101
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Formica S, González-García C, Senoussi M, Brass M. Neural oscillations track the maintenance and proceduralization of novel instructions. Neuroimage 2021; 232:117870. [PMID: 33607280 DOI: 10.1016/j.neuroimage.2021.117870] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/26/2021] [Accepted: 02/11/2021] [Indexed: 12/30/2022] Open
Abstract
Humans are capable of flexibly converting symbolic instructions into novel behaviors. Previous evidence and theoretical models suggest that the implementation of a novel instruction requires the reformatting of its declarative content into an action-oriented code optimized for the execution of the instructed behavior. While neuroimaging research focused on identifying the brain areas involved in such a process, the temporal and electrophysiological mechanisms remain poorly understood. These mechanisms, however, can provide information about the specific cognitive processes that characterize the proceduralization of information. In the present study, we recorded EEG activity while we asked participants to either simply maintain declaratively the content of novel S-R mappings or to proactively prepare for their implementation. By means of time-frequency analyses, we isolated the oscillatory features specific to the proceduralization of instructions. Implementation of the instructed mappings elicited stronger theta activity over frontal electrodes and suppression in mu and beta activity over central electrodes. On the contrary, activity in the alpha band, which has been shown to track the attentional deployment to task-relevant items, showed no differences between tasks. Together, these results support the idea that proceduralization of information is characterized by specific component processes such as orchestrating complex task settings and configuring the motor system that are not observed when instructions are held in a declarative format.
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Affiliation(s)
- Silvia Formica
- Department of Experimental Psychology, Ghent University, Belgium.
| | | | - Mehdi Senoussi
- Department of Experimental Psychology, Ghent University, Belgium
| | - Marcel Brass
- Department of Experimental Psychology, Ghent University, Belgium; School of Mind and Brain/Department of Psychology, Humboldt Universität zu Berlin, Germany
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102
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Matsuda D, Moriuchi T, Ikio Y, Mitsunaga W, Fujiwara K, Matsuo M, Nakamura J, Suzuki T, Sugawara K, Higashi T. A Study on the Effect of Mental Practice Using Motor Evoked Potential-Based Neurofeedback. Front Hum Neurosci 2021; 15:637401. [PMID: 33643014 PMCID: PMC7907172 DOI: 10.3389/fnhum.2021.637401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 01/11/2021] [Indexed: 01/10/2023] Open
Abstract
This study aimed to investigate whether the effect of mental practice (motor imagery training) can be enhanced by providing neurofeedback based on transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEP). Twenty-four healthy, right-handed subjects were enrolled in this study. The subjects were randomly allocated into two groups: a group that was given correct TMS feedback (Real-FB group) and a group that was given randomized false TMS feedback (Sham-FB group). The subjects imagined pushing the switch with just timing, when the target circle overlapped a cross at the center of the computer monitor. In the Real-FB group, feedback was provided to the subjects based on the MEP amplitude measured in the trial immediately preceding motor imagery. In contrast, the subjects of the Sham-FB group were provided with a feedback value that was independent of the MEP amplitude. TMS was applied when the target, moving from right to left, overlapped the cross at the center of the screen, and the MEP amplitude was measured. The MEP was recorded in the right first dorsal interosseous muscle. We evaluated the pre-mental practice and post-mental practice motor performance in both groups. As a result, a significant difference was observed in the percentage change of error values between the Real-FB group and the Sham-FB group. Furthermore, the MEP was significantly different between the groups in the 4th and 5th sets. Therefore, it was suggested that TMS-induced MEP-based neurofeedback might enhance the effect of mental practice.
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Affiliation(s)
- Daiki Matsuda
- Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
| | - Takefumi Moriuchi
- Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
| | - Yuta Ikio
- Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
| | - Wataru Mitsunaga
- Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
| | - Kengo Fujiwara
- Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
| | - Moemi Matsuo
- Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
| | - Jiro Nakamura
- Department of Occupational Therapy, Nagasaki Memorial Hospital, Nagasaki, Japan
| | - Tomotaka Suzuki
- Faculty of Health and Social Work, Division of Physical Therapy, Kanagawa University of Human Services, Yokosuka, Japan
| | - Kenichi Sugawara
- Faculty of Health and Social Work, Division of Physical Therapy, Kanagawa University of Human Services, Yokosuka, Japan
| | - Toshio Higashi
- Graduate School of Biomedical Sciences, Nagasaki University, Nagasaki, Japan
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103
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Kline A, Gaina Ghiroaga C, Pittman D, Goodyear B, Ronsky J. EEG differentiates left and right imagined Lower Limb movement. Gait Posture 2021; 84:148-154. [PMID: 33340844 DOI: 10.1016/j.gaitpost.2020.11.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Revised: 11/11/2020] [Accepted: 11/13/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Identifying which EEG signals distinguish left from right leg movements in imagined lower limb movement is crucial to building an effective and efficient brain-computer interface (BCI). Past findings on this issue have been mixed, partly due to the difficulty in collecting and isolating the relevant information. The purpose of this study was to contribute to this new and important literature. RESEARCH QUESTION Can left versus right imagined stepping be differentiated using the alpha, beta, and gamma frequencies of EEG data at four electrodes (C1, C2, PO3, and PO4)? METHODS An experiment was conducted with a sample of 16 healthy male participants. They imagined left and right lower limb movements across 60 trials at two time periods separated by one week. Participants were fitted with a 64-electrode headcap, lay supine on a specially designed device and then completed the imagined task while observing a customized computer-generated image of a human walking to signify the left and right steps, respectively. RESULTS Findings showed that eight of the twelve frequency bands from 4 EEG electrodes were significant in differentiating imagined left from right lower limb movement. Using these data points, a neural network analysis resulted in an overall participant average test classification accuracy of left versus right movements at 63 %. SIGNIFICANCE Our study provides support for using the alpha, beta and gamma frequency bands at the sensorimotor areas (C1 and C2 electrodes) and incorporating information from the parietal/occipital lobes (PO3 and PO4 electrodes) for focused, real-time EEG signal processing to assist in creating a BCI for those with lower limb compromised mobility.
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Affiliation(s)
- Adrienne Kline
- Department of Biomedical Engineering, University of Calgary, Calgary, Alberta Canada.
| | - Calin Gaina Ghiroaga
- Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada
| | - Daniel Pittman
- Department of Radiology, University of Calgary, Alberta, Canada
| | | | - Janet Ronsky
- Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada
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104
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Amidfar M, Kim YK. EEG Correlates of Cognitive Functions and Neuropsychiatric Disorders: A Review of Oscillatory Activity and Neural Synchrony Abnormalities. CURRENT PSYCHIATRY RESEARCH AND REVIEWS 2021. [DOI: 10.2174/2666082216999201209130117] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
A large body of evidence suggested that disruption of neural rhythms and
synchronization of brain oscillations are correlated with a variety of cognitive and perceptual processes.
Cognitive deficits are common features of psychiatric disorders that complicate treatment of
the motivational, affective and emotional symptoms.
Objective:
Electrophysiological correlates of cognitive functions will contribute to understanding of
neural circuits controlling cognition, the causes of their perturbation in psychiatric disorders and
developing novel targets for the treatment of cognitive impairments.
Methods:
This review includes a description of brain oscillations in Alzheimer’s disease, bipolar
disorder, attention-deficit/hyperactivity disorder, major depression, obsessive compulsive disorders,
anxiety disorders, schizophrenia and autism.
Results:
The review clearly shows that the reviewed neuropsychiatric diseases are associated with
fundamental changes in both spectral power and coherence of EEG oscillations.
Conclusion:
In this article, we examined the nature of brain oscillations, the association of brain
rhythms with cognitive functions and the relationship between EEG oscillations and neuropsychiatric
diseases. Accordingly, EEG oscillations can most likely be used as biomarkers in psychiatric
disorders.
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Affiliation(s)
- Meysam Amidfar
- Department of Neuroscience, Tehran University of Medical Sciences, Tehran, Iran
| | - Yong-Ku Kim
- Department of Psychiatry, College of Medicine, Korea University, Seoul, South Korea
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105
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Caspar EA, De Beir A, Lauwers G, Cleeremans A, Vanderborght B. How using brain-machine interfaces influences the human sense of agency. PLoS One 2021; 16:e0245191. [PMID: 33411838 PMCID: PMC7790430 DOI: 10.1371/journal.pone.0245191] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 12/23/2020] [Indexed: 11/18/2022] Open
Abstract
Brain-machine interfaces (BMI) allows individuals to control an external device by controlling their own brain activity, without requiring bodily or muscle movements. Performing voluntary movements is associated with the experience of agency ("sense of agency") over those movements and their outcomes. When people voluntarily control a BMI, they should likewise experience a sense of agency. However, using a BMI to act presents several differences compared to normal movements. In particular, BMIs lack sensorimotor feedback, afford lower controllability and are associated with increased cognitive fatigue. Here, we explored how these different factors influence the sense of agency across two studies in which participants learned to control a robotic hand through motor imagery decoded online through electroencephalography. We observed that the lack of sensorimotor information when using a BMI did not appear to influence the sense of agency. We further observed that experiencing lower control over the BMI reduced the sense of agency. Finally, we observed that the better participants controlled the BMI, the greater was the appropriation of the robotic hand, as measured by body-ownership and agency scores. Results are discussed based on existing theories on the sense of agency in light of the importance of BMI technology for patients using prosthetic limbs.
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Affiliation(s)
- Emilie A. Caspar
- CO3 lab, Center for Research in Cognition and Neuroscience, Université libre de Bruxelles, Brussels, Belgium
| | - Albert De Beir
- Vrij Universiteit Brussels, Brussels, Belgium
- Flanders Make, Lommel, Belgium
| | - Gil Lauwers
- Vrij Universiteit Brussels, Brussels, Belgium
| | - Axel Cleeremans
- CO3 lab, Center for Research in Cognition and Neuroscience, Université libre de Bruxelles, Brussels, Belgium
| | - Bram Vanderborght
- Vrij Universiteit Brussels, Brussels, Belgium
- Flanders Make, Lommel, Belgium
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106
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Vidaurre C, Haufe S, Jorajuría T, Müller KR, Nikulin VV. Sensorimotor Functional Connectivity: A Neurophysiological Factor Related to BCI Performance. Front Neurosci 2021; 14:575081. [PMID: 33390877 PMCID: PMC7775663 DOI: 10.3389/fnins.2020.575081] [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: 06/22/2020] [Accepted: 11/16/2020] [Indexed: 12/29/2022] Open
Abstract
Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. About 20% of potential users of sensorimotor BCIs do not gain reliable control of the system. The inefficiency to decode user's intentions requires the identification of neurophysiological factors determining “good” and “poor” BCI performers. One of the important neurophysiological aspects in BCI research is that the neuronal oscillations, used to control these systems, show a rich repertoire of spatial sensorimotor interactions. Considering this, we hypothesized that neuronal connectivity in sensorimotor areas would define BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in a calibration and an online feedback session recorded on the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post- as well as pre-stimulus connectivity in the calibration recording is significantly correlated to online feedback performance in μ and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study demonstrates that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sensorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance.
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Affiliation(s)
- Carmen Vidaurre
- Department of Statistics, Computer Science and Mathematics, Public University of Navarre, Pamplona, Spain
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Tania Jorajuría
- Department of Statistics, Computer Science and Mathematics, Public University of Navarre, Pamplona, Spain
| | - Klaus-Robert Müller
- Department of Machine Learning, Berlin University of Technology, Berlin, Germany.,Department of Artificial Intelligence, Korea University, Seoul, South Korea.,Max Planck Institute for Informatics, Saarbrücken, Germany.,Google Research, Brain Team, Berlin, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia
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107
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Comparison of Biofeedback and Combined Interventions on Athlete's Performance. Appl Psychophysiol Biofeedback 2021; 46:227-234. [PMID: 33386459 DOI: 10.1007/s10484-020-09498-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/27/2020] [Indexed: 10/22/2022]
Abstract
The aim of this study was the comparison of neurofeedback and biofeedback as a combination, against biofeedback intervention alone on athletic performance. 45 novice basketball players were allocated into three groups and assigned accordingly, two experimental and one control group. The experimental group 1 received 24 biofeedback sessions only, experimental group 2 received 24 biofeedback and neurofeedback sessions combined, whereas the control group didn't receive any form of intervention. Athletic performance scales were used before and after each intervention and multivariate analysis of covariance was used to compare the two groups. Results showed that in comparison to the control group, the athletic performance scales scores in both experimental groups were significantly increased. Furthermore, in experimental group 2 (combined method), we noticed a significantly greater improvement in performance levels than experimental group 1. We concluded that neurofeedback and biofeedback interventions combined, can be used as an effective method to enhance athletic performance.
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108
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Kraeutner SN, McArthur JL, Kraeutner PH, Westwood DA, Boe SG. Leveraging the effector independent nature of motor imagery when it is paired with physical practice. Sci Rep 2020; 10:21335. [PMID: 33288785 PMCID: PMC7721807 DOI: 10.1038/s41598-020-78120-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 11/18/2020] [Indexed: 12/04/2022] Open
Abstract
While considered analogous to physical practice, the nature of imagery-based skill acquisition—specifically whether or not both effector independent and dependent encoding occurs through motor imagery—is not well understood. Here, motor imagery-based training was applied prior to or after physical practice-based training to probe the nature of imagery-based skill acquisition. Three groups of participants (N = 38) engaged in 10 days of training of a dart throwing task: 5 days of motor imagery prior to physical practice (MIP-PP), motor imagery following physical practice (PP-MIP), or physical practice only (PP-PP). Performance-related outcomes were assessed throughout. Brain activity was measured at three time points using fMRI (pre/mid/post-training; MIP-PP and PP-MIP groups). In contrast with physical practice, motor imagery led to changes in global versus specific aspects of the movement. Following 10 days of training, performance was greater when motor imagery preceded physical practice, although remained inferior to performance resulting from physical practice alone. Greater activation of regions that support effector dependent encoding was observed mid-, but not post-training for the PP-MIP group. Findings indicate that changes driven by motor imagery reflect effector independent encoding, providing new information regarding how motor imagery may be leveraged for skill acquisition.
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Affiliation(s)
- Sarah N Kraeutner
- Brain Behaviour Laboratory, University of British Columbia, Vancouver, BC, V6T1Z3, Canada.,Department of Physical Therapy, University of British Columbia, Vancouver, BC, V6T1Z3, Canada
| | - Jennifer L McArthur
- Laboratory for Brain Recovery and Function, Dalhousie University, Halifax, NS, B3H4R1, Canada
| | - Paul H Kraeutner
- Laboratory for Brain Recovery and Function, Dalhousie University, Halifax, NS, B3H4R1, Canada
| | - David A Westwood
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, B3H4R2, Canada.,School of Health and Human Performance, Dalhousie University, Halifax, NS, B3H4R2, Canada
| | - Shaun G Boe
- Laboratory for Brain Recovery and Function, Dalhousie University, Halifax, NS, B3H4R1, Canada. .,Department of Psychology and Neuroscience, Dalhousie University, Halifax, NS, B3H4R2, Canada. .,School of Health and Human Performance, Dalhousie University, Halifax, NS, B3H4R2, Canada. .,School of Physiotherapy, Dalhousie University, Rm 407, 4th Floor Forrest Building, 5869 University Avenue, PO Box 15000, Halifax, NS, B3H4R2, Canada.
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109
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Sotoodeh MS, Taheri-Torbati H, Hadjikhani N, Lassalle A. Preserved action recognition in children with autism spectrum disorders: Evidence from an EEG and eye-tracking study. Psychophysiology 2020; 58:e13740. [PMID: 33280150 DOI: 10.1111/psyp.13740] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 09/23/2020] [Accepted: 11/10/2020] [Indexed: 01/24/2023]
Abstract
Individuals with Autism Spectrum Disorder (ASD) have difficulties recognizing and understanding others' actions. The goal of the present study was to determine whether children with and without ASD show differences in the way they process stimuli depicting Biological Motion (BM). Thirty-two children aged 7-16 (16 ASD and 16 typically developing (TD) controls) participated in two experiments. In the first experiment, electroencephalography (EEG) was used to record low (8-10 Hz) and high (10-13 Hz) mu and beta (15-25 Hz) bands during the observation three different Point Light Displays (PLD) of action. In the second experiment, participants answered to action-recognition tests and their accuracy and response time were recorded, together with their eye-movements. There were no group differences in EEG data (first experiment), indicating that children with and without ASD do not differ in their mu suppression (8-13 Hz) and beta activity (15-25 Hz). However, behavioral data from second experiment revealed that children with ASD were less accurate and slower than TD children in their responses to an action recognition task. In addition, eye-tracking data indicated that children with ASD paid less attention to the body compared to the background when watching PLD stimuli. Our results indicate that the more the participants focused on the PLDs, the more they displayed mu suppressions. These results could challenge the results of previous studies that had not controlled for visual attention and found a possible deficit in MNS functions of individuals with ASD. We discuss possible mechanisms and interpretations.
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Affiliation(s)
| | | | - Nouchine Hadjikhani
- Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA.,Gillberg Neurospychiatry Center, University of Gothenburg, Gothenburg, Sweden
| | - Amandine Lassalle
- Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, USA
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110
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Lim H, Ku J. Superior Facilitation of an Action Observation Network by Congruent Character Movements in Brain-Computer Interface Action-Observation Games. CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING 2020; 24:566-572. [PMID: 33275851 DOI: 10.1089/cyber.2020.0231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Action observation (AO) is a promising strategy for promoting motor function in neural rehabilitation. Recently, brain-computer interface (BCI)-AO game rehabilitation, which combines AO therapy with BCI technology, has been introduced to improve the effectiveness of rehabilitation. This approach can improve motor learning by providing feedback, which can be interactive in an observation task, and the game contents of the BCI-AO game paradigm can affect rehabilitation. In this study, the effects of congruent rather than incongruent feedback in a BCI-AO game on mirror neurons were investigated. Specifically, the mu suppression with congruent and incongruent BCI-AO games was measured in 17 healthy adults. The mu suppression in the central motor cortex was significantly higher with the congruent BCI-AO game than with the incongruent one. In addition, the satisfaction evaluation results were excellent for the congruent case. These results support the fact that providing feedback congruent with the motion of an action video facilitates mirror neuron activity and can offer useful guidelines for the design of BCI-AO games for rehabilitation.
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Affiliation(s)
- Hyunmi Lim
- Department of Biomedical Engineering, School of Medicine, Keimyung University, Daegu, Korea
| | - Jeonghun Ku
- Department of Biomedical Engineering, School of Medicine, Keimyung University, Daegu, Korea
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111
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Zickerick B, Kobald SO, Thönes S, Küper K, Wascher E, Schneider D. Don't stop me now: Hampered retrieval of action plans following interruptions. Psychophysiology 2020; 58:e13725. [PMID: 33226663 DOI: 10.1111/psyp.13725] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 10/09/2020] [Accepted: 10/29/2020] [Indexed: 11/27/2022]
Abstract
How can we retrieve action plans in working memory (WM) after being distracted or interrupted? The present EEG study investigated this question using a WM task in which a random sequence of single numbers (1-4 and 6-9) was presented. In a given trial, participants had to decide whether the number presented in the preceding trial was odd or even. Additionally, interfering stimuli were randomly presented in 25% of all trials, requiring the participants to either ignore a colored number (distraction) or respond to it (interruption) while maintaining the previously formed action plan in WM. Our results revealed a detrimental impact of interruptions on WM performance in trials after interrupting stimuli compared to trials without a preceding interference. This was reflected in decreased task accuracy and reduced stimulus- and response-locked P3b amplitudes potentially indicating a hampered reactivation of stimulus-response links. Moreover, decreased contralateral mu suppression prior to a given response highlighted an impaired response preparation following interruptions. Distractions, on the other hand, did not negatively affect task performance but were followed by faster responses in subsequent trials compared to trials without prior interference. This result pattern was supported by stronger contralateral mu suppression indicating a facilitated response preparation. Overall, these results suggest that action representations in WM are resistant to distractions but do suffer from interruptions that disrupt or interfere with their implementation. We thus propose that the possibility of adequately preparing for an upcoming response is essential for behavioral guidance in the presence of external interference.
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Affiliation(s)
- Bianca Zickerick
- Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - S Oliver Kobald
- Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Sven Thönes
- Experimental Psychology, Department of Psychology, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Kristina Küper
- Bundeswehr Institute for Preventive Medicine, Koblenz, Germany
| | - Edmund Wascher
- Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Daniel Schneider
- Department of Ergonomics, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
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112
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Lindig-León C, Rimbert S, Bougrain L. Multiclass Classification Based on Combined Motor Imageries. Front Neurosci 2020; 14:559858. [PMID: 33328845 PMCID: PMC7710761 DOI: 10.3389/fnins.2020.559858] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 08/13/2020] [Indexed: 11/13/2022] Open
Abstract
Motor imagery (MI) allows the design of self-paced brain–computer interfaces (BCIs), which can potentially afford an intuitive and continuous interaction. However, the implementation of non-invasive MI-based BCIs with more than three commands is still a difficult task. First, the number of MIs for decoding different actions is limited by the constraint of maintaining an adequate spacing among the corresponding sources, since the electroencephalography (EEG) activity from near regions may add up. Second, EEG generates a rather noisy image of brain activity, which results in a poor classification performance. Here, we propose a solution to address the limitation of identifiable motor activities by using combined MIs (i.e., MIs involving 2 or more body parts at the same time). And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. We recorded EEG signals from seven healthy subjects during an 8-class EEG experiment including the rest condition and all possible combinations using the left hand, right hand, and feet. The proposed multilabel approaches convert the original 8-class problem into a set of three binary problems to facilitate the use of the CSP algorithm. In the case of the MC2CMI method, each binary problem groups together in one class all the MIs engaging one of the three selected body parts, while the rest of MIs that do not engage the same body part are grouped together in the second class. In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. Finally, three sets of features are merged together to predict the user intention by applying an 8-class linear discriminant analysis. The MC2SMI method is quite similar, the only difference is that any of the combined MIs is considered during the training phase, which drastically accelerates the calibration time. For all subjects, both the MC2CMI and the MC2SMI approaches reached a higher accuracy than the classic pair-wise (PW) and one-vs.-all (OVA) methods. Our results show that, when brain activity is properly modulated, multilabel approaches represent a very interesting solution to increase the number of commands, and thus to provide a better interaction.
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Affiliation(s)
- Cecilia Lindig-León
- Université de Lorraine, CNRS, LORIA, Inria, Nancy, France.,Faculty of Engineering, Computer Science and Psychology, Institute of Neural Information Processing, Ulm University, Ulm, Germany
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113
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Hosni SM, Borgheai SB, McLinden J, Shahriari Y. An fNIRS-Based Motor Imagery BCI for ALS: A Subject-Specific Data-Driven Approach. IEEE Trans Neural Syst Rehabil Eng 2020; 28:3063-3073. [PMID: 33206606 DOI: 10.1109/tnsre.2020.3038717] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Functional near-infrared spectroscopy (fNIRS) has recently gained momentum in research on motor-imagery (MI)-based brain-computer interfaces (BCIs). However, strikingly, most of the research effort is primarily devoted to enhancing fNIRS-based BCIs for healthy individuals. The ability of patients with amyotrophic lateral sclerosis (ALS), among the main BCI end-users to utilize fNIRS-based hemodynamic responses to efficiently control an MI-based BCI, has not yet been explored. This study aims to quantify subject-specific spatio-temporal characteristics of ALS patients' hemodynamic responses to MI tasks, and to investigate the feasibility of using these responses as a means of communication to control a binary BCI. METHODS Hemodynamic responses were recorded using fNIRS from eight patients with ALS while performing MI-Rest tasks. The generalized linear model (GLM) analysis was conducted to statistically estimate and evaluate individualized spatial activation. Selected channel sets were statistically optimized for classification. Subject-specific discriminative features, including a proposed data-driven estimated coefficient obtained from GLM, and optimized classification parameters were identified and used to further evaluate the performance using a linear support vector machine (SVM) classifier. RESULTS Inter-subject variations were observed in spatio-temporal characteristics of patients' hemodynamic responses. Using optimized classification parameters and feature sets, all subjects could successfully use their MI hemodynamic responses to control a BCI with an average classification accuracy of 85.4% ± 9.8%. SIGNIFICANCE Our results indicate a promising application of fNIRS-based MI hemodynamic responses to control a binary BCI by ALS patients. These findings highlight the importance of subject-specific data-driven approaches for identifying discriminative spatio-temporal characteristics for an optimized BCI performance.
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114
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Roc A, Pillette L, Mladenovic J, Benaroch C, N'Kaoua B, Jeunet C, Lotte F. A review of user training methods in brain computer interfaces based on mental tasks. J Neural Eng 2020; 18. [PMID: 33181488 DOI: 10.1088/1741-2552/abca17] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 11/12/2020] [Indexed: 12/12/2022]
Abstract
Mental-Tasks based Brain-Computer Interfaces (MT-BCIs) allow their users to interact with an external device solely by using brain signals produced through mental tasks. While MT-BCIs are promising for many applications, they are still barely used outside laboratories due to their lack of reliability. MT-BCIs require their users to develop the ability to self-regulate specific brain signals. However, the human learning process to control a BCI is still relatively poorly understood and how to optimally train this ability is currently under investigation. Despite their promises and achievements, traditional training programs have been shown to be sub-optimal and could be further improved. In order to optimize user training and improve BCI performance, human factors should be taken into account. An interdisciplinary approach should be adopted to provide learners with appropriate and/or adaptive training. In this article, we provide an overview of existing methods for MT-BCI user training - notably in terms of environment, instructions, feedback and exercises. We present a categorization and taxonomy of these training approaches, provide guidelines on how to choose the best methods and identify open challenges and perspectives to further improve MT-BCI user training.
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Affiliation(s)
| | | | | | - Camille Benaroch
- Inria Centre de recherche Bordeaux Sud-Ouest, Talence, 33405, FRANCE
| | - Bernard N'Kaoua
- Handicap, Activity, Cognition, Health, Inserm / University of Bordeaux, Talence, FRANCE
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115
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Duan L, Li J, Ji H, Pang Z, Zheng X, Lu R, Li M, Zhuang J. Zero-Shot Learning for EEG Classification in Motor Imagery-Based BCI System. IEEE Trans Neural Syst Rehabil Eng 2020; 28:2411-2419. [PMID: 32986556 DOI: 10.1109/tnsre.2020.3027004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
A brain-computer interface (BCI) based on motor imagery (MI) translates human intentions into computer commands by recognizing the electroencephalogram (EEG) patterns of different imagination tasks. However, due to the scarcity of MI commands and the long calibration time, using the MI-based BCI system in practice is still challenging. Zero-shot learning (ZSL), which can recognize objects whose instances may not have been seen during training, has the potential to substantially reduce the calibration time. Thus, in this context, we first try to use a new type of motor imagery task, which is a combination of traditional tasks and propose a novel zero-shot learning model that can recognize both known and unknown categories of EEG signals. This is achieved by first learning a non-linear projection from EEG features to the target space and then applying a novelty detection method to differentiate unknown classes from known classes. Applications to a dataset collected from nine subjects confirm the possibility of identifying a new type of motor imagery only using already obtained motor imagery data. Results indicate that the classification accuracy of our zero-shot based method accounts for 91.81% of the traditional method which uses all categories of data.
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116
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Neural component analysis: A spatial filter for electroencephalogram analysis. J Neurosci Methods 2020; 348:108987. [PMID: 33157145 DOI: 10.1016/j.jneumeth.2020.108987] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 09/22/2020] [Accepted: 10/20/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Spatial filtering and source separation are valuable tools in the analysis of EEG data. However, despite the well-known spatial localisation of individual cognitive processes within the brain, the available methods for source separation, such as the widely used blind source separation technique, do not take into account the spatial distributions and locations of sources. This can result in sub-optimal source identification. NEW METHOD We present a new method for deriving a spatial filter for EEG data that attempts to identify sources that are maximally spatially distinct from one another in terms of the spatial distributions of their projections. RESULTS We first evaluate our method with simulated EEG and show that it is able to separate EEG signals into components with distinct spatial distributions that closely resemble the original simulated sources. We also evaluate our method with real EEG and show it is able to identify a spatial filter that can be used to significantly improve classification accuracy of the P300 event-related potential (ERP). COMPARISON WITH EXISTING METHODS We compare our method to a state of the art blind source separation methods, fast independent component analysis (ICA) and common spatial patterns (CSP). We evaluate the methods suitability for a common source separation application, analysis of ERPs. CONCLUSIONS Our results show that our method is well suited to identifying spatial filters for EEG analysis. This has potential applications in a wide range of EEG signal processing applications.
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117
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Improving performance in motor imagery BCI-based control applications via virtually embodied feedback. Comput Biol Med 2020; 127:104079. [PMID: 33126130 DOI: 10.1016/j.compbiomed.2020.104079] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 09/30/2020] [Accepted: 10/20/2020] [Indexed: 12/16/2022]
Abstract
OBJECTIVE Brain-computer interfaces (BCIs) based on motor imagery (MI) are commonly used for control applications. However, these applications require strong and discriminant neural patterns for which extensive experience in MI may be necessary. Inspired by the field of rehabilitation where embodiment is a key element for improving cortical activity, our study proposes a novel control scheme in which virtually embodiable feedback is provided during control to enhance performance. METHODS Subjects underwent two immersive virtual reality control scenarios in which they controlled the two-dimensional movement of a device using electroencephalography (EEG). The two scenarios only differ on whether embodiable feedback, which mirrors the movement of the classified intention, is provided. After undergoing each scenario, subjects also answered a questionnaire in which they rated how immersive the scenario and embodiable the feedback were. RESULTS Subjects exhibited higher control performance, greater discriminability in brain activity patterns, and enhanced cortical activation when using our control scheme compared to the standard control scheme in which embodiable feedback is absent. Moreover, the self-rated embodiment and presence scores showed significantly positive linear relationships with performance. SIGNIFICANCE The findings in our study provide evidence that providing embodiable feedback as guidance on how intention is classified may be effective for control applications by inducing enhanced neural activity and patterns with greater discriminability. By applying embodiable feedback to immersive virtual reality, our study also serves as another instance in which virtual reality is shown to be a promising tool for improving MI.
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118
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Osborn LE, Ding K, Hays MA, Bose R, Iskarous MM, Dragomir A, Tayeb Z, Lévay GM, Hunt CL, Cheng G, Armiger RS, Bezerianos A, Fifer MS, Thakor NV. Sensory stimulation enhances phantom limb perception and movement decoding. J Neural Eng 2020; 17:056006. [PMID: 33078717 PMCID: PMC8437134 DOI: 10.1088/1741-2552/abb861] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
OBJECTIVE A major challenge for controlling a prosthetic arm is communication between the device and the user's phantom limb. We show the ability to enhance phantom limb perception and improve movement decoding through targeted transcutaneous electrical nerve stimulation in individuals with an arm amputation. APPROACH Transcutaneous nerve stimulation experiments were performed with four participants with arm amputation to map phantom limb perception. We measured myoelectric signals during phantom hand movements before and after participants received sensory stimulation. Using electroencephalogram (EEG) monitoring, we measured the neural activity in sensorimotor regions during phantom movements and stimulation. In one participant, we also tracked sensory mapping over 2 years and movement decoding performance over 1 year. MAIN RESULTS Results show improvements in the participants' ability to perceive and move the phantom hand as a result of sensory stimulation, which leads to improved movement decoding. In the extended study with one participant, we found that sensory mapping remains stable over 2 years. Sensory stimulation improves within-day movement decoding while performance remains stable over 1 year. From the EEG, we observed cortical correlates of sensorimotor integration and increased motor-related neural activity as a result of enhanced phantom limb perception. SIGNIFICANCE This work demonstrates that phantom limb perception influences prosthesis control and can benefit from targeted nerve stimulation. These findings have implications for improving prosthesis usability and function due to a heightened sense of the phantom hand.
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Affiliation(s)
- Luke E. Osborn
- Department of Biomedical Engineering, Johns Hopkins School
of Medicine, Baltimore, MD, United States of America.,Research & Exploratory Development Department, Johns
Hopkins University Applied Physics Laboratory, Laurel, MD, United States of
America., (L.E.O.);
(N.V.T.)
| | - Keqin Ding
- Department of Biomedical Engineering, Johns Hopkins School
of Medicine, Baltimore, MD, United States of America
| | - Mark A. Hays
- Department of Biomedical Engineering, Johns Hopkins School
of Medicine, Baltimore, MD, United States of America
| | - Rohit Bose
- N.1 Institute for Health, National University of Singapore,
Singapore.,Department of Bioengineering, University of Pittsburgh,
Pittsburgh, PA, United States of America
| | - Mark M. Iskarous
- Department of Biomedical Engineering, Johns Hopkins School
of Medicine, Baltimore, MD, United States of America
| | - Andrei Dragomir
- N.1 Institute for Health, National University of Singapore,
Singapore.,Department of Biomedical Engineering, University of
Houston, Houston, TX, United States of America
| | - Zied Tayeb
- Institute for Cognitive Systems, Technical University of
Munich, München, Germany
| | - György M. Lévay
- Infinite Biomedical Technologies, Baltimore, MD, United
States of America.,Faculty of Medicine, Semmelweis University, Budapest,
Hungary
| | - Christopher L. Hunt
- Department of Biomedical Engineering, Johns Hopkins School
of Medicine, Baltimore, MD, United States of America
| | - Gordon Cheng
- Institute for Cognitive Systems, Technical University of
Munich, München, Germany
| | - Robert S. Armiger
- Research & Exploratory Development Department, Johns
Hopkins University Applied Physics Laboratory, Laurel, MD, United States of
America
| | - Anastasios Bezerianos
- N.1 Institute for Health, National University of Singapore,
Singapore.,Department of Medical Physics, University of Patras,
Patras, Greece
| | - Matthew S. Fifer
- Research & Exploratory Development Department, Johns
Hopkins University Applied Physics Laboratory, Laurel, MD, United States of
America
| | - Nitish V. Thakor
- Department of Biomedical Engineering, Johns Hopkins School
of Medicine, Baltimore, MD, United States of America.,N.1 Institute for Health, National University of Singapore,
Singapore.,Department of Electrical and Computer Engineering, Johns
Hopkins University, Baltimore, MD, United States of America., (L.E.O.);
(N.V.T.)
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119
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Naro A, Calabrò RS. Towards New Diagnostic Approaches in Disorders of Consciousness: A Proof of Concept Study on the Promising Use of Imagery Visuomotor Task. Brain Sci 2020; 10:brainsci10100746. [PMID: 33080823 PMCID: PMC7603054 DOI: 10.3390/brainsci10100746] [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: 09/05/2020] [Revised: 10/08/2020] [Accepted: 10/14/2020] [Indexed: 12/16/2022] Open
Abstract
Background: advanced paraclinical approaches using functional neuroimaging and electroencephalography (EEG) allow identifying patients who are covertly aware despite being diagnosed as unresponsive wakefulness syndrome (UWS). Bedside detection of covert awareness employing motor imagery tasks (MI), which is a universally accepted clinical indicator of awareness in the absence of overt behavior, may miss some of these patients, as they could still have a certain level of awareness. We aimed at assessing covert awareness in patients with UWS using a visuomotor-guided motor imagery task (VMI) during EEG recording. Methods: nine patients in a minimally conscious state (MCS), 11 patients in a UWS, and 15 healthy individuals (control group—CG) were provided with an VMI (imagine dancing while watching a group dance video to command), a simple-MI (imagine squeezing their right hand to command), and an advanced-MI (imagine dancing without watching a group dance video to command) to detect command-following. We analyzed the command-specific EEG responses (event-related synchronization/desynchronization—ERS/ERD) of each patient, assessing whether these responses were appropriate, consistent, and statistically similar to those elicited in the CG, as reliable markers of motor imagery. Results: All patients in MCS, all healthy individuals and one patient in UWS repeatedly and reliably generated appropriate EEG responses to distinct commands of motor imagery with a classification accuracy of 60–80%. Conclusions: VMI outperformed significantly MI tasks. Therefore, patients in UWS may be still misdiagnosed despite a rigorous clinical assessment and an appropriate MI assessment. It is thus possible to suggest that motor imagery tasks should be delivered to patients with chronic disorders of consciousness in visuomotor-aided modality (also in the rehabilitation setting) to greatly entrain patient’s participation. In this regard, the EEG approach we described has the clear advantage of being cheap, portable, widely available, and objective. It may be thus considered as, at least, a screening tool to identify the patients who deserve further, advanced paraclinical approaches.
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120
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Pavlov AN, Pitsik EN, Frolov NS, Badarin A, Pavlova ON, Hramov AE. Age-Related Distinctions in EEG Signals during Execution of Motor Tasks Characterized in Terms of Long-Range Correlations. SENSORS 2020; 20:s20205843. [PMID: 33076556 PMCID: PMC7602706 DOI: 10.3390/s20205843] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 09/23/2020] [Accepted: 10/12/2020] [Indexed: 12/20/2022]
Abstract
The problem of revealing age-related distinctions in multichannel electroencephalograms (EEGs) during the execution of motor tasks in young and elderly adults is addressed herein. Based on the detrended fluctuation analysis (DFA), differences in long-range correlations are considered, emphasizing changes in the scaling exponent α. Stronger responses in elderly subjects are confirmed, including the range and rate of increase in α. Unlike elderly subjects, young adults demonstrated about 2.5 times more pronounced differences between motor task responses with the dominant and non-dominant hand. Knowledge of age-related changes in brain electrical activity is important for understanding consequences of healthy aging and distinguishing them from pathological changes associated with brain diseases. Besides diagnosing age-related effects, the potential of DFA can also be used in the field of brain–computer interfaces.
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Affiliation(s)
- Alexey N. Pavlov
- Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia; (A.N.P.); (O.N.P.)
| | - Elena N. Pitsik
- Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Universitetskaya Str. 1, 420500 Innopolis, Russia; (E.N.P.); (N.S.F.); (A.B.)
| | - Nikita S. Frolov
- Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Universitetskaya Str. 1, 420500 Innopolis, Russia; (E.N.P.); (N.S.F.); (A.B.)
| | - Artem Badarin
- Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Universitetskaya Str. 1, 420500 Innopolis, Russia; (E.N.P.); (N.S.F.); (A.B.)
| | - Olga N. Pavlova
- Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia; (A.N.P.); (O.N.P.)
| | - Alexander E. Hramov
- Neuroscience and Cognitive Technology Laboratory, Center for Technologies in Robotics and Mechatronics Components, Innopolis University, Universitetskaya Str. 1, 420500 Innopolis, Russia; (E.N.P.); (N.S.F.); (A.B.)
- Lobachevsky University, 23 Gagarina Avenue, 603950 Nizhny Novgorod, Russia
- Saratov State Medical University, Bolshaya Kazachya Str. 112, 410012 Saratov, Russia
- Correspondence:
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121
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Guggenberger R, Raco V, Gharabaghi A. State-Dependent Gain Modulation of Spinal Motor Output. Front Bioeng Biotechnol 2020; 8:523866. [PMID: 33117775 PMCID: PMC7561675 DOI: 10.3389/fbioe.2020.523866] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 09/17/2020] [Indexed: 01/04/2023] Open
Abstract
Afferent somatosensory information plays a crucial role in modulating efferent motor output. A better understanding of this sensorimotor interplay may inform the design of neurorehabilitation interfaces. Current neurotechnological approaches that address motor restoration after trauma or stroke combine motor imagery (MI) and contingent somatosensory feedback, e.g., via peripheral stimulation, to induce corticospinal reorganization. These interventions may, however, change the motor output already at the spinal level dependent on alterations of the afferent input. Neuromuscular electrical stimulation (NMES) was combined with measurements of wrist deflection using a kinematic glove during either MI or rest. We investigated 360 NMES bursts to the right forearm of 12 healthy subjects at two frequencies (30 and 100 Hz) in random order. For each frequency, stimulation was assessed at nine intensities. Measuring the induced wrist deflection across different intensities allowed us to estimate the input-output curve (IOC) of the spinal motor output. MI decreased the slope of the IOC independent of the stimulation frequency. NMES with 100 Hz vs. 30 Hz decreased the threshold of the IOC. Human-machine interfaces for neurorehabilitation that combine MI and NMES need to consider bidirectional communication and may utilize the gain modulation of spinal circuitries by applying low-intensity, high-frequency stimulation.
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Affiliation(s)
- Robert Guggenberger
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University of Tüebingen, Tüebingen, Germany
| | - Valerio Raco
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University of Tüebingen, Tüebingen, Germany
| | - Alireza Gharabaghi
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University of Tüebingen, Tüebingen, Germany
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122
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Should I stay or should I go? How local-global implicit temporal expectancy shapes proactive motor control: An hdEEG study. Neuroimage 2020; 220:117071. [DOI: 10.1016/j.neuroimage.2020.117071] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 06/12/2020] [Accepted: 06/17/2020] [Indexed: 01/10/2023] Open
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123
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Liu H, Zhang Q. Neural correlates of the mechanism underlying negative response repetition effects in task-switching. Brain Cogn 2020; 145:105627. [PMID: 32980579 DOI: 10.1016/j.bandc.2020.105627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 07/21/2020] [Accepted: 09/02/2020] [Indexed: 11/25/2022]
Abstract
In a task-switching paradigm, usual response-repetition benefits are replaced by response-repetition costs when the task switches. Inhibition of a previous response and mismatch interference induced by response-repetition have been proposed as sources of negative response-repetition effects by the response inhibition account and episodic binding and retrieval model, respectively. The present study utilized electroencephalograph (EEG) to investigate the mechanism underlying negative response-repetition effects. Lateralized enhancements in the upper-alpha and beta bands served as indexes of response inhibition, and significant lateralized beta enhancements appeared after the previous response execution. About 500-600 ms after the onset of current stimuli, event-related potentials presented significant response-repeat negativity in the task-switch sequence, indicating the occurrence of mismatch interference induced by response repetition. Moreover, lateralized beta enhancements and response-repeat negativity were each positively related to behavioral negative response-repetition effects. These results suggest that both response inhibition and mismatch interference induced by response repetition make contributions to negative response-repetition effects.
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Affiliation(s)
- Hailan Liu
- Learning and Cognition Key Laboratory of Beijing, School of Psychology, Capital Normal University, Beijing, China
| | - Qin Zhang
- Learning and Cognition Key Laboratory of Beijing, School of Psychology, Capital Normal University, Beijing, China.
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124
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Liu H, Zhang Q. Response inhibition in the task-switching paradigm. Biol Psychol 2020; 156:107954. [PMID: 32976924 DOI: 10.1016/j.biopsycho.2020.107954] [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: 12/08/2019] [Revised: 08/14/2020] [Accepted: 09/14/2020] [Indexed: 10/23/2022]
Abstract
In a task-switching paradigm, response repetition (RR) often produces costs in task-switch trials but smaller costs or even benefits in task-repeat trials. Response inhibition accounts consistently attribute negative RR effects to the inhibition of the previous response, but they have different views on this inhibition process. According to the task-specific inhibition hypothesis, the previous response is inhibited when the task-switch is called for; whereas according to the general inhibition hypothesis, the response was generally inhibited after the execution. The present study utilized the electroencephalographs (EEGs) to investigate the response inhibition in the task-switching paradigm, with lateralized upper-alpha and beta enhancements serving as indexes of response inhibition. In blocks with task preparation, a task cue during the response-stimulus interval (RSI) was used to indicate which task was required, and the blocks without task preparation served as the control condition. The result indicated that, during the cue-stimulus interval (CSI), lateralized upper-alpha enhancements appeared only in trials with task-switch preparation, supporting the task-specific inhibition hypothesis. By contrast, regardless of whether there was task preparation and which task to prepare, lateralized beta enhancements appeared during the RSI, which provided evidence for the general inhibition hypothesis. These results suggest the existence of two different response inhibition processes in the task-switching paradigm.
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Affiliation(s)
- Hailan Liu
- Learning and Cognition Key Laboratory of Beijing, School of Psychology, Capital Normal University, Beijing, China
| | - Qin Zhang
- Learning and Cognition Key Laboratory of Beijing, School of Psychology, Capital Normal University, Beijing, China.
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125
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Kline A, Pittman D, Ronsky J, Goodyear B. Differentiating the Brain's involvement in Executed and Imagined Stepping using fMRI. Behav Brain Res 2020; 394:112829. [PMID: 32717374 DOI: 10.1016/j.bbr.2020.112829] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Revised: 07/12/2020] [Accepted: 07/21/2020] [Indexed: 12/31/2022]
Abstract
The purpose of this study was to extend the extant literature regarding brain areas that are activated during executed and imagined lower limb movement. Past research suggests that stepping, as a cyclical movement, should activate the motor control areas of the brain that integrates smooth movements with spinal cord nerves. The neuronal activity needed to imagine that same activity is likely to recruit additional sensory-motor areas that provide initiation and inhibition signals, making this task take on a neuronal activity pattern that is more similar to discrete movements. To assess this research question, 16 participants took part in the current study where they executed and imagined stepping, with movement at the hip, knee, and ankle joints, while viewing a computer-generated image of a human walking. A block design with a total of 10 blocks for rest and task for each condition was used. Rest blocks lasted 18 seconds, followed by an 18-second display of the visual stimulus. Results showed that in the executed condition, areas of the brain that are most prominently associated with sensory-motor activity were activated. In the imagined condition areas of the brain associated with movement control, inhibition of movement, and the integration of sensory input and motor output (parietal and occipital) were also activated. These findings contribute to the literature identifying brain areas that are activated in lower limb locomotion.
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Affiliation(s)
- Adrienne Kline
- Department of Biomedical Engineering, University of Calgary, Calgary, AB, Canada.
| | - Daniel Pittman
- Cumming School of Medicine University of Calgary, Calgary, AB, Canada
| | - Janet Ronsky
- Department of Mechanical and Manufacturing Engineering University of Calgary, Calgary, AB, Canada
| | - Bradley Goodyear
- Department of Radiology, University of Calgary, Calgary, AB, Canada
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126
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Neurofeedback of scalp bi-hemispheric EEG sensorimotor rhythm guides hemispheric activation of sensorimotor cortex in the targeted hemisphere. Neuroimage 2020; 223:117298. [PMID: 32828924 DOI: 10.1016/j.neuroimage.2020.117298] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/04/2020] [Accepted: 08/16/2020] [Indexed: 12/26/2022] Open
Abstract
Oscillatory electroencephalographic (EEG) activity is associated with the excitability of cortical regions. Visual feedback of EEG-oscillations may promote sensorimotor cortical activation, but its spatial specificity is not truly guaranteed due to signal interaction among interhemispheric brain regions. Guiding spatially specific activation is important for facilitating neural rehabilitation processes. Here, we tested whether users could explicitly guide sensorimotor cortical activity to the contralateral or ipsilateral hemisphere using a spatially bivariate EEG-based neurofeedback that monitors bi-hemispheric sensorimotor cortical activities for healthy participants. Two different motor imageries (shoulder and hand MIs) were selected to see how differences in intrinsic corticomuscular projection patterns might influence activity lateralization. We showed sensorimotor cortical activities during shoulder, but not hand MI, can be brought under ipsilateral control with guided EEG-based neurofeedback. These results are compatible with neuroanatomy; shoulder muscles are innervated bihemispherically, whereas hand muscles are mostly innervated contralaterally. We demonstrate the neuroanatomically-inspired approach enables us to investigate potent neural remodeling functions that underlie EEG-based neurofeedback via a BCI.
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127
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Zhang X, Li H, Xie T, Liu Y, Chen J, Long J. Movement speed effects on beta-band oscillations in sensorimotor cortex during voluntary activity. J Neurophysiol 2020; 124:352-359. [PMID: 32579410 DOI: 10.1152/jn.00238.2020] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Beta-band oscillations are a dominant feature in the sensorimotor system, which includes movement-related beta desynchronization (MRBD) during the preparation and execution phases of movement and postmovement beta synchronization (PMBS) on movement cessation. Many studies have linked this rhythm to motor functions. However, its associations to the movement speed are still unclear. We make a hypothesis that PMBS will be modulated with increasing of movement speeds. We assessed the MRBD and PMBS during isotonic slower self-paced and ballistic movements with 15 healthy subjects. Furthermore, we conduct an additional control experiment with the isometric contraction with two levels of forces to match those in the isotonic slower self-paced and ballistic movements separately. We found that the amplitude of PMBS but not MRBD in motor cortex is modulated by the speed during voluntary movement. PMBS was positively correlated with movement speed and acceleration through the partial correlation analysis. However, there were no changes in the PMBS and MRBD during the isometric contraction with two levels of forces. These results demonstrate a different function of PMBS and MRBD to the movement speed during voluntary activity and suggest that the movement speed would affect the amplitude of PMBS.NEW & NOTEWORTHY Beta-band oscillations are a dominant feature in the sensorimotor system that associate to the motor function. We found that the movement-related postmovement beta synchronization (PMBS) over the contralateral sensorimotor cortex was positively correlated with the speed of a voluntary movement, but the movement-related beta desynchronization (MRBD) was not. Our results show a differential response of the PMBS and MRBD to the movement speed during voluntary movement.
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Affiliation(s)
- Xiangzi Zhang
- College of Information Science and Technology, Jinan University, Guangzhou, Guangdong, China
| | - Hualiang Li
- Guangdong Power Grid Corporation, Guangzhou, Guangdong, China
| | - Tingjun Xie
- Guangdong Power Grid Corporation, Guangzhou, Guangdong, China
| | - Yuzhong Liu
- Guangdong Power Grid Corporation, Guangzhou, Guangdong, China
| | - Juan Chen
- School of Psychology, Center for the Study of Applied Psychology, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong Province, China.,Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, China
| | - Jinyi Long
- College of Information Science and Technology, Jinan University, Guangzhou, Guangdong, China
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128
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Choi JW, Kim BH, Huh S, Jo S. Observing Actions Through Immersive Virtual Reality Enhances Motor Imagery Training. IEEE Trans Neural Syst Rehabil Eng 2020; 28:1614-1622. [DOI: 10.1109/tnsre.2020.2998123] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Fleury M, Lioi G, Barillot C, Lécuyer A. A Survey on the Use of Haptic Feedback for Brain-Computer Interfaces and Neurofeedback. Front Neurosci 2020; 14:528. [PMID: 32655347 PMCID: PMC7325479 DOI: 10.3389/fnins.2020.00528] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 04/28/2020] [Indexed: 11/23/2022] Open
Abstract
Neurofeedback (NF) and brain-computer interface (BCI) applications rely on the registration and real-time feedback of individual patterns of brain activity with the aim of achieving self-regulation of specific neural substrates or control of external devices. These approaches have historically employed visual stimuli. However, in some cases vision is unsuitable or inadequately engaging. Other sensory modalities, such as auditory or haptic feedback have been explored, and multisensory stimulation is expected to improve the quality of the interaction loop. Moreover, for motor imagery tasks, closing the sensorimotor loop through haptic feedback may be relevant for motor rehabilitation applications, as it can promote plasticity mechanisms. This survey reviews the various haptic technologies and describes their application to BCIs and NF. We identify major trends in the use of haptic interfaces for BCI and NF systems and discuss crucial aspects that could motivate further studies.
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Affiliation(s)
- Mathis Fleury
- University of Rennes 1, INRIA, EMPENN & HYBRID, Rennes, France
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130
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Liu T, Huang G, Jiang N, Yao L, Zhang Z. Reduce brain computer interface inefficiency by combining sensory motor rhythm and movement-related cortical potential features. J Neural Eng 2020; 17:035003. [PMID: 32380494 DOI: 10.1088/1741-2552/ab914d] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Brain Computer Interface (BCI) inefficiency indicates that there would be 10% to 50% of users are unable to operate Motor-Imagery-based BCI systems. Importantly, the almost all previous studieds on BCI inefficiency were based on tests of Sensory Motor Rhythm (SMR) feature. In this work, we assessed the occurrence of BCI inefficiency with SMR and Movement-Related Cortical Potential (MRCP) features. APPROACH A pool of datasets of resting state and movements related EEG signals was recorded with 93 subjects during 2 sessions in separated days. Two methods, Common Spatial Pattern (CSP) and template matching, were used for SMR and MRCP feature extraction, and a winner-take-all strategy was applied to assess pattern recognition with posterior probabilities from Linear Discriminant Analysis to combine SMR and MRCP features. MAIN RESULTS The results showed that the two types of features showed high complementarity, in line with their weak intercorrelation. In the subject group with poor accuracies (< 70%) by SMR feature in the two-class problem (right foot vs. right hand), the combination of SMR and MRCP features improved the averaged accuracy from 62% to 79%. Importantly, accuracies obtained by feature combination exceeded the inefficiency threshold. SIGNIFICANCE The feature combination of SMR and MRCP is not new in BCI decoding, but the large scale and repeatable study on BCI inefficiency assessment by using SMR and MRCP features is novel. MRCP feature provides the similar classification accuracies on the two subject groups with poor (< 70%) and good (> 90%) accuracies by SMR feature. These results suggest that the combination of SMR and MRCP features may be a practical approach to reduce BCI inefficiency. While, 'BCI inefficiency' might be more aptly called 'SMR inefficiency' after this study.
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Affiliation(s)
- Tengjun Liu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, People's Republic of China. Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen 518060, People's Republic of China
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Huang S, Peng H, Chen Y, Sun K, Shen F, Wang T, Ma T. Tensor Discriminant Analysis for MI-EEG Signal Classification Using Convolutional Neural Network. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:5971-5974. [PMID: 31947207 DOI: 10.1109/embc.2019.8857422] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Motor Imagery (MI) is a typical paradigm for Brain-Computer Interface (BCI) system. In this paper, we propose a new framework by introducing a tensor-based feature representation of the data and also utilizing a convolutional neural network (CNN) architecture for performing classification of MI-EEG signal. The tensor-based representation that includes the structural information in multi-channel time-varying EEG spectrum is generated from tensor discriminant analysis (TDA), and CNN is designed and optimized accordingly for this representation. Compared with CSP+SVM (the conventional framework which is the most successful in MI-based BCI) in the applications to the BCI competition III-IVa dataset, the proposed framework has the following advantages: (1) the most discriminant patterns can be obtained by applying optimum selection of spatial-spectral-temporal subspace for each subject; (2) the corresponding CNN can take full advantage of tensor-based representation and identify discriminative characteristics robustly. The results demonstrate that our framework can further improve classification performance and has great potential for the practical application of BCI.
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132
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McFarland D, Norman S, Sarnacki W, Wolbrecht E, Reinkensmeyer D, Wolpaw J. BCI-based sensorimotor rhythm training can affect individuated finger movements. BRAIN-COMPUTER INTERFACES 2020. [DOI: 10.1080/2326263x.2020.1763060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- D.J. McFarland
- National Center for Adaptive Neurotechnologies, Wadsworth Center , Albany, NY, USA
| | - S.L. Norman
- Dept. of Mechanical and Aerospace Engineering, University of California Irvine , Irvine, CA, USA
- Division of Biology and Biological Engineering, California Institute of Technology , Pasadena, CA, USA
| | - W.A. Sarnacki
- National Center for Adaptive Neurotechnologies, Wadsworth Center , Albany, NY, USA
| | - E.T. Wolbrecht
- Dept. of Mechanical Engineering, University of Idaho , Moscow, ID, USA
| | - D.J. Reinkensmeyer
- Dept. of Mechanical and Aerospace Engineering, University of California Irvine , Irvine, CA, USA
| | - J.R. Wolpaw
- National Center for Adaptive Neurotechnologies, Wadsworth Center , Albany, NY, USA
- Dept. of Neurology, Stratton Veterans Administration Medical Center , Albany, NY, USA
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Kraeutner SN, Stratas A, McArthur JL, Helmick CA, Westwood DA, Boe SG. Neural and Behavioral Outcomes Differ Following Equivalent Bouts of Motor Imagery or Physical Practice. J Cogn Neurosci 2020; 32:1590-1606. [PMID: 32420839 DOI: 10.1162/jocn_a_01575] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Despite its reported effectiveness for the acquisition of motor skills, we know little about how motor imagery (MI)-based brain activation and performance evolves when MI (the imagined performance of a motor task) is used to learn a complex motor skill compared to physical practice (PP). The current study examined changes in MI-related brain activity and performance driven by an equivalent bout of MI- or PP-based training. Participants engaged in 5 days of either MI or PP of a dart-throwing task. Brain activity (via fMRI) and performance-related outcomes were obtained using a pre/post/retention design. Relative to PP, MI-based training did not drive robust changes in brain activation and was inferior for realizing improvements in performance: Greater activation in regions critical to refining the motor program was observed in the PP versus MI group posttraining, and relative to those driven via PP, MI led only to marginal improvements in performance. Findings indicate that the modality of practice (i.e., MI vs. PP) used to learn a complex motor skill manifests as differences in both resultant patterns of brain activity and performance. Ultimately, by directly comparing brain activity and behavioral outcomes after equivalent training through MI versus PP, this work provides unique knowledge regarding the neural mechanisms underlying learning through MI.
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134
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Foysal KMR, Baker SN. Induction of plasticity in the human motor system by motor imagery and transcranial magnetic stimulation. J Physiol 2020; 598:2385-2396. [PMID: 32266976 DOI: 10.1113/jp279794] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 04/02/2020] [Indexed: 12/28/2022] Open
Abstract
KEY POINTS Delivering transcranial magnetic brain stimulation over the motor cortex during motor imagination leads to enhanced motor output, which is selective for the muscles primarily involved in the imagined movement. This novel protocol may be useful to enhance function after damage to the motor system, such as after stroke. ABSTRACT Several paired stimulation paradigms are known to induce plasticity in the motor cortex, reflected by changes in the motor evoked potential (MEP) following the paired stimulation. Motor imagery (MI) is capable of activating the motor system and affecting cortical excitability. We hypothesized that it might be possible to use MI in conjunction with transcranial magnetic stimulation (TMS) to induce plasticity in the human motor system. TMS was delivered to the motor cortex of healthy human subjects, and baseline MEPs recorded from forearm flexor, forearm extensor and intrinsic hand muscles. Subjects were then asked to imagine either wrist flexion or extension movements during TMS delivery (n = 90 trials). Immediately after this intervention, MEP measurement was repeated. Control protocols tested the impact of imagination or TMS alone. Flexion imagination with TMS increased MEPs in flexors and an intrinsic hand muscle. Extensor imagination with TMS increased MEPs in extensor muscles only. The control paradigms did not produce significant changes. We conclude that delivering TMS during MI is capable of inducing plastic changes in the motor system. This new protocol may find utility to enhance functional rehabilitation after brain injury.
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Affiliation(s)
- K M Riashad Foysal
- Institute of Neurosciences, Medical School, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK
| | - Stuart N Baker
- Institute of Neurosciences, Medical School, Framlington Place, Newcastle upon Tyne, NE2 4HH, UK
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Stefano Filho CA, Costa TBS, S Uribe LF, Rodrigues PG, Soriano DC, Attux R, Castellano G. On the (in)efficacy of motor imagery training without feedback and event-related desynchronizations considerations. Biomed Phys Eng Express 2020; 6:035030. [PMID: 33438675 DOI: 10.1088/2057-1976/ab8992] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Motor imagery (MI) constitutes a recurrent strategy for signals generation in brain-computer interfaces (BCIs) - systems that aim to control external devices by directly associating brain responses to distinct commands. Although great improvement has been achieved in MI-BCIs performance over recent years, they still suffer from inter- and intra-subject variability issues. As an attempt to cope with this, some studies have suggested that MI training should aid users to appropriately modulate their response for BCI usage: generally, this training is performed based on the sensorimotor rhythms' modulation over the primary sensorimotor cortex (PMC), with the signal being feedbacked to the user. Nonetheless, recent studies have revisited the actual involvement of the PMC into MI, and little to no attention has been devoted to understanding the participation of other cortical areas into training protocols. Therefore, in this work, our aim was to analyze the response induced by hands MI of 10 healthy subjects in the form of event-related desynchronizations (ERDs) and to assess whether features from beyond the PMC might be useful for hands MI classification. We investigated how this response occurs for distinct frequency intervals between 7-30 Hz, and ex0plored changes in their evocation pattern across 12 MI training sessions without feedback. Overall, we found that ERD patterns occur differently for the frequencies encompassed by the μ and β bands, with its evocation being favored for the first band. Over time, the no-feedback approach was inefficient to aid in enhancing ERD evocation (EO). Moreover, to some extent, EO tends to decrease over blocks within a given run, and runs within an MI session, but remains stable within an MI block. We also found that the C3/C4 pair is not necessarily optimal for data classification, and both spectral and spatial subjects' specificities should be considered when designing training protocols.
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Affiliation(s)
- C A Stefano Filho
- Neurophysics Group, 'Gleb Wataghin' Physics Institute, University of Campinas (UNICAMP), Brazil. Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Brazil
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Power L, Neyedli HF, Boe SG, Bardouille T. Efficacy of low-cost wireless neurofeedback to modulate brain activity during motor imagery. Biomed Phys Eng Express 2020; 6:035024. [DOI: 10.1088/2057-1976/ab872c] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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137
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Cruz-Aguilar MA, Ramírez-Salado I, Hernández-González M, Guevara MA, Del Río JM. Melatonin effects on EEG activity during non-rapid eye movement sleep in mild-to-moderate Alzheimer´s disease: a pilot study. Int J Neurosci 2020; 131:580-590. [PMID: 32228330 DOI: 10.1080/00207454.2020.1750392] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
INTRODUCTION There is evidence to suggest that melatonin diminishes non-rapid eye movement sleep (NREMS) latency in patients with Alzheimer´s disease (AD). However, melatonin's effects on cortical activity during NREMS in AD have not been studied. The objective of this research was to analyze the effects of melatonin on cortical activity during the stages of NREMS in 8 mild-to-moderate AD patients that received 5-mg of fast-release melatonin. METHODS During a single-blind, placebo-controlled crossover study, polysomnographic recordings were obtained from C3-A1, C4-A2, F7-T3, F8-T4, F3-F4 and O1-O2. Also, the relative power (RP) and EEG coherences of the delta, theta, alpha1, alpha2, beta1, beta2 and gamma bands were calculated during NREMS-1, NREMS-2 and NREMS-3. These sleep latencies and all EEG data were then compared between the placebo and melatonin conditions. RESULTS During NREMS-2, a significant RP increase was observed in the theta band of the left-central hemisphere. During NREMS-3, significant RP decreases in the beta bands were recorded in the right-central hemisphere, compared to the placebo group. After melatonin administration, significant decreases of EEG coherences in the beta2, beta1 and gamma bands were observed in the right hemisphere during NREMS-3. DISCUSSION We conclude that short NREMS onset related to melatonin intake in AD patients is associated with a significant RP increase in the theta band and a decrease in RP and EEG coherences in the beta and gamma bands during NREMS-3. These results suggest that the GABAergic pathways are preserved in mild-to-moderate AD.
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Affiliation(s)
- Manuel Alejandro Cruz-Aguilar
- Instituto Nacional de Psiquiatría "Ramón de la Fuente Muñiz," Dirección de Investigaciones en Neurociencias, Laboratorio de Cronobiología y Sueño, CDMX, México
| | - Ignacio Ramírez-Salado
- Instituto Nacional de Psiquiatría "Ramón de la Fuente Muñiz," Dirección de Investigaciones en Neurociencias, Laboratorio de Cronobiología y Sueño, CDMX, México
| | - Marisela Hernández-González
- Instituto de Neurociencias, CUCBA, Laboratorio de Neurofisiología de la Conducta Reproductiva, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Miguel Angel Guevara
- Instituto de Neurociencias, CUCBA, Laboratorio de Correlación Electroencefalográfica y Conducta, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Jahaziel Molina Del Río
- Centro Universitario de los Valles, Departamento de Ciencias de la Salud, Laboratorio de Neuropsicología, División de Estudios de la Salud, Universidad de Guadalajara, Ameca, Jalisco, México
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138
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Gu L, Yu Z, Ma T, Wang H, Li Z, Fan H. EEG-based Classification of Lower Limb Motor Imagery with Brain Network Analysis. Neuroscience 2020; 436:93-109. [PMID: 32283182 DOI: 10.1016/j.neuroscience.2020.04.006] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 03/06/2020] [Accepted: 04/02/2020] [Indexed: 01/06/2023]
Abstract
This study aims to investigate the difference in cortical signal characteristics between the left and right foot imaginary movements and to improve the classification accuracy of the experimental tasks. Raw signals were gathered from 64-channel scalp electroencephalograms of 11 healthy participants. Firstly, the cortical source model was defined with 62 regions of interest over the sensorimotor cortex (nine Brodmann areas). Secondly, functional connectivity was calculated by phase lock value for α and β rhythm networks. Thirdly, network-based statistics were applied to identify whether there existed stable and significant subnetworks that formed between the two types of motor imagery tasks. Meanwhile, ten graph theory indices were investigated for each network by t-test to determine statistical significance between tasks. Finally, sparse multinomial logistic regression (SMLR)-support vector machine (SVM), as a feature selection and classification model, was used to analyze the graph theory features. The specific time-frequency (α event-related desynchronization and β event-related synchronization) difference network between the two tasks was congregated at the midline and demonstrated significant connections in the premotor areas and primary somatosensory cortex. A few of statistically significant differences in the network properties were observed between tasks in the α and β rhythm. The SMLR-SVM classification model achieved fair discrimination accuracy between imaginary movements of the two feet (maximum 75% accuracy rate in single-trial analyses). This study reveals the network mechanism of the discrimination of the left and right foot motor imagery, which can provide a novel avenue for the BCI system by unilateral lower limb motor imagery.
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Affiliation(s)
- Lingyun Gu
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, PR China
| | - Zhenhua Yu
- College of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an 710054, Shanxi, PR China
| | - Tian Ma
- College of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an 710054, Shanxi, PR China
| | - Haixian Wang
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, PR China.
| | - Zhanli Li
- College of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an 710054, Shanxi, PR China.
| | - Hui Fan
- Co-innovation Center of Shandong Colleges and Universities: Future Intelligent Computing, Shandong Technology and Business University, Yantai 264005, Shandong, PR China
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139
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Foldes ST, Boninger ML, Weber DJ, Collinger JL. Effects of MEG-based neurofeedback for hand rehabilitation after tetraplegia: preliminary findings in cortical modulations and grip strength. J Neural Eng 2020; 17:026019. [PMID: 32135525 DOI: 10.1088/1741-2552/ab7cfb] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Neurofeedback (NF) trains people to volitionally modulate their cortical activity to affect a behavioral outcome. We evaluated the feasibility of using NF to improve hand function after chronic cervical-level spinal cord injury (SCI) using biologically-relevant visual feedback of motor-related brain activity and an intuitive control scheme. APPROACH The NF system acquired magnetoencephalography (MEG) data in real-time to provide feedback of event-related desynchronization (ERD) measured over the sensorimotor cortex during attempted hand grasping. During brain control, stronger ERD resulting from attempted grasping drove the virtual hand towards a more closed grasp, while less ERD drove the hand more open. MAIN RESULTS Eight individuals with partial or complete hand impairment due to chronic SCI controlled the NF to perform a grasping task that increased in difficulty as the participants achieved success. During their first NF session, participants achieved an average success rate of 63.7 ± 6.4% (chance level of 13.9%). After as few as one intervention session, four of the seven individuals evaluated for ERD changes had significantly strengthened ERD and three of the four participants with measurable grip strength prior to NF had increased grip strength. Interestingly, both individuals who participated in a longer-term study (i.e. >8 NF sessions) had improved grip strength and significantly strengthened ERD. SIGNIFICANCE This study demonstrates that MEG-based NF training can change brain activity in individuals with hand impairment due to SCI and has the potential to induce acute changes in grip strength. Future studies will evaluate whether neuroplasticity induced with long term NF can improve hand function for those with moderate impairment.
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Affiliation(s)
- Stephen T Foldes
- VA Pittsburgh Healthcare System, Pittsburgh, PA, United States of America. Rehab Neural Engineering Labs, Departments of Physical Medicine and Rehabilitation and Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States of America. Center for the Neural Basis of Cognition, Pittsburgh, PA, United States of America. Barrow Neurological Institute, Phoenix Children's Hospital, Phoenix, AZ, United States of America
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140
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Birba A, Beltrán D, Martorell Caro M, Trevisan P, Kogan B, Sedeño L, Ibáñez A, García AM. Motor-system dynamics during naturalistic reading of action narratives in first and second language. Neuroimage 2020; 216:116820. [PMID: 32278096 PMCID: PMC7412856 DOI: 10.1016/j.neuroimage.2020.116820] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 02/06/2020] [Accepted: 03/27/2020] [Indexed: 12/12/2022] Open
Abstract
Do embodied semantic systems play different roles depending on when and how well a given language was learned? Emergent evidence suggests that this is the case for isolated, decontextualized stimuli, but no study has addressed the issue considering naturalistic narratives. Seeking to bridge this gap, we assessed motor-system dynamics in 26 Spanish-English bilinguals as they engaged in free, unconstrained reading of naturalistic action texts (ATs, highlighting the characters’ movements) and neutral texts (NTs, featuring low motility) in their first and second language (L1, L2). To explore functional connectivity spread over each reading session, we recorded ongoing high-density electroencephalographic signals and subjected them to functional connectivity analysis via a spatial clustering approach. Results showed that, in L1, AT (relative to NT) reading involved increased connectivity between left and right central electrodes consistently implicated in action-related processes, as well as distinct source-level modulations in motor regions. In L2, despite null group-level effects, enhanced motor-related connectivity during AT reading correlated positively with L2 proficiency and negatively with age of L2 learning. Taken together, these findings suggest that action simulations during unconstrained narrative reading involve neural couplings between motor-sensitive mechanisms, in proportion to how consolidated a language is. More generally, such evidence addresses recent calls to test the ecological validity of motor-resonance effects while offering new insights on their relation with experiential variables.
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Affiliation(s)
- Agustina Birba
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina
| | - David Beltrán
- Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, Tenerife, 3820, Spain
| | - Miguel Martorell Caro
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina
| | | | - Boris Kogan
- Institute of Basic and Applied Psychology and Technology (IPSIBAT), National University of Mar del Plata, Buenos Aires, Argentina; National Agency of Scientific and Technological Promotion (ANPCyT), Buenos Aires, Argentina
| | - Lucas Sedeño
- National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina
| | - Agustín Ibáñez
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina; Centre of Excellence in Cognition and Its Disorders, Australian Research Council (ARC), Sydney, NSW, 2109, Australia; Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago de Chile, 7550344, Chile; Universidad Autónoma del Caribe, Barranquilla, 08002, Colombia
| | - Adolfo M García
- Universidad de San Andrés, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, C1425FQB, Argentina; Faculty of Education, National University of Cuyo, Mendoza, M5502JMA, Argentina; Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile.
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141
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Bigirimana AD, Siddique N, Coyle D. Emotion-Inducing Imagery Versus Motor Imagery for a Brain-Computer Interface. IEEE Trans Neural Syst Rehabil Eng 2020; 28:850-859. [PMID: 32149645 DOI: 10.1109/tnsre.2020.2978951] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Neural correlates of intentionally induced human emotions may offer alternative imagery strategies to control brain-computer interface (BCI) applications. In this paper, a novel BCI control strategy i.e., imagining fictional or recalling mnemonic sad and happy events, emotion-inducing imagery (EII), is compared to motor imagery (MI) in a study involving multiple sessions using a two-class electroencephalogram (EEG)-based BCI paradigm with 12 participants. The BCI setup enabled online continuous visual feedback presentation in a game involving one-dimensional control of a game character. MI and EII are compared across different signal-processing frameworks which are based on neural-time-series-prediction-preprocessing (NTSPP), filter bank common spatial patterns (FBCSP) and hemispheric asymmetry (ASYM). Online single-trial classification accuracies (CA) results indicate that MI performance across all participants is 77.54% compared to EII performance of 68.78% ( ). The results show that an ensemble of the NTSPP, FBCSP and ASYM frameworks maximizes performance for EII with average CA of 71.64% across all participants. Furthermore, the participants' subjective responses indicate that they preferred MI over emotion-inducing imagery (EII) in controlling the game character, and MI was perceived to offer most control over the game character. The results suggest that EII is not a viable alternative to MI for the majority of participants in this study but may be an alternative imagery for a subset of BCI users based on acceptable EII performance (CA >70%) observed for some participants.
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142
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Orlandi A, Arno E, Proverbio AM. The Effect of Expertise on Kinesthetic Motor Imagery of Complex Actions. Brain Topogr 2020; 33:238-254. [PMID: 32112306 DOI: 10.1007/s10548-020-00760-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 02/23/2020] [Indexed: 12/25/2022]
Abstract
The ability to mentally simulate an action by recalling the body sensations relative to the real execution is referred to as kinesthetic motor imagery (MI). Frontal and parietal motor-related brain regions are generally engaged during MI. The present study aimed to investigate the time course and neural correlates of complex action imagery and possible effects of expertise on the underlying action representation processes. Professional ballet dancers and controls were presented with effortful and effortless ballet steps and instructed to mentally reproduce each movement during EEG recording. Time-locked MI was associated with an Anterior Negativity (AN) component (400-550 ms) that was larger in dancers relative to controls. The AN was differentially modulated by the motor content (effort) as a function of ballet expertise. It was more negative in response to effortful (than effortless) movements in control participants only. This effect also had a frontal distribution in controls and a centro-parietal distribution in dancers, as shown by the topographic maps of the scalp voltage. The source reconstruction (swLORETA) of the recorded potentials in the AN time-window showed enhanced engagement of prefrontal regions in controls (BA 10/47) relative to dancers, and occipitotemporal (BA 20) and bilateral sensorimotor areas in dancers (BA6/40) compared with controls. This evidence seems to suggest that kinesthetic MI of complex action relied on visuomotor simulation processes in participants with acquired dance expertise. Simultaneously, increased cognitive demands occurred in participants lacking in motor knowledge with the specific action. Hence, professional dance training may lead to refined action representation processes.
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Affiliation(s)
- Andrea Orlandi
- Department of Psychology, Neuro-MI, Milan Center for Neuroscience, University of Milano - Bicocca, Milan, Italy.
- Department of Psychology, Sapienza University of Rome, Via dei Marsi 78, 00185, Rome, Italy.
| | - Elisa Arno
- Department of Psychology, Neuro-MI, Milan Center for Neuroscience, University of Milano - Bicocca, Milan, Italy
| | - Alice Mado Proverbio
- Department of Psychology, Neuro-MI, Milan Center for Neuroscience, University of Milano - Bicocca, Milan, Italy
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Juliano JM, Spicer RP, Vourvopoulos A, Lefebvre S, Jann K, Ard T, Santarnecchi E, Krum DM, Liew SL. Embodiment Is Related to Better Performance on a Brain-Computer Interface in Immersive Virtual Reality: A Pilot Study. SENSORS (BASEL, SWITZERLAND) 2020; 20:E1204. [PMID: 32098317 PMCID: PMC7070491 DOI: 10.3390/s20041204] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Revised: 02/19/2020] [Accepted: 02/19/2020] [Indexed: 01/25/2023]
Abstract
Electroencephalography (EEG)-based brain-computer interfaces (BCIs) for motor rehabilitation aim to "close the loop" between attempted motor commands and sensory feedback by providing supplemental information when individuals successfully achieve specific brain patterns. Existing EEG-based BCIs use various displays to provide feedback, ranging from displays considered more immersive (e.g., head-mounted display virtual reality (HMD-VR)) to displays considered less immersive (e.g., computer screens). However, it is not clear whether more immersive displays improve neurofeedback performance and whether there are individual performance differences in HMD-VR versus screen-based neurofeedback. In this pilot study, we compared neurofeedback performance in HMD-VR versus a computer screen in 12 healthy individuals and examined whether individual differences on two measures (i.e., presence, embodiment) were related to neurofeedback performance in either environment. We found that, while participants' performance on the BCI was similar between display conditions, the participants' reported levels of embodiment were significantly different. Specifically, participants experienced higher levels of embodiment in HMD-VR compared to a computer screen. We further found that reported levels of embodiment positively correlated with neurofeedback performance only in HMD-VR. Overall, these preliminary results suggest that embodiment may relate to better performance on EEG-based BCIs and that HMD-VR may increase embodiment compared to computer screens.
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Affiliation(s)
- Julia M. Juliano
- Neural Plasticity and Neurorehabilitation Laboratory, Neuroscience Graduate Program, University of Southern California, Los Angeles, CA 90089, USA;
| | - Ryan P. Spicer
- Institute for Creative Technologies, University of Southern California, Playa Vista, CA 90094, USA; (R.P.S.); (D.M.K.)
| | - Athanasios Vourvopoulos
- Neural Plasticity and Neurorehabilitation Laboratory, Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA; (A.V.); (S.L.)
| | - Stephanie Lefebvre
- Neural Plasticity and Neurorehabilitation Laboratory, Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA; (A.V.); (S.L.)
| | - Kay Jann
- USC Stevens Neuroimaging and Informatics Institute, Department of Neurology, University of Southern California, Los Angeles, CA 90033, USA; (K.J.); (T.A.)
| | - Tyler Ard
- USC Stevens Neuroimaging and Informatics Institute, Department of Neurology, University of Southern California, Los Angeles, CA 90033, USA; (K.J.); (T.A.)
| | - Emiliano Santarnecchi
- Berenson-Allen Center for Non-Invasive Brain Stimulation and Division of Cognitive Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA;
| | - David M. Krum
- Institute for Creative Technologies, University of Southern California, Playa Vista, CA 90094, USA; (R.P.S.); (D.M.K.)
| | - Sook-Lei Liew
- Neural Plasticity and Neurorehabilitation Laboratory, Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA 90089, USA; (A.V.); (S.L.)
- USC Stevens Neuroimaging and Informatics Institute, Department of Neurology, University of Southern California, Los Angeles, CA 90033, USA; (K.J.); (T.A.)
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144
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The effects of handedness on sensorimotor rhythm desynchronization and motor-imagery BCI control. Sci Rep 2020; 10:2087. [PMID: 32034277 PMCID: PMC7005877 DOI: 10.1038/s41598-020-59222-w] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 01/27/2020] [Indexed: 11/17/2022] Open
Abstract
Brain–computer interfaces (BCIs) allow control of various applications or external devices solely by brain activity, e.g., measured by electroencephalography during motor imagery. Many users are unable to modulate their brain activity sufficiently in order to control a BCI. Most of the studies have been focusing on improving the accuracy of BCI control through advances in signal processing and BCI protocol modification. However, some research suggests that motor skills and physiological factors may affect BCI performance as well. Previous studies have indicated that there is differential lateralization of hand movements’ neural representation in right- and left-handed individuals. However, the effects of handedness on sensorimotor rhythm (SMR) distribution and BCI control have not been investigated in detail yet. Our study aims to fill this gap, by comparing the SMR patterns during motor imagery and real-feedback BCI control in right- (N = 20) and left-handers (N = 20). The results of our study show that the lateralization of SMR during a motor imagery task differs according to handedness. Left-handers present lower accuracy during BCI performance (single session) and weaker SMR suppression in the alpha band (8–13 Hz) during mental simulation of left-hand movements. Consequently, to improve BCI control, the user’s training should take into account individual differences in hand dominance.
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145
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Quiles E, Suay F, Candela G, Chio N, Jiménez M, Álvarez-Kurogi L. Low-Cost Robotic Guide Based on a Motor Imagery Brain-Computer Interface for Arm Assisted Rehabilitation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17030699. [PMID: 31973155 PMCID: PMC7036782 DOI: 10.3390/ijerph17030699] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 01/10/2020] [Accepted: 01/17/2020] [Indexed: 12/26/2022]
Abstract
Motor imagery has been suggested as an efficient alternative to improve the rehabilitation process of affected limbs. In this study, a low-cost robotic guide is implemented so that linear position can be controlled via the user’s motor imagination of movement intention. The patient can use this device to move the arm attached to the guide according to their own intentions. The first objective of this study was to check the feasibility and safety of the designed robotic guide controlled via a motor imagery (MI)-based brain–computer interface (MI-BCI) in healthy individuals, with the ultimate aim to apply it to rehabilitation patients. The second objective was to determine which are the most convenient MI strategies to control the different assisted rehabilitation arm movements. The results of this study show a better performance when the BCI task is controlled with an action–action MI strategy versus an action–relaxation one. No statistically significant difference was found between the two action–action MI strategies.
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Affiliation(s)
- Eduardo Quiles
- Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain;
- Correspondence: ; Tel.: +34-96-387-7007 (ext. 75793)
| | - Ferran Suay
- Departament de Psicobiologia, Facultat de Psicologia, Universitat de València, 46010 València, Spain; (F.S.); (G.C.)
| | - Gemma Candela
- Departament de Psicobiologia, Facultat de Psicologia, Universitat de València, 46010 València, Spain; (F.S.); (G.C.)
| | - Nayibe Chio
- Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain;
- Facultad de Ingeniería, Ingeniería Mecatrónica, Universidad Autónoma de Bucaramanga, Bucaramanga 680003, Colombia
| | - Manuel Jiménez
- Facultad de Educación, Universidad Internacional de la Rioja, 26006 Logroño, Spain; (M.J.); (L.Á.-K.)
| | - Leandro Álvarez-Kurogi
- Facultad de Educación, Universidad Internacional de la Rioja, 26006 Logroño, Spain; (M.J.); (L.Á.-K.)
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146
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Zhang X, Guo Y, Gao B, Long J. Enhancing Mu-based BCI Performance with Rhythmic Electrical Stimulation at Alpha Frequency. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:5540-5543. [PMID: 31947109 DOI: 10.1109/embc.2019.8857321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The accuracy of brain-computer interfaces (BCIs) is important for effective communication and control. The mu-based BCI is one of the widely used systems, of which the related methods to improve users' accuracy is still poorly studied. Here, we examined the way to enhance the mu-based BCI performance by rhythmic electrical stimulation on the ulnar nerve at the contralateral wrist at the alpha frequency (10 Hz) during the left-and right-hand motor imagery. Time-frequency analysis, spectral analysis, and discriminant analysis were performed on the electroencephalograph (EEG) data before and after the intervention of electrical stimulation in 9 healthy subjects. We found that the ERD/S on the somatosensory and motor cortex during left-or right-hand imagination was more obvious at the mu rhythm after intervention. Furthermore, average classification accuracy between left-and right-hand imagery significantly increased from 78.43% to 88.17% after intervention, suggesting that the electrical stimulation at alpha frequency effectively regulates the brain's mu rhythm and enhances the discriminability of the left-hand and right-hand imagination tasks. These results provide evidence that the electrical stimulation at the alpha frequency is an effective way to improve the mu-based BCI performance.
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147
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Abstract
The electroencephalogram (EEG) was invented almost 100 years ago and is still a method of choice for many research questions, even applications-from functional brain imaging in neuroscientific investigations during movement to real-time applications like brain-computer interfacing. This chapter gives some background information on the establishment and properties of the EEG. This chapter starts with a closer look at the sources of EEG at a micro or neuronal level, followed by recording techniques, types of electrodes, and common EEG artifacts. Then an overview on EEG phenomena, namely, spontaneous EEG and event-related potentials build the middle part of this chapter. The last part discusses brain signals, which are used in current BCI research, including short descriptions and examples of applications.
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Affiliation(s)
- Gernot R Müller-Putz
- Institute for Neural Engineering, Laboratory of Brain-Computer Interfaces, Graz University of Technology, Graz, Austria.
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148
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Lu RR, Zheng MX, Li J, Gao TH, Hua XY, Liu G, Huang SH, Xu JG, Wu Y. Motor imagery based brain-computer interface control of continuous passive motion for wrist extension recovery in chronic stroke patients. Neurosci Lett 2019; 718:134727. [PMID: 31887332 DOI: 10.1016/j.neulet.2019.134727] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Revised: 12/13/2019] [Accepted: 12/26/2019] [Indexed: 11/17/2022]
Abstract
Motor recovery of wrist and fingers is still a great challenge for chronic stroke survivors. The present study aimed to verify the efficiency of motor imagery based brain-computer interface (BCI) control of continuous passive motion (CPM) in the recovery of wrist extension due to stroke. An observational study was conducted in 26 chronic stroke patients, aged 49.0 ± 15.4 years, with upper extremity motor impairment. All patients showed no wrist extension recovery. A 24-channel highresolution electroencephalogram (EEG) system was used to acquire cortical signal while they were imagining extension of the affected wrist. Then, 20 sessions of BCI-driven CPM training were carried out for 6 weeks. Primary outcome was the increase of active range of motion (ROM) of the affected wrist from the baseline to final evaluation. Improvement of modified Barthel Index, EEG classification and motor imagery pattern of wrist extension were recorded as secondary outcomes. Twenty-one patients finally passed the EEG screening and completed all the BCI-driven CPM trainings. From baseline to the final evaluation, the increase of active ROM of the affected wrists was (24.05 ± 14.46)˚. The increase of modified Barthel Index was 3.10 ± 4.02 points. But no statistical difference was detected between the baseline and final evaluations (P > 0.05). Both EEG classification and motor imagery pattern improved. The present study demonstrated beneficial outcomes of MI-based BCI control of CPM training in motor recovery of wrist extension using motor imagery signal of brain in chronic stroke patients.
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Affiliation(s)
- Rong-Rong Lu
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Jie Li
- Department of Computer Science and Technology, Tongji University, No. 4800 Cao'an Highway, Shanghai 200092, China
| | - Tian-Hao Gao
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Xu-Yun Hua
- Department of Traumatology and Orthopedics, Yueyang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Gang Liu
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Song-Hua Huang
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
| | - Yi Wu
- Department of Rehabilitation, Huashan Hospital, Fudan University, No. 12 Middle Wulumuqi Road, Shanghai 200040, China.
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149
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Hosni SM, Deligani RJ, Zisk A, McLinden J, Borgheai SB, Shahriari Y. An exploration of neural dynamics of motor imagery for people with amyotrophic lateral sclerosis. J Neural Eng 2019; 17:016005. [PMID: 31597125 DOI: 10.1088/1741-2552/ab4c75] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Studies of the neuropathological effects of amyotrophic lateral sclerosis (ALS) on the underlying motor system have investigated abnormalities in the magnitude and timing of the event-related desynchronization (ERD) and synchronization (ERS) during motor execution (ME). However, the spatio-spectral-temporal dynamics of these sensorimotor oscillations during motor imagery (MI) have not been fully explored for these patients. This study explores the neural dynamics of sensorimotor oscillations for ALS patients during MI by quantifying ERD/ERS features in frequency, time, and space. APPROACH Electroencephalogram (EEG) data were recorded from six patients with ALS and 11 age-matched healthy controls (HC) while performing a MI task. ERD/ERS features were extracted using wavelet-based time-frequency analysis and compared between the two groups to quantify the abnormal neural dynamics of ALS in terms of both time and frequency. Topographic correlation analysis was conducted to compare the localization of MI activity between groups and to identify subject-specific frequencies in the µ and β frequency bands. MAIN RESULTS Overall, reduced and delayed ERD was observed for ALS patients, particularly during right-hand MI. ERD features were also correlated with ALS clinical scores, specifically disease duration, bulbar, and cognitive functions. SIGNIFICANCE The analyses in this study quantify abnormalities in the magnitude and timing of sensorimotor oscillations for ALS patients during MI tasks. Our findings reveal notable differences between MI and existing results on ME in ALS. The observed alterations are speculated to reflect disruptions in the underlying cortical networks involved in MI functions. Quantifying the neural dynamics of MI plays an important role in the study of EEG-based cortical markers for ALS.
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Affiliation(s)
- Sarah M Hosni
- Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States of America
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150
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Nierula B, Spanlang B, Martini M, Borrell M, Nikulin VV, Sanchez-Vives MV. Agency and responsibility over virtual movements controlled through different paradigms of brain-computer interface. J Physiol 2019; 599:2419-2434. [PMID: 31647122 DOI: 10.1113/jp278167] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2019] [Accepted: 10/16/2019] [Indexed: 11/08/2022] Open
Abstract
KEY POINTS Embodiment of a virtual body was induced and its movements were controlled by two different brain-computer interface (BCI) paradigms - one based on signals from sensorimotor versus one from visual cortical areas. BCI-control of movements engenders agency, but not equally for all paradigms. Cortical sensorimotor activation correlates with agency and responsibility. This has significant implications for neurological rehabilitation and neuroethics. ABSTRACT Agency is the attribution of an action to the self and is a prerequisite for experiencing responsibility over its consequences. Here we investigated agency and responsibility by studying the control of movements of an embodied avatar, via brain-computer interface (BCI) technology, in immersive virtual reality. After induction of virtual body ownership by visuomotor correlations, healthy participants performed a motor task with their virtual body. We compared the passive observation of the subject's 'own' virtual arm performing the task with (1) the control of the movement through activation of sensorimotor areas (motor imagery) and (2) the control of the movement through activation of visual areas (steady-state visually evoked potentials). The latter two conditions were carried out using a BCI and both shared the intention and the resulting action. We found that BCI-control of movements engenders the sense of agency, which is strongest for sensorimotor area activation. Furthermore, increased activity of sensorimotor areas, as measured using EEG, correlates with levels of agency and responsibility. We discuss the implications of these results for the neural basis of agency.
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Affiliation(s)
- Birgit Nierula
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Event-Lab, Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, Barcelona, Spain
| | - Bernhard Spanlang
- Event-Lab, Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, Barcelona, Spain
| | - Matteo Martini
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Event-Lab, Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, Barcelona, Spain
| | - Mireia Borrell
- Event-Lab, Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, Barcelona, Spain
| | - Vadim V Nikulin
- Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Center for Cognition & Decision Making, National Research University Higher School of Economics, Moscow, Russian Federation
| | - Maria V Sanchez-Vives
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Event-Lab, Department of Clinical Psychology and Psychobiology, Universitat de Barcelona, Barcelona, Spain.,ICREA, Barcelona, Spain.,Departamento de Psicología Básica, Universitat de Barcelona, Barcelona, Spain
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