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Siebner HR, Funke K, Aberra AS, Antal A, Bestmann S, Chen R, Classen J, Davare M, Di Lazzaro V, Fox PT, Hallett M, Karabanov AN, Kesselheim J, Beck MM, Koch G, Liebetanz D, Meunier S, Miniussi C, Paulus W, Peterchev AV, Popa T, Ridding MC, Thielscher A, Ziemann U, Rothwell JC, Ugawa Y. Transcranial magnetic stimulation of the brain: What is stimulated? - A consensus and critical position paper. Clin Neurophysiol 2022; 140:59-97. [PMID: 35738037 PMCID: PMC9753778 DOI: 10.1016/j.clinph.2022.04.022] [Citation(s) in RCA: 208] [Impact Index Per Article: 69.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 03/14/2022] [Accepted: 04/15/2022] [Indexed: 12/11/2022]
Abstract
Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentials in cortical neurons. The spatial relationship between the locally induced electric field and the stimulated neurons determines axonal depolarization. The induced electric field is influenced by the conductive properties of the tissue compartments and is strongest in the superficial parts of the targeted cortical gyri and underlying white matter. TMS likely targets axons of both excitatory and inhibitory neurons. The propensity of individual axons to fire an action potential in response to TMS depends on their geometry, myelination and spatial relation to the imposed electric field and the physiological state of the neuron. The latter is determined by its transsynaptic dendritic and somatic inputs, intrinsic membrane potential and firing rate. Modeling work suggests that the primary target of TMS is axonal terminals in the crown top and lip regions of cortical gyri. The induced electric field may additionally excite bends of myelinated axons in the juxtacortical white matter below the gyral crown. Neuronal excitation spreads ortho- and antidromically along the stimulated axons and causes secondary excitation of connected neuronal populations within local intracortical microcircuits in the target area. Axonal and transsynaptic spread of excitation also occurs along cortico-cortical and cortico-subcortical connections, impacting on neuronal activity in the targeted network. Both local and remote neural excitation depend critically on the functional state of the stimulated target area and network. TMS also causes substantial direct co-stimulation of the peripheral nervous system. Peripheral co-excitation propagates centrally in auditory and somatosensory networks, but also produces brain responses in other networks subserving multisensory integration, orienting or arousal. The complexity of the response to TMS warrants cautious interpretation of its physiological and behavioural consequences, and a deeper understanding of the mechanistic underpinnings of TMS will be critical for advancing it as a scientific and therapeutic tool.
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Affiliation(s)
- Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark; Institute for Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
| | - Klaus Funke
- Department of Neurophysiology, Medical Faculty, Ruhr-University Bochum, Bochum, Germany
| | - Aman S Aberra
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Andrea Antal
- Department of Clinical Neurophysiology, University Medical Center, Georg-August-University, Göttingen, Germany
| | - Sven Bestmann
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Robert Chen
- Krembil Brain Institute, University Health Network and Division of Neurology, University of Toronto, Toronto, Ontario, Canada
| | - Joseph Classen
- Department of Neurology, University of Leipzig, Leipzig, Germany
| | - Marco Davare
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico di Roma, via Álvaro del Portillo 21, 00128 Rome, Italy
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, United States
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Anke N Karabanov
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Nutrition and Exercise, University of Copenhagen, Copenhagen, Denmark
| | - Janine Kesselheim
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Mikkel M Beck
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Giacomo Koch
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy; Non-invasive Brain Stimulation Unit, Laboratorio di NeurologiaClinica e Comportamentale, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - David Liebetanz
- Department of Clinical Neurophysiology, University Medical Center, Georg-August-University, Göttingen, Germany
| | - Sabine Meunier
- Sorbonne Université, Faculté de Médecine, INSERM U 1127, CNRS 4 UMR 7225, Institut du Cerveau, F-75013, Paris, France
| | - Carlo Miniussi
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Italy; Cognitive Neuroscience Section, IRCCS Centro San Giovanni di DioFatebenefratelli, Brescia, Italy
| | - Walter Paulus
- Department of Clinical Neurophysiology, University Medical Center, Georg-August-University, Göttingen, Germany
| | - Angel V Peterchev
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Psychiatry & Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA; Department of Electrical & Computer Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, School of Medicine, Duke University, Durham, NC, USA
| | - Traian Popa
- Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland; Center for Neuroprosthetics (CNP) and Brain Mind Institute (BMI), Swiss Federal Institute of Technology (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Michael C Ridding
- University of South Australia, IIMPACT in Health, Adelaide, Australia
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark; Department of Health Technology, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Ulf Ziemann
- Department of Neurology & Stroke, University Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University Tübingen, Tübingen, Germany
| | - John C Rothwell
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Yoshikazu Ugawa
- Department of Neurology, Fukushima Medical University, Fukushima, Japan; Fukushima Global Medical Science Centre, Advanced Clinical Research Centre, Fukushima Medical University, Fukushima, Japan
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Rafiei F, Rahnev D. TMS Does Not Increase BOLD Activity at the Site of Stimulation: A Review of All Concurrent TMS-fMRI Studies. eNeuro 2022; 9:ENEURO.0163-22.2022. [PMID: 35981879 PMCID: PMC9410768 DOI: 10.1523/eneuro.0163-22.2022] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 06/14/2022] [Accepted: 06/30/2022] [Indexed: 11/21/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) is widely used for understanding brain function in neurologically intact subjects and for the treatment of various disorders. However, the precise neurophysiological effects of TMS at the site of stimulation remain poorly understood. The local effects of TMS can be studied using concurrent TMS-functional magnetic resonance imaging (fMRI), a technique where TMS is delivered during fMRI scanning. However, although concurrent TMS-fMRI was developed over 20 years ago and dozens of studies have used this technique, there is still no consensus on whether TMS increases blood oxygen level-dependent (BOLD) activity at the site of stimulation. To address this question, here we review all previous concurrent TMS-fMRI studies that reported analyses of BOLD activity at the target location. We find evidence that TMS increases local BOLD activity when stimulating the primary motor (M1) and visual (V1) cortices but that these effects are likely driven by the downstream consequences of TMS (finger twitches and phosphenes). However, TMS does not appear to increase BOLD activity at the site of stimulation for areas outside of the M1 and V1 when conducted at rest. We examine the possible reasons for such lack of BOLD signal increase based on recent work in nonhuman animals. We argue that the current evidence points to TMS inducing periods of increased and decreased neuronal firing that mostly cancel each other out and therefore lead to no change in the overall BOLD signal.
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Affiliation(s)
- Farshad Rafiei
- School of Psychology, Georgia Institute of Technology, Atlanta, GA 30313
| | - Dobromir Rahnev
- School of Psychology, Georgia Institute of Technology, Atlanta, GA 30313
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Sydnor VJ, Cieslak M, Duprat R, Deluisi J, Flounders MW, Long H, Scully M, Balderston NL, Sheline YI, Bassett DS, Satterthwaite TD, Oathes DJ. Cortical-subcortical structural connections support transcranial magnetic stimulation engagement of the amygdala. SCIENCE ADVANCES 2022; 8:eabn5803. [PMID: 35731882 PMCID: PMC9217085 DOI: 10.1126/sciadv.abn5803] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 05/04/2022] [Indexed: 05/31/2023]
Abstract
The amygdala processes valenced stimuli, influences emotion, and exhibits aberrant activity across anxiety disorders, depression, and PTSD. Interventions modulating amygdala activity hold promise as transdiagnostic psychiatric treatments. In 45 healthy participants, we investigated whether transcranial magnetic stimulation (TMS) elicits indirect changes in amygdala activity when applied to ventrolateral prefrontal cortex (vlPFC), a region important for emotion regulation. Harnessing in-scanner interleaved TMS/functional MRI (fMRI), we reveal that vlPFC neurostimulation evoked acute and focal modulations of amygdala fMRI BOLD signal. Larger TMS-evoked changes in the amygdala were associated with higher fiber density in a vlPFC-amygdala white matter pathway when stimulating vlPFC but not an anatomical control, suggesting this pathway facilitated stimulation-induced communication between cortex and subcortex. This work provides evidence of amygdala engagement by TMS, highlighting stimulation of vlPFC-amygdala circuits as a candidate treatment for transdiagnostic psychopathology. More broadly, it indicates that targeting cortical-subcortical structural connections may enhance the impact of TMS on subcortical neural activity and, by extension, subcortex-subserved behaviors.
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Affiliation(s)
- Valerie J. Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Romain Duprat
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Joseph Deluisi
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew W. Flounders
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hannah Long
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Morgan Scully
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nicholas L. Balderston
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yvette I. Sheline
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dani S. Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Theodore D. Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Desmond J. Oathes
- Center for Neuromodulation in Depression and Stress (CNDS), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Brain Science, Translation, Innovation, and Modulation Center (brainSTIM), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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Rossion B. Twenty years of investigation with the case of prosopagnosia PS to understand human face identity recognition. Part II: Neural basis. Neuropsychologia 2022; 173:108279. [PMID: 35667496 DOI: 10.1016/j.neuropsychologia.2022.108279] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 04/30/2022] [Accepted: 05/25/2022] [Indexed: 10/18/2022]
Abstract
Patient PS sustained her dramatic brain injury in 1992, the same year as the first report of a neuroimaging study of human face recognition. The present paper complements the review on the functional nature of PS's prosopagnosia (part I), illustrating how her case study directly, i.e., through neuroimaging investigations of her brain structure and activity, but also indirectly, through neural studies performed on other clinical cases and neurotypical individuals, inspired and constrained neural models of human face recognition. In the dominant right hemisphere for face recognition in humans, PS's main lesion concerns (inputs to) the inferior occipital gyrus (IOG), in a region where face-selective activity is typically found in normal individuals ('Occipital Face Area', OFA). Her case study initially supported the criticality of this region for face identity recognition (FIR) and provided the impetus for transcranial magnetic stimulation (TMS), intracerebral electrical stimulation, and cortical surgery studies that have generally supported this view. Despite PS's right IOG lesion, typical face-selectivity is found anteriorly in the middle portion of the fusiform gyrus, a hominoid structure (termed the right 'Fusiform Face Area', FFA) that is widely considered to be the most important region for human face recognition. This finding led to the original proposal of direct anatomico-functional connections from early visual cortices to the FFA, bypassing the IOG/OFA (lulu), a hypothesis supported by further neuroimaging studies of PS, other neurological cases and neuro-typical individuals with original visual stimulation paradigms, data recordings and analyses. The proposal of a lack of sensitivity to face identity in PS's right FFA due to defective reentrant inputs from the IOG/FFA has also been supported by other cases, functional connectivity and cortical surgery studies. Overall, neural studies of, and based on, the case of prosopagnosia PS strongly question the hierarchical organization of the human neural face recognition system, supporting a more flexible and dynamic view of this key social brain function.
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Affiliation(s)
- Bruno Rossion
- Université de Lorraine, CNRS, CRAN, F-54000, Nancy, France; CHRU-Nancy, Service de Neurologie, F-5400, France; Psychological Sciences Research Institute, Institute of Neuroscience, University of Louvain, Belgium.
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55
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Klooster DCW, Ferguson MA, Boon PAJM, Baeken C. Personalizing Repetitive Transcranial Magnetic Stimulation Parameters for Depression Treatment Using Multimodal Neuroimaging. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:536-545. [PMID: 34800726 DOI: 10.1016/j.bpsc.2021.11.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 10/24/2021] [Accepted: 11/09/2021] [Indexed: 06/13/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a tool that can be used to administer treatment for neuropsychiatric disorders such as major depressive disorder, although the clinical efficacy is still rather modest. Overly general stimulation protocols that consider neither patient-specific depression symptomology nor individualized brain characteristics, such as anatomy or structural and functional connections, may be the cause of the high inter- and intraindividual variability in rTMS clinical responses. Multimodal neuroimaging can provide the necessary insights into individual brain characteristics and can therefore be used to personalize rTMS parameters. Optimal coil positioning should include a three-step process: 1) identify the optimal (indirect) target area based on the exact symptom pattern of the patient; 2) derive the cortical (direct) target location based on functional and/or structural connectomes derived from functional and diffusion magnetic resonance imaging data; and 3) determine the ideal coil position by computational modeling, such that the electric field distribution overlaps with the cortical target. These TMS-induced electric field simulations, derived from anatomical and diffusion magnetic resonance imaging data, can be further applied to compute optimal stimulation intensities. In addition to magnetic resonance imaging, electroencephalography can provide complementary information regarding the ongoing brain oscillations. This information can be used to determine the optimal timing and frequency of the stimuli. The heightened benefits of these personalized stimulation approaches are logically reasoned, but speculative. Randomized clinical trials will be required to compare clinical responses from standard rTMS protocols to personalized protocols. Ultimately, an optimized clinical response may result from precision protocols derived from combinations of personalized stimulation parameters.
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Affiliation(s)
- Deborah C W Klooster
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Ghent University, Ghent, Belgium.
| | - Michael A Ferguson
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Paul A J M Boon
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; 4Brain, Department of Head and Skin, Ghent University, Ghent, Belgium; Department of Neurology, Ghent University Hospital, Ghent, Belgium
| | - Chris Baeken
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands; Ghent Experimental Psychiatry Laboratory, Department of Head and Skin, Ghent University, Ghent, Belgium; Department of Psychiatry, University Hospital Brussels, Jette, Belgium
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56
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Siddiqi SH, Kording KP, Parvizi J, Fox MD. Causal mapping of human brain function. Nat Rev Neurosci 2022; 23:361-375. [PMID: 35444305 PMCID: PMC9387758 DOI: 10.1038/s41583-022-00583-8] [Citation(s) in RCA: 154] [Impact Index Per Article: 51.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/14/2022] [Indexed: 12/11/2022]
Abstract
Mapping human brain function is a long-standing goal of neuroscience that promises to inform the development of new treatments for brain disorders. Early maps of human brain function were based on locations of brain damage or brain stimulation that caused a functional change. Over time, this approach was largely replaced by technologies such as functional neuroimaging, which identify brain regions in which activity is correlated with behaviours or symptoms. Despite their advantages, these technologies reveal correlations, not causation. This creates challenges for interpreting the data generated from these tools and using them to develop treatments for brain disorders. A return to causal mapping of human brain function based on brain lesions and brain stimulation is underway. New approaches can combine these causal sources of information with modern neuroimaging and electrophysiology techniques to gain new insights into the functions of specific brain areas. In this Review, we provide a definition of causality for translational research, propose a continuum along which to assess the relative strength of causal information from human brain mapping studies and discuss recent advances in causal brain mapping and their relevance for developing treatments.
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Affiliation(s)
- Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Konrad P Kording
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Josef Parvizi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
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57
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State-dependent effects of neural stimulation on brain function and cognition. Nat Rev Neurosci 2022; 23:459-475. [PMID: 35577959 DOI: 10.1038/s41583-022-00598-1] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/20/2022] [Indexed: 01/02/2023]
Abstract
Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.
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Modern Developments in Transcranial Magnetic Stimulation: The Editorial. Brain Sci 2022; 12:brainsci12050628. [PMID: 35625014 PMCID: PMC9139526 DOI: 10.3390/brainsci12050628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 05/03/2022] [Indexed: 12/02/2022] Open
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Cember ATJ, Deck BL, Kelkar A, Faseyitan O, Zimmerman JP, Erickson B, Elliott MA, Coslett HB, Hamilton RH, Reddy R, Medaglia JD. Glutamate-Weighted Magnetic Resonance Imaging (GluCEST) Detects Effects of Transcranial Magnetic Stimulation to the Motor Cortex. Neuroimage 2022; 256:119191. [PMID: 35413447 DOI: 10.1016/j.neuroimage.2022.119191] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 03/18/2022] [Accepted: 04/05/2022] [Indexed: 11/18/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) is used in several FDA-approved treatments and, increasingly, to treat neurological disorders in off-label uses. However, the mechanism by which TMS causes physiological change is unclear, as are the origins of response variability in the general population. Ideally, objective in vivo biomarkers could shed light on these unknowns and eventually inform personalized interventions. Continuous theta-burst stimulation (cTBS) is a form of TMS observed to reduce motor evoked potentials (MEPs) for 60 min or longer post-stimulation, although the consistency of this effect and its mechanism continue to be under debate. Here, we use glutamate-weighted chemical exchange saturation transfer (gluCEST) magnetic resonance imaging (MRI) at ultra-high magnetic field (7T) to measure changes in glutamate concentration at the site of cTBS. We find that the gluCEST signal in the ipsilateral hemisphere of the brain generally decreases in response to cTBS, whereas consistent changes were not detected in the contralateral region of interest (ROI) or in subjects receiving sham stimulation.
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Affiliation(s)
- Abigail T J Cember
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
| | - Benjamin L Deck
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA
| | - Apoorva Kelkar
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA
| | - Olu Faseyitan
- Department of Neurology, Laboratory for Cognition and Neural Stimulation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Jared P Zimmerman
- Department of Neurology, Laboratory for Cognition and Neural Stimulation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Brian Erickson
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA
| | - Mark A Elliott
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - H Branch Coslett
- Department of Neurology, Laboratory for Cognition and Neural Stimulation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Roy H Hamilton
- Department of Neurology, Laboratory for Cognition and Neural Stimulation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - John D Medaglia
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA; Department of Neurology, Laboratory for Cognition and Neural Stimulation, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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Cohen AL. Using causal methods to map symptoms to brain circuits in neurodevelopment disorders: moving from identifying correlates to developing treatments. J Neurodev Disord 2022; 14:19. [PMID: 35279095 PMCID: PMC8918299 DOI: 10.1186/s11689-022-09433-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 03/03/2022] [Indexed: 11/20/2022] Open
Abstract
A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders.With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for "bedside-to bedside-translation" with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods.Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.
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Affiliation(s)
- Alexander Li Cohen
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA. .,Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. .,Laboratory for Brain Network Imaging and Modulation, Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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Darmani G, Bergmann T, Butts Pauly K, Caskey C, de Lecea L, Fomenko A, Fouragnan E, Legon W, Murphy K, Nandi T, Phipps M, Pinton G, Ramezanpour H, Sallet J, Yaakub S, Yoo S, Chen R. Non-invasive transcranial ultrasound stimulation for neuromodulation. Clin Neurophysiol 2022; 135:51-73. [DOI: 10.1016/j.clinph.2021.12.010] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 12/20/2021] [Accepted: 12/22/2021] [Indexed: 12/13/2022]
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Harita S, Momi D, Mazza F, Griffiths JD. Mapping Inter-individual Functional Connectivity Variability in TMS Targets for Major Depressive Disorder. Front Psychiatry 2022; 13:902089. [PMID: 35815008 PMCID: PMC9260048 DOI: 10.3389/fpsyt.2022.902089] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 05/23/2022] [Indexed: 11/17/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) is an emerging alternative to existing treatments for major depressive disorder (MDD). The effects of TMS on both brain physiology and therapeutic outcomes are known to be highly variable from subject to subject, however. Proposed reasons for this variability include individual differences in neurophysiology, in cortical geometry, and in brain connectivity. Standard approaches to TMS target site definition tend to focus on coordinates or landmarks within the individual brain regions implicated in MDD, such as the dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC). Additionally considering the network connectivity of these sites (i.e., the wider set of brain regions that may be mono- or poly-synaptically activated by TMS stimulation) has the potential to improve subject-specificity of TMS targeting and, in turn, improve treatment outcomes. In this study, we looked at the functional connectivity (FC) of dlPFC and OFC TMS targets, based on induced electrical field (E-field) maps, estimated using the SimNIBS library. We hypothesized that individual differences in spontaneous functional brain dynamics would contribute more to downstream network engagement than individual differences in cortical geometry (i.e., E-field variability). We generated individualized E-field maps on the cortical surface for 121 subjects (67 female) from the Human Connectome Project database using tetrahedral head models generated from T1- and T2-weighted MR images. F3 and Fp1 electrode positions were used to target the left dlPFC and left OFC, respectively. We analyzed inter-subject variability in the shape and location of these TMS target E-field patterns, their FC, and the major functional networks to which they belong. Our results revealed the key differences in TMS target FC between the dlPFC and OFC, and also how this connectivity varies across subjects. Three major functional networks were targeted across the dlPFC and OFC: the ventral attention, fronto-parietal and default-mode networks in the dlPFC, and the fronto-parietal and default mode networks in the OFC. Inter-subject variability in cortical geometry and in FC was high. Our analyses showed that the use of normative neuroimaging reference data (group-average or representative FC and subject E-field) allows prediction of which networks are targeted, but fails to accurately quantify the relative loading of TMS targeting on each of the principal networks. Our results characterize the FC patterns of canonical therapeutic TMS targets, and the key dimensions of their variability across subjects. The high inter-individual variability in cortical geometry and FC, leading to high variability in distributions of targeted brain networks, may account for the high levels of variability in physiological and therapeutic TMS outcomes. These insights should, we hope, prove useful as part of the broader effort by the psychiatry, neurology, and neuroimaging communities to help improve and refine TMS therapy, through a better understanding of the technology and its neurophysiological effects.
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Affiliation(s)
- Shreyas Harita
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Davide Momi
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Frank Mazza
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - John D Griffiths
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
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63
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Caulfield KA, Brown JC. The Problem and Potential of TMS' Infinite Parameter Space: A Targeted Review and Road Map Forward. Front Psychiatry 2022; 13:867091. [PMID: 35619619 PMCID: PMC9127062 DOI: 10.3389/fpsyt.2022.867091] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/21/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive, effective, and FDA-approved brain stimulation method. However, rTMS parameter selection remains largely unexplored, with great potential for optimization. In this review, we highlight key studies underlying next generation rTMS therapies, particularly focusing on: (1) rTMS Parameters, (2) rTMS Target Engagement, (3) rTMS Interactions with Endogenous Brain Activity, and (4) Heritable Predisposition to Brain Stimulation Treatments. METHODS We performed a targeted review of pre-clinical and clinical rTMS studies. RESULTS Current evidence suggests that rTMS pattern, intensity, frequency, train duration, intertrain interval, intersession interval, pulse and session number, pulse width, and pulse shape can alter motor excitability, long term potentiation (LTP)-like facilitation, and clinical antidepressant response. Additionally, an emerging theme is how endogenous brain state impacts rTMS response. Researchers have used resting state functional magnetic resonance imaging (rsfMRI) analyses to identify personalized rTMS targets. Electroencephalography (EEG) may measure endogenous alpha rhythms that preferentially respond to personalized stimulation frequencies, or in closed-loop EEG, may be synchronized with endogenous oscillations and even phase to optimize response. Lastly, neuroimaging and genotyping have identified individual predispositions that may underlie rTMS efficacy. CONCLUSIONS We envision next generation rTMS will be delivered using optimized stimulation parameters to rsfMRI-determined targets at intensities determined by energy delivered to the cortex, and frequency personalized and synchronized to endogenous alpha-rhythms. Further research is needed to define the dose-response curve of each parameter on plasticity and clinical response at the group level, to determine how these parameters interact, and to ultimately personalize these parameters.
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Affiliation(s)
- Kevin A Caulfield
- Department of Psychiatry, Medical University of South Carolina, Charleston, SC, United States
| | - Joshua C Brown
- Departments of Psychiatry and Neurology, Brown University Medical School, Providence, RI, United States
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64
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Mizutani-Tiebel Y, Tik M, Chang KY, Padberg F, Soldini A, Wilkinson Z, Voon CC, Bulubas L, Windischberger C, Keeser D. Concurrent TMS-fMRI: Technical Challenges, Developments, and Overview of Previous Studies. Front Psychiatry 2022; 13:825205. [PMID: 35530029 PMCID: PMC9069063 DOI: 10.3389/fpsyt.2022.825205] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/09/2022] [Indexed: 11/13/2022] Open
Abstract
Transcranial magnetic stimulation (TMS) is a promising treatment modality for psychiatric and neurological disorders. Repetitive TMS (rTMS) is widely used for the treatment of psychiatric and neurological diseases, such as depression, motor stroke, and neuropathic pain. However, the underlying mechanisms of rTMS-mediated neuronal modulation are not fully understood. In this respect, concurrent or simultaneous TMS-fMRI, in which TMS is applied during functional magnetic resonance imaging (fMRI), is a viable tool to gain insights, as it enables an investigation of the immediate effects of TMS. Concurrent application of TMS during neuroimaging usually causes severe artifacts due to magnetic field inhomogeneities induced by TMS. However, by carefully interleaving the TMS pulses with MR signal acquisition in the way that these are far enough apart, we can avoid any image distortions. While the very first feasibility studies date back to the 1990s, recent developments in coil hardware and acquisition techniques have boosted the number of TMS-fMRI applications. As such, a concurrent application requires expertise in both TMS and MRI mechanisms and sequencing, and the hurdle of initial technical set up and maintenance remains high. This review gives a comprehensive overview of concurrent TMS-fMRI techniques by collecting (1) basic information, (2) technical challenges and developments, (3) an overview of findings reported so far using concurrent TMS-fMRI, and (4) current limitations and our suggestions for improvement. By sharing this review, we hope to attract the interest of researchers from various backgrounds and create an educational knowledge base.
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Affiliation(s)
- Yuki Mizutani-Tiebel
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany
| | - Martin Tik
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Kai-Yen Chang
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany
| | - Aldo Soldini
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany.,International Max Planck Research School for Translational Psychiatry, Munich, Germany
| | - Zane Wilkinson
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany
| | - Cui Ci Voon
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany
| | - Lucia Bulubas
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany.,International Max Planck Research School for Translational Psychiatry, Munich, Germany
| | - Christian Windischberger
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital LMU, Munich, Germany.,Neuroimaging Core Unit Munich - NICUM, University Hospital LMU, Munich, Germany.,Department of Radiology, University Hospital LMU, Munich, Germany
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65
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Janssens SEW, Sack AT. Spontaneous Fluctuations in Oscillatory Brain State Cause Differences in Transcranial Magnetic Stimulation Effects Within and Between Individuals. Front Hum Neurosci 2021; 15:802244. [PMID: 34924982 PMCID: PMC8674306 DOI: 10.3389/fnhum.2021.802244] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 11/16/2021] [Indexed: 01/01/2023] Open
Abstract
Transcranial magnetic stimulation (TMS) can cause measurable effects on neural activity and behavioral performance in healthy volunteers. In addition, TMS is increasingly used in clinical practice for treating various neuropsychiatric disorders. Unfortunately, TMS-induced effects show large intra- and inter-subject variability, hindering its reliability, and efficacy. One possible source of this variability may be the spontaneous fluctuations of neuronal oscillations. We present recent studies using multimodal TMS including TMS-EMG (electromyography), TMS-tACS (transcranial alternating current stimulation), and concurrent TMS-EEG-fMRI (electroencephalography, functional magnetic resonance imaging), to evaluate how individual oscillatory brain state affects TMS signal propagation within targeted networks. We demonstrate how the spontaneous oscillatory state at the time of TMS influences both immediate and longer-lasting TMS effects. These findings indicate that at least part of the variability in TMS efficacy may be attributable to the current practice of ignoring (spontaneous) oscillatory fluctuations during TMS. Ignoring this state-dependent spread of activity may cause great individual variability which so far is poorly understood and has proven impossible to control. We therefore also compare two technical solutions to directly account for oscillatory state during TMS, namely, to use (a) tACS to externally control these oscillatory states and then apply TMS at the optimal (controlled) brain state, or (b) oscillatory state-triggered TMS (closed-loop TMS). The described multimodal TMS approaches are paramount for establishing more robust TMS effects, and to allow enhanced control over the individual outcome of TMS interventions aimed at modulating information flow in the brain to achieve desirable changes in cognition, mood, and behavior.
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Affiliation(s)
- Shanice E. W. Janssens
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht, Netherlands
| | - Alexander T. Sack
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht, Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Brain + Nerve Centre, Maastricht University Medical Centre+ (MUMC+), Maastricht, Netherlands
- Centre for Integrative Neuroscience (CIN), Maastricht University, Maastricht, Netherlands
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66
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The Brain Electrophysiological recording & STimulation (BEST) toolbox. Brain Stimul 2021; 15:109-115. [PMID: 34826626 DOI: 10.1016/j.brs.2021.11.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 11/17/2021] [Accepted: 11/22/2021] [Indexed: 11/23/2022] Open
Abstract
Non-invasive brain stimulation (NIBS) experiments involve many recurring procedures that are not sufficiently standardized in the community. Given the diversity in experimental design and experience of the investigators, automated but yet flexible data collection and analysis tools are needed to increase objectivity, reliability, and reproducibility of NIBS experiments. The Brain Electrophysiological recording and STimulation (BEST) Toolbox is a MATLAB-based, open-source software with graphical user interface that allows users to design, run, and share freely configurable multi-protocol, multi-session NIBS studies, including transcranial magnetic, electric, and ultrasound stimulation (TMS, tES, TUS). Interfacing with a variety of recording and stimulation devices, the BEST toolbox analyzes EMG and EEG data, and configures stimulation parameters on-the-fly to facilitate closed-loop protocols and real-time applications. Its functionality is continuously expanded and includes e.g., TMS motor hotspot search, threshold estimation, motor evoked potential (MEP) and TMS-evoked EEG potential (TEP) measurements, dose-response curves, paired-pulse and dual-coil TMS, rTMS interventions.
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67
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Herrero JL, Smith A, Mishra A, Markowitz N, Mehta AD, Bickel S. Inducing neuroplasticity through intracranial θ-burst stimulation in the human sensorimotor cortex. J Neurophysiol 2021; 126:1723-1739. [PMID: 34644179 PMCID: PMC8782667 DOI: 10.1152/jn.00320.2021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/20/2021] [Accepted: 10/08/2021] [Indexed: 01/04/2023] Open
Abstract
The progress of therapeutic neuromodulation greatly depends on improving stimulation parameters to most efficiently induce neuroplasticity effects. Intermittent θ-burst stimulation (iTBS), a form of electrical stimulation that mimics natural brain activity patterns, has proved to efficiently induce such effects in animal studies and rhythmic transcranial magnetic stimulation studies in humans. However, little is known about the potential neuroplasticity effects of iTBS applied through intracranial electrodes in humans. This study characterizes the physiological effects of intracranial iTBS in humans and compare them with α-frequency stimulation, another frequently used neuromodulatory pattern. We applied these two stimulation patterns to well-defined regions in the sensorimotor cortex, which elicited contralateral hand muscle contractions during clinical mapping, in patients with epilepsy implanted with intracranial electrodes. Treatment effects were evaluated using oscillatory coherence across areas connected to the treatment site, as defined with corticocortical-evoked potentials. Our results show that iTBS increases coherence in the β-frequency band within the sensorimotor network indicating a potential neuroplasticity effect. The effect is specific to the sensorimotor system, the β band, and the stimulation pattern and outlasted the stimulation period by ∼3 min. The effect occurred in four out of seven subjects depending on the buildup of the effect during iTBS treatment and other patterns of oscillatory activity related to ceiling effects within the β band and to preexistent coherence within the α band. By characterizing the neurophysiological effects of iTBS within well-defined cortical networks, we hope to provide an electrophysiological framework that allows clinicians/researchers to optimize brain stimulation protocols which may have translational value.NEW & NOTEWORTHY θ-Burst stimulation (TBS) protocols in transcranial magnetic stimulation studies have shown improved treatment efficacy in a variety of neuropsychiatric disorders. The optimal protocol to induce neuroplasticity in invasive direct electrical stimulation approaches is not known. We report that intracranial TBS applied in human sensorimotor cortex increases local coherence of preexistent β rhythms. The effect is specific to the stimulation frequency and the stimulated network and outlasts the stimulation period by ∼3 min.
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Affiliation(s)
- Jose L Herrero
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Alexander Smith
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Akash Mishra
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Noah Markowitz
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Ashesh D Mehta
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
| | - Stephan Bickel
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
- Department of Neurology, Zucker School of Medicine at Hofstra/Northwell, Manhasset, New York
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68
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Baliga SP, Mehta UM. A Review of Studies Leveraging Multimodal TMS-fMRI Applications in the Pathophysiology and Treatment of Schizophrenia. Front Hum Neurosci 2021; 15:662976. [PMID: 34421559 PMCID: PMC8372850 DOI: 10.3389/fnhum.2021.662976] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 06/21/2021] [Indexed: 11/13/2022] Open
Abstract
The current review provides an overview of the existing literature on multimodal transcranial magnetic stimulation, and functional magnetic resonance imaging (TMS/fMRI) studies in individuals with schizophrenia and discusses potential future avenues related to the same. Multimodal studies investigating pathophysiology have explored the role of abnormal thalamic reactivity and have provided further evidence supporting the hypothesis of schizophrenia as a disorder of aberrant connectivity and cortical plasticity. Among studies examining treatment, low-frequency rTMS for the management of persistent auditory verbal hallucinations (AVH) was the most studied. While multimodal TMS/fMRI studies have provided evidence of involvement of local speech-related and distal networks on stimulation of the left temporoparietal cortex, current evidence does not suggest the superiority of fMRI based neuronavigation over conventional methods or of active rTMS over sham for treatment of AVH. Apart from these, preliminary findings suggest a role of rTMS in treating deficits in neurocognition, social cognition, and self-agency. However, most of these studies have only examined medication-resistant symptoms and have methodological concerns arising from small sample sizes and short treatment protocols. That being said, combining TMS with fMRI appears to be a promising approach toward elucidating the pathophysiology of schizophrenia and could also open up a possibility toward developing personalized treatment for its persistent and debilitating symptoms.
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Affiliation(s)
- Sachin Pradeep Baliga
- Department of Psychiatry, TN Medical College and BYL Nair Charitable Hospital, Mumbai, India
| | - Urvakhsh Meherwan Mehta
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bengaluru, India
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