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Hebron H, Lugli B, Dimitrova R, Jaramillo V, Yeh LR, Rhodes E, Grossman N, Dijk DJ, Violante IR. A closed-loop auditory stimulation approach selectively modulates alpha oscillations and sleep onset dynamics in humans. PLoS Biol 2024; 22:e3002651. [PMID: 38889194 PMCID: PMC11185466 DOI: 10.1371/journal.pbio.3002651] [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: 03/24/2023] [Accepted: 05/01/2024] [Indexed: 06/20/2024] Open
Abstract
Alpha oscillations play a vital role in managing the brain's resources, inhibiting neural activity as a function of their phase and amplitude, and are changed in many brain disorders. Developing minimally invasive tools to modulate alpha activity and identifying the parameters that determine its response to exogenous modulators is essential for the implementation of focussed interventions. We introduce Alpha Closed-Loop Auditory Stimulation (αCLAS) as an EEG-based method to modulate and investigate these brain rhythms in humans with specificity and selectivity, using targeted auditory stimulation. Across a series of independent experiments, we demonstrate that αCLAS alters alpha power, frequency, and connectivity in a phase, amplitude, and topography-dependent manner. Using single-pulse-αCLAS, we show that the effects of auditory stimuli on alpha oscillations can be explained within the theoretical framework of oscillator theory and a phase-reset mechanism. Finally, we demonstrate the functional relevance of our approach by showing that αCLAS can interfere with sleep onset dynamics in a phase-dependent manner.
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Affiliation(s)
- Henry Hebron
- School of Psychology, University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, United Kingdom
| | - Beatrice Lugli
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Radost Dimitrova
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Valeria Jaramillo
- School of Psychology, University of Surrey, Guildford, United Kingdom
- Surrey Sleep Research Centre, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, United Kingdom
| | - Lisa R. Yeh
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Edward Rhodes
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute Imperial College London, United Kingdom
| | - Nir Grossman
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute Imperial College London, United Kingdom
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, University of Surrey, Guildford, United Kingdom
- UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, Guildford, United Kingdom
| | - Ines R. Violante
- School of Psychology, University of Surrey, Guildford, United Kingdom
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2
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Ding Z, Wang Y, Niu Z, Ouyang G, Li X. The effect of EEG microstate on the characteristics of TMS-EEG. Comput Biol Med 2024; 173:108332. [PMID: 38555703 DOI: 10.1016/j.compbiomed.2024.108332] [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: 01/28/2024] [Revised: 02/26/2024] [Accepted: 03/17/2024] [Indexed: 04/02/2024]
Abstract
OBJECTIVE Differences in neural states at the time of transcranial magnetic stimulation (TMS) can lead to variations in the effectiveness of TMS stimulation. Strategies that aim to lock neural activity states and improve the precision of stimulation timing in TMS optimization should gradually receive attention. One feasible approach is to utilize microstate locking for TMS stimulation, and understanding the impact of microstates at the time of stimulation on TMS response forms the foundation of this approach. APPROACH TMS-EEG data were extracted from 21 healthy subjects through experiments. Based on the different microstates at the time of stimulation, the trials were classified into four datasets. TMS-evoked potential (TEP), topographical distribution, and natural frequency, were computed for each dataset to explore the differences in TMS-EEG characteristics across different microstates. MAIN RESULTS The N100 component of microstate C group (-2.376 μV) was significantly higher (p = 0.003) than of microstate D group (-1.739 μV), and the P180 component of microstate D group (2.482 μV) was significantly higher (p = 0.024) than of microstate B group (1.766 μV) and slightly higher (p = 0.058) than of microstate C group (1.863 μV) by calculating the ROI. The topographical distribution of TEP components during microstate C and microstate D still retained the template characteristics of the microstate at the time of stimulation, and the natural frequencies did not differ among the four classical microstates. SIGNIFICANCE This study showed the potential for future closed-loop TMS based on microstates and would guiding the development of microstate-based closed-loop TMS techniques.
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Affiliation(s)
- Zhaohuan Ding
- Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, 510640, China
| | - Yong Wang
- Zhuhai UM Science & Technology Research Institute, Zhuhai, 519031, China
| | - Zikang Niu
- Aviation Psychology Research Office, Air Force Medical Center, Beijing, 100142, China
| | - Gaoxiang Ouyang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.
| | - Xiaoli Li
- Guangdong Artificial Intelligence and Digital Economy Laboratory (Guangzhou), Guangzhou, 510335, China; School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510641, China.
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Zrenner C, Ziemann U. Closed-Loop Brain Stimulation. Biol Psychiatry 2024; 95:545-552. [PMID: 37743002 PMCID: PMC10881194 DOI: 10.1016/j.biopsych.2023.09.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/24/2023] [Accepted: 09/18/2023] [Indexed: 09/26/2023]
Abstract
In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.
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Affiliation(s)
- Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute for Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada; Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany.
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
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4
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Koponen LM, Martinez M, Wood E, Murphy DLK, Goetz SM, Appelbaum LG, Peterchev AV. Transcranial magnetic stimulation input-output curve slope differences suggest variation in recruitment across muscle representations in primary motor cortex. Front Hum Neurosci 2024; 18:1310320. [PMID: 38384332 PMCID: PMC10879434 DOI: 10.3389/fnhum.2024.1310320] [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: 10/09/2023] [Accepted: 01/29/2024] [Indexed: 02/23/2024] Open
Abstract
Measurement of the input-output (IO) curves of motor evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) can be used to assess corticospinal excitability and motor recruitment. While IO curves have been used to study disease and pharmacology, few studies have compared the IO curves across the body. This study sought to characterize IO curve parameters across the dominant and non-dominant sides of upper and lower limbs in healthy participants. Laterality preferences were assessed in eight healthy participants and IO curves were measured bilaterally for the first dorsal interosseous (FDI), biceps brachii (BB), and tibialis anterior (TA) muscles. Results show that FDI has lower motor threshold than BB which is, in turn, lower than TA. In addition, both BB and TA have markedly shallower logarithmic IO curve slopes from small to large MEP responses than FDI. After normalizing these slopes by their midpoints to account for differences in motor thresholds, which could result from geometric factors such as the target depth, large differences in logarithmic slopes remain present between all three muscles. The differences in slopes between the muscles could not be explained by differences in normalized IO curve spreads, which relate to the extent of the cortical representation and were comparable across the muscles. The IO curve differences therefore suggest muscle-dependent variations in TMS-evoked recruitment across the primary motor cortex, which should be considered when utilizing TMS-evoked MEPs to study disease states and treatment effects.
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Affiliation(s)
- Lari M. Koponen
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Miles Martinez
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
- Center for Cognitive Neuroscience, Duke University, Durham, NC, United States
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States
| | - Eleanor Wood
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - David L. K. Murphy
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
| | - Stefan M. Goetz
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States
- Department of Neurosurgery, Duke University, Durham, NC, United States
| | - Lawrence G. Appelbaum
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
- Department of Psychiatry, University of California, San Diego, San Diego, CA, United States
| | - Angel V. Peterchev
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, United States
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States
- Department of Neurosurgery, Duke University, Durham, NC, United States
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
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5
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Marzetti L, Makkinayeri S, Pieramico G, Guidotti R, D'Andrea A, Roine T, Mutanen TP, Souza VH, Kičić D, Baldassarre A, Ermolova M, Pankka H, Ilmoniemi RJ, Ziemann U, Luca Romani G, Pizzella V. Towards real-time identification of large-scale brain states for improved brain state-dependent stimulation. Clin Neurophysiol 2024; 158:196-203. [PMID: 37827877 DOI: 10.1016/j.clinph.2023.09.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/04/2023] [Accepted: 09/13/2023] [Indexed: 10/14/2023]
Affiliation(s)
- Laura Marzetti
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Abruzzo, Italy; Institute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, Abruzzo, Italy.
| | - Saeed Makkinayeri
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Abruzzo, Italy
| | - Giulia Pieramico
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Abruzzo, Italy
| | - Roberto Guidotti
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Abruzzo, Italy
| | - Antea D'Andrea
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Abruzzo, Italy
| | - Timo Roine
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; Turku Brain and Mind Center, University of Turku, Turku, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University and Helsinki University Hospital, Helsinki, Finland
| | - Tuomas P Mutanen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Victor H Souza
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University and Helsinki University Hospital, Helsinki, Finland
| | - Dubravko Kičić
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland; BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University and Helsinki University Hospital, Helsinki, Finland
| | - Antonello Baldassarre
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Abruzzo, Italy
| | - Maria Ermolova
- Hertie-Institute for Clinical Brain Research, Tübingen, Baden-Württemberg, Germany; Department of Neurology & Stroke, University of Tübingen, Tübingen, Baden-Württemberg, Germany
| | - Hanna Pankka
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Ulf Ziemann
- Hertie-Institute for Clinical Brain Research, Tübingen, Baden-Württemberg, Germany; Department of Neurology & Stroke, University of Tübingen, Tübingen, Baden-Württemberg, Germany
| | - Gian Luca Romani
- Institute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, Abruzzo, Italy
| | - Vittorio Pizzella
- Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti, Abruzzo, Italy; Institute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, Abruzzo, Italy
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6
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Bigoni C, Pagnamenta S, Cadic-Melchior A, Bevilacqua M, Harquel S, Raffin E, Hummel FC. MEP and TEP features variability: is it just the brain-state? J Neural Eng 2024; 21:016011. [PMID: 38211341 DOI: 10.1088/1741-2552/ad1dc2] [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: 08/29/2023] [Accepted: 01/11/2024] [Indexed: 01/13/2024]
Abstract
Objective.The literature investigating the effects of alpha oscillations on corticospinal excitability is divergent. We believe inconsistency in the findings may arise, among others, from the electroencephalography (EEG) processing for brain-state determination. Here, we provide further insights in the effects of the brain-state on cortical and corticospinal excitability and quantify the impact of different EEG processing.Approach.Corticospinal excitability was measured using motor evoked potential (MEP) peak-to-peak amplitudes elicited with transcranial magnetic stimulation (TMS); cortical responses were studied through TMS-evoked potentials' TEPs features. A TMS-EEG-electromyography (EMG) dataset of 18 young healthy subjects who received 180 single-pulse (SP) and 180 paired pulses (PP) to determine short-intracortical inhibition (SICI) was investigated. To study the effect of different EEG processing, we compared the brain-state estimation deriving from three published methods. The influence of presence of neural oscillations was also investigated. To evaluate the effect of the brain-state on MEP and TEP features variability, we defined the brain-state based on specific EEG phase and power combinations, only in trials where neural oscillations were present. The relationship between TEPs and MEPs was further evaluated.Main results.The presence of neural oscillations resulted in more consistent results regardless of the EEG processing approach. Nonetheless, the latter still critically affected the outcomes, making conclusive claims complex. With our approach, the MEP amplitude was positively modulated by the alpha power and phase, with stronger responses during the trough phase and high power. Power and phase also affected TEP features. Importantly, similar effects were observed in both TMS conditions.Significance.These findings support the view that the brain state of alpha oscillations is associated with the variability observed in cortical and corticospinal responses to TMS, with a tight correlation between the two. The results further highlight the importance of closed-loop stimulation approaches while underlining that care is needed in designing experiments and choosing the analytical approaches, which should be based on knowledge from offline studies to control for the heterogeneity originating from different EEG processing strategies.
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Affiliation(s)
- Claudia Bigoni
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Sion 1951, Switzerland
| | - Sara Pagnamenta
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
| | - Andéol Cadic-Melchior
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Sion 1951, Switzerland
| | - Michele Bevilacqua
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Sion 1951, Switzerland
| | - Sylvain Harquel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Sion 1951, Switzerland
| | - Estelle Raffin
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Sion 1951, Switzerland
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva 1202, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Sion 1951, Switzerland
- Clinical Neuroscience, University of Geneva Medical School, 1202 Geneva, Switzerland
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Emanuele M, D'Ausilio A, Koch G, Fadiga L, Tomassini A. Scale-invariant changes in corticospinal excitability reflect multiplexed oscillations in the motor output. J Physiol 2024; 602:205-222. [PMID: 38059677 DOI: 10.1113/jp284273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 11/22/2023] [Indexed: 12/08/2023] Open
Abstract
In the absence of disease, humans produce smooth and accurate movement trajectories. Despite such 'macroscopic' aspect, the 'microscopic' structure of movements reveals recurrent (quasi-rhythmic) discontinuities. To date, it is unclear how the sensorimotor system contributes to the macroscopic and microscopic architecture of movement. Here, we investigated how corticospinal excitability changes in relation to microscopic fluctuations that are naturally embedded within larger macroscopic variations in motor output. Participants performed a visuomotor tracking task. In addition to the 0.25 Hz modulation that is required for task fulfilment (macroscopic scale), the motor output shows tiny but systematic fluctuations at ∼2 and 8 Hz (microscopic scales). We show that motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) during task performance are consistently modulated at all (time) scales. Surprisingly, MEP modulation covers a similar range at both micro- and macroscopic scales, even though the motor output differs by several orders of magnitude. Thus, corticospinal excitability finely maps the multiscale temporal patterning of the motor output, but it does so according to a principle of scale invariance. These results suggest that corticospinal excitability indexes a relatively abstract level of movement encoding that may reflect the hierarchical organisation of sensorimotor processes. KEY POINTS: Motor behaviour is organised on multiple (time)scales. Small but systematic ('microscopic') fluctuations are engrained in larger and slower ('macroscopic') variations in motor output, which are instrumental in deploying the desired motor plan. Corticospinal excitability is modulated in relation to motor fluctuations on both macroscopic and microscopic (time)scales. Corticospinal excitability obeys a principle of scale invariance, that is, it is modulated similarly at all (time)scales, possibly reflecting hierarchical mechanisms that optimise motor encoding.
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Affiliation(s)
- Marco Emanuele
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, Italy
- Department of Computer Science, Western University, London, Ontario, Canada
| | - Alessandro D'Ausilio
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, Italy
| | - Giacomo Koch
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy
- IRCSS Santa Lucia, Roma, Italy
| | - Luciano Fadiga
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, Italy
| | - Alice Tomassini
- Center for Translational Neurophysiology of Speech and Communication, Istituto Italiano di Tecnologia, Ferrara, Italy
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Li W, Li C, Liu A, Lin PJ, Mo L, Zhao H, Xu Q, Meng X, Ji L. Lesion-specific cortical activation following sensory stimulation in patients with subacute stroke. J Neuroeng Rehabil 2023; 20:155. [PMID: 37957755 PMCID: PMC10644526 DOI: 10.1186/s12984-023-01276-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 11/01/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Sensory stimulation can play a fundamental role in the activation of the primary sensorimotor cortex (S1-M1), which can promote motor learning and M1 plasticity in stroke patients. However, studies have focused mainly on investigating the influence of brain lesion profiles on the activation patterns of S1-M1 during motor tasks instead of sensory tasks. Therefore, the objective of this study is to explore the lesion-specific activation patterns due to different brain lesion profiles and types during focal vibration (FV). METHODS In total 52 subacute stroke patients were recruited in this clinical experiment, including patients with basal ganglia hemorrhage/ischemia, brainstem ischemia, other subcortical ischemia, cortical ischemia, and mixed cortical-subcortical ischemia. Electroencephalograms (EEG) were recorded following a resting state lasting for 4 min and three sessions of FV. FV was applied over the muscle belly of the affected limb's biceps for 3 min each session. Beta motor-related EEG power desynchronization overlying S1-M1 was used to indicate the activation of S1-M1, while the laterality coefficient (LC) of the activation of S1-M1 was used to assess the interhemispheric asymmetry of brain activation. RESULTS (1) Regarding brain lesion profiles, FV could lead to the significant activation of bilateral S1-M1 in patients with basal ganglia ischemia and other subcortical ischemia. The activation of ipsilesional S1-M1 in patients with brainstem ischemia was higher than that in patients with cortical ischemia. No activation of S1-M1 was observed in patients with lesions involving cortical regions. (2) Regarding brain lesion types, FV could induce the activation of bilateral S1-M1 in patients with basal ganglia hemorrhage, which was significantly higher than that in patients with basal ganglia ischemia. Additionally, LC showed no significant correlation with the modified Barthel index (MBI) in all patients, but a positive correlation with MBI in patients with basal ganglia lesions. CONCLUSIONS These results reveal that sensory stimulation can induce lesion-specific activation patterns of S1-M1. This indicates FV could be applied in a personalized manner based on the lesion-specific activation of S1-M1 in stroke patients with different lesion profiles and types. Our study may contribute to a better understanding of the underlying mechanisms of cortical reorganization.
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Affiliation(s)
- Wei Li
- Division of Intelligent and Biomechanical System, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, China
- State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Chong Li
- Division of Intelligent and Biomechanical System, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, China.
- School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
- Medical Research Center, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China.
| | - Aixian Liu
- Neurological Rehabilitation Center, Beijing Rehabilitation Hospital Affiliated to Capital Medical University, Beijing, China
| | - Ping-Ju Lin
- Division of Intelligent and Biomechanical System, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, China
| | - Linhong Mo
- Neurological Rehabilitation Center, Beijing Rehabilitation Hospital Affiliated to Capital Medical University, Beijing, China
| | - Hongliang Zhao
- Department of Radiology, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China
| | - Quan Xu
- Division of Intelligent and Biomechanical System, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, China.
- Department of Rehabilitation Medicine, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China.
| | - Xiangzun Meng
- Division of Intelligent and Biomechanical System, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, China
| | - Linhong Ji
- Division of Intelligent and Biomechanical System, Department of Mechanical Engineering, Tsinghua University, Haidian, Beijing, China
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9
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Pillen S, Shulga A, Zrenner C, Ziemann U, Bergmann TO. Repetitive sensorimotor mu-alpha phase-targeted afferent stimulation produces no phase-dependent plasticity related changes in somatosensory evoked potentials or sensory thresholds. PLoS One 2023; 18:e0293546. [PMID: 37903116 PMCID: PMC10615264 DOI: 10.1371/journal.pone.0293546] [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: 05/24/2023] [Accepted: 10/13/2023] [Indexed: 11/01/2023] Open
Abstract
Phase-dependent plasticity has been proposed as a neurobiological mechanism by which oscillatory phase-amplitude cross-frequency coupling mediates memory process in the brain. Mimicking this mechanism, real-time EEG oscillatory phase-triggered transcranial magnetic stimulation (TMS) has successfully induced LTP-like changes in corticospinal excitability in the human motor cortex. Here we asked whether EEG phase-triggered afferent stimulation alone, if repetitively applied to the peaks, troughs, or random phases of the sensorimotor mu-alpha rhythm, would be sufficient to modulate the strength of thalamocortical synapses as assessed by changes in somatosensory evoked potential (SEP) N20 and P25 amplitudes and sensory thresholds (ST). Specifically, we applied 100 Hz triplets of peripheral electrical stimulation (PES) to the thumb, middle, and little finger of the right hand in pseudorandomized trials, with the afferent input from each finger repetitively and consistently arriving either during the cortical mu-alpha trough or peak or at random phases. No significant changes in SEP amplitudes or ST were observed across the phase-dependent PES intervention. We discuss potential limitations of the study and argue that suboptimal stimulation parameter choices rather than a general lack of phase-dependent plasticity in thalamocortical synapses are responsible for this null finding. Future studies should further explore the possibility of phase-dependent sensory stimulation.
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Affiliation(s)
- Steven Pillen
- Department of Neurology & Stroke, Eberhard Karls University of Tübingen, Tübingen, Germany
- Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Anastasia Shulga
- Ward for Demanding Rehabilitation, Helsinki University Hospital, Department of Physical and Rehabilitation Medicine, Helsinki, Finland
- BioMag Laboratory, Helsinki University Hospital Medical Imaging Center, Helsinki, Finland
| | - Christoph Zrenner
- Department of Neurology & Stroke, Eberhard Karls University of Tübingen, Tübingen, Germany
- Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, and Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Institute for Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Ulf Ziemann
- Department of Neurology & Stroke, Eberhard Karls University of Tübingen, Tübingen, Germany
- Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Til Ole Bergmann
- Department of Neurology & Stroke, Eberhard Karls University of Tübingen, Tübingen, Germany
- Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
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10
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Goldenkoff ER, Deluisi JA, Destiny DP, Lee TG, Michon KJ, Brissenden JA, Taylor SF, Polk TA, Vesia M. The behavioral and neural effects of parietal theta burst stimulation on the grasp network are stronger during a grasping task than at rest. Front Neurosci 2023; 17:1198222. [PMID: 37954875 PMCID: PMC10637360 DOI: 10.3389/fnins.2023.1198222] [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: 03/31/2023] [Accepted: 10/05/2023] [Indexed: 11/14/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (TMS) is widely used in neuroscience and clinical settings to modulate human cortical activity. The effects of TMS on neural activity depend on the excitability of specific neural populations at the time of stimulation. Accordingly, the brain state at the time of stimulation may influence the persistent effects of repetitive TMS on distal brain activity and associated behaviors. We applied intermittent theta burst stimulation (iTBS) to a region in the posterior parietal cortex (PPC) associated with grasp control to evaluate the interaction between stimulation and brain state. Across two experiments, we demonstrate the immediate responses of motor cortex activity and motor performance to state-dependent parietal stimulation. We randomly assigned 72 healthy adult participants to one of three TMS intervention groups, followed by electrophysiological measures with TMS and behavioral measures. Participants in the first group received iTBS to PPC while performing a grasping task concurrently. Participants in the second group received iTBS to PPC while in a task-free, resting state. A third group of participants received iTBS to a parietal region outside the cortical grasping network while performing a grasping task concurrently. We compared changes in motor cortical excitability and motor performance in the three stimulation groups within an hour of each intervention. We found that parietal stimulation during a behavioral manipulation that activates the cortical grasping network increased downstream motor cortical excitability and improved motor performance relative to stimulation during rest. We conclude that constraining the brain state with a behavioral task during brain stimulation has the potential to optimize plasticity induction in cortical circuit mechanisms that mediate movement processes.
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Affiliation(s)
| | - Joseph A. Deluisi
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States
| | - Danielle P. Destiny
- Department of Psychology, University of Michigan, Ann Arbor, MI, United States
| | - Taraz G. Lee
- Department of Psychology, University of Michigan, Ann Arbor, MI, United States
| | - Katherine J. Michon
- Department of Psychology, University of Michigan, Ann Arbor, MI, United States
| | - James A. Brissenden
- Department of Psychology, University of Michigan, Ann Arbor, MI, United States
| | - Stephan F. Taylor
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, United States
| | - Thad A. Polk
- Department of Psychology, University of Michigan, Ann Arbor, MI, United States
| | - Michael Vesia
- School of Kinesiology, University of Michigan, Ann Arbor, MI, United States
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11
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de Andrade DC, García-Larrea L. Beyond trial-and-error: Individualizing therapeutic transcranial neuromodulation for chronic pain. Eur J Pain 2023; 27:1065-1083. [PMID: 37596980 PMCID: PMC7616049 DOI: 10.1002/ejp.2164] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/18/2023] [Accepted: 07/19/2023] [Indexed: 08/21/2023]
Abstract
BACKGROUND AND OBJECTIVE Repetitive transcranial magnetic stimulation (rTMS) applied to the motor cortex provides supplementary relief for some individuals with chronic pain who are refractory to pharmacological treatment. As rTMS slowly enters treatment guidelines for pain relief, its starts to be confronted with challenges long known to pharmacological approaches: efficacy at the group-level does not grant pain relief for a particular patient. In this review, we present and discuss a series of ongoing attempts to overcome this therapeutic challenge in a personalized medicine framework. DATABASES AND DATA TREATMENT Relevant scientific publications published in main databases such as PubMed and EMBASE from inception until March 2023 were systematically assessed, as well as a wide number of studies dedicated to the exploration of the mechanistic grounds of rTMS analgesic effects in humans, primates and rodents. RESULTS The main strategies reported to personalize cortical neuromodulation are: (i) the use of rTMS to predict individual response to implanted motor cortex stimulation; (ii) modifications of motor cortex stimulation patterns; (iii) stimulation of extra-motor targets; (iv) assessment of individual cortical networks and rhythms to personalize treatment; (v) deep sensory phenotyping; (vi) personalization of location, precision and intensity of motor rTMS. All approaches except (i) have so far low or moderate levels of evidence. CONCLUSIONS Although current evidence for most strategies under study remains at best moderate, the multiple mechanisms set up by cortical stimulation are an advantage over single-target 'clean' drugs, as they can influence multiple pathophysiologic paths and offer multiple possibilities of individualization. SIGNIFICANCE Non-invasive neuromodulation is on the verge of personalised medicine. Strategies ranging from integration of detailed clinical phenotyping into treatment design to advanced patient neurophysiological characterisation are being actively explored and creating a framework for actual individualisation of care.
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Affiliation(s)
- Daniel Ciampi de Andrade
- Department of Health Science and Technology, Faculty of Medicine, Center for Neuroplasticity and Pain (CNAP), Aalborg University, Aalborg, Denmark
| | - Luís García-Larrea
- University Hospital Pain Center (CETD), Neurological Hospital P. Wertheimer, Hospices Civils de Lyon, Lyon, France
- NeuroPain Lab, INSERM U1028, UMR5292, Lyon Neuroscience Research Center, CNRS, University Claude Bernard Lyon 1, Lyon, France
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12
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Wang B, Peterchev AV, Goetz SM. Three novel methods for determining motor threshold with transcranial magnetic stimulation outperform conventional procedures. J Neural Eng 2023; 20:10.1088/1741-2552/acf1cc. [PMID: 37595573 PMCID: PMC10516469 DOI: 10.1088/1741-2552/acf1cc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/18/2023] [Indexed: 08/20/2023]
Abstract
Objective. Thresholding of neural responses is central to many applications of transcranial magnetic stimulation (TMS), but the stochastic aspect of neuronal activity and motor evoked potentials (MEPs) challenges thresholding techniques. We analyzed existing methods for obtaining TMS motor threshold and their variations, introduced new methods from other fields, and compared their accuracy and speed.Approach. In addition to existing relative-frequency methods, such as the five-out-of-ten method, we examined adaptive methods based on a probabilistic motor threshold model using maximum-likelihood (ML) or maximuma-posteriori(MAP) estimation. To improve the performance of these adaptive estimation methods, we explored variations in the estimation procedure and inclusion of population-level prior information. We adapted a Bayesian estimation method which iteratively incorporated information of the TMS responses into the probability density function. A family of non-parametric stochastic root-finding methods with different convergence criteria and stepping rules were explored as well. The performance of the thresholding methods was evaluated with an independent stochastic MEP model.Main Results. The conventional relative-frequency methods required a large number of stimuli, were inherently biased on the population level, and had wide error distributions for individual subjects. The parametric estimation methods obtained the thresholds much faster and their accuracy depended on the estimation method, with performance significantly improved when population-level prior information was included. Stochastic root-finding methods were comparable to adaptive estimation methods but were much simpler to implement and did not rely on a potentially inaccurate underlying estimation model.Significance. Two-parameter MAP estimation, Bayesian estimation, and stochastic root-finding methods have better error convergence compared to conventional single-parameter ML estimation, and all these methods require significantly fewer TMS pulses for accurate estimation than conventional relative-frequency methods. Stochastic root-finding appears particularly attractive due to the low computational requirements, simplicity of the algorithmic implementation, and independence from potential model flaws in the parametric estimators.
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Affiliation(s)
- Boshuo Wang
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Angel V. Peterchev
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Biomedical Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, School of Medicine, Duke University, Durham, NC, USA
| | - Stefan M. Goetz
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, School of Medicine, Duke University, Durham, NC, USA
- Department of Engineering, School of Technology, University of Cambridge, Cambridge, UK
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13
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Spampinato DA, Ibanez J, Rocchi L, Rothwell J. Motor potentials evoked by transcranial magnetic stimulation: interpreting a simple measure of a complex system. J Physiol 2023; 601:2827-2851. [PMID: 37254441 PMCID: PMC10952180 DOI: 10.1113/jp281885] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 05/18/2023] [Indexed: 06/01/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) is a non-invasive technique that is increasingly used to study the human brain. One of the principal outcome measures is the motor-evoked potential (MEP) elicited in a muscle following TMS over the primary motor cortex (M1), where it is used to estimate changes in corticospinal excitability. However, multiple elements play a role in MEP generation, so even apparently simple measures such as peak-to-peak amplitude have a complex interpretation. Here, we summarize what is currently known regarding the neural pathways and circuits that contribute to the MEP and discuss the factors that should be considered when interpreting MEP amplitude measured at rest in the context of motor processing and patients with neurological conditions. In the last part of this work, we also discuss how emerging technological approaches can be combined with TMS to improve our understanding of neural substrates that can influence MEPs. Overall, this review aims to highlight the capabilities and limitations of TMS that are important to recognize when attempting to disentangle sources that contribute to the physiological state-related changes in corticomotor excitability.
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Affiliation(s)
- Danny Adrian Spampinato
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
- Department of Human NeurosciencesSapienza University of RomeRomeItaly
- Department of Clinical and Behavioral NeurologyIRCCS Santa Lucia FoundationRomeItaly
| | - Jaime Ibanez
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
- BSICoS group, I3A Institute and IIS AragónUniversity of ZaragozaZaragozaSpain
- Department of Bioengineering, Centre for NeurotechnologiesImperial College LondonLondonUK
| | - Lorenzo Rocchi
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
- Department of Medical Sciences and Public HealthUniversity of CagliariCagliariItaly
| | - John Rothwell
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
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14
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Chang YC, Chao PH, Kuan YM, Huang CJ, Chen LF, Mao WC, Su TP, Chen SH, Wei CS. Delay Analysis in Closed-Loop EEG Phase-Triggered Transcranial Magnetic Stimulation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083335 DOI: 10.1109/embc40787.2023.10340744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The recent development of closed-loop EEG phase-triggered transcranial magnetic stimulation (TMS) has advanced potential applications of adaptive neuromodulation based on the current brain state. Closed-loop TMS involves instantaneous acquisition of the EEG rhythm, timing prediction of the target phase, and triggering of TMS. However, the accuracy of EEG phase prediction algorithms is largely influenced by the system's transport delay, and their relationship is rarely considered in related work. This paper proposes a delay analysis that considers the delay of the closed-loop EEG phase-triggered TMS system as a primary factor in the validation of phase prediction algorithms. An in-silico validation using real EEG data was performed to compare the performance of commonly used algorithms. The experimental results indicate a significant influence of the total delay on the algorithm performance, and the performance ranking among algorithms varies at different levels of delay. We conclude that the delay analysis framework should be widely adopted in the design and validation of phase prediction algorithms for closed-loop EEG phase-triggered TMS systems.
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15
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Lieb A, Zrenner B, Zrenner C, Kozák G, Martus P, Grefkes C, Ziemann U. Brain-oscillation-synchronized stimulation to enhance motor recovery in early subacute stroke: a randomized controlled double-blind three- arm parallel-group exploratory trial comparing personalized, non- personalized and sham repetitive transcranial magnetic stimulation (Acronym: BOSS-STROKE). BMC Neurol 2023; 23:204. [PMID: 37231390 PMCID: PMC10210305 DOI: 10.1186/s12883-023-03235-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/29/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND Stroke is a major cause of death and the most frequent cause of permanent disability in western countries. Repetitive transcranial brain stimulation (rTMS) has been used to enhance neuronal plasticity after stroke, yet with only moderate effect sizes. Here we will apply a highly innovative technology that synchronizes rTMS to specific brain states identified by real-time analysis of electroencephalography. METHODS One hundred forty-four patients with early subacute ischemic motor stroke will be included in a multicenter 3-arm parallel, randomized, double-blind, standard rTMS and sham rTMS-controlled exploratory trial in Germany. In the experimental condition, rTMS will be synchronized to the trough of the sensorimotor µ-oscillation, a high-excitability state, over ipsilesional motor cortex. In the standard rTMS control condition the identical protocol will be applied, but non-synchronized to the ongoing µ-oscillation. In the sham condition, the same µ-oscillation-synchronized protocol as in experimental condition will be applied, but with ineffective rTMS, using the sham side of an active/placebo TMS coil. The treatment will be performed over five consecutive work days (1,200 pulses per day, 6,000 pulses total). The primary endpoint will be motor performance after the last treatment session as measured by the Fugl-Meyer Assessment Upper Extremity. DISCUSSION This study investigates, for the first time, the therapeutic efficacy of personalized, brain-state-dependent rTMS. We hypothesize that synchronization of rTMS with a high-excitability state will lead to significantly stronger improvement of paretic upper extremity motor function than standard or sham rTMS. Positive results may catalyze a paradigm-shift towards personalized brain-state-dependent stimulation therapies. TRIAL REGISTRATION This study was registered at ClinicalTrials.gov (NCT05600374) on 10-21-2022.
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Affiliation(s)
- Anne Lieb
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Brigitte Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Institute for Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Christoph Zrenner
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Institute for Biomedical Engineering, University of Toronto, Toronto, ON, Canada
| | - Gábor Kozák
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Peter Martus
- Institute for Clinical Epidemiology and Applied Statistics, University of Tübingen, Tübingen, Germany
| | - Christian Grefkes
- Department of Neurology, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Ulf Ziemann
- Department of Neurology and Stroke, and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
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16
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Ding Z, Guan L, He W, Gu H, Wang Y, Li X. Spatial characteristics of closed-loop TMS-EEG with occipital alpha-phase synchronized. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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17
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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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18
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Poorganji M, Zomorrodi R, Zrenner C, Bansal A, Hawco C, Hill AT, Hadas I, Rajji TK, Chen R, Zrenner B, Voineskos D, Blumberger DM, Daskalakis ZJ. Pre-Stimulus Power but Not Phase Predicts Prefrontal Cortical Excitability in TMS-EEG. BIOSENSORS 2023; 13:220. [PMID: 36831986 PMCID: PMC9953459 DOI: 10.3390/bios13020220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/10/2023] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
The cortical response to transcranial magnetic stimulation (TMS) has notable inter-trial variability. One source of this variability can be the influence of the phase and power of pre-stimulus neuronal oscillations on single-trial TMS responses. Here, we investigate the effect of brain oscillatory activity on TMS response in 49 distinct healthy participants (64 datasets) who had received single-pulse TMS over the left dorsolateral prefrontal cortex. Across all frequency bands of theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz), there was no significant effect of pre-TMS phase on single-trial cortical evoked activity. After high-powered oscillations, whether followed by a TMS pulse or not, the subsequent activity was larger than after low-powered oscillations. We further defined a measure, corrected_effect, to enable us to investigate brain responses to the TMS pulse disentangled from the power of ongoing (spontaneous) oscillations. The corrected_effect was significantly different from zero (meaningful added effect of TMS) only in theta and beta bands. Our results suggest that brain state prior to stimulation might play some role in shaping the subsequent TMS-EEG response. Specifically, our findings indicate that the power of ongoing oscillatory activity, but not phase, can influence brain responses to TMS. Aligning the TMS pulse with specific power thresholds of an EEG signal might therefore reduce variability in neurophysiological measurements and also has the potential to facilitate more robust therapeutic effects of stimulation.
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Affiliation(s)
- Mohsen Poorganji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Reza Zomorrodi
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute for Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Aiyush Bansal
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Colin Hawco
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Aron T. Hill
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC 3125, Australia
| | - Itay Hadas
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093-0603, USA
| | - Tarek K. Rajji
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Robert Chen
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Brigitte Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Daphne Voineskos
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Daniel M. Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
| | - Zafiris J. Daskalakis
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093-0603, USA
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Zrenner C, Kozák G, Schaworonkow N, Metsomaa J, Baur D, Vetter D, Blumberger DM, Ziemann U, Belardinelli P. Corticospinal excitability is highest at the early rising phase of sensorimotor µ-rhythm. Neuroimage 2023; 266:119805. [PMID: 36513289 DOI: 10.1016/j.neuroimage.2022.119805] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 11/30/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022] Open
Abstract
Alpha oscillations are thought to reflect alternating cortical states of excitation and inhibition. Studies of perceptual thresholds and evoked potentials have shown the scalp EEG negative phase of the oscillation to correspond to a short-lasting low-threshold and high-excitability state of underlying visual, somatosensory, and primary motor cortex. The negative peak of the oscillation is assumed to correspond to the state of highest excitability based on biophysical considerations and considerable effort has been made to improve the extraction of a predictive signal by individually optimizing EEG montages. Here, we investigate whether it is the negative peak of sensorimotor µ-rhythm that corresponds to the highest corticospinal excitability, and whether this is consistent between individuals. In 52 adult participants, a standard 5-channel surface Laplacian EEG montage was used to extract sensorimotor µ-rhythm during transcranial magnetic stimulation (TMS) of primary motor cortex. Post-hoc trials were sorted from 800 TMS-evoked motor potentials (MEPs) according to the pre-stimulus EEG (estimated instantaneous phase) and MEP amplitude (as an index of corticospinal excitability). Different preprocessing transformations designed to improve the accuracy by which µ-alpha phase predicts excitability were also tested. By fitting a sinusoid to the MEP amplitudes, sorted according to pre-stimulus EEG-phase, we found that excitability was highest during the early rising phase, at a significant delay with respect to the negative peak by on average 45° or 10 ms. The individual phase of highest excitability was consistent across study participants and unaffected by two different EEG-cleaning methods that utilize 64 channels to improve signal quality by compensating for individual noise level and channel covariance. Personalized transformations of the montage did not yield better prediction of excitability from µ-alpha phase. The relationship between instantaneous phase of a brain oscillation and fluctuating cortical excitability appears to be more complex than previously hypothesized. In TMS of motor cortex, a standard surface Laplacian 5-channel EEG montage is effective in extracting a predictive signal and the phase corresponding to the highest excitability appears to be consistent between individuals. This is an encouraging result with respect to the clinical potential of therapeutic personalized brain interventions in the motor system. However, it remains to be investigated, whether similar results can be obtained for other brain areas and brain oscillations targeted with EEG and TMS.
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Affiliation(s)
- Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Institute for Biomedical Engineering, University of Toronto, Toronto, ON, Canada; Department of Neurology & Stroke, University of Tübingen, Germany.
| | - Gábor Kozák
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Natalie Schaworonkow
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Johanna Metsomaa
- Department of Neurology & Stroke, University of Tübingen, Germany; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - David Baur
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - David Vetter
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany
| | - Daniel M Blumberger
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Germany.
| | - Paolo Belardinelli
- Department of Neurology & Stroke, University of Tübingen, Germany; CIMeC, Center for Mind/Brain Sciences, University of Trento, Trento, Italy
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20
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Ozdemir RA, Kirkman S, Magnuson JR, Fried PJ, Pascual-Leone A, Shafi MM. Phase matters when there is power: Phasic modulation of corticospinal excitability occurs at high amplitude sensorimotor mu-oscillations. NEUROIMAGE. REPORTS 2022; 2:100132. [PMID: 36570046 PMCID: PMC9784422 DOI: 10.1016/j.ynirp.2022.100132] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Prior studies have suggested that oscillatory activity in cortical networks can modulate stimulus-evoked responses through time-varying fluctuations in neural excitation-inhibition dynamics. Studies combining transcranial magnetic stimulation (TMS) with electromyography (EMG) and electroencephalography (EEG) can provide direct measurements to examine how instantaneous fluctuations in cortical oscillations contribute to variability in TMS-induced corticospinal responses. However, the results of these studies have been conflicting, as some reports showed consistent phase effects of sensorimotor mu-rhythms with increased excitability at the negative mu peaks, while others failed to replicate these findings or reported unspecific mu-phase effects across subjects. Given the lack of consistent results, we systematically examined the modulatory effects of instantaneous and pre-stimulus sensorimotor mu-rhythms on corticospinal responses with offline EEG-based motor evoked potential (MEP) classification analyses across five identical visits. Instantaneous sensorimotor mu-phase or pre-stimulus mu-power alone did not significantly modulate MEP responses. Instantaneous mu-power analyses showed weak effects with larger MEPs during high-power trials at the overall group level analyses, but this trend was not reproducible across visits. However, TMS delivered at the negative peak of high magnitude mu-oscillations generated the largest MEPs across all visits, with significant differences compared to other peak-phase combinations. High power effects on MEPs were only observed at the trough phase of ongoing mu oscillations originating from the stimulated region, indicating site and phase specificity, respectively. More importantly, such phase-dependent power effects on corticospinal excitability were reproducible across multiple visits. We provide further evidence that fluctuations in corticospinal excitability indexed by MEP amplitudes are partially driven by dynamic interactions between the magnitude and the phase of ongoing sensorimotor mu oscillations at the time of TMS, and suggest promising insights for (re)designing neuromodulatory TMS protocols targeted to specific cortical oscillatory states.
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Affiliation(s)
- Recep A. Ozdemir
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA,Corresponding author. Mouhsin Shafi Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Medical Center, Harvard Medical School, Boston, MA, USA. (R.A. Ozdemir)
| | - Sofia Kirkman
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Justine R. Magnuson
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Peter J. Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, MA, USA,Hinda and Arthur Marcus Institute for Aging Research and Deanne and Sidney Wolk Center for Memory Health, Hebrew Senior Life, Boston, MA, USA,Guttmann Brain Health Institute, Institut Guttmann de Neurorehabilitació, Universitat Autonoma de Barcelona, Badalona, Spain
| | - Mouhsin M. Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA,Corresponding author. Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA. (M.M. Shafi)
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21
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The phase of sensorimotor mu and beta oscillations has the opposite effect on corticospinal excitability. Brain Stimul 2022; 15:1093-1100. [PMID: 35964870 DOI: 10.1016/j.brs.2022.08.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 08/05/2022] [Accepted: 08/06/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Neural oscillations in the primary motor cortex (M1) shape corticospinal excitability. Power and phase of ongoing mu (8-13 Hz) and beta (14-30 Hz) activity may mediate motor cortical output. However, the functional dynamics of both mu and beta phase and power relationships and their interaction, are largely unknown. OBJECTIVE Here, we employ recently developed real-time targeting of the mu and beta rhythm, to apply phase-specific brain stimulation and probe motor corticospinal excitability non-invasively. For this, we used instantaneous read-out and analysis of ongoing oscillations, targeting four different phases (0°, 90°, 180°, and 270°) of mu and beta rhythms with suprathreshold single-pulse transcranial magnetic stimulation (TMS) to M1. Ensuing motor evoked potentials (MEPs) in the right first dorsal interossei muscle were recorded. Twenty healthy adults took part in this double-blind randomized crossover study. RESULTS Mixed model regression analyses showed significant phase-dependent modulation of corticospinal output by both mu and beta rhythm. Strikingly, these modulations exhibit a double dissociation. MEPs are larger at the mu trough and rising phase and smaller at the peak and falling phase. For the beta rhythm we found the opposite behavior. Also, mu power, but not beta power, was positively correlated with corticospinal output. Power and phase effects did not interact for either rhythm, suggesting independence between these aspects of oscillations. CONCLUSION Our results provide insights into real-time motor cortical oscillation dynamics, which offers the opportunity to improve the effectiveness of TMS by specifically targeting different frequency bands.
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22
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Nasr K, Haslacher D, Dayan E, Censor N, Cohen LG, Soekadar SR. Breaking the boundaries of interacting with the human brain using adaptive closed-loop stimulation. Prog Neurobiol 2022; 216:102311. [PMID: 35750290 DOI: 10.1016/j.pneurobio.2022.102311] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 06/20/2022] [Indexed: 11/18/2022]
Abstract
The human brain is arguably one of the most complex systems in nature. To understand how it operates, it is essential to understand the link between neural activity and behavior. Experimental investigation of that link requires tools to interact with neural activity during behavior. Human neuroscience, however, has been severely bottlenecked by the limitations of these tools. While invasive methods can support highly specific interaction with brain activity during behavior, their applicability in human neuroscience is limited. Despite extensive development in the last decades, noninvasive alternatives have lacked spatial specificity and yielded results that are commonly fraught with variability and replicability issues, along with relatively limited understanding of the neural mechanisms involved. Here we provide a comprehensive review of the state-of-the-art in interacting with human brain activity and highlight current limitations and recent efforts to overcome these limitations. Beyond crucial technical and scientific advancements in electromagnetic brain stimulation, new frontiers in interacting with human brain activity such as task-irrelevant sensory stimulation and focal ultrasound stimulation are introduced. Finally, we argue that, along with technological improvements and breakthroughs in noninvasive methods, a paradigm shift towards adaptive closed-loop stimulation will be a critical step for advancing human neuroscience.
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Affiliation(s)
- Khaled Nasr
- Clinical Neurotechnology Laboratory & Center for Translational Neuromodulation, Department of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - David Haslacher
- Clinical Neurotechnology Laboratory & Center for Translational Neuromodulation, Department of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Eran Dayan
- Department of Radiology and Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nitzan Censor
- School of Psychological Sciences and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Leonardo G Cohen
- Human Cortical Physiology and Neurorehabilitation Section, National Institutes of Neurological Disorders and Stroke (NINDS), Bethesda, MD, USA
| | - Surjo R Soekadar
- Clinical Neurotechnology Laboratory & Center for Translational Neuromodulation, Department of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany.
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23
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Goetz SM, Howell B, Wang B, Li Z, Sommer MA, Peterchev AV, Grill WM. Isolating two sources of variability of subcortical stimulation to quantify fluctuations of corticospinal tract excitability. Clin Neurophysiol 2022; 138:134-142. [PMID: 35397278 PMCID: PMC9271909 DOI: 10.1016/j.clinph.2022.02.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/17/2022] [Accepted: 02/01/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Investigate the variability previously found with cortical stimulation and handheld transcranial magnetic stimulation (TMS) coils, criticized for its high potential of coil position fluctuations, bypassing the cortex using deep brain electrical stimulation (DBS) of the corticospinal tract with fixed electrodes where both latent variations of the coil position of TMS are eliminated and cortical excitation fluctuations should be absent. METHODS Ten input-output curves were recorded from five anesthetized cats with implanted DBS electrodes targeting the corticospinal tract. Goodness of fit of regressions with a conventional single variability source as well as a dual variability source model was quantified using a Schwarz Bayesian Information approach to avoid overfitting. RESULTS Motor evoked potentials (MEPs) through DBS of the corticospinal tract revealed short-term fluctuations in excitability of the targeted neuron pathway reflecting endogenous input-side variability at similar magnitude as TMS despite bypassing cortical networks. CONCLUSION Input-side variability, i.e., variability resulting in changing MEP amplitudes as if the stimulation strength was modulated, also emerges in electrical stimulation at a similar degree and is not primarily a result of varying stimulation, such as minor coil movements in TMS. More importantly, this variability component is present, although the cortex is bypassed. Thus, it may be of spinal origin, which can include cortical input from spinal projections. Further, the nonlinearity of the compound variability entails complex heteroscedastic non-Gaussian distributions and typically does not allow simple linear averages in statistical analysis of MEPs. As the average is dominated by outliers, it risks bias. With appropriate regression, the net effects of excitatory and inhibitory inputs to the targeted neuron pathways become noninvasively observable and quantifiable. SIGNIFICANCE The neural responses evoked by artificial stimulation in the cerebral cortex are variable. For example, MEPs in response to repeated presentations of the same stimulus can vary from no response to saturation across trials. Several sources of such variability have been suggested, and most of them may be technical in nature, but localization is missing.
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Affiliation(s)
- Stefan M Goetz
- Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, UK; Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC 27710, USA; Department of Neurosurgery, Duke University, Durham, NC 27710, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA.
| | - Bryan Howell
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Boshuo Wang
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC 27710, USA
| | - Zhongxi Li
- Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA
| | - Marc A Sommer
- Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Department of Neurobiology, Duke University, Durham, NC 27710, USA
| | - Angel V Peterchev
- Department of Psychiatry & Behavioral Sciences, Duke University, Durham, NC 27710, USA; Department of Neurosurgery, Duke University, Durham, NC 27710, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Warren M Grill
- Department of Neurosurgery, Duke University, Durham, NC 27710, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC 27708, USA; Duke Institute of Brain Sciences, Duke University, Durham, NC 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Department of Neurobiology, Duke University, Durham, NC 27710, USA
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24
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Klooster DCW, Ferguson MA, Boon PAJM, Baeken C. Personalizing Repetitive Transcranial Magnetic Stimulation Parameters for Depression Treatment Using Multimodal Neuroimaging. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:536-545. [PMID: 34800726 DOI: 10.1016/j.bpsc.2021.11.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/24/2021] [Accepted: 11/09/2021] [Indexed: 06/13/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a tool that can be used to administer treatment for neuropsychiatric disorders such as major depressive disorder, although the clinical efficacy is still rather modest. Overly general stimulation protocols that consider neither patient-specific depression symptomology nor individualized brain characteristics, such as anatomy or structural and functional connections, may be the cause of the high inter- and intraindividual variability in rTMS clinical responses. Multimodal neuroimaging can provide the necessary insights into individual brain characteristics and can therefore be used to personalize rTMS parameters. Optimal coil positioning should include a three-step process: 1) identify the optimal (indirect) target area based on the exact symptom pattern of the patient; 2) derive the cortical (direct) target location based on functional and/or structural connectomes derived from functional and diffusion magnetic resonance imaging data; and 3) determine the ideal coil position by computational modeling, such that the electric field distribution overlaps with the cortical target. These TMS-induced electric field simulations, derived from anatomical and diffusion magnetic resonance imaging data, can be further applied to compute optimal stimulation intensities. In addition to magnetic resonance imaging, electroencephalography can provide complementary information regarding the ongoing brain oscillations. This information can be used to determine the optimal timing and frequency of the stimuli. The heightened benefits of these personalized stimulation approaches are logically reasoned, but speculative. Randomized clinical trials will be required to compare clinical responses from standard rTMS protocols to personalized protocols. Ultimately, an optimized clinical response may result from precision protocols derived from combinations of personalized stimulation parameters.
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Affiliation(s)
- Deborah C W Klooster
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Ghent University, Ghent, Belgium.
| | - Michael A Ferguson
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Paul A J M Boon
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium; Department of Neurology, Ghent University Hospital, Ghent, Belgium
| | - Chris Baeken
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Ghent University, Ghent, Belgium; Department of Psychiatry, University Hospital Brussels, Jette, Belgium
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25
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State-dependent effects of neural stimulation on brain function and cognition. Nat Rev Neurosci 2022; 23:459-475. [PMID: 35577959 DOI: 10.1038/s41583-022-00598-1] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/20/2022] [Indexed: 01/02/2023]
Abstract
Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.
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26
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Schaworonkow N, Nikulin VV. Is sensor space analysis good enough? Spatial patterns as a tool for assessing spatial mixing of EEG/MEG rhythms. Neuroimage 2022; 253:119093. [PMID: 35288283 DOI: 10.1016/j.neuroimage.2022.119093] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 03/07/2022] [Accepted: 03/10/2022] [Indexed: 12/25/2022] Open
Abstract
Analyzing non-invasive recordings of electroencephalography (EEG) and magnetoencephalography (MEG) directly in sensor space, using the signal from individual sensors, is a convenient and standard way of working with this type of data. However, volume conduction introduces considerable challenges for sensor space analysis. While the general idea of signal mixing due to volume conduction in EEG/MEG is recognized, the implications have not yet been clearly exemplified. Here, we illustrate how different types of activity overlap on the level of individual sensors. We show spatial mixing in the context of alpha rhythms, which are known to have generators in different areas of the brain. Using simulations with a realistic 3D head model and lead field and data analysis of a large resting-state EEG dataset, we show that electrode signals can be differentially affected by spatial mixing by computing a sensor complexity measure. While prominent occipital alpha rhythms result in less heterogeneous spatial mixing on posterior electrodes, central electrodes show a diversity of rhythms present. This makes the individual contributions, such as the sensorimotor mu-rhythm and temporal alpha rhythms, hard to disentangle from the dominant occipital alpha. Additionally, we show how strong occipital rhythms can contribute the majority of activity to frontal channels, potentially compromising analyses that are solely conducted in sensor space. We also outline specific consequences of signal mixing for frequently used assessment of power, power ratios and connectivity profiles in basic research and for neurofeedback application. With this work, we hope to illustrate the effects of volume conduction in a concrete way, such that the provided practical illustrations may be of use to EEG researchers to in order to evaluate whether sensor space is an appropriate choice for their topic of investigation.
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Affiliation(s)
- Natalie Schaworonkow
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main 60528, Germany.
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
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27
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Momi D, Ozdemir RA, Tadayon E, Boucher P, Di Domenico A, Fasolo M, Shafi MM, Pascual-Leone A, Santarnecchi E. Phase-dependent local brain states determine the impact of image-guided transcranial magnetic stimulation on motor network electroencephalographic synchronization. J Physiol 2022; 600:1455-1471. [PMID: 34799873 PMCID: PMC9728936 DOI: 10.1113/jp282393] [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: 09/19/2021] [Accepted: 11/10/2021] [Indexed: 11/08/2022] Open
Abstract
Recent studies have synchronized transcranial magnetic stimulation (TMS) application with pre-defined brain oscillatory phases showing how brain response to perturbation depends on the brain state. However, none have investigated whether phase-dependent TMS can possibly modulate connectivity with homologous distant brain regions belonging to the same network. In the framework of network-targeted TMS, we investigated whether stimulation delivered at a specific phase of ongoing brain oscillations might favour stronger cortico-cortical (c-c) synchronization of distant network nodes connected to the stimulation target. Neuronavigated TMS pulses were delivered over the primary motor cortex (M1) during ongoing electroencephalography recording in 24 healthy individuals over two repeated sessions 1 month apart. Stimulation effects were analysed considering whether the TMS pulse was delivered at the time of a positive (peak) or negative (trough) phase of μ-frequency oscillation, which determines c-c synchrony within homologous areas of the sensorimotor network. Diffusion weighted imaging was used to study c-c connectivity within the sensorimotor network and identify contralateral regions connected with the stimulation spot. Depending on when during the μ-activity the TMS-pulse was applied (peak or trough), its impact on inter-hemispheric network synchrony varied significantly. Higher M1-M1 phase-lock synchronization after the TMS-pulse (0-200 ms) in the μ-frequency band was found for trough compared to peak stimulation trials in both study visits. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of the response to the external perturbation, with implications for interventions aimed at engaging more distributed functional brain networks. KEY POINTS: Synchronized transcranial magnetic stimulation (TMS) pulses with pre-defined brain oscillatory phases allow evaluation of the impact of brain states on TMS effects. TMS pulses over M1 at the negative peak of the μ-frequency band induce higher phase-lock synchronization with interconnected contralateral homologous regions. Cortico-cortical synchronization changes are linearly predicted by the fibre density and cross-section of the white matter tract that connects the two brain regions. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of within-network synchronization.
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Affiliation(s)
- Davide Momi
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, Chieti
| | - Recep A. Ozdemir
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Ehsan Tadayon
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Pierre Boucher
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Alberto Di Domenico
- Department of Psychological Science, Humanities and Territory, University of Chieti-Pescara, Chieti, Italy
| | - Mirco Fasolo
- Department of Psychological Science, Humanities and Territory, University of Chieti-Pescara, Chieti, Italy
| | - Mouhsin M. Shafi
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston MA,Department of Neurology, Harvard Medical School, Boston, MA, USA,Guttmann Brain Health Institute, Guttmann Institut, Universitat Autonoma, Barcelona, Spain
| | - Emiliano Santarnecchi
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA
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28
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Bridging the gap: TMS-EEG from Lab to Clinic. J Neurosci Methods 2022; 369:109482. [PMID: 35041855 DOI: 10.1016/j.jneumeth.2022.109482] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/09/2022] [Accepted: 01/13/2022] [Indexed: 01/06/2023]
Abstract
The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has reached technological maturity and has been an object of significant scientific interest for over two decades. Ιn parallel, accumulating evidence highlights the potential of TMS-EEG as a useful tool in the field of clinical neurosciences. Nevertheless, its clinical utility has not yet been established, partly because technical and methodological limitations have created a gap between an evolving scientific tool and standard clinical practice. Here we review some of the identified gaps that still prevent TMS-EEG moving from science laboratories to clinical practice. The principal and partly overlapping gaps include: 1) complex and laborious application, 2) difficulty in obtaining high-quality signals, 3) suboptimal accuracy and reliability, and 4) insufficient understanding of the neurobiological substrate of the responses. All these four aspects need to be satisfactorily addressed for the method to become clinically applicable and enter the diagnostic and therapeutic arena. In the current review, we identify steps that might be taken to address these issues and discuss promising recent studies providing tools to aid bridging the gaps.
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Kallioniemi E, Awiszus F, Pitkänen M, Julkunen P. Fast acquisition of resting motor threshold with a stimulus-response curve - Possibility or hazard for transcranial magnetic stimulation applications? Clin Neurophysiol Pract 2022; 7:7-15. [PMID: 35024510 PMCID: PMC8733273 DOI: 10.1016/j.cnp.2021.10.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 09/15/2021] [Accepted: 10/05/2021] [Indexed: 11/24/2022] Open
Abstract
Objective Previous research has suggested that transcranial magnetic stimulation (TMS) related cortical excitability measures could be estimated quickly using stimulus-response curves with short interstimulus intervals (ISIs). Here we evaluated the resting motor threshold (rMT) estimated with these curves. Methods Stimulus-response curves were measured with three ISIs: 1.2-2 s, 2-3 s, and 3-4 s. Each curve was formed with 108 stimuli using stimulation intensities ranging from 0.75 to 1.25 times the rMTguess, which was estimated based on motor evoked potential (MEP) amplitudes of three scout responses. Results The ISI did not affect the rMT estimated from the curves (F = 0.235, p = 0.683) or single-trial MEP amplitudes at the group level (F = 0.90, p = 0.405), but a significant subject by ISI interaction (F = 3.64; p < 0.001) was detected in MEP amplitudes. No trend was observed which ISI was most excitable, as it varied between subjects. Conclusions At the group level, the stimulus-response curves are unaffected by the short ISI. At the individual level, these curves are highly affected by the ISI. Significance Estimating rMT using stimulus-response curves with short ISIs impacts the rMT estimate and should be avoided in clinical and research TMS applications.
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Key Words
- APB, abductor pollicis brevis
- EMG, electromyography
- ISI, interstimulus interval
- Interstimulus interval
- MEP, motor evoked potential
- MRI, magnetic resonance imaging
- MSO, maximum stimulator output
- Motor evoked potential
- Motor threshold
- SI, stimulation intensity
- Stimulus-response curve
- TMS, transcranial magnetic stimulation
- rMT, resting motor threshold
- rMTRR, resting motor threshold estimated with the Rossini-Rothwell method
- rMTestimate, resting motor threshold estimated with stimulus–response curves
- rMTguess, resting motor threshold estimated with prior information and three scout pulses
- rMTthreshold, resting motor threshold estimated with the threshold-hunting method
- rMTtrue, true resting motor threshold in simulations
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Affiliation(s)
- Elisa Kallioniemi
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, United States
| | - Friedemann Awiszus
- Neuromuscular Research Group at the Department of Orthopaedics, Otto-von-Guericke University, Magdeburg, Germany
| | - Minna Pitkänen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
| | - Petro Julkunen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.,Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio, Finland
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30
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α Phase-Amplitude Tradeoffs Predict Visual Perception. eNeuro 2022; 9:ENEURO.0244-21.2022. [PMID: 35105658 PMCID: PMC8868024 DOI: 10.1523/eneuro.0244-21.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 01/12/2022] [Accepted: 01/16/2022] [Indexed: 11/21/2022] Open
Abstract
Spontaneous α oscillations (∼10 Hz) have been associated with various cognitive functions, including perception. Their phase and amplitude independently predict cortical excitability and subsequent perceptual performance. However, the causal role of α phase-amplitude tradeoffs on visual perception remains ill-defined. We aimed to fill this gap and tested two clear predictions from the pulsed inhibition theory according to which α oscillations are associated with periodic functional inhibition. (1) High-α amplitude induces cortical inhibition at specific phases, associated with low perceptual performance, while at opposite phases, inhibition decreases (potentially increasing excitation) and perceptual performance increases. (2) Low-α amplitude is less susceptible to these phasic (periodic) pulses of inhibition, leading to overall higher perceptual performance. Here, cortical excitability was assessed in humans using phosphene (illusory) perception induced by single pulses of transcranial magnetic stimulation (TMS) applied over visual cortex at perceptual threshold, and its postpulse evoked activity recorded with simultaneous electroencephalography (EEG). We observed that prepulse α phase modulates the probability to perceive a phosphene, predominantly for high-α amplitude, with a nonoptimal phase for phosphene perception between -π/2 and -π/4. The prepulse nonoptimal phase further leads to an increase in postpulse-evoked activity [event-related potential (ERP)], in phosphene-perceived trials specifically. Together, these results show that α oscillations create periodic inhibitory moments when α amplitude is high, leading to periodic decrease of perceptual performance. This study provides strong causal evidence in favor of the pulsed inhibition theory.
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31
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Janssens SEW, Sack AT. Spontaneous Fluctuations in Oscillatory Brain State Cause Differences in Transcranial Magnetic Stimulation Effects Within and Between Individuals. Front Hum Neurosci 2021; 15:802244. [PMID: 34924982 PMCID: PMC8674306 DOI: 10.3389/fnhum.2021.802244] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 11/16/2021] [Indexed: 01/01/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) can cause measurable effects on neural activity and behavioral performance in healthy volunteers. In addition, TMS is increasingly used in clinical practice for treating various neuropsychiatric disorders. Unfortunately, TMS-induced effects show large intra- and inter-subject variability, hindering its reliability, and efficacy. One possible source of this variability may be the spontaneous fluctuations of neuronal oscillations. We present recent studies using multimodal TMS including TMS-EMG (electromyography), TMS-tACS (transcranial alternating current stimulation), and concurrent TMS-EEG-fMRI (electroencephalography, functional magnetic resonance imaging), to evaluate how individual oscillatory brain state affects TMS signal propagation within targeted networks. We demonstrate how the spontaneous oscillatory state at the time of TMS influences both immediate and longer-lasting TMS effects. These findings indicate that at least part of the variability in TMS efficacy may be attributable to the current practice of ignoring (spontaneous) oscillatory fluctuations during TMS. Ignoring this state-dependent spread of activity may cause great individual variability which so far is poorly understood and has proven impossible to control. We therefore also compare two technical solutions to directly account for oscillatory state during TMS, namely, to use (a) tACS to externally control these oscillatory states and then apply TMS at the optimal (controlled) brain state, or (b) oscillatory state-triggered TMS (closed-loop TMS). The described multimodal TMS approaches are paramount for establishing more robust TMS effects, and to allow enhanced control over the individual outcome of TMS interventions aimed at modulating information flow in the brain to achieve desirable changes in cognition, mood, and behavior.
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Affiliation(s)
- Shanice E W Janssens
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht, Netherlands
| | - Alexander T Sack
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht, Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Brain + Nerve Centre, Maastricht University Medical Centre+ (MUMC+), Maastricht, Netherlands.,Centre for Integrative Neuroscience (CIN), Maastricht University, Maastricht, Netherlands
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32
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Lehmann SJ, Corneil BD. Completing the puzzle: Why studies in non-human primates are needed to better understand the effects of non-invasive brain stimulation. Neurosci Biobehav Rev 2021; 132:1074-1085. [PMID: 34742722 DOI: 10.1016/j.neubiorev.2021.10.040] [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: 06/11/2021] [Revised: 09/29/2021] [Accepted: 10/31/2021] [Indexed: 11/27/2022]
Abstract
Brain stimulation is a core method in neuroscience. Numerous non-invasive brain stimulation (NIBS) techniques are currently in use in basic and clinical research, and recent advances promise the ability to non-invasively access deep brain structures. While encouraging, there is a surprising gap in our understanding of precisely how NIBS perturbs neural activity throughout an interconnected network, and how such perturbed neural activity ultimately links to behaviour. In this review, we will consider why non-human primate (NHP) models of NIBS are ideally situated to address this gap in knowledge, and why the oculomotor network that moves our line of sight offers a particularly valuable platform in which to empirically test hypothesis regarding NIBS-induced changes in brain and behaviour. NHP models of NIBS will enable investigation of the complex, dynamic effects of brain stimulation across multiple hierarchically interconnected brain areas, networks, and effectors. By establishing such links between brain and behavioural output, work in NHPs can help optimize experimental and therapeutic approaches, improve NIBS efficacy, and reduce side-effects of NIBS.
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Affiliation(s)
- Sebastian J Lehmann
- Department of Physiology and Pharmacology, Western University, London, Ontario, N6A 5B7, Canada.
| | - Brian D Corneil
- Department of Physiology and Pharmacology, Western University, London, Ontario, N6A 5B7, Canada; Department of Psychology, Western University, London, Ontario, N6A 5B7, Canada; Robarts Research Institute, London, Ontario, N6A 5B7, Canada.
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33
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Watanabe T. Causal roles of prefrontal cortex during spontaneous perceptual switching are determined by brain state dynamics. eLife 2021; 10:69079. [PMID: 34713803 PMCID: PMC8631941 DOI: 10.7554/elife.69079] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 10/28/2021] [Indexed: 12/23/2022] Open
Abstract
The prefrontal cortex (PFC) is thought to orchestrate cognitive dynamics. However, in tests of bistable visual perception, no direct evidence supporting such presumable causal roles of the PFC has been reported except for a recent work. Here, using a novel brain-state-dependent neural stimulation system, we identified causal effects on percept dynamics in three PFC activities—right frontal eye fields, dorsolateral PFC (DLPFC), and inferior frontal cortex (IFC). The causality is behaviourally detectable only when we track brain state dynamics and modulate the PFC activity in brain-state-/state-history-dependent manners. The behavioural effects are underpinned by transient neural changes in the brain state dynamics, and such neural effects are quantitatively explainable by structural transformations of the hypothetical energy landscapes. Moreover, these findings indicate distinct functions of the three PFC areas: in particular, the DLPFC enhances the integration of two PFC-active brain states, whereas IFC promotes the functional segregation between them. This work resolves the controversy over the PFC roles in spontaneous perceptual switching and underlines brain state dynamics in fine investigations of brain-behaviour causality. A cube that seems to shift its spatial arrangement as you keep looking; the elegant silhouette of a pirouetting dancer, which starts to spin in the opposite direction the more you stare at it; an illustration that shows two profiles – or is it a vase? These optical illusions are examples of bistable visual perception. Beyond their entertaining aspect, they provide a way for scientists to explore the dynamics of human consciousness, and the neural regions involved in this process. Some studies show that bistable visual perception is associated with the activation of the prefrontal cortex, a brain area involved in complex cognitive processes. However, it is unclear whether this region is required for the illusions to emerge. Some research has showed that even if sections of the prefrontal cortex are temporally deactivated, participants can still experience the illusions. Instead, Takamitsu Watanabe proposes that bistable visual perception is a process tied to dynamic brain states – that is, that distinct regions of the prefontal cortex are required for this fluctuating visual awareness, depending on the state of the whole brain. Such causal link cannot be observed if brain activity is not tracked closely. To investigate this, the brain states of 65 participants were recorded as individuals were experiencing the optical illusions; the activity of their various brain regions could therefore be mapped, and then areas of the prefrontal cortex could precisely be inhibited at the right time using transcranial magnetic stimulation. This revealed that, indeed, prefrontal cortex regions were necessary for bistable visual perception, but not in a simple way. Instead, which ones were required and when depended on activity dynamics taking place in the whole brain. Overall, these results indicate that monitoring brain states is necessary to better understand – and ultimately, control – the neural pathways underlying perception and behaviour.
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Affiliation(s)
- Takamitsu Watanabe
- International Research Centre for Neurointelligence, The University of Tokyo Institutes for Advanced Study, Tokyo, Japan.,RIKEN Centre for Brain Science, Saitama, Japan
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34
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Metsomaa J, Belardinelli P, Ermolova M, Ziemann U, Zrenner C. Causal decoding of individual cortical excitability states. Neuroimage 2021; 245:118652. [PMID: 34687858 DOI: 10.1016/j.neuroimage.2021.118652] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 09/30/2021] [Accepted: 10/11/2021] [Indexed: 10/20/2022] Open
Abstract
Brain responsiveness to stimulation fluctuates with rapidly shifting cortical excitability state, as reflected by oscillations in the electroencephalogram (EEG). For example, the amplitude of motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) of motor cortex changes from trial to trial. To date, individual estimation of the cortical processes leading to this excitability fluctuation has not been possible. Here, we propose a data-driven method to derive individually optimized EEG classifiers in healthy humans using a supervised learning approach that relates pre-TMS EEG activity dynamics to MEP amplitude. Our approach enables considering multiple brain regions and frequency bands, without defining them a priori, whose compound phase-pattern information determines the excitability. The individualized classifier leads to an increased classification accuracy of cortical excitability states from 57% to 67% when compared to μ-oscillation phase extracted by standard fixed spatial filters. Results show that, for the used TMS protocol, excitability fluctuates predominantly in the μ-oscillation range, and relevant cortical areas cluster around the stimulated motor cortex, but between subjects there is variability in relevant power spectra, phases, and cortical regions. This novel decoding method allows causal investigation of the cortical excitability state, which is critical also for individualizing therapeutic brain stimulation.
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Affiliation(s)
- J Metsomaa
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen
| | - P Belardinelli
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen; CIMeC, Center for Mind-Brain Sciences, University of Trento, Italy
| | - M Ermolova
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen
| | - U Ziemann
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen.
| | - C Zrenner
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen; Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, and Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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35
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Geffen A, Bland N, Sale MV. Effects of Slow Oscillatory Transcranial Alternating Current Stimulation on Motor Cortical Excitability Assessed by Transcranial Magnetic Stimulation. Front Hum Neurosci 2021; 15:726604. [PMID: 34588969 PMCID: PMC8473706 DOI: 10.3389/fnhum.2021.726604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 08/24/2021] [Indexed: 11/13/2022] Open
Abstract
Converging evidence suggests that transcranial alternating current stimulation (tACS) may entrain endogenous neural oscillations to match the frequency and phase of the exogenously applied current and this entrainment may outlast the stimulation (although only for a few oscillatory cycles following the cessation of stimulation). However, observing entrainment in the electroencephalograph (EEG) during stimulation is extremely difficult due to the presence of complex tACS artifacts. The present study assessed entrainment to slow oscillatory (SO) tACS by measuring motor cortical excitability across different oscillatory phases during (i.e., online) and outlasting (i.e., offline) stimulation. 30 healthy participants received 60 trials of intermittent SO tACS (0.75 Hz; 16 s on/off interleaved) at an intensity of 2 mA peak-to-peak. Motor cortical excitability was assessed using transcranial magnetic stimulation (TMS) of the hand region of the primary motor cortex (M1HAND) to induce motor evoked potentials (MEPs) in the contralateral thumb. MEPs were acquired at four time-points within each trial – early online, late online, early offline, and late offline – as well as at the start and end of the overall stimulation period (to probe longer-lasting aftereffects of tACS). A significant increase in MEP amplitude was observed from pre- to post-tACS (paired-sample t-test; t29 = 2.64, P = 0.013, d = 0.48) and from the first to the last tACS block (t29 = −2.93, P = 0.02, d = 0.54). However, no phase-dependent modulation of excitability was observed. Therefore, although SO tACS had a facilitatory effect on motor cortical excitability that outlasted stimulation, there was no evidence supporting entrainment of endogenous oscillations as the underlying mechanism.
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Affiliation(s)
- Asher Geffen
- School of Health and Rehabilitation Sciences, The University of Queensland, St Lucia, QLD, Australia
| | - Nicholas Bland
- School of Health and Rehabilitation Sciences, The University of Queensland, St Lucia, QLD, Australia.,Queensland Brain Institute, The University of Queensland, St Lucia, QLD, Australia.,School of Human Movement and Nutrition Sciences, The University of Queensland, St Lucia, QLD, Australia
| | - Martin V Sale
- School of Health and Rehabilitation Sciences, The University of Queensland, St Lucia, QLD, Australia.,Queensland Brain Institute, The University of Queensland, St Lucia, QLD, Australia
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36
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Schilberg L, Ten Oever S, Schuhmann T, Sack AT. Phase and power modulations on the amplitude of TMS-induced motor evoked potentials. PLoS One 2021; 16:e0255815. [PMID: 34529682 PMCID: PMC8445484 DOI: 10.1371/journal.pone.0255815] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 07/23/2021] [Indexed: 11/30/2022] Open
Abstract
The evaluation of transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEPs) promises valuable information about fundamental brain related mechanisms and may serve as a diagnostic tool for clinical monitoring of therapeutic progress or surgery procedures. However, reports about spontaneous fluctuations of MEP amplitudes causing high intra-individual variability have led to increased concerns about the reliability of this measure. One possible cause for high variability of MEPs could be neuronal oscillatory activity, which reflects fluctuations of membrane potentials that systematically increase and decrease the excitability of neuronal networks. Here, we investigate the dependence of MEP amplitude on oscillation power and phase by combining the application of single pulse TMS over the primary motor cortex with concurrent recordings of electromyography and electroencephalography. Our results show that MEP amplitude is correlated to alpha phase, alpha power as well as beta phase. These findings may help explain corticospinal excitability fluctuations by highlighting the modulatory effect of alpha and beta phase on MEPs. In the future, controlling for such a causal relationship may allow for the development of new protocols, improve this method as a (diagnostic) tool and increase the specificity and efficacy of general TMS applications.
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Affiliation(s)
- Lukas Schilberg
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Sanne Ten Oever
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Language and Computation in Neural Systems Group, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Neuroimaging, Radboud University, Nijmegen, The Netherlands
| | - Teresa Schuhmann
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
- Faculty of Psychology and Neuroscience, Faculty of Health, Medicine and Life Sciences, Centre for Integrative Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Alexander T. Sack
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
- Faculty of Psychology and Neuroscience, Faculty of Health, Medicine and Life Sciences, Centre for Integrative Neuroscience, Maastricht University, Maastricht, The Netherlands
- School for Mental Health and Neuroscience (MHeNS), Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre, Maastricht, The Netherlands
- * E-mail:
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37
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Paradoxical facilitation alongside interhemispheric inhibition. Exp Brain Res 2021; 239:3303-3313. [PMID: 34476535 PMCID: PMC8541949 DOI: 10.1007/s00221-021-06183-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 07/20/2021] [Indexed: 11/03/2022]
Abstract
Neurophysiological experiments using transcranial magnetic stimulation (TMS) have sought to probe the function of the motor division of the corpus callosum. Primary motor cortex sends projections via the corpus callosum with a net inhibitory influence on the homologous region of the opposite hemisphere. Interhemispheric inhibition (IHI) experiments probe this inhibitory pathway. A test stimulus (TS) delivered to the motor cortex in one hemisphere elicits motor evoked potentials (MEPs) in a target muscle, while a conditioning stimulus (CS) applied to the homologous region of the opposite hemisphere modulates the effect of the TS. We predicted that large CS MEPs would be associated with increased IHI since they should be a reliable index of how effectively contralateral motor cortex was stimulated and therefore of the magnitude of interhemispheric inhibition. However, we observed a strong tendency for larger CS MEPs to be associated with reduced interhemispheric inhibition which in the extreme lead to a net effect of facilitation. This surprising effect was large, systematic, and observed in nearly all participants. We outline several hypotheses for mechanisms which may underlie this phenomenon to guide future research.
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38
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Wang Y, Bai Y, Xia X, Niu Z, Yang Y, He J, Li X. Comparison of synchrosqueezing transform to alternative methods for time-frequency analysis of TMS-evoked EEG oscillations. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102975] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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39
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Leuchter AF, Wilson AC, Vince-Cruz N, Corlier J. Novel method for identification of individualized resonant frequencies for treatment of Major Depressive Disorder (MDD) using repetitive Transcranial Magnetic Stimulation (rTMS): A proof-of-concept study. Brain Stimul 2021; 14:1373-1383. [PMID: 34425244 DOI: 10.1016/j.brs.2021.08.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 07/28/2021] [Accepted: 08/11/2021] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Repetitive Transcranial Magnetic Stimulation (rTMS) is an effective treatment for Major Depressive Disorder (MDD), but therapeutic benefit is highly variable. Clinical improvement is related to changes in brain circuits, which have preferred resonant frequencies (RFs) and vary across individuals. OBJECTIVE We developed a novel rTMS-electroencephalography (rTMS-EEG) interrogation paradigm to identify RFs using the association of power/connectivity measures with symptom severity and treatment outcome. METHODS 35 subjects underwent rTMS interrogation at 71 frequencies ranging from 3 to 17 Hz administered to left dorsolateral prefrontal cortex (DLPFC). rTMS-EEG was used to assess resonance in oscillatory power/connectivity changes (phase coherence [PC], envelope correlation [EC], and spectral correlation coefficient [SCC]) after each frequency. Multiple regression was used to detect relationships between 10 Hz resonance and baseline symptoms as well as clinical improvement after 10 sessions of 10 Hz rTMS treatment. RESULTS Baseline symptom severity was significantly associated with SCC resonance in left sensorimotor (SM; p < 0.0004), PC resonance in fronto-parietal (p = 0.001), and EC resonance in centro-posterior channels (p = 0.002). Subjects significantly improved with 10 sessions of rTMS treatment. Only decreased SCC SM resonance was significantly associated with clinical improvement (r = 0.35, p = 0.04). Subjects for whom 10 Hz SM SCC was highly ranked as an RF among all stimulation frequencies had better outcomes from 10 Hz treatment. CONCLUSIONS Resonance of 10 Hz stimulation measured using SCC correlated with both symptom severity and improvement with 10 Hz rTMS treatment. Research should determine whether this interrogation paradigm can identify individualized rTMS treatment frequencies.
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Affiliation(s)
- Andrew F Leuchter
- From the TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, And the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
| | - Andrew C Wilson
- From the TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, And the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Nikita Vince-Cruz
- From the TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, And the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Juliana Corlier
- From the TMS Clinical and Research Program, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, And the Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
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40
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Sondergaard RE, Martino D, Kiss ZHT, Condliffe EG. TMS Motor Mapping Methodology and Reliability: A Structured Review. Front Neurosci 2021; 15:709368. [PMID: 34489629 PMCID: PMC8417420 DOI: 10.3389/fnins.2021.709368] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 07/13/2021] [Indexed: 11/29/2022] Open
Abstract
Motor cortical representation can be probed non-invasively using a transcranial magnetic stimulation (TMS) technique known as motor mapping. The mapping technique can influence features of the maps because of several controllable elements. Here we review the literature on six key motor mapping parameters, as well as their influence on outcome measures and discuss factors impacting their selection. 132 of 1,587 distinct records were examined in detail and synthesized to form the basis of our review. A summary of mapping parameters, their impact on outcome measures and feasibility considerations are reported to support the design and interpretation of TMS mapping studies.
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Affiliation(s)
- Rachel E. Sondergaard
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Davide Martino
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Zelma H. T. Kiss
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Elizabeth G. Condliffe
- Department of Clinical Neuroscience, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Pediatrics, University of Calgary, Calgary, AB, Canada
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41
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Barban F, Chiappalone M, Bonassi G, Mantini D, Semprini M. Yet another artefact rejection study: an exploration of cleaning methods for biological and neuromodulatory noise. J Neural Eng 2021; 18. [PMID: 34342270 DOI: 10.1088/1741-2552/ac01fe] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 05/17/2021] [Indexed: 02/02/2023]
Abstract
Objective. Electroencephalography (EEG) cleaning has been a longstanding issue in the research community. In recent times, huge leaps have been made in the field, resulting in very promising techniques to address the issue. The most widespread ones rely on a family of mathematical methods known as blind source separation (BSS), ideally capable of separating artefactual signals from the brain originated ones. However, corruption of EEG data still remains a problem, especially in real life scenario where a mixture of artefact components affects the signal and thus correctly choosing the correct cleaning procedure can be non trivial. Our aim is here to evaluate and score the plethora of available BSS-based cleaning methods, providing an overview of their advantages and downsides and of their best field of application.Approach. To address this, we here first characterized and modeled different types of artefact, i.e. arising from muscular or blinking activity as well as from transcranial alternate current stimulation. We then tested and scored several BSS-based cleaning procedures on semi-synthetic datasets corrupted by the previously modeled noise sources. Finally, we built a lifelike dataset affected by many artefactual components. We tested an iterative multistep approach combining different BSS steps, aimed at sequentially removing each specific artefactual component.Main results. We did not find an overall best method, as different scenarios require different approaches. We therefore provided an overview of the performance in terms of both reconstruction accuracy and computational burden of each method in different use cases.Significance. Our work provides insightful guidelines for signal cleaning procedures in the EEG related field.
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Affiliation(s)
- Federico Barban
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, Italy
| | - Michela Chiappalone
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genoa, Italy
| | - Gaia Bonassi
- S.C. Medicina Fisica e Riabilitazione Ospedaliera, ASL 4, Azienda Sanitaria Locale Chiavarese, 16034 Chiavari Genoa, Italy
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, 3001 Leuven, Belgium.,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, 30126 Venice, Italy
| | - Marianna Semprini
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genoa, Italy
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Schaworonkow N, Voytek B. Enhancing oscillations in intracranial electrophysiological recordings with data-driven spatial filters. PLoS Comput Biol 2021; 17:e1009298. [PMID: 34411096 PMCID: PMC8407590 DOI: 10.1371/journal.pcbi.1009298] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 08/31/2021] [Accepted: 07/22/2021] [Indexed: 11/19/2022] Open
Abstract
In invasive electrophysiological recordings, a variety of neural oscillations can be detected across the cortex, with overlap in space and time. This overlap complicates measurement of neural oscillations using standard referencing schemes, like common average or bipolar referencing. Here, we illustrate the effects of spatial mixing on measuring neural oscillations in invasive electrophysiological recordings and demonstrate the benefits of using data-driven referencing schemes in order to improve measurement of neural oscillations. We discuss referencing as the application of a spatial filter. Spatio-spectral decomposition is used to estimate data-driven spatial filters, a computationally fast method which specifically enhances signal-to-noise ratio for oscillations in a frequency band of interest. We show that application of these data-driven spatial filters has benefits for data exploration, investigation of temporal dynamics and assessment of peak frequencies of neural oscillations. We demonstrate multiple use cases, exploring between-participant variability in presence of oscillations, spatial spread and waveform shape of different rhythms as well as narrowband noise removal with the aid of spatial filters. We find high between-participant variability in the presence of neural oscillations, a large variation in spatial spread of individual rhythms and many non-sinusoidal rhythms across the cortex. Improved measurement of cortical rhythms will yield better conditions for establishing links between cortical activity and behavior, as well as bridging scales between the invasive intracranial measurements and noninvasive macroscale scalp measurements.
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Affiliation(s)
- Natalie Schaworonkow
- Department of Cognitive Science, University of California, San Diego, California, United States of America
| | - Bradley Voytek
- Department of Cognitive Science, University of California, San Diego, California, United States of America
- Halıcıoğlu Data Science Institute, University of California, San Diego, California, United States of America
- Neurosciences Graduate Program, University of California, San Diego, California, United States of America
- Kavli Institute for Brain and Mind, University of California, San Diego, California, United States of America
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Shibuya S, Unenaka S, Shimada S, Ohki Y. Distinct modulation of mu and beta rhythm desynchronization during observation of embodied fake hand rotation. Neuropsychologia 2021; 159:107952. [PMID: 34252417 DOI: 10.1016/j.neuropsychologia.2021.107952] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 06/16/2021] [Accepted: 07/06/2021] [Indexed: 12/17/2022]
Abstract
The rubber hand illusion (RHI) is a phenomenon whereby participants recognize a fake hand as their own. Studies have examined the effects of observing fake hand movements after the RHI on brain sensorimotor activity, although results remain controversial. To address these discrepancies, we investigated the effects of observation of fake hand rotation after the RHI on sensorimotor mu (μ: 8-13 Hz) and beta (β: 15-25 Hz) rhythm event-related desynchronization (ERD) using electroencephalography (EEG). Questionnaire results and proprioceptive drift revealed that the RHI occurred in participants when their invisible hand and fake visible hand were stroked synchronously but not during asynchronous stroking. Independent component (IC) clustering from EEG data during movement observation identified three IC clusters, including the right sensorimotor, left sensorimotor, and left occipital cluster. In the right sensorimotor cluster, we observed distinct modulation of μ and β ERD during fake hand rotation. Illusory ownership over the fake hand enhanced μ ERD but inversely attenuated β ERD. Further, the extent of μ ERD correlated with proprioceptive drift, but not with questionnaire ratings, whereas the converse results were obtained for β ERD. No ownership-dependent ERD modulation was detected in the left sensorimotor cluster. Alpha (α: 8-13 Hz) rhythm ERD of the left occipital cluster was smaller in the synchronous condition than in the asynchronous condition, but α ERD was not correlated with questionnaire rating or drift. These findings suggest that observing embodied fake hand rotation induces distinct cortical processing in sensorimotor brain areas.
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Affiliation(s)
- Satoshi Shibuya
- Department of Integrative Physiology, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo, Japan.
| | - Satoshi Unenaka
- Department of Sport Education, School of Lifelong Sport, Hokusho University, 23 Bunkyodai, Ebetsu, Hokkaido, Japan
| | - Sotaro Shimada
- Department of Electronics and Bioinformatics, School of Science and Technology, Meiji University, 1-1-1 Higashi-Mita, Tama-ku, Kawasaki, Kanagawa, Japan
| | - Yukari Ohki
- Department of Integrative Physiology, Kyorin University School of Medicine, 6-20-2 Shinkawa, Mitaka, Tokyo, Japan
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44
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Mrachacz-Kersting N, Ibáñez J, Farina D. Towards a mechanistic approach for the development of non-invasive brain-computer interfaces for motor rehabilitation. J Physiol 2021; 599:2361-2374. [PMID: 33728656 DOI: 10.1113/jp281314] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Accepted: 03/05/2021] [Indexed: 12/11/2022] Open
Abstract
Brain-computer interfaces (BCIs) designed for motor rehabilitation use brain signals associated with motor-processing states to guide neuroplastic changes in a state-dependent manner. These technologies are uniquely positioned to induce targeted and functionally relevant plastic changes in the human motor nervous system. However, while several studies have shown that BCI-based neuromodulation interventions may improve motor function in patients with lesions in the central nervous system, the neurophysiological structures and processes targeted with the BCI interventions have not been identified. In this review, we first summarize current knowledge of the changes in the central nervous system associated with learning new motor skills. Then, we propose a classification of current BCI paradigms for plasticity induction and motor rehabilitation based on the expected neural plastic changes promoted. This classification proposes four paradigms based on two criteria: the plasticity induction methods and the brain states targeted. The existing evidence regarding the brain circuits and processes targeted with these different BCIs is discussed in detail. The proposed classification aims to serve as a starting point for future studies trying to elucidate the underlying plastic changes following BCI interventions.
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Affiliation(s)
| | - Jaime Ibáñez
- Department of Bioengineering, Centre for Neurotechnologies, Imperial College London, London, UK
- Department of Clinical and Movement Neuroscience, Institute of Neurology, University College London, London, UK
| | - Dario Farina
- Department of Bioengineering, Centre for Neurotechnologies, Imperial College London, London, UK
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45
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Does pericentral mu-rhythm "power" corticomotor excitability? - A matter of EEG perspective. Brain Stimul 2021; 14:713-722. [PMID: 33848678 DOI: 10.1016/j.brs.2021.03.017] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 03/01/2021] [Accepted: 03/25/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Electroencephalography (EEG) and single-pulse transcranial magnetic stimulation (spTMS) of the primary motor hand area (M1-HAND) have been combined to explore whether the instantaneous expression of pericentral mu-rhythm drives fluctuations in corticomotor excitability, but this line of research has yielded diverging results. OBJECTIVES To re-assess the relationship between the mu-rhythm power expressed in left pericentral cortex and the amplitude of motor potentials (MEP) evoked with spTMS in left M1-HAND. METHODS 15 non-preselected healthy young participants received spTMS to the motor hot spot of left M1-HAND. Regional expression of mu-rhythm was estimated online based on a radial source at motor hotspot and informed the timing of spTMS which was applied either during epochs belonging to the highest or lowest quartile of regionally expressed mu-power. Using MEP amplitude as dependent variable, we computed a linear mixed-effects model, which included mu-power and mu-phase at the time of stimulation and the inter-stimulus interval (ISI) as fixed effects and subject as a random effect. Mu-phase was estimated by post-hoc sorting of trials into four discrete phase bins. We performed a follow-up analysis on the same EEG-triggered MEP data set in which we isolated mu-power at the sensor level using a Laplacian montage centered on the electrode above the M1-HAND. RESULTS Pericentral mu-power traced as radial source at motor hot spot did not significantly modulate the MEP, but mu-power determined by the surface Laplacian did, showing a positive relation between mu-power and MEP amplitude. In neither case, there was an effect of mu-phase on MEP amplitude. CONCLUSION The relationship between cortical oscillatory activity and cortical excitability is complex and minor differences in the methodological choices may critically affect sensitivity.
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46
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Engelhardt M, Komnenić D, Roth F, Kawelke L, Finke C, Picht T. No Impact of Functional Connectivity of the Motor System on the Resting Motor Threshold: A Replication Study. Front Neurosci 2021; 15:627445. [PMID: 33867916 PMCID: PMC8044353 DOI: 10.3389/fnins.2021.627445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 02/26/2021] [Indexed: 11/29/2022] Open
Abstract
The physiological mechanisms of corticospinal excitability and factors influencing its measurement with transcranial magnetic stimulation are still poorly understood. A recent study reported an impact of functional connectivity (FC) between the primary motor cortex (M1) and the dorsal premotor cortex (PMd) on the resting motor threshold (RMT) of the dominant hemisphere. We aimed to replicate these findings in a larger sample of 38 healthy right-handed subjects with data from both hemispheres. Resting-state FC was assessed between the M1 and five a priori defined motor-relevant regions on each hemisphere as well as interhemispherically between both primary motor cortices. Following the procedure by the original authors, we included age, cortical gray matter volume, and coil-to-cortex distance (CCD) as further predictors in the analysis. We report replication models for the dominant hemisphere as well as an extension to data from both hemispheres and support the results with Bayes factors. FC between the M1 and the PMd did not explain the variability in the RMT, and we obtained moderate evidence for the absence of this effect. In contrast, CCD could be confirmed as an important predictor with strong evidence. These findings contradict the previously proposed effect, thus questioning the notion of the PMd playing a major role in modifying corticospinal excitability.
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Affiliation(s)
- Melina Engelhardt
- Charité – Universitätsmedizin Berlin, Department of Neurosurgery, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences, Berlin, Germany
| | - Darko Komnenić
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Fabia Roth
- Charité – Universitätsmedizin Berlin, Department of Neurosurgery, Berlin, Germany
| | - Leona Kawelke
- Charité – Universitätsmedizin Berlin, Department of Neurosurgery, Berlin, Germany
| | - Carsten Finke
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Department of Neurology, Berlin, Germany
| | - Thomas Picht
- Charité – Universitätsmedizin Berlin, Department of Neurosurgery, Berlin, Germany
- Charité – Universitätsmedizin Berlin, Einstein Center for Neurosciences, Berlin, Germany
- Cluster of Excellence Matters of Activity, Image Space Material, Humboldt-Universität zu Berlin, Berlin, Germany
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47
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Saha S, Mamun KA, Ahmed K, Mostafa R, Naik GR, Darvishi S, Khandoker AH, Baumert M. Progress in Brain Computer Interface: Challenges and Opportunities. Front Syst Neurosci 2021; 15:578875. [PMID: 33716680 PMCID: PMC7947348 DOI: 10.3389/fnsys.2021.578875] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 01/06/2021] [Indexed: 12/13/2022] Open
Abstract
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
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Affiliation(s)
- Simanto Saha
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Khondaker A. Mamun
- Advanced Intelligent Multidisciplinary Systems (AIMS) Lab, Department of Computer Science and Engineering, United International University, Dhaka, Bangladesh
| | - Khawza Ahmed
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Raqibul Mostafa
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Ganesh R. Naik
- Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - Sam Darvishi
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
| | - Ahsan H. Khandoker
- Healthcare Engineering Innovation Center, Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Mathias Baumert
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
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48
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Vallence AM, Dansie K, Goldsworthy MR, McAllister SM, Yang R, Rothwell JC, Ridding MC. Examining motor evoked potential amplitude and short-interval intracortical inhibition on the up-going and down-going phases of a transcranial alternating current stimulation (tacs) imposed alpha oscillation. Eur J Neurosci 2021; 53:2755-2762. [PMID: 33480046 DOI: 10.1111/ejn.15124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 12/19/2020] [Accepted: 01/17/2021] [Indexed: 01/18/2023]
Abstract
Many brain regions exhibit rhythmical activity thought to reflect the summed behaviour of large populations of neurons. The endogenous alpha rhythm has been associated with phase-dependent modulation of corticospinal excitability. However, whether exogenous alpha rhythm, induced using transcranial alternating current stimulation (tACS) also has a phase-dependent effect on corticospinal excitability remains unknown. Here, we triggered transcranial magnetic stimuli (TMS) on the up- or down-going phase of a tACS-imposed alpha oscillation and measured motor evoked potential (MEP) amplitude and short-interval intracortical inhibition (SICI). There was no significant difference in MEP amplitude or SICI when TMS was triggered on the up- or down-going phase of the tACS-imposed alpha oscillation. The current study provides no evidence of differences in corticospinal excitability or GABAergic inhibition when targeting the up-going (peak) and down-going (trough) phase of the tACS-imposed oscillation.
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Affiliation(s)
- Ann-Maree Vallence
- Discipline of Psychology, College of Science, Health, Engineering, and Education, Murdoch University, Perth, Australia
| | - Kathryn Dansie
- Australia and New Zealand Dialysis and Transplant Registry (ANZDATA), South Australian Health and Medical Research Institute (SAHMIR), Adelaide, South, Australia
| | - Mitchell R Goldsworthy
- Adelaide Medical School, University of Adelaide, Adelaide, Australia.,Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, Australia
| | - Suzanne M McAllister
- Formerly of the Discipline of Physiology, School of Medical Science, University of Adelaide, Adelaide, Australia
| | | | - John C Rothwell
- Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, UK
| | - Michael C Ridding
- University of South Australia, IIMPACT in Health, Adelaide, Australia
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49
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Ahn S, Fröhlich F. Pinging the brain with transcranial magnetic stimulation reveals cortical reactivity in time and space. Brain Stimul 2021; 14:304-315. [PMID: 33516859 DOI: 10.1016/j.brs.2021.01.018] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 01/19/2021] [Accepted: 01/23/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Single-pulse transcranial magnetic stimulation (TMS) elicits an evoked electroencephalography (EEG) potential (TMS-evoked potential, TEP), which is interpreted as direct evidence of cortical reactivity to TMS. Thus, combining TMS with EEG can be used to investigate the mechanism underlying brain network engagement in TMS treatment paradigms. However, controversy remains regarding whether TEP is a genuine marker of TMS-induced cortical reactivity or if it is confounded by responses to peripheral somatosensory and auditory inputs. Resolving this controversy is of great significance for the field and will validate TMS as a tool to probe networks of interest in cognitive and clinical neuroscience. OBJECTIVE Here, we delineated the cortical origin of TEP by spatially and temporally localizing successive TEP components, and modulating them with transcranial direct current stimulation (tDCS) to investigate cortical reactivity elicited by single-pulse TMS and its causal relationship with cortical excitability. METHODS We recruited 18 healthy participants in a double-blind, cross-over, sham-controlled design. We collected motor-evoked potentials (MEPs) and TEPs elicited by suprathreshold single-pulse TMS targeting the left primary motor cortex (M1). To causally test cortical and corticospinal excitability, we applied tDCS to the left M1. RESULTS We found that the earliest TEP component (P25) was localized to the left M1. The following TEP components (N45 and P60) were largely localized to the primary somatosensory cortex, which may reflect afferent input by hand-muscle twitches. The later TEP components (N100, P180, and N280) were largely localized to the auditory cortex. As hypothesized, tDCS selectively modulated cortical and corticospinal excitability by modulating the pre-stimulus mu-rhythm oscillatory power. CONCLUSION Together, our findings provide causal evidence that the early TEP components reflect cortical reactivity to TMS.
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Affiliation(s)
- Sangtae Ahn
- School of Electronics Engineering, Kyungpook National University, Daegu, 41566, South Korea; School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, 41566, South Korea; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Flavio Fröhlich
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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50
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Zhang W, Song A, Zeng H, Xu B, Miao M. Closed-Loop Phase-Dependent Vibration Stimulation Improves Motor Imagery-Based Brain-Computer Interface Performance. Front Neurosci 2021; 15:638638. [PMID: 33568973 PMCID: PMC7868341 DOI: 10.3389/fnins.2021.638638] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/06/2021] [Indexed: 11/13/2022] Open
Abstract
The motor imagery (MI) paradigm has been wildly used in brain-computer interface (BCI), but the difficulties in performing imagery tasks limit its application. Mechanical vibration stimulus has been increasingly used to enhance the MI performance, but its improvement consistence is still under debate. To develop more effective vibration stimulus methods for consistently enhancing MI, this study proposes an EEG phase-dependent closed-loop mechanical vibration stimulation method. The subject's index finger of the non-dominant hand was given 4 different vibration stimulation conditions (i.e., continuous open-loop vibration stimulus, two different phase-dependent closed-loop vibration stimuli and no stimulus) when performing two tasks of imagining movement and rest of the index finger from his/her dominant hand. We compared MI performance and brain oscillatory patterns under different conditions to verify the effectiveness of this method. The subjects performed 80 trials of each type in a random order, and the average phase-lock value of closed-loop stimulus conditions was 0.71. It was found that the closed-loop vibration stimulus applied in the falling phase helped the subjects to produce stronger event-related desynchronization (ERD) and sustain longer. Moreover, the classification accuracy was improved by about 9% compared with MI without any vibration stimulation (p = 0.012, paired t-test). This method helps to modulate the mu rhythm and make subjects more concentrated on the imagery and without negative enhancement during rest tasks, ultimately improves MI-based BCI performance. Participants reported that the tactile fatigue under closed-loop stimulation conditions was significantly less than continuous stimulation. This novel method is an improvement to the traditional vibration stimulation enhancement research and helps to make stimulation more precise and efficient.
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Affiliation(s)
- Wenbin Zhang
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Aiguo Song
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Hong Zeng
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Baoguo Xu
- The State Key Laboratory of Bioelectronics, School of Instrument Science and Engineering, Southeast University, Nanjing, China
| | - Minmin Miao
- School of Information Engineering, Huzhou University, Huzhou, China
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