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Zhang S, Xie X, Xu Y, Mi J, Li Z, Guo Z, Xu G. Effects of transcranial magneto-acoustic stimulation on cognitive function and neural signal transmission in the hippocampal CA1 region of mice. Neuroscience 2024; 556:86-95. [PMID: 39047971 DOI: 10.1016/j.neuroscience.2024.01.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/16/2023] [Accepted: 01/29/2024] [Indexed: 07/27/2024]
Abstract
As a new means of brain neuroregulation and research, transcranial magneto-acoustic stimulation (TMAS) uses the coupling effect of ultrasound and a static magnetic field to regulate neural activity in the corresponding brain areas. Calcium ions can promote the secretion of neurotransmitters and play a key role in the transmission of neural signals in brain cognition. In this study, to explore the effects of TMAS on cognitive function and neural signaling in the CA1 region of the hippocampus, TMAS was applied to male 2-month-old C57 mice with a magnetic field strength of 0.3 T and ultrasound intensity of 2.6 W/cm2. First, the efficiency of neural signaling in the CA1 region of the mouse hippocampus was detected by fiber photometry. Second, the effects of TMAS on cognitive function in mice were investigated through multiple behavioral experiments, including spatial learning and memory ability, anxiety and desire for novelty. The experimental results showed that TMAS could improve cognitive function in mice, and the efficiency of neural signaling in the CA1 area of the hippocampus was significantly increased during stimulation and maintained for one week after stimulation. In addition, the neural signaling efficiency in the CA1 area of the hippocampus increased in the open field (OF) experiment and recovered after one week, the neural signaling efficiency in the new object exploration (NOE) experiment was significantly enhanced, and the intensity slowed after one week. In conclusion, TMAS enhances cognitive performance and promotes neural signaling in the CA1 region of the mouse hippocampus.
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Affiliation(s)
- Shuai Zhang
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectricity and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; Hebei Key Laboratory of Electromagnetic Field and Electrical Reliability, Hebei University of Technology, Tianjin 300130, China.
| | - Xiaofeng Xie
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectricity and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; Hebei Key Laboratory of Electromagnetic Field and Electrical Reliability, Hebei University of Technology, Tianjin 300130, China
| | - Yihao Xu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectricity and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; Hebei Key Laboratory of Electromagnetic Field and Electrical Reliability, Hebei University of Technology, Tianjin 300130, China
| | - Jinrui Mi
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectricity and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; Hebei Key Laboratory of Electromagnetic Field and Electrical Reliability, Hebei University of Technology, Tianjin 300130, China
| | - Zichun Li
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectricity and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; Hebei Key Laboratory of Electromagnetic Field and Electrical Reliability, Hebei University of Technology, Tianjin 300130, China
| | - Zhongsheng Guo
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectricity and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; Hebei Key Laboratory of Electromagnetic Field and Electrical Reliability, Hebei University of Technology, Tianjin 300130, China
| | - Guizhi Xu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectricity and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; Hebei Key Laboratory of Electromagnetic Field and Electrical Reliability, Hebei University of Technology, Tianjin 300130, China
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Houde F, Butler R, St-Onge E, Martel M, Thivierge V, Descoteaux M, Whittingstall K, Leonard G. Anatomical measurements and field modeling to assess transcranial magnetic stimulation motor and non-motor effects. Neurophysiol Clin 2024; 54:103011. [PMID: 39244826 DOI: 10.1016/j.neucli.2024.103011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 08/22/2024] [Accepted: 08/22/2024] [Indexed: 09/10/2024] Open
Abstract
OBJECTIVE Explore how anatomical measurements and field modeling can be leveraged to improve investigations of transcranial magnetic stimulation (TMS) effects on both motor and non-motor TMS targets. METHODS TMS motor effects (targeting the primary motor cortex [M1]) were evaluated using the resting motor threshold (rMT), while TMS non-motor effects (targeting the superior temporal gyrus [STG]) were assessed using a pain memory task. Anatomical measurements included scalp-cortex distance (SCD) and cortical thickness (CT), whereas field modeling encompassed the magnitude of the electric field (E) induced by TMS. RESULTS Anatomical measurements and field modeling values differed significantly between M1 and STG. For TMS motor effects, rMT was correlated with SCD, CT, and E values at M1 (p < 0.05). No correlations were found between these metrics for the STG and TMS non-motor effects (pain memory; all p-values > 0.05). CONCLUSION Although anatomical measurements and field modeling are closely related to TMS motor effects, their relationship to non-motor effects - such as pain memory - appear to be much more tenuous and complex, highlighting the need for further advancement in our use of TMS and virtual lesion paradigms.
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Affiliation(s)
- Francis Houde
- Research Centre on Aging, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC, Canada, J1H 5N4; Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada, J1H 5N4
| | - Russell Butler
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada, J1H 5N4
| | - Etienne St-Onge
- Department of Computer Science and Engineering, Université du Québec en Outaouais, Saint-Jérôme, QC, Canada, J7Z 0B7
| | - Marylie Martel
- Research Centre on Aging, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC, Canada, J1H 5N4
| | - Véronique Thivierge
- Research Centre on Aging, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC, Canada, J1H 5N4
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, QC, Canada, J1K 0A5
| | - Kevin Whittingstall
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada, J1H 5N4
| | - Guillaume Leonard
- Research Centre on Aging, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC, Canada, J1H 5N4; School of Rehabilitation, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada.
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3
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Liao WY, Opie GM, Ziemann U, Semmler JG. Modulation of dorsal premotor cortex differentially influences visuomotor adaptation in young and older adults. Neurobiol Aging 2024; 141:34-45. [PMID: 38815412 DOI: 10.1016/j.neurobiolaging.2024.05.011] [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: 12/06/2023] [Revised: 05/09/2024] [Accepted: 05/20/2024] [Indexed: 06/01/2024]
Abstract
The communication between dorsal premotor cortex (PMd) and primary motor cortex (M1) is important for visuomotor adaptation, but it is unclear how this relationship changes with advancing age. The present study recruited 21 young and 23 older participants for two experimental sessions during which intermittent theta burst stimulation (iTBS) or sham was applied over PMd. We assessed the effects of PMd iTBS on M1 excitability using motor evoked potentials (MEP) recorded from right first dorsal interosseous when single-pulse transcranial magnetic stimulation (TMS) was applied with posterior-anterior (PA) or anterior-posterior (AP) currents; and adaptation by quantifying error recorded during a visuomotor adaptation task (VAT). PMd iTBS potentiated PA (P < 0.0001) and AP (P < 0.0001) MEP amplitude in both young and older adults. PMd iTBS increased error in young adults during adaptation (P = 0.026), but had no effect in older adults (P = 0.388). Although PMd iTBS potentiated M1 excitability in both young and older adults, the intervention attenuated visuomotor adaptation specifically in young adults.
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Affiliation(s)
- Wei-Yeh Liao
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia.
| | - George M Opie
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia
| | - Ulf Ziemann
- Department of Neurology & Stroke, Eberhard Karls University of Tübingen, Tübingen, Germany; Hertie-Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - John G Semmler
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia
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Kumari P, Wunderlich H, Milojkovic A, López JE, Fossati A, Jahanshahi A, Kozielski K. Multiscale Modeling of Magnetoelectric Nanoparticles for the Analysis of Spatially Selective Neural Stimulation. Adv Healthc Mater 2024; 13:e2302871. [PMID: 38262344 DOI: 10.1002/adhm.202302871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 01/17/2024] [Indexed: 01/25/2024]
Abstract
The growing field of nanoscale neural stimulators offers a potential alternative to larger scale electrodes for brain stimulation. Nanoelectrodes made of magnetoelectric nanoparticles (MENPs) can provide an alternative to invasive electrodes for brain stimulation via magnetic-to-electric signal transduction. However, the magnetoelectric effect is a complex phenomenon and challenging to probe experimentally. Consequently, quantifying the stimulation voltage provided by MENPs is difficult, hindering precise regulation and control of neural stimulation and limiting their practical implementation as wireless nanoelectrodes. The work herein develops an approach to determine the stimulation voltage for MENPs in a finite element analysis (FEA) model. This model is informed by atomistic material properties from ab initio Density Functional Theory (DFT) calculations and supplemented by experimentally obtainable nanoscale parameters. This process overcomes the need for experimentally inaccessible characteristics for magnetoelectricity, and offers insights into the effect of the more manageable variables, such as the driving magnetic field. The model's voltage is compared to in vivo experimental data to assess its validity. With this, a predictable and controllable stimulation is simulated by MENPs, computationally substantiating their spatial selectivity. This work proposes a generalizable and accessible method for evaluating the stimulation capability of magnetoelectric nanostructures, facilitating their realization as wireless neural stimulators in the future.
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Affiliation(s)
- Prachi Kumari
- Professorship of Neuroengineering Materials, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Hannah Wunderlich
- Professorship of Neuroengineering Materials, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Aleksandra Milojkovic
- Professorship of Neuroengineering Materials, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Jorge Estudillo López
- Professorship of Neuroengineering Materials, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
| | - Arianna Fossati
- Department of Electronics and Information, Politecnico di Milano, Milano, 20133, Italy
| | - Ali Jahanshahi
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, 6229, Netherlands
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, 1105, Netherlands
| | - Kristen Kozielski
- Professorship of Neuroengineering Materials, School of Computation, Information and Technology, Technical University of Munich, 80333, Munich, Germany
- Munich Institute of Biomedical Engineering, Technical University of Munich, 85748, Garching, Germany
- Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, 80992, Munich, Germany
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5
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Ponasso GN. A survey on integral equations for bioelectric modeling. Phys Med Biol 2024; 69:17TR02. [PMID: 39042098 PMCID: PMC11410390 DOI: 10.1088/1361-6560/ad66a9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 07/23/2024] [Indexed: 07/24/2024]
Abstract
Bioelectric modeling problems, such as electroencephalography, magnetoencephalography, transcranial electrical stimulation, deep brain stimulation, and transcranial magnetic stimulation, among others, can be approached through the formulation and resolution of integral equations of theboundary element method(BEM). Recently, it has been realized that thecharge-based formulationof the BEM is naturally well-suited for the application of thefast multipole method(FMM). The FMM is a powerful algorithm for the computation of many-body interactions and is widely applied in electromagnetic modeling problems. With the introduction of BEM-FMM in the context of bioelectromagnetism, the BEM can now compete with thefinite element method(FEM) in a number of application cases. This survey has two goals: first, to give a modern account of the main BEM formulations in the literature and their integration with FMM, directed to general researchers involved in development of BEM software for bioelectromagnetic applications. Second, to survey different techniques and available software, and to contrast different BEM and FEM approaches. As a new contribution, we showcase that the charge-based formulation is dual to the more common surface potential formulation.
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Affiliation(s)
- Guillermo Nuñez Ponasso
- Department of Electrical & Computer Engineering, Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA, United States of America
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6
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Beyh A, Howells H, Giampiccolo D, Cancemi D, De Santiago Requejo F, Citro S, Keeble H, Lavrador JP, Bhangoo R, Ashkan K, Dell'Acqua F, Catani M, Vergani F. Connectivity defines the distinctive anatomy and function of the hand-knob area. Brain Commun 2024; 6:fcae261. [PMID: 39239149 PMCID: PMC11375856 DOI: 10.1093/braincomms/fcae261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 05/19/2024] [Accepted: 08/10/2024] [Indexed: 09/07/2024] Open
Abstract
Control of the hand muscles during fine digit movements requires a high level of sensorimotor integration, which relies on a complex network of cortical and subcortical hubs. The components of this network have been extensively studied in human and non-human primates, but discrepancies in the findings obtained from different mapping approaches are difficult to interpret. In this study, we defined the cortical and connectional components of the hand motor network in the same cohort of 20 healthy adults and 3 neurosurgical patients. We used multimodal structural magnetic resonance imaging (including T1-weighted imaging and diffusion tractography), as well as functional magnetic resonance imaging and navigated transcranial magnetic stimulation (nTMS). The motor map obtained from nTMS compared favourably with the one obtained from functional magnetic resonance imaging, both of which overlapped well within the 'hand-knob' region of the precentral gyrus and in an adjacent region of the postcentral gyrus. nTMS stimulation of the precentral and postcentral gyri led to motor-evoked potentials in the hand muscles in all participants, with more responses recorded from precentral stimulations. We also observed that precentral stimulations tended to produce motor-evoked potentials with shorter latencies and higher amplitudes than postcentral stimulations. Tractography showed that the region of maximum overlap between terminations of precentral-postcentral U-shaped association fibres and somatosensory projection tracts colocalizes with the functional motor maps. The relationships between the functional maps, and between them and the tract terminations, were replicated in the patient cohort. Three main conclusions can be drawn from our study. First, the hand-knob region is a reliable anatomical landmark for the functional localization of fine digit movements. Second, its distinctive shape is determined by the convergence of highly myelinated long projection fibres and short U-fibres. Third, the unique role of the hand-knob area is explained by its direct action on the spinal motoneurons and the access to high-order somatosensory information for the online control of fine movements. This network is more developed in the hand region compared to other body parts of the homunculus motor strip, and it may represent an important target for enhancing motor learning during early development.
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Affiliation(s)
- Ahmad Beyh
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ 08854, USA
| | - Henrietta Howells
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | - Davide Giampiccolo
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK
- Department of Neurosurgery, Institute of Neurosciences, Cleveland Clinic London, London SW1X 7HY, UK
| | - Daniele Cancemi
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | | | | | - Hannah Keeble
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | | | - Ranjeev Bhangoo
- Neurosurgical Department, King's College Hospital, London SE5 9RS, UK
| | - Keyoumars Ashkan
- Neurosurgical Department, King's College Hospital, London SE5 9RS, UK
| | - Flavio Dell'Acqua
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, UK
| | | | - Francesco Vergani
- Neurosurgical Department, King's College Hospital, London SE5 9RS, UK
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Farahani MV, Shariatpanahi SP, Goliaei B. A computational model elucidating mechanisms and variability in theta burst stimulation responses. J Comput Neurosci 2024; 52:183-196. [PMID: 39120822 DOI: 10.1007/s10827-024-00875-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 04/22/2024] [Accepted: 07/17/2024] [Indexed: 08/10/2024]
Abstract
Theta burst stimulation (TBS) is a form of repetitive transcranial magnetic stimulation (rTMS) with unknown underlying mechanisms and highly variable responses across subjects. To investigate these issues, we developed a simple computational model. Our model consisted of two neurons linked by an excitatory synapse that incorporates two mechanisms: short-term plasticity (STP) and spike-timing-dependent plasticity (STDP). We applied a variable-amplitude current through I-clamp with a TBS time pattern to the pre- and post-synaptic neurons, simulating synaptic plasticity. We analyzed the results and provided an explanation for the effects of TBS, as well as the variability of responses to it. Our findings suggest that the interplay of STP and STDP mechanisms determines the direction of plasticity, which selectively affects synapses in extended neurons and underlies functional effects. Our model describes how the timing, number, and intensity of pulses delivered to neurons during rTMS contribute to induced plasticity. This not only successfully explains the different effects of intermittent TBS (iTBS) and continuous TBS (cTBS), but also predicts the results of other protocols such as 10 Hz rTMS. We propose that the variability in responses to TBS can be attributed to the variable span of neuronal thresholds across individuals and sessions. Our model suggests a biologically plausible mechanism for the diverse responses to TBS protocols and aligns with experimental data on iTBS and cTBS outcomes. This model could potentially aid in improving TBS and rTMS protocols and customizing treatments for patients, brain areas, and brain disorders.
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Affiliation(s)
| | | | - Bahram Goliaei
- Institute of Biochemistry and Biophysics, University of Tehran, P.O.Box, 13145-1384, Tehran, Iran
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8
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Pavey NA, Menon P, Peterchev AV, Kiernan MC, Vucic S. Abnormalities of cortical stimulation strength-duration time constant in amyotrophic lateral sclerosis. Clin Neurophysiol 2024; 164:161-167. [PMID: 38901111 PMCID: PMC11345808 DOI: 10.1016/j.clinph.2024.05.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 04/23/2024] [Accepted: 05/26/2024] [Indexed: 06/22/2024]
Abstract
OBJECTIVES Strength-duration time constant (SDTC) may now be determined for cortical motor neurones, with activity mediated by transient Na+ conductances. The present study determined whether cortical SDTC is abnormal and linked to the pathogenesis of amyotrophic lateral sclerosis. METHODS Cortical SDTC and rheobase were estimated from 17 ALS patients using a controllable pulse parameter transcranial magnetic stimulation (cTMS) device. Resting motor thresholds (RMTs) were determined at pulse widths (PW) of 30, 45, 60, 90 and 120 µs and M-ratio of 0.1, using a figure-of-eight coil applied to the primary motor cortex. RESULTS SDTC was significantly reduced in ALS patients (150.58 ± 9.98 µs; controls 205.94 ± 13.7 µs, P < 0.01). The reduced SDTC correlated with a rate of disease progression (Rho = -0.440, P < 0.05), ALS functional rating score (ALSFRS-R) score (Rho = 0.446, P < 0.05), and disease duration (R = 0.428, P < 0.05). The degree of change in SDTC was greater in patients with cognitive abnormalities as manifested by an abnormal total Edinburgh Cognitive ALS Screen score (140.5 ± 28.7 µs, P < 0.001) and ALS-specific subscore (141.7 ± 33.2 µs, P = 0.003). CONCLUSIONS Cortical SDTC reduction was associated with a more aggressive ALS phenotype, or with more prominent cognitive impairment. SIGNIFICANCE An increase in transient Na+ conductances may account for the reduction in SDTC, linked to the pathogenesis of ALS.
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Affiliation(s)
- Nathan A Pavey
- Brain and Nerve Research Centre, Concord Clinical School, University of Sydney, Concord Hospital, Sydney, Australia
| | - Parvathi Menon
- Brain and Nerve Research Centre, Concord Clinical School, University of Sydney, Concord Hospital, Sydney, Australia
| | - Angel V Peterchev
- Department of Biological Sciences, Dartmouth College, Hanover, NH, USA; Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Psychiatry and Behavioural Sciences, Duke University, Durham, NC, USA; Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, Duke University, Durham, NC, USA
| | | | - Steve Vucic
- Brain and Nerve Research Centre, Concord Clinical School, University of Sydney, Concord Hospital, Sydney, Australia.
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Cerins A, Thomas EHX, Barbour T, Taylor JJ, Siddiqi SH, Trapp N, McGirr A, Caulfield KA, Brown JC, Chen L. A New Angle on Transcranial Magnetic Stimulation Coil Orientation: A Targeted Narrative Review. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:744-753. [PMID: 38729243 DOI: 10.1016/j.bpsc.2024.04.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/19/2024] [Accepted: 04/26/2024] [Indexed: 05/12/2024]
Abstract
Transcranial magnetic stimulation (TMS) is used to treat several neuropsychiatric disorders including depression, where it is effective in approximately one half of patients for whom pharmacological approaches have failed. Treatment response is related to stimulation parameters such as the stimulation frequency, pattern, intensity, location, total number of pulses and sessions applied, and target brain network engagement. One critical but underexplored component of the stimulation procedure is the orientation or yaw angle of the commonly used figure-of-eight TMS coil, which is known to impact neuronal response to TMS. However, coil orientation has remained largely unchanged since TMS was first used to treat depression and continues to be based on motor cortex anatomy, which may not be optimal for the dorsolateral prefrontal cortex treatment site. In this targeted narrative review, we evaluate experimental, clinical, and computational evidence indicating that optimizing coil orientation may improve TMS treatment outcomes. The properties of the electric field induced by TMS, the changes to this field caused by the differing conductivities of head tissues, and the interaction between coil orientation and the underlying cortical anatomy are summarized. We describe evidence that the magnitude and site of cortical activation, surrogate markers of TMS dosing and brain network targeting considered central in clinical response to TMS, are influenced by coil orientation. We suggest that coil orientation should be considered when applying therapeutic TMS and propose several approaches to optimizing this potentially important treatment parameter.
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Affiliation(s)
- Andris Cerins
- Department of Psychiatry, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia.
| | - Elizabeth H X Thomas
- Department of Psychiatry, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
| | - Tracy Barbour
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Joseph J Taylor
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts; Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nicholas Trapp
- University of Iowa, Department of Psychiatry, Carver College of Medicine, Iowa City, Iowa; Iowa Neuroscience Institute, Iowa City, Iowa
| | - Alexander McGirr
- Department of Psychiatry, University of Calgary, Alberta, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Kevin A Caulfield
- Brain Stimulation Division, Department of Psychiatry, Medical University of South Carolina, Charleston, South Carolina
| | - Joshua C Brown
- Brain Stimulation Mechanisms Laboratory, Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Leo Chen
- Department of Psychiatry, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia; Alfred Mental and Addiction Health, Alfred Health, Melbourne, Victoria, Australia
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10
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Tamaki A, Uenishi S, Yamada S, Yasuda K, Ikeda N, Tabata M, Kita A, Mizutani-Tiebel Y, Keeser D, Padberg F, Tsuji T, Kimoto S, Takahashi S. Female sex and age-based advantage of simulated electric field in TMS to the prefrontal cortex in schizophrenia and mood disorders. Psychiatry Res Neuroimaging 2024; 342:111844. [PMID: 38901089 DOI: 10.1016/j.pscychresns.2024.111844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 06/03/2024] [Accepted: 06/04/2024] [Indexed: 06/22/2024]
Abstract
This study investigates computational models of electric field strength for transcranial magnetic stimulation (TMS) of the left dorsolateral prefrontal cortex (DLPFC) based on individual MRI data of patients with schizophrenia (SZ), major depressive disorder (MDD), bipolar disorder (BP), and healthy controls (HC). In addition, it explores the association of electric field intensities with age, gender and intracranial volume. The subjects were 23 SZ (12 male, mean age = 45.30), 24 MDD (16 male, mean age = 43.57), 23 BP (16 male, mean age = 39.29), 23 HC (13 male, mean age = 40.91). Based on individual MRI sequences, electric fields were computationally modeled by two independent investigators using SimNIBS ver. 2.1.1. There was no significant difference in electric field strength between the groups (HC vs SZ, HC vs MDD, HC vs BP, SZ vs MDD, SZ vs BP, MDD vs BP). Female subjects showed higher electric field intensities in widespread areas than males, and age was positively significantly associated with electric field strength in the left parahippocampal area as observed. Our results suggest differences in electric field strength of left DLPFC TMS for gender and age. It may open future avenues for individually modeling TMS based on structural MRI data.
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Affiliation(s)
- Atsushi Tamaki
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan; Department of Psychiatry, Wakayama Prefectural Mental Health Care Center, Wakayama, 643-0811, Japan.
| | - Shinya Uenishi
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan; Department of Psychiatry, Hidaka Hospital, Gobo 6440002, Wakayama, Japan
| | - Shinichi Yamada
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan
| | - Kasumi Yasuda
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan
| | - Natsuko Ikeda
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan
| | - Michiyo Tabata
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan
| | - Akira Kita
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan
| | - Yuki Mizutani-Tiebel
- Department of Psychiatry and Psychotherapy, LMU University Hospital Munich, 80336, Munich, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, LMU University Hospital Munich, 80336, Munich, Germany; Department of Radiology, LMU University Hospital Munich, 81377, Munich, Germany; Munich Center for Neurosciences (MCN) Brain & Mind, Planegg-Martinsried 82152, Munich, Germany
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, LMU University Hospital Munich, 80336, Munich, Germany
| | - Tomikimi Tsuji
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan
| | - Sohei Kimoto
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan
| | - Shun Takahashi
- Department of Neuropsychiatry, Wakayama Medical University, Wakayama 6410012, Wakayama, Japan; Department of Psychiatry, Osaka University Graduate School of Medicine, Suita 5650871, Osaka, Japan; Graduate School of Rehabilitation Science, Osaka Metropolitan University, Habikino 5838555, Osaka, Japan; Clinical Research and Education Center, Asakayama General Hospital, Sakai 5900018, Osaka, Japan
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11
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Goswami N, Shen M, Gomez LJ, Dannhauer M, Sommer MA, Peterchev AV. A semi-automated pipeline for finite element modeling of electric field induced in nonhuman primates by transcranial magnetic stimulation. J Neurosci Methods 2024; 408:110176. [PMID: 38795980 PMCID: PMC11227653 DOI: 10.1016/j.jneumeth.2024.110176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 04/18/2024] [Accepted: 05/22/2024] [Indexed: 05/28/2024]
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) is used to treat a range of brain disorders by inducing an electric field (E-field) in the brain. However, the precise neural effects of TMS are not well understood. Nonhuman primates (NHPs) are used to model the impact of TMS on neural activity, but a systematic method of quantifying the induced E-field in the cortex of NHPs has not been developed. NEW METHOD The pipeline uses statistical parametric mapping (SPM) to automatically segment a structural MRI image of a rhesus macaque into five tissue compartments. Manual corrections are necessary around implants. The segmented tissues are tessellated into 3D meshes used in finite element method (FEM) software to compute the TMS induced E-field in the brain. The gray matter can be further segmented into cortical laminae using a volume preserving method for defining layers. RESULTS Models of three NHPs were generated with TMS coils placed over the precentral gyrus. Two coil configurations, active and sham, were simulated and compared. The results demonstrated a large difference in E-fields at the target. Additionally, the simulations were calculated using two different E-field solvers and were found to not significantly differ. COMPARISON WITH EXISTING METHODS Current methods segment NHP tissues manually or use automated methods for only the brain tissue. Existing methods also do not stratify the gray matter into layers. CONCLUSION The pipeline calculates the induced E-field in NHP models by TMS and can be used to plan implant surgeries and determine approximate E-field values around neuron recording sites.
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Affiliation(s)
- Neerav Goswami
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
| | - Michael Shen
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Luis J Gomez
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Moritz Dannhauer
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Marc A Sommer
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA; Department of Neurobiology, Duke University, Durham, NC, USA
| | - Angel V Peterchev
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, Duke University, Durham, NC, USA
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12
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Wang B, Peterchev AV, Gaugain G, Ilmoniemi RJ, Grill WM, Bikson M, Nikolayev D. Quasistatic approximation in neuromodulation. J Neural Eng 2024; 21:10.1088/1741-2552/ad625e. [PMID: 38994790 PMCID: PMC11370654 DOI: 10.1088/1741-2552/ad625e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 06/28/2024] [Indexed: 07/13/2024]
Abstract
We define and explain the quasistatic approximation (QSA) as applied to field modeling for electrical and magnetic stimulation. Neuromodulation analysis pipelines include discrete stages, and QSA is applied specifically when calculating the electric and magnetic fields generated in tissues by a given stimulation dose. QSA simplifies the modeling equations to support tractable analysis, enhanced understanding, and computational efficiency. The application of QSA in neuromodulation is based on four underlying assumptions: (A1) no wave propagation or self-induction in tissue, (A2) linear tissue properties, (A3) purely resistive tissue, and (A4) non-dispersive tissue. As a consequence of these assumptions, each tissue is assigned a fixed conductivity, and the simplified equations (e.g. Laplace's equation) are solved for the spatial distribution of the field, which is separated from the field's temporal waveform. Recognizing that electrical tissue properties may be more complex, we explain how QSA can be embedded in parallel or iterative pipelines to model frequency dependence or nonlinearity of conductivity. We survey the history and validity of QSA across specific applications, such as microstimulation, deep brain stimulation, spinal cord stimulation, transcranial electrical stimulation, and transcranial magnetic stimulation. The precise definition and explanation of QSA in neuromodulation are essential for rigor when using QSA models or testing their limits.
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Affiliation(s)
- Boshuo Wang
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27710, United States of America
| | - Angel V Peterchev
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC 27710, United States of America
- Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, United States of America
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, United States of America
- Department of Neurosurgery, Duke University, Durham, NC 27710, United States of America
| | - Gabriel Gaugain
- Institut d’Électronique et des Technologies du numéRique (IETR UMR 6164), CNRS / University of Rennes, 35000 Rennes, France
| | - Risto J Ilmoniemi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Warren M Grill
- Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, United States of America
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, United States of America
- Department of Neurosurgery, Duke University, Durham, NC 27710, United States of America
- Department of Neurobiology, Duke University, Durham, NC 27710, United States of America
| | - Marom Bikson
- The City College of New York, New York, NY 11238, United States of America
| | - Denys Nikolayev
- Institut d’Électronique et des Technologies du numéRique (IETR UMR 6164), CNRS / University of Rennes, 35000 Rennes, France
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13
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Pavey N, Hannaford A, van den Bos M, Kiernan MC, Menon P, Vucic S. Distinct neuronal circuits mediate cortical hyperexcitability in amyotrophic lateral sclerosis. Brain 2024; 147:2344-2356. [PMID: 38374770 DOI: 10.1093/brain/awae049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/16/2024] [Accepted: 01/27/2024] [Indexed: 02/21/2024] Open
Abstract
Cortical hyperexcitability is an important pathophysiological mechanism in amyotrophic lateral sclerosis (ALS), reflecting a complex interaction of inhibitory and facilitatory interneuronal processes that evolves in the degenerating brain. The advances in physiological techniques have made it possible to interrogate progressive changes in the motor cortex. Specifically, the direction of transcranial magnetic stimulation (TMS) stimulus within the primary motor cortex can be utilized to influence descending corticospinal volleys and to thereby provide information about distinct interneuronal circuits. Cortical motor function and cognition was assessed in 29 ALS patients with results compared to healthy volunteers. Cortical dysfunction was assessed using threshold-tracking TMS to explore alterations in short interval intracortical inhibition (SICI), short interval intracortical facilitation (SICF), the index of excitation and stimulus response curves using a figure-of-eight coil with the coil oriented relative to the primary motor cortex in a posterior-anterior, lateral-medial and anterior-posterior direction. Mean SICI, between interstimulus interval of 1-7 ms, was significantly reduced in ALS patients compared to healthy controls when assessed with the coil oriented in posterior-anterior (P = 0.044) and lateral-medial (P = 0.005) but not the anterior-posterior (P = 0.08) directions. A significant correlation between mean SICI oriented in a posterior-anterior direction and the total Edinburgh Cognitive and Behavioural ALS Screen score (Rho = 0.389, P = 0.037) was evident. In addition, the mean SICF, between interstimulus interval 1-5 ms, was significantly increased in ALS patients when recorded with TMS coil oriented in posterior-anterior (P = 0.035) and lateral-medial (P < 0.001) directions. In contrast, SICF recorded with TMS coil oriented in the anterior-posterior direction was comparable between ALS and controls (P = 0.482). The index of excitation was significantly increased in ALS patients when recorded with the TMS coil oriented in posterior-anterior (P = 0.041) and lateral-medial (P = 0.003) directions. In ALS patients, a significant increase in the stimulus response curve gradient was evident compared to controls when recorded with TMS coil oriented in posterior-anterior (P < 0.001), lateral-medial (P < 0.001) and anterior-posterior (P = 0.002) directions. The present study has established that dysfunction of distinct interneuronal circuits mediates the development of cortical hyperexcitability in ALS. Specifically, complex interplay between inhibitory circuits and facilitatory interneuronal populations, that are preferentially activated by stimulation in posterior-to-anterior or lateral-to-medial directions, promotes cortical hyperexcitability in ALS. Mechanisms that underlie dysfunction of these specific cortical neuronal circuits will enhance understanding of the pathophysiological processes in ALS, with the potential to uncover focussed therapeutic targets.
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Affiliation(s)
- Nathan Pavey
- Brain and Nerve Research Centre, Concord Clinical School, The University of Sydney, Concord Hospital, Sydney, NSW 2139, Australia
| | - Andrew Hannaford
- Brain and Nerve Research Centre, Concord Clinical School, The University of Sydney, Concord Hospital, Sydney, NSW 2139, Australia
| | - Mehdi van den Bos
- Brain and Nerve Research Centre, Concord Clinical School, The University of Sydney, Concord Hospital, Sydney, NSW 2139, Australia
| | - Matthew C Kiernan
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2139, Australia
- Department of Neurology, Royal Prince Alfred Hospital, Sydney, NSW 2139, Australia
| | - Parvathi Menon
- Brain and Nerve Research Centre, Concord Clinical School, The University of Sydney, Concord Hospital, Sydney, NSW 2139, Australia
| | - Steve Vucic
- Brain and Nerve Research Centre, Concord Clinical School, The University of Sydney, Concord Hospital, Sydney, NSW 2139, Australia
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14
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Liao WY, Opie GM, Ziemann U, Semmler JG. The effects of intermittent theta burst stimulation over dorsal premotor cortex on primary motor cortex plasticity in young and older adults. Eur J Neurosci 2024; 60:4019-4033. [PMID: 38757748 DOI: 10.1111/ejn.16395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 04/15/2024] [Accepted: 05/02/2024] [Indexed: 05/18/2024]
Abstract
Previous transcranial magnetic stimulation (TMS) research suggests that the dorsal premotor cortex (PMd) influences neuroplasticity within the primary motor cortex (M1) through indirect (I) wave interneuronal circuits. However, it is unclear how the influence of PMd on the plasticity of M1 I-waves changes with advancing age. This study therefore investigated the neuroplastic effects of intermittent theta burst stimulation (iTBS) to M1 early and late I-wave circuits when preceded by iTBS (PMd iTBS-M1 iTBS) or sham stimulation (PMd sham-M1 iTBS) to PMd in 15 young and 16 older adults. M1 excitability was assessed with motor evoked potentials (MEP) recorded from the right first dorsal interosseous using posterior-anterior (PA) and anterior-posterior (AP) current TMS at standard stimulation intensities (PA1mV, AP1mV) and reduced stimulation intensities (PA0.5mV, early I-waves; AP0.5mV, late I-waves). PMd iTBS-M1 iTBS lowered the expected facilitation of PA0.5mV (to M1 iTBS) in young and older adults (P = 0.009), whereas the intervention had no effect on AP0.5mV facilitation in either group (P = 0.305). The modulation of PA0.5mV following PMd iTBS-M1 iTBS may reflect a specific influence of PMd on different I-wave circuits that are involved in M1 plasticity within young and older adults.
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Affiliation(s)
- Wei-Yeh Liao
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia
| | - George M Opie
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia
| | - Ulf Ziemann
- Department of Neurology & Stroke, Eberhard Karls University of Tübingen, Tübingen, Germany
- Hertie-Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - John G Semmler
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia
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15
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Hess S, Yeshua M, Eisen A, Burnishev Y, Sultan E, Pell G, Hanlon CA, Weizman A, Zangen A, Roth Y, Moses E, Weiss D. Efficacy of rotational field TMS in major depressive disorder - A pilot study. Brain Stimul 2024; 17:907-910. [PMID: 39069126 DOI: 10.1016/j.brs.2024.07.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Accepted: 07/24/2024] [Indexed: 07/30/2024] Open
Affiliation(s)
- Shmuel Hess
- Lev Hasharon Mental Health Center, Tsur Moshe, Israel; Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Maor Yeshua
- Department of Psychology, Ben Gurion University in the Negev, Beer Sheva, Israel; Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
| | - Ami Eisen
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
| | - Yuri Burnishev
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel
| | - Elsa Sultan
- Geha Mental Health Center, Petah Tikva, Israel
| | - Gaby Pell
- Department of Life Sciences, Ben Gurion University in the Negev, Beer Sheva, Israel; BrainsWay Ltd, Jerusalem, Israel
| | - Colleen A Hanlon
- BrainsWay Ltd, Jerusalem, Israel; Wake Forest University School of Medicine, Winston Salem, USA
| | - Abraham Weizman
- Geha Mental Health Center, Petah Tikva, Israel; Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Abraham Zangen
- Department of Life Sciences, Ben Gurion University in the Negev, Beer Sheva, Israel
| | - Yiftach Roth
- Department of Life Sciences, Ben Gurion University in the Negev, Beer Sheva, Israel; BrainsWay Ltd, Jerusalem, Israel
| | - Elisha Moses
- Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot, Israel.
| | - Dror Weiss
- Geha Mental Health Center, Petah Tikva, Israel; Faculty of Medicine and Health Sciences, Tel Aviv University, Tel Aviv, Israel
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16
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Qi Z, Noetscher GM, Miles A, Weise K, Knosche T, Cadman CR, Potashinsky AR, Liu K, Wartman WA, Nunez Ponasso GC, Bikson M, Lu H, Deng ZD, Nummenmaa A, Makaroff SN. Enabling Electric Field Modeling of Microscopically Realistic Brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.04.588004. [PMID: 38645100 PMCID: PMC11030228 DOI: 10.1101/2024.04.04.588004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Across all domains of brain stimulation (neuromodulation), conventional analysis of neuron activation involves two discrete steps: i) prediction of macroscopic electric field, ignoring presence of cells and; ii) prediction of cell activation from tissue electric fields. The first step assumes that current flow is not distorted by the dense tortuous network of cell structures. The deficiencies of this assumption have long been recognized, but - except for trivial geometries - ignored, because it presented intractable computation hurdles. This study introduces a novel approach for analyzing electric fields within a microscopically realistic brain volume. Our pipeline overcomes the technical intractability that prevented such analysis while also showing significant implications for brain stimulation. Contrary to the standard finite element method (FEM), we suggest using a nested iterative boundary element method (BEM) coupled with the fast multipole method (FMM). This approach allows for solving problems with multiple length scales more efficiently. A target application is a subvolume of the L2/3 P36 mouse primary visual cortex containing approximately 400 detailed densely packed neuronal cells at a resolution of 100 nm, which is obtained from scanning electron microscopy data. Our immediate result is a reduction of the stimulation field strength necessary for neuron activation by a factor of 0.85-0.55 (by 15%-45%) as compared to macroscopic predictions. This is in line with modern experimental data stating that existing macroscopic theories substantially overestimate electric field levels necessary for brain stimulation.
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17
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Harquel S, Cadic-Melchior A, Morishita T, Fleury L, Witon A, Ceroni M, Brügger J, Meyer NH, Evangelista GG, Egger P, Beanato E, Menoud P, Van de Ville D, Micera S, Blanke O, Léger B, Adolphsen J, Jagella C, Constantin C, Alvarez V, Vuadens P, Turlan JL, Mühl A, Bonvin C, Koch PJ, Wessel MJ, Hummel FC. Stroke Recovery-Related Changes in Cortical Reactivity Based on Modulation of Intracortical Inhibition. Stroke 2024; 55:1629-1640. [PMID: 38639087 DOI: 10.1161/strokeaha.123.045174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 02/29/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Cortical excitation/inhibition dynamics have been suggested as a key mechanism occurring after stroke. Their supportive or maladaptive role in the course of recovery is still not completely understood. Here, we used transcranial magnetic stimulation (TMS)-electroencephalography coupling to study cortical reactivity and intracortical GABAergic inhibition, as well as their relationship to residual motor function and recovery longitudinally in patients with stroke. METHODS Electroencephalography responses evoked by TMS applied to the ipsilesional motor cortex were acquired in patients with stroke with upper limb motor deficit in the acute (1 week), early (3 weeks), and late subacute (3 months) stages. Readouts of cortical reactivity, intracortical inhibition, and complexity of the evoked dynamics were drawn from TMS-evoked potentials induced by single-pulse and paired-pulse TMS (short-interval intracortical inhibition). Residual motor function was quantified through a detailed motor evaluation. RESULTS From 76 patients enrolled, 66 were included (68.2±13.2 years old, 18 females), with a Fugl-Meyer score of the upper extremity of 46.8±19. The comparison with TMS-evoked potentials of healthy older revealed that most affected patients exhibited larger and simpler brain reactivity patterns (Pcluster<0.05). Bayesian ANCOVA statistical evidence for a link between abnormally high motor cortical excitability and impairment level. A decrease in excitability in the following months was significantly correlated with better motor recovery in the whole cohort and the subgroup of recovering patients. Investigation of the intracortical GABAergic inhibitory system revealed the presence of beneficial disinhibition in the acute stage, followed by a normalization of inhibitory activity. This was supported by significant correlations between motor scores and the contrast of local mean field power and readouts of signal dynamics. CONCLUSIONS The present results revealed an abnormal motor cortical reactivity in patients with stroke, which was driven by perturbations and longitudinal changes within the intracortical inhibition system. They support the view that disinhibition in the ipsilesional motor cortex during the first-week poststroke is beneficial and promotes neuronal plasticity and recovery.
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Affiliation(s)
- Sylvain Harquel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Andéol Cadic-Melchior
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Takuya Morishita
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Lisa Fleury
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Adrien Witon
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Health-IT, Centre de Service, Hôpital du Valais, Switzerland (A.W.)
| | - Martino Ceroni
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Julia Brügger
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Nathalie H Meyer
- Laboratory of Cognitive Neuroscience, INX and BMI, EPFL, Geneva, Switzerland (N.H.M., O.B.)
| | - Giorgia G Evangelista
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Philip Egger
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Elena Beanato
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Pauline Menoud
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
| | - Dimitri Van de Ville
- Medical Image Processing Laboratory, INX, EPFL, Geneva, Switzerland (D.V.V.)
- Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Switzerland (D.V.d.V.)
| | - Silvestro Micera
- The Biorobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy (S.M.)
- Bertarelli Foundation Chair in Translational Neuroengineering, INX and Institute of Bioengineering, School of Engineering, Ecole Polytechnique Fédérale de Lausanne (S.M.)
| | - Olaf Blanke
- Laboratory of Cognitive Neuroscience, INX and BMI, EPFL, Geneva, Switzerland (N.H.M., O.B.)
- Department of Neurology, Geneva University Hospital (HUG), Switzerland (O.B.)
| | - Bertrand Léger
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | | | | | | | - Vincent Alvarez
- Department of Neurology, Hôpital du Valais, Sion, Switzerland (C.C., V.A., C.B.)
| | - Philippes Vuadens
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | - Jean-Luc Turlan
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | - Andreas Mühl
- Clinique Romande de Réadaptation, Sion, Switzerland (B.L., P.V., J.-L.T., A.M.)
| | - Christophe Bonvin
- Department of Neurology, Hôpital du Valais, Sion, Switzerland (C.C., V.A., C.B.)
| | - Philipp J Koch
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Department of Neurology, University of Lübeck, Germany (P.J.K.)
| | - Maximilian J Wessel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Department of Neurology, Julius-Maximilians-University Würzburg, Germany (M.J.W.)
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland (S.H., A.C.-M., T.M., L.F., A.W., M.C., J.B., G.G.E., P.E., E.B., P.M., P.J.K., M.J.W., F.C.H.)
- Clinical Neuroscience, Geneva University Hospital, Switzerland (F.C.H.)
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18
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Lenizky MW, Meehan SK. The effects of verbal and spatial working memory on short- and long-latency sensorimotor circuits in the motor cortex. PLoS One 2024; 19:e0302989. [PMID: 38753604 PMCID: PMC11098330 DOI: 10.1371/journal.pone.0302989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/17/2024] [Indexed: 05/18/2024] Open
Abstract
Multiple sensorimotor loops converge in the motor cortex to create an adaptable system capable of context-specific sensorimotor control. Afferent inhibition provides a non-invasive tool to investigate the substrates by which procedural and cognitive control processes interact to shape motor corticospinal projections. Varying the transcranial magnetic stimulation properties during afferent inhibition can probe specific sensorimotor circuits that contribute to short- and long-latency periods of inhibition in response to the peripheral stimulation. The current study used short- (SAI) and long-latency (LAI) afferent inhibition to probe the influence of verbal and spatial working memory load on the specific sensorimotor circuits recruited by posterior-anterior (PA) and anterior-posterior (AP) TMS-induced current. Participants completed two sessions where SAI and LAI were assessed during the short-term maintenance of two- or six-item sets of letters (verbal) or stimulus locations (spatial). The only difference between the sessions was the direction of the induced current. PA SAI decreased as the verbal working memory load increased. In contrast, AP SAI was not modulated by verbal working memory load. Visuospatial working memory load did not affect PA or AP SAI. Neither PA LAI nor AP LAI were sensitive to verbal or spatial working memory load. The dissociation of short-latency PA and AP sensorimotor circuits and short- and long-latency PA sensorimotor circuits with increasing verbal working memory load support multiple convergent sensorimotor loops that provide distinct functional information to facilitate context-specific supraspinal control.
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Affiliation(s)
- Markus W. Lenizky
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
| | - Sean K. Meehan
- Department of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
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19
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Pruitt T, Davenport EM, Proskovec AL, Maldjian JA, Liu H. Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation. Front Neurosci 2024; 18:1368172. [PMID: 38817913 PMCID: PMC11137218 DOI: 10.3389/fnins.2024.1368172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 04/22/2024] [Indexed: 06/01/2024] Open
Abstract
Introduction Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain. Methods MEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05). Results The 8-min tPBM enabled significant increases in alpha (8-12 Hz) and beta (13-30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side. Discussion MEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.
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Affiliation(s)
- Tyrell Pruitt
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | | | - Amy L. Proskovec
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | - Joseph A. Maldjian
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
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20
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Wang B, Peterchev AV, Gaugain G, Ilmoniemi RJ, Grill WM, Bikson M, Nikolayev D. Quasistatic approximation in neuromodulation. ARXIV 2024:arXiv:2402.00486v5. [PMID: 38351938 PMCID: PMC10862934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
We define and explain the quasistatic approximation (QSA) as applied to field modeling for electrical and magnetic stimulation. Neuromodulation analysis pipelines include discrete stages, and QSA is applied specifically when calculating the electric and magnetic fields generated in tissues by a given stimulation dose. QSA simplifies the modeling equations to support tractable analysis, enhanced understanding, and computational efficiency. The application of QSA in neuro-modulation is based on four underlying assumptions: (A1) no wave propagation or self-induction in tissue, (A2) linear tissue properties, (A3) purely resistive tissue, and (A4) non-dispersive tissue. As a consequence of these assumptions, each tissue is assigned a fixed conductivity, and the simplified equations (e.g., Laplace's equation) are solved for the spatial distribution of the field, which is separated from the field's temporal waveform. Recognizing that electrical tissue properties may be more complex, we explain how QSA can be embedded in parallel or iterative pipelines to model frequency dependence or nonlinearity of conductivity. We survey the history and validity of QSA across specific applications, such as microstimulation, deep brain stimulation, spinal cord stimulation, transcranial electrical stimulation, and transcranial magnetic stimulation. The precise definition and explanation of QSA in neuromodulation are essential for rigor when using QSA models or testing their limits.
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21
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Galanis C, Neuhaus L, Hananeia N, Turi Z, Jedlicka P, Vlachos A. Axon morphology and intrinsic cellular properties determine repetitive transcranial magnetic stimulation threshold for plasticity. Front Cell Neurosci 2024; 18:1374555. [PMID: 38638302 PMCID: PMC11025360 DOI: 10.3389/fncel.2024.1374555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 03/13/2024] [Indexed: 04/20/2024] Open
Abstract
Introduction Repetitive transcranial magnetic stimulation (rTMS) is a widely used therapeutic tool in neurology and psychiatry, but its cellular and molecular mechanisms are not fully understood. Standardizing stimulus parameters, specifically electric field strength, is crucial in experimental and clinical settings. It enables meaningful comparisons across studies and facilitates the translation of findings into clinical practice. However, the impact of biophysical properties inherent to the stimulated neurons and networks on the outcome of rTMS protocols remains not well understood. Consequently, achieving standardization of biological effects across different brain regions and subjects poses a significant challenge. Methods This study compared the effects of 10 Hz repetitive magnetic stimulation (rMS) in entorhino-hippocampal tissue cultures from mice and rats, providing insights into the impact of the same stimulation protocol on similar neuronal networks under standardized conditions. Results We observed the previously described plastic changes in excitatory and inhibitory synaptic strength of CA1 pyramidal neurons in both mouse and rat tissue cultures, but a higher stimulation intensity was required for the induction of rMS-induced synaptic plasticity in rat tissue cultures. Through systematic comparison of neuronal structural and functional properties and computational modeling, we found that morphological parameters of CA1 pyramidal neurons alone are insufficient to explain the observed differences between the groups. Although morphologies of mouse and rat CA1 neurons showed no significant differences, simulations confirmed that axon morphologies significantly influence individual cell activation thresholds. Notably, differences in intrinsic cellular properties were sufficient to account for the 10% higher intensity required for the induction of synaptic plasticity in the rat tissue cultures. Conclusion These findings demonstrate the critical importance of axon morphology and intrinsic cellular properties in predicting the plasticity effects of rTMS, carrying valuable implications for the development of computer models aimed at predicting and standardizing the biological effects of rTMS.
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Affiliation(s)
- Christos Galanis
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Lena Neuhaus
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Nicholas Hananeia
- 3R-Zentrum Gießen, Justus-Liebig-Universitat Giessen, Giessen, Germany
| | - Zsolt Turi
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Peter Jedlicka
- 3R-Zentrum Gießen, Justus-Liebig-Universitat Giessen, Giessen, Germany
| | - Andreas Vlachos
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
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22
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Haggie L, Besier T, McMorland A. Circuits in the motor cortex explain oscillatory responses to transcranial magnetic stimulation. Netw Neurosci 2024; 8:96-118. [PMID: 38562291 PMCID: PMC10861165 DOI: 10.1162/netn_a_00341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/11/2023] [Indexed: 04/04/2024] Open
Abstract
Transcranial magnetic stimulation (TMS) is a popular method used to investigate brain function. Stimulation over the motor cortex evokes muscle contractions known as motor evoked potentials (MEPs) and also high-frequency volleys of electrical activity measured in the cervical spinal cord. The physiological mechanisms of these experimentally derived responses remain unclear, but it is thought that the connections between circuits of excitatory and inhibitory neurons play a vital role. Using a spiking neural network model of the motor cortex, we explained the generation of waves of activity, so called 'I-waves', following cortical stimulation. The model reproduces a number of experimentally known responses including direction of TMS, increased inhibition, and changes in strength. Using populations of thousands of neurons in a model of cortical circuitry we showed that the cortex generated transient oscillatory responses without any tuning, and that neuron parameters such as refractory period and delays influenced the pattern and timing of those oscillations. By comparing our network with simpler, previously proposed circuits, we explored the contributions of specific connections and found that recurrent inhibitory connections are vital in producing later waves that significantly impact the production of motor evoked potentials in downstream muscles (Thickbroom, 2011). This model builds on previous work to increase our understanding of how complex circuitry of the cortex is involved in the generation of I-waves.
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Affiliation(s)
- Lysea Haggie
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Thor Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Angus McMorland
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Exercise Sciences, University of Auckland, Auckland, New Zealand
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23
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Cerri DH, Albaugh DL, Walton LR, Katz B, Wang TW, Chao THH, Zhang W, Nonneman RJ, Jiang J, Lee SH, Etkin A, Hall CN, Stuber GD, Shih YYI. Distinct neurochemical influences on fMRI response polarity in the striatum. Nat Commun 2024; 15:1916. [PMID: 38429266 PMCID: PMC10907631 DOI: 10.1038/s41467-024-46088-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 02/13/2024] [Indexed: 03/03/2024] Open
Abstract
The striatum, known as the input nucleus of the basal ganglia, is extensively studied for its diverse behavioral roles. However, the relationship between its neuronal and vascular activity, vital for interpreting functional magnetic resonance imaging (fMRI) signals, has not received comprehensive examination within the striatum. Here, we demonstrate that optogenetic stimulation of dorsal striatal neurons or their afferents from various cortical and subcortical regions induces negative striatal fMRI responses in rats, manifesting as vasoconstriction. These responses occur even with heightened striatal neuronal activity, confirmed by electrophysiology and fiber-photometry. In parallel, midbrain dopaminergic neuron optogenetic modulation, coupled with electrochemical measurements, establishes a link between striatal vasodilation and dopamine release. Intriguingly, in vivo intra-striatal pharmacological manipulations during optogenetic stimulation highlight a critical role of opioidergic signaling in generating striatal vasoconstriction. This observation is substantiated by detecting striatal vasoconstriction in brain slices after synthetic opioid application. In humans, manipulations aimed at increasing striatal neuronal activity likewise elicit negative striatal fMRI responses. Our results emphasize the necessity of considering vasoactive neurotransmission alongside neuronal activity when interpreting fMRI signal.
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Affiliation(s)
- Domenic H Cerri
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daniel L Albaugh
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lindsay R Walton
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brittany Katz
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Wen Wang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tzu-Hao Harry Chao
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Weiting Zhang
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Randal J Nonneman
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jing Jiang
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Sung-Ho Lee
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
- Alto Neuroscience, Los Altos, CA, USA
| | - Catherine N Hall
- Sussex Neuroscience, University of Sussex, Falmer, United Kingdom
- School of Psychology, University of Sussex, Falmer, United Kingdom
| | - Garret D Stuber
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Department of Pharmacology, University of Washington, Seattle, WA, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Biomedical Research Imaging Center, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Neurology, the University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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24
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Wischnewski M, Tran H, Zhao Z, Shirinpour S, Haigh ZJ, Rotteveel J, Perera ND, Alekseichuk I, Zimmermann J, Opitz A. Induced neural phase precession through exogenous electric fields. Nat Commun 2024; 15:1687. [PMID: 38402188 PMCID: PMC10894208 DOI: 10.1038/s41467-024-45898-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 02/06/2024] [Indexed: 02/26/2024] Open
Abstract
The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.
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Affiliation(s)
- Miles Wischnewski
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA.
| | - Harry Tran
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Zhihe Zhao
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Sina Shirinpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Zachary J Haigh
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Jonna Rotteveel
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Nipun D Perera
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Ivan Alekseichuk
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Jan Zimmermann
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA.
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25
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Christova M, Sylwester V, Gallasch E, Fresnoza S. Reduced Cerebellar Brain Inhibition and Vibrotactile Perception in Response to Mechanical Hand Stimulation at Flutter Frequency. CEREBELLUM (LONDON, ENGLAND) 2024; 23:67-81. [PMID: 36502502 PMCID: PMC10864223 DOI: 10.1007/s12311-022-01502-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/30/2022] [Indexed: 12/14/2022]
Abstract
The cerebellum is traditionally considered a movement control structure because of its established afferent and efferent anatomical and functional connections with the motor cortex. In the last decade, studies also proposed its involvement in perception, particularly somatosensory acquisition and prediction of the sensory consequences of movement. However, compared to its role in motor control, the cerebellum's specific role or modulatory influence on other brain areas involved in sensory perception, specifically the primary sensorimotor cortex, is less clear. In the present study, we explored whether peripherally applied vibrotactile stimuli at flutter frequency affect functional cerebello-cortical connections. In 17 healthy volunteers, changes in cerebellar brain inhibition (CBI) and vibration perception threshold (VPT) were measured before and after a 20-min right hand mechanical stimulation at 25 Hz. 5 Hz mechanical stimulation of the right foot served as an active control condition. Performance in a Grooved Pegboard test (GPT) was also measured to assess stimulation's impact on motor performance. Hand stimulation caused a reduction in CBI (13.16%) and increased VPT but had no specific effect on GPT performance, while foot stimulation had no significant effect on all measures. The result added evidence to the functional connections between the cerebellum and primary motor cortex, as shown by CBI reduction. Meanwhile, the parallel increase in VPT indirectly suggests that the cerebellum influences the processing of vibrotactile stimulus through motor-sensory interactions.
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Affiliation(s)
- Monica Christova
- Otto Loewi Research Center, Physiology Section, Medical University of Graz, Neue Stiftingtalstraße 6/D05, 8010, Graz, Austria.
- Institute of Physiotherapy, University of Applied Sciences FH-Joanneum, Graz, Austria.
| | | | - Eugen Gallasch
- Otto Loewi Research Center, Physiology Section, Medical University of Graz, Neue Stiftingtalstraße 6/D05, 8010, Graz, Austria
| | - Shane Fresnoza
- Institute of Psychology, University of Graz, Graz, Austria
- BioTechMed, Graz, Austria
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26
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Desmons M, Cherif A, Rohel A, de Oliveira FCL, Mercier C, Massé-Alarie H. Corticomotor Control of Lumbar Erector Spinae in Postural and Voluntary Tasks: The Influence of Transcranial Magnetic Stimulation Current Direction. eNeuro 2024; 11:ENEURO.0454-22.2023. [PMID: 38167617 PMCID: PMC10883751 DOI: 10.1523/eneuro.0454-22.2023] [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: 10/28/2022] [Revised: 11/30/2023] [Accepted: 12/16/2023] [Indexed: 01/05/2024] Open
Abstract
Lumbar erector spinae (LES) contribute to spine postural and voluntary control. Transcranial magnetic stimulation (TMS) preferentially depolarizes different neural circuits depending on the direction of electrical currents evoked in the brain. Posteroanterior current (PA-TMS) and anteroposterior (AP-TMS) current would, respectively, depolarize neurons in the primary motor cortex (M1) and the premotor cortex. These regions may contribute differently to LES control. This study examined whether responses evoked by PA- and AP-TMS are different during the preparation and execution of LES voluntary and postural tasks. Participants performed a reaction time task. A Warning signal indicated to prepare to flex shoulders (postural; n = 15) or to tilt the pelvis (voluntary; n = 13) at the Go signal. Single- and paired-pulse TMS (short-interval intracortical inhibition-SICI) were applied using PA- and AP-TMS before the Warning signal (baseline), between the Warning and Go signals (preparation), or 30 ms before the LES onset (execution). Changes from baseline during preparation and execution were calculated in AP/PA-TMS. In the postural task, MEP amplitude was higher during the execution than that during preparation independently of the current direction (p = 0.0002). In the voluntary task, AP-MEP amplitude was higher during execution than that during preparation (p = 0.016). More PA inhibition (SICI) was observed in execution than that in preparation (p = 0.028). Different neural circuits are preferentially involved in the two motor tasks assessed, as suggested by different patterns of change in execution of the voluntary task (AP-TMS, increase; PA-TMS, no change). Considering that PA-TMS preferentially depolarize neurons in M1, it questions their importance in LES voluntary control.
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Affiliation(s)
- Mikaël Desmons
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), CIUSSS de la Capitale-Nationale, Quebec City, Quebec G1M 2S8, Canada
- Rehabilitation Department, University Laval, Quebec City, Quebec G1V 0A6, Canada, G1V 0A6
| | - Amira Cherif
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), CIUSSS de la Capitale-Nationale, Quebec City, Quebec G1M 2S8, Canada
- Rehabilitation Department, University Laval, Quebec City, Quebec G1V 0A6, Canada, G1V 0A6
| | - Antoine Rohel
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), CIUSSS de la Capitale-Nationale, Quebec City, Quebec G1M 2S8, Canada
- Rehabilitation Department, University Laval, Quebec City, Quebec G1V 0A6, Canada, G1V 0A6
| | - Fábio Carlos Lucas de Oliveira
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), CIUSSS de la Capitale-Nationale, Quebec City, Quebec G1M 2S8, Canada
- Rehabilitation Department, University Laval, Quebec City, Quebec G1V 0A6, Canada, G1V 0A6
| | - Catherine Mercier
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), CIUSSS de la Capitale-Nationale, Quebec City, Quebec G1M 2S8, Canada
- Rehabilitation Department, University Laval, Quebec City, Quebec G1V 0A6, Canada, G1V 0A6
| | - Hugo Massé-Alarie
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), CIUSSS de la Capitale-Nationale, Quebec City, Quebec G1M 2S8, Canada
- Rehabilitation Department, University Laval, Quebec City, Quebec G1V 0A6, Canada, G1V 0A6
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Hehl M, Van Malderen S, Geraerts M, Meesen RLJ, Rothwell JC, Swinnen SP, Cuypers K. Probing intrahemispheric interactions with a novel dual-site TMS setup. Clin Neurophysiol 2024; 158:180-195. [PMID: 38232610 DOI: 10.1016/j.clinph.2023.12.128] [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: 10/24/2023] [Revised: 12/02/2023] [Accepted: 12/19/2023] [Indexed: 01/19/2024]
Abstract
OBJECTIVE Using dual-site transcranial magnetic stimulation (dsTMS), the effective connectivity between the primary motor cortex (M1) and adjacent brain areas such as the dorsal premotor cortex (PMd) can be investigated. However, stimulating two brain regions in close proximity (e.g., ±2.3 cm for intrahemispheric PMd-M1) is subject to considerable spatial restrictions that potentially can be overcome by combining two standard figure-of-eight coils in a novel dsTMS setup. METHODS After a technical evaluation of its induced electric fields, the dsTMS setup was tested in vivo (n = 23) by applying a short-interval intracortical inhibition (SICI) protocol. Additionally, the intrahemispheric PMd-M1 interaction was probed. E-field modelling was performed using SimNIBS. RESULTS The technical evaluation yielded no major alterations of the induced electric fields due to coil overlap. In vivo, the setup reliably elicited SICI. Investigating intrahemispheric PMd-M1 interactions was feasible (inter-stimulus interval 6 ms), resulting in modulation of M1 output. CONCLUSIONS The presented dsTMS setup provides a novel way to stimulate two adjacent brain regions with fewer technical and spatial limitations than previous attempts. SIGNIFICANCE This dsTMS setup enables more accurate and repeatable targeting of brain regions in close proximity and can facilitate innovation in the field of effective connectivity.
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Affiliation(s)
- Melina Hehl
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - Shanti Van Malderen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - Marc Geraerts
- Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - Raf L J Meesen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium
| | - John C Rothwell
- Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, London, United Kingdom
| | - Stephan P Swinnen
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium
| | - Koen Cuypers
- Movement Control & Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, 3001 Heverlee, Belgium; KU Leuven, Leuven Brain Institute (LBI), Leuven, Belgium; Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium.
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Noetscher GM, Tang D, Nummenmaa AR, Bingham CS, McIntyre CC, Makaroff SN. Estimations of Charge Deposition Onto Convoluted Axon Surfaces Within Extracellular Electric Fields. IEEE Trans Biomed Eng 2024; 71:307-317. [PMID: 37535481 PMCID: PMC10837334 DOI: 10.1109/tbme.2023.3299734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
OBJECTIVE Biophysical models of neural stimulation are a valuable approach to explaining the mechanisms of neuronal recruitment via applied extracellular electric fields. Typically, the applied electric field is estimated via a macroscopic finite element method solution and then applied to cable models as an extracellular voltage source. However, the field resolution is limited by the finite element size (typically 10's-100's of times greater than average neuronal cross-section). As a result, induced charges deposited onto anatomically realistic curved membrane interfaces are not taken into consideration. However, these details may alter estimates of the applied electric field and predictions of neural tissue activation. METHODS To estimate microscopic variations of the electric field, data for intra-axonal space segmented from 3D scanning electron microscopy of the mouse brain genu of corpus callosum were used. The boundary element fast multipole method was applied to accurately compute the extracellular solution. Neuronal recruitment was then estimated via an activating function. RESULTS Taking the physical structure of the arbor into account generally predicts higher values of the activating function. The relative integral 2-norm difference is 90% on average when the entire axonal arbor is present. A large fraction of this difference might be due to the axonal body itself. When an isolated physical axon is considered with all other axons removed, the relative integral 2-norm difference between the single-axon solution and the complete solution is 25% on average. CONCLUSION Our result may provide an explanation as to why Deep Brain Stimulation experiments typically predict lower activation thresholds than commonly used FEM/Cable model approaches to predicting neuronal responses to extracellular electrical stimulation. SIGNIFICANCE These results may change methods for bi-domain neural modeling and neural excitation.
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Matilainen N, Kataja J, Laakso I. Predicting the hotspot location and motor threshold prior to transcranial magnetic stimulation using electric field modelling. Phys Med Biol 2023; 69:015012. [PMID: 37816371 DOI: 10.1088/1361-6560/ad0219] [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: 05/26/2023] [Accepted: 10/10/2023] [Indexed: 10/12/2023]
Abstract
Objective.To investigate whether the motor threshold (MT) and the location of the motor hotspot in transcranial magnetic stimulation (TMS) can be predicted with computational models of the induced electric field.Approach.Individualized computational models were constructed from structural magnetic resonance images of ten healthy participants, and the induced electric fields were determined with the finite element method. The models were used to optimize the location and direction of the TMS coil on the scalp to produce the largest electric field at a predetermined cortical target location. The models were also used to predict how the MT changes as the magnetic coil is moved to various locations over the scalp. To validate the model predictions, the motor evoked potentials were measured from the first dorsal interosseous (FDI) muscle with TMS in the ten participants. Both computational and experimental methods were preregistered prior to the experiments.Main results.Computationally optimized hotspot locations were nearly as accurate as those obtained using manual hotspot search procedures. The mean Euclidean distance between the predicted and the measured hotspot locations was approximately 1.3 cm with a 0.8 cm bias towards the anterior direction. Exploratory analyses showed that the bias could be removed by changing the cortical target location that was used for the prediction. The results also indicated a statistically significant relationship (p< 0.001) between the calculated electric field and the MT measured at several locations on the scalp.Significance.The results show that the individual TMS hotspot can be located using computational analysis without stimulating the subject or patient even once. Adapting computational modelling would save time and effort in research and clinical use of TMS.
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Affiliation(s)
- Noora Matilainen
- Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
| | - Juhani Kataja
- Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
| | - Ilkka Laakso
- Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland
- Aalto Neuroimaging, Aalto University, Espoo, Finland
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Hasan NI, Wang D, Gomez LJ. Fast and accurate computational E-field dosimetry for group-level transcranial magnetic stimulation targeting. Comput Biol Med 2023; 167:107614. [PMID: 37913615 PMCID: PMC10880124 DOI: 10.1016/j.compbiomed.2023.107614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/11/2023] [Accepted: 10/23/2023] [Indexed: 11/03/2023]
Abstract
Transcranial magnetic stimulation (TMS) is used to study brain function and treat mental health disorders. During TMS, a coil placed on the scalp induces an E-field in the brain that modulates its activity. TMS is known to stimulate regions that are exposed to a large E-field. Clinical TMS protocols prescribe a coil placement based on scalp landmarks. There are inter-individual variations in brain anatomy that result in variations in the TMS-induced E-field at the targeted region and its outcome. These variations across individuals could in principle be minimized by developing a large database of head subjects and determining scalp landmarks that maximize E-field at the targeted brain region while minimizing its variation using computational methods. However, this approach requires repeated execution of a computational method to determine the E-field induced in the brain for a large number of subjects and coil placements. We developed a probabilistic matrix decomposition-based approach for rapidly evaluating the E-field induced during TMS for a large number of coil placements due to a pre-defined coil model. Our approach can determine the E-field induced in over 1 Million coil placements in 9.5 h, in contrast, to over 5 years using a brute-force approach. After the initial set-up stage, the E-field can be predicted over the whole brain within 2-3 ms and to 2% accuracy. We tested our approach in over 200 subjects and achieved an error of <2% in most and <3.5% in all subjects. We will present several examples of bench-marking analysis for our tool in terms of accuracy and speed. Furthermore, we will show the methods' applicability for group-level optimization of coil placement for illustration purposes only. The software implementation link is provided in the appendix.
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Affiliation(s)
- Nahian I Hasan
- Elmore Family School of Electrical and Computer Engineering, Purdue University, 465, Northwestern Ave, West Lafayette, 47907, IN, USA.
| | - Dezhi Wang
- Elmore Family School of Electrical and Computer Engineering, Purdue University, 465, Northwestern Ave, West Lafayette, 47907, IN, USA.
| | - Luis J Gomez
- Elmore Family School of Electrical and Computer Engineering, Purdue University, 465, Northwestern Ave, West Lafayette, 47907, IN, USA.
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Anil S, Lu H, Rotter S, Vlachos A. Repetitive transcranial magnetic stimulation (rTMS) triggers dose-dependent homeostatic rewiring in recurrent neuronal networks. PLoS Comput Biol 2023; 19:e1011027. [PMID: 37956202 PMCID: PMC10681319 DOI: 10.1371/journal.pcbi.1011027] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 11/27/2023] [Accepted: 10/11/2023] [Indexed: 11/15/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique used to induce neuronal plasticity in healthy individuals and patients. Designing effective and reproducible rTMS protocols poses a major challenge in the field as the underlying biomechanisms of long-term effects remain elusive. Current clinical protocol designs are often based on studies reporting rTMS-induced long-term potentiation or depression of synaptic transmission. Herein, we employed computational modeling to explore the effects of rTMS on long-term structural plasticity and changes in network connectivity. We simulated a recurrent neuronal network with homeostatic structural plasticity among excitatory neurons, and demonstrated that this mechanism was sensitive to specific parameters of the stimulation protocol (i.e., frequency, intensity, and duration of stimulation). Particularly, the feedback-inhibition initiated by network stimulation influenced the net stimulation outcome and hindered the rTMS-induced structural reorganization, highlighting the role of inhibitory networks. These findings suggest a novel mechanism for the lasting effects of rTMS, i.e., rTMS-induced homeostatic structural plasticity, and highlight the importance of network inhibition in careful protocol design, standardization, and optimization of stimulation.
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Affiliation(s)
- Swathi Anil
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Han Lu
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Center BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - Stefan Rotter
- Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
- Center BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - Andreas Vlachos
- Department of Neuroanatomy, Institute of Anatomy and Cell Biology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany
- Center BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
- Center for Basics in NeuroModulation (NeuroModulBasics), Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Van Hoornweder S, Nuyts M, Frieske J, Verstraelen S, Meesen RLJ, Caulfield KA. Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study. Neuroimage 2023; 281:120379. [PMID: 37716590 PMCID: PMC11008458 DOI: 10.1016/j.neuroimage.2023.120379] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/18/2023] [Accepted: 09/13/2023] [Indexed: 09/18/2023] Open
Abstract
BACKGROUND Electric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing. OBJECTIVES This two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures. METHODS Three electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals. RESULTS In the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model. CONCLUSIONS Outcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.
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Affiliation(s)
- Sybren Van Hoornweder
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium.
| | - Marten Nuyts
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium
| | - Joana Frieske
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium; Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
| | - Stefanie Verstraelen
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium
| | - Raf L J Meesen
- REVAL - Rehabilitation Research Center, Faculty of Rehabilitation Sciences, University of Hasselt, Diepenbeek, Belgium; Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
| | - Kevin A Caulfield
- Brain Stimulation Laboratory, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States.
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Aberra AS, Wang R, Grill WM, Peterchev AV. Multi-scale model of axonal and dendritic polarization by transcranial direct current stimulation in realistic head geometry. Brain Stimul 2023; 16:1776-1791. [PMID: 38056825 PMCID: PMC10842743 DOI: 10.1016/j.brs.2023.11.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 11/06/2023] [Accepted: 11/29/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation modality that can alter cortical excitability. However, it remains unclear how the subcellular elements of different neuron types are polarized by specific electric field (E-field) distributions. OBJECTIVE To quantify neuronal polarization generated by tDCS in a multi-scale computational model. METHODS We embedded layer-specific, morphologically-realistic cortical neuron models in a finite element model of the E-field in a human head and simulated steady-state polarization generated by conventional primary-motor-cortex-supraorbital (M1-SO) and 4 × 1 high-definition (HD) tDCS. We quantified somatic, axonal, and dendritic polarization of excitatory pyramidal cells in layers 2/3, 5, and 6, as well as inhibitory interneurons in layers 1 and 4 of the hand knob. RESULTS Axonal and dendritic terminals were polarized more than the soma in all neurons, with peak axonal and dendritic polarization of 0.92 mV and 0.21 mV, respectively, compared to peak somatic polarization of 0.07 mV for 1.8 mA M1-SO stimulation. Both montages generated regions of depolarization and hyperpolarization beneath the M1 anode; M1-SO produced slightly stronger, more diffuse polarization peaking in the central sulcus, while 4 × 1 HD produced higher peak polarization in the gyral crown. The E-field component normal to the cortical surface correlated strongly with pyramidal neuron somatic polarization (R2>0.9), but exhibited weaker correlations with peak pyramidal axonal and dendritic polarization (R2:0.5-0.9) and peak polarization in all subcellular regions of interneurons (R2:0.3-0.6). Simulating polarization by uniform local E-field extracted at the soma approximated the spatial distribution of tDCS polarization but produced large errors in some regions (median absolute percent error: 7.9 %). CONCLUSIONS Polarization of pre- and postsynaptic compartments of excitatory and inhibitory cortical neurons may play a significant role in tDCS neuromodulation. These effects cannot be predicted from the E-field distribution alone but rather require calculation of the neuronal response.
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Affiliation(s)
- Aman S Aberra
- Dept. of Biomedical Engineering, Pratt School of Engineering, Duke University, NC, USA.
| | - Ruochen Wang
- Dept. of Biomedical Engineering, Pratt School of Engineering, Duke University, NC, USA; Dept. of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, NC, USA.
| | - Warren M Grill
- Dept. of Biomedical Engineering, Pratt School of Engineering, Duke University, NC, USA; Dept. of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, NC, USA; Dept. of Neurobiology, School of Medicine, Duke University, NC, USA; Dept. of Neurosurgery, School of Medicine, Duke University, NC, USA.
| | - Angel V Peterchev
- Dept. of Biomedical Engineering, Pratt School of Engineering, Duke University, NC, USA; Dept. of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, NC, USA; Dept. of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, NC, USA; Dept. of Neurosurgery, School of Medicine, Duke University, NC, USA.
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Wischnewski M, Tran H, Zhao Z, Shirinpour S, Haigh Z, Rotteveel J, Perera N, Alekseichuk I, Zimmermann J, Opitz A. Induced neural phase precession through exogeneous electric fields. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.31.535073. [PMID: 37034780 PMCID: PMC10081336 DOI: 10.1101/2023.03.31.535073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/20/2023]
Abstract
The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.
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Affiliation(s)
- M. Wischnewski
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - H. Tran
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Z. Zhao
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - S. Shirinpour
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Z.J. Haigh
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - J. Rotteveel
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - N.D. Perera
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - I. Alekseichuk
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - J. Zimmermann
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - A. Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
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Galanis C, Neuhaus L, Hananeia N, Turi Z, Jedlicka P, Vlachos A. Axon morphology and intrinsic cellular properties determine repetitive transcranial magnetic stimulation threshold for plasticity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.25.559399. [PMID: 37808716 PMCID: PMC10557586 DOI: 10.1101/2023.09.25.559399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a widely used therapeutic tool in neurology and psychiatry, but its cellular and molecular mechanisms are not fully understood. Standardizing stimulus parameters, specifically electric field strength and direction, is crucial in experimental and clinical settings. It enables meaningful comparisons across studies and facilitating the translation of findings into clinical practice. However, the impact of biophysical properties inherent to the stimulated neurons and networks on the outcome of rTMS protocols remains not well understood. Consequently, achieving standardization of biological effects across different brain regions and subjects poses a significant challenge. This study compared the effects of 10 Hz repetitive magnetic stimulation (rMS) in entorhino-hippocampal tissue cultures from mice and rats, providing insights into the impact of the same stimulation protocol on similar neuronal networks under standardized conditions. We observed the previously described plastic changes in excitatory and inhibitory synaptic strength of CA1 pyramidal neurons in both mouse and rat tissue cultures, but a higher stimulation intensity was required for the induction of rMS-induced synaptic plasticity in rat tissue cultures. Through systematic comparison of neuronal structural and functional properties and computational modeling, we found that morphological parameters of CA1 pyramidal neurons alone are insufficient to explain the observed differences between the groups. However, axon morphologies of individual cells played a significant role in determining activation thresholds. Notably, differences in intrinsic cellular properties were sufficient to account for the 10 % higher intensity required for the induction of synaptic plasticity in the rat tissue cultures. These findings demonstrate the critical importance of axon morphology and intrinsic cellular properties in predicting the plasticity effects of rTMS, carrying valuable implications for the development of computer models aimed at predicting and standardizing the biological effects of rTMS.
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Hand BJ, Merkin A, Opie GM, Ziemann U, Semmler JG. Repetitive paired-pulse TMS increases motor cortex excitability and visuomotor skill acquisition in young and older adults. Cereb Cortex 2023; 33:10660-10675. [PMID: 37689833 PMCID: PMC10560576 DOI: 10.1093/cercor/bhad315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 08/13/2023] [Accepted: 08/15/2023] [Indexed: 09/11/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) over primary motor cortex (M1) recruits indirect (I) waves that can be modulated by repetitive paired-pulse TMS (rppTMS). The purpose of this study was to examine the effect of rppTMS on M1 excitability and visuomotor skill acquisition in young and older adults. A total of 37 healthy adults (22 young, 18-32 yr; 15 older, 60-79 yr) participated in a study that involved rppTMS at early (1.4 ms) and late (4.5 ms) interstimulus intervals (ISIs), followed by the performance of a visuomotor training task. M1 excitability was examined with motor-evoked potential (MEP) amplitudes and short-interval intracortical facilitation (SICF) using posterior-anterior (PA) and anterior-posterior (AP) TMS current directions. We found that rppTMS increased M1 excitability in young and old adults, with the greatest effects for PA TMS at the late ISI (4.5 ms). Motor skill acquisition was improved by rppTMS at an early (1.4 ms) but not late (4.5 ms) ISI in young and older adults. An additional study using a non-I-wave interval (3.5 ms) also showed increased M1 excitability and visuomotor skill acquisition. These findings show that rppTMS at both I-wave and non-I-wave intervals can alter M1 excitability and improve visuomotor skill acquisition in young and older adults.
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Affiliation(s)
- Brodie J Hand
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide 5005, Australia
| | - Ashley Merkin
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide 5005, Australia
| | - George M Opie
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide 5005, Australia
| | - Ulf Ziemann
- Department of Neurology & Stroke, and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen 72076, Germany
| | - John G Semmler
- Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide 5005, Australia
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Guidali G, Zazio A, Lucarelli D, Marcantoni E, Stango A, Barchiesi G, Bortoletto M. Effects of transcranial magnetic stimulation (TMS) current direction and pulse waveform on cortico-cortical connectivity: A registered report TMS-EEG study. Eur J Neurosci 2023; 58:3785-3809. [PMID: 37649453 DOI: 10.1111/ejn.16127] [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: 04/30/2023] [Revised: 07/14/2023] [Accepted: 08/04/2023] [Indexed: 09/01/2023]
Abstract
Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) are a promising proxy for measuring effective connectivity, that is, the directed transmission of physiological signals along cortico-cortical tracts, and for developing connectivity-based biomarkers. A crucial point is how stimulation parameters may affect TEPs, as they may contribute to the general variability of findings across studies. Here, we manipulated two TMS parameters (i.e. current direction and pulse waveform) while measuring (a) an early TEP component reflecting contralateral inhibition of motor areas, namely, M1-P15, as an operative model of interhemispheric cortico-cortical connectivity, and (b) motor-evoked potentials (MEP) for the corticospinal pathway. Our results showed that these two TMS parameters are crucial to evoke the M1-P15, influencing its amplitude, latency, and replicability. Specifically, (a) M1-P15 amplitude was strongly affected by current direction in monophasic stimulation; (b) M1-P15 latency was significantly modulated by current direction for monophasic and biphasic pulses. The replicability of M1-P15 was substantial for the same stimulation condition. At the same time, it was poor when stimulation parameters were changed, suggesting that these factors must be controlled to obtain stable single-subject measures. Finally, MEP latency was modulated by current direction, whereas non-statistically significant changes were evident for amplitude. Overall, our study highlights the importance of TMS parameters for early TEP responses recording and suggests controlling their impact in developing connectivity biomarkers from TEPs. Moreover, these results point out that the excitability of the corticospinal tract, which is commonly used as a reference to set TMS intensity, may not correspond to the excitability of cortico-cortical pathways.
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Affiliation(s)
- Giacomo Guidali
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Agnese Zazio
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Delia Lucarelli
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Eleonora Marcantoni
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Antonietta Stango
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Guido Barchiesi
- Department of Philosophy, University of Milano, Milan, Italy
| | - Marta Bortoletto
- Neurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
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Esmaeilzadeh Kiabani N, Kazemi R, Hadipour AL, Khomami S, Kalloch B, Hlawitschka M. Targeting the insula with transcranial direct current stimulation; A simulation study. Psychiatry Res Neuroimaging 2023; 335:111718. [PMID: 37738706 DOI: 10.1016/j.pscychresns.2023.111718] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 08/26/2023] [Accepted: 09/11/2023] [Indexed: 09/24/2023]
Abstract
Insula is considered an important region of the brain in the generation and maintenance of a wide range of psychiatric symptoms, possibly due to being key in fundamental functions such as interoception and cognition in general. Investigating the possibility of targeting this area using non-invasive brain stimulation techniques can open new possibilities to probe the normal and abnormal functioning of the brain and potentially new treatment protocols to alleviate symptoms of different psychiatric disorders. In the current study, COMETS2, a MATLAB based toolbox was used to simulate the magnitude of the current density and electric field in the brain caused by different transcranial direct current stimulation (tDCS) protocols to find an optimum montage to target the insula and its 6 subregions for three different current intensities, namely 2, 3, and 4 mA. Frontal and occipital regions were found to be optimal candidate regions.. The results of the current study showed that it is viable to reach the insula and its individual subregions using tDCS.
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Affiliation(s)
| | - Reza Kazemi
- Faculty of Entrepreneurship, University of Tehran, Tehran, Iran.
| | - Abed L Hadipour
- Department of Cognitive Sciences, University of Messina, Messina, Italy
| | - Sanaz Khomami
- Department of Psychology, South Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Benjamin Kalloch
- Max Planck Institute for Human Cognitive and Brain Sciences, Instiute of Biomedical Engineering and Informatics, Germany & Technische Universität Ilmenau, Ilmenau, Leipzig, Germany
| | - Mario Hlawitschka
- Faculty of Computer Science and Media, Leipzig University of Applied Science, Leipzig, Germany
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Wang B, Peterchev AV, Goetz SM. Three novel methods for determining motor threshold with transcranial magnetic stimulation outperform conventional procedures. J Neural Eng 2023; 20:10.1088/1741-2552/acf1cc. [PMID: 37595573 PMCID: PMC10516469 DOI: 10.1088/1741-2552/acf1cc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/18/2023] [Indexed: 08/20/2023]
Abstract
Objective. Thresholding of neural responses is central to many applications of transcranial magnetic stimulation (TMS), but the stochastic aspect of neuronal activity and motor evoked potentials (MEPs) challenges thresholding techniques. We analyzed existing methods for obtaining TMS motor threshold and their variations, introduced new methods from other fields, and compared their accuracy and speed.Approach. In addition to existing relative-frequency methods, such as the five-out-of-ten method, we examined adaptive methods based on a probabilistic motor threshold model using maximum-likelihood (ML) or maximuma-posteriori(MAP) estimation. To improve the performance of these adaptive estimation methods, we explored variations in the estimation procedure and inclusion of population-level prior information. We adapted a Bayesian estimation method which iteratively incorporated information of the TMS responses into the probability density function. A family of non-parametric stochastic root-finding methods with different convergence criteria and stepping rules were explored as well. The performance of the thresholding methods was evaluated with an independent stochastic MEP model.Main Results. The conventional relative-frequency methods required a large number of stimuli, were inherently biased on the population level, and had wide error distributions for individual subjects. The parametric estimation methods obtained the thresholds much faster and their accuracy depended on the estimation method, with performance significantly improved when population-level prior information was included. Stochastic root-finding methods were comparable to adaptive estimation methods but were much simpler to implement and did not rely on a potentially inaccurate underlying estimation model.Significance. Two-parameter MAP estimation, Bayesian estimation, and stochastic root-finding methods have better error convergence compared to conventional single-parameter ML estimation, and all these methods require significantly fewer TMS pulses for accurate estimation than conventional relative-frequency methods. Stochastic root-finding appears particularly attractive due to the low computational requirements, simplicity of the algorithmic implementation, and independence from potential model flaws in the parametric estimators.
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Affiliation(s)
- Boshuo Wang
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Angel V. Peterchev
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Biomedical Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, School of Medicine, Duke University, Durham, NC, USA
| | - Stefan M. Goetz
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, School of Medicine, Duke University, Durham, NC, USA
- Department of Engineering, School of Technology, University of Cambridge, Cambridge, UK
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Casarotto A, Dolfini E, Fadiga L, Koch G, D'Ausilio A. Cortico-cortical paired associative stimulation conditioning superficial ventral premotor cortex-primary motor cortex connectivity influences motor cortical activity during precision grip. J Physiol 2023; 601:3945-3960. [PMID: 37526070 DOI: 10.1113/jp284500] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
The ventral premotor cortex (PMv) and primary motor cortex (M1) represent critical nodes of a parietofrontal network involved in grasping actions, such as power and precision grip. Here, we investigated how the functional PMv-M1 connectivity drives the dissociation between these two actions. We applied a PMv-M1 cortico-cortical paired associative stimulation (cc-PAS) protocol, stimulating M1 in both postero-anterior (PA) and antero-posterior (AP) directions, in order to induce long-term changes in the activity of different neuronal populations within M1. We evaluated the motor-evoked potential (MEP) amplitude, MEP latency and cortical silent period, in both PA and AP, during the isometric execution of precision and power grip, before and after the PMv-M1 cc-PAS. The repeated activation of the PMv-M1 cortico-cortical network with PA orientation over M1 did not change MEP amplitude or cortical silent period duration during both actions. In contrast, the PMv-M1 cc-PAS stimulation of M1 with an AP direction led to a specific modulation of precision grip motor drive. In particular, MEPs tested with AP stimulation showed a selective increase of corticospinal excitability during precision grip. These findings suggest that the more superficial M1 neuronal populations recruited by the PMv input are involved preferentially in the execution of precision grip actions. KEY POINTS: Ventral premotor cortex (PMv)-primary motor cortex (M1) cortico-cortical paired associative stimulation (cc-PAS) with different coil orientation targets dissociable neural populations. PMv-M1 cc-PAS with M1 antero-posterior coil orientation specifically modulates corticospinal excitability during precision grip. Superficial M1 populations are involved preferentially in the execution of precision grip. A plasticity induction protocol targeting the specific PMv-M1 subpopulation might have important translational value for the rehabilitation of hand function.
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Affiliation(s)
- Andrea Casarotto
- IIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy
- Department of Neuroscience and Rehabilitation, Section of Physiology, Università di Ferrara, Ferrara, Italy
| | - Elisa Dolfini
- Department of Neuroscience and Rehabilitation, Section of Physiology, Università di Ferrara, Ferrara, Italy
| | - Luciano Fadiga
- IIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy
- Department of Neuroscience and Rehabilitation, Section of Physiology, Università di Ferrara, Ferrara, Italy
| | - Giacomo Koch
- IIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy
- Department of Neuroscience and Rehabilitation, Section of Physiology, Università di Ferrara, Ferrara, Italy
- Experimental Neuropsychophysiology Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - Alessandro D'Ausilio
- IIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy
- Department of Neuroscience and Rehabilitation, Section of Physiology, Università di Ferrara, Ferrara, Italy
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Aberra AS, Wang R, Grill WM, Peterchev AV. Multi-scale model of axonal and dendritic polarization by transcranial direct current stimulation in realistic head geometry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.23.554447. [PMID: 37767087 PMCID: PMC10522328 DOI: 10.1101/2023.08.23.554447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
Background Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation modality that can alter cortical excitability. However, it remains unclear how the subcellular elements of different neuron types are polarized by specific electric field (E-field) distributions. Objective To quantify neuronal polarization generated by tDCS in a multi-scale computational model. Methods We embedded layer-specific, morphologically-realistic cortical neuron models in a finite element model of the E-field in a human head and simulated steady-state polarization generated by conventional primary-motor-cortex-supraorbital (M1-SO) and 4×1 high-definition (HD) tDCS. We quantified somatic, axonal, and dendritic polarization of excitatory pyramidal cells in layers 2/3, 5, and 6, as well as inhibitory interneurons in layers 1 and 4 of the hand knob. Results Axonal and dendritic terminals were polarized more than the soma in all neurons, with peak axonal and dendritic polarization of 0.92 mV and 0.21 mV, respectively, compared to peak somatic polarization of 0.07 mV for 1.8 mA M1-SO stimulation. Both montages generated regions of depolarization and hyperpolarization beneath the M1 anode; M1-SO produced slightly stronger, more diffuse polarization peaking in the central sulcus, while 4×1 HD produced higher peak polarization in the gyral crown. Simulating polarization by uniform local E-field approximated the spatial distribution of tDCS polarization but produced large errors in some regions. Conclusions Polarization of pre- and postsynaptic compartments of excitatory and inhibitory cortical neurons may play a significant role in tDCS neuromodulation. These effects cannot be predicted from the E-field distribution alone but rather require calculation of the neuronal response.
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Cabrera-Álvarez J, Sánchez-Claros J, Carrasco-Gómez M, del Cerro-León A, Gómez-Ariza CJ, Maestú F, Mirasso CR, Susi G. Understanding the effects of cortical gyrification in tACS: insights from experiments and computational models. Front Neurosci 2023; 17:1223950. [PMID: 37655010 PMCID: PMC10467425 DOI: 10.3389/fnins.2023.1223950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/25/2023] [Indexed: 09/02/2023] Open
Abstract
The alpha rhythm is often associated with relaxed wakefulness or idling and is altered by various factors. Abnormalities in the alpha rhythm have been linked to several neurological and psychiatric disorders, including Alzheimer's disease. Transcranial alternating current stimulation (tACS) has been proposed as a potential tool to restore a disrupted alpha rhythm in the brain by stimulating at the individual alpha frequency (IAF), although some research has produced contradictory results. In this study, we applied an IAF-tACS protocol over parieto-occipital areas to a sample of healthy subjects and measured its effects over the power spectra. Additionally, we used computational models to get a deeper understanding of the results observed in the experiment. Both experimental and numerical results showed an increase in alpha power of 8.02% with respect to the sham condition in a widespread set of regions in the cortex, excluding some expected parietal regions. This result could be partially explained by taking into account the orientation of the electric field with respect to the columnar structures of the cortex, showing that the gyrification in parietal regions could generate effects in opposite directions (hyper-/depolarization) at the same time in specific brain regions. Additionally, we used a network model of spiking neuronal populations to explore the effects that these opposite polarities could have on neural activity, and we found that the best predictor of alpha power was the average of the normal components of the electric field. To sum up, our study sheds light on the mechanisms underlying tACS brain activity modulation, using both empirical and computational approaches. Non-invasive brain stimulation techniques hold promise for treating brain disorders, but further research is needed to fully understand and control their effects on brain dynamics and cognition. Our findings contribute to this growing body of research and provide a foundation for future studies aimed at optimizing the use of non-invasive brain stimulation in clinical settings.
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Affiliation(s)
- Jesús Cabrera-Álvarez
- Centre for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Jaime Sánchez-Claros
- Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC, UIB-CSIC), Campus UIB, Palma de Mallorca, Spain
| | - Martín Carrasco-Gómez
- Centre for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
| | - Alberto del Cerro-León
- Centre for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | | | - Fernando Maestú
- Centre for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Claudio R. Mirasso
- Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC, UIB-CSIC), Campus UIB, Palma de Mallorca, Spain
| | - Gianluca Susi
- Centre for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Structure of Matter, Thermal Physics and Electronics, School of Physics, Complutense University of Madrid, Madrid, Spain
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43
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Pérez-Benítez JA, Martínez-Ortiz P, Aguila-Muñoz J. A Review of Formulations, Boundary Value Problems and Solutions for Numerical Computation of Transcranial Magnetic Stimulation Fields. Brain Sci 2023; 13:1142. [PMID: 37626498 PMCID: PMC10452852 DOI: 10.3390/brainsci13081142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 07/22/2023] [Accepted: 07/24/2023] [Indexed: 08/27/2023] Open
Abstract
Since the inception of the transcranial magnetic stimulation (TMS) technique, it has become imperative to numerically compute the distribution of the electric field induced in the brain. Various models of the coil-brain system have been proposed for this purpose. These models yield a set of formulations and boundary conditions that can be employed to calculate the induced electric field. However, the literature on TMS simulation presents several of these formulations, leading to potential confusion regarding the interpretation and contribution of each source of electric field. The present study undertakes an extensive compilation of widely utilized formulations, boundary value problems and numerical solutions employed in TMS fields simulations, analyzing the advantages and disadvantages associated with each used formulation and numerical method. Additionally, it explores the implementation strategies employed for their numerical computation. Furthermore, this work provides numerical expressions that can be utilized for the numerical computation of TMS fields using the finite difference and finite element methods. Notably, some of these expressions are deduced within the present study. Finally, an overview of some of the most significant results obtained from numerical computation of TMS fields is presented. The aim of this work is to serve as a guide for future research endeavors concerning the numerical simulation of TMS.
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Affiliation(s)
- J. A. Pérez-Benítez
- Laboratorio de Bio-Electromagnetismo, ESIME-SEPI, Edif. Z-4, Instituto Politécnico Nacional, Mexico City 07738, CDMX, Mexico;
| | - P. Martínez-Ortiz
- Laboratorio de Bio-Electromagnetismo, ESIME-SEPI, Edif. Z-4, Instituto Politécnico Nacional, Mexico City 07738, CDMX, Mexico;
| | - J. Aguila-Muñoz
- CONAHCYT—Centro de Nanociencias y Nanotecnología, Universidad Nacional Autónoma de México, km 107 Carretera Tijuana-Ensenada, Apartado Postal 14, Ensenada 22800, BC, Mexico
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44
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Aberra AS, Lopez A, Grill WM, Peterchev AV. Rapid estimation of cortical neuron activation thresholds by transcranial magnetic stimulation using convolutional neural networks. Neuroimage 2023; 275:120184. [PMID: 37230204 PMCID: PMC10281353 DOI: 10.1016/j.neuroimage.2023.120184] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 04/13/2023] [Accepted: 05/22/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) can modulate neural activity by evoking action potentials in cortical neurons. TMS neural activation can be predicted by coupling subject-specific head models of the TMS-induced electric field (E-field) to populations of biophysically realistic neuron models; however, the significant computational cost associated with these models limits their utility and eventual translation to clinically relevant applications. OBJECTIVE To develop computationally efficient estimators of the activation thresholds of multi-compartmental cortical neuron models in response to TMS-induced E-field distributions. METHODS Multi-scale models combining anatomically accurate finite element method (FEM) simulations of the TMS E-field with layer-specific representations of cortical neurons were used to generate a large dataset of activation thresholds. 3D convolutional neural networks (CNNs) were trained on these data to predict thresholds of model neurons given their local E-field distribution. The CNN estimator was compared to an approach using the uniform E-field approximation to estimate thresholds in the non-uniform TMS-induced E-field. RESULTS The 3D CNNs estimated thresholds with mean absolute percent error (MAPE) on the test dataset below 2.5% and strong correlation between the CNN predicted and actual thresholds for all cell types (R2 > 0.96). The CNNs estimated thresholds with a 2-4 orders of magnitude reduction in the computational cost of the multi-compartmental neuron models. The CNNs were also trained to predict the median threshold of populations of neurons, speeding up computation further. CONCLUSION 3D CNNs can estimate rapidly and accurately the TMS activation thresholds of biophysically realistic neuron models using sparse samples of the local E-field, enabling simulating responses of large neuron populations or parameter space exploration on a personal computer.
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Affiliation(s)
- Aman S Aberra
- Department of Biomedical Engineering, School of Engineering, Duke University, NC, USA
| | - Adrian Lopez
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, NC, USA; Department of Mathematics, College of Arts and Sciences, Duke University, NC, USA
| | - Warren M Grill
- Department of Biomedical Engineering, School of Engineering, Duke University, NC, USA; Department of Electrical and Computer Engineering, School of Engineering, Duke University, NC, USA; Department of Neurobiology, School of Medicine, Duke University, NC, USA; Department of Neurosurgery, School of Medicine, Duke University, NC, USA
| | - Angel V Peterchev
- Department of Biomedical Engineering, School of Engineering, Duke University, NC, USA; Department of Electrical and Computer Engineering, School of Engineering, Duke University, NC, USA; Department of Neurosurgery, School of Medicine, Duke University, NC, USA; Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, NC, USA.
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45
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Spampinato DA, Ibanez J, Rocchi L, Rothwell J. Motor potentials evoked by transcranial magnetic stimulation: interpreting a simple measure of a complex system. J Physiol 2023; 601:2827-2851. [PMID: 37254441 PMCID: PMC10952180 DOI: 10.1113/jp281885] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 05/18/2023] [Indexed: 06/01/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) is a non-invasive technique that is increasingly used to study the human brain. One of the principal outcome measures is the motor-evoked potential (MEP) elicited in a muscle following TMS over the primary motor cortex (M1), where it is used to estimate changes in corticospinal excitability. However, multiple elements play a role in MEP generation, so even apparently simple measures such as peak-to-peak amplitude have a complex interpretation. Here, we summarize what is currently known regarding the neural pathways and circuits that contribute to the MEP and discuss the factors that should be considered when interpreting MEP amplitude measured at rest in the context of motor processing and patients with neurological conditions. In the last part of this work, we also discuss how emerging technological approaches can be combined with TMS to improve our understanding of neural substrates that can influence MEPs. Overall, this review aims to highlight the capabilities and limitations of TMS that are important to recognize when attempting to disentangle sources that contribute to the physiological state-related changes in corticomotor excitability.
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Affiliation(s)
- Danny Adrian Spampinato
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
- Department of Human NeurosciencesSapienza University of RomeRomeItaly
- Department of Clinical and Behavioral NeurologyIRCCS Santa Lucia FoundationRomeItaly
| | - Jaime Ibanez
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
- BSICoS group, I3A Institute and IIS AragónUniversity of ZaragozaZaragozaSpain
- Department of Bioengineering, Centre for NeurotechnologiesImperial College LondonLondonUK
| | - Lorenzo Rocchi
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
- Department of Medical Sciences and Public HealthUniversity of CagliariCagliariItaly
| | - John Rothwell
- Department of Clinical and Movement NeurosciencesUniversity College LondonLondonUK
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Wendt K, Sorkhabi MM, Stagg CJ, Fleming MK, Denison T, O'Shea J. The effect of pulse shape in theta-burst stimulation: Monophasic vs biphasic TMS. Brain Stimul 2023; 16:1178-1185. [PMID: 37543172 PMCID: PMC10444700 DOI: 10.1016/j.brs.2023.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 07/30/2023] [Accepted: 08/02/2023] [Indexed: 08/07/2023] Open
Abstract
BACKGROUND Intermittent theta-burst stimulation (i) (TBS) is a transcranial magnetic stimulation (TMS) plasticity protocol. Conventionally, TBS is applied using biphasic pulses due to hardware limitations. However, monophasic pulses are hypothesised to recruit cortical neurons more selectively than biphasic pulses, predicting stronger plasticity effects. Monophasic and biphasic TBS can be generated using a custom-made pulse-width modulation-based TMS device (pTMS). OBJECTIVE Using pTMS, we tested the hypothesis that monophasic iTBS would induce a stronger plasticity effect than biphasic, measured as induced increases in motor corticospinal excitability. METHODS In a repeated-measures design, thirty healthy volunteers participated in three separate sessions, where monophasic and biphasic iTBS was applied to the primary motor cortex (M1 condition) or the vertex (control condition). Plasticity was quantified as increases in motor corticospinal excitability after versus before iTBS, by comparing peak-to-peak amplitudes of motor evoked potentials (MEP) measured at baseline and over 60 min after iTBS. RESULTS Both monophasic and biphasic M1 iTBS led to significant increases in MEP amplitude. As predicted, linear mixed effects (LME) models showed that the iTBS condition had a significant effect on the MEP amplitude (χ2 (1) = 27.615, p < 0.001) with monophasic iTBS leading to significantly stronger plasticity than biphasic iTBS (t (693) = 2.311, p = 0.021). Control vertex iTBS had no effect. CONCLUSIONS In this study, monophasic iTBS induced a stronger motor corticospinal excitability increase than biphasic within participants. This greater physiological effect suggests that monophasic iTBS may also have potential for greater functional impact, of interest for future fundamental and clinical applications of TBS.
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Affiliation(s)
- Karen Wendt
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3TH, UK; Department of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK.
| | - Majid Memarian Sorkhabi
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3TH, UK
| | - Charlotte J Stagg
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3TH, UK; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Melanie K Fleming
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Timothy Denison
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3TH, UK; Department of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK
| | - Jacinta O'Shea
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity (OHBA), University of Oxford Department of Psychiatry, Warneford Hospital, Warneford Lane, Oxford, UK
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Liao W, Opie GM, Ziemann U, Semmler JG. Modulation of dorsal premotor cortex differentially influences I-wave excitability in primary motor cortex of young and older adults. J Physiol 2023; 601:2959-2974. [PMID: 37194369 PMCID: PMC10952229 DOI: 10.1113/jp284204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 05/12/2023] [Indexed: 05/18/2023] Open
Abstract
Previous research using transcranial magnetic stimulation (TMS) has demonstrated weakened connectivity between dorsal premotor cortex (PMd) and motor cortex (M1) with age. While this alteration is probably mediated by changes in the communication between the two regions, the effect of age on the influence of PMd on specific indirect (I) wave circuits within M1 remains unclear. The present study therefore investigated the influence of PMd on early and late I-wave excitability in M1 of young and older adults. Twenty-two young (mean ± SD, 22.9 ± 2.9 years) and 20 older (66.6 ± 4.2 years) adults participated in two experimental sessions involving either intermittent theta burst stimulation (iTBS) or sham stimulation over PMd. Changes within M1 following the intervention were assessed with motor-evoked potentials (MEPs) recorded from the right first dorsal interosseous muscle. We applied posterior-anterior (PA) and anterior-posterior (AP) current single-pulse TMS to assess corticospinal excitability (PA1mV ; AP1mV ; PA0.5mV , early; AP0.5mV , late), and paired-pulse TMS short intracortical facilitation for I-wave excitability (PA SICF, early; AP SICF, late). Although PMd iTBS potentiated PA1mV and AP1mV MEPs in both age groups (both P < 0.05), the time course of this effect was delayed for AP1mV in older adults (P = 0.001). Furthermore, while AP0.5mV , PA SICF and AP SICF were potentiated in both groups (all P < 0.05), potentiation of PA0.5mV was only apparent in young adults (P < 0.0001). While PMd influences early and late I-wave excitability in young adults, direct PMd modulation of the early circuits is specifically reduced in older adults. KEY POINTS: Interneuronal circuits responsible for late I-waves within primary motor cortex (M1) mediate projections from dorsal premotor cortex (PMd), but this communication probably changes with advancing age. We investigated the effects of intermittent theta burst stimulation (iTBS) to PMd on transcranial magnetic stimulation (TMS) measures of M1 excitability in young and older adults. We found that PMd iTBS facilitated M1 excitability assessed with posterior-anterior (PA, early I-waves) and anterior-posterior (AP, late I-waves) current TMS in young adults, with a stronger effect for AP TMS. M1 excitability assessed with AP TMS also increased in older adults following PMd iTBS, but there was no facilitation for PA TMS responses. We conclude that changes in M1 excitability following PMd iTBS are specifically reduced for the early I-waves in older adults, which could be a potential target for interventions that enhance cortical excitability in older adults.
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Affiliation(s)
- Wei‐Yeh Liao
- Discipline of Physiology, School of BiomedicineThe University of AdelaideAdelaideAustralia
| | - George M. Opie
- Discipline of Physiology, School of BiomedicineThe University of AdelaideAdelaideAustralia
| | - Ulf Ziemann
- Department of Neurology & StrokeEberhard Karls University of TübingenTübingenGermany
- Hertie‐Institute for Clinical Brain ResearchEberhard Karls University of TübingenTübingenGermany
| | - John G. Semmler
- Discipline of Physiology, School of BiomedicineThe University of AdelaideAdelaideAustralia
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牛 瑞, 张 丞, 吴 昌, 林 华, 张 广, 霍 小. [The influence of tissue conductivity on the calculation of electric field in the transcranial magnetic stimulation head model]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2023; 40:401-408. [PMID: 37380377 PMCID: PMC10307604 DOI: 10.7507/1001-5515.202211070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/15/2023] [Indexed: 06/30/2023]
Abstract
In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.
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Affiliation(s)
- 瑞奇 牛
- 中国科学院电工研究所 生物电磁学北京市重点实验室(北京 100190)Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, P. R. China
- 中国科学院大学 电子电气与通信工程学院(北京 100049)School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - 丞 张
- 中国科学院电工研究所 生物电磁学北京市重点实验室(北京 100190)Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, P. R. China
- 中国科学院大学 电子电气与通信工程学院(北京 100049)School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - 昌哲 吴
- 中国科学院电工研究所 生物电磁学北京市重点实验室(北京 100190)Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, P. R. China
- 中国科学院大学 电子电气与通信工程学院(北京 100049)School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - 华 林
- 中国科学院电工研究所 生物电磁学北京市重点实验室(北京 100190)Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, P. R. China
| | - 广浩 张
- 中国科学院电工研究所 生物电磁学北京市重点实验室(北京 100190)Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, P. R. China
- 中国科学院大学 电子电气与通信工程学院(北京 100049)School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - 小林 霍
- 中国科学院电工研究所 生物电磁学北京市重点实验室(北京 100190)Beijing Key Laboratory of Bioelectromagnetism, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, P. R. China
- 中国科学院大学 电子电气与通信工程学院(北京 100049)School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, P. R. China
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49
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Fisher LE, Lempka SF. Neurotechnology for Pain. Annu Rev Biomed Eng 2023; 25:387-412. [PMID: 37068766 DOI: 10.1146/annurev-bioeng-111022-121637] [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] [Indexed: 04/19/2023]
Abstract
Neurotechnologies for treating pain rely on electrical stimulation of the central or peripheral nervous system to disrupt or block pain signaling and have been commercialized to treat a variety of pain conditions. While their adoption is accelerating, neurotechnologies are still frequently viewed as a last resort, after many other treatment options have been explored. We review the pain conditions commonly treated with electrical stimulation, as well as the specific neurotechnologies used for treating those conditions. We identify barriers to adoption, including a limited understanding of mechanisms of action, inconsistent efficacy across patients, and challenges related to selectivity of stimulation and off-target side effects. We describe design improvements that have recently been implemented, as well as some cutting-edge technologies that may address the limitations of existing neurotechnologies. Addressing these challenges will accelerate adoption and change neurotechnologies from last-line to first-line treatments for people living with chronic pain.
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Affiliation(s)
- Lee E Fisher
- Rehab Neural Engineering Labs, Department of Physical Medicine and Rehabilitation, and Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA;
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Scott F Lempka
- Department of Biomedical Engineering, Biointerfaces Institute, and Department of Anesthesiology, University of Michigan, Ann Arbor, Michigan, USA;
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Wang B, Zhang J, Li Z, Grill WM, Peterchev AV, Goetz SM. Optimized monophasic pulses with equivalent electric field for rapid-rate transcranial magnetic stimulation. J Neural Eng 2023; 20:10.1088/1741-2552/acd081. [PMID: 37100051 PMCID: PMC10464893 DOI: 10.1088/1741-2552/acd081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 04/26/2023] [Indexed: 04/28/2023]
Abstract
Objective.Transcranial magnetic stimulation (TMS) with monophasic pulses achieves greater changes in neuronal excitability but requires higher energy and generates more coil heating than TMS with biphasic pulses, and this limits the use of monophasic pulses in rapid-rate protocols. We sought to design a stimulation waveform that retains the characteristics of monophasic TMS but significantly reduces coil heating, thereby enabling higher pulse rates and increased neuromodulation effectiveness.Approach.A two-step optimization method was developed that uses the temporal relationship between the electric field (E-field) and coil current waveforms. The model-free optimization step reduced the ohmic losses of the coil current and constrained the error of the E-field waveform compared to a template monophasic pulse, with pulse duration as a second constraint. The second, amplitude adjustment step scaled the candidate waveforms based on simulated neural activation to account for differences in stimulation thresholds. The optimized waveforms were implemented to validate the changes in coil heating.Main results.Depending on the pulse duration and E-field matching constraints, the optimized waveforms produced 12%-75% less heating than the original monophasic pulse. The reduction in coil heating was robust across a range of neural models. The changes in the measured ohmic losses of the optimized pulses compared to the original pulse agreed with numeric predictions.Significance.The first step of the optimization approach was independent of any potentially inaccurate or incorrect model and exhibited robust performance by avoiding the highly nonlinear behavior of neural responses, whereas neural simulations were only run once for amplitude scaling in the second step. This significantly reduced computational cost compared to iterative methods using large populations of candidate solutions and more importantly reduced the sensitivity to the choice of neural model. The reduced coil heating and power losses of the optimized pulses can enable rapid-rate monophasic TMS protocols.
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Affiliation(s)
- Boshuo Wang
- Department of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC, USA
| | - Jinshui Zhang
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
| | - Zhongxi Li
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
| | - Warren M. Grill
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Biomedical Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, School of Medicine, Duke University, NC, USA
- Department of Neurobiology, School of Medicine, Duke University, NC, USA
| | - Angel V. Peterchev
- Department of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Biomedical Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, School of Medicine, Duke University, NC, USA
| | - Stefan M. Goetz
- Department of Psychiatry and Behavior Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Electrical and Computer Engineering, School of Engineering, Duke University, Durham, NC, USA
- Department of Neurosurgery, School of Medicine, Duke University, NC, USA
- Department of Engineering, School of Technology, University of Cambridge, Cambridge, UK
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