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Quivira-Lopesino A, Sevilla-García M, Cuesta P, Pusil S, Bruña R, Fiedler P, Cebolla AM, Cheron G, Funke M, Maestu F. Changes of EEG beta band power and functional connectivity during spaceflight: a retrospective study. Sci Rep 2025; 15:13399. [PMID: 40251277 PMCID: PMC12008298 DOI: 10.1038/s41598-025-96897-5] [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: 10/15/2024] [Accepted: 04/01/2025] [Indexed: 04/20/2025] Open
Abstract
Spaceflight exposes astronauts to unique conditions like microgravity, which may affect brain function, though it remains underexplored compared to other physiological systems. Astronauts often report temporary neurological symptoms, such as disorientation, visual disturbances, and motor issues, potentially linked to structural and electrophysiological brain changes. To investigate this, electroencephalography (EEG) is a reliable tool to study brain activity in space, measuring oscillatory activity and functional connectivity (FC). This study analyzed EEG data from five male astronauts during three stages: pre-flight, during low Earth orbit (LEO), and post-flight in a 2-min task-free eyes-closed (EC) condition followed by another 2-min of eyes-open (EO) condition. The focus was on beta band (12-30 Hz) activity, which is associated with motor control and proprioception. Results showed increased beta power during spaceflight when compared to pre-flight (EC: p < 0.01) and post-flight (EC: p < 0.01; EO: p < 0.05) conditions. FC strength also increased during spaceflight when compared to pre-flight (EO: p < 0.05) and post-flight (EC: p < 0.01; EO: p < 0.01) conditions. These differences were found primarily in the sensorimotor cortex (SMC) and frontotemporal regions, suggesting the brain's adaptation to altered vestibular and proprioceptive inputs during microgravity. As these results reflect astronaut's movement adaptation to microgravity, this study highlights the importance of understanding central nervous system (CNS) changes during spaceflights to ensure optimal performance and protect astronaut's health during long-duration missions.
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Affiliation(s)
- Adrián Quivira-Lopesino
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Radiology, Rehabilitation, and Physiotherapy, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes, and Speech Therapy, School of Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - María Sevilla-García
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Electric Engineering, Universidad Politécnica de Madrid, Madrid, Spain
| | - Pablo Cuesta
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Radiology, Rehabilitation, and Physiotherapy, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
| | - Sandra Pusil
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Radiology, Rehabilitation, and Physiotherapy, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Patrique Fiedler
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany.
| | - Ana Maria Cebolla
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium
| | - Guy Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium
| | - Michael Funke
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Fernando Maestu
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes, and Speech Therapy, School of Psychology, Universidad Complutense de Madrid, Madrid, Spain
- Health Research Institute of the Hospital Clínico San Carlos (IdISSC), Madrid, Spain
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Meng M, Chen G, Chen S, Ma Y, Gao Y, Luo Z. DGPDR: discriminative geometric perception dimensionality reduction of SPD matrices on Riemannian manifold for EEG classification. Comput Methods Biomech Biomed Engin 2025:1-11. [PMID: 40083123 DOI: 10.1080/10255842.2025.2476184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 02/03/2025] [Accepted: 02/28/2025] [Indexed: 03/16/2025]
Abstract
Manifold learning with Symmetric Positive Definite (SPD) matrices has demonstrated potential for classifying Electroencephalography (EEG) in Brain-Computer Interface (BCI) applications. However, SPD matrices may lead to crucial information loss of EEG signals. This paper proposes a dimensionality reduction method based on discriminative geometric perception on the Riemannian manifold to enhance SPD matrix discriminability. Experiments on BCI Competition IV Dataset 1 and Dataset 2a show the proposed method improves accuracy by 5.0% and 19.38% respectively, demonstrating that applying discriminative geometric perception can effectively maintain robust performance associated with the dimensionality-reduced SPD matrix.
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Affiliation(s)
- Ming Meng
- International Joint Research Laboratory for Autonomous Robotic Systems, Hangzhou Dianzi University, Hangzhou, Zhejiang, China
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
| | - Guanzhen Chen
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
| | - Siqi Chen
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
| | - Yuliang Ma
- International Joint Research Laboratory for Autonomous Robotic Systems, Hangzhou Dianzi University, Hangzhou, Zhejiang, China
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
| | - Yunyuan Gao
- International Joint Research Laboratory for Autonomous Robotic Systems, Hangzhou Dianzi University, Hangzhou, Zhejiang, China
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
| | - Zhizeng Luo
- School of Automation, Hangzhou Dianzi University, Hangzhou, China
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Tamburro G, Fiedler P, De Fano A, Raeisi K, Khazaei M, Vaquero L, Bruña R, Oppermann H, Bertollo M, Filho E, Zappasodi F, Comani S. An ecological study protocol for the multimodal investigation of the neurophysiological underpinnings of dyadic joint action. Front Hum Neurosci 2023; 17:1305331. [PMID: 38125713 PMCID: PMC10730734 DOI: 10.3389/fnhum.2023.1305331] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Accepted: 11/15/2023] [Indexed: 12/23/2023] Open
Abstract
A novel multimodal experimental setup and dyadic study protocol were designed to investigate the neurophysiological underpinnings of joint action through the synchronous acquisition of EEG, ECG, EMG, respiration and kinematic data from two individuals engaged in ecologic and naturalistic cooperative and competitive joint actions involving face-to-face real-time and real-space coordinated full body movements. Such studies are still missing because of difficulties encountered in recording reliable neurophysiological signals during gross body movements, in synchronizing multiple devices, and in defining suitable study protocols. The multimodal experimental setup includes the synchronous recording of EEG, ECG, EMG, respiration and kinematic signals of both individuals via two EEG amplifiers and a motion capture system that are synchronized via a single-board microcomputer and custom Python scripts. EEG is recorded using new dry sports electrode caps. The novel study protocol is designed to best exploit the multimodal data acquisitions. Table tennis is the dyadic motor task: it allows naturalistic and face-to-face interpersonal interactions, free in-time and in-space full body movement coordination, cooperative and competitive joint actions, and two task difficulty levels to mimic changing external conditions. Recording conditions-including minimum table tennis rally duration, sampling rate of kinematic data, total duration of neurophysiological recordings-were defined according to the requirements of a multilevel analytical approach including a neural level (hyperbrain functional connectivity, Graph Theoretical measures and Microstate analysis), a cognitive-behavioral level (integrated analysis of neural and kinematic data), and a social level (extending Network Physiology to neurophysiological data recorded from two interacting individuals). Four practical tests for table tennis skills were defined to select the study population, permitting to skill-match the dyad members and to form two groups of higher and lower skilled dyads to explore the influence of skill level on joint action performance. Psychometric instruments are included to assess personality traits and support interpretation of results. Studying joint action with our proposed protocol can advance the understanding of the neurophysiological mechanisms sustaining daily life joint actions and could help defining systems to predict cooperative or competitive behaviors before being overtly expressed, particularly useful in real-life contexts where social behavior is a main feature.
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Affiliation(s)
- Gabriella Tamburro
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Patrique Fiedler
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Antonio De Fano
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Khadijeh Raeisi
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Mohammad Khazaei
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Lucia Vaquero
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Pschology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid, Madrid, Spain
| | - Ricardo Bruña
- Center for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Radiology, Universidad Complutense de Madrid, IdISSC, Madrid, Spain
| | - Hannes Oppermann
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Maurizio Bertollo
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Department of Medicine and Sciences of Aging, “University G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Edson Filho
- Wheelock College of Education and Human Development, Boston University, Boston, MA, United States
| | - Filippo Zappasodi
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Silvia Comani
- Department of Neuroscience Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “G. d’Annunzio” of Chieti–Pescara, Chieti, Italy
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Pusil S, Zegarra-Valdivia J, Cuesta P, Laohathai C, Cebolla AM, Haueisen J, Fiedler P, Funke M, Maestú F, Cheron G. Effects of spaceflight on the EEG alpha power and functional connectivity. Sci Rep 2023; 13:9489. [PMID: 37303002 DOI: 10.1038/s41598-023-34744-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 05/06/2023] [Indexed: 06/13/2023] Open
Abstract
Electroencephalography (EEG) can detect changes in cerebral activity during spaceflight. This study evaluates the effect of spaceflight on brain networks through analysis of the Default Mode Network (DMN)'s alpha frequency band power and functional connectivity (FC), and the persistence of these changes. Five astronauts' resting state EEGs under three conditions were analyzed (pre-flight, in-flight, and post-flight). DMN's alpha band power and FC were computed using eLORETA and phase-locking value. Eyes-opened (EO) and eyes-closed (EC) conditions were differentiated. We found a DMN alpha band power reduction during in-flight (EC: p < 0.001; EO: p < 0.05) and post-flight (EC: p < 0.001; EO: p < 0.01) when compared to pre-flight condition. FC strength decreased during in-flight (EC: p < 0.01; EO: p < 0.01) and post-flight (EC: ns; EO: p < 0.01) compared to pre-flight condition. The DMN alpha band power and FC strength reduction persisted until 20 days after landing. Spaceflight caused electrocerebral alterations that persisted after return to earth. Periodic assessment by EEG-derived DMN analysis has the potential to become a neurophysiologic marker of cerebral functional integrity during exploration missions to space.
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Affiliation(s)
- Sandra Pusil
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
| | - Jonathan Zegarra-Valdivia
- Achucarro Basque Center for Neuroscience, Leioa, Spain
- Global Brain Health Institute (GBHI), University of California, San Francisco (UCSF), San Francisco, CA, USA
- Universidad Señor de Sipán, Chiclayo, Peru
| | - Pablo Cuesta
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Radiology, Rehabilitation, and Physiotherapy, Universidad Complutense de Madrid, Madrid, Spain
| | | | - Ana Maria Cebolla
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium
| | - Jens Haueisen
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Patrique Fiedler
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Ilmenau, Germany
| | - Michael Funke
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Fernando Maestú
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
- Department of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Department of Experimental Psychology, Universidad Complutense de Madrid, Madrid, Spain
- Instituto de Investigación Sanitario, Hospital Clínico San Carlos, Madrid, Spain
| | - Guy Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium.
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