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Abstract
In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.
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Affiliation(s)
- Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Institute for Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada; Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany.
| | - Ulf Ziemann
- Department of Neurology & Stroke, University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.
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Campos B, Choi H, DeMarco AT, Seydell-Greenwald A, Hussain SJ, Joy MT, Turkeltaub PE, Zeiger W. Rethinking Remapping: Circuit Mechanisms of Recovery after Stroke. J Neurosci 2023; 43:7489-7500. [PMID: 37940595 PMCID: PMC10634578 DOI: 10.1523/jneurosci.1425-23.2023] [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: 07/27/2023] [Revised: 08/21/2023] [Accepted: 08/21/2023] [Indexed: 11/10/2023] Open
Abstract
Stroke is one of the most common causes of disability, and there are few treatments that can improve recovery after stroke. Therapeutic development has been hindered because of a lack of understanding of precisely how neural circuits are affected by stroke, and how these circuits change to mediate recovery. Indeed, some of the hypotheses for how the CNS changes to mediate recovery, including remapping, redundancy, and diaschisis, date to more than a century ago. Recent technological advances have enabled the interrogation of neural circuits with ever greater temporal and spatial resolution. These techniques are increasingly being applied across animal models of stroke and to human stroke survivors, and are shedding light on the molecular, structural, and functional changes that neural circuits undergo after stroke. Here we review these studies and highlight important mechanisms that underlie impairment and recovery after stroke. We begin by summarizing knowledge about changes in neural activity that occur in the peri-infarct cortex, specifically considering evidence for the functional remapping hypothesis of recovery. Next, we describe the importance of neural population dynamics, disruptions in these dynamics after stroke, and how allocation of neurons into spared circuits can restore functionality. On a more global scale, we then discuss how effects on long-range pathways, including interhemispheric interactions and corticospinal tract transmission, contribute to post-stroke impairments. Finally, we look forward and consider how a deeper understanding of neural circuit mechanisms of recovery may lead to novel treatments to reduce disability and improve recovery after stroke.
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Affiliation(s)
- Baruc Campos
- Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
| | - Hoseok Choi
- Department of Neurology, Weill Institute for Neuroscience, University of California-San Francisco, San Francisco, California 94158
| | - Andrew T DeMarco
- Center for Brain Plasticity and Recovery, Georgetown University Medical Center, Georgetown University, Washington, DC 20057
- Department of Rehabilitation Medicine, Georgetown University Medical Center, Georgetown University, Washington, DC 20057
| | - Anna Seydell-Greenwald
- Center for Brain Plasticity and Recovery, Georgetown University Medical Center, Georgetown University, Washington, DC 20057
- MedStar National Rehabilitation Hospital, Washington, DC 20010
| | - Sara J Hussain
- Movement and Cognitive Rehabilitation Science Program, Department of Kinesiology and Health Education, University of Texas at Austin, Austin, Texas 78712
| | - Mary T Joy
- The Jackson Laboratory, Bar Harbor, Maine 04609
| | - Peter E Turkeltaub
- Center for Brain Plasticity and Recovery, Georgetown University Medical Center, Georgetown University, Washington, DC 20057
- MedStar National Rehabilitation Hospital, Washington, DC 20010
| | - William Zeiger
- Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
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Suresh T, Hussain SJ. Re-evaluating the contribution of sensorimotor mu rhythm phase and power to human corticospinal output: A replication study. Brain Stimul 2023; 16:936-938. [PMID: 37257815 DOI: 10.1016/j.brs.2023.05.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 05/28/2023] [Indexed: 06/02/2023] Open
Affiliation(s)
- Tharan Suresh
- Movement and Cognitive Rehabilitation Science Program, Department of Kinesiology and Health Education, The University of Texas at Austin, TX, 78712, USA
| | - Sara J Hussain
- Movement and Cognitive Rehabilitation Science Program, Department of Kinesiology and Health Education, The University of Texas at Austin, TX, 78712, USA.
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Ozdemir RA, Kirkman S, Magnuson JR, Fried PJ, Pascual-Leone A, Shafi MM. Phase matters when there is power: Phasic modulation of corticospinal excitability occurs at high amplitude sensorimotor mu-oscillations. NEUROIMAGE. REPORTS 2022; 2:100132. [PMID: 36570046 PMCID: PMC9784422 DOI: 10.1016/j.ynirp.2022.100132] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Prior studies have suggested that oscillatory activity in cortical networks can modulate stimulus-evoked responses through time-varying fluctuations in neural excitation-inhibition dynamics. Studies combining transcranial magnetic stimulation (TMS) with electromyography (EMG) and electroencephalography (EEG) can provide direct measurements to examine how instantaneous fluctuations in cortical oscillations contribute to variability in TMS-induced corticospinal responses. However, the results of these studies have been conflicting, as some reports showed consistent phase effects of sensorimotor mu-rhythms with increased excitability at the negative mu peaks, while others failed to replicate these findings or reported unspecific mu-phase effects across subjects. Given the lack of consistent results, we systematically examined the modulatory effects of instantaneous and pre-stimulus sensorimotor mu-rhythms on corticospinal responses with offline EEG-based motor evoked potential (MEP) classification analyses across five identical visits. Instantaneous sensorimotor mu-phase or pre-stimulus mu-power alone did not significantly modulate MEP responses. Instantaneous mu-power analyses showed weak effects with larger MEPs during high-power trials at the overall group level analyses, but this trend was not reproducible across visits. However, TMS delivered at the negative peak of high magnitude mu-oscillations generated the largest MEPs across all visits, with significant differences compared to other peak-phase combinations. High power effects on MEPs were only observed at the trough phase of ongoing mu oscillations originating from the stimulated region, indicating site and phase specificity, respectively. More importantly, such phase-dependent power effects on corticospinal excitability were reproducible across multiple visits. We provide further evidence that fluctuations in corticospinal excitability indexed by MEP amplitudes are partially driven by dynamic interactions between the magnitude and the phase of ongoing sensorimotor mu oscillations at the time of TMS, and suggest promising insights for (re)designing neuromodulatory TMS protocols targeted to specific cortical oscillatory states.
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Affiliation(s)
- Recep A. Ozdemir
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA,Corresponding author. Mouhsin Shafi Berenson-Allen Center for Non-Invasive Brain Stimulation, Beth Israel Medical Center, Harvard Medical School, Boston, MA, USA. (R.A. Ozdemir)
| | - Sofia Kirkman
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Justine R. Magnuson
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Peter J. Fried
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alvaro Pascual-Leone
- Department of Neurology, Harvard Medical School, Boston, MA, USA,Hinda and Arthur Marcus Institute for Aging Research and Deanne and Sidney Wolk Center for Memory Health, Hebrew Senior Life, Boston, MA, USA,Guttmann Brain Health Institute, Institut Guttmann de Neurorehabilitació, Universitat Autonoma de Barcelona, Badalona, Spain
| | - Mouhsin M. Shafi
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA,Department of Neurology, Harvard Medical School, Boston, MA, USA,Corresponding author. Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, USA. (M.M. Shafi)
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Bakulin I, Zabirova A, Sinitsyn D, Poydasheva A, Lagoda D, Suponeva N, Piradov M. Adding a Second iTBS Block in 15 or 60 Min Time Interval Does Not Increase iTBS Effects on Motor Cortex Excitability and the Responder Rates. Brain Sci 2022; 12:brainsci12081064. [PMID: 36009127 PMCID: PMC9405900 DOI: 10.3390/brainsci12081064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/06/2022] [Accepted: 08/09/2022] [Indexed: 11/16/2022] Open
Abstract
The use of metaplasticity-based intermittent theta-burst stimulation (iTBS) protocols including several stimulation blocks could be a possible approach to increasing stimulation effectiveness. Our aim was to investigate the neurophysiological effects of two protocols with a short and a long interval between blocks. Seventeen healthy volunteers received four protocols in a pseudorandomized order: iTBS 0-15 (two blocks of active iTBS of primary motor cortex (M1) separated by 15 min and a control stimulation block of the vertex in 60 min from the first block); iTBS 0-60 (active iTBS, a control block in 15 min, and an active block in 60 min); iTBS 0 (active iTBS and two control blocks with the same intervals); and Control (three control blocks). The motor evoked potentials (MEPs) were measured before the first and after the second and third blocks. We have shown no significant differences between the effects of the protocols on both the motor cortex excitability and the responder rates. No significant changes of MEPs were observed after all the protocols. The reliability for the responsiveness to a single block between two sessions was insignificant. Our data confirm low reproducibility of the response to iTBS and suggest that the use of repeated protocols does not increase the responder rates or neurophysiological effects of iTBS.
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The phase of sensorimotor mu and beta oscillations has the opposite effect on corticospinal excitability. Brain Stimul 2022; 15:1093-1100. [PMID: 35964870 DOI: 10.1016/j.brs.2022.08.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 08/05/2022] [Accepted: 08/06/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Neural oscillations in the primary motor cortex (M1) shape corticospinal excitability. Power and phase of ongoing mu (8-13 Hz) and beta (14-30 Hz) activity may mediate motor cortical output. However, the functional dynamics of both mu and beta phase and power relationships and their interaction, are largely unknown. OBJECTIVE Here, we employ recently developed real-time targeting of the mu and beta rhythm, to apply phase-specific brain stimulation and probe motor corticospinal excitability non-invasively. For this, we used instantaneous read-out and analysis of ongoing oscillations, targeting four different phases (0°, 90°, 180°, and 270°) of mu and beta rhythms with suprathreshold single-pulse transcranial magnetic stimulation (TMS) to M1. Ensuing motor evoked potentials (MEPs) in the right first dorsal interossei muscle were recorded. Twenty healthy adults took part in this double-blind randomized crossover study. RESULTS Mixed model regression analyses showed significant phase-dependent modulation of corticospinal output by both mu and beta rhythm. Strikingly, these modulations exhibit a double dissociation. MEPs are larger at the mu trough and rising phase and smaller at the peak and falling phase. For the beta rhythm we found the opposite behavior. Also, mu power, but not beta power, was positively correlated with corticospinal output. Power and phase effects did not interact for either rhythm, suggesting independence between these aspects of oscillations. CONCLUSION Our results provide insights into real-time motor cortical oscillation dynamics, which offers the opportunity to improve the effectiveness of TMS by specifically targeting different frequency bands.
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Hussain SJ, Quentin R. Decoding personalized motor cortical excitability states from human electroencephalography. Sci Rep 2022; 12:6323. [PMID: 35428785 PMCID: PMC9012777 DOI: 10.1038/s41598-022-10239-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 03/30/2022] [Indexed: 11/22/2022] Open
Abstract
Brain state-dependent transcranial magnetic stimulation (TMS) requires real-time identification of cortical excitability states. Current approaches deliver TMS during brain states that correlate with motor cortex (M1) excitability at the group level. Here, we hypothesized that machine learning classifiers could successfully discriminate between high and low M1 excitability states in individual participants using information obtained from low-density electroencephalography (EEG) signals. To test this, we analyzed a publicly available dataset that delivered 600 single TMS pulses to the right M1 during EEG and electromyography (EMG) recordings in 20 healthy adults. Multivariate pattern classification was used to discriminate between brain states during which TMS evoked small and large motor-evoked potentials (MEPs). Results show that personalized classifiers successfully discriminated between low and high M1 excitability states in 80% of tested participants. MEPs elicited during classifier-predicted high excitability states were significantly larger than those elicited during classifier-predicted low excitability states in 90% of tested participants. Personalized classifiers did not generalize across participants. Overall, results show that individual participants exhibit unique brain activity patterns which predict low and high M1 excitability states and that these patterns can be efficiently captured using low-density EEG signals. Our findings suggest that deploying individualized classifiers during brain state-dependent TMS may enable fully personalized neuromodulation in the future.
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Affiliation(s)
- Sara J Hussain
- Movement and Cognitive Rehabilitation Science Program, Department of Kinesiology and Health Education, University of Texas at Austin, 540 Bellmont Hall, 2109 San Jacinto Blvd, Austin, TX, 78712, USA.
| | - Romain Quentin
- MEL Group, EDUWELL Team, Lyon Neuroscience Research Center (CRNL), INSERM U1028, CRNS UMR5292, Université Claude Bernard Lyon 1, Lyon, France
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