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Baumgartner NW, Hill JP, Bhatnagar S, Roos R, Soliven B, Rezania K, Issa NP. Added load increases the peak frequency of intermuscular coherence. J Electromyogr Kinesiol 2024; 76:102881. [PMID: 38574588 PMCID: PMC11111328 DOI: 10.1016/j.jelekin.2024.102881] [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: 11/17/2023] [Revised: 02/15/2024] [Accepted: 03/30/2024] [Indexed: 04/06/2024] Open
Abstract
Cortical motor neuron activity appears to drive lower motor neurons through two distinct frequency bands: the β range (15-30 Hz) during weak muscle contractions and γ range (30-50 Hz) during strong contractions. It is unknown whether the frequency of cortical drive shifts continuously or abruptly between the β and γ frequency bands as contraction strength changes. Intermuscular coherence (IMC) between synergistic arm muscles was used to assess how the frequency of common neuronal drive shifts with increasing contraction strength. Muscle activity was recorded by surface electromyography (EMG) from the biceps and brachioradialis in nine healthy adults performing 30-second isometric holds with added loads. IMC was calculated across the two muscle groups during the isometric contraction. Significant IMC was present in the 20 to 50 Hz range with all loads. Repeated measures ANOVA show the peak frequency of IMC increased significantly when load was added, from a peak of 32.7 Hz with no added load, to 35.3 Hz, 35.7 Hz, and 36.3 Hz with three-, five-, and ten-pound loads respectively. An increase in IMC frequency occurs in response to added load, suggesting that cortical drive functions over a range of frequencies as a function of an isometric contraction against load.
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Affiliation(s)
- Nicholas W Baumgartner
- Department of Neurology, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA
| | - Jacquelyn P Hill
- Department of Neurology, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA
| | - Shail Bhatnagar
- Department of Neurology, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA
| | - Raymond Roos
- Department of Neurology, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA
| | - Betty Soliven
- Department of Neurology, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA
| | - Kourosh Rezania
- Department of Neurology, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA
| | - Naoum P Issa
- Department of Neurology, University of Chicago, 5841 S. Maryland Ave, Chicago, IL 60637, USA.
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2
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Lemon R. The Corticospinal System and Amyotrophic Lateral Sclerosis: IFCN handbook chapter. Clin Neurophysiol 2024; 160:56-67. [PMID: 38401191 DOI: 10.1016/j.clinph.2024.02.001] [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: 08/31/2023] [Revised: 12/23/2023] [Accepted: 02/03/2024] [Indexed: 02/26/2024]
Abstract
Corticospinal neurons located in motor areas of the cerebral neocortex project corticospinal axons which synapse with the spinal network; a parallel corticobulbar system projects to the cranial motor network and to brainstem motor pathways. The primate corticospinal system has a widespread cortical origin and an extensive range of different fibre diameters, including thick, fast-conducting axons. Direct cortico-motoneuronal (CM) projections from the motor cortex to arm and hand alpha motoneurons are a recent evolutionary feature, that is well developed in dexterous primates and particularly in humans. Many of these projections originate from the caudal subdivision of area 4 ('new' M1: primary motor cortex). They arise from corticospinal neurons of varied soma size, including those with fast- and relatively slow-conducting axons. This CM system has been shown to be involved in the control of skilled movements, carried out with fractionation of the distal extremities and at low force levels. During movement, corticospinal neurons are activated quite differently from 'lower' motoneurons, and there is no simple or fixed functional relationship between a so-called 'upper' motoneuron and its target lower motoneuron. There are key differences in the organisation and function of the corticospinal and CM system in primates versus non-primates, such as rodents. These differences need to be recognized when making the choice of animal model for understanding disorders such as amyotrophic lateral sclerosis (ALS). In this neurodegenerative brain disease there is a selective loss of fast-conducting corticospinal axons, and their synaptic connections, and this is reflected in responses to non-invasive cortical stimuli and measures of cortico-muscular coherence. The loss of CM connections influencing distal limb muscles results in a differential loss of muscle strength or 'split-hand' phenotype. Importantly, there is also a unique impairment in the coordination of skilled hand tasks that require fractionation of digit movement. Scores on validated tests of skilled hand function could be used to assess disease progression.
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Affiliation(s)
- Roger Lemon
- Department of Clinical and Movement Sciences, Queen Square Institute of Neurology, UCL, London WC1N 3BG, UK.
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3
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Arjmandi-Rad S, Vestergaard Nieland JD, Goozee KG, Vaseghi S. The effects of different acetylcholinesterase inhibitors on EEG patterns in patients with Alzheimer's disease: A systematic review. Neurol Sci 2024; 45:417-430. [PMID: 37843690 DOI: 10.1007/s10072-023-07114-y] [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: 06/21/2023] [Accepted: 10/01/2023] [Indexed: 10/17/2023]
Abstract
OBJECTIVE Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the most common type of dementia. The early diagnosis of AD is an important factor for the control of AD progression. Electroencephalography (EEG) can be used for early diagnosis of AD. Acetylcholinesterase inhibitors (AChEIs) are also used for the amelioration of AD symptoms. In this systematic review, we reviewed the effect of different AChEIs including donepezil, rivastigmine, tacrine, physostigmine, and galantamine on EEG patterns in patients with AD. METHODS PubMed electronic database was searched and 122 articles were found. After removal of unrelated articles, 24 articles were selected for the present study. RESULTS AChEIs can decrease beta, theta, and delta frequency bands in patients with AD. However, conflicting results were found for alpha band. Some studies have shown increased alpha frequency, while others have shown decreased alpha frequency following treatment with AChEIs. The only difference was the type of drug. CONCLUSIONS We found that studies reporting the decreased alpha frequency used donepezil and galantamine, while studies reporting the increased alpha frequency used rivastigmine and tacrine. It was suggested that future studies should focus on the effect of different AChEIs on EEG bands, especially alpha frequency in patients with AD, to compare their effects and find the reason for their different influence on EEG patterns. Also, differences between the effects of AChEIs on oligodendrocyte differentiation and myelination may be another important factor. This is the first article investigating the effect of different AChEIs on EEG patterns in patients with AD.
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Affiliation(s)
- Shirin Arjmandi-Rad
- Institute for Cognitive & Brain Sciences, Shahid Beheshti University, Tehran, Iran
| | | | - Kathryn G Goozee
- KaRa Institute of Neurological Diseases Pty Ltd, Macquarie, NSW, Australia
- Faculty of Medicine and Health Sciences, Macquarie University, Sydney, NSW, Australia
| | - Salar Vaseghi
- Cognitive Neuroscience Lab, Medicinal Plants Research Center, Institute of Medicinal Plants, ACECR, Karaj, Iran.
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4
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Sun J, Jia T, Lin PJ, Li Z, Ji L, Li C. Multiscale Canonical Coherence for Functional Corticomuscular Coupling Analysis. IEEE J Biomed Health Inform 2024; 28:812-822. [PMID: 37963005 DOI: 10.1109/jbhi.2023.3332657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Functional corticomuscular coupling (FCMC) probes multi-level information communication in the sensorimotor system. The canonical Coherence (caCOH) method has been leveraged to measure the FCMC between two multivariate signals within the single scale. In this paper, we propose the concept of multiscale canonical Coherence (MS-caCOH) to disentangle complex multi-layer information and extract coupling features in multivariate spaces from multiple scales. Then, we verified the reliability and effectiveness of MS-caCOH on two types of data sets, i.e., a synthetic multivariate data set and a real-world multivariate data set. Our simulation results showed that compared with caCOH, MS-caCOH enhanced coupling detection and achieved lower pattern recovery errors at multiple frequency scales. Further analysis on experimental data demonstrated that the proposed MS-caCOH method could also capture detailed multiscale spatial-frequency characteristics. This study leverages the multiscale analysis framework and multivariate method to give a new insight into corticomuscular coupling analysis.
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Younger DS. Spinal cord motor disorders. HANDBOOK OF CLINICAL NEUROLOGY 2023; 196:3-42. [PMID: 37620076 DOI: 10.1016/b978-0-323-98817-9.00007-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
Spinal cord diseases are frequently devastating due to the precipitous and often permanently debilitating nature of the deficits. Spastic or flaccid paraparesis accompanied by dermatomal and myotomal signatures complementary to the incurred deficits facilitates localization of the insult within the cord. However, laboratory studies often employing disease-specific serology, neuroradiology, neurophysiology, and cerebrospinal fluid analysis aid in the etiologic diagnosis. While many spinal cord diseases are reversible and treatable, especially when recognized early, more than ever, neuroscientists are being called to investigate endogenous mechanisms of neural plasticity. This chapter is a review of the embryology, neuroanatomy, clinical localization, evaluation, and management of adult and childhood spinal cord motor disorders.
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Affiliation(s)
- David S Younger
- Department of Clinical Medicine and Neuroscience, CUNY School of Medicine, New York, NY, United States; Department of Medicine, Section of Internal Medicine and Neurology, White Plains Hospital, White Plains, NY, United States.
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Echeverria-Altuna I, Quinn AJ, Zokaei N, Woolrich MW, Nobre AC, van Ede F. Transient beta activity and cortico-muscular connectivity during sustained motor behaviour. Prog Neurobiol 2022; 214:102281. [PMID: 35550908 PMCID: PMC9742854 DOI: 10.1016/j.pneurobio.2022.102281] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 03/13/2022] [Accepted: 05/02/2022] [Indexed: 12/15/2022]
Abstract
Neural oscillations are thought to play a central role in orchestrating activity states between distant neural populations. For example, during isometric contraction, 13-30 Hz beta activity becomes phase coupled between the motor cortex and the contralateral muscle. This and related observations have led to the proposal that beta activity and connectivity sustain stable cognitive and motor states - or the 'status quo' - in the brain. Recently, however, beta activity at the single-trial level has been shown to be short-lived - though so far this has been reported for regional beta activity in tasks without sustained motor demands. Here, we measured magnetoencephalography (MEG) and electromyography (EMG) in 18 human participants performing a sustained isometric contraction (gripping) task. If cortico-muscular beta connectivity is directly responsible for sustaining a stable motor state, then beta activity within single trials should be (or become) sustained in this context. In contrast, we found that motor beta activity and connectivity with the downstream muscle were transient. Moreover, we found that sustained motor requirements did not prolong beta-event duration in comparison to rest. These findings suggest that neural synchronisation between the brain and the muscle involves short 'bursts' of frequency-specific connectivity, even when task demands - and motor behaviour - are sustained.
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Affiliation(s)
- Irene Echeverria-Altuna
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom,Corresponding authors at: Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Andrew J. Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Nahid Zokaei
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Mark W. Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Anna C. Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom,Corresponding authors at: Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Freek van Ede
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom,Institute for Brain and Behavior Amsterdam, Department of Experimental and Applied Psychology, Vrije University Amsterdam, Amsterdam, The Netherlands
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7
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Keihani A, Mohammadi AM, Marzbani H, Nafissi S, Haidari MR, Jafari AH. Sparse representation of brain signals offers effective computation of cortico-muscular coupling value to predict the task-related and non-task sEMG channels: A joint hdEEG-sEMG study. PLoS One 2022; 17:e0270757. [PMID: 35776772 PMCID: PMC9249190 DOI: 10.1371/journal.pone.0270757] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 06/17/2022] [Indexed: 11/19/2022] Open
Abstract
Cortico-muscular interactions play important role in sensorimotor control during motor task and are commonly studied by cortico-muscular coherence (CMC) method using joint electroencephalogram-surface electromyogram (EEG-sEMG) signals. As noise and time delay between the two signals weaken the CMC value, coupling difference between non-task sEMG channels is often undetectable. We used sparse representation of EEG channels to compute CMC and detect coupling for task-related and non-task sEMG signals. High-density joint EEG-sEMG (53 EEG channels, 4 sEMG bipolar channels) signals were acquired from 15 subjects (30.26 ± 4.96 years) during four specific hand and foot contraction tasks (2 dynamic and 2 static contraction). Sparse representations method was applied to detect projection of EEG signals on each sEMG channel. Bayesian optimization was employed to select best-fitted method with tuned hyperparameters on the input feeding data while using 80% data as the train set and 20% as test set. K-fold (K = 5) cross-validation method was used for evaluation of trained model. Two models were trained separately, one for CMC data and the other from sparse representation of EEG channels on each sEMG channel. Sensitivity, specificity, and accuracy criteria were obtained for test dataset to evaluate the performance of task-related and non-task sEMG channels detection. Coupling values were significantly different between grand average of task-related compared to the non-task sEMG channels (Z = -6.33, p< 0.001, task-related median = 2.011, non-task median = 0.112). Strong coupling index was found even in single trial analysis. Sparse representation approach (best fitted model: SVM, Accuracy = 88.12%, Sensitivity = 83.85%, Specificity = 92.45%) outperformed CMC method (best fitted model: KNN, Accuracy = 50.83%, Sensitivity = 52.17%, Specificity = 49.47%). Sparse representation approach offers high performance to detect CMC for discerning the EMG channels involved in the contraction tasks and non-tasks.
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Affiliation(s)
- Ahmadreza Keihani
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, I.R. Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, I.R. Iran
| | - Amin Mohammad Mohammadi
- Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, I.R. Iran
- Department of Electrical and Computer Engineering, University of Tehran, Tehran, I.R. Iran
| | - Hengameh Marzbani
- Department of Biomedical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, I.R. Iran
| | - Shahriar Nafissi
- Department of Neurology, Neuromuscular Research Center, Shariati Hospital, Tehran University of Medical Sciences, Tehran, I.R. Iran
| | - Mohsen Reza Haidari
- Section of Neuroscience, Department of Neurology, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, I.R. Iran
- * E-mail: (AHJ); (MRH)
| | - Amir Homayoun Jafari
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, I.R. Iran
- Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, I.R. Iran
- * E-mail: (AHJ); (MRH)
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8
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Ogawa A, Koganemaru S, Takahashi T, Takemura Y, Irisawa H, Matsuhashi M, Mima T, Mizushima T, Kansaku K. Case Report: Event-Related Desynchronization Observed During Volitional Swallow by Electroencephalography Recordings in ALS Patients With Dysphagia. Front Behav Neurosci 2022; 16:798375. [PMID: 35250502 PMCID: PMC8888887 DOI: 10.3389/fnbeh.2022.798375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/24/2022] [Indexed: 11/13/2022] Open
Abstract
Dysphagia is a severe disability affecting daily life in patients with amyotrophic lateral sclerosis (ALS). It is caused by degeneration of both the bulbar motor neurons and cortical motoneurons projecting to the oropharyngeal areas. A previous report showed decreased event-related desynchronization (ERD) in the medial sensorimotor areas in ALS dysphagic patients. In the process of degeneration, brain reorganization may also be induced in other areas than the sensorimotor cortices. Furthermore, ALS patients with dysphagia often show a longer duration of swallowing. However, there have been no reports on brain activity in other cortical areas and the time course of brain activity during prolonged swallowing in these patients. In this case report, we investigated the distribution and the time course of ERD and corticomuscular coherence (CMC) in the beta (15–25 Hz) frequency band during volitional swallow using electroencephalography (EEG) in two patients with ALS. Case 1 (a 71-year-old man) was diagnosed 2 years before the evaluation. His first symptom was muscle weakness in the right hand; 5 months later, dysphagia developed and exacerbated. Since his dietary intake decreased, he was given an implantable venous access port. Case 2 (a 64-year-old woman) was diagnosed 1 year before the evaluation. Her first symptom was open-nasal voice and dysarthria; 3 months later, dysphagia developed and exacerbated. She was given a percutaneous endoscopic gastrostomy. EEG recordings were performed during volitional swallowing, and the ERD was calculated. The average swallow durations were 7.6 ± 3.0 s in Case 1 and 8.3 ± 2.9 s in Case 2. The significant ERD was localized in the prefrontal and premotor areas and lasted from a few seconds after the initiation of swallowing to the end in Case 1. The ERD was localized in the lateral sensorimotor areas only at the initiation of swallowing in Case 2. CMC was not observed in either case. These results suggest that compensatory processes for cortical motor outputs might depend on individual patients and that a new therapeutic approach using ERD should be developed according to the individuality of ALS patients with dysphagia.
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Affiliation(s)
- Akari Ogawa
- Cognitive Motor Neuroscience, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Regenerative Systems Neuroscience, Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoko Koganemaru
- Department of Regenerative Systems Neuroscience, Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Department of Physiology, Dokkyo Medical University, Shimotsuga-gun, Tochigi, Japan
- *Correspondence: Satoko Koganemaru
| | - Toshimitsu Takahashi
- Department of Physiology, Dokkyo Medical University, Shimotsuga-gun, Tochigi, Japan
| | - Yuu Takemura
- Department of Rehabilitation Medicine, Dokkyo Medical University, Shimotsuga-gun, Tochigi, Japan
| | - Hiroshi Irisawa
- Department of Rehabilitation Medicine, Dokkyo Medical University, Shimotsuga-gun, Tochigi, Japan
| | - Masao Matsuhashi
- Department of Epilepsy, Movement Disorders and Physiology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tatsuya Mima
- The Graduate School of Core Ethics and Frontier Sciences, Ritsumeikan University, Kyoto, Japan
| | - Takashi Mizushima
- Department of Rehabilitation Medicine, Dokkyo Medical University, Shimotsuga-gun, Tochigi, Japan
| | - Kenji Kansaku
- Department of Physiology, Dokkyo Medical University, Shimotsuga-gun, Tochigi, Japan
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9
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Eisen A, Bede P. The strength of corticomotoneuronal drive underlies ALS split phenotypes and reflects early upper motor neuron dysfunction. Brain Behav 2021; 11:e2403. [PMID: 34710283 PMCID: PMC8671797 DOI: 10.1002/brb3.2403] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 09/02/2021] [Accepted: 10/05/2021] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Split phenotypes, (split hand, elbow, leg, and foot), are probably unique to ALS, and are characterized by having a shared peripheral input of both affected and unaffected muscles. This implies an anatomical origin rostral to the spinal cord, primarily within the cerebral cortex. Therefore, split phenotypes are a potential marker of ALS upper motor neuron pathology. However, to date, reports documenting upper motor neuron dysfunction in split phenotypes have been limited to using transcranial magnetic stimulation and cortical threshold tracking techniques. Here, we consider several other potential methodologies that could confirm a primary upper motor neuron pathology in split phenotypes. METHODS We review the potential of: 1. measuring the compound excitatory post-synaptic potential recorded from a single activated motor unit, 2. cortical-muscular coherence, and 3. new advanced modalities of neuroimaging (high-resolution imaging protocols, ultra-high field MRI platforms [7T], and novel Non-Gaussian diffusion models). CONCLUSIONS We propose that muscles involved in split phenotypes are those functionally involved in the human motor repertoire used particularly in complex activities. Their anterior horn cells receive the strongest corticomotoneuronal input. This is also true of the weakest muscles that are the earliest to be affected in ALS. Descriptions of split hand in non-ALS cases and proposals that peripheral nerve or muscle dysfunction may be causative are contentious. Only a few carefully controlled cases of each form of split phenotype, using upper motor neuron directed methodologies, are necessary to prove our postulate.
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Affiliation(s)
- Andrew Eisen
- Division of Neurology, Department of Medicine, University of British Columbia, British Columbia, Canada
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France
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10
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Garro F, Chiappalone M, Buccelli S, De Michieli L, Semprini M. Neuromechanical Biomarkers for Robotic Neurorehabilitation. Front Neurorobot 2021; 15:742163. [PMID: 34776920 PMCID: PMC8579108 DOI: 10.3389/fnbot.2021.742163] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 09/22/2021] [Indexed: 02/06/2023] Open
Abstract
One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the “biomarkers” that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the “Rehabilomics” has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.
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Affiliation(s)
- Florencia Garro
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
| | - Michela Chiappalone
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy.,Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, Genoa, Italy
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11
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Bao SC, Chen C, Yuan K, Yang Y, Tong RKY. Disrupted cortico-peripheral interactions in motor disorders. Clin Neurophysiol 2021; 132:3136-3151. [PMID: 34749233 DOI: 10.1016/j.clinph.2021.09.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 08/08/2021] [Accepted: 09/19/2021] [Indexed: 11/15/2022]
Abstract
Motor disorders may arise from neurological damage or diseases at different levels of the hierarchical motor control system and side-loops. Altered cortico-peripheral interactions might be essential characteristics indicating motor dysfunctions. By integrating cortical and peripheral responses, top-down and bottom-up cortico-peripheral coupling measures could provide new insights into the motor control and recovery process. This review first discusses the neural bases of cortico-peripheral interactions, and corticomuscular coupling and corticokinematic coupling measures are addressed. Subsequently, methodological efforts are summarized to enhance the modeling reliability of neural coupling measures, both linear and nonlinear approaches are introduced. The latest progress, limitations, and future directions are discussed. Finally, we emphasize clinical applications of cortico-peripheral interactions in different motor disorders, including stroke, neurodegenerative diseases, tremor, and other motor-related disorders. The modified interaction patterns and potential changes following rehabilitation interventions are illustrated. Altered coupling strength, modified coupling directionality, and reorganized cortico-peripheral activation patterns are pivotal attributes after motor dysfunction. More robust coupling estimation methodologies and combination with other neurophysiological modalities might more efficiently shed light on motor control and recovery mechanisms. Future studies with large sample sizes might be necessary to determine the reliabilities of cortico-peripheral interaction measures in clinical practice.
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Affiliation(s)
- Shi-Chun Bao
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong
| | - Cheng Chen
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong
| | - Kai Yuan
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong
| | - Yuan Yang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Tulsa, OK, USA; Laureate Institute for Brain Research, Tulsa, OK, USA; Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Raymond Kai-Yu Tong
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong.
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12
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Zokaei N, Quinn AJ, Hu MT, Husain M, van Ede F, Nobre AC. Reduced cortico-muscular beta coupling in Parkinson's disease predicts motor impairment. Brain Commun 2021; 3:fcab179. [PMID: 34514395 PMCID: PMC8421699 DOI: 10.1093/braincomms/fcab179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 05/15/2021] [Accepted: 05/28/2021] [Indexed: 11/16/2022] Open
Abstract
Long-range communication through the motor system is thought to be facilitated by phase coupling between neural activity in the 15–30 Hz beta range. During periods of sustained muscle contraction (grip), such coupling is manifest between motor cortex and the contralateral forearm muscles—measured as the cortico-muscular coherence. We examined alterations in cortico-muscular coherence in individuals with Parkinson’s disease, while equating grip strength between individuals with Parkinson’s disease (off their medication) and healthy control participants. We show a marked reduction in beta cortico-muscular coherence in the Parkinson’s disease group, even though the grip strength was comparable between the two groups. Moreover, the reduced cortico-muscular coherence was related to motor symptoms, so that individuals with lower cortico-muscular coherence also displayed worse motor symptoms. These findings highlight the cortico-muscular coherence as a simple, effective and clinically relevant neural marker of Parkinson’s disease pathology, with the potential to aid monitoring of disease progression and the efficacy of novel treatments for Parkinson’s disease.
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Affiliation(s)
- Nahid Zokaei
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Michele T Hu
- Department of Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Masud Husain
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK
| | - Freek van Ede
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Anna Christina Nobre
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
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13
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Eisen A, Lemon R. The motor deficit of ALS reflects failure to generate muscle synergies for complex motor tasks, not just muscle strength. Neurosci Lett 2021; 762:136171. [PMID: 34391870 DOI: 10.1016/j.neulet.2021.136171] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 08/09/2021] [Accepted: 08/10/2021] [Indexed: 11/17/2022]
Abstract
Customarily the motor deficits that develop in ALS are considered in terms of muscle weakness. Functional rating scales used to assess ALS in terms of functional decline do not measure the deficits when performing complex motor tasks, that make up the human skilled motor repertoire, best exemplified by tasks requiring skilled hand and finger movement. This repertoire depends primarily upon the strength of direct corticomotoneuronal (CM) connectivity from primary motor cortex to the motor units subserving skilled movements. Our review prompts the question: if accumulating evidence suggests involvement of the CM system in the early stages of ALS, what kinds of motor deficit might be expected to result, and is current methodology able to identify such deficits? We point out that the CM system is organized not in "commands" to individual muscles, but rather encodes the building blocks of complex and intricate movements, which depend upon synergy between not only the prime mover muscles, but other muscles that stabilize the limb during skilled movement. Our knowledge of the functional organization of the CM system has come both from invasive studies in non-human primates and from advanced imaging and neurophysiological techniques in humans, some of which are now being applied in ALS. CM pathology in ALS has consequences not only for muscle strength, but importantly in the failure to generate complex motor tasks, often involving elaborate muscle synergies. Our aim is to encourage innovative methodology specifically directed to assessing complex motor tasks, failure of which is likely a very early clinical deficit in ALS.
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Affiliation(s)
- Andrew Eisen
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, Canada.
| | - Roger Lemon
- Department of Clinical and Motor Neurosciences, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK.
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14
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Ibáñez J, Del Vecchio A, Rothwell JC, Baker SN, Farina D. Only the Fastest Corticospinal Fibers Contribute to β Corticomuscular Coherence. J Neurosci 2021; 41:4867-4879. [PMID: 33893222 PMCID: PMC8260170 DOI: 10.1523/jneurosci.2908-20.2021] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 02/04/2021] [Accepted: 03/15/2021] [Indexed: 01/09/2023] Open
Abstract
Human corticospinal transmission is commonly studied using brain stimulation. However, this approach is biased to activity in the fastest conducting axons. It is unclear whether conclusions obtained in this context are representative of volitional activity in mild-to-moderate contractions. An alternative to overcome this limitation may be to study the corticospinal transmission of endogenously generated brain activity. Here, we investigate in humans (N = 19; of either sex), the transmission speeds of cortical β rhythms (∼20 Hz) traveling to arm (first dorsal interosseous) and leg (tibialis anterior; TA) muscles during tonic mild contractions. For this purpose, we propose two improvements for the estimation of corticomuscular β transmission delays. First, we show that the cumulant density (cross-covariance) is more accurate than the commonly-used directed coherence to estimate transmission delays in bidirectional systems transmitting band-limited signals. Second, we show that when spiking motor unit activity is used instead of interference electromyography, corticomuscular transmission delay estimates are unaffected by the shapes of the motor unit action potentials (MUAPs). Applying these improvements, we show that descending corticomuscular β transmission is only 1-2 ms slower than expected from the fastest corticospinal pathways. In the last part of our work, we show results from simulations using estimated distributions of the conduction velocities for descending axons projecting to lower motoneurons (from macaque histologic measurements) to suggest two scenarios that can explain fast corticomuscular transmission: either only the fastest corticospinal axons selectively transmit β activity, or else the entire pool does. The implications of these two scenarios for our understanding of corticomuscular interactions are discussed.SIGNIFICANCE STATEMENT We present and validate an improved methodology to measure the delay in the transmission of cortical β activity to tonically-active muscles. The estimated corticomuscular β transmission delays obtained with this approach are remarkably similar to those expected from transmission in the fastest corticospinal axons. A simulation of β transmission along a pool of corticospinal axons using an estimated distribution of fiber diameters suggests two possible mechanisms by which fast corticomuscular transmission is achieved: either a very small fraction of the fastest descending axons transmits β activity to the muscles or, alternatively, the entire population does and natural cancellation of slow channels occurs because of the distribution of axon diameters in the corticospinal tract.
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Affiliation(s)
- J Ibáñez
- Department of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom
- Department of Clinical and Movement Disorders, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
| | - A Del Vecchio
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander University, Erlangen-Nürnberg, Erlangen 91052, Germany
| | - J C Rothwell
- Department of Clinical and Movement Disorders, Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
| | - S N Baker
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne NE2 4HH, United Kingdom
| | - D Farina
- Department of Bioengineering, Imperial College London, London SW7 2AZ, United Kingdom
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15
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de Carvalho M, Kiernan MC, Pullman SL, Rezania K, Turner MR, Simmons Z. Neurophysiological features of primary lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener 2021; 21:11-17. [DOI: 10.1080/21678421.2020.1837174] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Affiliation(s)
- Mamede de Carvalho
- Instituto de Fisiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Department of Neurosciences and Mental Health, Hospital de Santa Maria, Centro Hospitalar Universitário de Lisboa Norte, Lisbon, Portugal
| | - Matthew C. Kiernan
- Brain and Mind Centre, University of Sydney, and Department of Neurology, Royal Prince Alfred Hospital, Sydney, Australia
| | - Seth L Pullman
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Kourosh Rezania
- Department of Neurology, The University of Chicago, Chicago, IL, USA
| | - MR Turner
- Department of Clinical Neurology, University of Oxford, John Radcliffe Hospital, Oxford, UK, and
| | - Zachary Simmons
- Department of Neurology, Pennsylvania State University, Hershey, PA, US
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16
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Aikio R, Laaksonen K, Sairanen V, Parkkonen E, Abou Elseoud A, Kujala J, Forss N. CMC is more than a measure of corticospinal tract integrity in acute stroke patients. NEUROIMAGE: CLINICAL 2021; 32:102818. [PMID: 34555801 PMCID: PMC8458977 DOI: 10.1016/j.nicl.2021.102818] [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: 12/29/2020] [Revised: 06/06/2021] [Accepted: 08/30/2021] [Indexed: 11/17/2022] Open
Abstract
CMC is weaker and occurs at lower frequencies in acute stroke patients. Both afferent and efferent input signals contribute to CMC. CMC should not be used as a direct measure of corticospinal tract integrity.
In healthy subjects, motor cortex activity and electromyographic (EMG) signals from contracting contralateral muscle show coherence in the beta (15–30 Hz) range. Corticomuscular coherence (CMC) is considered a sign of functional coupling between muscle and brain. Based on prior studies, CMC is altered in stroke, but functional significance of this finding has remained unclear. Here, we examined CMC in acute stroke patients and correlated the results with clinical outcome measures and corticospinal tract (CST) integrity estimated with diffusion tensor imaging (DTI). During isometric contraction of the extensor carpi radialis muscle, EMG and magnetoencephalographic oscillatory signals were recorded from 29 patients with paresis of the upper extremity due to ischemic stroke and 22 control subjects. CMC amplitudes and peak frequencies at 13–30 Hz were compared between the two groups. In the patients, the peak frequency in both the affected and the unaffected hemisphere was significantly (p < 0.01) lower and the strength of CMC was significantly (p < 0.05) weaker in the affected hemisphere compared to the control subjects. The strength of CMC in the patients correlated with the level of tactile sensitivity and clinical test results of hand function. In contrast, no correlation between measures of CST integrity and CMC was found. The results confirm the earlier findings that CMC is altered in acute stroke and demonstrate that CMC is bidirectional and not solely a measure of integrity of the efferent corticospinal tract.
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17
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Zilio F, Gomez-Pilar J, Cao S, Zhang J, Zang D, Qi Z, Tan J, Hiromi T, Wu X, Fogel S, Huang Z, Hohmann MR, Fomina T, Synofzik M, Grosse-Wentrup M, Owen AM, Northoff G. Are intrinsic neural timescales related to sensory processing? Evidence from abnormal behavioral states. Neuroimage 2020; 226:117579. [PMID: 33221441 DOI: 10.1016/j.neuroimage.2020.117579] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 10/15/2020] [Accepted: 11/12/2020] [Indexed: 12/11/2022] Open
Abstract
The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioral states. We address these questions by investigating the brain's intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activity's intrinsic neural timescale is related to the neural capacity that specifically supports sensory rather than motor information processing in the healthy brain.
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Affiliation(s)
- Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy.
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Shumei Cao
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jun Zhang
- Department of Anesthesiology, Huashan Hospital, Fudan University, Shanghai, China
| | - Di Zang
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Jiaxing Tan
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Tanigawa Hiromi
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Xuehai Wu
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China
| | - Stuart Fogel
- The Brain and Mind Institute, Department of Physiology and Pharmacology and the Department of Psychology, University of Western Ontario, Canada
| | - Zirui Huang
- Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Matthias R Hohmann
- Department for Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany
| | - Tatiana Fomina
- Department for Empirical Inference, Max Planck Institute for Intelligent Systems, Tübingen, Germany
| | - Matthis Synofzik
- Department of Neurology, Hertie Institute for Clinical Brain Research, Tübingen, Germany
| | - Moritz Grosse-Wentrup
- Research Group Neuroinformatics, Faculty of Computer Science, University of Vienna, Austria
| | - Adrian M Owen
- The Brain and Mind Institute, Department of Physiology and Pharmacology and the Department of Psychology, University of Western Ontario, Canada
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
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18
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Coffey A, Bista S, Fasano A, Buxo T, Mitchell M, Giglia ER, Dukic S, Fenech M, Barry M, Wade A, Heverin M, Muthuraman M, Carson RG, Lowery M, Hardiman O, Nasseroleslami B. Altered supraspinal motor networks in survivors of poliomyelitis: A cortico-muscular coherence study. Clin Neurophysiol 2020; 132:106-113. [PMID: 33271481 DOI: 10.1016/j.clinph.2020.10.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 10/25/2020] [Accepted: 10/26/2020] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Poliomyelitis results in changes to the anterior horn cell. The full extent of cortical network changes in the motor physiology of polio survivors has not been established. Our aim was to investigate how focal degeneration of the lower motor neurons (LMN) in infancy/childhood affects motor network connectivity in adult survivors of polio. METHODS Surface electroencephalography (EEG) and electromyography (EMG) were recorded during an isometric pincer grip task in 25 patients and 11 healthy controls. Spectral signal analysis of cortico-muscular (EEG-EMG) coherence (CMC) was used to identify the cortical regions that are functionally synchronous and connected to the periphery during the pincer grip task. RESULTS A pattern of CMC was noted in polio survivors that was not present in healthy individuals. Significant CMC in low gamma frequency bands (30-47 Hz) was observed in frontal and parietal regions. CONCLUSION These findings imply a differential engagement of cortical networks in polio survivors that extends beyond the motor cortex and suggest a disease-related functional reorganisation of the cortical motor network. SIGNIFICANCE This research has implications for other similar LMN conditions, including spinal muscular atrophy (SMA). CMC has potential in future clinical trials as a biomarker of altered function in motor networks in post-polio syndrome, SMA, and other related conditions.
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Affiliation(s)
- Amina Coffey
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Saroj Bista
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Antonio Fasano
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland
| | - Teresa Buxo
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Matthew Mitchell
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Eileen Rose Giglia
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Stefan Dukic
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland; Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, the Netherlands.
| | - Matthew Fenech
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Megan Barry
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Andrew Wade
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland
| | - Mark Heverin
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
| | - Muthuraman Muthuraman
- Section of Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Johannes-Gutenberg-University Hospital, Mainz, Germany.
| | - Richard G Carson
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, the University of Dublin, Ireland; School of Psychology, Queen's University Belfast, Northern Ireland, UK.
| | - Madeleine Lowery
- School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland.
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland; Beaumont Hospital, Beaumont Road, Dublin 9, Ireland.
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, The University of Dublin, Ireland.
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19
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McColgan P, Joubert J, Tabrizi SJ, Rees G. The human motor cortex microcircuit: insights for neurodegenerative disease. Nat Rev Neurosci 2020; 21:401-415. [PMID: 32555340 DOI: 10.1038/s41583-020-0315-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2020] [Indexed: 12/22/2022]
Abstract
The human motor cortex comprises a microcircuit of five interconnected layers with different cell types. In this Review, we use a layer-specific and cell-specific approach to integrate physiological accounts of this motor cortex microcircuit with the pathophysiology of neurodegenerative diseases affecting motor functions. In doing so we can begin to link motor microcircuit pathology to specific disease stages and clinical phenotypes. Based on microcircuit physiology, we can make future predictions of axonal loss and microcircuit dysfunction. With recent advances in high-resolution neuroimaging we can then test these predictions in humans in vivo, providing mechanistic insights into neurodegenerative disease.
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Affiliation(s)
- Peter McColgan
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.
| | - Julie Joubert
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.,Dementia Research Institute at UCL, London, UK
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK.,UCL Institute of Cognitive Neuroscience, University College London, London, UK
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20
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Turner MR, Barohn RJ, Corcia P, Fink JK, Harms MB, Kiernan MC, Ravits J, Silani V, Simmons Z, Statland J, van den Berg LH, Mitsumoto H. Primary lateral sclerosis: consensus diagnostic criteria. J Neurol Neurosurg Psychiatry 2020; 91:373-377. [PMID: 32029539 PMCID: PMC7147236 DOI: 10.1136/jnnp-2019-322541] [Citation(s) in RCA: 113] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 12/27/2019] [Accepted: 12/27/2019] [Indexed: 02/06/2023]
Abstract
Primary lateral sclerosis (PLS) is a neurodegenerative disorder of the adult motor system. Characterised by a slowly progressive upper motor neuron syndrome, the diagnosis is clinical, after exclusion of structural, neurodegenerative and metabolic mimics. Differentiation of PLS from upper motor neuron-predominant forms of amyotrophic lateral sclerosis remains a significant challenge in the early symptomatic phase of both disorders, with ongoing debate as to whether they form a clinical and histopathological continuum. Current diagnostic criteria for PLS may be a barrier to therapeutic development, requiring long delays between symptom onset and formal diagnosis. While new technologies sensitive to both upper and lower motor neuron involvement may ultimately resolve controversies in the diagnosis of PLS, we present updated consensus diagnostic criteria with the aim of reducing diagnostic delay, optimising therapeutic trial design and catalysing the development of disease-modifying therapy.
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Affiliation(s)
- Martin R Turner
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Richard J Barohn
- Department of Neurology, The University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Philippe Corcia
- ALS Centre, Department of Neurology, CHRU Bretonneau, Tours, France
| | - John K Fink
- Neurology, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew B Harms
- Neurology, Columbia University College of Physicians and Surgeons, New York City, New York, USA
| | - Matthew C Kiernan
- Bushell Chair of Neurology, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia.,Neurology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
| | - John Ravits
- Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Vincenzo Silani
- Department of Neurology & Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS, Milano, Italy.,Department of Pathophysiology & Transplantation, "Dino Ferrari" Center, Università degli Studi di Milano, Milano, Italy
| | - Zachary Simmons
- Neurology, Penn State Health Milton S Hershey Medical Center, Hershey, Pennsylvania, USA
| | - Jeffrey Statland
- Department of Neurology, The University of Kansas Medical Center, Kansas City, Kansas, USA
| | | | | | - Hiroshi Mitsumoto
- Neurology, Columbia University College of Physicians and Surgeons, New York City, New York, USA
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21
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Swash M, Burke D, Turner MR, Grosskreutz J, Leigh PN, deCarvalho M, Kiernan MC. Occasional essay: Upper motor neuron syndrome in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2020; 91:227-234. [PMID: 32054724 DOI: 10.1136/jnnp-2019-321938] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 10/17/2019] [Accepted: 10/24/2019] [Indexed: 11/04/2022]
Affiliation(s)
- Michael Swash
- Barts and the London School of Medicine, QMUL, Instituto de Medicina Molecular, Faculdade de Medicina, Univeridade de Lisboa, London, UK
| | - David Burke
- University of Sydney and Department of Neurology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Julian Grosskreutz
- Universitätsklinikum Jena, Friedrich-Schiller-University Jena, Jena, Germany
| | - P Nigel Leigh
- Trafford Centre for Biomedical Research, Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Mamede deCarvalho
- Instituto de Fisiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Univeridade de Lisboa, and Department of Neurosciences and Mental Health, Hospital de Santa Maria, Centro Hospitalar Universitário de Lisboa Norte, Lisbon, Portugal
| | - Matthew C Kiernan
- University of Sydney and Department of Neurology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia.,Neurology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
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22
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Heideman SG, Quinn AJ, Woolrich MW, van Ede F, Nobre AC. Dissecting beta-state changes during timed movement preparation in Parkinson's disease. Prog Neurobiol 2019; 184:101731. [PMID: 31778771 PMCID: PMC6977086 DOI: 10.1016/j.pneurobio.2019.101731] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 10/18/2019] [Accepted: 11/12/2019] [Indexed: 12/11/2022]
Abstract
An emerging perspective describes beta-band (15-28 Hz) activity as consisting of short-lived high-amplitude events that only appear sustained in conventional measures of trial-average power. This has important implications for characterising abnormalities observed in beta-band activity in disorders like Parkinson's disease. Measuring parameters associated with beta-event dynamics may yield more sensitive measures, provide more selective diagnostic neural markers, and provide greater mechanistic insight into the breakdown of brain dynamics in this disease. Here, we used magnetoencephalography in eighteen Parkinson's disease participants off dopaminergic medication and eighteen healthy control participants to investigate beta-event dynamics during timed movement preparation. We used the Hidden Markov Model to classify event dynamics in a data-driven manner and derived three parameters of beta events: (1) beta-state amplitude, (2) beta-state lifetime, and (3) beta-state interval time. Of these, changes in beta-state interval time explained the overall decreases in beta power during timed movement preparation and uniquely captured the impairment in such preparation in patients with Parkinson's disease. Thus, the increased granularity of the Hidden Markov Model analysis (compared with conventional analysis of power) provides increased sensitivity and suggests a possible reason for impairments of timed movement preparation in Parkinson's disease.
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Affiliation(s)
- Simone G Heideman
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Freek van Ede
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom; Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
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23
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Edmond EC, Stagg CJ, Turner MR. Therapeutic non-invasive brain stimulation in amyotrophic lateral sclerosis: rationale, methods and experience. J Neurol Neurosurg Psychiatry 2019; 90:1131-1138. [PMID: 31072957 DOI: 10.1136/jnnp-2018-320213] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Revised: 03/29/2019] [Accepted: 04/08/2019] [Indexed: 01/24/2023]
Abstract
The neurodegenerative syndrome amyotrophic lateral sclerosis (ALS) is characterised by increased cortical excitability, thought to reflect pathological changes in the balance of local excitatory and inhibitory neuronal influences. Non-invasive brain stimulation (NIBS) has been shown to modulate cortical activity, with some protocols showing effects that outlast the stimulation by months. NIBS has been suggested as a potential therapeutic approach for disorders associated with changes in cortical neurophysiology, including ALS. This article reviews NIBS methodology, rationale for its application to ALS and progress to date.
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Affiliation(s)
- Evan C Edmond
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford University, Oxford, UK.,Oxford Centre for Human Brain Activity (OHBA), Oxford University, Oxford, UK.,Oxford Centre for Functional MRI of the Brain (FMRIB), Oxford University, Oxford, UK
| | - Charlotte J Stagg
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK.,Wellcome Centre for Integrative Neuroimaging, Oxford University, Oxford, UK.,Oxford Centre for Human Brain Activity (OHBA), Oxford University, Oxford, UK.,Oxford Centre for Functional MRI of the Brain (FMRIB), Oxford University, Oxford, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK .,Wellcome Centre for Integrative Neuroimaging, Oxford University, Oxford, UK.,Oxford Centre for Human Brain Activity (OHBA), Oxford University, Oxford, UK.,Oxford Centre for Functional MRI of the Brain (FMRIB), Oxford University, Oxford, UK
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24
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Dukic S, McMackin R, Buxo T, Fasano A, Chipika R, Pinto-Grau M, Costello E, Schuster C, Hammond M, Heverin M, Coffey A, Broderick M, Iyer PM, Mohr K, Gavin B, Pender N, Bede P, Muthuraman M, Lalor EC, Hardiman O, Nasseroleslami B. Patterned functional network disruption in amyotrophic lateral sclerosis. Hum Brain Mapp 2019; 40:4827-4842. [PMID: 31348605 PMCID: PMC6852475 DOI: 10.1002/hbm.24740] [Citation(s) in RCA: 57] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Revised: 07/01/2019] [Accepted: 07/17/2019] [Indexed: 12/11/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease primarily affecting motor function, with additional evidence of extensive nonmotor involvement. Despite increasing recognition of the disease as a multisystem network disorder characterised by impaired connectivity, the precise neuroelectric characteristics of impaired cortical communication remain to be fully elucidated. Here, we characterise changes in functional connectivity using beamformer source analysis on resting‐state electroencephalography recordings from 74 ALS patients and 47 age‐matched healthy controls. Spatiospectral characteristics of network changes in the ALS patient group were quantified by spectral power, amplitude envelope correlation (co‐modulation) and imaginary coherence (synchrony). We show patterns of decreased spectral power in the occipital and temporal (δ‐ to β‐band), lateral/orbitofrontal (δ‐ to θ‐band) and sensorimotor (β‐band) regions of the brain in patients with ALS. Furthermore, we show increased co‐modulation of neural oscillations in the central and posterior (δ‐, θ‐ and γl‐band) and frontal (δ‐ and γl‐band) regions, as well as decreased synchrony in the temporal and frontal (δ‐ to β‐band) and sensorimotor (β‐band) regions. Factorisation of these complex connectivity patterns reveals a distinct disruption of both motor and nonmotor networks. The observed changes in connectivity correlated with structural MRI changes, functional motor scores and cognitive scores. Characteristic patterned changes of cortical function in ALS signify widespread disease‐associated network disruption, pointing to extensive dysfunction of both motor and cognitive networks. These statistically robust findings, that correlate with clinical scores, provide a strong rationale for further development as biomarkers of network disruption for future clinical trials.
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Affiliation(s)
- Stefan Dukic
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland.,Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, The Netherlands
| | - Roisin McMackin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Teresa Buxo
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Antonio Fasano
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Rangariroyashe Chipika
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Marta Pinto-Grau
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Emmet Costello
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Christina Schuster
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Michaela Hammond
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Mark Heverin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Amina Coffey
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Michael Broderick
- Trinity Centre for Bioengineering, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Parameswaran M Iyer
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Kieran Mohr
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Brighid Gavin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Niall Pender
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Muthuraman Muthuraman
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Johannes-Gutenberg-University Hospital, Mainz, Germany
| | - Edmund C Lalor
- Trinity Centre for Bioengineering, Trinity College Dublin, University of Dublin, Dublin, Ireland.,Trinity College Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin, Ireland.,Department of Biomedical Engineering and Department of Neuroscience, University of Rochester, Rochester, New York
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland.,Trinity College Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin, Ireland.,Department of Neurology, Beaumont Hospital, Dublin, Ireland
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
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25
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Liu J, Sheng Y, Liu H. Corticomuscular Coherence and Its Applications: A Review. Front Hum Neurosci 2019; 13:100. [PMID: 30949041 PMCID: PMC6435838 DOI: 10.3389/fnhum.2019.00100] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 03/04/2019] [Indexed: 12/11/2022] Open
Abstract
Corticomuscular coherence (CMC) is an index utilized to indicate coherence between brain motor cortex and associated body muscles, conventionally. As an index of functional connections between the cortex and muscles, CMC research is the focus of neurophysiology in recent years. Although CMC has been extensively studied in healthy subjects and sports disorders, the purpose of its applications is still ambiguous, and the magnitude of CMC varies among individuals. Here, we aim to investigate factors that modulate the variation of CMC amplitude and compare significant CMC between these factors to find a well-developed research prospect. In the present review, we discuss the mechanism of CMC and propose a general definition of CMC. Factors affecting CMC are also summarized as follows: experimental design, band frequencies and force levels, age correlation, and difference between healthy controls and patients. In addition, we provide a detailed overview of the current CMC applications for various motor disorders. Further recognition of the factors affecting CMC amplitude can clarify the physiological mechanism and is beneficial to the implementation of CMC clinical methods.
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Affiliation(s)
- Jinbiao Liu
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yixuan Sheng
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Honghai Liu
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
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26
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Proudfoot M, Bede P, Turner MR. Imaging Cerebral Activity in Amyotrophic Lateral Sclerosis. Front Neurol 2019; 9:1148. [PMID: 30671016 PMCID: PMC6332509 DOI: 10.3389/fneur.2018.01148] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 12/11/2018] [Indexed: 01/30/2023] Open
Abstract
Advances in neuroimaging, complementing histopathological insights, have established a multi-system involvement of cerebral networks beyond the traditional neuromuscular pathological view of amyotrophic lateral sclerosis (ALS). The development of effective disease-modifying therapy remains a priority and this will be facilitated by improved biomarkers of motor system integrity against which to assess the efficacy of candidate drugs. Functional MRI (FMRI) is an established measure of both cerebral activity and connectivity, but there is an increasing recognition of neuronal oscillations in facilitating long-distance communication across the cortical surface. Such dynamic synchronization vastly expands the connectivity foundations defined by traditional neuronal architecture. This review considers the unique pathogenic insights afforded by the capture of cerebral disease activity in ALS using FMRI and encephalography.
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Affiliation(s)
- Malcolm Proudfoot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Peter Bede
- Computational Neuroimaging Group, Academic Unit of Neurology, Trinity College Dublin, Dublin, Ireland
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.,Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
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27
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Turner MR. Progress and new frontiers in biomarkers for amyotrophic lateral sclerosis. Biomark Med 2018; 12:693-696. [PMID: 29856233 DOI: 10.2217/bmm-2018-0149] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Affiliation(s)
- Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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28
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Baker MR, Dharmadasa T, Jaiser SR, Kiernan MC. Amyotrophic lateral sclerosis - Time for beta testing? Clin Neurophysiol 2018; 129:1455-1456. [PMID: 29754830 DOI: 10.1016/j.clinph.2018.04.613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Accepted: 04/18/2018] [Indexed: 11/29/2022]
Affiliation(s)
- M R Baker
- Institute of Neuroscience, The Medical School, Newcastle University, NE2 4HH, UK; Department of Neurology, Royal Victoria Infirmary, Newcastle upon Tyne, NE1 4LP, UK; Department of Clinical Neurophysiology, Royal Victoria Infirmary, Newcastle upon Tyne, NE1 4LP, UK.
| | - T Dharmadasa
- Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - S R Jaiser
- Institute of Neuroscience, The Medical School, Newcastle University, NE2 4HH, UK; Department of Clinical Neurophysiology, Royal Victoria Infirmary, Newcastle upon Tyne, NE1 4LP, UK
| | - M C Kiernan
- Brain and Mind Centre, The University of Sydney, Sydney, Australia; Institute of Clinical Neurosciences, Royal Prince Alfred Hospital, Sydney, Australia
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