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Pauls KAM, Nurmi P, Ala-Salomäki H, Renvall H, Kujala J, Liljeström M. Human sensorimotor resting state beta events and aperiodic activity show good test-retest reliability. Clin Neurophysiol 2024; 163:244-254. [PMID: 38820994 DOI: 10.1016/j.clinph.2024.03.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 03/04/2024] [Accepted: 03/20/2024] [Indexed: 06/02/2024]
Abstract
OBJECTIVE Diseases affecting sensorimotor function impair physical independence. Reliable functional clinical biomarkers allowing early diagnosis or targeting treatment and rehabilitation could reduce this burden. Magnetoencephalography (MEG) non-invasively measures brain rhythms such as the somatomotor 'rolandic' rhythm which shows intermittent high-amplitude beta (14-30 Hz) 'events' that predict behavior across tasks and species and are altered by sensorimotor neurological diseases. METHODS We assessed test-retest stability, a prerequisite for biomarkers, of spontaneous sensorimotor aperiodic (1/f) signal and beta events in 50 healthy human controls across two MEG sessions using the intraclass correlation coefficient (ICC). Beta events were determined using an amplitude-thresholding approach on a narrow-band filtered amplitude envelope obtained using Morlet wavelet decomposition. RESULTS Resting sensorimotor characteristics showed good to excellent test-retest stability. Aperiodic component (ICC 0.77-0.88) and beta event amplitude (ICC 0.74-0.82) were very stable, whereas beta event duration was more variable (ICC 0.55-0.7). 2-3 minute recordings were sufficient to obtain stable results. Analysis automatization was successful in 86%. CONCLUSIONS Sensorimotor beta phenotype is a stable feature of an individual's resting brain activity even for short recordings easily measured in patients. SIGNIFICANCE Spontaneous sensorimotor beta phenotype has potential as a clinical biomarker of sensorimotor system integrity.
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Affiliation(s)
- K Amande M Pauls
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, 00290 Helsinki, Finland; Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, 00029 Helsinki, Finland.
| | - Pietari Nurmi
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, 02150 Espoo, Finland
| | - Heidi Ala-Salomäki
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, 02150 Espoo, Finland
| | - Hanna Renvall
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, 00290 Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, 02150 Espoo, Finland
| | - Jan Kujala
- Department of Psychology, University of Jyväskylä, 40014 Jyväskylä, Finland
| | - Mia Liljeström
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, 00290 Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, 02150 Espoo, Finland; Aalto NeuroImaging, Aalto University, 00076 Aalto, Finland
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2
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Dash D, Teplansky K, Ferrari P, Babajani-Feremi A, Calley CS, Heitzman D, Austin SG, Wang J. Automatic detection of ALS from single-trial MEG signals during speech tasks: a pilot study. Front Psychol 2024; 15:1114811. [PMID: 38903475 PMCID: PMC11188989 DOI: 10.3389/fpsyg.2024.1114811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 05/24/2024] [Indexed: 06/22/2024] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is an idiopathic, fatal, and fast-progressive neurodegenerative disease characterized by the degeneration of motor neurons. ALS patients often experience an initial misdiagnosis or a diagnostic delay due to the current unavailability of an efficient biomarker. Since impaired speech is typical in ALS, we hypothesized that functional differences between healthy and ALS participants during speech tasks can be explained by cortical pattern changes, thereby leading to the identification of a neural biomarker for ALS. In this pilot study, we collected magnetoencephalography (MEG) recordings from three early-diagnosed patients with ALS and three healthy controls during imagined (covert) and overt speech tasks. First, we computed sensor correlations, which showed greater correlations for speakers with ALS than healthy controls. Second, we compared the power of the MEG signals in canonical bands between the two groups, which showed greater dissimilarity in the beta band for ALS participants. Third, we assessed differences in functional connectivity, which showed greater beta band connectivity for ALS than healthy controls. Finally, we performed single-trial classification, which resulted in highest performance with beta band features (∼ 98%). These findings were consistent across trials, phrases, and participants for both imagined and overt speech tasks. Our preliminary results indicate that speech-evoked beta oscillations could be a potential neural biomarker for diagnosing ALS. To our knowledge, this is the first demonstration of the detection of ALS from single-trial neural signals.
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Affiliation(s)
- Debadatta Dash
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - Kristin Teplansky
- Department of Speech, Language, and Hearing Sciences, University of Texas at Austin, Austin, TX, United States
| | - Paul Ferrari
- Helen DeVos Children’s Hospital, Corewell Health, Grand Rapids, MI, United States
| | | | - Clifford S. Calley
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | | | - Sara G. Austin
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - Jun Wang
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
- Department of Speech, Language, and Hearing Sciences, University of Texas at Austin, Austin, TX, United States
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3
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Trubshaw M, Gohil C, Yoganathan K, Kohl O, Edmond E, Proudfoot M, Thompson AG, Talbot K, Stagg CJ, Nobre AC, Woolrich M, Turner MR. The cortical neurophysiological signature of amyotrophic lateral sclerosis. Brain Commun 2024; 6:fcae164. [PMID: 38779353 PMCID: PMC11109820 DOI: 10.1093/braincomms/fcae164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/11/2024] [Accepted: 03/09/2024] [Indexed: 05/25/2024] Open
Abstract
The progressive loss of motor function characteristic of amyotrophic lateral sclerosis is associated with widespread cortical pathology extending beyond primary motor regions. Increasing muscle weakness reflects a dynamic, variably compensated brain network disorder. In the quest for biomarkers to accelerate therapeutic assessment, the high temporal resolution of magnetoencephalography is uniquely able to non-invasively capture micro-magnetic fields generated by neuronal activity across the entire cortex simultaneously. This study examined task-free magnetoencephalography to characterize the cortical oscillatory signature of amyotrophic lateral sclerosis for having potential as a pharmacodynamic biomarker. Eight to ten minutes of magnetoencephalography in the task-free, eyes-open state was recorded in amyotrophic lateral sclerosis (n = 36) and healthy age-matched controls (n = 51), followed by a structural MRI scan for co-registration. Extracted magnetoencephalography metrics from the delta, theta, alpha, beta, low-gamma, high-gamma frequency bands included oscillatory power (regional activity), 1/f exponent (complexity) and amplitude envelope correlation (connectivity). Groups were compared using a permutation-based general linear model with correction for multiple comparisons and confounders. To test whether the extracted metrics could predict disease severity, a random forest regression model was trained and evaluated using nested leave-one-out cross-validation. Amyotrophic lateral sclerosis was characterized by reduced sensorimotor beta band and increased high-gamma band power. Within the premotor cortex, increased disability was associated with a reduced 1/f exponent. Increased disability was more widely associated with increased global connectivity in the delta, theta and high-gamma bands. Intra-hemispherically, increased disability scores were particularly associated with increases in temporal connectivity and inter-hemispherically with increases in frontal and occipital connectivity. The random forest model achieved a coefficient of determination (R2) of 0.24. The combined reduction in cortical sensorimotor beta and rise in gamma power is compatible with the established hypothesis of loss of inhibitory, GABAergic interneuronal circuits in pathogenesis. A lower 1/f exponent potentially reflects a more excitable cortex and a pathology unique to amyotrophic lateral sclerosis when considered with the findings published in other neurodegenerative disorders. Power and complexity changes corroborate with the results from paired-pulse transcranial magnetic stimulation. Increased magnetoencephalography connectivity in worsening disability is thought to represent compensatory responses to a failing motor system. Restoration of cortical beta and gamma band power has significant potential to be tested in an experimental medicine setting. Magnetoencephalography-based measures have potential as sensitive outcome measures of therapeutic benefit in drug trials and may have a wider diagnostic value with further study, including as predictive markers in asymptomatic carriers of disease-causing genetic variants.
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Affiliation(s)
- Michael Trubshaw
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Chetan Gohil
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Katie Yoganathan
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Oliver Kohl
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Evan Edmond
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Malcolm Proudfoot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Alexander G Thompson
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Kevin Talbot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Charlotte J Stagg
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Martin R Turner
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
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Salzinger A, Ramesh V, Das Sharma S, Chandran S, Thangaraj Selvaraj B. Neuronal Circuit Dysfunction in Amyotrophic Lateral Sclerosis. Cells 2024; 13:792. [PMID: 38786016 PMCID: PMC11120636 DOI: 10.3390/cells13100792] [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: 03/19/2024] [Revised: 04/27/2024] [Accepted: 04/30/2024] [Indexed: 05/25/2024] Open
Abstract
The primary neural circuit affected in Amyotrophic Lateral Sclerosis (ALS) patients is the corticospinal motor circuit, originating in upper motor neurons (UMNs) in the cerebral motor cortex which descend to synapse with the lower motor neurons (LMNs) in the spinal cord to ultimately innervate the skeletal muscle. Perturbation of these neural circuits and consequent loss of both UMNs and LMNs, leading to muscle wastage and impaired movement, is the key pathophysiology observed. Despite decades of research, we are still lacking in ALS disease-modifying treatments. In this review, we document the current research from patient studies, rodent models, and human stem cell models in understanding the mechanisms of corticomotor circuit dysfunction and its implication in ALS. We summarize the current knowledge about cortical UMN dysfunction and degeneration, altered excitability in LMNs, neuromuscular junction degeneration, and the non-cell autonomous role of glial cells in motor circuit dysfunction in relation to ALS. We further highlight the advances in human stem cell technology to model the complex neural circuitry and how these can aid in future studies to better understand the mechanisms of neural circuit dysfunction underpinning ALS.
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Affiliation(s)
- Andrea Salzinger
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK; (A.S.); (V.R.); (S.D.S.); (S.C.)
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Vidya Ramesh
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK; (A.S.); (V.R.); (S.D.S.); (S.C.)
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Shreya Das Sharma
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK; (A.S.); (V.R.); (S.D.S.); (S.C.)
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Siddharthan Chandran
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK; (A.S.); (V.R.); (S.D.S.); (S.C.)
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic (ARRNC), University of Edinburgh, Edinburgh EH16 4SB, UK
| | - Bhuvaneish Thangaraj Selvaraj
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK; (A.S.); (V.R.); (S.D.S.); (S.C.)
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH16 4SB, UK
- Anne Rowling Regenerative Neurology Clinic (ARRNC), University of Edinburgh, Edinburgh EH16 4SB, UK
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5
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Dukic S, Fasano A, Coffey A, Buxó T, McMackin R, Chipika R, Heverin M, Bede P, Muthuraman M, Lowery M, Carson RG, Hardiman O, Nasseroleslami B. Electroencephalographic β-band oscillations in the sensorimotor network reflect motor symptom severity in amyotrophic lateral sclerosis. Eur J Neurol 2024; 31:e16201. [PMID: 38235854 PMCID: PMC11235881 DOI: 10.1111/ene.16201] [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: 07/31/2023] [Revised: 11/27/2023] [Accepted: 12/21/2023] [Indexed: 01/19/2024]
Abstract
BACKGROUND AND PURPOSE Resting-state electroencephalography (EEG) holds promise for assessing brain networks in amyotrophic lateral sclerosis (ALS). We investigated whether neural β-band oscillations in the sensorimotor network could serve as an objective quantitative measure of progressive motor impairment and functional disability in ALS patients. METHODS Resting-state EEG was recorded in 18 people with ALS and 38 age- and gender-matched healthy controls. We estimated source-localized β-band spectral power in the sensorimotor cortex. Clinical evaluation included lower (LMN) and upper motor neuron scores, Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score, fine motor function (FMF) subscore, and progression rate. Correlations between clinical scores and β-band power were analysed and corrected using a false discovery rate of q = 0.05. RESULTS β-Band power was significantly lower in people with ALS than controls (p = 0.004), and correlated with LMN score (R = -0.65, p = 0.013), FMF subscore (R = -0.53, p = 0.036), and FMF progression rate (R = 0.52, p = 0.036). CONCLUSIONS β-Band spectral power in the sensorimotor cortex reflects clinically evaluated motor impairment in ALS. This technology merits further investigation as a biomarker of progressive functional disability.
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Affiliation(s)
- Stefan Dukic
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
- Department of Neurology, University Medical Centre Utrecht Brain CentreUtrecht UniversityUtrechtthe Netherlands
| | - Antonio Fasano
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
| | - Amina Coffey
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
| | - Teresa Buxó
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
| | - Roisin McMackin
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
- Discipline of Physiology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
| | - Rangariroyashe Chipika
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
| | - Mark Heverin
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Muthuraman Muthuraman
- Neural Engineering With Signal Analytics and Artificial Intelligence, Department of NeurologyUniversity of WürzburgWürzburgGermany
| | - Madeleine Lowery
- School of Electrical and Electronic EngineeringUniversity College DublinDublinIreland
| | - Richard G. Carson
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College DublinUniversity of DublinDublinIreland
- School of PsychologyQueen's University BelfastBelfastIreland
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
- Department of NeurologyBeaumont HospitalDublinIreland
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, School of Medicine, Trinity College DublinUniversity of DublinDublinIreland
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6
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McMackin R, Bede P, Ingre C, Malaspina A, Hardiman O. Biomarkers in amyotrophic lateral sclerosis: current status and future prospects. Nat Rev Neurol 2023; 19:754-768. [PMID: 37949994 DOI: 10.1038/s41582-023-00891-2] [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] [Accepted: 10/09/2023] [Indexed: 11/12/2023]
Abstract
Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us predict the disease course and survival, but quantitative measures are also needed that can enhance the sensitivity of the clinical categorization. In this Review, we describe the emerging landscape of diagnostic, categorical and pharmacodynamic biomarkers in amyotrophic lateral sclerosis and their place in the rapidly evolving landscape of new therapeutics. Fluid-based markers from cerebrospinal fluid, blood and urine are emerging as useful diagnostic, pharmacodynamic and predictive biomarkers. Combinations of imaging measures have the potential to provide important diagnostic and prognostic information, and neurophysiological methods, including various electromyography-based measures and quantitative EEG-magnetoencephalography-evoked responses and corticomuscular coherence, are generating useful diagnostic, categorical and prognostic markers. Although none of these biomarker technologies has been fully incorporated into clinical practice or clinical trials as a primary outcome measure, strong evidence is accumulating to support their clinical utility.
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Affiliation(s)
- Roisin McMackin
- Discipline of Physiology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | - Peter Bede
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Caroline Ingre
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Andrea Malaspina
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland.
- Department of Neurology, Beaumont Hospital, Dublin, Ireland.
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7
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Sattler R, Traynor BJ, Robertson J, Van Den Bosch L, Barmada SJ, Svendsen CN, Disney MD, Gendron TF, Wong PC, Turner MR, Boxer A, Babu S, Benatar M, Kurnellas M, Rohrer JD, Donnelly CJ, Bustos LM, Van Keuren-Jensen K, Dacks PA, Sabbagh MN. Roadmap for C9ORF72 in Frontotemporal Dementia and Amyotrophic Lateral Sclerosis: Report on the C9ORF72 FTD/ALS Summit. Neurol Ther 2023; 12:1821-1843. [PMID: 37847372 PMCID: PMC10630271 DOI: 10.1007/s40120-023-00548-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 09/14/2023] [Indexed: 10/18/2023] Open
Abstract
A summit held March 2023 in Scottsdale, Arizona (USA) focused on the intronic hexanucleotide expansion in the C9ORF72 gene and its relevance in frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS; C9ORF72-FTD/ALS). The goal of this summit was to connect basic scientists, clinical researchers, drug developers, and individuals affected by C9ORF72-FTD/ALS to evaluate how collaborative efforts across the FTD-ALS disease spectrum might break down existing disease silos. Presentations and discussions covered recent discoveries in C9ORF72-FTD/ALS disease mechanisms, availability of disease biomarkers and recent advances in therapeutic development, and clinical trial design for prevention and treatment for individuals affected by C9ORF72-FTD/ALS and asymptomatic pathological expansion carriers. The C9ORF72-associated hexanucleotide repeat expansion is an important locus for both ALS and FTD. C9ORF72-FTD/ALS may be characterized by loss of function of the C9ORF72 protein and toxic gain of functions caused by both dipeptide repeat (DPR) proteins and hexanucleotide repeat RNA. C9ORF72-FTD/ALS therapeutic strategies discussed at the summit included the use of antisense oligonucleotides, adeno-associated virus (AAV)-mediated gene silencing and gene delivery, and engineered small molecules targeting RNA structures associated with the C9ORF72 expansion. Neurofilament light chain, DPR proteins, and transactive response (TAR) DNA-binding protein 43 (TDP-43)-associated molecular changes were presented as biomarker candidates. Similarly, brain imaging modalities (i.e., magnetic resonance imaging [MRI] and positron emission tomography [PET]) measuring structural, functional, and metabolic changes were discussed as important tools to monitor individuals affected with C9ORF72-FTD/ALS, at both pre-symptomatic and symptomatic disease stages. Finally, summit attendees evaluated current clinical trial designs available for FTD or ALS patients and concluded that therapeutics relevant to FTD/ALS patients, such as those specifically targeting C9ORF72, may need to be tested with composite endpoints covering clinical symptoms of both FTD and ALS. The latter will require novel clinical trial designs to be inclusive of all patient subgroups spanning the FTD/ALS spectrum.
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Affiliation(s)
- Rita Sattler
- Barrow Neurological Institute, 2910 N Third Ave, Phoenix, AZ, 85013, USA.
| | - Bryan J Traynor
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Janice Robertson
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
| | - Ludo Van Den Bosch
- VIB, Center for Brain & Disease Research, Laboratory of Neurobiology and KU Leuven, Leuven, Belgium
- Department of Neurosciences, Experimental Neurology and Leuven Brain Institute (LBI), University of Leuven, Leuven, Belgium
| | - Sami J Barmada
- Department of Neurology, Neuroscience Program, University of Michigan, Ann Arbor, MI, USA
| | - Clive N Svendsen
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Matthew D Disney
- Department of Chemistry, The Herbert Wertheim UF-Scripps Institute for Biomedical Research and Innovation, The Scripps Research Institute, Jupiter, FL, USA
| | - Tania F Gendron
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Philip C Wong
- Departments of Pathology and Neuroscience, Johns Hopkins Medicine, Baltimore, MD, USA
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Adam Boxer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of San Francisco, San Francisco, CA, USA
| | - Suma Babu
- Sean M. Healey and AMG Center for ALS and the Neurological Clinical Research Institute, Massachusetts General Hospital-Harvard Medical School, Boston, MA, USA
| | - Michael Benatar
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, 33129, USA
| | | | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Christopher J Donnelly
- LiveLikeLou Center for ALS Research, Brain Institute, University of Pittsburgh, Pittsburgh, USA
- Department of Neurobiology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lynette M Bustos
- Barrow Neurological Institute, 2910 N Third Ave, Phoenix, AZ, 85013, USA
| | | | - Penny A Dacks
- The Association for Frontotemporal Degeneration and FTD Disorders Registry, King of Prussia, PA, USA
| | - Marwan N Sabbagh
- Barrow Neurological Institute, 2910 N Third Ave, Phoenix, AZ, 85013, USA.
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8
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Xie M, Pallegar PN, Parusel S, Nguyen AT, Wu LJ. Regulation of cortical hyperexcitability in amyotrophic lateral sclerosis: focusing on glial mechanisms. Mol Neurodegener 2023; 18:75. [PMID: 37858176 PMCID: PMC10585818 DOI: 10.1186/s13024-023-00665-w] [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: 04/01/2023] [Accepted: 10/05/2023] [Indexed: 10/21/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the loss of both upper and lower motor neurons, resulting in muscle weakness, atrophy, paralysis, and eventually death. Motor cortical hyperexcitability is a common phenomenon observed at the presymptomatic stage of ALS. Both cell-autonomous (the intrinsic properties of motor neurons) and non-cell-autonomous mechanisms (cells other than motor neurons) are believed to contribute to cortical hyperexcitability. Decoding the pathological relevance of these dynamic changes in motor neurons and glial cells has remained a major challenge. This review summarizes the evidence of cortical hyperexcitability from both clinical and preclinical research, as well as the underlying mechanisms. We discuss the potential role of glial cells, particularly microglia, in regulating abnormal neuronal activity during the disease progression. Identifying early changes such as neuronal hyperexcitability in the motor system may provide new insights for earlier diagnosis of ALS and reveal novel targets to halt the disease progression.
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Affiliation(s)
- Manling Xie
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Praveen N Pallegar
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, USA
| | - Sebastian Parusel
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Long-Jun Wu
- Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.
- Department of Immunology, Mayo Clinic, Rochester, MN, USA.
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9
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Xia Y, Sun H, Hua L, Dai Z, Wang X, Tang H, Han Y, Du Y, Zhou H, Zou H, Yao Z, Lu Q. Spontaneous beta power, motor-related beta power and cortical thickness in major depressive disorder with psychomotor disturbance. Neuroimage Clin 2023; 38:103433. [PMID: 37216848 PMCID: PMC10209543 DOI: 10.1016/j.nicl.2023.103433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/05/2023] [Accepted: 05/11/2023] [Indexed: 05/24/2023]
Abstract
INTRODUCTION The psychomotor disturbance is a common symptom in patients with major depressive disorder (MDD). The neurological mechanisms of psychomotor disturbance are intricate, involving alterations in the structure and function of motor-related regions. However, the relationship among changes in the spontaneous activity, motor-related activity, local cortical thickness, and psychomotor function remains unclear. METHOD A total of 140 patients with MDD and 68 healthy controls performed a simple right-hand visuomotor task during magnetoencephalography (MEG) scanning. All patients were divided into two groups according to the presence of psychomotor slowing. Spontaneous beta power, movement-related beta desynchronization (MRBD), absolute beta power during movement and cortical characteristics in the bilateral primary motor cortex were compared using general linear models with the group as a fixed effect and age as a covariate. Finally, the moderated mediation model was tested to examine the relationship between brain metrics with group differences and psychomotor performance. RESULTS The patients with psychomotor slowing showed higher spontaneous beta power, movement-related beta desynchronization and absolute beta power during movement than patients without psychomotor slowing. Compared with the other two groups, significant decreases were found in cortical thickness of the left primary motor cortex in patients with psychomotor slowing. Our moderated mediation model showed that the increased spontaneous beta power indirectly affected impaired psychomotor performance by abnormal MRBD, and the indirect effects were moderated by cortical thickness. CONCLUSION These results suggest that patients with MDD have aberrant cortical beta activity at rest and during movement, combined with abnormal cortical thickness, contributing to the psychomotor disturbance observed in this patient population.
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Affiliation(s)
- Yi Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hao Sun
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Lingling Hua
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing 210096, China
| | - Xiaoqin Wang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hao Tang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yinglin Han
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yishan Du
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hongliang Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Haowen Zou
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Zhijian Yao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing 210096, China.
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10
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Perry A, Hughes LE, Adams N, Naessens M, Murley AG, Rouse MA, Street D, Jones PS, Cope TE, Kocagoncu E, Rowe JB. The neurophysiological effect of NMDA-R antagonism of frontotemporal lobar degeneration is conditional on individual GABA concentration. Transl Psychiatry 2022; 12:348. [PMID: 36030249 PMCID: PMC9420128 DOI: 10.1038/s41398-022-02114-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/09/2022] [Accepted: 08/11/2022] [Indexed: 02/02/2023] Open
Abstract
There is a pressing need to accelerate therapeutic strategies against the syndromes caused by frontotemporal lobar degeneration, including symptomatic treatments. One approach is for experimental medicine, coupling neurophysiological studies of the mechanisms of disease with pharmacological interventions aimed at restoring neurochemical deficits. Here we consider the role of glutamatergic deficits and their potential as targets for treatment. We performed a double-blind placebo-controlled crossover pharmaco-magnetoencephalography study in 20 people with symptomatic frontotemporal lobar degeneration (10 behavioural variant frontotemporal dementia, 10 progressive supranuclear palsy) and 19 healthy age- and gender-matched controls. Both magnetoencephalography sessions recorded a roving auditory oddball paradigm: on placebo or following 10 mg memantine, an uncompetitive NMDA-receptor antagonist. Ultra-high-field magnetic resonance spectroscopy confirmed lower concentrations of GABA in the right inferior frontal gyrus of people with frontotemporal lobar degeneration. While memantine showed a subtle effect on early-auditory processing in patients, there was no significant main effect of memantine on the magnitude of the mismatch negativity (MMN) response in the right frontotemporal cortex in patients or controls. However, the change in the right auditory cortex MMN response to memantine (vs. placebo) in patients correlated with individuals' prefrontal GABA concentration. There was no moderating effect of glutamate concentration or cortical atrophy. This proof-of-concept study demonstrates the potential for baseline dependency in the pharmacological restoration of neurotransmitter deficits to influence cognitive neurophysiology in neurodegenerative disease. With changes to multiple neurotransmitters in frontotemporal lobar degeneration, we suggest that individuals' balance of excitation and inhibition may determine drug efficacy, with implications for drug selection and patient stratification in future clinical trials.
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Affiliation(s)
- Alistair Perry
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK.
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK.
| | - Laura E Hughes
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Natalie Adams
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Michelle Naessens
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Alexander G Murley
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Matthew A Rouse
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
| | - Duncan Street
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - P Simon Jones
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Thomas E Cope
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Ece Kocagoncu
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - James B Rowe
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK
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11
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Romano A, Trosi Lopez E, Liparoti M, Polverino A, Minino R, Trojsi F, Bonavita S, Mandolesi L, Granata C, Amico E, Sorrentino G, Sorrentino P. The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment. Neuroimage Clin 2022; 35:103095. [PMID: 35764029 PMCID: PMC9241102 DOI: 10.1016/j.nicl.2022.103095] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/31/2022] [Accepted: 06/19/2022] [Indexed: 10/25/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = -7.40), and the MiToS (p = 0.0025; β = -4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho = -0.6041, p = 0.0003) and MiToS scales (Spearman's rho = -0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.
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Affiliation(s)
- Antonella Romano
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Emahnuel Trosi Lopez
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Marianna Liparoti
- Department of Social and Developmental Psychology, University of Rome "Sapienza", Italy
| | - Arianna Polverino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy
| | - Roberta Minino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Francesca Trojsi
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Simona Bonavita
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Laura Mandolesi
- Department of Humanistic Studies, University of Naples Federico II, via Porta di Massa 1, 80133, Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy
| | - Enrico Amico
- Institute of Bioengineering, Center for Neuroprosthetics, EPFL, Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy; Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy; Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy; Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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12
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Govaarts R, Beeldman E, Fraschini M, Griffa A, Engels MMA, van Es MA, Veldink JH, van den Berg LH, van der Kooi AJ, Pijnenburg YAL, de Visser M, Stam CJ, Raaphorst J, Hillebrand A. Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia. Neuroimage Clin 2022; 34:102965. [PMID: 35217500 PMCID: PMC8867127 DOI: 10.1016/j.nicl.2022.102965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 01/17/2023]
Abstract
The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends.
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Affiliation(s)
- Rosanne Govaarts
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Emma Beeldman
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Matteo Fraschini
- University of Cagliari, Department of Electrical and Electronic Engineering, Cagliari, Italy
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Marjolein M A Engels
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Michael A van Es
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Jan H Veldink
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Leonard H van den Berg
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Anneke J van der Kooi
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam University Medical Centers, Vrije Universiteit, Alzheimer Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Marianne de Visser
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Joost Raaphorst
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
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13
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Cortical Hyperexcitability in the Driver’s Seat in ALS. CLINICAL AND TRANSLATIONAL NEUROSCIENCE 2022. [DOI: 10.3390/ctn6010005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal disease characterized by the degeneration of cortical and spinal motor neurons. With no effective treatment available to date, patients face progressive paralysis and eventually succumb to the disease due to respiratory failure within only a few years. Recent research has revealed the multifaceted nature of the mechanisms and cell types involved in motor neuron degeneration, thereby opening up new therapeutic avenues. Intriguingly, two key features present in both ALS patients and rodent models of the disease are cortical hyperexcitability and hyperconnectivity, the mechanisms of which are still not fully understood. We here recapitulate current findings arguing for cell autonomous and non-cell autonomous mechanisms causing cortical excitation and inhibition imbalance, which is involved in the degeneration of motor neurons in ALS. Moreover, we will highlight recent evidence that strongly indicates a cardinal role for the motor cortex as a main driver and source of the disease, thus arguing for a corticofugal trajectory of the pathology.
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14
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Pasniceanu IS, Atwal MS, Souza CDS, Ferraiuolo L, Livesey MR. Emerging Mechanisms Underpinning Neurophysiological Impairments in C9ORF72 Repeat Expansion-Mediated Amyotrophic Lateral Sclerosis/Frontotemporal Dementia. Front Cell Neurosci 2022; 15:784833. [PMID: 34975412 PMCID: PMC8715728 DOI: 10.3389/fncel.2021.784833] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/10/2021] [Indexed: 12/15/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are characterized by degeneration of upper and lower motor neurons and neurons of the prefrontal cortex. The emergence of the C9ORF72 hexanucleotide repeat expansion mutation as the leading genetic cause of ALS and FTD has led to a progressive understanding of the multiple cellular pathways leading to neuronal degeneration. Disturbances in neuronal function represent a major subset of these mechanisms and because such functional perturbations precede degeneration, it is likely that impaired neuronal function in ALS/FTD plays an active role in pathogenesis. This is supported by the fact that ALS/FTD patients consistently present with neurophysiological impairments prior to any apparent degeneration. In this review we summarize how the discovery of the C9ORF72 repeat expansion mutation has contributed to the current understanding of neuronal dysfunction in ALS/FTD. Here, we discuss the impact of the repeat expansion on neuronal function in relation to intrinsic excitability, synaptic, network and ion channel properties, highlighting evidence of conserved and divergent pathophysiological impacts between cortical and motor neurons and the influence of non-neuronal cells. We further highlight the emerging association between these dysfunctional properties with molecular mechanisms of the C9ORF72 mutation that appear to include roles for both, haploinsufficiency of the C9ORF72 protein and aberrantly generated dipeptide repeat protein species. Finally, we suggest that relating key pathological observations in C9ORF72 repeat expansion ALS/FTD patients to the mechanistic impact of the C9ORF72 repeat expansion on neuronal function will lead to an improved understanding of how neurophysiological dysfunction impacts upon pathogenesis.
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Affiliation(s)
- Iris-Stefania Pasniceanu
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Manpreet Singh Atwal
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Cleide Dos Santos Souza
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Laura Ferraiuolo
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Matthew R Livesey
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
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15
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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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16
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Dukic S, McMackin R, Costello E, Metzger M, Buxo T, Fasano A, Chipika R, Pinto-Grau M, Schuster C, Hammond M, Heverin M, Coffey A, Broderick M, Iyer PM, Mohr K, Gavin B, McLaughlin R, Pender N, Bede P, Muthuraman M, van den Berg L, Hardiman O, Nasseroleslami B. Resting-state EEG reveals four subphenotypes of amyotrophic lateral sclerosis. Brain 2021; 145:621-631. [PMID: 34791079 PMCID: PMC9014749 DOI: 10.1093/brain/awab322] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 06/25/2021] [Accepted: 07/26/2021] [Indexed: 11/14/2022] Open
Abstract
Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis. Recently, we have shown that resting-state EEG can reliably and quantitatively capture abnormal patterns of motor and cognitive network disruption in amyotrophic lateral sclerosis. These network disruptions have been identified across multiple frequency bands, and using measures of neural activity (spectral power) and connectivity (comodulation of activity by amplitude envelope correlation and synchrony by imaginary coherence) on source-localized brain oscillations from high-density EEG. Using data-driven methods (similarity network fusion and spectral clustering), we have now undertaken a clustering analysis to identify disease subphenotypes and to determine whether different patterns of disruption are predictive of disease outcome. We show that amyotrophic lateral sclerosis patients (n = 95) can be subgrouped into four phenotypes with distinct neurophysiological profiles. These clusters are characterized by varying degrees of disruption in the somatomotor (α-band synchrony), frontotemporal (β-band neural activity and γl-band synchrony) and frontoparietal (γl-band comodulation) networks, which reliably correlate with distinct clinical profiles and different disease trajectories. Using an in-depth stability analysis, we show that these clusters are statistically reproducible and robust, remain stable after reassessment using a follow-up EEG session, and continue to predict the clinical trajectory and disease outcome. Our data demonstrate that novel phenotyping using neuroelectric signal analysis can distinguish disease subtypes based exclusively on different patterns of network disturbances. These patterns may reflect underlying disease neurobiology. The identification of amyotrophic lateral sclerosis subtypes based on profiles of differential impairment in neuronal networks has clear potential in future stratification for clinical trials. Advanced network profiling in amyotrophic lateral sclerosis can also underpin new therapeutic strategies that are based on principles of neurobiology and designed to modulate network disruption.
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Affiliation(s)
- Stefan Dukic
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of 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, Ireland
| | - Emmet Costello
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Marjorie Metzger
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Teresa Buxo
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Antonio Fasano
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Rangariroyashe Chipika
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Marta Pinto-Grau
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Christina Schuster
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Michaela Hammond
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Mark Heverin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Amina Coffey
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Michael Broderick
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Parameswaran M Iyer
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Kieran Mohr
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Brighid Gavin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Russell McLaughlin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Niall Pender
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Muthuraman Muthuraman
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Johannes-Gutenberg-University Hospital, Mainz, Germany
| | - Leonard van den Berg
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, The Netherlands
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland.,Trinity College Institute of Neuroscience, Trinity College Dublin, University of 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, Ireland
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17
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Perez-Ortiz CX, Gordillo JL, Mendoza-Montoya O, Antelis JM, Caraza R, Martinez HR. Functional Connectivity and Frequency Power Alterations during P300 Task as a Result of Amyotrophic Lateral Sclerosis. SENSORS (BASEL, SWITZERLAND) 2021; 21:6801. [PMID: 34696014 PMCID: PMC8541445 DOI: 10.3390/s21206801] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 09/22/2021] [Accepted: 09/26/2021] [Indexed: 12/01/2022]
Abstract
Amyotrophic Lateral Sclerosis (ALS) is one of the most aggressive neurodegenerative diseases and is now recognized as a multisystem network disorder with impaired connectivity. Further research for the understanding of the nature of its cognitive affections is necessary to monitor and detect the disease, so this work provides insight into the neural alterations occurring in ALS patients during a cognitive task (P300 oddball paradigm) by measuring connectivity and the power and latency of the frequency-specific EEG activity of 12 ALS patients and 16 healthy subjects recorded during the use of a P300-based BCI to command a robotic arm. For ALS patients, in comparison to Controls, the results (p < 0.05) were: an increment in latency of the peak ERP in the Delta range (OZ) and Alpha range (PO7), and a decreased power in the Beta band among most electrodes; connectivity alterations among all bands, especially in the Alpha band between PO7 and the channels above the motor cortex. The evolution observed over months of an advanced-state patient backs up these findings. These results were used to compute connectivity- and power-based features to discriminate between ALS and Control groups using Support Vector Machine (SVM). Cross-validation achieved a 100% in specificity and 75% in sensitivity, with an overall 89% success.
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Affiliation(s)
- Claudia X. Perez-Ortiz
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, Mexico; (C.X.P.-O.); (J.L.G.); (J.M.A.)
| | - Jose L. Gordillo
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, Mexico; (C.X.P.-O.); (J.L.G.); (J.M.A.)
| | - Omar Mendoza-Montoya
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, Mexico; (C.X.P.-O.); (J.L.G.); (J.M.A.)
| | - Javier M. Antelis
- Escuela de Ingeniería y Ciencias, Tecnologico de Monterrey, Monterrey 64849, Mexico; (C.X.P.-O.); (J.L.G.); (J.M.A.)
| | - Ricardo Caraza
- Escuela de Medicina y Ciencias de la Salud, Tecnologico de Monterrey, Monterrey 64849, Mexico; (R.C.); (H.R.M.)
| | - Hector R. Martinez
- Escuela de Medicina y Ciencias de la Salud, Tecnologico de Monterrey, Monterrey 64849, Mexico; (R.C.); (H.R.M.)
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18
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McKenna MC, Corcia P, Couratier P, Siah WF, Pradat PF, Bede P. Frontotemporal Pathology in Motor Neuron Disease Phenotypes: Insights From Neuroimaging. Front Neurol 2021; 12:723450. [PMID: 34484106 PMCID: PMC8415268 DOI: 10.3389/fneur.2021.723450] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 07/22/2021] [Indexed: 01/18/2023] Open
Abstract
Frontotemporal involvement has been extensively investigated in amyotrophic lateral sclerosis (ALS) but remains relatively poorly characterized in other motor neuron disease (MND) phenotypes such as primary lateral sclerosis (PLS), progressive muscular atrophy (PMA), spinal muscular atrophy (SMA), spinal bulbar muscular atrophy (SBMA), post poliomyelitis syndrome (PPS), and hereditary spastic paraplegia (HSP). This review focuses on insights from structural, metabolic, and functional neuroimaging studies that have advanced our understanding of extra-motor disease burden in these phenotypes. The imaging literature is limited in the majority of these conditions and frontotemporal involvement has been primarily evaluated by neuropsychology and post mortem studies. Existing imaging studies reveal that frontotemporal degeneration can be readily detected in ALS and PLS, varying degree of frontotemporal pathology may be captured in PMA, SBMA, and HSP, SMA exhibits cerebral involvement without regional predilection, and there is limited evidence for cerebral changes in PPS. Our review confirms the heterogeneity extra-motor pathology across the spectrum of MNDs and highlights the role of neuroimaging in characterizing anatomical patterns of disease burden in vivo. Despite the contribution of neuroimaging to MND research, sample size limitations, inclusion bias, attrition rates in longitudinal studies, and methodological constraints need to be carefully considered. Frontotemporal involvement is a quintessential clinical facet of MND which has important implications for screening practices, individualized management strategies, participation in clinical trials, caregiver burden, and resource allocation. The academic relevance of imaging frontotemporal pathology in MND spans from the identification of genetic variants, through the ascertainment of presymptomatic changes to the design of future epidemiology studies.
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Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Philippe Corcia
- Department of Neurology-Neurophysiology, CRMR ALS, Tours, France.,UMR 1253 iBrain, University of Tours, Tours, France.,LITORALS, Federation of ALS Centres: Tours-Limoges, Limoges, France
| | - Philippe Couratier
- LITORALS, Federation of ALS Centres: Tours-Limoges, Limoges, France.,ALS Centre, Limoges University Hospital (CHU de Limoges), Limoges, France
| | - We Fong Siah
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | | | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland.,Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France
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19
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Schulz R, Bönstrup M, Guder S, Liu J, Frey B, Quandt F, Krawinkel LA, Cheng B, Thomalla G, Gerloff C. Corticospinal Tract Microstructure Correlates With Beta Oscillatory Activity in the Primary Motor Cortex After Stroke. Stroke 2021; 52:3839-3847. [PMID: 34412514 DOI: 10.1161/strokeaha.121.034344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Cortical beta oscillations are reported to serve as robust measures of the integrity of the human motor system. Their alterations after stroke, such as reduced movement-related beta desynchronization in the primary motor cortex, have been repeatedly related to the level of impairment. However, there is only little data whether such measures of brain function might directly relate to structural brain changes after stroke. METHODS This multimodal study investigated 18 well-recovered patients with stroke (mean age 65 years, 12 males) by means of task-related EEG and diffusion-weighted structural MRI 3 months after stroke. Beta power at rest and movement-related beta desynchronization was assessed in 3 key motor areas of the ipsilesional hemisphere that are the primary motor cortex (M1), the ventral premotor area and the supplementary motor area. Template trajectories of corticospinal tracts (CST) originating from M1, premotor cortex, and supplementary motor area were used to quantify the microstructural state of CST subcomponents. Linear mixed-effects analyses were used to relate tract-related mean fractional anisotropy to EEG measures. RESULTS In the present cohort, we detected statistically significant reductions in ipsilesional CST fractional anisotropy but no alterations in EEG measures when compared with healthy controls. However, in patients with stroke, there was a significant association between both beta power at rest (P=0.002) and movement-related beta desynchronization (P=0.003) in M1 and fractional anisotropy of the CST specifically originating from M1. Similar structure-function relationships were neither evident for ventral premotor area and supplementary motor area, particularly with respect to their CST subcomponents originating from premotor cortex and supplementary motor area, in patients with stroke nor in controls. CONCLUSIONS These data suggest there might be a link connecting microstructure of the CST originating from M1 pyramidal neurons and beta oscillatory activity, measures which have already been related to motor impairment in patients with stroke by previous reports.
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Affiliation(s)
- Robert Schulz
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
| | - Marlene Bönstrup
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.).,Department of Neurology, University Medical Centre, Leipzig, Germany (M.B.)
| | - Stephanie Guder
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
| | - Jingchun Liu
- Department of Radiology, Tianjin Medical University General Hospital, China (J.L.)
| | - Benedikt Frey
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
| | - Fanny Quandt
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
| | - Lutz A Krawinkel
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
| | - Bastian Cheng
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
| | - Götz Thomalla
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
| | - Christian Gerloff
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Germany (R.S., M.B., S.G., B.F., F.Q., L.A.K., B.C., G.T., C.G.)
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20
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van den Boom M, Miller KJ, Gregg NM, Ojeda Valencia G, Lee KH, Richner TJ, Ramsey NF, Worrell GA, Hermes D. Typical somatomotor physiology of the hand is preserved in a patient with an amputated arm: An ECoG case study. Neuroimage Clin 2021; 31:102728. [PMID: 34182408 PMCID: PMC8253998 DOI: 10.1016/j.nicl.2021.102728] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 04/17/2021] [Accepted: 05/10/2021] [Indexed: 12/03/2022]
Abstract
Electrophysiological signals in the human motor system may change in different ways after deafferentation, with some studies emphasizing reorganization while others propose retained physiology. Understanding whether motor electrophysiology is retained over longer periods of time can be invaluable for patients with paralysis (e.g. ALS or brainstem stroke) when signals from sensorimotor areas may be used for communication or control over neural prosthetic devices. In addition, a maintained electrophysiology can potentially benefit the treatment of phantom limb pains through prolonged use of these signals in a brain-machine interface (BCI). Here, we were presented with the unique opportunity to investigate the physiology of the sensorimotor cortex in a patient with an amputated arm using electrocorticographic (ECoG) measurements. While implanted with an ECoG grid for clinical evaluation of electrical stimulation for phantom limb pain, the patient performed attempted finger movements with the contralateral (lost) hand and executed finger movements with the ipsilateral (healthy) hand. The electrophysiology of the sensorimotor cortex contralateral to the amputated hand remained very similar to that of hand movement in healthy people, with a spatially focused increase of high-frequency band (65-175 Hz; HFB) power over the hand region and a distributed decrease in low-frequency band (15-28 Hz; LFB) power. The representation of the three different fingers (thumb, index and little) remained intact and HFB patterns could be decoded using support vector learning at single-trial classification accuracies of >90%, based on the first 1-3 s of the HFB response. These results indicate that hand representations are largely retained in the motor cortex. The intact physiological response of the amputated hand, the high distinguishability of the fingers and fast temporal peak are encouraging for neural prosthetic devices that target the sensorimotor cortex.
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Affiliation(s)
- Max van den Boom
- Department of Physiology and Biomedical Engineering, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA; Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
| | - Kai J Miller
- Department of Neurosurgery, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Nicholas M Gregg
- Department of Neurology, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Gabriela Ojeda Valencia
- Department of Physiology and Biomedical Engineering, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Kendall H Lee
- Department of Neurosurgery, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Thomas J Richner
- Department of Neurosurgery, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Nick F Ramsey
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Greg A Worrell
- Department of Neurology, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Dora Hermes
- Department of Physiology and Biomedical Engineering, Mayo Clinic Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
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21
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McMackin R, Dukic S, Costello E, Pinto-Grau M, McManus L, Broderick M, Chipika R, Iyer PM, Heverin M, Bede P, Muthuraman M, Pender N, Hardiman O, Nasseroleslami B. Cognitive network hyperactivation and motor cortex decline correlate with ALS prognosis. Neurobiol Aging 2021; 104:57-70. [PMID: 33964609 DOI: 10.1016/j.neurobiolaging.2021.03.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 02/26/2021] [Accepted: 03/02/2021] [Indexed: 02/07/2023]
Abstract
We aimed to quantitatively characterize progressive brain network disruption in Amyotrophic Lateral Sclerosis (ALS) during cognition using the mismatch negativity (MMN), an electrophysiological index of attention switching. We measured the MMN using 128-channel EEG longitudinally (2-5 timepoints) in 60 ALS patients and cross-sectionally in 62 healthy controls. Using dipole fitting and linearly constrained minimum variance beamforming we investigated cortical source activity changes over time. In ALS, the inferior frontal gyri (IFG) show significantly lower baseline activity compared to controls. The right IFG and both superior temporal gyri (STG) become progressively hyperactive longitudinally. By contrast, the left motor and dorsolateral prefrontal cortices are initially hyperactive, declining progressively. Baseline motor hyperactivity correlates with cognitive disinhibition, and lower baseline IFG activities correlate with motor decline rate, while left dorsolateral prefrontal activity predicted cognitive and behavioural impairment. Shorter survival correlates with reduced baseline IFG and STG activity and later STG hyperactivation. Source-resolved EEG facilitates quantitative characterization of symptom-associated and symptom-preceding motor and cognitive-behavioral cortical network decline in ALS.
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Affiliation(s)
- Roisin McMackin
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Stefan Dukic
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Emmet Costello
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Marta Pinto-Grau
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland; Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, The Netherlands
| | - Lara McManus
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Michael Broderick
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland; Trinity Centre for Bioengineering, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Rangariroyashe Chipika
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland; Computational Neuroimaging Group, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Parameswaran M Iyer
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland; Beaumont Hospital Dublin, Department of Neurology, Dublin 9, Ireland
| | - Mark Heverin
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Peter Bede
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland; Computational Neuroimaging Group, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
| | - Muthuraman Muthuraman
- Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Johannes-Gutenberg-University Hospital, Mainz, Germany
| | - Niall Pender
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland; Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, The Netherlands; Beaumont Hospital Dublin, Department of Neurology, Dublin 9, Ireland
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland; Beaumont Hospital Dublin, Department of Neurology, Dublin 9, Ireland.
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin 2, Ireland
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22
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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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23
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Li Hi Shing S, McKenna MC, Siah WF, Chipika RH, Hardiman O, Bede P. The imaging signature of C9orf72 hexanucleotide repeat expansions: implications for clinical trials and therapy development. Brain Imaging Behav 2021; 15:2693-2719. [PMID: 33398779 DOI: 10.1007/s11682-020-00429-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2020] [Indexed: 01/14/2023]
Abstract
While C9orf72-specific imaging signatures have been proposed by both ALS and FTD research groups and considerable presymptomatic alterations have also been confirmed in young mutation carriers, considerable inconsistencies exist in the literature. Accordingly, a systematic review of C9orf72-imaging studies has been performed to identify consensus findings, stereotyped shortcomings, and unique contributions to outline future directions. A formal literature review was conducted according to the STROBE guidelines. All identified papers were individually reviewed for sample size, choice of controls, study design, imaging modalities, statistical models, clinical profiling, and identified genotype-associated pathological patterns. A total of 74 imaging papers were systematically reviewed. ALS patients with GGGGCC repeat expansions exhibit relatively limited motor cortex involvement and widespread extra-motor pathology. C9orf72 positive FTD patients often show preferential posterior involvement. Reports of thalamic involvement are relatively consistent across the various phenotypes. Asymptomatic hexanucleotide repeat carriers often exhibit structural and functional changes decades prior to symptom onset. Common shortcomings included sample size limitations, lack of disease-controls, limited clinical profiling, lack of genetic testing in healthy controls, and absence of post mortem validation. There is a striking paucity of longitudinal studies and existing presymptomatic studies have not evaluated the predictive value of radiological changes with regard to age of onset and phenoconversion. With the advent of antisense oligonucleotide therapies, the meticulous characterisation of C9orf72-associated changes has gained practical relevance. Neuroimaging offers non-invasive biomarkers for future clinical trials, presymptomatic ascertainment, diagnostic and prognostic applications.
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Affiliation(s)
- Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Mary Clare McKenna
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
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24
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Borgheai SB, McLinden J, Mankodiya K, Shahriari Y. Frontal Functional Network Disruption Associated with Amyotrophic Lateral Sclerosis: An fNIRS-Based Minimum Spanning Tree Analysis. Front Neurosci 2020; 14:613990. [PMID: 33424544 PMCID: PMC7785833 DOI: 10.3389/fnins.2020.613990] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 12/03/2020] [Indexed: 11/13/2022] Open
Abstract
Recent evidence increasingly associates network disruption in brain organization with multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), a rare terminal disease. However, the comparability of brain network characteristics across different studies remains a challenge for conventional graph theoretical methods. One suggested method to address this issue is minimum spanning tree (MST) analysis, which provides a less biased comparison. Here, we assessed the novel application of MST network analysis to hemodynamic responses recorded by functional near-infrared spectroscopy (fNIRS) neuroimaging modality, during an activity-based paradigm to investigate hypothetical disruptions in frontal functional brain network topology as a marker of the executive dysfunction, one of the most prevalent cognitive deficit reported across ALS studies. We analyzed data recorded from nine participants with ALS and ten age-matched healthy controls by first estimating functional connectivity, using phase-locking value (PLV) analysis, and then constructing the corresponding individual and group MSTs. Our results showed significant between-group differences in several MST topological properties, including leaf fraction, maximum degree, diameter, eccentricity, and degree divergence. We further observed a global shift toward more centralized frontal network organizations in the ALS group, interpreted as a more random or dysregulated network in this cohort. Moreover, the similarity analysis demonstrated marginally significantly increased overlap in the individual MSTs from the control group, implying a reference network with lower topological variation in the healthy cohort. Our nodal analysis characterized the main local hubs in healthy controls as distributed more evenly over the frontal cortex, with slightly higher occurrence in the left prefrontal cortex (PFC), while in the ALS group, the most frequent hubs were asymmetrical, observed primarily in the right prefrontal cortex. Furthermore, it was demonstrated that the global PLV (gPLV) synchronization metric is associated with disease progression, and a few topological properties, including leaf fraction and tree hierarchy, are linked to disease duration. These results suggest that dysregulation, centralization, and asymmetry of the hemodynamic-based frontal functional network during activity are potential neuro-topological markers of ALS pathogenesis. Our findings can possibly support new bedside assessments of the functional status of ALS' brain network and could hypothetically extend to applications in other neurodegenerative diseases.
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Affiliation(s)
- Seyyed Bahram Borgheai
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States
| | - John McLinden
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States
| | - Kunal Mankodiya
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States.,Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, RI, United States
| | - Yalda Shahriari
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States.,Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, RI, United States
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25
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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: 50] [Impact Index Per Article: 12.5] [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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26
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Chipika RH, Siah WF, McKenna MC, Li Hi Shing S, Hardiman O, Bede P. The presymptomatic phase of amyotrophic lateral sclerosis: are we merely scratching the surface? J Neurol 2020; 268:4607-4629. [PMID: 33130950 DOI: 10.1007/s00415-020-10289-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 10/18/2020] [Accepted: 10/20/2020] [Indexed: 02/06/2023]
Abstract
Presymptomatic studies in ALS have consistently captured considerable disease burden long before symptom manifestation and contributed important academic insights. With the emergence of genotype-specific therapies, however, there is a pressing need to address practical objectives such as the estimation of age of symptom onset, phenotypic prediction, informing the optimal timing of pharmacological intervention, and identifying a core panel of biomarkers which may detect response to therapy. Existing presymptomatic studies in ALS have adopted striking different study designs, relied on a variety of control groups, used divergent imaging and electrophysiology methods, and focused on different genotypes and demographic groups. We have performed a systematic review of existing presymptomatic studies in ALS to identify common themes, stereotyped shortcomings, and key learning points for future studies. Existing presymptomatic studies in ALS often suffer from sample size limitations, lack of disease controls and rarely follow their cohort until symptom manifestation. As the characterisation of presymptomatic processes in ALS serves a multitude of academic and clinical purposes, the careful review of existing studies offers important lessons for future initiatives.
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Affiliation(s)
- Rangariroyashe H Chipika
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Mary Clare McKenna
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), Biomedical Sciences Institute, Trinity College Dublin, Pearse Street, Dublin, Ireland.
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27
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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: 45] [Impact Index Per Article: 11.3] [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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28
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Walker S, Monto S, Piirainen JM, Avela J, Tarkka IM, Parviainen TM, Piitulainen H. Older Age Increases the Amplitude of Muscle Stretch-Induced Cortical Beta-Band Suppression But Does not Affect Rebound Strength. Front Aging Neurosci 2020; 12:117. [PMID: 32508626 PMCID: PMC7248310 DOI: 10.3389/fnagi.2020.00117] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 04/07/2020] [Indexed: 12/11/2022] Open
Abstract
Healthy aging is associated with deterioration of the sensorimotor system, which impairs balance and somatosensation. However, the exact age-related changes in the cortical processing of sensorimotor integration are unclear. This study investigated primary sensorimotor cortex (SM1) oscillations in the 15-30 Hz beta band at rest and following (involuntary) rapid stretches to the triceps surae muscles (i.e., proprioceptive stimulation) of young and older adults. A custom-built, magnetoencephalography (MEG)-compatible device was used to deliver rapid (190°·s-1) ankle rotations as subjects sat passively in a magnetically-shielded room while MEG recorded their cortical signals. Eleven young (age 25 ± 3 years) and 12 older (age 70 ± 3 years) adults matched for physical activity level demonstrated clear 15-30 Hz beta band suppression and rebound in response to the stretches. A sub-sample (10 young and nine older) were tested for dynamic balance control on a sliding platform. Older adults had greater cortical beta power pre-stretch (e.g., right leg: 4.0 ± 1.6 fT vs. 5.6 ± 1.7 fT, P = 0.044) and, subsequently, greater normalized movement-related cortical beta suppression post-proprioceptive stimulation (e.g., right leg: -5.8 ± 1.3 vs. -7.6 ± 1.7, P = 0.01) than young adults. Furthermore, poorer balance was associated with stronger cortical beta suppression following proprioceptive stimulation (r = -0.478, P = 0.038, n = 19). These results provide further support that cortical processing of proprioception is hindered in older adults, potentially (adversely) influencing sensorimotor integration. This was demonstrated by the impairment of prompt motor action control, i.e., regaining perturbed balance. Finally, SM1 cortex beta suppression to a proprioceptive stimulus seems to indicate poorer sensorimotor functioning in older adults.
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Affiliation(s)
- Simon Walker
- NeuroMuscular Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Simo Monto
- Department of Psychology, Centre for Interdisciplinary Brain Research, University of Jyväskylä, Jyväskylä, Finland
| | - Jarmo M Piirainen
- NeuroMuscular Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Janne Avela
- NeuroMuscular Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Ina M Tarkka
- Faculty of Sport and Health Sciences and Centre for Interdisciplinary Brain Research, University of Jyväskylä, Jyväskylä, Finland
| | - Tiina M Parviainen
- Department of Psychology, Centre for Interdisciplinary Brain Research, University of Jyväskylä, Jyväskylä, Finland
| | - Harri Piitulainen
- NeuroMuscular Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.,Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
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29
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Brunet A, Stuart-Lopez G, Burg T, Scekic-Zahirovic J, Rouaux C. Cortical Circuit Dysfunction as a Potential Driver of Amyotrophic Lateral Sclerosis. Front Neurosci 2020; 14:363. [PMID: 32410944 PMCID: PMC7201269 DOI: 10.3389/fnins.2020.00363] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 03/25/2020] [Indexed: 12/11/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease that affects selected cortical and spinal neuronal populations, leading to progressive paralysis and death. A growing body of evidences suggests that the disease may originate in the cerebral cortex and propagate in a corticofugal manner. In particular, transcranial magnetic stimulation studies revealed that ALS patients present with early cortical hyperexcitability arising from a combination of increased excitability and decreased inhibition. Here, we discuss the possibility that initial cortical circuit dysfunction might act as the main driver of ALS onset and progression, and review recent functional, imaging and transcriptomic studies conducted on ALS patients, along with electrophysiological, pathological and transcriptomic studies on animal and cellular models of the disease, in order to evaluate the potential cellular and molecular origins of cortical hyperexcitability in ALS.
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Affiliation(s)
| | | | | | | | - Caroline Rouaux
- INSERM UMR_S 1118, Mécanismes Centraux et Périphériques de la Neurodégénérescence, Faculté de Médecine, Université de Strasbourg, Strasbourg, France
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30
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Bede P, Chipika RH. Commissural fiber degeneration in motor neuron diseases. Amyotroph Lateral Scler Frontotemporal Degener 2020; 21:321-323. [PMID: 32290711 DOI: 10.1080/21678421.2020.1752253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Ireland
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31
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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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32
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Hosni SM, Deligani RJ, Zisk A, McLinden J, Borgheai SB, Shahriari Y. An exploration of neural dynamics of motor imagery for people with amyotrophic lateral sclerosis. J Neural Eng 2019; 17:016005. [PMID: 31597125 DOI: 10.1088/1741-2552/ab4c75] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Studies of the neuropathological effects of amyotrophic lateral sclerosis (ALS) on the underlying motor system have investigated abnormalities in the magnitude and timing of the event-related desynchronization (ERD) and synchronization (ERS) during motor execution (ME). However, the spatio-spectral-temporal dynamics of these sensorimotor oscillations during motor imagery (MI) have not been fully explored for these patients. This study explores the neural dynamics of sensorimotor oscillations for ALS patients during MI by quantifying ERD/ERS features in frequency, time, and space. APPROACH Electroencephalogram (EEG) data were recorded from six patients with ALS and 11 age-matched healthy controls (HC) while performing a MI task. ERD/ERS features were extracted using wavelet-based time-frequency analysis and compared between the two groups to quantify the abnormal neural dynamics of ALS in terms of both time and frequency. Topographic correlation analysis was conducted to compare the localization of MI activity between groups and to identify subject-specific frequencies in the µ and β frequency bands. MAIN RESULTS Overall, reduced and delayed ERD was observed for ALS patients, particularly during right-hand MI. ERD features were also correlated with ALS clinical scores, specifically disease duration, bulbar, and cognitive functions. SIGNIFICANCE The analyses in this study quantify abnormalities in the magnitude and timing of sensorimotor oscillations for ALS patients during MI tasks. Our findings reveal notable differences between MI and existing results on ME in ALS. The observed alterations are speculated to reflect disruptions in the underlying cortical networks involved in MI functions. Quantifying the neural dynamics of MI plays an important role in the study of EEG-based cortical markers for ALS.
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Affiliation(s)
- Sarah M Hosni
- Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States of America
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33
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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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34
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Gaetz W, Rhodes E, Bloy L, Blaskey L, Jackel CR, Brodkin ES, Waldman A, Embick D, Hall S, Roberts TPL. Evaluating motor cortical oscillations and age-related change in autism spectrum disorder. Neuroimage 2019; 207:116349. [PMID: 31726253 DOI: 10.1016/j.neuroimage.2019.116349] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 11/07/2019] [Accepted: 11/09/2019] [Indexed: 12/11/2022] Open
Abstract
Autism spectrum disorder (ASD) is primarily characterized by impairments in social communication and the appearance of repetitive behaviors with restricted interests. Increasingly, evidence also points to a general deficit of motor tone and coordination in children and adults with ASD; yet the neural basis of motor functional impairment in ASD remains poorly characterized. In this study, we used magnetoencephalography (MEG) to (1) assess potential group differences between typically developing (TD) and ASD participants in motor cortical oscillatory activity observed on a simple button-press task and (2) to do so over a sufficiently broad age-range so as to capture age-dependent changes associated with development. Event-related desynchronization was evaluated in Mu (8-13 Hz) and Beta (15-30 Hz) frequency bands (Mu-ERD, Beta-ERD). In addition, post-movement Beta rebound (PMBR), and movement-related gamma (60-90 Hz) synchrony (MRGS) were also assessed in a cohort of 123 participants (63 typically developing (TD) and 59 with ASD) ranging in age from 8 to 24.9 years. We observed significant age-dependent linear trends in Beta-ERD and MRGS power with age for both TD and ASD groups; which did not differ significantly between groups. However, for PMBR, in addition to a significant effect of age, we also observed a significant reduction in PMBR power in the ASD group (p < 0.05). Post-hoc tests showed that this omnibus group difference was driven by the older cohort of children >13.2 years (p < 0.001) and this group difference was not observed when assessing PMBR activity for the younger PMBR groups (ages 8-13.2 years; p = 0.48). Moreover, for the older ASD cohort, hierarchical regression showed a significant relationship between PMBR activity and clinical scores of ASD severity (Social Responsiveness Scale (SRS T scores)), after regressing out the effect of age (p < 0.05). Our results show substantial age-dependent changes in motor cortical oscillations (Beta-ERD and MRGS) occur for both TD and ASD children and diverge only for PMBR, and most significantly for older adolescents and adults with ASD. While the functional significance of PMBR and reduced PMBR signaling remains to be fully elucidated, these results underscore the importance of considering age as a factor when assessing motor cortical oscillations and group differences in children with ASD.
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Affiliation(s)
- William Gaetz
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Edward Rhodes
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Luke Bloy
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lisa Blaskey
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Carissa R Jackel
- Division of Developmental and Behavioral Pediatrics, Children's Hospital of Philadelphia, USA
| | - Edward S Brodkin
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Amy Waldman
- Division of Neurology, Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David Embick
- Department of Linguistics, University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen Hall
- Brain Research and Imaging Centre, University of Plymouth, Devon, UK
| | - Timothy P L Roberts
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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35
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Turner MR. The early biomarker challenge in neurodegenerative disorders. J Neurol Neurosurg Psychiatry 2019; 90:1190-1191. [PMID: 31243045 DOI: 10.1136/jnnp-2019-321145] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Accepted: 06/18/2019] [Indexed: 12/11/2022]
Affiliation(s)
- Martin R Turner
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
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36
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Post-stimulus beta responses are modulated by task duration. Neuroimage 2019; 206:116288. [PMID: 31654762 PMCID: PMC6985901 DOI: 10.1016/j.neuroimage.2019.116288] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 09/12/2019] [Accepted: 10/16/2019] [Indexed: 02/08/2023] Open
Abstract
Modulation of beta-band neural oscillations during and following movement is a robust marker of brain function. In particular, the post-movement beta rebound (PMBR), which occurs on movement cessation, has been related to inhibition and connectivity in the healthy brain, and is perturbed in disease. However, to realise the potential of the PMBR as a biomarker, its modulation by task parameters must be characterised and its functional role determined. Here, we used MEG to image brain electrophysiology during and after a grip-force task, with the aim to characterise how task duration, in the form of an isometric contraction, modulates beta responses. Fourteen participants exerted a 30% maximum voluntary grip-force for 2, 5 and 10 s. Our results showed that the amplitude of the PMBR is modulated by task duration, with increasing duration significantly reducing PMBR amplitude and increasing its time-to-peak. No variation in the amplitude of the movement related beta decrease (MRBD) with task duration was observed. To gain insight into what may underlie these trial-averaged results, we used a Hidden Markov Model to identify the individual trial dynamics of a brain network encompassing bilateral sensorimotor areas. The rapidly evolving dynamics of this network demonstrated similar variation with task parameters to the ‘classical’ rebound, and we show that the modulation of the PMBR can be well-described in terms of increased frequency of beta events on a millisecond timescale rather than modulation of beta amplitude during this time period. Our results add to the emerging picture that, in the case of a carefully controlled paradigm, beta modulation can be systematically controlled by task parameters and such control can reveal new information as to the processes that generate the average beta timecourse. These findings will support design of clinically relevant paradigms and analysis pipelines in future use of the PMBR as a marker of neuropathology. The post-movement beta rebound is modulated by task duration. Increasing task duration reduces amplitude of the post-movement beta rebound. The modulation is explained by increased frequency of short-timescale beta events.
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37
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Freudenburg ZV, Branco MP, Leinders S, van der Vijgh BH, Pels EGM, Denison T, van den Berg LH, Miller KJ, Aarnoutse EJ, Ramsey NF, Vansteensel MJ. Sensorimotor ECoG Signal Features for BCI Control: A Comparison Between People With Locked-In Syndrome and Able-Bodied Controls. Front Neurosci 2019; 13:1058. [PMID: 31680806 PMCID: PMC6805728 DOI: 10.3389/fnins.2019.01058] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 09/20/2019] [Indexed: 01/10/2023] Open
Abstract
The sensorimotor cortex is a frequently targeted brain area for the development of Brain-Computer Interfaces (BCIs) for communication in people with severe paralysis and communication problems (locked-in syndrome; LIS). It is widely acknowledged that this area displays an increase in high-frequency band (HFB) power and a decrease in the power of the low frequency band (LFB) during movement of, for example, the hand. Upon termination of hand movement, activity in the LFB band typically shows a short increase (rebound). The ability to modulate the neural signal in the sensorimotor cortex by imagining or attempting to move is crucial for the implementation of sensorimotor BCI in people who are unable to execute movements. This may not always be self-evident, since the most common causes of LIS, amyotrophic lateral sclerosis (ALS) and brain stem stroke, are associated with significant damage to the brain, potentially affecting the generation of baseline neural activity in the sensorimotor cortex and the modulation thereof by imagined or attempted hand movement. In the Utrecht NeuroProsthesis (UNP) study, a participant with LIS caused by ALS and a participant with LIS due to brain stem stroke were implanted with a fully implantable BCI, including subdural electrocorticography (ECoG) electrodes over the sensorimotor area, with the purpose of achieving ECoG-BCI-based communication. We noted differences between these participants in the spectral power changes generated by attempted movement of the hand. To better understand the nature and origin of these differences, we compared the baseline spectral features and task-induced modulation of the neural signal of the LIS participants, with those of a group of able-bodied people with epilepsy who received a subchronic implant with ECoG electrodes for diagnostic purposes. Our data show that baseline LFB oscillatory components and changes generated in the LFB power of the sensorimotor cortex by (attempted) hand movement differ between participants, despite consistent HFB responses in this area. We conclude that the etiology of LIS may have significant effects on the LFB spectral components in the sensorimotor cortex, which is relevant for the development of communication-BCIs for this population.
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Affiliation(s)
- Zachary V Freudenburg
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Mariana P Branco
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Sacha Leinders
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Benny H van der Vijgh
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Elmar G M Pels
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Timothy Denison
- Department of Engineering Science, University of Oxford, Oxford, United Kingdom
| | - Leonard H van den Berg
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Kai J Miller
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Erik J Aarnoutse
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Nick F Ramsey
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
| | - Mariska J Vansteensel
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands
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38
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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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39
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Cognitive and White-Matter Compartment Models Reveal Selective Relations between Corticospinal Tract Microstructure and Simple Reaction Time. J Neurosci 2019; 39:5910-5921. [PMID: 31123103 PMCID: PMC6650993 DOI: 10.1523/jneurosci.2954-18.2019] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 04/25/2019] [Accepted: 04/26/2019] [Indexed: 12/11/2022] Open
Abstract
The speed of motor reaction to an external stimulus varies substantially between individuals and is slowed in aging. However, the neuroanatomical origins of interindividual variability in reaction time (RT) remain unclear. Here, we combined a cognitive model of RT and a biophysical compartment model of diffusion-weighted MRI (DWI) to characterize the relationship between RT and microstructure of the corticospinal tract (CST) and the optic radiation (OR), the primary motor output and visual input pathways associated with visual-motor responses. We fitted an accumulator model of RT to 46 female human participants' behavioral performance in a simple reaction time task. The non-decision time parameter (T er) derived from the model was used to account for the latencies of stimulus encoding and action initiation. From multi-shell DWI data, we quantified tissue microstructure of the CST and OR with the neurite orientation dispersion and density imaging (NODDI) model as well as the conventional diffusion tensor imaging model. Using novel skeletonization and segmentation approaches, we showed that DWI-based microstructure metrics varied substantially along CST and OR. The T er of individual participants was negatively correlated with the NODDI measure of the neurite density in the bilateral superior CST. Further, we found no significant correlation between the microstructural measures and mean RT. Thus, our findings suggest a link between interindividual differences in sensorimotor speed and selective microstructural properties in white-matter tracts.SIGNIFICANCE STATEMENT How does our brain structure contribute to our speed to react? Here, we provided anatomically specific evidence that interindividual differences in response speed is associated with white-matter microstructure. Using a cognitive model of reaction time (RT), we estimated the non-decision time, as an index of the latencies of stimulus encoding and action initiation, during a simple reaction time task. Using an advanced microstructural model for diffusion MRI, we estimated the tissue properties and their variations along the corticospinal tract and optic radiation. We found significant location-specific correlations between the microstructural measures and the model-derived parameter of non-decision time but not mean RT. These results highlight the neuroanatomical signature of interindividual variability in response speed along the sensorimotor pathways.
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40
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Henderson RD, Garton FC, Kiernan MC, Turner MR, Eisen A. Human cerebral evolution and the clinical syndrome of amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2019; 90:570-575. [PMID: 29666205 PMCID: PMC6581076 DOI: 10.1136/jnnp-2017-317245] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 03/23/2018] [Accepted: 03/29/2018] [Indexed: 12/11/2022]
Affiliation(s)
- Robert D Henderson
- Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia
| | - Fleur C Garton
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Matthew C Kiernan
- Brain & Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Andrew Eisen
- Division of Neurology Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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41
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The changing landscape of motor neuron disease imaging: the transition from descriptive studies to precision clinical tools. Curr Opin Neurol 2019; 31:431-438. [PMID: 29750730 DOI: 10.1097/wco.0000000000000569] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE OF REVIEW Neuroimaging in motor neuron disease (MND) has traditionally been seen as an academic tool with limited direct relevance to individualized patient care. This has changed radically in recent years as computational imaging has emerged as a viable clinical tool with true biomarker potential. This transition is not only fuelled by technological advances but also by important conceptual developments. RECENT FINDINGS The natural history of MND is now evaluated by presymptomatic, postmortem and multi-timepoint longitudinal imaging studies. The anatomical spectrum of MND imaging has also been expanded from an overwhelmingly cerebral focus to innovative spinal and muscle applications. In contrast to the group-comparisons of previous studies, machine-learning and deep-learning approaches are increasingly utilized to model real-life diagnostic dilemmas and aid prognostic classification. The focus from evaluating focal structural changes has shifted to the appraisal of network integrity by connectivity-based approaches. The armamentarium of MND imaging has also been complemented by novel PET-ligands, spinal toolboxes and the availability of magnetoencephalography and high-field magnetic resonance (MR) imaging platforms. SUMMARY In addition to the technological and conceptual advances, collaborative multicentre research efforts have also gained considerable momentum. This opinion-piece reviews emerging trends in MND imaging and their implications to clinical care and drug development.
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42
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Finegan E, Chipika RH, Shing SLH, Hardiman O, Bede P. Primary lateral sclerosis: a distinct entity or part of the ALS spectrum? Amyotroph Lateral Scler Frontotemporal Degener 2019; 20:133-145. [PMID: 30654671 DOI: 10.1080/21678421.2018.1550518] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Primary lateral sclerosis (PLS) has been traditionally viewed as a distinct upper motor neuron condition (UMN) but is increasingly regarded as a sub-phenotype within the amyotrophic lateral sclerosis (ALS) spectrum. Despite established diagnostic criteria, formal diagnosis can be challenging and the protracted diagnostic journey and uncertainty about longer-term prognosis cause considerable distress to patients and caregivers. PLS patients are invariably excluded from ALS clinical trials, while PLS pharmacological trials are lacking. There remains an unmet need for diagnostic biomarkers for upper motor neuron predominant conditions and prognostic indicators regarding prognosis, survival, and risk of conversion to ALS. Validated biomarkers will not only have implications for individualized patient care but also serve as outcome measures in pharmaceutical trials. Given the paucity of post-mortem studies in PLS, novel pathological insights are generally inferred from state-of-the-art imaging studies. Computational neuroimaging has already contributed significantly to the characterization of PLS-associated pathology in vivo and has underscored the role of neuro-inflammation, the presence of extra-motor changes, and confirmed pathological patterns similar to ALS. This systematic review assesses the current state of PLS research across clinical, neuroimaging and neuropathological domains from a combined clinical and academic perspective. We discuss patterns of pathological overlap with other ALS phenotypes, examine if the biological processes of PLS warrant therapeutic strategies distinct from ALS, and evaluate the evidence that classes PLS as a distinct clinico-pathological entity.
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Affiliation(s)
- Eoin Finegan
- a Computational Neuroimaging Group, Academic Unit of Neurology , Biomedical Sciences Institute, Trinity College , Dublin , Ireland
| | - Rangariroyashe H Chipika
- a Computational Neuroimaging Group, Academic Unit of Neurology , Biomedical Sciences Institute, Trinity College , Dublin , Ireland
| | - Stacey Li Hi Shing
- a Computational Neuroimaging Group, Academic Unit of Neurology , Biomedical Sciences Institute, Trinity College , Dublin , Ireland
| | - Orla Hardiman
- a Computational Neuroimaging Group, Academic Unit of Neurology , Biomedical Sciences Institute, Trinity College , Dublin , Ireland
| | - Peter Bede
- a Computational Neuroimaging Group, Academic Unit of Neurology , Biomedical Sciences Institute, Trinity College , Dublin , Ireland
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43
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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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44
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Frequency Shifts and Depth Dependence of Premotor Beta Band Activity during Perceptual Decision-Making. J Neurosci 2019; 39:1420-1435. [PMID: 30606756 DOI: 10.1523/jneurosci.1066-18.2018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2018] [Revised: 11/29/2018] [Accepted: 12/17/2018] [Indexed: 12/11/2022] Open
Abstract
Neural activity in the premotor and motor cortices shows prominent structure in the beta frequency range (13-30 Hz). Currently, the behavioral relevance of this beta band activity (BBA) is debated. The underlying source of motor BBA and how it changes as a function of cortical depth are also not completely understood. Here, we addressed these unresolved questions by investigating BBA recorded using laminar electrodes in the dorsal premotor cortex of 2 male rhesus macaques performing a visual reaction time (RT) reach discrimination task. We observed robust BBA before and after the onset of the visual stimulus but not during the arm movement. While poststimulus BBA was positively correlated with RT throughout the beta frequency range, prestimulus correlation varied by frequency. Low beta frequencies (∼12-20 Hz) were positively correlated with RT, and high beta frequencies (∼22-30 Hz) were negatively correlated with RT. Analysis and simulations suggested that these frequency-dependent correlations could emerge due to a shift in the component frequencies of the prestimulus BBA as a function of RT, such that faster RTs are accompanied by greater power in high beta frequencies. We also observed a laminar dependence of BBA, with deeper electrodes demonstrating stronger power in low beta frequencies both prestimulus and poststimulus. The heterogeneous nature of BBA and the changing relationship between BBA and RT in different task epochs may be a sign of the differential network dynamics involved in cue expectation, decision-making, motor preparation, and movement execution.SIGNIFICANCE STATEMENT Beta band activity (BBA) has been implicated in motor tasks, in disease states, and as a potential signal for brain-machine interfaces. However, the behavioral relevance of BBA and its laminar organization in premotor cortex have not been completely elucidated. Here we addressed these unresolved issues using simultaneous recordings from multiple cortical layers of the premotor cortex of monkeys performing a decision-making task. Our key finding is that BBA is not a monolithic signal. Instead, BBA consists of at least two frequency bands. The relationship between BBA and eventual behavior, such as reaction time, also dynamically changes depending on task epoch. We also provide further evidence that BBA is laminarly organized, with greater power in deeper electrodes for low beta frequencies.
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45
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Neurodegeneration of brain networks in the amyotrophic lateral sclerosis-frontotemporal lobar degeneration (ALS-FTLD) continuum: evidence from MRI and MEG studies. CNS Spectr 2018; 23:378-387. [PMID: 29076800 DOI: 10.1017/s109285291700075x] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Brain imaging techniques, especially those based on magnetic resonance imaging (MRI) and magnetoencephalography (MEG), have been increasingly applied to study multiple large-scale distributed brain networks in healthy people and neurological patients. With regard to neurodegenerative disorders, amyotrophic lateral sclerosis (ALS), clinically characterized by the predominant loss of motor neurons and progressive weakness of voluntary muscles, and frontotemporal lobar degeneration (FTLD), the second most common early-onset dementia, have been proven to share several clinical, neuropathological, genetic, and neuroimaging features. Specifically, overlapping or mildly diverging brain structural and functional connectivity patterns, mostly evaluated by advanced MRI techniques-such as diffusion tensor and resting-state functional MRI (DT-MRI, RS-fMRI)-have been described comparing several ALS and FTLD populations. Moreover, though only pioneering, promising clues on connectivity patterns in the ALS-FTLD continuum may derive from MEG investigations. We will herein overview the current state of knowledge concerning the most advanced neuroimaging findings associated with clinical and genetic patterns of neurodegeneration across the ALS-FTLD continuum, underlying the possibility that network-based approaches may be useful to develop novel biomarkers of disease for adequately designing and monitoring more appropriate treatment strategies.
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46
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Collaboration of Cerebello-Rubral and Cerebello-Striatal Loops in a Motor Preparation Task. THE CEREBELLUM 2018; 18:203-211. [DOI: 10.1007/s12311-018-0980-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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47
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Talbot K, Feneberg E, Scaber J, Thompson AG, Turner MR. Amyotrophic lateral sclerosis: the complex path to precision medicine. J Neurol 2018; 265:2454-2462. [PMID: 30054789 PMCID: PMC6182683 DOI: 10.1007/s00415-018-8983-8] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Accepted: 07/19/2018] [Indexed: 12/11/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease of the corticomotorneuronal network responsible for voluntary movement. There are well-established clinical, genetic and pathological overlaps between ALS and frontotemporal dementia (FTD), which together constitute the 'TDP-43 proteinopathies'. An ever-expanding list of genes in which mutation leads to typical ALS have implicated abnormalities in RNA processing, protein homoeostasis and axonal transport. How these apparently distinct pathways converge to cause the characteristic clinical syndrome of ALS remains unclear. Although there are major gaps in our understanding of the essential nature of ALS pathophysiology, the identification of genetic causes in up to 15% of ALS patients, coupled with advances in biotechnology and biomarker research provide a foundation for approaches to treatment based on 'precision medicine', and even prevention of the disease in pre-symptomatic mutation carriers in the future. Currently, multidisciplinary care remains the bedrock of management and this is increasingly being put onto an evidence-based footing.
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Affiliation(s)
- Kevin Talbot
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK.
| | - Emily Feneberg
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Jakub Scaber
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Alexander G Thompson
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DU, UK
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Sorrentino P, Rucco R, Jacini F, Trojsi F, Lardone A, Baselice F, Femiano C, Santangelo G, Granata C, Vettoliere A, Monsurrò MR, Tedeschi G, Sorrentino G. Brain functional networks become more connected as amyotrophic lateral sclerosis progresses: a source level magnetoencephalographic study. Neuroimage Clin 2018; 20:564-571. [PMID: 30186760 PMCID: PMC6120607 DOI: 10.1016/j.nicl.2018.08.001] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 07/12/2018] [Accepted: 08/02/2018] [Indexed: 12/18/2022]
Abstract
This study hypothesizes that the brain shows hyper connectedness as amyotrophic lateral sclerosis (ALS) progresses. 54 patients (classified as "early stage" or "advanced stage") and 25 controls underwent magnetoencephalography and MRI recordings. The activity of the brain areas was reconstructed, and the synchronization between them was estimated in the classical frequency bands using the phase lag index. Brain topological metrics such as the leaf fraction (number of nodes with degree of 1), the degree divergence (a measure of the scale-freeness) and the degree correlation (a measure of disassortativity) were estimated. Betweenness centrality was used to estimate the centrality of the brain areas. In all frequency bands, it was evident that, the more advanced the disease, the more connected, scale-free and disassortative the brain networks. No differences were evident in specific brain areas. Such modified brain topology is sub-optimal as compared to controls. Within this framework, our study shows that brain networks become more connected according to disease staging in ALS patients.
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Affiliation(s)
- Pierpaolo Sorrentino
- Department of Engineering - University of Naples "Parthenope", Centro Direzionale Isola C4, 80133 Naples, Italy; Institute for High Performance Computing and Networking, CNR, via Pietro Castellino 111, 80131 Naples, Italy.
| | - Rosaria Rucco
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Francesca Jacini
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy; Hermitage Capodimonte Hospital, via Cupa delle Tozzole 2, 80131 Naples, Italy
| | - Francesca Trojsi
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences - MRI Research Center SUN-FISM, University of Campania "Luigi Vanvitelli", P.zza Miraglia 2, 80138 Naples, Italy
| | - Anna Lardone
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy; Hermitage Capodimonte Hospital, via Cupa delle Tozzole 2, 80131 Naples, Italy
| | - Fabio Baselice
- Department of Engineering - University of Naples "Parthenope", Centro Direzionale Isola C4, 80133 Naples, Italy
| | - Cinzia Femiano
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences - MRI Research Center SUN-FISM, University of Campania "Luigi Vanvitelli", P.zza Miraglia 2, 80138 Naples, Italy
| | - Gabriella Santangelo
- Department of Psychology, University of Campania "Luigi Vanvitelli", viale Ellittico 31, 80100 Caserta, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy
| | - Antonio Vettoliere
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy
| | - Maria Rosaria Monsurrò
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences - MRI Research Center SUN-FISM, University of Campania "Luigi Vanvitelli", P.zza Miraglia 2, 80138 Naples, Italy
| | - Gioacchino Tedeschi
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences - MRI Research Center SUN-FISM, University of Campania "Luigi Vanvitelli", P.zza Miraglia 2, 80138 Naples, Italy
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy; Hermitage Capodimonte Hospital, via Cupa delle Tozzole 2, 80131 Naples, Italy
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49
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Proudfoot M, van Ede F, Quinn A, Colclough GL, Wuu J, Talbot K, Benatar M, Woolrich MW, Nobre AC, Turner MR. Impaired corticomuscular and interhemispheric cortical beta oscillation coupling in amyotrophic lateral sclerosis. Clin Neurophysiol 2018; 129:1479-1489. [DOI: 10.1016/j.clinph.2018.03.019] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2017] [Revised: 03/02/2018] [Accepted: 03/13/2018] [Indexed: 01/01/2023]
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50
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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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