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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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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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Momi D, Wang Z, Griffiths JD. TMS-evoked responses are driven by recurrent large-scale network dynamics. eLife 2023; 12:83232. [PMID: 37083491 PMCID: PMC10121222 DOI: 10.7554/elife.83232] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 04/03/2023] [Indexed: 04/22/2023] Open
Abstract
A compelling way to disentangle the complexity of the brain is to measure the effects of spatially and temporally synchronized systematic perturbations. In humans, this can be non-invasively achieved by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Spatiotemporally complex and long-lasting TMS-EEG evoked potential (TEP) waveforms are believed to result from recurrent, re-entrant activity that propagates broadly across multiple cortical and subcortical regions, dispersing from and later re-converging on, the primary stimulation site. However, if we loosely understand the TEP of a TMS-stimulated region as the impulse response function of a noisy underdamped harmonic oscillator, then multiple later activity components (waveform peaks) should be expected even for an isolated network node in the complete absence of recurrent inputs. Thus emerges a critically important question for basic and clinical research on human brain dynamics: what parts of the TEP are due to purely local dynamics, what parts are due to reverberant, re-entrant network activity, and how can we distinguish between the two? To disentangle this, we used source-localized TMS-EEG analyses and whole-brain connectome-based computational modelling. Results indicated that recurrent network feedback begins to drive TEP responses from 100 ms post-stimulation, with earlier TEP components being attributable to local reverberatory activity within the stimulated region. Subject-specific estimation of neurophysiological parameters additionally indicated an important role for inhibitory GABAergic neural populations in scaling cortical excitability levels, as reflected in TEP waveform characteristics. The novel discoveries and new software technologies introduced here should be of broad utility in basic and clinical neuroscience research.
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Affiliation(s)
- Davide Momi
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, Canada
| | - Zheng Wang
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, Canada
| | - John D Griffiths
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Canada
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Bigoni C, Cadic-Melchior A, Morishita T, Hummel FC. Optimization of phase prediction for brain-state dependent stimulation: a grid-search approach. J Neural Eng 2023; 20. [PMID: 36626830 DOI: 10.1088/1741-2552/acb1d8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/10/2023] [Indexed: 01/11/2023]
Abstract
Objective.Sources of heterogeneity in non-invasive brain stimulation literature can be numerous, with underlying brain states and protocol differences at the top of the list. Yet, incoherent results from brain-state-dependent stimulation experiments suggest that there are further factors adding to the variance. Hypothesizing that different signal processing pipelines might be partly responsible for heterogeneity; we investigated their effects on brain-state forecasting approaches.Approach.A grid-search was used to determine the fastest and most-accurate combination of preprocessing parameters and phase-forecasting algorithms. The grid-search was applied on a synthetic dataset and validated on electroencephalographic (EEG) data from a healthy (n= 18) and stroke (n= 31) cohort.Main results.Differences in processing pipelines led to different results; the grid-search chosen pipelines significantly increased the accuracy of published forecasting methods. The accuracy achieved in healthy was comparably high in stroke patients.Significance.This systematic offline analysis highlights the importance of the specific EEG processing and forecasting pipelines used for online state-dependent setups where precision in phase prediction is critical. Moreover, successful results in the stroke cohort pave the way to test state-dependent interventional treatment approaches.
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Affiliation(s)
- Claudia Bigoni
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, 1951 Sion, Switzerland
| | - Andéol Cadic-Melchior
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, 1951 Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, 1951 Sion, Switzerland
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1202 Geneva, Switzerland.,Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), Ecole Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, 1951 Sion, Switzerland.,Clinical Neuroscience, University of Geneva Medical School, 1202 Geneva, Switzerland
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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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Caulfield KA, Brown JC. The Problem and Potential of TMS' Infinite Parameter Space: A Targeted Review and Road Map Forward. Front Psychiatry 2022; 13:867091. [PMID: 35619619 PMCID: PMC9127062 DOI: 10.3389/fpsyt.2022.867091] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/21/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive, effective, and FDA-approved brain stimulation method. However, rTMS parameter selection remains largely unexplored, with great potential for optimization. In this review, we highlight key studies underlying next generation rTMS therapies, particularly focusing on: (1) rTMS Parameters, (2) rTMS Target Engagement, (3) rTMS Interactions with Endogenous Brain Activity, and (4) Heritable Predisposition to Brain Stimulation Treatments. METHODS We performed a targeted review of pre-clinical and clinical rTMS studies. RESULTS Current evidence suggests that rTMS pattern, intensity, frequency, train duration, intertrain interval, intersession interval, pulse and session number, pulse width, and pulse shape can alter motor excitability, long term potentiation (LTP)-like facilitation, and clinical antidepressant response. Additionally, an emerging theme is how endogenous brain state impacts rTMS response. Researchers have used resting state functional magnetic resonance imaging (rsfMRI) analyses to identify personalized rTMS targets. Electroencephalography (EEG) may measure endogenous alpha rhythms that preferentially respond to personalized stimulation frequencies, or in closed-loop EEG, may be synchronized with endogenous oscillations and even phase to optimize response. Lastly, neuroimaging and genotyping have identified individual predispositions that may underlie rTMS efficacy. CONCLUSIONS We envision next generation rTMS will be delivered using optimized stimulation parameters to rsfMRI-determined targets at intensities determined by energy delivered to the cortex, and frequency personalized and synchronized to endogenous alpha-rhythms. Further research is needed to define the dose-response curve of each parameter on plasticity and clinical response at the group level, to determine how these parameters interact, and to ultimately personalize these parameters.
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Affiliation(s)
- Kevin A Caulfield
- Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States
| | - Joshua C Brown
- Departments of Psychiatry and Neurology, Brown University Medical School, Providence, RI, United States
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