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Buoite Stella A, Ajčević M, Furlanis G, Manganotti P. Neurophysiological adaptations to spaceflight and simulated microgravity. Clin Neurophysiol 2020; 132:498-504. [PMID: 33450569 DOI: 10.1016/j.clinph.2020.11.033] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 11/12/2020] [Accepted: 11/29/2020] [Indexed: 01/03/2023]
Abstract
Changes in physiological functions after spaceflight and simulated spaceflight involve several mechanisms. Microgravity is one of them and it can be partially reproduced with models, such as head down bed rest (HDBR). Yet, only a few studies have investigated in detail the complexity of neurophysiological systems and their integration to maintain homeostasis. Central nervous system changes have been studied both in their structural and functional component with advanced techniques, such as functional magnetic resonance (fMRI), showing the main involvement of the cerebellum, cortical sensorimotor, and somatosensory areas, as well as vestibular-related pathways. Analysis of electroencephalography (EEG) led to contrasting results, mainly due to the different factors affecting brain activity. The study of corticospinal excitability may enable a deeper understanding of countermeasures' effect, since greater excitability has been shown being correlated with better preservation of functions. Less is known about somatosensory evoked potentials and peripheral nerve function, yet they may be involved in a homeostatic mechanism fundamental to thermoregulation. Extending the knowledge of such alterations during simulated microgravity may be useful not only for space exploration, but for its application in clinical conditions and for life on Earth, as well.
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Affiliation(s)
- Alex Buoite Stella
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Cattinara University Hospital ASUGI, University of Trieste, Strada di Fiume, 447, 34149 Trieste, Italy
| | - Miloš Ajčević
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Cattinara University Hospital ASUGI, University of Trieste, Strada di Fiume, 447, 34149 Trieste, Italy; Department of Engineering and Architecture, University of Trieste, Via Alfonso Valerio, 6/1, 34127 Trieste, Italy
| | - Giovanni Furlanis
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Cattinara University Hospital ASUGI, University of Trieste, Strada di Fiume, 447, 34149 Trieste, Italy
| | - Paolo Manganotti
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Cattinara University Hospital ASUGI, University of Trieste, Strada di Fiume, 447, 34149 Trieste, Italy.
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Al Harrach M, Rousseau F, Groeschel S, Chabrier S, Hertz-Pannier L, Lefevre J, Dinomais M. Is the Blood Oxygenation Level-Dependent fMRI Response to Motor Tasks Altered in Children After Neonatal Stroke? Front Hum Neurosci 2020; 14:154. [PMID: 32410976 PMCID: PMC7202247 DOI: 10.3389/fnhum.2020.00154] [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: 12/04/2019] [Accepted: 04/07/2020] [Indexed: 12/13/2022] Open
Abstract
Functional MRI is increasingly being used in the assessment of brain activation and connectivity following stroke. Many of these studies rely on the Blood Oxygenation Level Dependent (BOLD) contrast. However, the stability, as well as the accuracy of the BOLD response to motor task in the ipsilesional hemisphere, remains ambiguous. In this work, the BOLD signal acquired from both healthy and affected hemispheres was analyzed in 7-year-old children who sustained a Neonatal Arterial Ischemic Stroke (NAIS). Accordingly, a repetitive motor task of the contralesional and the ipsilesional hands was performed by 33 patients with unilateral lesions. These patients were divided into two groups: those without cerebral palsy (NAIS), and those with cerebral palsy (CP). The BOLD signal time course was obtained from distinctly defined regions of interest (ROIs) extracted from the functional activation maps of 30 healthy controls with similar age and demographic characteristics as the patients. An ROI covering both the primary motor cortex (M1) and the primary somatosensory cortex (S1) was also tested. Compared with controls, NAIS patients without CP had similar BOLD amplitude variation for both the contralesional and the ipsilesional hand movements. However, in the case of NAIS patients with CP, a significant difference in the averaged BOLD amplitude was found between the healthy and affected hemisphere. In both cases, no progressive attenuation of the BOLD signal amplitude was observed throughout the task epochs. Besides, results also showed a correlation between the BOLD signal percentage variation of the lesioned hemisphere and the dexterity level. These findings suggest that for patients who sustained a NAIS with no extensive permanent motor impairment, BOLD signal-based data analysis can be a valuable tool for the evaluation of functional brain networks.
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Affiliation(s)
- Mariam Al Harrach
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS) EA7315, Université d'Angers, Polytech Angers, Angers, France
| | | | - Samuel Groeschel
- Department of Child Neurology, Paediatric Neuroimaging, University Hospital, Tübingen, Germany
| | - Stéphane Chabrier
- INSERM UMR1059 Sainbiose, Univ Saint-Étienne, Univ Lyon, Saint-Étienne, France.,INSERM, CIC 1408, CHU Saint-Étienne, French Centre for Paediatric Stroke, Paediatric Physical and Rehabilitation Medicine Department, Saint-Étienne, France
| | - Lucie Hertz-Pannier
- INSERM U114 Neurospin, UNIACT, Institut Joliot, Université de Paris, CEA-Paris Saclay, Gif sur Yvette, France
| | - Julien Lefevre
- UMR CNRS 7289, Aix Marseille Université, Institut de Neurosciences de la Timone, Marseille, France
| | - Mickael Dinomais
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS) EA7315, Université d'Angers, Polytech Angers, Angers, France.,CHU Angers, Département de Médecine Physique et de Réadaptions and LUNAM, Angers, France
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Storti SF, Formaggio E, Manganotti P, Menegaz G. Brain Network Connectivity and Topological Analysis During Voluntary Arm Movements. Clin EEG Neurosci 2016; 47:276-290. [PMID: 26251456 DOI: 10.1177/1550059415598905] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 07/08/2015] [Indexed: 11/16/2022]
Abstract
Functional connectivity estimates the temporal synchrony among functionally homogeneous brain regions based on the assessment of the dynamics of topologically localized neurophysiological responses. The aim of this study was to investigate task-related changes in brain activity and functional connectivity by applying different methods namely event-related desynchronization (ERD), coherence, and graph-theoretical analysis to electroencephalographic (EEG) recordings, for comparing their respective descriptive power and complementarity. As it is well known, ERD provides an estimate of differences in power spectral densities between active (or task) and rest conditions, functional connectivity allows assessing the level of synchronization between the signals recorded at different scalp locations and graph analysis enables the estimation of the functional network features and topology. EEG activity was recorded on 10 subjects during left/right arm movements. The theta, alpha, and beta bands were considered. Conventional analysis showed a significant ERD in both alpha and beta bands over the sensorimotor cortex during the left arm movement and in beta band during the right arm movement, besides identifying the regions involved in the task, as it was expected. On the other hand, connectivity assessment highlighted that stronger connections are those that involved the motor regions for which graph analysis revealed reduced accessibility and an increased centrality during the movement. Jointly, the last two methods allow identifying the cortical areas that are functionally related in the active condition as well as the topological organization of the functional network. Results support the hypothesis that network analysis brings complementary knowledge with respect to established approaches for modeling motor-induced functional connectivity and could be profitably exploited in clinical contexts.
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Affiliation(s)
| | - Emanuela Formaggio
- Department of Neurophysiology, Foundation IRCCS San Camillo Hospital, Venice, Italy
| | - Paolo Manganotti
- Department of Medical, Surgical and Health Sciences, Clinical Neurology Unit, Cattinara University Hospital, Trieste, Italy
| | - Gloria Menegaz
- Department of Computer Science, University of Verona, Verona, Italy
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