on the amplitude of MEPs. Overall, these results suggest that M1 produces peculiar responses to TMS possibly reflecting specific anatomo-functional properties, such as the re-entry of proprioceptive feedback associated with target muscle activation.
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Affiliation(s)
- Matteo Fecchio
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Andrea Pigorini
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Angela Comanducci
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Isabella Premoli
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, United Kingdom
- Department of Neurology & Stroke, and Hertie Institute for Clinical Brain Research, University Tübingen, Tübingen, Germany
| | - Chiara-Camilla Derchi
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Alice Mazza
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Simone Russo
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Federico Resta
- Division of Radiology, Hospital Luigi Sacco, Milan, Italy
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, United States of America
| | - Maurizio Mariotti
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
| | - Ulf Ziemann
- Department of Neurology & Stroke, and Hertie Institute for Clinical Brain Research, University Tübingen, Tübingen, Germany
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
- IRCCS Fondazione Don Gnocchi Onlus, Milan, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences “L. Sacco”, University of Milan, Milan, Italy
- Fondazione Europea per la Ricerca Biomedica Onlus, Milan, Italy
- * E-mail:
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31
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Ragazzoni A, Cincotta M, Giovannelli F, Cruse D, Young GB, Miniussi C, Rossi S. Clinical neurophysiology of prolonged disorders of consciousness: From diagnostic stimulation to therapeutic neuromodulation. Clin Neurophysiol 2017; 128:1629-1646. [DOI: 10.1016/j.clinph.2017.06.037] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2017] [Revised: 05/17/2017] [Accepted: 06/15/2017] [Indexed: 10/19/2022]
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32
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Automatized set-up procedure for transcranial magnetic stimulation protocols. Neuroimage 2017; 153:307-318. [DOI: 10.1016/j.neuroimage.2017.04.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Revised: 02/03/2017] [Accepted: 04/01/2017] [Indexed: 12/15/2022] Open
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