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Holzapfel K, Bayas A, Naumann M, Ghosh T, Steuerwald V, Allweyer M, Kirschke JS, Behrens L. Mirror movements in multiple sclerosis -a clinical, electrophysiological, and imaging study. BMC Neurol 2024; 24:326. [PMID: 39242510 PMCID: PMC11378473 DOI: 10.1186/s12883-024-03828-4] [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: 02/10/2024] [Accepted: 08/27/2024] [Indexed: 09/09/2024] Open
Abstract
BACKGROUND Mirror movements (MM) are commonly caused by a defect of interhemispheric pathways also affected in multiple sclerosis (MS), particularly the corpus callosum. We investigated the prevalence of MM in MS in relation to functional and morphological callosal fiber integrity by transcranial magnetic stimulation (TMS), magnetic resonance imaging (MRI), as well as fatigue. METHODS In 21 patients with relapsing-remitting MS and 19 healthy controls, MM were assessed and graded (Woods and Teuber scale: MM 1-4) using a bedside test. Fatigue was evaluated using the Fatigue Scale for Motor and Cognitive Functions (FSMC) questionnaire. TMS measured ipsilateral silent period latency and duration. MRI assessed callosal atrophy by measuring the normalized corpus callosum area (nCCA), corpus callosum index (CCI), and lesion volume. RESULTS MS patients had significantly more often and pronounced MM compared to healthy controls (p = 0.0002) and nCCA was significantly lower (p = 0.045) in MRI studies. Patients with higher MM scores (MM > 1 vs. MM 0/1) showed significantly more fatigue (higher FSMC sum score, p = 0.04, motor score, p = 0.01). In TMS and MRI studies, no significant differences were found between patients with MM 0/1 and those with MM > 1 (ipsilateral silent period measurements, CCA, CCI and lesion volume). CONCLUSIONS MM are common in MS and can easily be detected through bedside testing. As MM are associated with fatigue, they might indicate fatigue in MS. It is possible that other cerebral structures, in addition to the corpus callosum, may contribute to the origin of MM in MS.
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Affiliation(s)
- Korbinian Holzapfel
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Augsburg, Germany.
| | - Antonios Bayas
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Markus Naumann
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Tanupriya Ghosh
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Verena Steuerwald
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Martin Allweyer
- Department of Neurology and Clinical Neurophysiology, Medical Faculty, University of Augsburg, Augsburg, Germany
| | - Jan S Kirschke
- Department of Neuroradiology, Faculty of Medicine, Technical University of Munich, Munich, Germany
| | - Lars Behrens
- Department of Diagnostic and Interventional Neuroradiology, Medical Faculty, University of Augsburg, Augsburg, Germany
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Cano LA, Albarracín AL, Pizá AG, García-Cena CE, Fernández-Jover E, Farfán FD. Assessing Cognitive Workload in Motor Decision-Making through Functional Connectivity Analysis: Towards Early Detection and Monitoring of Neurodegenerative Diseases. SENSORS (BASEL, SWITZERLAND) 2024; 24:1089. [PMID: 38400247 PMCID: PMC10893317 DOI: 10.3390/s24041089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/04/2023] [Accepted: 02/05/2024] [Indexed: 02/25/2024]
Abstract
Neurodegenerative diseases (NDs), such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and frontotemporal dementia, among others, are increasingly prevalent in the global population. The clinical diagnosis of these NDs is based on the detection and characterization of motor and non-motor symptoms. However, when these diagnoses are made, the subjects are often in advanced stages where neuromuscular alterations are frequently irreversible. In this context, we propose a methodology to evaluate the cognitive workload (CWL) of motor tasks involving decision-making processes. CWL is a concept widely used to address the balance between task demand and the subject's available resources to complete that task. In this study, multiple models for motor planning during a motor decision-making task were developed by recording EEG and EMG signals in n=17 healthy volunteers (9 males, 8 females, age 28.66±8.8 years). In the proposed test, volunteers have to make decisions about which hand should be moved based on the onset of a visual stimulus. We computed functional connectivity between the cortex and muscles, as well as among muscles using both corticomuscular and intermuscular coherence. Despite three models being generated, just one of them had strong performance. The results showed two types of motor decision-making processes depending on the hand to move. Moreover, the central processing of decision-making for the left hand movement can be accurately estimated using behavioral measures such as planning time combined with peripheral recordings like EMG signals. The models provided in this study could be considered as a methodological foundation to detect neuromuscular alterations in asymptomatic patients, as well as to monitor the process of a degenerative disease.
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Affiliation(s)
- Leonardo Ariel Cano
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
| | - Ana Lía Albarracín
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
| | - Alvaro Gabriel Pizá
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
| | - Cecilia Elisabet García-Cena
- ETSIDI-Center for Automation and Robotics, Universidad Politécnica de Madrid, Ronda de Valencia 3, 28012 Madrid, Spain
| | - Eduardo Fernández-Jover
- Institute of Bioengineering, Universidad Miguel Hernández of Elche, 03202 Elche, Spain
- Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029 Madrid, Spain
| | - Fernando Daniel Farfán
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
- Institute of Bioengineering, Universidad Miguel Hernández of Elche, 03202 Elche, Spain
- Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029 Madrid, Spain
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