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Ngo T, Pathirana PN, Horne MK, Power L, Szmulewicz DJ, Milne SC, Corben LA, Roberts M, Delatycki MB. Balance Deficits due to Cerebellar Ataxia: A Machine Learning and Cloud-Based Approach. IEEE Trans Biomed Eng 2020; 68:1507-1517. [PMID: 33044924 DOI: 10.1109/tbme.2020.3030077] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Cerebellar ataxia (CA) refers to the disordered movement that occurs when the cerebellum is injured or affected by disease. It manifests as uncoordinated movement of the limbs, speech, and balance. This study is aimed at the formation of a simple, objective framework for the quantitative assessment of CA based on motion data. We adopted the Recurrence Quantification Analysis concept in identifying features of significance for the diagnosis. Eighty-six subjects were observed undertaking three standard neurological tests (Romberg's, Heel-shin and Truncal ataxia) to capture 213 time series inertial measurements each. The feature selection was based on engaging six different common techniques to distinguish feature subset for diagnosis and severity assessment separately. The Gaussian Naive Bayes classifier performed best in diagnosing CA with an average double cross-validation accuracy, sensitivity, and specificity of 88.24%, 85.89%, and 92.31%, respectively. Regarding severity assessment, the voting regression model exhibited a significant correlation (0.72 Pearson) with the clinical scores in the case of the Romberg's test. The Heel-shin and Truncal tests were considered for diagnosis and assessment of severity concerning subjects who were unable to stand. The underlying approach proposes a reliable, comprehensive framework for the assessment of postural stability due to cerebellar dysfunction using a single inertial measurement unit.
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Carment L, Dupin L, Guedj L, Térémetz M, Cuenca M, Krebs MO, Amado I, Maier MA, Lindberg PG. Neural noise and cortical inhibition in schizophrenia. Brain Stimul 2020; 13:1298-1304. [PMID: 32585356 DOI: 10.1016/j.brs.2020.06.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 05/25/2020] [Accepted: 06/14/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Neural information processing is subject to noise and this leads to variability in neural firing and behavior. Schizophrenia has been associated with both more variable motor control and impaired cortical inhibition, which is crucial for excitatory/inhibitory balance in neural commands. HYPOTHESIS In this study, we hypothesized that impaired intracortical inhibition in motor cortex would contribute to task-related motor noise in schizophrenia. METHODS We measured variability of force and of electromyographic (EMG) activity in upper limb and hand muscles during a visuomotor grip force-tracking paradigm in patients with schizophrenia (N = 25), in unaffected siblings (N = 17) and in healthy control participants (N = 25). Task-dependent primary motor cortex (M1) excitability and inhibition were assessed using transcranial magnetic stimulation (TMS). RESULTS During force maintenance patients with schizophrenia showed increased variability in force and EMG, despite similar mean force and EMG magnitudes. Compared to healthy controls, patients with schizophrenia also showed increased M1 excitability and reduced cortical inhibition during grip-force tracking. EMG variability and force variability correlated negatively to cortical inhibition in patients with schizophrenia. EMG variability also correlated positively to negative symptoms. Siblings had similar variability and cortical inhibition compared to controls. Increased EMG and force variability indicate enhanced motor noise in schizophrenia, which relates to reduced motor cortex inhibition. CONCLUSION The findings suggest that excessive motor noise in schizophrenia may arise from an imbalance of M1 excitation/inhibition of GABAergic origin. Thus, higher motor noise may provide a useful marker of impaired cortical inhibition in schizophrenia.
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Affiliation(s)
- Loïc Carment
- Institute of Psychiatry and Neuroscience of Paris, INSERM U894, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Institut de Psychiatrie, CNRS, GDR3557, Paris, France.
| | - Lucile Dupin
- Institute of Psychiatry and Neuroscience of Paris, INSERM U894, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Institut de Psychiatrie, CNRS, GDR3557, Paris, France
| | - Laura Guedj
- Resource Center for Cognitive Remediation and Psychosocial Rehabilitation, C3RP, Université de Paris, GHU Psychiatrie et Neurosciences Sainte-Anne, Paris, France
| | - Maxime Térémetz
- Institute of Psychiatry and Neuroscience of Paris, INSERM U894, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Institut de Psychiatrie, CNRS, GDR3557, Paris, France
| | - Macarena Cuenca
- Institut de Psychiatrie, CNRS, GDR3557, Paris, France; Centre de Recherche Clinique, Hôpital Sainte-Anne, Paris, France
| | - Marie-Odile Krebs
- Institute of Psychiatry and Neuroscience of Paris, INSERM U894, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Institut de Psychiatrie, CNRS, GDR3557, Paris, France; Resource Center for Cognitive Remediation and Psychosocial Rehabilitation, C3RP, Université de Paris, GHU Psychiatrie et Neurosciences Sainte-Anne, Paris, France
| | - Isabelle Amado
- Institute of Psychiatry and Neuroscience of Paris, INSERM U894, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Institut de Psychiatrie, CNRS, GDR3557, Paris, France; Resource Center for Cognitive Remediation and Psychosocial Rehabilitation, C3RP, Université de Paris, GHU Psychiatrie et Neurosciences Sainte-Anne, Paris, France
| | - Marc A Maier
- Institut de Psychiatrie, CNRS, GDR3557, Paris, France; Université de Paris, CNRS UMR, 8002, Paris, France
| | - Påvel G Lindberg
- Institute of Psychiatry and Neuroscience of Paris, INSERM U894, Université Paris Descartes, Sorbonne Paris Cité, Paris, France; Institut de Psychiatrie, CNRS, GDR3557, Paris, France
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Miroshnichenko GG, Meigal AY, Saenko IV, Gerasimova-Meigal LI, Chernikova LA, Subbotina NS, Rissanen SM, Karjalainen PA. Parameters of Surface Electromyogram Suggest That Dry Immersion Relieves Motor Symptoms in Patients With Parkinsonism. Front Neurosci 2018; 12:667. [PMID: 30319343 PMCID: PMC6168649 DOI: 10.3389/fnins.2018.00667] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 09/05/2018] [Indexed: 11/13/2022] Open
Abstract
Dry immersion (DI) is acknowledged as a reliable space flight analog condition. At DI, subject is immersed in water being wrapped in a waterproof film to imitate microgravity (μG). Microgravity is known to decrease muscle tone due to deprivation of the sensory stimuli that activate the reflexes that keep up the muscle tone. In contrary, parkinsonian patients are characterized by elevated muscle tone, or rigidity, along with rest tremor and akinesia. We hypothesized that DI can diminish the elevated muscle tone and/or the tremor in parkinsonian patients. Fourteen patients with Parkinson's disease (PD, 10 males, 4 females, 47-73 years) and 5 patients with vascular parkinsonism (VP, 1 male, 4 females, 65-72 years) participated in the study. To evaluate the effect of DI on muscles' functioning, we compared parameters of surface electromyogram (sEMG) measured before and after a single 45-min long immersion session. The sEMG recordings were made from the biceps brachii muscle, bilaterally. Each recording was repeated with the following loading conditions: with arms hanging freely down, and with 0, 1, and 2 kg loading on each hand with elbows flexed to 90°. The sEMG parameters comprised of amplitude, median frequency, time of decay of mutual information, sample entropy, correlation dimension, recurrence rate, and determinism of sEMG. These parameters have earlier been proved to be sensitive to PD severity. We used the Wilcoxon test to decide which parameters were statistically significantly different before and after the dry immersion. Accepting the p < 0.05 significance level, amplitude, time of decay of mutual information, recurrence rate, and determinism tended to decrease, while median frequency and sample entropy of sEMG tended to increase after the DI. The most statistically significant change was for the determinism of sEMG from the left biceps with 1 kg loading, which decreased for 84% of the patients. The results suggest that DI can promptly relieve motor symptoms of parkinsonism. We conclude that DI has strong potential as a rehabilitation method for parkinsonian patients.
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Affiliation(s)
- German G Miroshnichenko
- Biosignal Analysis and Medical Imaging Group, Department of Applied Physics, Faculty of Science and Forestry, University of Eastern Finland, Kuopio, Finland
| | - Alexander Yu Meigal
- Laboratory for Novel Methods in Physiology, Institute of High-Tech Biomedical Solutions, Petrozavodsk State University, Petrozavodsk, Russia
| | - Irina V Saenko
- Laboratory of Gravitational Physiology of Sensorimotor System, Department of Sensorimotor Physiology and Countermeasure, Institute of BioMedical Problems, Russian Academy of Sciences, Moscow, Russia
| | - Liudmila I Gerasimova-Meigal
- Department of Human and Animal Physiology, Physiopathology, Histology, Petrozavodsk State University, Petrozavodsk, Russia
| | - Liudmila A Chernikova
- Department of Neurorehabilitation and Physiotherapy, Research Center of Neurology, Russian Academy of Medical Sciences, Moscow, Russia
| | - Natalia S Subbotina
- Department of Neurology, Psychiatry, and Microbiology, Petrozavodsk State University, Petrozavodsk, Russia
| | - Saara M Rissanen
- Biosignal Analysis and Medical Imaging Group, Department of Applied Physics, Faculty of Science and Forestry, University of Eastern Finland, Kuopio, Finland
| | - Pasi A Karjalainen
- Biosignal Analysis and Medical Imaging Group, Department of Applied Physics, Faculty of Science and Forestry, University of Eastern Finland, Kuopio, Finland
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