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Barnes L, Davidson MJ, Alais D. The speed and phase of locomotion dictate saccade probability and simultaneous low-frequency power spectra. Atten Percept Psychophys 2024:10.3758/s13414-024-02932-4. [PMID: 39048846 DOI: 10.3758/s13414-024-02932-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/14/2024] [Indexed: 07/27/2024]
Abstract
Every day we make thousands of saccades and take thousands of steps as we explore our environment. Despite their common co-occurrence in a typical active state, we know little about the coordination between eye movements, walking behaviour and related changes in cortical activity. Technical limitations have been a major impediment, which we overcome here by leveraging the advantages of an immersive wireless virtual reality (VR) environment with three-dimensional (3D) position tracking, together with simultaneous recording of eye movements and mobile electroencephalography (EEG). Using this approach with participants engaged in unencumbered walking along a clear, level path, we find that the likelihood of eye movements at both slow and natural walking speeds entrains to the rhythm of footfall, peaking after the heel-strike of each step. Compared to previous research, this entrainment was captured in a task that did not require visually guided stepping - suggesting a persistent interaction between locomotor and visuomotor functions. Simultaneous EEG recordings reveal a concomitant modulation entrained to heel-strike, with increases and decreases in oscillatory power for a broad range of frequencies. The peak of these effects occurred in the theta and alpha range for slow and natural walking speeds, respectively. Together, our data show that the phase of the step-cycle influences other behaviours such as eye movements, and produces related modulations of simultaneous EEG following the same rhythmic pattern. These results reveal gait as an important factor to be considered when interpreting saccadic and time-frequency EEG data in active observers, and demonstrate that saccadic entrainment to gait may persist throughout everyday activities.
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Affiliation(s)
- Lydia Barnes
- School of Psychology, The University of Sydney, Sydney, NSW, Australia
| | | | - David Alais
- School of Psychology, The University of Sydney, Sydney, NSW, Australia
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Richer N, Bradford JC, Ferris DP. Mobile neuroimaging: What we have learned about the neural control of human walking, with an emphasis on EEG-based research. Neurosci Biobehav Rev 2024; 162:105718. [PMID: 38744350 DOI: 10.1016/j.neubiorev.2024.105718] [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: 10/30/2023] [Revised: 04/18/2024] [Accepted: 05/08/2024] [Indexed: 05/16/2024]
Abstract
Our understanding of the neural control of human walking has changed significantly over the last twenty years and mobile brain imaging methods have contributed substantially to current knowledge. High-density electroencephalography (EEG) has the advantages of being lightweight and mobile while providing temporal resolution of brain changes within a gait cycle. Advances in EEG hardware and processing methods have led to a proliferation of research on the neural control of locomotion in neurologically intact adults. We provide a narrative review of the advantages and disadvantages of different mobile brain imaging methods, then summarize findings from mobile EEG studies quantifying electrocortical activity during human walking. Contrary to historical views on the neural control of locomotion, recent studies highlight the widespread involvement of many areas, such as the anterior cingulate, posterior parietal, prefrontal, premotor, sensorimotor, supplementary motor, and occipital cortices, that show active fluctuations in electrical power during walking. The electrocortical activity changes with speed, stability, perturbations, and gait adaptation. We end with a discussion on the next steps in mobile EEG research.
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Affiliation(s)
- Natalie Richer
- Department of Kinesiology and Applied Health, University of Winnipeg, Winnipeg, Manitoba, Canada.
| | - J Cortney Bradford
- US Army Combat Capabilities Development Command US Army Research Laboratory, Adelphi, MD, USA
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
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Arpaia P, Cuocolo R, Fullin A, Gargiulo L, Mancino F, Moccaldi N, Vallefuoco E, De Blasiis P. Executive Functions Assessment Based on Wireless EEG and 3D Gait Analysis During Dual-Task: A Feasibility Study. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2024; 12:268-278. [PMID: 38410182 PMCID: PMC10896422 DOI: 10.1109/jtehm.2024.3357287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/16/2024] [Accepted: 01/17/2024] [Indexed: 02/28/2024]
Abstract
Executive functions (EFs) are neurocognitive processes planning and regulating daily life actions. Performance of two simultaneous tasks, requiring the same cognitive resources, lead to a cognitive fatigue. Several studies investigated cognitive-motor task and the interference during walking, highlighting an increasing risk of falls especially in elderly and people with neurological diseases. A few studies instrumentally explored relationship between activation-no-activation of two EFs (working memory and inhibition) and spatial-temporal gait parameters. Aim of our study was to detect activation of inhibition and working memory during progressive difficulty levels of cognitive tasks and spontaneous walking using, respectively, wireless electroencephalography (EEG) and 3D-gait analysis. Thirteen healthy subjects were recruited. Two cognitive tasks were performed, activating inhibition (Go-NoGo) and working memory (N-back). EEG features (absolute and relative power in different bands) and kinematic parameters (7 spatial-temporal ones and Gait Variable Score for 9 range of motion of lower limbs) were analyzed. A significant decrease of stride length and an increase of external-rotation of foot progression were found during dual task with Go-NoGo. Moreover, a significant correlation was found between the relative power in the delta band at channels Fz, C4 and progressive difficulty levels of Go-NoGo (activating inhibition) during walking, whereas working memory showed no correlation. This study reinforces the hypothesis of the prevalent involvement of inhibition with respect to working memory during dual task walking and reveals specific kinematic adaptations. The foundations for EEG-based monitoring of cognitive processes involved in gait are laid. Clinical and Translational Impact Statement: Clinical and instrumental evaluation and training of executive functions (as inhibition), during cognitive-motor task, could be useful for rehabilitation treatment of gait disorder in elderly and people with neurological disease.
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Affiliation(s)
- Pasquale Arpaia
- Department of Electrical Engineering and Information TechnologiesUniversity of Naples Federico II 80138 Naples Italy
| | - Renato Cuocolo
- Department of Medicine, Surgery, and DentistryScuola Medica SalernitanaUniversity of Salerno 84084 Salerno Italy
| | - Allegra Fullin
- Department of Mental and Physical Health and Preventive MedicineSection of Human AnatomyUniversity of Campania Luigi Vanvitelli Caserta 81100 Naples Italy
- Department of Advanced Biomedical SciencesUniversity of Naples Federico II 80138 Naples Italy
| | - Ludovica Gargiulo
- Department of Electrical Engineering and Information TechnologiesUniversity of Naples Federico II 80138 Naples Italy
| | - Francesca Mancino
- Department of Electrical Engineering and Information TechnologiesUniversity of Naples Federico II 80138 Naples Italy
| | - Nicola Moccaldi
- Department of Electrical Engineering and Information TechnologiesUniversity of Naples Federico II 80138 Naples Italy
| | - Ersilia Vallefuoco
- Department of Psychology and Cognitive ScienceUniversity of Trento 38122 Rovereto Italy
| | - Paolo De Blasiis
- Department of Mental and Physical Health and Preventive MedicineSection of Human AnatomyUniversity of Campania Luigi Vanvitelli Caserta 81100 Naples Italy
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Lorenz EA, Su X, Skjæret-Maroni N. A review of combined functional neuroimaging and motion capture for motor rehabilitation. J Neuroeng Rehabil 2024; 21:3. [PMID: 38172799 PMCID: PMC10765727 DOI: 10.1186/s12984-023-01294-6] [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: 06/23/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Technological advancements in functional neuroimaging and motion capture have led to the development of novel methods that facilitate the diagnosis and rehabilitation of motor deficits. These advancements allow for the synchronous acquisition and analysis of complex signal streams of neurophysiological data (e.g., EEG, fNIRS) and behavioral data (e.g., motion capture). The fusion of those data streams has the potential to provide new insights into cortical mechanisms during movement, guide the development of rehabilitation practices, and become a tool for assessment and therapy in neurorehabilitation. RESEARCH OBJECTIVE This paper aims to review the existing literature on the combined use of motion capture and functional neuroimaging in motor rehabilitation. The objective is to understand the diversity and maturity of technological solutions employed and explore the clinical advantages of this multimodal approach. METHODS This paper reviews literature related to the combined use of functional neuroimaging and motion capture for motor rehabilitation following the PRISMA guidelines. Besides study and participant characteristics, technological aspects of the used systems, signal processing methods, and the nature of multimodal feature synchronization and fusion were extracted. RESULTS Out of 908 publications, 19 were included in the final review. Basic or translation studies were mainly represented and based predominantly on healthy participants or stroke patients. EEG and mechanical motion capture technologies were most used for biomechanical data acquisition, and their subsequent processing is based mainly on traditional methods. The system synchronization techniques at large were underreported. The fusion of multimodal features mainly supported the identification of movement-related cortical activity, and statistical methods were occasionally employed to examine cortico-kinematic relationships. CONCLUSION The fusion of motion capture and functional neuroimaging might offer advantages for motor rehabilitation in the future. Besides facilitating the assessment of cognitive processes in real-world settings, it could also improve rehabilitative devices' usability in clinical environments. Further, by better understanding cortico-peripheral coupling, new neuro-rehabilitation methods can be developed, such as personalized proprioceptive training. However, further research is needed to advance our knowledge of cortical-peripheral coupling, evaluate the validity and reliability of multimodal parameters, and enhance user-friendly technologies for clinical adaptation.
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Affiliation(s)
- Emanuel A Lorenz
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway.
| | - Xiaomeng Su
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Nina Skjæret-Maroni
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
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Khajuria A, Sharma R, Joshi D. EEG Dynamics of Locomotion and Balancing: Solution to Neuro-Rehabilitation. Clin EEG Neurosci 2024; 55:143-163. [PMID: 36052404 DOI: 10.1177/15500594221123690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The past decade has witnessed tremendous growth in analyzing the cortical representation of human locomotion and balance using Electroencephalography (EEG). With the advanced developments in miniaturized electronics, wireless brain recording systems have been developed for mobile recordings, such as in locomotion. In this review, the cortical dynamics during locomotion are presented with extensive focus on motor imagery, and employing the treadmill as a tool for performing different locomotion tasks. Further, the studies that examine the cortical dynamics during balancing, focusing on two types of balancing tasks, ie, static and dynamic, with the challenges in sensory inputs and cognition (dual-task), are presented. Moreover, the current literature demonstrates the advancements in signal processing methods to detect and remove the artifacts from EEG signals. Prior studies show the electrocortical sources in the anterior cingulate, posterior parietal, and sensorimotor cortex was found to be activated during locomotion. The event-related potential has been observed to increase in the fronto-central region for a wide range of balance tasks. The advanced knowledge of cortical dynamics during mobility can benefit various application areas such as neuroprosthetics and gait/balance rehabilitation. This review will be beneficial for the development of neuroprostheses, and rehabilitation devices for patients suffering from movement or neurological disorders.
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Affiliation(s)
- Aayushi Khajuria
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Richa Sharma
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Deepak Joshi
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
- Department of Biomedical Engineering, All India Institute of Medical Sciences, New Delhi, India
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Yang SY, Lin YP. Movement Artifact Suppression in Wearable Low-Density and Dry EEG Recordings Using Active Electrodes and Artifact Subspace Reconstruction. IEEE Trans Neural Syst Rehabil Eng 2023; 31:3844-3853. [PMID: 37751338 DOI: 10.1109/tnsre.2023.3319355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/28/2023]
Abstract
Wearable low-density dry electroencephalogram (EEG) headsets facilitate multidisciplinary applications of brain-activity decoding and brain-triggered interaction for healthy people in real-world scenarios. However, movement artifacts pose a great challenge to their validity in users with naturalistic behaviors (i.e., without highly controlled settings in a laboratory). High-precision, high-density EEG instruments commonly embed an active electrode infrastructure and/or incorporate an auxiliary artifact subspace reconstruction (ASR) pipeline to handle movement artifact interferences. Existing endeavors motivate this study to explore the efficacy of both hardware and software solutions in low-density and dry EEG recordings against non-tethered settings, which are rarely found in the literature. Therefore, this study employed a LEGO-like electrode-holder assembly grid to coordinate three 3-channel system designs (with passive/active dry vs. passive wet electrodes). It also conducted a simultaneous EEG recording while performing an oddball task during treadmill walking, with speeds of 1 and 2 KPH. The quantitative metrics of pre-stimulus noise, signal-to-noise ratio, and inter-subject correlation from the collected event-related potentials of 18 subjects were assessed. Results indicate that while treating a passive-wet system as benchmark, only the active-electrode design more or less rectified movement artifacts for dry electrodes, whereas the ASR pipeline was substantially compromised by limited electrodes. These findings suggest that a lightweight, minimally obtrusive dry EEG headset should at least equip an active-electrode infrastructure to withstand realistic movement artifacts for potentially sustaining its validity and applicability in real-world scenarios.
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Monroe DC, Berry NT, Fino PC, Rhea CK. A Dynamical Systems Approach to Characterizing Brain-Body Interactions during Movement: Challenges, Interpretations, and Recommendations. SENSORS (BASEL, SWITZERLAND) 2023; 23:6296. [PMID: 37514591 PMCID: PMC10385586 DOI: 10.3390/s23146296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/16/2023] [Accepted: 06/20/2023] [Indexed: 07/30/2023]
Abstract
Brain-body interactions (BBIs) have been the focus of intense scrutiny since the inception of the scientific method, playing a foundational role in the earliest debates over the philosophy of science. Contemporary investigations of BBIs to elucidate the neural principles of motor control have benefited from advances in neuroimaging, device engineering, and signal processing. However, these studies generally suffer from two major limitations. First, they rely on interpretations of 'brain' activity that are behavioral in nature, rather than neuroanatomical or biophysical. Second, they employ methodological approaches that are inconsistent with a dynamical systems approach to neuromotor control. These limitations represent a fundamental challenge to the use of BBIs for answering basic and applied research questions in neuroimaging and neurorehabilitation. Thus, this review is written as a tutorial to address both limitations for those interested in studying BBIs through a dynamical systems lens. First, we outline current best practices for acquiring, interpreting, and cleaning scalp-measured electroencephalography (EEG) acquired during whole-body movement. Second, we discuss historical and current theories for modeling EEG and kinematic data as dynamical systems. Third, we provide worked examples from both canonical model systems and from empirical EEG and kinematic data collected from two subjects during an overground walking task.
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Affiliation(s)
- Derek C Monroe
- Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, NC 27402, USA
| | - Nathaniel T Berry
- Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, NC 27402, USA
- Under Armour, Inc., Innovation, Baltimore, MD 21230, USA
| | - Peter C Fino
- Department of Health and Kinesiology, University of Utah, Salt Lake City, UT 84112, USA
| | - Christopher K Rhea
- College of Health Sciences, Old Dominion University, Norfolk, VA 23508, USA
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Wang P, Cao X, Zhou Y, Gong P, Yousefnezhad M, Shao W, Zhang D. A comprehensive review on motion trajectory reconstruction for EEG-based brain-computer interface. Front Neurosci 2023; 17:1086472. [PMID: 37332859 PMCID: PMC10272365 DOI: 10.3389/fnins.2023.1086472] [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: 11/01/2022] [Accepted: 05/03/2023] [Indexed: 06/20/2023] Open
Abstract
The advance in neuroscience and computer technology over the past decades have made brain-computer interface (BCI) a most promising area of neurorehabilitation and neurophysiology research. Limb motion decoding has gradually become a hot topic in the field of BCI. Decoding neural activity related to limb movement trajectory is considered to be of great help to the development of assistive and rehabilitation strategies for motor-impaired users. Although a variety of decoding methods have been proposed for limb trajectory reconstruction, there does not yet exist a review that covers the performance evaluation of these decoding methods. To alleviate this vacancy, in this paper, we evaluate EEG-based limb trajectory decoding methods regarding their advantages and disadvantages from a variety of perspectives. Specifically, we first introduce the differences in motor execution and motor imagery in limb trajectory reconstruction with different spaces (2D and 3D). Then, we discuss the limb motion trajectory reconstruction methods including experiment paradigm, EEG pre-processing, feature extraction and selection, decoding methods, and result evaluation. Finally, we expound on the open problem and future outlooks.
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Affiliation(s)
| | | | | | | | | | - Wei Shao
- *Correspondence: Wei Shao, ; Daoqiang Zhang,
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9
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Korivand S, Jalili N, Gong J. Experiment protocols for brain-body imaging of locomotion: A systematic review. Front Neurosci 2023; 17:1051500. [PMID: 36937690 PMCID: PMC10014824 DOI: 10.3389/fnins.2023.1051500] [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: 09/22/2022] [Accepted: 02/06/2023] [Indexed: 03/05/2023] Open
Abstract
Introduction Human locomotion is affected by several factors, such as growth and aging, health conditions, and physical activity levels for maintaining overall health and well-being. Notably, impaired locomotion is a prevalent cause of disability, significantly impacting the quality of life of individuals. The uniqueness and high prevalence of human locomotion have led to a surge of research to develop experimental protocols for studying the brain substrates, muscle responses, and motion signatures associated with locomotion. However, from a technical perspective, reproducing locomotion experiments has been challenging due to the lack of standardized protocols and benchmarking tools, which impairs the evaluation of research quality and the validation of previous findings. Methods This paper addresses the challenges by conducting a systematic review of existing neuroimaging studies on human locomotion, focusing on the settings of experimental protocols, such as locomotion intensity, duration, distance, adopted brain imaging technologies, and corresponding brain activation patterns. Also, this study provides practical recommendations for future experiment protocols. Results The findings indicate that EEG is the preferred neuroimaging sensor for detecting brain activity patterns, compared to fMRI, fNIRS, and PET. Walking is the most studied human locomotion task, likely due to its fundamental nature and status as a reference task. In contrast, running has received little attention in research. Additionally, cycling on an ergometer at a speed of 60 rpm using fNIRS has provided some research basis. Dual-task walking tasks are typically used to observe changes in cognitive function. Moreover, research on locomotion has primarily focused on healthy individuals, as this is the scenario most closely resembling free-living activity in real-world environments. Discussion Finally, the paper outlines the standards and recommendations for setting up future experiment protocols based on the review findings. It discusses the impact of neurological and musculoskeletal factors, as well as the cognitive and locomotive demands, on the experiment design. It also considers the limitations imposed by the sensing techniques used, including the acceptable level of motion artifacts in brain-body imaging experiments and the effects of spatial and temporal resolutions on brain sensor performance. Additionally, various experiment protocol constraints that need to be addressed and analyzed are explained.
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Affiliation(s)
- Soroush Korivand
- Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL, United States
- Department of Computer Science, The University of Alabama, Tuscaloosa, AL, United States
| | - Nader Jalili
- Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL, United States
| | - Jiaqi Gong
- Department of Computer Science, The University of Alabama, Tuscaloosa, AL, United States
- *Correspondence: Jiaqi Gong
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Palucci Vieira LH, Carling C, da Silva JP, Santinelli FB, Polastri PF, Santiago PRP, Barbieri FA. Modelling the relationships between EEG signals, movement kinematics and outcome in soccer kicking. Cogn Neurodyn 2022; 16:1303-1321. [PMID: 36408067 PMCID: PMC9666621 DOI: 10.1007/s11571-022-09786-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 01/03/2022] [Accepted: 01/21/2022] [Indexed: 12/16/2022] Open
Abstract
The contribution of cortical activity (e.g. EEG recordings) in various brain regions to motor control during goal-directed manipulative tasks using lower limbs remains unexplored. Therefore, the aim of the current study was to determine the magnitude of associations between EEG-derived brain activity and soccer kicking parameters. Twenty-four under-17 players performed an instep kicking task (18 m from the goal) aiming to hit 1 × 1 m targets allocated in the goalpost upper corners in the presence of a goalkeeper. Using a portable 64-channel EEG system, brain oscillations in delta, theta, alpha, beta and gamma frequency bands were determined at the frontal, motor, parietal and occipital regions separately for three phases of the kicks: preparatory, approach and immediately prior to ball contact. Movement kinematic measures included segmental linear and relative velocities, angular joint displacement and velocities. Mean radial error and ball velocity were assumed as outcome indicators. A significant influence of frontal theta power immediately prior to ball contact was observed in the variance of ball velocity (R 2 = 35%, P = 0.01) while the expression of occipital alpha component recorded during the preparatory phase contributed to the mean radial error (R 2 = 20%, P = 0.049). Ankle eversion angle at impact moment likely mediated the association between frontal theta power and subsequent ball velocity (β = 0.151, P = 0.06). The present analysis showed that the brain signalling at cortical level may be determinant in movement control, ball velocity and accuracy when performing kick attempts from the edge of penalty area. Trial registration number #RBR-8prx2m-Brazilian Registry of Clinical Trials ReBec. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09786-2.
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Affiliation(s)
- Luiz H. Palucci Vieira
- Human Movement Research Laboratory (MOVI-LAB), Faculty of Sciences, Graduate Program in Movement Sciences, Department of Physical Education, São Paulo State University (Unesp), Av. Eng. Luís Edmundo Carrijo Coube, 2085 - Nucleo Res. Pres. Geisel, Bauru, SP 17033-360 Brazil
| | | | - João Pedro da Silva
- Human Movement Research Laboratory (MOVI-LAB), Faculty of Sciences, Graduate Program in Movement Sciences, Department of Physical Education, São Paulo State University (Unesp), Av. Eng. Luís Edmundo Carrijo Coube, 2085 - Nucleo Res. Pres. Geisel, Bauru, SP 17033-360 Brazil
| | - Felipe B. Santinelli
- Human Movement Research Laboratory (MOVI-LAB), Faculty of Sciences, Graduate Program in Movement Sciences, Department of Physical Education, São Paulo State University (Unesp), Av. Eng. Luís Edmundo Carrijo Coube, 2085 - Nucleo Res. Pres. Geisel, Bauru, SP 17033-360 Brazil
| | - Paula F. Polastri
- Laboratory of Information, Vision and Action (LIVIA), São Paulo State University (Unesp), Faculty of Sciences, Department of Physical Education, Graduate Program in Movement Sciences, Bauru, Brazil
| | - Paulo R. P. Santiago
- Biomechanics and Motor Control Laboratory (LaBioCoM), School of Physical Education and Sport of Ribeirão Preto (EEFERP), University of São Paulo (USP), Ribeirão Preto, Brazil
| | - Fabio A. Barbieri
- Human Movement Research Laboratory (MOVI-LAB), Faculty of Sciences, Graduate Program in Movement Sciences, Department of Physical Education, São Paulo State University (Unesp), Av. Eng. Luís Edmundo Carrijo Coube, 2085 - Nucleo Res. Pres. Geisel, Bauru, SP 17033-360 Brazil
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11
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Jacobsen NSJ, Blum S, Scanlon JEM, Witt K, Debener S. Mobile electroencephalography captures differences of walking over even and uneven terrain but not of single and dual-task gait. Front Sports Act Living 2022; 4:945341. [PMID: 36275441 PMCID: PMC9582531 DOI: 10.3389/fspor.2022.945341] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 09/13/2022] [Indexed: 11/09/2022] Open
Abstract
Walking on natural terrain while performing a dual-task, such as typing on a smartphone is a common behavior. Since dual-tasking and terrain change gait characteristics, it is of interest to understand how altered gait is reflected by changes in gait-associated neural signatures. A study was performed with 64-channel electroencephalography (EEG) of healthy volunteers, which was recorded while they walked over uneven and even terrain outdoors with and without performing a concurrent task (self-paced button pressing with both thumbs). Data from n = 19 participants (M = 24 years, 13 females) were analyzed regarding gait-phase related power modulations (GPM) and gait performance (stride time and stride time-variability). GPMs changed significantly with terrain, but not with the task. Descriptively, a greater beta power decrease following right-heel strikes was observed on uneven compared to even terrain. No evidence of an interaction was observed. Beta band power reduction following the initial contact of the right foot was more pronounced on uneven than on even terrain. Stride times were longer on uneven compared to even terrain and during dual- compared to single-task gait, but no significant interaction was observed. Stride time variability increased on uneven terrain compared to even terrain but not during single- compared to dual-tasking. The results reflect that as the terrain difficulty increases, the strides become slower and more irregular, whereas a secondary task slows stride duration only. Mobile EEG captures GPM differences linked to terrain changes, suggesting that the altered gait control demands and associated cortical processes can be identified. This and further studies may help to lay the foundation for protocols assessing the cognitive demand of natural gait on the motor system.
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Affiliation(s)
- Nadine Svenja Josée Jacobsen
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,*Correspondence: Nadine Svenja Josée Jacobsen
| | - Sarah Blum
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,Hörzentrum Oldenburg GmbH, Oldenburg, Germany,Cluster of Excellence Hearing4all, Oldenburg, Germany
| | - Joanna Elizabeth Mary Scanlon
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,Branch for Hearing, Speech and Audio Technology HSA, Fraunhofer Institute for Digital Media Technology IDMT, Oldenburg, Germany
| | - Karsten Witt
- Department of Neurology and Research Center Neurosensory Science, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Stefan Debener
- Neuropsychology Lab, Department of Psychology, School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany,Cluster of Excellence Hearing4all, Oldenburg, Germany
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12
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Studnicki A, Downey RJ, Ferris DP. Characterizing and Removing Artifacts Using Dual-Layer EEG during Table Tennis. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22155867. [PMID: 35957423 PMCID: PMC9371038 DOI: 10.3390/s22155867] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 07/28/2022] [Accepted: 08/02/2022] [Indexed: 05/27/2023]
Abstract
Researchers can improve the ecological validity of brain research by studying humans moving in real-world settings. Recent work shows that dual-layer EEG can improve the fidelity of electrocortical recordings during gait, but it is unclear whether these positive results extrapolate to non-locomotor paradigms. For our study, we recorded brain activity with dual-layer EEG while participants played table tennis, a whole-body, responsive sport that could help investigate visuomotor feedback, object interception, and performance monitoring. We characterized artifacts with time-frequency analyses and correlated scalp and reference noise data to determine how well different sensors captured artifacts. As expected, individual scalp channels correlated more with noise-matched channel time series than with head and body acceleration. We then compared artifact removal methods with and without the use of the dual-layer noise electrodes. Independent Component Analysis separated channels into components, and we counted the number of high-quality brain components based on the fit of a dipole model and using an automated labeling algorithm. We found that using noise electrodes for data processing provided cleaner brain components. These results advance technological approaches for recording high fidelity brain dynamics in human behaviors requiring whole body movement, which will be useful for brain science research.
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Zhao M, Bonassi G, Samogin J, Taberna GA, Pelosin E, Nieuwboer A, Avanzino L, Mantini D. Frequency-dependent modulation of neural oscillations across the gait cycle. Hum Brain Mapp 2022; 43:3404-3415. [PMID: 35384123 PMCID: PMC9248303 DOI: 10.1002/hbm.25856] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/08/2022] [Accepted: 03/22/2022] [Indexed: 12/14/2022] Open
Abstract
Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait‐related modulations of neural activity, we collected high‐density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event‐related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG‐based brain–body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders.
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Affiliation(s)
- Mingqi Zhao
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | - Gaia Bonassi
- S.C. Medicina Fisica e Riabilitazione Ospedaliera, Chiavari, Italy
| | - Jessica Samogin
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
| | | | - Elisa Pelosin
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal Child Health, University of Genova, Genova, Italy.,IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Alice Nieuwboer
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Laura Avanzino
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Genoa, Italy
| | - Dante Mantini
- Movement Control and Neuroplasticity Research Group, KU Leuven, Leuven, Belgium
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14
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Lehmann N, Kuhn YA, Keller M, Aye N, Herold F, Draganski B, Taube W, Taubert M. Brain Activation During Active Balancing and Its Behavioral Relevance in Younger and Older Adults: A Functional Near-Infrared Spectroscopy (fNIRS) Study. Front Aging Neurosci 2022; 14:828474. [PMID: 35418854 PMCID: PMC8997341 DOI: 10.3389/fnagi.2022.828474] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 02/28/2022] [Indexed: 12/26/2022] Open
Abstract
Age-related deterioration of balance control is widely regarded as an important phenomenon influencing quality of life and longevity, such that a more comprehensive understanding of the neural mechanisms underlying this process is warranted. Specifically, previous studies have reported that older adults typically show higher neural activity during balancing as compared to younger counterparts, but the implications of this finding on balance performance remain largely unclear. Using functional near-infrared spectroscopy (fNIRS), differences in the cortical control of balance between healthy younger (n = 27) and older (n = 35) adults were explored. More specifically, the association between cortical functional activity and balance performance across and within age groups was investigated. To this end, we measured hemodynamic responses (i.e., changes in oxygenated and deoxygenated hemoglobin) while participants balanced on an unstable device. As criterion variables for brain-behavior-correlations, we also assessed postural sway while standing on a free-swinging platform and while balancing on wobble boards with different levels of difficulty. We found that older compared to younger participants had higher activity in prefrontal and lower activity in postcentral regions. Subsequent robust regression analyses revealed that lower prefrontal brain activity was related to improved balance performance across age groups, indicating that higher activity of the prefrontal cortex during balancing reflects neural inefficiency. We also present evidence supporting that age serves as a moderator in the relationship between brain activity and balance, i.e., cortical hemodynamics generally appears to be a more important predictor of balance performance in the older than in the younger. Strikingly, we found that age differences in balance performance are mediated by balancing-induced activation of the superior frontal gyrus, thus suggesting that differential activation of this region reflects a mechanism involved in the aging process of the neural control of balance. Our study suggests that differences in functional brain activity between age groups are not a mere by-product of aging, but instead of direct behavioral relevance for balance performance. Potential implications of these findings in terms of early detection of fall-prone individuals and intervention strategies targeting balance and healthy aging are discussed.
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Affiliation(s)
- Nico Lehmann
- Department of Sport Science, Institute III, Faculty of Humanities, Otto von Guericke University, Magdeburg, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- *Correspondence: Nico Lehmann,
| | - Yves-Alain Kuhn
- Department of Neurosciences and Movement Science, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
| | - Martin Keller
- Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | - Norman Aye
- Department of Sport Science, Institute III, Faculty of Humanities, Otto von Guericke University, Magdeburg, Germany
| | - Fabian Herold
- Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, Potsdam, Germany
| | - Bogdan Draganski
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Wolfgang Taube
- Department of Neurosciences and Movement Science, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
| | - Marco Taubert
- Department of Sport Science, Institute III, Faculty of Humanities, Otto von Guericke University, Magdeburg, Germany
- Center for Behavioral Brain Science, Otto von Guericke University, Magdeburg, Germany
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15
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Gorjan D, Gramann K, De Pauw K, Marusic U. Removal of movement-induced EEG artifacts: current state of the art and guidelines. J Neural Eng 2022; 19. [PMID: 35147512 DOI: 10.1088/1741-2552/ac542c] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 02/08/2022] [Indexed: 11/12/2022]
Abstract
Electroencephalography (EEG) is a non-invasive technique used to record cortical neurons' electrical activity using electrodes placed on the scalp. It has become a promising avenue for research beyond state-of-the-art EEG research that is conducted under static conditions. EEG signals are always contaminated by artifacts and other physiological signals. Artifact contamination increases with the intensity of movement. In the last decade (since 2010), researchers have started to implement EEG measurements in dynamic setups to increase the overall ecological validity of the studies. Many different methods are used to remove non-brain activity from the EEG signal, and there are no clear guidelines on which method should be used in dynamic setups and for specific movement intensities. Currently, the most common methods for removing artifacts in movement studies are methods based on independent component analysis (ICA). However, the choice of method for artifact removal depends on the type and intensity of movement, which affects the characteristics of the artifacts and the EEG parameters of interest. When dealing with EEG under non-static conditions, special care must be taken already in the designing period of an experiment. Software and hardware solutions must be combined to achieve sufficient removal of unwanted signals from EEG measurements. We have provided recommendations for the use of each method depending on the intensity of the movement and highlighted the advantages and disadvantages of the methods. However, due to the current gap in the literature, further development and evaluation of methods for artifact removal in EEG data during locomotion is needed.
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Affiliation(s)
- Dasa Gorjan
- Science and Research Centre Koper, Garibaldijeva 1, Koper, 6000, SLOVENIA
| | - Klaus Gramann
- Technische Universität Berlin, Fasanenstr. 1, Berlin, Berlin, 10623, GERMANY
| | - Kevin De Pauw
- Vrije Universiteit Brussel, Pleinlaan 2, Brussel, Brussel, 1050, BELGIUM
| | - Uros Marusic
- Science and Research Centre Koper, Garibaldijeva 1, Koper, 6000, SLOVENIA
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16
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Chang M, Büchel D, Reinecke K, Lehmann T, Baumeister J. Ecological validity in exercise neuroscience research: A systematic investigation. Eur J Neurosci 2022; 55:487-509. [PMID: 34997653 DOI: 10.1111/ejn.15595] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 12/27/2021] [Accepted: 01/03/2022] [Indexed: 11/28/2022]
Abstract
The contribution of cortical processes to adaptive motor behaviour is of great interest in the field of exercise neuroscience. Next to established criteria of objectivity, reliability and validity, ecological validity refers to the concerns of whether measurements and behaviour in research settings are representative of the real world. Because exercise neuroscience investigations using mobile electroencephalography are oftentimes conducted in laboratory settings under controlled environments, methodological approaches may interfere with the idea of ecological validity. This review utilizes an original ecological validity tool to assess the degree of ecological validity in current exercise neuroscience research. A systematic literature search was conducted to identify articles investigating cortical dynamics during goal-directed sports movement. To assess ecological validity, five elements (environment, stimulus, response, body and mind) were assessed on a continuum of artificiality-naturality and simplicity-complexity. Forty-seven studies were included in the present review. Results indicate lowest average ratings for the element of environment. The elements stimulus, body and mind had mediocre ratings, and the element of response had the highest overall ratings. In terms of the type of sport, studies that assessed closed-skill indoor sports had the highest ratings, whereas closed-skill outdoor sports had the lowest overall rating. Our findings identify specific elements that are lacking in ecological validity and areas of improvement in current exercise neuroscience literature. Future studies may potentially increase ecological validity by moving from reductionist, artificial environments towards complex, natural environments and incorporating real-world sport elements such as adaptive responses and competition.
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Affiliation(s)
- Melissa Chang
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Daniel Büchel
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Kirsten Reinecke
- Institute of Sports Medicine, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Tim Lehmann
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
| | - Jochen Baumeister
- Exercise Science & Neuroscience Unit, Department of Exercise & Health, Paderborn University, Paderborn, Germany
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17
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Bibián C, Irastorza-Landa N, Schönauer M, Birbaumer N, López-Larraz E, Ramos-Murguialday A. On the Extraction of Purely Motor EEG Neural Correlates during an Upper Limb Visuomotor Task. Cereb Cortex 2021; 32:4243-4254. [PMID: 34969088 DOI: 10.1093/cercor/bhab479] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 11/11/2021] [Accepted: 11/12/2021] [Indexed: 11/14/2022] Open
Abstract
Deciphering and analyzing the neural correlates of different movements from the same limb using electroencephalography (EEG) would represent a notable breakthrough in the field of sensorimotor neurophysiology. Functional movements involve concurrent posture co-ordination and head and eye movements, which create electrical activity that affects EEG recordings. In this paper, we revisit the identification of brain signatures of different reaching movements using EEG and present, test, and validate a protocol to separate the effect of head and eye movements from a reaching task-related visuomotor brain activity. Ten healthy participants performed reaching movements under two different conditions: avoiding head and eye movements and moving with no constrains. Reaching movements can be identified from EEG with unconstrained eye and head movement, whereas the discriminability of the signals drops to chance level otherwise. These results show that neural patterns associated with different arm movements could only be extracted from EEG if the eye and head movements occurred concurrently with the task, polluting the recordings. Although these findings do not imply that brain correlates of reaching directions cannot be identified from EEG, they show the consequences that ignoring these events can have in any EEG study that includes a visuomotor task.
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Affiliation(s)
- Carlos Bibián
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen 72076, Germany
- International Max Planck Research School for Cognitive and Systems Neuroscience, Tübingen 72074, Germany
| | - Nerea Irastorza-Landa
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen 72076, Germany
- TECNALIA, Basque Research and Technology Alliance (BRTA), Neurotechnology Laboratory, San Sebastián 20009, Spain
| | - Monika Schönauer
- Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg 79085, Germany
| | - Niels Birbaumer
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen 72076, Germany
| | - Eduardo López-Larraz
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen 72076, Germany
- Bitbrain, Zaragoza 50008, Spain
| | - Ander Ramos-Murguialday
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen 72076, Germany
- TECNALIA, Basque Research and Technology Alliance (BRTA), Neurotechnology Laboratory, San Sebastián 20009, Spain
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18
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Song S, Nordin AD. Mobile Electroencephalography for Studying Neural Control of Human Locomotion. Front Hum Neurosci 2021; 15:749017. [PMID: 34858154 PMCID: PMC8631362 DOI: 10.3389/fnhum.2021.749017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 10/05/2021] [Indexed: 01/09/2023] Open
Abstract
Walking or running in real-world environments requires dynamic multisensory processing within the brain. Studying supraspinal neural pathways during human locomotion provides opportunities to better understand complex neural circuity that may become compromised due to aging, neurological disorder, or disease. Knowledge gained from studies examining human electrical brain dynamics during gait can also lay foundations for developing locomotor neurotechnologies for rehabilitation or human performance. Technical barriers have largely prohibited neuroimaging during gait, but the portability and precise temporal resolution of non-invasive electroencephalography (EEG) have expanded human neuromotor research into increasingly dynamic tasks. In this narrative mini-review, we provide a (1) brief introduction and overview of modern neuroimaging technologies and then identify considerations for (2) mobile EEG hardware, (3) and data processing, (4) including technical challenges and possible solutions. Finally, we summarize (5) knowledge gained from human locomotor control studies that have used mobile EEG, and (6) discuss future directions for real-world neuroimaging research.
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Affiliation(s)
- Seongmi Song
- Department of Health and Kinesiology, Texas A&M University, College Station, TX, United States
| | - Andrew D Nordin
- Department of Health and Kinesiology, Texas A&M University, College Station, TX, United States
- Department of Biomedical Engineering, Texas A&M University, College Station, TX, United States
- Texas A&M Institute for Neuroscience, College Station, TX, United States
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19
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Delaux A, de Saint Aubert JB, Ramanoël S, Bécu M, Gehrke L, Klug M, Chavarriaga R, Sahel JA, Gramann K, Arleo A. Mobile brain/body imaging of landmark-based navigation with high-density EEG. Eur J Neurosci 2021; 54:8256-8282. [PMID: 33738880 PMCID: PMC9291975 DOI: 10.1111/ejn.15190] [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: 05/29/2020] [Revised: 03/05/2021] [Accepted: 03/14/2021] [Indexed: 01/07/2023]
Abstract
Coupling behavioral measures and brain imaging in naturalistic, ecological conditions is key to comprehend the neural bases of spatial navigation. This highly integrative function encompasses sensorimotor, cognitive, and executive processes that jointly mediate active exploration and spatial learning. However, most neuroimaging approaches in humans are based on static, motion‐constrained paradigms and they do not account for all these processes, in particular multisensory integration. Following the Mobile Brain/Body Imaging approach, we aimed to explore the cortical correlates of landmark‐based navigation in actively behaving young adults, solving a Y‐maze task in immersive virtual reality. EEG analysis identified a set of brain areas matching state‐of‐the‐art brain imaging literature of landmark‐based navigation. Spatial behavior in mobile conditions additionally involved sensorimotor areas related to motor execution and proprioception usually overlooked in static fMRI paradigms. Expectedly, we located a cortical source in or near the posterior cingulate, in line with the engagement of the retrosplenial complex in spatial reorientation. Consistent with its role in visuo‐spatial processing and coding, we observed an alpha‐power desynchronization while participants gathered visual information. We also hypothesized behavior‐dependent modulations of the cortical signal during navigation. Despite finding few differences between the encoding and retrieval phases of the task, we identified transient time–frequency patterns attributed, for instance, to attentional demand, as reflected in the alpha/gamma range, or memory workload in the delta/theta range. We confirmed that combining mobile high‐density EEG and biometric measures can help unravel the brain structures and the neural modulations subtending ecological landmark‐based navigation.
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Affiliation(s)
- Alexandre Delaux
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | | | - Stephen Ramanoël
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Marcia Bécu
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Lukas Gehrke
- Institute of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany
| | - Marius Klug
- Institute of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany
| | - Ricardo Chavarriaga
- Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.,Zurich University of Applied Sciences, ZHAW Datalab, Winterthur, Switzerland
| | - José-Alain Sahel
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France.,CHNO des Quinze-Vingts, INSERM-DGOS CIC 1423, Paris, France.,Fondation Ophtalmologique Rothschild, Paris, France.,Department of Ophthalmology, The University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Klaus Gramann
- Institute of Psychology and Ergonomics, Technische Universität Berlin, Berlin, Germany
| | - Angelo Arleo
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
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20
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Cao L, Chen X, Haendel BF. Overground Walking Decreases Alpha Activity and Entrains Eye Movements in Humans. Front Hum Neurosci 2021; 14:561755. [PMID: 33414709 PMCID: PMC7782973 DOI: 10.3389/fnhum.2020.561755] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 12/02/2020] [Indexed: 01/25/2023] Open
Abstract
Experiments in animal models have shown that running increases neuronal activity in early visual areas in light as well as in darkness. This suggests that visual processing is influenced by locomotion independent of visual input. Combining mobile electroencephalography, motion- and eye-tracking, we investigated the influence of overground free walking on cortical alpha activity (~10 Hz) and eye movements in healthy humans. Alpha activity has been considered a valuable marker of inhibition of sensory processing and shown to negatively correlate with neuronal firing rates. We found that walking led to a decrease in alpha activity over occipital cortex compared to standing. This decrease was present during walking in darkness as well as during light. Importantly, eye movements could not explain the change in alpha activity. Nevertheless, we found that walking and eye related movements were linked. While the blink rate increased with increasing walking speed independent of light or darkness, saccade rate was only significantly linked to walking speed in the light. Pupil size, on the other hand, was larger during darkness than during light, but only showed a modulation by walking in darkness. Analyzing the effect of walking with respect to the stride cycle, we further found that blinks and saccades preferentially occurred during the double support phase of walking. Alpha power, as shown previously, was lower during the swing phase than during the double support phase. We however could exclude the possibility that the alpha modulation was introduced by a walking movement induced change in electrode impedance. Overall, our work indicates that the human visual system is influenced by the current locomotion state of the body. This influence affects eye movement pattern as well as neuronal activity in sensory areas and might form part of an implicit strategy to optimally extract sensory information during locomotion.
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Affiliation(s)
- Liyu Cao
- Department of Psychology (III), Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Xinyu Chen
- Department of Psychology (III), Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Barbara F Haendel
- Department of Psychology (III), Julius-Maximilians-Universität Würzburg, Würzburg, Germany
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21
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George KA, Damiano DL, Kim Y, Bulea TC. Mu Rhythm during Standing and Walking Is Altered in Children with Unilateral Cerebral Palsy Compared to Children with Typical Development. Dev Neurorehabil 2021; 24:8-17. [PMID: 32372674 DOI: 10.1080/17518423.2020.1756005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Background: Rehabilitation in cerebral palsy (CP) seeks to harness neuroplasticity to improve movement, including walking, yet cortical activation underlying gait is not well understood. Methods: We used electroencephalography (EEG) to compare motor related cortical activity, measured by mu rhythm, during quiet standing and treadmill walking in 10 children with unilateral CP and 10 age- and sex-matched children with typical development (TD). Peak mu band frequency, mu rhythm desynchronization (MRD), and gait related intra- and inter-hemispheric coherence were examined. Results: MRD during walking was observed bilaterally over motor cortex in both cohorts but peak mu band frequency showing MRD was significantly lower in CP compared to TD. Coherence during quiet standing between motor and frontal regions was significantly higher in the non-dominant compared to dominant hemisphere in CP with no hemispheric differences in TD. Conclusions: EEG-based measures should be further investigated as clinical biomarkers for atypical motor development and to assess rehabilitation effectiveness.
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Affiliation(s)
| | | | - Yushin Kim
- National Institutes of Health , Bethesda, MD, USA.,Cheongju University , Cheongju, Republic of Korea
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22
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Simar C, Cebolla AM, Chartier G, Petieau M, Bontempi G, Berthoz A, Cheron G. Hyperscanning EEG and Classification Based on Riemannian Geometry for Festive and Violent Mental State Discrimination. Front Neurosci 2020; 14:588357. [PMID: 33424535 PMCID: PMC7793677 DOI: 10.3389/fnins.2020.588357] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 11/04/2020] [Indexed: 12/14/2022] Open
Abstract
Interactions between two brains constitute the essence of social communication. Daily movements are commonly executed during social interactions and are determined by different mental states that may express different positive or negative behavioral intent. In this context, the effective recognition of festive or violent intent before the action execution remains crucial for survival. Here, we hypothesize that the EEG signals contain the distinctive features characterizing movement intent already expressed before movement execution and that such distinctive information can be identified by state-of-the-art classification algorithms based on Riemannian geometry. We demonstrated for the first time that a classifier based on covariance matrices and Riemannian geometry can effectively discriminate between neutral, festive, and violent mental states only on the basis of non-invasive EEG signals in both the actor and observer participants. These results pave the way for new electrophysiological discrimination of mental states based on non-invasive EEG recordings and cutting-edge machine learning techniques.
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Affiliation(s)
- Cédric Simar
- Machine Learning Group (MLG), Computer Science Department, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Ana-Maria Cebolla
- Laboratory of Neurophysiology and Movement Biomechanics, ULB Neuroscience Institute, Université libre de Bruxelles, Brussels, Belgium
| | - Gaëlle Chartier
- Centre Interdisciplinaire de Biologie, Collège de France-CNRS, Paris, France.,Department of Health, Medicine and Human Biology, Université Paris 13, Bobigny, France
| | - Mathieu Petieau
- Laboratory of Neurophysiology and Movement Biomechanics, ULB Neuroscience Institute, Université libre de Bruxelles, Brussels, Belgium
| | - Gianluca Bontempi
- Machine Learning Group (MLG), Computer Science Department, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Alain Berthoz
- Centre Interdisciplinaire de Biologie, Collège de France-CNRS, Paris, France
| | - Guy Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, ULB Neuroscience Institute, Université libre de Bruxelles, Brussels, Belgium.,Laboratory of Electrophysiology, Université de Mons-Hainaut, Mons, Belgium
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23
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Exploring the Limitations of Event-Related Potential Measures in Moving Subjects: Pilot Studies of Four Different Technical Modifications in Ergometer Rowing. SENSORS 2020; 20:s20195618. [PMID: 33019577 PMCID: PMC7583081 DOI: 10.3390/s20195618] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 09/22/2020] [Accepted: 09/29/2020] [Indexed: 12/31/2022]
Abstract
Measuring brain activity in moving subjects is of great importance for investigating human behavior in ecological settings. For this purpose, EEG measures are applicable; however, technical modifications are required to reduce the typical massive movement artefacts. Four different approaches to measure EEG/ERPs during rowing were tested: (i) a purpose-built head-mounted preamplifier, (ii) a laboratory system with active electrodes, and a wireless headset combined with (iii) passive or (iv) active electrodes. A standard visual oddball task revealed very similar (within subjects) visual evoked potentials for rowing and rest (without movement). The small intraindividual differences between rowing and rest, in comparison to the typically larger interindividual differences in the ERP waveforms, revealed that ERPs can be measured reliably even in an athletic movement such as rowing. On the other hand, the expected modulation of the motor-related activity by force output was largely affected by movement artefacts. Therefore, for a successful application of ERP measures in movement research, further developments to differentiate between movement-related neuronal activity and movement-related artefacts are required. However, activities with small magnitudes related to motor learning and motor control may be difficult to detect because they are superimposed by the very large motor potential, which increases with force output.
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24
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Jacobsen NSJ, Blum S, Witt K, Debener S. A walk in the park? Characterizing gait-related artifacts in mobile EEG recordings. Eur J Neurosci 2020; 54:8421-8440. [PMID: 32909315 DOI: 10.1111/ejn.14965] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 08/31/2020] [Accepted: 09/01/2020] [Indexed: 01/22/2023]
Abstract
Brain activity during natural walking outdoors can be captured using mobile electroencephalography (EEG). However, EEG recorded during gait is confounded with artifacts from various sources, possibly obstructing the interpretation of brain activity patterns. Currently, there is no consensus on how the amount of artifact present in these recordings should be quantified, or is there a systematic description of gait artifact properties. In the current study, we expand several features into a seven-dimensional footprint of gait-related artifacts, combining features of time, time-frequency, spatial, and source domains. EEG of N = 26 participants was recorded while standing and walking outdoors. Footprints of gait-related artifacts before and after two different artifact attenuation strategies (after artifact subspace reconstruction (ASR) and after subsequent independent component analysis [ICA]) were systematically different. We also evaluated topographies, morphologies, and signal-to-noise ratios (SNR) of button-press event-related potentials (ERP) before and after artifact handling, to confirm gait-artifact reduction specificity. Morphologies and SNR remained unchanged after artifact attenuation, whereas topographies improved in quality. Our results show that the footprint can provide a detailed assessment of gait-related artifacts and can be used to estimate the sensitivity of different artifact reduction strategies. Moreover, the analysis of button-press ERPs demonstrated its specificity, as processing did not only reduce gait-related artifacts but ERPs of interest remained largely unchanged. We conclude that the proposed footprint is well suited to characterize individual differences in gait-related artifact extent. In the future, it could be used to compare and optimize recording setups and processing pipelines comprehensively.
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Affiliation(s)
- Nadine Svenja Josée Jacobsen
- School of Medicine and Health Sciences, Department of Psychology, Neuropsychology Lab, University of Oldenburg, Oldenburg, Germany
| | - Sarah Blum
- School of Medicine and Health Sciences, Department of Psychology, Neuropsychology Lab, University of Oldenburg, Oldenburg, Germany
| | - Karsten Witt
- School of Medicine and Health Sciences, Department of Neurology and Research Center Neurosensory Science, University of Oldenburg, Oldenburg, Germany
| | - Stefan Debener
- School of Medicine and Health Sciences, Department of Psychology, Neuropsychology Lab, University of Oldenburg, Oldenburg, Germany
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25
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Leroy A, Cheron G. EEG dynamics and neural generators of psychological flow during one tightrope performance. Sci Rep 2020; 10:12449. [PMID: 32709919 PMCID: PMC7381607 DOI: 10.1038/s41598-020-69448-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 06/19/2020] [Indexed: 12/13/2022] Open
Abstract
Psychological “flow” emerges from a goal requiring action, and a match between skills and challenge. Using high-density electroencephalographic (EEG) recording, we quantified the neural generators characterizing psychological “flow” compared to a mindful “stress” state during a professional tightrope performance. Applying swLORETA based on self-reported mental states revealed the right superior temporal gyrus (BA38), right globus pallidus, and putamen as generators of delta, alpha, and beta oscillations, respectively, when comparing “flow” versus “stress”. Comparison of “stress” versus “flow” identified the middle temporal gyrus (BA39) as the delta generator, and the medial frontal gyrus (BA10) as the alpha and beta generator. These results support that “flow” emergence required transient hypo-frontality. Applying swLORETA on the motor command represented by the tibialis anterior EMG burst identified the ipsilateral cerebellum and contralateral sensorimotor cortex in association with on-line control exerted during both “flow” and “stress”, while the basal ganglia was identified only during “flow”.
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Affiliation(s)
- A Leroy
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium.,Haute Ecole Provinciale du Hainaut-Condorcet, Mons, Belgium
| | - G Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, Université Libre de Bruxelles, Brussels, Belgium. .,Laboratory of Electrophysiology, Université de Mons, Mons, Belgium.
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26
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Yokoyama H, Kaneko N, Masugi Y, Ogawa T, Watanabe K, Nakazawa K. Gait-phase-dependent and gait-phase-independent cortical activity across multiple regions involved in voluntary gait modifications in humans. Eur J Neurosci 2020; 54:8092-8105. [PMID: 32557966 DOI: 10.1111/ejn.14867] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 05/13/2020] [Accepted: 06/08/2020] [Indexed: 12/20/2022]
Abstract
Modification of ongoing walking movement to fit changes in external environments requires accurate voluntary control. In cats, the motor and posterior parietal cortices have crucial roles for precisely adjusting limb trajectory during walking. In human walking, however, it remains unclear which cortical information contributes to voluntary gait modification. In this study, we investigated cortical activity changes associated with visually guided precision stepping using electroencephalography source analysis. Our results demonstrated frequency- and gait-event-dependent changes in the cortical power spectrum elicited by voluntary gait modification. The main differences between normal walking and precision stepping were as follows: (a) the alpha, beta or gamma power decrease during the swing phases in the sensorimotor, anterior cingulate and parieto-occipital cortices, and (b) a power decrease in the theta, alpha and beta bands and increase in the gamma band throughout the gait cycle in the parieto-occipital cortex. Based on the previous knowledge of brain functions, the former change was considered to be related to execution and planning of leg movement, while the latter change was considered to be related to multisensory integration and motor awareness. Therefore, our results suggest that the gait modification is achieved by higher cortical involvements associated with different sensorimotor-related functions across multiple cortical regions including the sensorimotor, anterior cingulate and parieto-occipital cortices. The results imply the critical importance of the cortical contribution to voluntary modification in human locomotion. Further, the observed cortical information related to voluntary gait modification would contribute to developing volitional control systems of brain-machine interfaces for walking rehabilitation.
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Affiliation(s)
- Hikaru Yokoyama
- Rehabilitation Engineering Laboratory, Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.,Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan.,Japan Society for the Promotion of Science, Tokyo, Japan
| | - Naotsugu Kaneko
- Japan Society for the Promotion of Science, Tokyo, Japan.,Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Yohei Masugi
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan.,Institute of Sports Medicine and Science, Tokyo International University, Saitama, Japan
| | - Tetsuya Ogawa
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan.,Department of Clothing, Faculty of Human Sciences and Design, Japan Women's University, Tokyo, Japan
| | - Katsumi Watanabe
- Faculty of Science and Engineering, Waseda University, Tokyo, Japan.,Art & Design, University of New South Wales, Sydney, NSW, Australia.,Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada
| | - Kimitaka Nakazawa
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
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27
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New Directions in Exercise Prescription: Is There a Role for Brain-Derived Parameters Obtained by Functional Near-Infrared Spectroscopy? Brain Sci 2020; 10:brainsci10060342. [PMID: 32503207 PMCID: PMC7348779 DOI: 10.3390/brainsci10060342] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 05/25/2020] [Accepted: 05/29/2020] [Indexed: 02/06/2023] Open
Abstract
In the literature, it is well established that regular physical exercise is a powerful strategy to promote brain health and to improve cognitive performance. However, exact knowledge about which exercise prescription would be optimal in the setting of exercise–cognition science is lacking. While there is a strong theoretical rationale for using indicators of internal load (e.g., heart rate) in exercise prescription, the most suitable parameters have yet to be determined. In this perspective article, we discuss the role of brain-derived parameters (e.g., brain activity) as valuable indicators of internal load which can be beneficial for individualizing the exercise prescription in exercise–cognition research. Therefore, we focus on the application of functional near-infrared spectroscopy (fNIRS), since this neuroimaging modality provides specific advantages, making it well suited for monitoring cortical hemodynamics as a proxy of brain activity during physical exercise.
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28
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Berchicci M, Russo Y, Bianco V, Quinzi F, Rum L, Macaluso A, Committeri G, Vannozzi G, Di Russo F. Stepping forward, stepping backward: a movement-related cortical potential study unveils distinctive brain activities. Behav Brain Res 2020; 388:112663. [DOI: 10.1016/j.bbr.2020.112663] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 03/16/2020] [Accepted: 04/21/2020] [Indexed: 01/03/2023]
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29
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Iturrate I, Chavarriaga R, Millán JDR. General principles of machine learning for brain-computer interfacing. HANDBOOK OF CLINICAL NEUROLOGY 2020; 168:311-328. [PMID: 32164862 DOI: 10.1016/b978-0-444-63934-9.00023-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Brain-computer interfaces (BCIs) are systems that translate brain activity patterns into commands that can be executed by an artificial device. This enables the possibility of controlling devices such as a prosthetic arm or exoskeleton, a wheelchair, typewriting applications, or games directly by modulating our brain activity. For this purpose, BCI systems rely on signal processing and machine learning algorithms to decode the brain activity. This chapter provides an overview of the main steps required to do such a process, including signal preprocessing, feature extraction and selection, and decoding. Given the large amount of possible methods that can be used for these processes, a comprehensive review of them is beyond the scope of this chapter, and it is focused instead on the general principles that should be taken into account, as well as discussing good practices on how these methods should be applied and evaluated for proper design of reliable BCI systems.
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Affiliation(s)
- Iñaki Iturrate
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
| | - Ricardo Chavarriaga
- Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland; Institute of Applied Information Technology (InIT), Zurich University of Applied Sciences ZHAW, Winterthur, Switzerland.
| | - José Del R Millán
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, United States; Department of Neurology, The University of Texas at Austin, Austin, TX, United States
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30
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Nakagome S, Luu TP, He Y, Ravindran AS, Contreras-Vidal JL. An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding. Sci Rep 2020; 10:4372. [PMID: 32152333 PMCID: PMC7062700 DOI: 10.1038/s41598-020-60932-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 02/03/2020] [Indexed: 11/09/2022] Open
Abstract
Previous studies of Brain Computer Interfaces (BCI) based on scalp electroencephalography (EEG) have demonstrated the feasibility of decoding kinematics for lower limb movements during walking. In this computational study, we investigated offline decoding analysis with different models and conditions to assess how they influence the performance and stability of the decoder. Specifically, we conducted three computational decoding experiments that investigated decoding accuracy: (1) based on delta band time-domain features, (2) when downsampling data, (3) of different frequency band features. In each experiment, eight different decoder algorithms were compared including the current state-of-the-art. Different tap sizes (sample window sizes) were also evaluated for a real-time applicability assessment. A feature of importance analysis was conducted to ascertain which features were most relevant for decoding; moreover, the stability to perturbations was assessed to quantify the robustness of the methods. Results indicated that generally the Gated Recurrent Unit (GRU) and Quasi Recurrent Neural Network (QRNN) outperformed other methods in terms of decoding accuracy and stability. Previous state-of-the-art Unscented Kalman Filter (UKF) still outperformed other decoders when using smaller tap sizes, with fast convergence in performance, but occurred at a cost to noise vulnerability. Downsampling and the inclusion of other frequency band features yielded overall improvement in performance. The results suggest that neural network-based decoders with downsampling or a wide range of frequency band features could not only improve decoder performance but also robustness with applications for stable use of BCIs.
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Affiliation(s)
- Sho Nakagome
- Non-Invasive Brain Machine Interface Laboratory, Electrical and Computer Engineering Department, Houston, 77004, USA
| | - Trieu Phat Luu
- Non-Invasive Brain Machine Interface Laboratory, Electrical and Computer Engineering Department, Houston, 77004, USA
| | - Yongtian He
- Non-Invasive Brain Machine Interface Laboratory, Electrical and Computer Engineering Department, Houston, 77004, USA
| | - Akshay Sujatha Ravindran
- Non-Invasive Brain Machine Interface Laboratory, Electrical and Computer Engineering Department, Houston, 77004, USA
| | - Jose L Contreras-Vidal
- Non-Invasive Brain Machine Interface Laboratory, Electrical and Computer Engineering Department, Houston, 77004, USA.
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31
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Nordin AD, Hairston WD, Ferris DP. Faster Gait Speeds Reduce Alpha and Beta EEG Spectral Power From Human Sensorimotor Cortex. IEEE Trans Biomed Eng 2020; 67:842-853. [PMID: 31199248 PMCID: PMC7134343 DOI: 10.1109/tbme.2019.2921766] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Our aim was to determine if walking speed affected human sensorimotor electrocortical dynamics using mobile high-density electroencephalography (EEG). METHODS To overcome limitations associated with motion and muscle artifact contamination in EEG recordings, we compared solutions for artifact removal using novel dual-layer EEG electrodes and alternative signal processing methods. Dual-layer EEG simultaneously recorded human electrocortical signals and isolated motion artifacts using pairs of mechanically coupled and electrically independent electrodes. For electrical muscle activity removal, we incorporated electromyographic (EMG) recordings from the neck into our mobile EEG data processing pipeline. We compared artifact removal methods during treadmill walking at four speeds (0.5, 1.0, 1.5, and 2.0 m/s). RESULTS Left and right sensorimotor alpha and beta spectral power increased in contralateral limb single support and push off, and decreased during contralateral limb swing at each speed. At faster walking speeds, sensorimotor spectral power fluctuations were less pronounced across the gait cycle with reduced alpha and beta power (p < 0.05) compared to slower speeds. Isolated noise recordings and neck EMG spectral power fluctuations matched gait events and showed broadband spectral power increases at faster speeds. CONCLUSION AND SIGNIFICANCE Dual-layer EEG enabled us to isolate changes in human sensorimotor electrocortical dynamics across walking speeds. A comparison of signal processing approaches revealed similar intrastride cortical fluctuations when applying common (e.g., artifact subspace reconstruction) and novel artifact rejection methods. Dual-layer EEG, however, allowed us to document and rule out residual artifacts, which exposed sensorimotor spectral power changes across gait speeds.
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32
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Corticomuscular control of walking in older people and people with Parkinson's disease. Sci Rep 2020; 10:2980. [PMID: 32076045 PMCID: PMC7031238 DOI: 10.1038/s41598-020-59810-w] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 01/30/2020] [Indexed: 12/29/2022] Open
Abstract
Changes in human gait resulting from ageing or neurodegenerative diseases are multifactorial. Here we assess the effects of age and Parkinson’s disease (PD) on corticospinal activity recorded during treadmill and overground walking. Electroencephalography (EEG) from 10 electrodes and electromyography (EMG) from bilateral tibialis anterior muscles were acquired from 22 healthy young, 24 healthy older and 20 adults with PD. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence were assessed for EEG from bilateral sensorimotor cortices and EMG during the double-support phase of the gait cycle. CMC and EMG power at low beta frequencies (13–21 Hz) was significantly decreased in older and PD participants compared to young people, but there was no difference between older and PD groups. Older and PD participants spent shorter time in the swing phase than young individuals. These findings indicate age-related changes in the temporal coordination of gait. The decrease in low-beta CMC suggests reduced cortical input to spinal motor neurons in older people during the double-support phase. We also observed multiple changes in electrophysiological measures at low-gamma frequencies during treadmill compared to overground walking, indicating task-dependent differences in corticospinal locomotor control. These findings may be affected by artefacts and should be interpreted with caution.
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33
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Short MR, Damiano DL, Kim Y, Bulea TC. Children With Unilateral Cerebral Palsy Utilize More Cortical Resources for Similar Motor Output During Treadmill Gait. Front Hum Neurosci 2020; 14:36. [PMID: 32153376 PMCID: PMC7047842 DOI: 10.3389/fnhum.2020.00036] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 01/27/2020] [Indexed: 12/23/2022] Open
Abstract
Children with unilateral cerebral palsy (CP) walk independently although with an asymmetrical, more poorly coordinated pattern compared to their peers. While gait biomechanics in unilateral CP and their alteration from those without CP have been well documented, cortical mechanisms underlying gait remain inadequately understood. To the best of our knowledge, this is the first study utilizing electroencephalography (EEG) during treadmill gait in older children with and without CP. Lower limb surface electromyographic (EMG) data were collected and muscle synergy analyses performed to quantify motor output. Our primary goal was to evaluate the relationships between cortical and muscle activation within and across groups and hemispheres to provide novel insights into neural control of gait and how it may be disrupted by an early unilateral brain injury. Participants included 9 children with unilateral CP, mean age 16.0 ± 2.7 years, and 12 with typical development (TD), mean age 14.8 ± 3.0 years. EEG data were collected during a standing baseline and treadmill walking at self-selected speed. EMG of 16 lower limb muscles were also collected bilaterally and synchronized with EEG. No significant group differences were found in synergy number or structure across groups. Six cortical clusters were identified as having gait-related activation and all contained participants from both CP and TD groups; however, the percent of individuals per group appearing in different clusters varied. Notably, the cluster least represented in CP was the non-dominant motor region. Both groups showed mu-band ERD in the motor clusters during gait although sustained beta-band ERD was not evident in TD. The CP group showed greater cortical activation than TD during walking as measured by mu- and beta-ERD in the dominant and non-dominant motor and parietal regions and elevated low gamma-activity in the frontal and parietal areas, a unique finding in CP. CP showed greater bilateral motor EEG-EMG coherence in the gamma-band with the hallucis longus compared to TD. In summary, individuals with CP display increased cortical activation during gait possibly relating to differences in distal motor control of the more affected side. Strategies that iteratively reduce cortical activation while improving selective motor control are needed in CP.
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Affiliation(s)
- Matthew R. Short
- Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, United States
| | - Diane L. Damiano
- Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, United States
| | - Yushin Kim
- Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, United States
- Sports Health Rehabilitation, Cheongju University, Cheongju, South Korea
| | - Thomas C. Bulea
- Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, National Institutes of Health, Bethesda, MD, United States
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34
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Delval A, Bayot M, Defebvre L, Dujardin K. Cortical Oscillations during Gait: Wouldn't Walking be so Automatic? Brain Sci 2020; 10:E90. [PMID: 32050471 PMCID: PMC7071606 DOI: 10.3390/brainsci10020090] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 02/03/2020] [Accepted: 02/07/2020] [Indexed: 01/12/2023] Open
Abstract
Gait is often considered as an automatic movement but cortical control seems necessary to adapt gait pattern with environmental constraints. In order to study cortical activity during real locomotion, electroencephalography (EEG) appears to be particularly appropriate. It is now possible to record changes in cortical neural synchronization/desynchronization during gait. Studying gait initiation is also of particular interest because it implies motor and cognitive cortical control to adequately perform a step. Time-frequency analysis enables to study induced changes in EEG activity in different frequency bands. Such analysis reflects cortical activity implied in stabilized gait control but also in more challenging tasks (obstacle crossing, changes in speed, dual tasks…). These spectral patterns are directly influenced by the walking context but, when analyzing gait with a more demanding attentional task, cortical areas other than the sensorimotor cortex (prefrontal, posterior parietal cortex, etc.) seem specifically implied. While the muscular activity of legs and cortical activity are coupled, the precise role of the motor cortex to control the level of muscular contraction according to the gait task remains debated. The decoding of this brain activity is a necessary step to build valid brain-computer interfaces able to generate gait artificially.
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Affiliation(s)
- Arnaud Delval
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Clinical Neurophysiology Department, CHU Lille, 59000 Lille, France
| | - Madli Bayot
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Clinical Neurophysiology Department, CHU Lille, 59000 Lille, France
| | - Luc Defebvre
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Movement Disorders Department, CHU Lille, 59000 Lille, France
| | - Kathy Dujardin
- UMR-S1172, Lille Neuroscience & Cognition, Inserm, University Lille, 59000 Lille, France; (M.B.); (L.D.); (K.D.)
- Movement Disorders Department, CHU Lille, 59000 Lille, France
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35
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Clark DJ, Manini TM, Ferris DP, Hass CJ, Brumback BA, Cruz-Almeida Y, Pahor M, Reuter-Lorenz PA, Seidler RD. Multimodal Imaging of Brain Activity to Investigate Walking and Mobility Decline in Older Adults (Mind in Motion Study): Hypothesis, Theory, and Methods. Front Aging Neurosci 2020; 11:358. [PMID: 31969814 PMCID: PMC6960208 DOI: 10.3389/fnagi.2019.00358] [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: 08/06/2019] [Accepted: 12/09/2019] [Indexed: 12/25/2022] Open
Abstract
Age-related brain changes likely contribute to mobility impairments, but the specific mechanisms are poorly understood. Current brain measurement approaches (e.g., functional magnetic resonance imaging (fMRI), functional near infrared spectroscopy (fNIRS), PET) are limited by inability to measure activity from the whole brain during walking. The Mind in Motion Study will use cutting edge, mobile, high-density electroencephalography (EEG). This approach relies upon innovative hardware and software to deliver three-dimensional localization of active cortical and subcortical regions with good spatial and temporal resolution during walking. Our overarching objective is to determine age-related changes in the central neural control of walking and correlate these findings with a comprehensive set of mobility outcomes (clinic-based, complex walking, and community mobility measures). Our hypothesis is that age-related walking deficits are explained in part by the Compensation Related Utilization of Neural Circuits Hypothesis (CRUNCH). CRUNCH is a well-supported model that describes the over-recruitment of brain regions exhibited by older adults in comparison to young adults, even at low levels of task complexity. CRUNCH also describes the limited brain reserve resources available with aging. These factors cause older adults to quickly reach a ceiling in brain resources when performing tasks of increasing complexity, leading to poor performance. Two hundred older adults and twenty young adults will undergo extensive baseline neuroimaging and walking assessments. Older adults will subsequently be followed for up to 3 years. Aim 1 will evaluate whether brain activity during actual walking explains mobility decline. Cross sectional and longitudinal designs will be used to study whether poorer walking performance and steeper trajectories of decline are associated with CRUNCH indices. Aim 2 is to harmonize high-density EEG during walking with fNIRS (during actual and imagined walking) and fMRI (during imagined walking). This will allow integration of CRUNCH-related hallmarks of brain activity across neuroimaging modalities, which is expected to lead to more widespread application of study findings. Aim 3 will study central and peripheral mechanisms (e.g., cerebral blood flow, brain regional volumes, and connectivity, sensory function) to explain differences in CRUNCH indices during walking. Research performed in the Mind in Motion Study will comprehensively characterize the aging brain during walking for developing new intervention targets.
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Affiliation(s)
- David J Clark
- Department of Aging and Geriatric Research, University of Florida, Gainesville, FL, United States.,Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, FL, United States
| | - Todd M Manini
- Department of Aging and Geriatric Research, University of Florida, Gainesville, FL, United States
| | - Daniel P Ferris
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Chris J Hass
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Babette A Brumback
- Department of Biostatistics, University of Florida, Gainesville, FL, United States
| | - Yenisel Cruz-Almeida
- Pain Research and Intervention Center of Excellence, University of Florida, Gainesville, FL, United States
| | - Marco Pahor
- Department of Aging and Geriatric Research, University of Florida, Gainesville, FL, United States
| | | | - Rachael D Seidler
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
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36
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Weersink JB, Gefferie SR, van Laar T, Maurits NM, de Jong BM. Pre-Movement Cortico-Muscular Dynamics Underlying Improved Parkinson Gait Initiation after Instructed Arm Swing. JOURNAL OF PARKINSON'S DISEASE 2020; 10:1675-1693. [PMID: 32773398 PMCID: PMC7683047 DOI: 10.3233/jpd-202112] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 07/12/2020] [Indexed: 11/15/2022]
Abstract
BACKGROUND The supplementary motor area (SMA) is implicated in both motor initiation and stereotypic multi-limb movements such as walking with arm swing. Gait in Parkinson's disease exhibits starting difficulties and reduced arm swing, consistent with reduced SMA activity. OBJECTIVE We tested whether enhanced arm swing could improve Parkinson gait initiation and assessed whether increased SMA activity during preparation might facilitate such improvement. METHODS Effects of instructed arm swing on cortical activity, muscle activity and kinematics were assessed by ambulant EEG, EMG, accelerometers and video in 17 Parkinson patients and 19 controls. At baseline, all participants repeatedly started walking after a simple auditory cue. Next, patients started walking at this cue, which now meant starting with enhanced arm swing. EEG changes over the putative SMA and leg motor cortex were assessed by event related spectral perturbation (ERSP) analysis of recordings at Fz and Cz. RESULTS Over the putative SMA location (Fz), natural PD gait initiation showed enhanced alpha/theta synchronization around the auditory cue, and reduced alpha/beta desynchronization during gait preparation and movement onset, compared to controls. Leg muscle activity in patients was reduced during preparation and movement onset, while the latter was delayed compared to controls. When starting with enhanced arm swing, these group differences virtually disappeared. CONCLUSION Instructed arm swing improves Parkinson gait initiation. ERSP normalization around the cue indicates that the attributed information may serve as a semi-internal cue, recruiting an internalized motor program to overcome initiation difficulties.
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Affiliation(s)
- Joyce B. Weersink
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Silvano R. Gefferie
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Teus van Laar
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Natasha M. Maurits
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Bauke M. de Jong
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Barry DN, Tierney TM, Holmes N, Boto E, Roberts G, Leggett J, Bowtell R, Brookes MJ, Barnes GR, Maguire EA. Imaging the human hippocampus with optically-pumped magnetoencephalography. Neuroimage 2019; 203:116192. [PMID: 31521823 PMCID: PMC6854457 DOI: 10.1016/j.neuroimage.2019.116192] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 09/07/2019] [Accepted: 09/12/2019] [Indexed: 12/17/2022] Open
Abstract
Optically-pumped (OP) magnetometers allow magnetoencephalography (MEG) to be performed while a participant's head is unconstrained. To fully leverage this new technology, and in particular its capacity for mobility, the activity of deep brain structures which facilitate explorative behaviours such as navigation, must be detectable using OP-MEG. One such crucial brain region is the hippocampus. Here we had three healthy adult participants perform a hippocampal-dependent task - the imagination of novel scene imagery - while being scanned using OP-MEG. A conjunction analysis across these three participants revealed a significant change in theta power in the medial temporal lobe. The peak of this activated cluster was located in the anterior hippocampus. We repeated the experiment with the same participants in a conventional SQUID-MEG scanner and found similar engagement of the medial temporal lobe, also with a peak in the anterior hippocampus. These OP-MEG findings indicate exciting new opportunities for investigating the neural correlates of a range of crucial cognitive functions in naturalistic contexts including spatial navigation, episodic memory and social interactions.
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Affiliation(s)
- Daniel N Barry
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Elena Boto
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Gillian Roberts
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - James Leggett
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Eleanor A Maguire
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.
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Wagner J, Martinez-Cancino R, Delorme A, Makeig S, Solis-Escalante T, Neuper C, Mueller-Putz G. High-density EEG mobile brain/body imaging data recorded during a challenging auditory gait pacing task. Sci Data 2019; 6:211. [PMID: 31624252 PMCID: PMC6797727 DOI: 10.1038/s41597-019-0223-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 09/06/2019] [Indexed: 02/07/2023] Open
Abstract
In this report we present a mobile brain/body imaging (MoBI) dataset that allows study of source-resolved cortical dynamics supporting coordinated gait movements in a rhythmic auditory cueing paradigm. Use of an auditory pacing stimulus stream has been recommended to identify deficits and treat gait impairments in neurologic populations. Here, the rhythmic cueing paradigm required healthy young participants to walk on a treadmill (constant speed) while attempting to maintain step synchrony with an auditory pacing stream and to adapt their step length and rate to unanticipated shifts in tempo of the pacing stimuli (e.g., sudden shifts to a faster or slower tempo). High-density electroencephalography (EEG, 108 channels), surface electromyography (EMG, bilateral tibialis anterior), pressure sensors on the heel (to register timing of heel strikes), and goniometers (knee, hip, and ankle joint angles) were concurrently recorded in 20 participants. The data is provided in the Brain Imaging Data Structure (BIDS) format to promote data sharing and reuse, and allow the inclusion of the data into fully automated data analysis workflows.
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Affiliation(s)
- Johanna Wagner
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA.
- Laboratory for Brain Computer Interfaces, Institute of Neural Engineering, Graz University of Technology, Graz, Austria.
| | - Ramon Martinez-Cancino
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA
- Electric and Computer Engineering Department, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
| | - Arnaud Delorme
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA
| | - Scott Makeig
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA, USA
| | - Teodoro Solis-Escalante
- Laboratory for Brain Computer Interfaces, Institute of Neural Engineering, Graz University of Technology, Graz, Austria
- Department of Rehabilitation, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christa Neuper
- Laboratory for Brain Computer Interfaces, Institute of Neural Engineering, Graz University of Technology, Graz, Austria
- Department of Psychology, University of Graz, Graz, Austria
| | - Gernot Mueller-Putz
- Laboratory for Brain Computer Interfaces, Institute of Neural Engineering, Graz University of Technology, Graz, Austria
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McCrimmon CM, Wang PT, Heydari P, Nguyen A, Shaw SJ, Gong H, Chui LA, Liu CY, Nenadic Z, Do AH. Electrocorticographic Encoding of Human Gait in the Leg Primary Motor Cortex. ACTA ACUST UNITED AC 2019; 28:2752-2762. [PMID: 28981644 DOI: 10.1093/cercor/bhx155] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Indexed: 11/14/2022]
Abstract
While prior noninvasive (e.g., electroencephalographic) studies suggest that the human primary motor cortex (M1) is active during gait processes, the limitations of noninvasive recordings make it impossible to determine whether M1 is involved in high-level motor control (e.g., obstacle avoidance, walking speed), low-level motor control (e.g., coordinated muscle activation), or only nonmotor processes (e.g., integrating/relaying sensory information). This study represents the first invasive electroneurophysiological characterization of the human leg M1 during walking. Two subjects with an electrocorticographic grid over the interhemispheric M1 area were recruited. Both exhibited generalized γ-band (40-200 Hz) synchronization across M1 during treadmill walking, as well as periodic γ-band changes within each stride (across multiple walking speeds). Additionally, these changes appeared to be of motor, rather than sensory, origin. However, M1 activity during walking shared few features with M1 activity during individual leg muscle movements, and was not highly correlated with lower limb trajectories on a single channel basis. These findings suggest that M1 primarily encodes high-level gait motor control (i.e., walking duration and speed) instead of the low-level patterns of leg muscle activation or movement trajectories. Therefore, M1 likely interacts with subcortical/spinal networks, which are responsible for low-level motor control, to produce normal human walking.
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Affiliation(s)
- Colin M McCrimmon
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
| | - Po T Wang
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA
| | - Payam Heydari
- Department of Electrical Engineering and Computer Science, University of California Irvine, Irvine, CA, USA
| | - Angelica Nguyen
- Electrophysiology Lab, Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA
| | - Susan J Shaw
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA.,Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Hui Gong
- Department of Neurology, Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA.,Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Luis A Chui
- Department of Neurology, University of California Irvine, Irvine, CA, USA
| | - Charles Y Liu
- Department of Neurosurgery, Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA.,Center for Neurorestoration, University of Southern California, Los Angeles, CA, USA.,Department of Neurosurgery, University of Southern California, Los Angeles, CA, USA
| | - Zoran Nenadic
- Department of Biomedical Engineering, University of California Irvine, Irvine, CA, USA.,Department of Electrical Engineering and Computer Science, University of California Irvine, Irvine, CA, USA
| | - An H Do
- Department of Neurology, University of California Irvine, Irvine, CA, USA
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A Comparison of Mental Workload in Individuals with Transtibial and Transfemoral Lower Limb Loss during Dual-Task Walking under Varying Demand. J Int Neuropsychol Soc 2019; 25:985-997. [PMID: 31462338 DOI: 10.1017/s1355617719000602] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
OBJECTIVES This study aimed to evaluate the influence of lower limb loss (LL) on mental workload by assessing neurocognitive measures in individuals with unilateral transtibial (TT) versus those with transfemoral (TF) LL while dual-task walking under varying cognitive demand. METHODS Electroencephalography (EEG) was recorded as participants performed a task of varying cognitive demand while being seated or walking (i.e., varying physical demand). RESULTS The findings revealed both groups of participants (TT LL vs. TF LL) exhibited a similar EEG theta synchrony response as either the cognitive or the physical demand increased. Also, while individuals with TT LL maintained similar performance on the cognitive task during seated and walking conditions, those with TF LL exhibited performance decrements (slower response times) on the cognitive task during the walking in comparison to the seated conditions. Furthermore, those with TF LL neither exhibited regional differences in EEG low-alpha power while walking, nor EEG high-alpha desynchrony as a function of cognitive task difficulty while walking. This lack of alpha modulation coincided with no elevation of theta/alpha ratio power as a function of cognitive task difficulty in the TF LL group. CONCLUSIONS This work suggests that both groups share some common but also different neurocognitive features during dual-task walking. Although all participants were able to recruit neural mechanisms critical for the maintenance of cognitive-motor performance under elevated cognitive or physical demands, the observed differences indicate that walking with a prosthesis, while concurrently performing a cognitive task, imposes additional cognitive demand in individuals with more proximal levels of amputation.
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Cerebral cortical networking for mental workload assessment under various demands during dual-task walking. Exp Brain Res 2019; 237:2279-2295. [DOI: 10.1007/s00221-019-05550-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 04/24/2019] [Indexed: 01/22/2023]
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Neale C, Aspinall P, Roe J, Tilley S, Mavros P, Cinderby S, Coyne R, Thin N, Ward Thompson C. The impact of walking in different urban environments on brain activity in older people. ACTA ACUST UNITED AC 2019. [DOI: 10.1080/23748834.2019.1619893] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Affiliation(s)
- Chris Neale
- Stockholm Environment Institute, Environment Department, University of York, York, England
- Frank Batten School of Leadership and Public Policy, University of Virginia, Charlottesville, VA, USA
| | - Peter Aspinall
- School of Built Environment, Heriot-Watt University, Edinburgh, Scotland
| | - Jenny Roe
- Center for Design and Health, School of Architecture, University of Virginia, Charlottesville, VA, USA
| | - Sara Tilley
- OPENspace Research Centre, Edinburgh College of Art, University of Edinburgh, Edinburgh, Scotland
| | - Panagiotis Mavros
- Future Cities Laboratory, Singapore-ETH Centre, ETH, Zürich, Singapore
| | - Steve Cinderby
- Stockholm Environment Institute, Environment Department, University of York, York, England
| | - Richard Coyne
- Edinburgh School of Architecture and Landscape Architecture, University of Edinburgh, Edinburgh, Scotland
| | - Neil Thin
- School of Social and Political Science, University of Edinburgh, Edinburgh, Scotland
| | - Catharine Ward Thompson
- OPENspace Research Centre, Edinburgh College of Art, University of Edinburgh, Edinburgh, Scotland
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Wagner J, Martínez-Cancino R, Makeig S. Trial-by-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation. Neuroimage 2019; 199:691-703. [PMID: 31181332 DOI: 10.1016/j.neuroimage.2019.06.018] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 06/04/2019] [Accepted: 06/06/2019] [Indexed: 12/12/2022] Open
Abstract
A growing body of evidence indicates a pivotal role of cognition and in particular executive function in gait control and fall prevention. In a recent gait study using electroencephalographic (EEG) imaging, we provided direct proof for cortical top-down inhibitory control in step adaptation. A crucial part of motor inhibition is recognizing stimuli that signal the need to inhibit or adjust motor actions such as steps during walking. One of the EEG signatures of performance monitoring in response to events signaling the need to adjust motor responses, are error-related potential (error-ERP) features. To examine whether error-ERP features may index executive control during gait adaptation, we analyzed high-density (108-channel) EEG data from an auditory gait pacing study. Participants (N = 18) walking on a steadily moving treadmill were asked to step in time to an auditory cue tone sequence, and then to quickly adapt their step length and rate, to regain step-cue synchrony following occasional unexpected shifts in the pacing cue train to a faster or slower cue tempo. Decomposition of the continuous EEG data by independent component analysis revealed a negative deflection in the source-resolved event-related potential (ERP) time locked to 'late' cue tones marking a shift to a slower cue tempo. This vertex-negative ERP feature, localized primarily to posterior medial frontal cortex (pMFC) and peaking 250 ms after the onset of the tempo-shift cue, we here refer to as the step-cue delay negativity (SDN). SDN source, timing, and polarity resemble other error-related ERP features, e.g., the Error-Related Negativity (ERN) and Feedback-Related Negativity (FRN) in (seated) button press response tasks. In single trials, SDN amplitude varied with the magnitude of the cue latency deviation (the time interval between the expected and actual cue onsets). Regression analysis also identified linear coupling between SDN amplitude and the subsequent speed of gait tempo adaptation (as measured by the increase in length of the ensuing adaptation step). The SDN in this paradigm thus seems both to index the perceived need for and the subsequent magnitude of the immediate gait adjustment, consistent with performance-monitoring models. Future research might investigate relationships of these control processes to the impairment of gait adjustment in motor disorders and cognitive decline, for example to develop a biomarker for fall risk prediction in early-stage Parkinson's.
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Affiliation(s)
- Johanna Wagner
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0559, USA.
| | - Ramón Martínez-Cancino
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0559, USA
| | - Scott Makeig
- Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0559, USA
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Rahman M, Karwowski W, Fafrowicz M, Hancock PA. Neuroergonomics Applications of Electroencephalography in Physical Activities: A Systematic Review. Front Hum Neurosci 2019; 13:182. [PMID: 31214002 PMCID: PMC6558147 DOI: 10.3389/fnhum.2019.00182] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 05/20/2019] [Indexed: 11/13/2022] Open
Abstract
Recent years have seen increased interest in neuroergonomics, which investigates the brain activities of people engaged in diverse physical and cognitive activities at work and in everyday life. The present work extends upon prior assessments of the state of this art. However, here we narrow our focus specifically to studies that use electroencephalography (EEG) to measure brain activity, correlates, and effects during physical activity. The review uses systematically selected, openly published works derived from a guided search through peer-reviewed journals and conference proceedings. Identified studies were then categorized by the type of physical activity and evaluated considering methodological and chronological aspects via statistical and content-based analyses. From the identified works (n = 110), a specific number (n = 38) focused on less mobile muscular activities, while an additional group (n = 22) featured both physical and cognitive tasks. The remainder (n = 50) investigated various physical exercises and sporting activities and thus were here identified as a miscellaneous grouping. Most of the physical activities were isometric exertions, moving parts of upper and lower limbs, or walking and cycling. These primary categories were sub-categorized based on movement patterns, the use of the event-related potentials (ERP) technique, the use of recording methods along with EEG and considering mental effects. Further information on subjects' gender, EEG recording devices, data processing, and artifact correction methods and citations was extracted. Due to the heterogeneous nature of the findings from various studies, statistical analyses were not performed. These were thus included in a descriptive fashion. Finally, contemporary research gaps were pointed out, and future research prospects to address those gaps were discussed.
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Affiliation(s)
- Mahjabeen Rahman
- Computational Neuroergonomics Laboratory, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, United States
| | - Waldemar Karwowski
- Computational Neuroergonomics Laboratory, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, United States
| | - Magdalena Fafrowicz
- Department of Cognitive Neuroscience and Neuroergonomics, Neurobiology Department, The Maloploska Center of Biotechnology, Jagiellonian University in Krakow, Krakow, Poland
| | - Peter A Hancock
- Department of Psychology, University of Central Florida, Orlando, FL, United States
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Corticospinal control of normal and visually guided gait in healthy older and younger adults. Neurobiol Aging 2019; 78:29-41. [DOI: 10.1016/j.neurobiolaging.2019.02.005] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Revised: 01/25/2019] [Accepted: 02/02/2019] [Indexed: 01/18/2023]
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Weersink JB, Maurits NM, de Jong BM. EEG time-frequency analysis provides arguments for arm swing support in human gait control. Gait Posture 2019; 70:71-78. [PMID: 30826690 DOI: 10.1016/j.gaitpost.2019.02.017] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Revised: 01/31/2019] [Accepted: 02/22/2019] [Indexed: 02/02/2023]
Abstract
BACKGROUND Human gait benefits from arm swing, which requires four-limb co-ordination. The Supplementary Motor Area (SMA) is involved in multi-limb coordination. With its location anterior to the leg motor cortex and the pattern of its connections, this suggests a distinct role in gait control. RESEARCH QUESTION Is the SMA functionally implicated in gait-related arm swing? METHODS Ambulant electroencephalography (EEG) was employed during walking with and without arm swing in twenty healthy subjects (mean age: 64.9yrs, SD 7.2). Power changes across the EEG frequency spectrum were assessed by Event Related Spectral Perturbation (ERSP) analysis over both the putative SMA at electrode position Fz and additional sensorimotor regions. RESULTS During walking with arm swing, midline electrodes Fz and Cz showed a step-related pattern of Event Related Desynchronization (ERD) followed by Event Related Synchronization (ERS). Walking without arm swing was associated with significant ERD-ERS power reduction in the high-beta/low-gamma band over Fz and a power increase over Cz. Electrodes C3 and C4 revealed a pattern of ERD during contralateral- and ERS during ipsilateral leg swing. This ERD power decreased in gait without arm swing (low-frequency band). The ERSP pattern during walking with arm swing was similar at CP1 and CP2: ERD was seen during double support and the initial swing phase of the right leg, while a strong ERS emerged during the second half of the left leg's swing. Walking without arm swing showed a significant power reduction of this ERD-ERS pattern over CP2, while over CP1, ERS during left leg's swing turned into ERD. CONCLUSION The relation between arm swing in walking and a step-related ERD-ERS pattern in the high-beta/low-gamma band over the putative SMA, points at an SMA contribution to integrated cyclic anti-phase movements of upper- and lower limbs. This supports a cortical underpinning of arm swing support in gait control.
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Affiliation(s)
- Joyce B Weersink
- Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, POB 30.001, Groningen, the Netherlands
| | - Natasha M Maurits
- Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, POB 30.001, Groningen, the Netherlands
| | - Bauke M de Jong
- Department of Neurology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, POB 30.001, Groningen, the Netherlands.
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Vaidya M, Flint RD, Wang PT, Barry A, Li Y, Ghassemi M, Tomic G, Yao J, Carmona C, Mugler EM, Gallick S, Driver S, Brkic N, Ripley D, Liu C, Kamper D, Do AH, Slutzky MW. Hemicraniectomy in Traumatic Brain Injury: A Noninvasive Platform to Investigate High Gamma Activity for Brain Machine Interfaces. IEEE Trans Neural Syst Rehabil Eng 2019; 27:1467-1472. [PMID: 31021800 DOI: 10.1109/tnsre.2019.2912298] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Brain-machine interfaces (BMIs) translate brain signals into control signals for an external device, such as a computer cursor or robotic limb. These signals can be obtained either noninvasively or invasively. Invasive recordings, using electrocorticography (ECoG) or intracortical microelectrodes, provide higher bandwidth and more informative signals. Rehabilitative BMIs, which aim to drive plasticity in the brain to enhance recovery after brain injury, have almost exclusively used non-invasive recordings, such electroencephalography (EEG) or magnetoencephalography (MEG), which have limited bandwidth and information content. Invasive recordings provide more information and spatiotemporal resolution, but do incur risk, and thus are not usually investigated in people with stroke or traumatic brain injury (TBI). Here, in this paper, we describe a new BMI paradigm to investigate the use of higher frequency signals in brain-injured subjects without incurring significant risk. We recorded EEG in TBI subjects who required hemicraniectomies (removal of a part of the skull). EEG over the hemicraniectomy (hEEG) contained substantial information in the high gamma frequency range (65-115 Hz). Using this information, we decoded continuous finger flexion force with moderate to high accuracy (variance accounted for 0.06 to 0.52), which at best approaches that using epidural signals. These results indicate that people with hemicraniectomies can provide a useful resource for developing BMI therapies for the treatment of brain injury.
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Yokoyama H, Kaneko N, Ogawa T, Kawashima N, Watanabe K, Nakazawa K. Cortical Correlates of Locomotor Muscle Synergy Activation in Humans: An Electroencephalographic Decoding Study. iScience 2019; 15:623-639. [PMID: 31054838 PMCID: PMC6547791 DOI: 10.1016/j.isci.2019.04.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Revised: 02/09/2019] [Accepted: 04/04/2019] [Indexed: 01/17/2023] Open
Abstract
Muscular control during walking is believed to be simplified by the coactivation of muscles called muscle synergies. Although significant corticomuscular connectivity during walking has been reported, the level at which the cortical activity is involved in muscle activity (muscle synergy or individual muscle level) remains unclear. Here we examined cortical correlates of muscle activation during walking by brain decoding of activation of muscle synergies and individual muscles from electroencephalographic signals. We demonstrated that the activation of locomotor muscle synergies was decoded from slow cortical waves. In addition, the decoding accuracy for muscle synergies was greater than that for individual muscles and the decoding of individual muscle activation was based on muscle-synergy-related cortical information. These results indicate the cortical correlates of locomotor muscle synergy activation. These findings expand our understanding of the relationships between brain and locomotor muscle synergies and could accelerate the development of effective brain-machine interfaces for walking rehabilitation.
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Affiliation(s)
- Hikaru Yokoyama
- Department of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Koganei-shi, Tokyo 184-8588, Japan; Japan Society for the Promotion of Science, Chiyoda-ku, Tokyo 102-0083, Japan
| | - Naotsugu Kaneko
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Tetsuya Ogawa
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan
| | - Noritaka Kawashima
- Department of Rehabilitation for the Movement Functions, Research Institute of National Rehabilitation Center for the Disabled, Tokorozawa-shi, Saitama 359-0042, Japan
| | - Katsumi Watanabe
- Faculty of Science and Engineering, Waseda University, Shinjuku-ku Tokyo 169-8555, Japan; Art & Design, University of New South Wales, Sydney, NSW 2021, Australia; Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Kimitaka Nakazawa
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan.
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Cognitive performance and brain dynamics during walking with a novel bionic foot: A pilot study. PLoS One 2019; 14:e0214711. [PMID: 30943265 PMCID: PMC6447229 DOI: 10.1371/journal.pone.0214711] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 03/19/2019] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES The objectives are to determine neural dynamics during gait using electro-encephalography and source localization, and to investigate the attentional demand during walking in able-bodied individuals, and individuals with an amputation. MATERIALS & METHODS Six able-bodied individuals conducted one experimental trial, and 6 unilateral transtibial and 6 unilateral transfemoral amputees performed 2 experimental trials; the first with the prosthesis currently used by the subjects and the second with a novel powered transtibial prosthesis, i.e. the Ankle Mimicking Prosthetic foot 4.0. Each experimental trial comprised 2 walking tasks; 6 and 2 minutes treadmill walking at normal speed interspersed by 5 minutes of rest. During 6 minutes walking the Sustained Attention to Response (go-no go) Task, which measures reaction time and accuracy, was performed. Electro-encephalographic data were gathered when subjects walked 2 minutes. Motor-related cortical potentials and brain source activity during gait were examined. Normality and (non-) parametric tests were conducted (p<0.05). RESULTS AND DISCUSSION In contrast to transtibial amputees, transfemoral amputees required more attentional demands during walking with Ankle Mimicking Prosthetic foot 4.0 compared to the current passive prosthetic device and able-bodied individuals (reaction time and accuracy: p≤0.028). Since risk of falling is associated with altered attentional demands, propulsive forces of the novel device need to be better controlled for transfemoral amputees. No motor-related cortical potentials at Cz were observed in transfemoral amputees walking with the novel prosthesis, whereas motor-related cortical potentials between transtibial amputees and able-bodied individuals during walking at normal speed did not differ. The first positive electro-physiological peak deflection appeared during toe-off phase and showed higher activity within the underlying brain sources in transtibial amputees walking with Ankle Mimicking Prosthetic foot 4.0 compared to able-bodied individuals. The required higher neural input to accomplish the same physical activity compared to able-bodied individuals is possibly due to the limited acclimation period to the novel device and consequently increased afferent sensory feedback for postural control.
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Nordin AD, Hairston WD, Ferris DP. Human electrocortical dynamics while stepping over obstacles. Sci Rep 2019; 9:4693. [PMID: 30886202 PMCID: PMC6423113 DOI: 10.1038/s41598-019-41131-2] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 02/28/2019] [Indexed: 12/21/2022] Open
Abstract
To better understand human brain dynamics during visually guided locomotion, we developed a method of removing motion artifacts from mobile electroencephalography (EEG) and studied human subjects walking and running over obstacles on a treadmill. We constructed a novel dual-layer EEG electrode system to isolate electrocortical signals, and then validated the system using an electrical head phantom and robotic motion platform. We collected data from young healthy subjects walking and running on a treadmill while they encountered unexpected obstacles to step over. Supplementary motor area and premotor cortex had spectral power increases within ~200 ms after object appearance in delta, theta, and alpha frequency bands (3–13 Hz). That activity was followed by similar posterior parietal cortex spectral power increase that decreased in lag time with increasing locomotion speed. The sequence of activation suggests that supplementary motor area and premotor cortex interrupted the gait cycle, while posterior parietal cortex tracked obstacle location for planning foot placement nearly two steps ahead of reaching the obstacle. Together, these results highlight advantages of adopting dual-layer mobile EEG, which should greatly facilitate the study of human brain dynamics in physically active real-world settings and tasks.
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Affiliation(s)
- Andrew D Nordin
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, USA.
| | - W David Hairston
- Human Research and Engineering Directorate, U.S. Army Research Laboratory, Aberdeen Proving Ground, USA
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, USA
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