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Chowdhury NS, Chang WJ, Cavaleri R, Chiang AKI, Schabrun SM. The reliability and validity of rapid transcranial magnetic stimulation mapping for muscles under active contraction. BMC Neurosci 2024; 25:43. [PMID: 39215217 PMCID: PMC11363547 DOI: 10.1186/s12868-024-00885-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 07/26/2024] [Indexed: 09/04/2024] Open
Abstract
Rapid mapping is a transcranial magnetic stimulation (TMS) mapping method which can significantly reduce data collection time compared to traditional approaches. However, its validity and reliability has only been established for upper-limb muscles during resting-state activity. Here, we determined the validity and reliability of rapid mapping for non-upper limb muscles that require active contraction during TMS: the masseter and quadriceps muscles. Eleven healthy participants attended two sessions, spaced two hours apart, each involving rapid and 'traditional' mapping of the masseter muscle and three quadriceps muscles (rectus femoris, vastus medialis, vastus lateralis). Map parameters included map volume, map area and centre of gravity (CoG) in the medial-lateral and anterior-posterior directions. Low to moderate measurement errors (%SEMeas = 10-32) were observed across muscles. Relative reliability varied from good-to-excellent (ICC = 0.63-0.99) for map volume, poor-to-excellent (ICC = 0.11-0.86) for map area, and fair-to-excellent for CoG (ICC = 0.25-0.8) across muscles. There was Bayesian evidence of equivalence (BF's > 3) in most map outcomes between rapid and traditional maps across all muscles, supporting the validity of the rapid mapping method. Overall, rapid TMS mapping produced similar estimates of map parameters to the traditional method, however the reliability results were mixed. As mapping of non-upper limb muscles is relatively challenging, rapid mapping is a promising substitute for traditional mapping, however further work is required to refine this method.
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Affiliation(s)
- Nahian S Chowdhury
- Center for Pain IMPACT, Neuroscience Research Australia, 139 Barker Street, Randwick, Sydney, NSW, 2031, Australia.
- University of New South Wales, Sydney, NSW, Australia.
| | - Wei-Ju Chang
- Center for Pain IMPACT, Neuroscience Research Australia, 139 Barker Street, Randwick, Sydney, NSW, 2031, Australia.
- School of Health Sciences, College of Health, Medicine and Wellbeing, The University of Newcastle, Callaghan, NSW, Australia.
| | - Rocco Cavaleri
- Brain Stimulation and Rehabilitation (BrainStAR) Lab, School of Health Sciences, Western Sydney University, Sydney, NSW, Australia
| | - Alan K I Chiang
- Center for Pain IMPACT, Neuroscience Research Australia, 139 Barker Street, Randwick, Sydney, NSW, 2031, Australia
- University of New South Wales, Sydney, NSW, Australia
| | - Siobhan M Schabrun
- Center for Pain IMPACT, Neuroscience Research Australia, 139 Barker Street, Randwick, Sydney, NSW, 2031, Australia
- The Gray Centre for Mobility and Activity, Parkwood Institute, London, Canada
- School of Physical Therapy, University of Western Ontario, London, Canada
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Hamel R, Waltzing BM, Massey T, Blenkinsop J, McConnell L, Osborne K, Sesay K, Stoneman F, Carter A, Maaroufi H, Jenkinson N. Sub-concussive head impacts from heading footballs do not acutely alter brain excitability as compared to a control group. PLoS One 2024; 19:e0306560. [PMID: 39088385 PMCID: PMC11293750 DOI: 10.1371/journal.pone.0306560] [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] [Received: 08/21/2023] [Accepted: 06/18/2024] [Indexed: 08/03/2024] Open
Abstract
BACKGROUND Repeated sub-concussive head impacts are a growing brain health concern, but their possible biomarkers remain elusive. One impediment is the lack of a randomised controlled human experimental model to study their effects on the human brain. OBJECTIVES This work had two objectives. The first one was to provide a randomised controlled human experimental model to study the acute effects of head impacts on brain functions. To achieve this, this work's second objective was to investigate if head impacts from heading footballs acutely alter brain excitability by increasing corticospinal inhibition as compared to a control group. METHODS In practised and unpractised young healthy adults, transcranial magnetic stimulation was used to assess corticospinal silent period (CSP) duration and corticospinal excitability (CSE) before and immediately after performing headings by returning 20 hand-thrown balls directed to the head (Headings; n = 30) or the dominant foot (Control; n = 30). Moreover, the Rivermead Post-Concussion Questionnaire (RPQ) was used to assess the symptoms of head impacts. Head acceleration was also assessed in subgroups of participants. RESULTS The intervention lengthened CSP duration in both the Headings (6.4 ± 7.5%) and Control groups (4.6 ± 2.6%), with no difference in lengthening between the two groups. Moreover, CSE was not altered by the intervention and did not differ between groups. However, performing headings increased headaches and dizziness symptoms and resulted in greater head acceleration upon each football throw (12.5 ± 1.9g) as compared to the control intervention (5.5 ± 1.3g). CONCLUSIONS The results suggest that head impacts from football headings do not acutely alter brain excitability as compared to a control intervention. However, the results also suggest that the present protocol can be used as an experimental model to investigate the acute effects of head impacts on the human brain.
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Affiliation(s)
- Raphael Hamel
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | | | - Tom Massey
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - James Blenkinsop
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Leah McConnell
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Kieran Osborne
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Karamo Sesay
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Finn Stoneman
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Adam Carter
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Hajar Maaroufi
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Ned Jenkinson
- School of Sports, Exercise, and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
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Agboada D, Osnabruegge M, Rethwilm R, Kanig C, Schwitzgebel F, Mack W, Schecklmann M, Seiberl W, Schoisswohl S. Semi-automated motor hotspot search (SAMHS): a framework toward an optimised approach for motor hotspot identification. Front Hum Neurosci 2023; 17:1228859. [PMID: 38164193 PMCID: PMC10757939 DOI: 10.3389/fnhum.2023.1228859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 11/23/2023] [Indexed: 01/03/2024] Open
Abstract
Background Motor hotspot identification represents the first step in the determination of the motor threshold and is the basis for the specification of stimulation intensity used for various Transcranial Magnetic Stimulation (TMS) applications. The level of experimenters' experience and the methodology of motor hotspot identification differ between laboratories. The need for an optimized and time-efficient technique for motor hotspot identification is therefore substantial. Objective With the current work, we present a framework for an optimized and time-efficient semi-automated motor hotspot search (SAMHS) technique utilizing a neuronavigated robot-assisted TMS system (TMS-cobot). Furthermore, we aim to test its practicality and accuracy by a comparison with a manual motor hotspot identification method. Method A total of 32 participants took part in this dual-center study. At both study centers, participants underwent manual hotspot search (MHS) with an experienced TMS researcher, and the novel SAMHS procedure with a TMS-cobot (hereafter, called cobot hotspot search, CHS) in a randomized order. Resting motor threshold (RMT), and stimulus intensity to produce 1 mV (SI1mV) peak-to-peak of motor-evoked potential (MEP), as well as MEPs with 120% RMT and SI1mV were recorded as outcome measures for comparison. Results Compared to the MHS method, the CHS produced lower RMT, lower SI1mV and a trend-wise higher peak-to-peak MEP amplitude in stimulations with SI1mV. The duration of the CHS procedure was longer than that of the MHS (15.60 vs. 2.43 min on average). However, accuracy of the hotspot was higher for the CHS compared to the MHS. Conclusions The SAMHS procedure introduces an optimized motor hotspot determination system that is easy to use, and strikes a fairly good balance between accuracy and speed. This new procedure can thus be deplored by experienced as well as beginner-level TMS researchers.
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Affiliation(s)
- Desmond Agboada
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Mirja Osnabruegge
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Roman Rethwilm
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Carolina Kanig
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Florian Schwitzgebel
- Department of Electrical Engineering, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Wolfgang Mack
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Martin Schecklmann
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - Wolfgang Seiberl
- Institute of Sport Science, University of the Bundeswehr Munich, Neubiberg, Germany
| | - Stefan Schoisswohl
- Institute of Psychology, University of the Bundeswehr Munich, Neubiberg, Germany
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
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4
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Chen Y, Jiang Y, Zhang Z, Li Z, Zhu C. Transcranial magnetic stimulation mapping of the motor cortex: comparison of five estimation algorithms. Front Neurosci 2023; 17:1301075. [PMID: 38130697 PMCID: PMC10733534 DOI: 10.3389/fnins.2023.1301075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 11/21/2023] [Indexed: 12/23/2023] Open
Abstract
Background There are currently five different kinds of transcranial magnetic stimulation (TMS) motor mapping algorithms available, from ordinary point-based algorithms to advanced field-based algorithms. However, there have been only a limited number of comparison studies conducted, and they have not yet examined all of the currently available algorithms. This deficiency impedes the judicious selection of algorithms for application in both clinical and basic neuroscience, and hinders the potential promotion of a potential superior algorithm. Considering the influence of algorithm complexity, further investigation is needed to examine the differences between fMRI peaks and TMS cortical hotspots that were identified previously. Methods Twelve healthy participants underwent TMS motor mapping and a finger-tapping task during fMRI. The motor cortex TMS mapping results were estimated by five algorithms, and fMRI activation results were obtained. For each algorithm, the prediction error was defined as the distance between the measured scalp hotspot and optimized coil position, which was determined by the maximum electric field strength in the estimated motor cortex. Additionally, the study identified the minimum number of stimuli required for stable mapping. Finally, the location difference between the TMS mapping cortical hotspot and the fMRI activation peak was analyzed. Results The projection yielded the lowest prediction error (5.27 ± 4.24 mm) among the point-based algorithms and the association algorithm yielded the lowest (6.66 ± 3.48 mm) among field-based estimation algorithms. The projection algorithm required fewer stimuli, possibly resulting from its suitability for the grid-based mapping data collection method. The TMS cortical hotspots from all algorithms consistently deviated from the fMRI activation peak (20.52 ± 8.46 mm for five algorithms). Conclusion The association algorithm might be a superior choice for clinical applications and basic neuroscience research, due to its lower prediction error and higher estimation sensitivity in the deep cortical structure, especially for the sulcus. It also has potential applicability in various other TMS domains, including language area mapping and more. Otherwise, our results provide further evidence that TMS motor mapping intrinsically differs from fMRI motor mapping.
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Affiliation(s)
- Yuanyuan Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yihan Jiang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Center for the Cognitive Science of Language, Beijing Language and Culture University, Beijing, China
| | - Zong Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zheng Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University Zhuhai, Zhuhai, China
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
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5
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Matsuda RH, Souza VH, Kirsten PN, Ilmoniemi RJ, Baffa O. MarLe: Markerless estimation of head pose for navigated transcranial magnetic stimulation. Phys Eng Sci Med 2023; 46:887-896. [PMID: 37166586 DOI: 10.1007/s13246-023-01263-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 04/16/2023] [Indexed: 05/12/2023]
Abstract
Navigated transcranial magnetic stimulation (nTMS) is a valuable tool for non-invasive brain stimulation. Currently, nTMS requires fixing of markers on the patient's head. Head marker displacements lead to changes in coil placement and brain stimulation inaccuracy. A markerless neuronavigation method is needed to increase the reliability of nTMS and simplify the nTMS protocol. In this study, we introduce and release MarLe, a Python markerless head tracker neuronavigation software for TMS. This novel software uses computer-vision techniques combined with low-cost cameras to estimate the head pose for neuronavigation. A coregistration algorithm, based on a closed-form solution, was designed to track the patient's head and the TMS coil referenced to the individual's brain image. We show that MarLe can estimate head pose based on real-time video processing. An intuitive pipeline was developed to connect the MarLe and nTMS neuronavigation software. MarLe achieved acceptable accuracy and stability in a mockup nTMS experiment. MarLe allows real-time tracking of the patient's head without any markers. The combination of face detection and a coregistration algorithm can overcome nTMS head marker displacement concerns. MarLe can improve reliability, simplify, and reduce the protocol time of brain intervention techniques such as nTMS.
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Affiliation(s)
- Renan H Matsuda
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, Ribeirão Preto, 3900, 14040-901, SP, Brazil.
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, Espoo, 02150, Finland.
| | - Victor H Souza
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, Ribeirão Preto, 3900, 14040-901, SP, Brazil
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, Espoo, 02150, Finland
- School of Physiotherapy, Federal University of Juiz de Fora, Juiz de Fora - MG, Cascatinha, Brazil
| | - Petrus N Kirsten
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, Ribeirão Preto, 3900, 14040-901, SP, Brazil
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2, Espoo, 02150, Finland
| | - Oswaldo Baffa
- Department of Physics, Faculty of Philosophy Sciences and Letters of Ribeirão Preto, University of São Paulo, Av. Bandeirantes, Ribeirão Preto, 3900, 14040-901, SP, Brazil
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6
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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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Hikita K, Gomez-Tames J, Hirata A. Mapping Brain Motor Functions Using Transcranial Magnetic Stimulation with a Volume Conductor Model and Electrophysiological Experiments. Brain Sci 2023; 13:brainsci13010116. [PMID: 36672097 PMCID: PMC9856731 DOI: 10.3390/brainsci13010116] [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: 12/03/2022] [Revised: 12/26/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) activates brain cells in a noninvasive manner and can be used for mapping brain motor functions. However, the complexity of the brain anatomy prevents the determination of the exact location of the stimulated sites, resulting in the limitation of the spatial resolution of multiple targets. The aim of this study is to map two neighboring muscles in cortical motor areas accurately and quickly. Multiple stimuli were applied to the subject using a TMS stimulator to measure the motor-evoked potentials (MEPs) in the corresponding muscles. For each stimulation condition (coil location and angle), the induced electric field (EF) in the brain was computed using a volume conductor model for an individualized head model of the subject constructed from magnetic resonance images. A post-processing method was implemented to determine a TMS hotspot using EF corresponding to multiple stimuli, considering the amplitude of the measured MEPs. The dependence of the computationally estimated hotspot distribution on two target muscles was evaluated (n = 11). The center of gravity of the first dorsal interosseous cortical representation was lateral to the abductor digiti minimi by a minimum of 2 mm. The localizations were consistent with the putative sites obtained from previous EF-based studies and fMRI studies. The simultaneous cortical mapping of two finger muscles was achieved with only several stimuli, which is one or two orders of magnitude smaller than that in previous studies. Our proposal would be useful in the preoperative mapping of motor or speech areas to plan brain surgery interventions.
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Affiliation(s)
- Keigo Hikita
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Aichi, Japan
| | - Jose Gomez-Tames
- Center for Frontier Medical Engineering, Chiba University, Chiba 263-8522, Chiba, Japan
| | - Akimasa Hirata
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Aichi, Japan
- Correspondence:
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8
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Nieminen AE, Nieminen JO, Stenroos M, Novikov P, Nazarova M, Vaalto S, Nikulin V, Ilmoniemi RJ. Accuracy and precision of navigated transcranial magnetic stimulation. J Neural Eng 2022; 19. [PMID: 36541458 DOI: 10.1088/1741-2552/aca71a] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/29/2022] [Indexed: 12/02/2022]
Abstract
Objective.Transcranial magnetic stimulation (TMS) induces an electric field (E-field) in the cortex. To facilitate stimulation targeting, image-guided neuronavigation systems have been introduced. Such systems track the placement of the coil with respect to the head and visualize the estimated cortical stimulation location on an anatomical brain image in real time. The accuracy and precision of the neuronavigation is affected by multiple factors. Our aim was to analyze how different factors in TMS neuronavigation affect the accuracy and precision of the coil-head coregistration and the estimated E-field.Approach.By performing simulations, we estimated navigation errors due to distortions in magnetic resonance images (MRIs), head-to-MRI registration (landmark- and surface-based registrations), localization and movement of the head tracker, and localization of the coil tracker. We analyzed the effect of these errors on coil and head coregistration and on the induced E-field as determined with simplistic and realistic head models.Main results.Average total coregistration accuracies were in the range of 2.2-3.6 mm and 1°; precision values were about half of the accuracy values. The coregistration errors were mainly due to head-to-MRI registration with average accuracies 1.5-1.9 mm/0.2-0.4° and precisions 0.5-0.8 mm/0.1-0.2° better with surface-based registration. The other major source of error was the movement of the head tracker with average accuracy of 1.5 mm and precision of 1.1 mm. When assessed within an E-field method, the average accuracies of the peak E-field location, orientation, and magnitude ranged between 1.5 and 5.0 mm, 0.9 and 4.8°, and 4.4 and 8.5% across the E-field models studied. The largest errors were obtained with the landmark-based registration. When computing another accuracy measure with the most realistic E-field model as a reference, the accuracies tended to improve from about 10 mm/15°/25% to about 2 mm/2°/5% when increasing realism of the E-field model.Significance.The results of this comprehensive analysis help TMS operators to recognize the main sources of error in TMS navigation and that the coregistration errors and their effect in the E-field estimation depend on the methods applied. To ensure reliable TMS navigation, we recommend surface-based head-to-MRI registration and realistic models for E-field computations.
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Affiliation(s)
- Aino E Nieminen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,AMI Centre, Aalto NeuroImaging, Aalto University School of Science, Espoo, Finland
| | - Jaakko O Nieminen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Pavel Novikov
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
| | - Maria Nazarova
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States of America
| | - Selja Vaalto
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.,HUS Diagnostic Center, Clinical Neurophysiology, Clinical Neurosciences, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Vadim Nikulin
- Centre for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia.,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
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9
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Yuasa A, Uehara S, Sawada Y, Otaka Y. Systematic determination of muscle groups and optimal stimulation intensity for simultaneous TMS mapping of multiple muscles in the upper limb. Physiol Rep 2022; 10:e15527. [PMID: 36461646 PMCID: PMC9718942 DOI: 10.14814/phy2.15527] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 10/31/2022] [Accepted: 11/14/2022] [Indexed: 05/01/2023] Open
Abstract
Transcranial magnetic stimulation has been used to assess plastic changes in the cortical motor representations of targeted muscles. The present study explored the optimal settings and stimulation intensity for simultaneous motor mapping of multiple upper-limb muscles across segments. In 15 healthy volunteers, we evaluated cortical representations simultaneously from one muscle in the shoulder, two in the upper arm, two in the forearm, and two intrinsic hand muscles, using five stimulation intensities, ranging from 40% to 100% of the maximum stimulator output. We represented the motor map area acquired at each intensity as a percentage of the maximum for each muscle. We defined a motor map area between 25% and 75% of the maximum as the optimal area size with sufficient scope for both up- and down-regulation, and stimulation intensities producing the map area size within this range as the optimal intensities. We found that motor maps with optimal area sizes could be produced simultaneously for the four distal muscles of the forearm and hand in most participants when the stimulation intensity was set at 120-140% of the resting motor threshold (RMT) of the first dorsal interosseous. For the remaining three proximal muscles, motor maps with optimal area sizes were produced only in a few participants, even when using a higher intensity (180-220% RMT). These findings suggest that cortical representations can be assessed simultaneously in a group of distal muscles using a relatively low stimulation intensity, while a separate operation is required to assess that of the proximal muscles.
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Affiliation(s)
- Akiko Yuasa
- Department of Rehabilitation Medicine IFujita Health University School of MedicineToyoakeAichiJapan
| | - Shintaro Uehara
- Faculty of RehabilitationFujita Health University School of Health SciencesToyoakeAichiJapan
| | - Yusuke Sawada
- Fujita Health University Nanakuri Memorial HospitalTsuMieJapan
| | - Yohei Otaka
- Department of Rehabilitation Medicine IFujita Health University School of MedicineToyoakeAichiJapan
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10
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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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11
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Jin F, Bruijn SM, Daffertshofer A. Accounting for Stimulations That Do Not Elicit Motor-Evoked Potentials When Mapping Cortical Representations of Multiple Muscles. Front Hum Neurosci 2022; 16:920538. [PMID: 35814946 PMCID: PMC9263445 DOI: 10.3389/fnhum.2022.920538] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 05/31/2022] [Indexed: 11/13/2022] Open
Abstract
The representation of muscles in the cortex can be mapped using navigated transcranial magnetic stimulation. The commonly employed measure to quantify the mapping are the center of gravity or the centroid of the region of excitability as well as its size. Determining these measures typically relies only on stimulation points that yield motor-evoked potentials (MEPs); stimulations that do not elicit an MEP, i.e., non-MEP points, are ignored entirely. In this study, we show how incorporating non-MEP points may affect the estimates of the size and centroid of the excitable area in eight hand and forearm muscles after mono-phasic single-pulse TMS. We performed test-retest assessments in twenty participants and estimated the reliability of centroids and sizes of the corresponding areas using inter-class correlation coefficients. For most muscles, the reliability turned out good. As expected, removing the non-MEP points significantly decreased area sizes and area weights, suggesting that conventional approaches that do not account for non-MEP points are likely to overestimate the regions of excitability.
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Affiliation(s)
- Fang Jin
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Faculty of Behavioural and Movement Sciences, Institute Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Sjoerd M. Bruijn
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Faculty of Behavioural and Movement Sciences, Institute Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Andreas Daffertshofer
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Faculty of Behavioural and Movement Sciences, Institute Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- *Correspondence: Andreas Daffertshofer,
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12
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Forearm and Hand Muscles Exhibit High Coactivation and Overlapping of Cortical Motor Representations. Brain Topogr 2022; 35:322-336. [PMID: 35262840 PMCID: PMC9098558 DOI: 10.1007/s10548-022-00893-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 02/04/2022] [Indexed: 11/09/2022]
Abstract
Most of the motor mapping procedures using navigated transcranial magnetic stimulation (nTMS) follow the conventional somatotopic organization of the primary motor cortex (M1) by assessing the representation of a particular target muscle, disregarding the possible coactivation of synergistic muscles. In turn, multiple reports describe a functional organization of the M1 with an overlapping among motor representations acting together to execute movements. In this context, the overlap degree among cortical representations of synergistic hand and forearm muscles remains an open question. This study aimed to evaluate the muscle coactivation and representation overlapping common to the grasping movement and its dependence on the stimulation parameters. The nTMS motor maps were obtained from one carpal muscle and two intrinsic hand muscles during rest. We quantified the overlapping motor maps in size (area and volume overlap degree) and topography (similarity and centroid Euclidean distance) parameters. We demonstrated that these muscle representations are highly overlapped and similar in shape. The overlap degrees involving the forearm muscle were significantly higher than only among the intrinsic hand muscles. Moreover, the stimulation intensity had a stronger effect on the size compared to the topography parameters. Our study contributes to a more detailed cortical motor representation towards a synergistic, functional arrangement of M1. Understanding the muscle group coactivation may provide more accurate motor maps when delineating the eloquent brain tissue during pre-surgical planning.
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13
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Nazarova M, Asmolova A. Towards more reliable TMS studies - How fast can we probe cortical excitability? Clin Neurophysiol Pract 2021; 7:21-22. [PMID: 35036660 PMCID: PMC8752992 DOI: 10.1016/j.cnp.2021.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 11/23/2021] [Indexed: 11/30/2022] Open
Affiliation(s)
- Maria Nazarova
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, 101000, Krivokolenny per. 3 Entrance 2, Moscow, Russian Federation
- Federal State Budgetary Institution Federal Center for Brain Research and Neurotechnologies of the Federal Medical Biological Agency, 117513 Ostrovityanova Street 1/10, Russian Federation
| | - Anastasia Asmolova
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, 101000, Krivokolenny per. 3 Entrance 2, Moscow, Russian Federation
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14
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Xu S, Yang Q, Chen M, Deng P, Zhuang R, Sun Z, Li C, Yan Z, Zhang Y, Jia J. Capturing Neuroplastic Changes after iTBS in Patients with Post-Stroke Aphasia: A Pilot fMRI Study. Brain Sci 2021; 11:1451. [PMID: 34827450 PMCID: PMC8615629 DOI: 10.3390/brainsci11111451] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 10/25/2021] [Accepted: 10/27/2021] [Indexed: 11/16/2022] Open
Abstract
Intermittent theta-burst stimulation (iTBS) is a high-efficiency transcranial magnetic stimulation (TMS) paradigm that has been applied to post-stroke aphasia (PSA). However, its efficacy mechanisms have not been clarified. This study aimed to explore the immediate effects of iTBS of the primary motor cortex (M1) of the affected hemisphere, on the functional activities and connectivity of the brains of PSA patients. A total of 16 patients with aphasia after stroke received iTBS with 800 pulses for 300 s. All patients underwent motor, language, and cognitive assessments and resting-state functional MRI scans immediately before and after the iTBS intervention. Regional, seed-based connectivity, and graph-based measures were used to test the immediate functional effects of the iTBS intervention, including the fractional amplitude of low-frequency fluctuation (fALFF), degree centrality (DC), and functional connectivity (FC) of the left M1 area throughout the whole brain. The results showed that after one session of iTBS intervention, the fALFF, DC, and FC values changed significantly in the patients' brains. Specifically, the DC values were significantly higher in the right middle frontal gyrus and parts of the left parietal lobe (p < 0.05), while fALFF values were significantly lower in the right medial frontal lobe and parts of the left intracalcarine cortex (p < 0.05), and the strength of the functional connectivity between the left M1 area and the left superior frontal gyrus was reduced (p < 0.05). Our findings provided preliminary evidences that the iTBS on the ipsilesional M1 could induce neural activity and functional connectivity changes in the motor, language, and other brain regions in patients with PSA, which may promote neuroplasticity and functional recovery.
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Affiliation(s)
- Shuo Xu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China; (S.X.); (Q.Y.); (M.C.)
| | - Qing Yang
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China; (S.X.); (Q.Y.); (M.C.)
| | - Mengye Chen
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China; (S.X.); (Q.Y.); (M.C.)
| | - Panmo Deng
- Department of Rehabilitation Medicine, Jingan District Central Hospital Affiliated to Fudan University, Shanghai 200040, China;
| | - Ren Zhuang
- Department of Rehabilitation Medicine, Changzhou Dean Hospital, Changzhou 213000, China;
| | - Zengchun Sun
- Sichuan Bayi Rehabilitation Center, Affiliated Sichuan Provincial Rehabilitation Hospital of Chengdu University of TCM, Chengdu 610075, China;
| | - Chong Li
- Faculty of Sport and Science, Shanghai University of Sport, Shanghai 200040, China;
| | - Zhijie Yan
- The Third Affiliated Hospital, Xinxiang Medical University, Xinxiang 453003, China;
| | - Yongli Zhang
- Institute of Rehabilitation, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China;
| | - Jie Jia
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China; (S.X.); (Q.Y.); (M.C.)
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15
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Sollmann N, Krieg SM, Säisänen L, Julkunen P. Mapping of Motor Function with Neuronavigated Transcranial Magnetic Stimulation: A Review on Clinical Application in Brain Tumors and Methods for Ensuring Feasible Accuracy. Brain Sci 2021; 11:brainsci11070897. [PMID: 34356131 PMCID: PMC8305823 DOI: 10.3390/brainsci11070897] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 06/29/2021] [Accepted: 07/02/2021] [Indexed: 12/15/2022] Open
Abstract
Navigated transcranial magnetic stimulation (nTMS) has developed into a reliable non-invasive clinical and scientific tool over the past decade. Specifically, it has undergone several validating clinical trials that demonstrated high agreement with intraoperative direct electrical stimulation (DES), which paved the way for increasing application for the purpose of motor mapping in patients harboring motor-eloquent intracranial neoplasms. Based on this clinical use case of the technique, in this article we review the evidence for the feasibility of motor mapping and derived models (risk stratification and prediction, nTMS-based fiber tracking, improvement of clinical outcome, and assessment of functional plasticity), and provide collected sets of evidence for the applicability of quantitative mapping with nTMS. In addition, we provide evidence-based demonstrations on factors that ensure methodological feasibility and accuracy of the motor mapping procedure. We demonstrate that selection of the stimulation intensity (SI) for nTMS and spatial density of stimuli are crucial factors for applying motor mapping accurately, while also demonstrating the effect on the motor maps. We conclude that while the application of nTMS motor mapping has been impressively spread over the past decade, there are still variations in the applied protocols and parameters, which could be optimized for the purpose of reliable quantitative mapping.
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Affiliation(s)
- Nico Sollmann
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Albert-Einstein-Allee 23, 89081 Ulm, Germany
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany;
- Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, San Francisco, CA 94143, USA
- Correspondence:
| | - Sandro M. Krieg
- TUM-Neuroimaging Center, Klinikum rechts der Isar, Technical University of Munich, 81675 Munich, Germany;
- Department of Neurosurgery, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675 Munich, Germany
| | - Laura Säisänen
- Department of Clinical Neurophysiology, Kuopio University Hospital, 70029 Kuopio, Finland; (L.S.); (P.J.)
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
| | - Petro Julkunen
- Department of Clinical Neurophysiology, Kuopio University Hospital, 70029 Kuopio, Finland; (L.S.); (P.J.)
- Department of Applied Physics, University of Eastern Finland, 70211 Kuopio, Finland
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16
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Nazarova M, Novikov P, Ivanina E, Kozlova K, Dobrynina L, Nikulin VV. Mapping of multiple muscles with transcranial magnetic stimulation: absolute and relative test-retest reliability. Hum Brain Mapp 2021; 42:2508-2528. [PMID: 33682975 PMCID: PMC8090785 DOI: 10.1002/hbm.25383] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 02/09/2021] [Accepted: 02/11/2021] [Indexed: 12/13/2022] Open
Abstract
The spatial accuracy of transcranial magnetic stimulation (TMS) may be as small as a few millimeters. Despite such great potential, navigated TMS (nTMS) mapping is still underused for the assessment of motor plasticity, particularly in clinical settings. Here, we investigate the within-limb somatotopy gradient as well as absolute and relative reliability of three hand muscle cortical representations (MCRs) using a comprehensive grid-based sulcus-informed nTMS motor mapping. We enrolled 22 young healthy male volunteers. Two nTMS mapping sessions were separated by 5-10 days. Motor evoked potentials were obtained from abductor pollicis brevis (APB), abductor digiti minimi, and extensor digitorum communis. In addition to individual MRI-based analysis, we studied normalized MNI MCRs. For the reliability assessment, we calculated intraclass correlation and the smallest detectable change. Our results revealed a somatotopy gradient reflected by APB MCR having the most lateral location. Reliability analysis showed that the commonly used metrics of MCRs, such as areas, volumes, centers of gravity (COGs), and hotspots had a high relative and low absolute reliability for all three muscles. For within-limb TMS somatotopy, the most common metrics such as the shifts between MCR COGs and hotspots had poor relative reliability. However, overlaps between different muscle MCRs were highly reliable. We, thus, provide novel evidence that inter-muscle MCR interaction can be reliably traced using MCR overlaps while shifts between the COGs and hotspots of different MCRs are not suitable for this purpose. Our results have implications for the interpretation of nTMS motor mapping results in healthy subjects and patients with neurological conditions.
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Affiliation(s)
- Maria Nazarova
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of EconomicsMoscowRussian Federation
- Federal State Budgetary Institution «Federal center of brain research and neurotechnologies» of the Federal Medical Biological AgencyMoscowRussian Federation
| | - Pavel Novikov
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of EconomicsMoscowRussian Federation
| | - Ekaterina Ivanina
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of EconomicsMoscowRussian Federation
| | - Ksenia Kozlova
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of EconomicsMoscowRussian Federation
| | | | - Vadim V. Nikulin
- Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of EconomicsMoscowRussian Federation
- Department of NeurologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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