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Ekhtiari H, Ghobadi-Azbari P, Thielscher A, Antal A, Li LM, Shereen AD, Cabral-Calderin Y, Keeser D, Bergmann TO, Jamil A, Violante IR, Almeida J, Meinzer M, Siebner HR, Woods AJ, Stagg CJ, Abend R, Antonenko D, Auer T, Bächinger M, Baeken C, Barron HC, Chase HW, Crinion J, Datta A, Davis MH, Ebrahimi M, Esmaeilpour Z, Falcone B, Fiori V, Ghodratitoostani I, Gilam G, Grabner RH, Greenspan JD, Groen G, Hartwigsen G, Hauser TU, Herrmann CS, Juan CH, Krekelberg B, Lefebvre S, Liew SL, Madsen KH, Mahdavifar-Khayati R, Malmir N, Marangolo P, Martin AK, Meeker TJ, Ardabili HM, Moisa M, Momi D, Mulyana B, Opitz A, Orlov N, Ragert P, Ruff CC, Ruffini G, Ruttorf M, Sangchooli A, Schellhorn K, Schlaug G, Sehm B, Soleimani G, Tavakoli H, Thompson B, Timmann D, Tsuchiyagaito A, Ulrich M, Vosskuhl J, Weinrich CA, Zare-Bidoky M, Zhang X, Zoefel B, Nitsche MA, Bikson M. A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement. Nat Protoc 2022; 17:596-617. [PMID: 35121855 PMCID: PMC7612687 DOI: 10.1038/s41596-021-00664-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 11/12/2021] [Indexed: 11/09/2022]
Abstract
Low-intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation, applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional MRI (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability. Despite the growing number of published reports, there are no consensus-based checklists for disclosing methodological details of concurrent tES-fMRI studies. The objective of this work was to develop a consensus-based checklist of reporting standards for concurrent tES-fMRI studies to support methodological rigor, transparency and reproducibility (ContES checklist). A two-phase Delphi consensus process was conducted by a steering committee (SC) of 13 members and 49 expert panelists through the International Network of the tES-fMRI Consortium. The process began with a circulation of a preliminary checklist of essential items and additional recommendations, developed by the SC on the basis of a systematic review of 57 concurrent tES-fMRI studies. Contributors were then invited to suggest revisions or additions to the initial checklist. After the revision phase, contributors rated the importance of the 17 essential items and 42 additional recommendations in the final checklist. The state of methodological transparency within the 57 reviewed concurrent tES-fMRI studies was then assessed by using the checklist. Experts refined the checklist through the revision and rating phases, leading to a checklist with three categories of essential items and additional recommendations: (i) technological factors, (ii) safety and noise tests and (iii) methodological factors. The level of reporting of checklist items varied among the 57 concurrent tES-fMRI papers, ranging from 24% to 76%. On average, 53% of checklist items were reported in a given article. In conclusion, use of the ContES checklist is expected to enhance the methodological reporting quality of future concurrent tES-fMRI studies and increase methodological transparency and reproducibility.
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Affiliation(s)
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Andrea Antal
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Lucia M Li
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
- UK DRI Centre for Care Research and Technology, Imperial College London, London, UK
| | - A Duke Shereen
- Advanced Science Research Center, The Graduate Center, City University of New York, New York, NY, USA
| | - Yuranny Cabral-Calderin
- Research Group Neural and Environmental Rhythms, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Munich, Germany
- Department of Radiology, University Hospital LMU Munich, Munich, Germany
- NeuroImaging Core Unit Munich (NICUM), University Hospital LMU Munich, Munich, Germany
| | - Til Ole Bergmann
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
- Department of Neurology and Stroke and Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Asif Jamil
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Jorge Almeida
- Proaction Lab, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
- CINEICC, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Marcus Meinzer
- Centre for Clinical Research (UQCCR), The University of Queensland, Brisbane, Queensland, Australia
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Neurology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, UK
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Rany Abend
- Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, MD, USA
| | - Daria Antonenko
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Tibor Auer
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Marc Bächinger
- Neural Control of Movement Lab, Department of Health Sciences and Technology, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Chris Baeken
- Department of Psychiatry and Medical Psychology, University Hospital Ghent, Ghent, Belgium
- Department of Psychiatry, Vrije Universiteit Brussel, University Hospital Brussels, Brussels, Belgium
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Helen C Barron
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, UK
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jenny Crinion
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Abhishek Datta
- Research and Development, Soterix Medical, New York, USA
- The City College of the City University of New York, New York, USA
| | - Matthew H Davis
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Mohsen Ebrahimi
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY, USA
| | - Brian Falcone
- Northrop Grumman Company, Mission Systems, Falls Church, VA, USA
| | - Valentina Fiori
- Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Iman Ghodratitoostani
- Neurocognitive Engineering Laboratory (NEL), Center for Engineering Applied to Health, Institute of Mathematics and Computer Science (ICMC), University of Sao Paulo, Sao Paulo, Brazil
| | - Gadi Gilam
- Systems Neuroscience and Pain Laboratory, Division of Pain Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine, School of Medicine, Stanford University, Palo Alto, CA, USA
- The Institute of Biomedical and Oral Research, Faculty of Dental Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Roland H Grabner
- Educational Neuroscience, Institute of Psychology, University of Graz, Graz, Austria
| | - Joel D Greenspan
- Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore, MD, USA
| | - Georg Groen
- Department of Psychiatry, University of Ulm, Ulm, Germany
| | - Gesa Hartwigsen
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias U Hauser
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Christoph S Herrmann
- Experimental Psychology Lab, Cluster of Excellence "Hearing4all", European Medical School, University of Oldenburg, Oldenburg, Germany
- Neuroimaging Unit, European Medical School, University of Oldenburg, Oldenburg, Germany
- Research Centre Neurosensory Science, University of Oldenburg, Oldenburg, Germany
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
| | - Bart Krekelberg
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA
| | - Stephanie Lefebvre
- Translational Research Centre, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Sook-Lei Liew
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
- Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA
| | - Kristoffer H Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, K, Lyngby, Denmark
| | | | - Nastaran Malmir
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Paola Marangolo
- Department of Humanities Studies, University Federico II, Naples, Italy
- Aphasia Research Lab, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Andrew K Martin
- Centre for Clinical Research (UQCCR), The University of Queensland, Brisbane, Queensland, Australia
- Department of Psychology, University of Kent, Canterbury, UK
| | - Timothy J Meeker
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - Hossein Mohaddes Ardabili
- Psychiatry and Behavioral Sciences Research Center, Ibn-e-Sina Hospital, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Marius Moisa
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Davide Momi
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Natasza Orlov
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Department of Psychology, Jagiellonian University, Cracow, Poland
| | - Patrick Ragert
- Institute for General Kinesiology and Exercise Science, University of Leipzig, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christian C Ruff
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Giulio Ruffini
- Neuroelectrics Corporation, Cambridge, Cambridge, MA, USA
- Neuroelectrics Corporation, Barcelona, Barcelona, Spain
| | - Michaela Ruttorf
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arshiya Sangchooli
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | | | - Gottfried Schlaug
- Neuroimaging-Neuromodulation and Stroke Recovery Laboratories, Department of Neurology, Baystate-University of Massachusetts Medical School, and Department of Biomedical Engineering, Institute of Applied Life Sciences, University of Massachusetts, Amherst, MA, USA
| | - Bernhard Sehm
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Ghazaleh Soleimani
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Hosna Tavakoli
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Department of Cognitive Neuroscience, Institute for Cognitive Sciences Studies, Tehran, Iran
| | - Benjamin Thompson
- School of Optometry and Vision Science, University of Auckland, Auckland, New Zealand
- School of Optometry and Vision Science, University of Waterloo, Waterloo, Ontario, Canada
- Centre for Eye and Vision Research, Hong Kong, Hong Kong
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | | | - Martin Ulrich
- Department of Psychiatry, University of Ulm, Ulm, Germany
| | - Johannes Vosskuhl
- Experimental Psychology Lab, Cluster of Excellence "Hearing4all", European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Christiane A Weinrich
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
- Department of Cognitive Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Mehran Zare-Bidoky
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Shahid-Sadoughi University of Medical Sciences, Yazd, Iran
| | - Xiaochu Zhang
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, China
| | - Benedikt Zoefel
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Centre de Recherche Cerveau et Cognition (CerCo), CNRS, Toulouse, France
- Université Toulouse III Paul Sabatier, Toulouse, France
| | - Michael A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
- Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY, USA
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Kreisberg E, Esmaeilpour Z, Adair D, Khadka N, Datta A, Badran BW, Bremner JD, Bikson M. High-resolution computational modeling of the current flow in the outer ear during transcutaneous auricular Vagus Nerve Stimulation (taVNS). Brain Stimul 2021; 14:1419-1430. [PMID: 34517143 PMCID: PMC8608747 DOI: 10.1016/j.brs.2021.09.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 09/07/2021] [Accepted: 09/09/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Transcutaneous auricular Vagus Nerve Stimulation (taVNS) applies low-intensity electrical current to the ear with the intention of activating the auricular branch of the Vagus nerve. The sensitivity and selectivity of stimulation applied to the ear depends on current flow pattern produced by a given electrode montage (size and placement). OBJECTIVE We compare different electrodes designs for taVNS considering both the predicted peak electric fields (sensitivity) and their spatial distribution (selectivity). METHODS Based on optimized high-resolution (0.47 mm) T1 and T2 weighted MRI, we developed an anatomical model of the left ear and the surrounding head tissues including brain, CSF/meninges, skull, muscle, blood vessels, fat, cartilage, and skin. The ear was further segmented into 6 regions of interest (ROI) based on various nerve densities: cavum concha, cymba concha, crus of helix, tragus, antitragus, and earlobe. A range of taVNS electrode montages were reproduced spanning varied electrodes sizes and placements over the tragus, cymba concha, earlobe, cavum concha, and crus of helix. Electric field across the ear (from superficial skin to cartilage) for each montage at 1 mA or 2 mA taVNS, assuming an activation threshold of 6.15 V/m, 12.3 V/m or 24.6 V/m was predicted using a Finite element method (FEM). Finally, considering every ROI, we calculated the sensitivity and selectivity of each montage. RESULTS Current flow patterns through the ear were highly specific to the electrode montage. Electric field was maximal at the ear regions directly under the electrodes, and for a given total current, increases with decreasing electrode size. Depending on the applied current and nerves threshold, activation may also occur in the regions between multiple anterior surface electrodes. Each considered montage was selective for one or two regions of interest. For example, electrodes across the tragus restricted significant electric field to the tragus. Stimulation across the earlobe restricted significant electric field to the earlobe and the antitragus. Because of this relative selectivity, use of control ear montages in experimental studies, support testing of targeting. Relative targeting was robust across assumptions of activation threshold and tissue properties. DISCUSSION Computational models provide additional insight on how details in electrode shape and placement impact sensitivity (how much current is needed) and selectivity (spatial distribution), thereby supporting analysis of existing approaches and optimization of new devices. Our result suggest taVNS current patterns and relative target are robust across individuals, though (variance in) axon morphology was not represented.
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Affiliation(s)
- Erica Kreisberg
- Department of Biomedical Engineering, The City College of New York, New York, NY, USA
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of New York, New York, NY, USA
| | - Devin Adair
- Department of Biomedical Engineering, The City College of New York, New York, NY, USA
| | - Niranjan Khadka
- Department of Psychiatry, Division of Neuropsychiatry and Neuromodulation, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Abhishek Datta
- Research and Development, Soterix Medical, New York, USA, The City College of the City University of New York, New York, USA
| | - Bashar W Badran
- Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA
| | - J Douglas Bremner
- Departments of Psychiatry & Behavioral Sciences and Radiology, Emory University School of Medicine, And the Atlanta VA Medical Center, Decatur, Atlanta, GA, USA
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York, New York, NY, USA.
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Gebodh N, Esmaeilpour Z, Datta A, Bikson M. A large open source neuromodulation dataset of concurrent EEG, ECG, behavior, and transcranial electrical stimulation. Brain Stimul 2021. [DOI: 10.1016/j.brs.2021.10.108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Gebodh N, Esmaeilpour Z, Datta A, Bikson M. Dataset of concurrent EEG, ECG, and behavior with multiple doses of transcranial electrical stimulation. Sci Data 2021; 8:274. [PMID: 34707095 PMCID: PMC8551279 DOI: 10.1038/s41597-021-01046-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 08/25/2021] [Indexed: 01/03/2023] Open
Abstract
We present a dataset combining human-participant high-density electroencephalography (EEG) with physiological and continuous behavioral metrics during transcranial electrical stimulation (tES). Data include within participant application of nine High-Definition tES (HD-tES) types, targeting three cortical regions (frontal, motor, parietal) with three stimulation waveforms (DC, 5 Hz, 30 Hz); more than 783 total stimulation trials over 62 sessions with EEG, physiological (ECG, EOG), and continuous behavioral vigilance/alertness metrics. Experiment 1 and 2 consisted of participants performing a continuous vigilance/alertness task over three 70-minute and two 70.5-minute sessions, respectively. Demographic data were collected, as well as self-reported wellness questionnaires before and after each session. Participants received all 9 stimulation types in Experiment 1, with each session including three stimulation types, with 4 trials per type. Participants received two stimulation types in Experiment 2, with 20 trials of a given stimulation type per session. Within-participant reliability was tested by repeating select sessions. This unique dataset supports a range of hypothesis testing including interactions of tDCS/tACS location and frequency, brain-state, physiology, fatigue, and cognitive performance.
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Affiliation(s)
- Nigel Gebodh
- The Department of Biomedical Engineering, The City College of New York, The City University of New York, New York, USA.
- Soterix Medical Inc., New York, USA.
| | - Zeinab Esmaeilpour
- The Department of Biomedical Engineering, The City College of New York, The City University of New York, New York, USA
| | | | - Marom Bikson
- The Department of Biomedical Engineering, The City College of New York, The City University of New York, New York, USA
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Esmaeilpour Z, Kronberg G, Reato D, Parra LC, Bikson M. Temporal interference stimulation targets deep brain regions by modulating neural oscillations. Brain Stimul 2020; 14:55-65. [PMID: 33186778 PMCID: PMC9382891 DOI: 10.1016/j.brs.2020.11.007] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 11/06/2020] [Accepted: 11/07/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Temporal interference (TI) stimulation of the brain generates amplitude-modulated electric fields oscillating in the kHz range with the goal of non-invasive targeted deep brain stimulation. Yet, the current intensities required in human (sensitivity) to modulate deep brain activity and if superficial brain region are spared (selectivity) at these intensities remains unclear. OBJECTIVE We developed an experimentally constrained theory for TI sensitivity to kHz electric field given the attenuation by membrane low-pass filtering property, and for TI selectivity to deep structures given the distribution of modulated and unmodulated electric fields in brain. METHODS The electric field threshold to modulate carbachol-induced gamma oscillations in rat hippocampal slices was determined for unmodulated 0.05-2 kHz sine waveforms, and 5 Hz amplitude-modulated waveforms with 0.1-2 kHz carrier frequencies. The neuronal effects are replicated with a computational network model to explore the underlying mechanisms, and then coupled to a validated current-flow model of the human head. RESULTS Amplitude-modulated electric fields are stronger in deep brain regions, while unmodulated electric fields are maximal at the cortical regions. Both experiment and model confirmed the hypothesis that spatial selectivity of temporal interference stimulation depends on the phasic modulation of neural oscillations only in deep brain regions. Adaptation mechanism (e.g. GABAb) enhanced sensitivity to amplitude modulated waveform in contrast to unmodulated kHz and produced selectivity in modulating gamma oscillation (i.e. Higher gamma modulation in amplitude modulated vs unmodulated kHz stimulation). Selection of carrier frequency strongly affected sensitivity to amplitude modulation stimulation. Amplitude modulated stimulation with 100 Hz carrier frequency required ∼5 V/m (corresponding to ∼13 mA at the scalp surface), whereas, 1 kHz carrier frequency ∼60 V/m (∼160 mA) and 2 kHz carrier frequency ∼80 V/m (∼220 mA) to significantly modulate gamma oscillation. Sensitivity is increased (scalp current required decreased) for theoretical neuronal membranes with faster time constants. CONCLUSION The TI sensitivity (current required at the scalp) depends on the neuronal membrane time-constant (e.g. axons) approaching the kHz carrier frequency. TI selectivity is governed by network adaption (e.g. GABAb) that is faster than the amplitude-modulation frequency. Thus, we show neuronal and network oscillations time-constants determine the scalp current required and the selectivity achievable with TI in humans.
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Affiliation(s)
- Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA.
| | - Greg Kronberg
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Davide Reato
- Champalimaud Centre for the Unknown, Neuroscience Program, Lisbon, Portugal
| | - Lucas C Parra
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
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Esmaeilpour Z, Shereen AD, Ghobadi‐Azbari P, Datta A, Woods AJ, Ironside M, O'Shea J, Kirk U, Bikson M, Ekhtiari H. Methodology for tDCS integration with fMRI. Hum Brain Mapp 2020; 41:1950-1967. [PMID: 31872943 PMCID: PMC7267907 DOI: 10.1002/hbm.24908] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 11/09/2019] [Accepted: 12/10/2019] [Indexed: 12/28/2022] Open
Abstract
Understanding and reducing variability of response to transcranial direct current stimulation (tDCS) requires measuring what factors predetermine sensitivity to tDCS and tracking individual response to tDCS. Human trials, animal models, and computational models suggest structural traits and functional states of neural systems are the major sources of this variance. There are 118 published tDCS studies (up to October 1, 2018) that used fMRI as a proxy measure of neural activation to answer mechanistic, predictive, and localization questions about how brain activity is modulated by tDCS. FMRI can potentially contribute as: a measure of cognitive state-level variance in baseline brain activation before tDCS; inform the design of stimulation montages that aim to target functional networks during specific tasks; and act as an outcome measure of functional response to tDCS. In this systematic review, we explore methodological parameter space of tDCS integration with fMRI spanning: (a) fMRI timing relative to tDCS (pre, post, concurrent); (b) study design (parallel, crossover); (c) control condition (sham, active control); (d) number of tDCS sessions; (e) number of follow up scans; (f) stimulation dose and combination with task; (g) functional imaging sequence (BOLD, ASL, resting); and (h) additional behavioral (cognitive, clinical) or quantitative (neurophysiological, biomarker) measurements. Existing tDCS-fMRI literature shows little replication across these permutations; few studies used comparable study designs. Here, we use a representative sample study with both task and resting state fMRI before and after tDCS in a crossover design to discuss methodological confounds. We further outline how computational models of current flow should be combined with imaging data to understand sources of variability. Through the representative sample study, we demonstrate how modeling and imaging methodology can be integrated for individualized analysis. Finally, we discuss the importance of conducting tDCS-fMRI with stimulation equipment certified as safe to use inside the MR scanner, and of correcting for image artifacts caused by tDCS. tDCS-fMRI can address important questions on the functional mechanisms of tDCS action (e.g., target engagement) and has the potential to support enhancement of behavioral interventions, provided studies are designed rationally.
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Affiliation(s)
- Zeinab Esmaeilpour
- Neural Engineering Laboratory, Department of Biomedical EngineeringThe City College of the City University of New York, City College Center for Discovery and InnovationNew YorkNew York
| | - A. Duke Shereen
- Advanced Science Research Center, The Graduate CenterCity University of New YorkNew YorkNew York
| | | | | | - Adam J. Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health PsychologyUniversity of FloridaGainesvilleFlorida
| | - Maria Ironside
- Center for Depression, Anxiety and Stress Research, McLean HospitalBelmontMassachusetts
- Department of PsychiatryHarvard Medical SchoolBostonMassachusetts
| | - Jacinta O'Shea
- Nuffield Department of Clinical Neuroscience, Medical Science DivisionUniversity of OxfordOxfordEnglandUK
| | - Ulrich Kirk
- Department of PsychologyUniversity of Southern DenmarkOdenseDenmark
| | - Marom Bikson
- Neural Engineering Laboratory, Department of Biomedical EngineeringThe City College of the City University of New York, City College Center for Discovery and InnovationNew YorkNew York
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Adair D, Truong D, Esmaeilpour Z, Gebodh N, Borges H, Ho L, Bremner JD, Badran BW, Napadow V, Clark VP, Bikson M. Electrical stimulation of cranial nerves in cognition and disease. Brain Stimul 2020; 13:717-750. [PMID: 32289703 PMCID: PMC7196013 DOI: 10.1016/j.brs.2020.02.019] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 02/13/2020] [Accepted: 02/17/2020] [Indexed: 02/06/2023] Open
Abstract
The cranial nerves are the pathways through which environmental information (sensation) is directly communicated to the brain, leading to perception, and giving rise to higher cognition. Because cranial nerves determine and modulate brain function, invasive and non-invasive cranial nerve electrical stimulation methods have applications in the clinical, behavioral, and cognitive domains. Among other neuromodulation approaches such as peripheral, transcranial and deep brain stimulation, cranial nerve stimulation is unique in allowing axon pathway-specific engagement of brain circuits, including thalamo-cortical networks. In this review we amalgamate relevant knowledge of 1) cranial nerve anatomy and biophysics; 2) evidence of the modulatory effects of cranial nerves on cognition; 3) clinical and behavioral outcomes of cranial nerve stimulation; and 4) biomarkers of nerve target engagement including physiology, electroencephalography, neuroimaging, and behavioral metrics. Existing non-invasive stimulation methods cannot feasibly activate the axons of only individual cranial nerves. Even with invasive stimulation methods, selective targeting of one nerve fiber type requires nuance since each nerve is composed of functionally distinct axon-types that differentially branch and can anastomose onto other nerves. None-the-less, precisely controlling stimulation parameters can aid in affecting distinct sets of axons, thus supporting specific actions on cognition and behavior. To this end, a rubric for reproducible dose-response stimulation parameters is defined here. Given that afferent cranial nerve axons project directly to the brain, targeting structures (e.g. thalamus, cortex) that are critical nodes in higher order brain networks, potent effects on cognition are plausible. We propose an intervention design framework based on driving cranial nerve pathways in targeted brain circuits, which are in turn linked to specific higher cognitive processes. State-of-the-art current flow models that are used to explain and design cranial-nerve-activating stimulation technology require multi-scale detail that includes: gross anatomy; skull foramina and superficial tissue layers; and precise nerve morphology. Detailed simulations also predict that some non-invasive electrical or magnetic stimulation approaches that do not intend to modulate cranial nerves per se, such as transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), may also modulate activity of specific cranial nerves. Much prior cranial nerve stimulation work was conceptually limited to the production of sensory perception, with individual titration of intensity based on the level of perception and tolerability. However, disregarding sensory emulation allows consideration of temporal stimulation patterns (axon recruitment) that modulate the tone of cortical networks independent of sensory cortices, without necessarily titrating perception. For example, leveraging the role of the thalamus as a gatekeeper for information to the cerebral cortex, preventing or enhancing the passage of specific information depending on the behavioral state. We show that properly parameterized computational models at multiple scales are needed to rationally optimize neuromodulation that target sets of cranial nerves, determining which and how specific brain circuitries are modulated, which can in turn influence cognition in a designed manner.
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Affiliation(s)
- Devin Adair
- Department of Biomedical Engineering, City College of New York, New York, NY, USA
| | - Dennis Truong
- Department of Biomedical Engineering, City College of New York, New York, NY, USA
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, City College of New York, New York, NY, USA.
| | - Nigel Gebodh
- Department of Biomedical Engineering, City College of New York, New York, NY, USA
| | - Helen Borges
- Department of Biomedical Engineering, City College of New York, New York, NY, USA
| | - Libby Ho
- Department of Biomedical Engineering, City College of New York, New York, NY, USA
| | - J Douglas Bremner
- Department of Psychiatry & Behavioral Sciences and Radiology, Emory University School of Medicine, Atlanta, GA, USA; Atlanta VA Medical Center, Decatur, GA, USA
| | - Bashar W Badran
- Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Vitaly Napadow
- Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Harvard medical school, Boston, MA, USA
| | - Vincent P Clark
- Psychology Clinical Neuroscience Center, Dept. Psychology, MSC03-2220, University of New Mexico, Albuquerque, NM, 87131, USA; Department of Psychology, University of New Mexico, Albuquerque, NM, 87131, USA; The Mind Research Network of the Lovelace Biomedical Research Institute, 1101 Yale Blvd. NE, Albuquerque, NM, 87106, USA
| | - Marom Bikson
- Department of Biomedical Engineering, City College of New York, New York, NY, USA.
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Esmaeilpour Z, Kronberg G, Parra L, Bikson M. P58 Mechanisms of Temporal Interference (TI) stimulation. Clin Neurophysiol 2020. [DOI: 10.1016/j.clinph.2019.12.063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Abstract
OBJECTIVE Understanding how current reaches the brain during transcranial electrical stimulation (tES) underpins efforts to rationalize outcomes and optimize interventions. To this end, computational models of current flow relate applied dose to brain electric field. Conventional tES modeling considers distinct tissues like scalp, skull, cerebrospinal fluid (CSF), gray matter and white matter. The properties of highly conductive CSF are especially important. However, modeling the space between skull and brain as entirely CSF is not an accurate representation of anatomy. The space conventionally modeled as CSF is approximately half meninges (dura, arachnoid, and pia) with lower conductivity. However, the resolution required to describe individual meningeal layers is computationally restrictive in an MRI-derived head model. Emulating the effect of meninges through CSF conductivity modification could improve accuracy with minimal cost. APPROACH Models with meningeal layers were developed in a concentric sphere head model. Then, in a model with only CSF between skull and brain, CSF conductivity was optimized to emulate the effect of meningeal layers on cortical electric field for multiple electrode positions. This emulated conductivity was applied to MRI-derived models. MAIN RESULTS Compared to a model with conventional CSF conductivity (1.65 S m-1), emulated CSF conductivity (0.85 S m-1) produced voltage fields better correlated with intracranial recordings from epilepsy patients. SIGNIFICANCE Conventional tES models have been validated using intracranial recording. Residual errors may nonetheless impact model utility. Because CSF is so conductive to current flow, misrepresentation of the skull-brain interface as entirely CSF is not realistic for tES modeling. Updating the conventional model with a CSF conductivity emulating the effect of the meninges enhances modeling accuracy without increasing model complexity. This allows existing modeling pipelines to be leveraged with a simple conductivity change. Using 0.85 S m-1 emulated CSF conductivity is recommended as the new standard in non-invasive brain stimulation modeling.
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Affiliation(s)
- Jimmy Jiang
- Department of Biomedical Engineering, Neural Engineering Laboratory, City College of New York of the City University of New York, New York, NY 10031, United States of America. Authors contributed equally
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Morya E, Monte-Silva K, Bikson M, Esmaeilpour Z, Biazoli CE, Fonseca A, Bocci T, Farzan F, Chatterjee R, Hausdorff JM, da Silva Machado DG, Brunoni AR, Mezger E, Moscaleski LA, Pegado R, Sato JR, Caetano MS, Sá KN, Tanaka C, Li LM, Baptista AF, Okano AH. Beyond the target area: an integrative view of tDCS-induced motor cortex modulation in patients and athletes. J Neuroeng Rehabil 2019; 16:141. [PMID: 31730494 PMCID: PMC6858746 DOI: 10.1186/s12984-019-0581-1] [Citation(s) in RCA: 72] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Accepted: 08/19/2019] [Indexed: 02/07/2023] Open
Abstract
Transcranial Direct Current Stimulation (tDCS) is a non-invasive technique used to modulate neural tissue. Neuromodulation apparently improves cognitive functions in several neurologic diseases treatment and sports performance. In this study, we present a comprehensive, integrative review of tDCS for motor rehabilitation and motor learning in healthy individuals, athletes and multiple neurologic and neuropsychiatric conditions. We also report on neuromodulation mechanisms, main applications, current knowledge including areas such as language, embodied cognition, functional and social aspects, and future directions. We present the use and perspectives of new developments in tDCS technology, namely high-definition tDCS (HD-tDCS) which promises to overcome one of the main tDCS limitation (i.e., low focality) and its application for neurological disease, pain relief, and motor learning/rehabilitation. Finally, we provided information regarding the Transcutaneous Spinal Direct Current Stimulation (tsDCS) in clinical applications, Cerebellar tDCS (ctDCS) and its influence on motor learning, and TMS combined with electroencephalography (EEG) as a tool to evaluate tDCS effects on brain function.
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Affiliation(s)
- Edgard Morya
- Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaíba, Rio Grande do Norte Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
| | - Kátia Monte-Silva
- Universidade Federal de Pernambuco, Recife, Pernambuco Brazil
- Núcleo de Assistência e Pesquisa em Neuromodulação (NAPeN), Universidade Federal do ABC (UFABC)/Universidade de São Paulo (USP)/Universidade Cidade de São Paulo (UNICID)/Universidade Federal de Pernambuco (UFPE), Escola Bahiana de Medicina e Saúde Pública (EBMSP), Santo André, Brazil
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY USA
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY USA
| | - Claudinei Eduardo Biazoli
- Center of Mathematics, Computing and Cognition (CMCC), Universidade Federal do ABC (UFABC), Alameda da Universidade, 3 - Anchieta, Bloco Delta – Sala 257, São Bernardo do Campo, SP CEP 09606-070 Brazil
| | - Andre Fonseca
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
- Center of Mathematics, Computing and Cognition (CMCC), Universidade Federal do ABC (UFABC), Alameda da Universidade, 3 - Anchieta, Bloco Delta – Sala 257, São Bernardo do Campo, SP CEP 09606-070 Brazil
| | - Tommaso Bocci
- Aldo Ravelli Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Sciences, International Medical School, University of Milan, Milan, Italy
| | - Faranak Farzan
- School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, British Columbia Canada
| | - Raaj Chatterjee
- School of Mechatronic Systems Engineering, Simon Fraser University, Surrey, British Columbia Canada
| | - Jeffrey M. Hausdorff
- Department of Physical Therapy, Sackler Faculty of Medicine and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | | | | | - Eva Mezger
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Luciane Aparecida Moscaleski
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
- Center of Mathematics, Computing and Cognition (CMCC), Universidade Federal do ABC (UFABC), Alameda da Universidade, 3 - Anchieta, Bloco Delta – Sala 257, São Bernardo do Campo, SP CEP 09606-070 Brazil
| | - Rodrigo Pegado
- Graduate Program in Rehabilitation Science, Universidade Federal do Rio Grande do Norte, Santa Cruz, Rio Grande do Norte Brazil
| | - João Ricardo Sato
- Center of Mathematics, Computing and Cognition (CMCC), Universidade Federal do ABC (UFABC), Alameda da Universidade, 3 - Anchieta, Bloco Delta – Sala 257, São Bernardo do Campo, SP CEP 09606-070 Brazil
| | - Marcelo Salvador Caetano
- Center of Mathematics, Computing and Cognition (CMCC), Universidade Federal do ABC (UFABC), Alameda da Universidade, 3 - Anchieta, Bloco Delta – Sala 257, São Bernardo do Campo, SP CEP 09606-070 Brazil
| | - Kátia Nunes Sá
- Núcleo de Assistência e Pesquisa em Neuromodulação (NAPeN), Universidade Federal do ABC (UFABC)/Universidade de São Paulo (USP)/Universidade Cidade de São Paulo (UNICID)/Universidade Federal de Pernambuco (UFPE), Escola Bahiana de Medicina e Saúde Pública (EBMSP), Santo André, Brazil
- Escola Bahiana de Medicina e Saúde Pública, Salvador, Bahia Brazil
| | - Clarice Tanaka
- Núcleo de Assistência e Pesquisa em Neuromodulação (NAPeN), Universidade Federal do ABC (UFABC)/Universidade de São Paulo (USP)/Universidade Cidade de São Paulo (UNICID)/Universidade Federal de Pernambuco (UFPE), Escola Bahiana de Medicina e Saúde Pública (EBMSP), Santo André, Brazil
- Laboratório de Investigações Médicas-54, Universidade de São Paulo, São Paulo, São Paulo Brazil
| | - Li Min Li
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
| | - Abrahão Fontes Baptista
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
- Núcleo de Assistência e Pesquisa em Neuromodulação (NAPeN), Universidade Federal do ABC (UFABC)/Universidade de São Paulo (USP)/Universidade Cidade de São Paulo (UNICID)/Universidade Federal de Pernambuco (UFPE), Escola Bahiana de Medicina e Saúde Pública (EBMSP), Santo André, Brazil
- Center of Mathematics, Computing and Cognition (CMCC), Universidade Federal do ABC (UFABC), Alameda da Universidade, 3 - Anchieta, Bloco Delta – Sala 257, São Bernardo do Campo, SP CEP 09606-070 Brazil
- Escola Bahiana de Medicina e Saúde Pública, Salvador, Bahia Brazil
- Laboratório de Investigações Médicas-54, Universidade de São Paulo, São Paulo, São Paulo Brazil
| | - Alexandre Hideki Okano
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
- Núcleo de Assistência e Pesquisa em Neuromodulação (NAPeN), Universidade Federal do ABC (UFABC)/Universidade de São Paulo (USP)/Universidade Cidade de São Paulo (UNICID)/Universidade Federal de Pernambuco (UFPE), Escola Bahiana de Medicina e Saúde Pública (EBMSP), Santo André, Brazil
- Center of Mathematics, Computing and Cognition (CMCC), Universidade Federal do ABC (UFABC), Alameda da Universidade, 3 - Anchieta, Bloco Delta – Sala 257, São Bernardo do Campo, SP CEP 09606-070 Brazil
- Graduate Program in Physical Education. State University of Londrina, Londrina, Paraná, Brazil
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Bikson M, Esmaeilpour Z, Adair D, Kronberg G, Tyler WJ, Antal A, Datta A, Sabel BA, Nitsche MA, Loo C, Edwards D, Ekhtiari H, Knotkova H, Woods AJ, Hampstead BM, Badran BW, Peterchev AV. Transcranial electrical stimulation nomenclature. Brain Stimul 2019; 12:1349-1366. [PMID: 31358456 DOI: 10.1016/j.brs.2019.07.010] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 06/25/2019] [Accepted: 07/14/2019] [Indexed: 01/03/2023] Open
Abstract
Transcranial electrical stimulation (tES) aims to alter brain function non-invasively by applying current to electrodes on the scalp. Decades of research and technological advancement are associated with a growing diversity of tES methods and the associated nomenclature for describing these methods. Whether intended to produce a specific response so the brain can be studied or lead to a more enduring change in behavior (e.g. for treatment), the motivations for using tES have themselves influenced the evolution of nomenclature, leading to some scientific, clinical, and public confusion. This ambiguity arises from (i) the infinite parameter space available in designing tES methods of application and (ii) varied naming conventions based upon the intended effects and/or methods of application. Here, we compile a cohesive nomenclature for contemporary tES technologies that respects existing and historical norms, while incorporating insight and classifications based on state-of-the-art findings. We consolidate and clarify existing terminology conventions, but do not aim to create new nomenclature. The presented nomenclature aims to balance adopting broad definitions that encourage flexibility and innovation in research approaches, against classification specificity that minimizes ambiguity about protocols but can hinder progress. Constructive research around tES classification, such as transcranial direct current stimulation (tDCS), should allow some variations in protocol but also distinguish from approaches that bear so little resemblance that their safety and efficacy should not be compared directly. The proposed framework includes terms in contemporary use across peer-reviewed publications, including relatively new nomenclature introduced in the past decade, such as transcranial alternating current stimulation (tACS) and transcranial pulsed current stimulation (tPCS), as well as terms with long historical use such as electroconvulsive therapy (ECT). We also define commonly used terms-of-the-trade including electrode, lead, anode, and cathode, whose prior use, in varied contexts, can also be a source of confusion. This comprehensive clarification of nomenclature and associated preliminary proposals for standardized terminology can support the development of consensus on efficacy, safety, and regulatory standards.
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Affiliation(s)
- Marom Bikson
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA.
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA.
| | - Devin Adair
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - Greg Kronberg
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, USA
| | - William J Tyler
- Arizona State University, School of Biological and Health Systems Engineering, Tempe, AZ, USA
| | - Andrea Antal
- Department of Clinical Neurophysiology, University Medical Center Goettingen, Goettingen, Germany; Institute of Medical Psychology, Medical Faculty, Otto-v.-Guericke University of Magdeburg, Magdeburg, Germany
| | | | - Bernhard A Sabel
- Institute of Medical Psychology, Medical Faculty, Otto-v.-Guericke University of Magdeburg, Magdeburg, Germany
| | - Michael A Nitsche
- Leibniz Research Centre for Working Environment ant Human Factors, Dept. Psychology and Neurosciences, Dortmund, Germany; University Medical Hospital Bergmannsheil, Dept. Neurology, Bochum, Germany
| | - Colleen Loo
- School of Psychiatry & Black Dog Institute, University of New South Wales, Sydney, Australia
| | - Dylan Edwards
- Moss Rehabilitation Research Institute, Philadelphia, PA, USA; Edith Cowan University, Joondalup, Australia
| | | | - Helena Knotkova
- MJHS Institute for Innovation in Palliative Care, New York, NY, USA; Department of Family and Social Medicine, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Benjamin M Hampstead
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA; Neuropsychology Section, Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Bashar W Badran
- Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA
| | - Angel V Peterchev
- Department of Psychiatry & Behavioral Sciences, Department of Biomedical Engineering, Department of Electrical & Computer Engineering, Department of Neurosurgery, Duke University, Durham, NC, USA
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Meiron O, Gale R, Namestnic J, Bennet-Back O, Gebodh N, Esmaeilpour Z, Mandzhiyev V, Bikson M. Antiepileptic Effects of a Novel Non-invasive Neuromodulation Treatment in a Subject With Early-Onset Epileptic Encephalopathy: Case Report With 20 Sessions of HD-tDCS Intervention. Front Neurosci 2019; 13:547. [PMID: 31191235 PMCID: PMC6548848 DOI: 10.3389/fnins.2019.00547] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Accepted: 05/13/2019] [Indexed: 01/30/2023] Open
Abstract
The current clinical investigation examined high-definition transcranial direct current stimulation (HD-tDCS) as a focal, non-invasive, anti-epileptic treatment in a child with early-onset epileptic encephalopathy. We investigated the clinical impact of repetitive (20 daily sessions) cathode-centered 4 × 1 HD-tDCS (1 mA, 20 min, 4 mm ring radius) over the dominant seizure-generating cortical zone in a 40-month-old child suffering from a severe neonatal epileptic syndrome known as Ohtahara syndrome (OS). Seizures and epileptiform activity were monitored and quantified using video-EEG over multiple days of baseline, intervention, and post-intervention periods. Primary outcome measures were changes in seizure frequency and duration on the last day of intervention versus the last baseline day, preceding the intervention. In particular, we examined changes in tonic spasms, tonic-myoclonic seizures (TM-S), and myoclonic seizures from baseline to post-intervention. A trend in TM-S frequency was observed indicating a reduction of 73% in TM-S frequency, which was non-significant [t(4) = 2.05, p = 0.1], and denoted a clinically significant change. Myoclonic seizure (M-S) frequency was significantly reduced [t(4) = 3.83, p = 0.019] by 68.42%, compared to baseline, and indicated a significant clinical change as well. A 73% decrease in interictal epileptic discharges (IEDs) frequency was also observed immediately after the intervention period, compared to IED frequency at 3 days prior to intervention. Post-intervention seizure-related peak delta desynchronization was reduced by 57%. Our findings represent a case-specific significant clinical response, reduction in IED, and change in seizure-related delta activity following the application of HD-tDCS. The clinical outcomes, as noted in the current study, encourage the further investigation of this focal, non-invasive neuromodulation procedure in other severe electroclinical syndromes (e.g., West syndrome) and in larger pediatric populations diagnosed with early-onset epileptic encephalopathy. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT02960347, protocol ID: Meiron 2013-4.
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Affiliation(s)
- Oded Meiron
- The Clinical Research Center for Brain Sciences, Herzog Medical Center, Jerusalem, Israel
| | - Rena Gale
- Children Respiratory Unit, Herzog Medical Center, Jerusalem, Israel
| | - Julia Namestnic
- Children Respiratory Unit, Herzog Medical Center, Jerusalem, Israel
| | - Odeya Bennet-Back
- Pediatric Neurology Department, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Nigel Gebodh
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, United States
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, United States
| | - Vladislav Mandzhiyev
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, United States
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of the City University of New York, New York, NY, United States
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Gebodh N, Esmaeilpour Z, Adair D, Chelette K, Dmochowski J, Parra L, Woods AJ, Kappenman ES, Bikson M. Abstract #125: Failure Of Conventional Signal Processing Techniques To Remove “Physiological” Artifacts From EEG During tDCS. Brain Stimul 2019. [DOI: 10.1016/j.brs.2018.12.132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
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Esmaeilpour Z, Shereen AD, Bikson M, Ekhtiari H. Abstract #147: MRI Neuroimaging Methods for tDCS: A methodological note on study design and parameter space. Brain Stimul 2019. [DOI: 10.1016/j.brs.2018.12.154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Meiron O, Gale R, Namestnic J, Bennet-Back O, David J, Gebodh N, Adair D, Esmaeilpour Z, Bikson M. Abstract #123: Attenuation of Pathological EEG features in Nonatal Electroclinical Syndromes: HD-tDCS in Catastrophic Epilepsies. Brain Stimul 2019. [DOI: 10.1016/j.brs.2018.12.130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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Gebodh N, Esmaeilpour Z, Adair D, Chelette K, Dmochowski J, Woods AJ, Kappenman ES, Parra LC, Bikson M. Inherent physiological artifacts in EEG during tDCS. Neuroimage 2018; 185:408-424. [PMID: 30321643 DOI: 10.1016/j.neuroimage.2018.10.025] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 09/10/2018] [Accepted: 10/08/2018] [Indexed: 12/30/2022] Open
Abstract
Online imaging and neuromodulation is invalid if stimulation distorts measurements beyond the point of accurate measurement. In theory, combining transcranial Direct Current Stimulation (tDCS) with electroencephalography (EEG) is compelling, as both use non-invasive electrodes and image-guided dose can be informed by the reciprocity principle. To distinguish real changes in EEG from stimulation artifacts, prior studies applied conventional signal processing techniques (e.g. high-pass filtering, ICA). Here, we address the assumptions underlying the suitability of these approaches. We distinguish physiological artifacts - defined as artifacts resulting from interactions between the stimulation induced voltage and the body and so inherent regardless of tDCS or EEG hardware performance - from methodology-related artifacts - arising from non-ideal experimental conditions or non-ideal stimulation and recording equipment performance. Critically, we identify inherent physiological artifacts which are present in all online EEG-tDCS: 1) cardiac distortion and 2) ocular motor distortion. In conjunction, non-inherent physiological artifacts which can be minimized in most experimental conditions include: 1) motion and 2) myogenic distortion. Artifact dynamics were analyzed for varying stimulation parameters (montage, polarity, current) and stimulation hardware. Together with concurrent physiological monitoring (ECG, respiration, ocular, EMG, head motion), and current flow modeling, each physiological artifact was explained by biological source-specific body impedance changes, leading to incremental changes in scalp DC voltage that are significantly larger than real neural signals. Because these artifacts modulate the DC voltage and scale with applied current, they are dose specific such that their contamination cannot be accounted for by conventional experimental controls (e.g. differing stimulation montage or current as a control). Moreover, because the EEG artifacts introduced by physiologic processes during tDCS are high dimensional (as indicated by Generalized Singular Value Decomposition- GSVD), non-stationary, and overlap highly with neurogenic frequencies, these artifacts cannot be easily removed with conventional signal processing techniques. Spatial filtering techniques (GSVD) suggest that the removal of physiological artifacts would significantly degrade signal integrity. Physiological artifacts, as defined here, would emerge only during tDCS, thus processing techniques typically applied to EEG in the absence of tDCS would not be suitable for artifact removal during tDCS. All concurrent EEG-tDCS must account for physiological artifacts that are a) present regardless of equipment used, and b) broadband and confound a broad range of experiments (e.g. oscillatory activity and event related potentials). Removal of these artifacts requires the recognition of their non-stationary, physiology-specific dynamics, and individualized nature. We present a broad taxonomy of artifacts (non/stimulation related), and suggest possible approaches and challenges to denoising online EEG-tDCS stimulation artifacts.
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Affiliation(s)
- Nigel Gebodh
- Neural Engineering Laboratory, Department of Biomedical Engineering, The City College of New York of the City University of New York, New York, NY, USA.
| | - Zeinab Esmaeilpour
- Neural Engineering Laboratory, Department of Biomedical Engineering, The City College of New York of the City University of New York, New York, NY, USA.
| | - Devin Adair
- Department of Psychology, The Graduate Center at City University of New York, New York, NY, USA.
| | | | - Jacek Dmochowski
- Neural Engineering Laboratory, Department of Biomedical Engineering, The City College of New York of the City University of New York, New York, NY, USA.
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, Department of Neuroscience, University of Florida, Gainesville, FL, USA.
| | | | - Lucas C Parra
- Neural Engineering Laboratory, Department of Biomedical Engineering, The City College of New York of the City University of New York, New York, NY, USA.
| | - Marom Bikson
- Neural Engineering Laboratory, Department of Biomedical Engineering, The City College of New York of the City University of New York, New York, NY, USA; Department of Psychology, The Graduate Center at City University of New York, New York, NY, USA.
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Esmaeilpour Z, Marangolo P, Hampstead BM, Bestmann S, Galletta E, Knotkova H, Bikson M. Incomplete evidence that increasing current intensity of tDCS boosts outcomes. Brain Stimul 2017; 11:310-321. [PMID: 29258808 DOI: 10.1016/j.brs.2017.12.002] [Citation(s) in RCA: 119] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Revised: 12/06/2017] [Accepted: 12/08/2017] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Transcranial direct current stimulation (tDCS) is investigated to modulate neuronal function by applying a fixed low-intensity direct current to scalp. OBJECTIVES We critically discuss evidence for a monotonic response in effect size with increasing current intensity, with a specific focus on a question if increasing applied current enhance the efficacy of tDCS. METHODS We analyzed tDCS intensity does-response from different perspectives including biophysical modeling, animal modeling, human neurophysiology, neuroimaging and behavioral/clinical measures. Further, we discuss approaches to design dose-response trials. RESULTS Physical models predict electric field in the brain increases with applied tDCS intensity. Data from animal studies are lacking since a range of relevant low-intensities is rarely tested. Results from imaging studies are ambiguous while human neurophysiology, including using transcranial magnetic stimulation (TMS) as a probe, suggests a complex state-dependent non-monotonic dose response. The diffusivity of brain current flow produced by conventional tDCS montages complicates this analysis, with relatively few studies on focal High Definition (HD)-tDCS. In behavioral and clinical trials, only a limited range of intensities (1-2 mA), and typically just one intensity, are conventionally tested; moreover, outcomes are subject brain-state dependent. Measurements and models of current flow show that for the same applied current, substantial differences in brain current occur across individuals. Trials are thus subject to inter-individual differences that complicate consideration of population-level dose response. CONCLUSION The presence or absence of simple dose response does not impact how efficacious a given tDCS dose is for a given indication. Understanding dose-response in human applications of tDCS is needed for protocol optimization including individualized dose to reduce outcome variability, which requires intelligent design of dose-response studies.
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Affiliation(s)
- Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY 10031, USA; Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran.
| | - Paola Marangolo
- Dipartimento di Studi Umanistici, University Federico II, Naples and IRCCS Fondazione Santa Lucia, Rome Italy
| | - Benjamin M Hampstead
- VA Ann Arbor Healthcare System, Ann Arbor, MI 48105, USA; Department of Psychiatry, University of Michigan, Ann Arbor, MI 48105, USA
| | - Sven Bestmann
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London, UK
| | - Elisabeth Galletta
- Rusk Rehabilitation Medicine, New York University Langone Medical Center, USA
| | - Helena Knotkova
- MJHS Institute for Innovation in Palliative Care, New York, NY, USA; Department of Family and Social Medicine, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY 10031, USA
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Meiron O, Gale R, Namestnic J, Bennet-Back O, David J, Gebodh N, Adair D, Esmaeilpour Z, Bikson M. High-Definition transcranial direct current stimulation in early onset epileptic encephalopathy: a case study. Brain Inj 2017; 32:135-143. [PMID: 29156988 DOI: 10.1080/02699052.2017.1390254] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
PRIMARY OBJECTIVE Early onset epileptic encephalopathy is characterized by high daily seizure-frequency, multifocal epileptic discharges, severe psychomotor retardation, and death at infancy. Currently, there are no effective treatments to alleviate seizure frequency and high-voltage epileptic discharges in these catastrophic epilepsy cases. The current study examined the safety and feasibility of High-Definition transcranial direct current stimulation (HD-tDCS) in reducing epileptiform activity in a 30-month-old child suffering from early onset epileptic encephalopathy. DESIGN AND METHODS HD-tDCS was administered over 10 intervention days spanning two weeks including pre- and post-intervention video-EEG monitoring. RESULTS There were no serious adverse events or side effects related to the HD-tDCS intervention. Frequency of clinical seizures was not significantly reduced. However, interictal sharp wave amplitudes were significantly lower during the post-intervention period versus baseline. Vital signs and blood biochemistry remained stable throughout the entire study. CONCLUSIONS These exploratory findings support the safety and feasibility of 4 × 1 HD-tDCS in early onset epileptic encephalopathy and provide the first evidence of HD-tDCS effects on paroxysmal EEG features in electroclinical cases under the age of 36 months. Extending HD-tDCS treatment may enhance electrographic findings and clinical effects.
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Affiliation(s)
- Oded Meiron
- a Clinical Research Center for Brain Sciences , Herzog Medical Center , Jerusalem , Israel
| | - Rena Gale
- b Children Respiratory Unit , Herzog Medical Center , Jerusalem , Israel
| | - Julia Namestnic
- b Children Respiratory Unit , Herzog Medical Center , Jerusalem , Israel
| | - Odeya Bennet-Back
- c Pediatric Neurology Department , Shaare Zedek Medical Center , Jerusalem , Israel
| | - Jonathan David
- a Clinical Research Center for Brain Sciences , Herzog Medical Center , Jerusalem , Israel
| | - Nigel Gebodh
- d Department of Biomedical Engineering , The City College of the City University of New York , New York , USA
| | - Devin Adair
- d Department of Biomedical Engineering , The City College of the City University of New York , New York , USA
| | - Zeinab Esmaeilpour
- d Department of Biomedical Engineering , The City College of the City University of New York , New York , USA.,e Biomedical Engineering Department , Amirkabir University of Technology , Tehran , Iran
| | - Marom Bikson
- d Department of Biomedical Engineering , The City College of the City University of New York , New York , USA
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Bikson M, Paneri B, Mourdoukoutas A, Esmaeilpour Z, Badran BW, Azzam R, Adair D, Datta A, Fang XH, Wingeier B, Chao D, Alonso-Alonso M, Lee K, Knotkova H, Woods AJ, Hagedorn D, Jeffery D, Giordano J, Tyler WJ. Limited output transcranial electrical stimulation (LOTES-2017): Engineering principles, regulatory statutes, and industry standards for wellness, over-the-counter, or prescription devices with low risk. Brain Stimul 2017; 11:134-157. [PMID: 29122535 DOI: 10.1016/j.brs.2017.10.012] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Revised: 09/16/2017] [Accepted: 10/15/2017] [Indexed: 01/17/2023] Open
Abstract
We present device standards for low-power non-invasive electrical brain stimulation devices classified as limited output transcranial electrical stimulation (tES). Emerging applications of limited output tES to modulate brain function span techniques to stimulate brain or nerve structures, including transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), and transcranial pulsed current stimulation (tPCS), have engendered discussion on how access to technology should be regulated. In regards to legal regulations and manufacturing standards for comparable technologies, a comprehensive framework already exists, including quality systems (QS), risk management, and (inter)national electrotechnical standards (IEC). In Part 1, relevant statutes are described for medical and wellness application. While agencies overseeing medical devices have broad jurisdiction, enforcement typically focuses on those devices with medical claims or posing significant risk. Consumer protections regarding responsible marketing and manufacture apply regardless. In Part 2 of this paper, we classify the electrical output performance of devices cleared by the United States Food and Drug Administration (FDA) including over-the-counter (OTC) and prescription electrostimulation devices, devices available for therapeutic or cosmetic purposes, and devices indicated for stimulation of the body or head. Examples include iontophoresis devices, powered muscle stimulators (PMS), cranial electrotherapy stimulation (CES), and transcutaneous electrical nerve stimulation (TENS) devices. Spanning over 13 FDA product codes, more than 1200 electrical stimulators have been cleared for marketing since 1977. The output characteristics of conventional tDCS, tACS, and tPCS techniques are well below those of most FDA cleared devices, including devices that are available OTC and those intended for stimulation on the head. This engineering analysis demonstrates that with regard to output performance and standing regulation, the availability of tDCS, tACS, or tPCS to the public would not introduce risk, provided such devices are responsibly manufactured and legally marketed. In Part 3, we develop voluntary manufacturer guidance for limited output tES that is aligned with current regulatory standards. Based on established medical engineering and scientific principles, we outline a robust and transparent technical framework for ensuring limited output tES devices are designed to minimize risks, while also supporting access and innovation. Alongside applicable medical and government activities, this voluntary industry standard (LOTES-2017) further serves an important role in supporting informed decisions by the public.
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Affiliation(s)
- Marom Bikson
- The City College of New York, Department of Biomedical Engineering, New York, NY 10031, USA.
| | - Bhaskar Paneri
- The City College of New York, Department of Biomedical Engineering, New York, NY 10031, USA
| | - Andoni Mourdoukoutas
- The City College of New York, Department of Biomedical Engineering, New York, NY 10031, USA
| | - Zeinab Esmaeilpour
- The City College of New York, Department of Biomedical Engineering, New York, NY 10031, USA
| | - Bashar W Badran
- U.S. Army Research Laboratory, Aberdeen Proving Ground, MD, USA; Department of Psychology, University of New Mexico, Albuquerque, NM, USA
| | | | - Devin Adair
- The City College of New York, Department of Biomedical Engineering, New York, NY 10031, USA
| | | | - Xiao Hui Fang
- The City College of New York, Department of Biomedical Engineering, New York, NY 10031, USA
| | | | - Daniel Chao
- Halo Neuroscience Inc., San Francisco, CA 94103, USA
| | - Miguel Alonso-Alonso
- Harvard Medical School, Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Boston, MA, USA
| | - Kiwon Lee
- Ybrain Inc., Sampyeong-dong, Seongnam-si, South Korea
| | - Helena Knotkova
- MJHS Institute for Innovation in Palliative Care, New York, NY, USA; Department of Family and Social Medicine, Albert Einstein College of Medicine, The Bronx, NY, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, University of Florida, USA
| | | | | | - James Giordano
- Department of Neurology and Neuroethics Studies Program, Pellegrino Center for Clinical Bioethics, Georgetown University Medical Center, Washington, DC, USA
| | - William J Tyler
- Arizona State University, School of Biological and Health Systems Engineering, Tempe, AZ 85287, USA
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Gebodh N, Adair D, Chelette K, Esmaeilpour Z, Bikson M, Dmochowski J, Woods A, Kappenman E. Physiologic Artifacts When Combining EEG and tDCS. Brain Stimul 2017. [DOI: 10.1016/j.brs.2017.04.051] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Esmaeilpour Z, Schestatsky P, Bikson M, Brunoni AR, Pellegrinelli A, Piovesan FX, Santos MMSA, Menezes RB, Fregni F. Notes on Human Trials of Transcranial Direct Current Stimulation between 1960 and 1998. Front Hum Neurosci 2017; 11:71. [PMID: 28280463 PMCID: PMC5322235 DOI: 10.3389/fnhum.2017.00071] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 02/06/2017] [Indexed: 11/13/2022] Open
Abstract
Background: Transcranial direct current stimulation (tDCS) is investigated to modulate neuronal function including cognitive neuroscience and neuropsychiatric therapies. While cases of human stimulation with rudimentary batteries date back more than 200 years, clinical trials with current controlled stimulation were published intermittently since the 1960s. The modern era of tDCS only started after 1998. Objectives: To review methods and outcomes of tDCS studies from old literature (between 1960 and 1998) with intention of providing new insight for ongoing tDCS trials and development of tDCS protocols especially for the purpose of treatment. Methods: Articles were identified through a search in PubMed and through the reference list from its selected articles. We included only non-invasive human studies that provided controlled direct current and were written in English, French, Spanish or Portuguese before the year of 1998, the date in which modern stimulation paradigms were implemented. Results: Fifteen articles met our criteria. The majority were small-randomized controlled clinical trials that enrolled a mean of approximately 26 subjects (Phase II studies). Most of the studies (around 83%) assessed the role of tDCS in the treatment of psychiatric conditions, in which the main outcomes were measured by means of behavioral scales and clinical observation, but the diagnostic precision and the quality of outcome monitoring, including adverse events, were deficient by modern standards. Compared to modern tDCS dose, the stimulation intensities used (0.1-1 mA) were lower, however as the electrodes were typically smaller (e.g., 1.26 cm2), the average electrode current density (0.2 mA/cm2) was approximately 4× higher. The number of sessions ranged from one to 120 (median 14). Notably, the stimulation session durations of several minutes to 11 h (median 4.5 h) could markedly exceed modern tDCS protocols. Twelve studies out of 15 showed positive results. Only mild side effects were reported, with headache and skin alterations the most common. Conclusion: Most of the studies identified were for psychiatric indications, especially in patients with depression and/or schizophrenia and majority indicated some positive results. Variability in outcome is noted across trials and within trials across subjects, but overall results were reported as encouraging, and consistent with modern efforts, given some responders and mild side effects. The significant difference with modern dose, low current with smaller electrode size and interestingly much longer stimulation duration may worth considering.
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Affiliation(s)
- Zeinab Esmaeilpour
- Neural Engineering Laboratory, Department of Biomedical Engineering, City College of New York, City University of New YorkNew York, NY, USA; Biomedical Engineering Department, Amirkabir University of TechnologyTehran, Iran
| | - Pedro Schestatsky
- Neurology Service Hospital de Cínicas de Porto Alegre, Department of Internal Medicina, Universidade Federal do Rio Grande do Sul (UFRGS)Porto Alegre, Brazil; Hospital Moinhos de VentoPorto Alegre, Brazil
| | - Marom Bikson
- Neural Engineering Laboratory, Department of Biomedical Engineering, City College of New York, City University of New York New York, NY, USA
| | - André R Brunoni
- Laboratory of Neuroscience (LIM27), Department and Institute of Psychiatry, University of São Paulo São Paulo, Brazil
| | - Ada Pellegrinelli
- Faculdade de Ciências Médicas da Santa Casa de São Paulo, School of Medical Sciences São Paulo, Brazil
| | - Fernanda X Piovesan
- Faculdade de Ciências Médicas da Santa Casa de São Paulo, School of Medical Sciences São Paulo, Brazil
| | - Mariana M S A Santos
- Faculdade de Ciências Médicas da Santa Casa de São Paulo, School of Medical Sciences São Paulo, Brazil
| | - Renata B Menezes
- Departamento de Medicina - Fortaleza, Universidade de Fortaleza, Centro de Ciências da Saúde Ceará, Brazil
| | - Felipe Fregni
- Laboratory of Neuromodulation, Physical Medicine and Rehabilitation Department, Spaulding Rehabilitation Hospital, Harvard Medical School Boston, MA, USA
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