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Sánchez Cuesta FJ, González-Zamorano Y, Moreno-Verdú M, Vourvopoulos A, Serrano IJ, Del Castillo-Sobrino MD, Figueiredo P, Romero JP. Effects of motor imagery-based neurofeedback training after bilateral repetitive transcranial magnetic stimulation on post-stroke upper limb motor function: an exploratory crossover clinical trial. J Rehabil Med 2024; 56:jrm18253. [PMID: 38450442 PMCID: PMC10938141 DOI: 10.2340/jrm.v56.18253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 01/23/2024] [Indexed: 03/08/2024] Open
Abstract
OBJECTIVE To examine the clinical effects of combining motor imagery-based neurofeedback training with bilateral repetitive transcranial magnetic stimulation for upper limb motor function in subacute and chronic stroke. DESIGN Clinical trial following an AB/BA crossover design with counterbalanced assignment. SUBJECTS Twenty individuals with subacute (n = 4) or chronic stroke (n = 16). METHODS Ten consecutive sessions of bilateral repetitive transcranial magnetic stimulation alone (therapy A) were compared vs a combination of10 consecutive sessions of bilateral repetitive transcranial magnetic stimulation with 12 non-consecutive sessions of motor imagery-based neurofeedback training (therapy B). Patients received both therapies (1-month washout period), in sequence AB or BA. Participants were assessed before and after each therapy and at 15-days follow-up, using the Fugl-Meyer Assessment-upper limb, hand-grip strength, and the Nottingham Sensory Assessment as primary outcome measures. RESULTS Both therapies resulted in improved functionality and sensory function. Therapy B consistently exhibited superior effects compared with therapy A, according to Fugl-Meyer Assessment and tactile and kinaesthetic sensory function across multiple time-points, irrespective of treatment sequence. No statistically significant differences between therapies were found for hand-grip strength. CONCLUSION Following subacute and chronic stroke, integrating bilateral repetitive transcranial magnetic stimulation and motor imagery-based neurofeedback training has the potential to enhance functional performance compared with using bilateral repetitive transcranial magnetic stimulation alone in upper limb recovery.
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Affiliation(s)
- Francisco José Sánchez Cuesta
- Faculty of Experimental Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain
| | - Yeray González-Zamorano
- Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Department of Physiotherapy, Occupational Therapy, Rehabilitation and Physical Medicine, King Juan Carlos University, Alcorcón, Spain; Cognitive Neuroscience, Pain, and Rehabilitation Research Group (NECODOR), Faculty of Health Sciences, Rey Juan Carlos University, Madrid, Spain
| | - Marcos Moreno-Verdú
- Faculty of Experimental Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain.
| | - Athanasios Vourvopoulos
- Institute for Systems and Robotics-Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Ignacio J Serrano
- Neural and Cognitive Engineering group, Centre for Automation and Robotics (CAR) CSIC-UPM, Arganda del Rey, Madrid, Spain
| | | | - Patrícia Figueiredo
- Institute for Systems and Robotics-Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Juan Pablo Romero
- Faculty of Experimental Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Injury and Movement Disorders Neurorehabilitation Group (GINDAT), Institute of Life Sciences, Francisco de Vitoria University, Pozuelo de Alarcón, Spain; Brain Damage Unit, Beata María Ana Hospital, Madrid, Spain.
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Fleury M, Figueiredo P, Vourvopoulos A, Lécuyer A. Two is better? combining EEG and fMRI for BCI and neurofeedback: a systematic review. J Neural Eng 2023; 20:051003. [PMID: 37879343 DOI: 10.1088/1741-2552/ad06e1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 10/25/2023] [Indexed: 10/27/2023]
Abstract
Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are two commonly used non-invasive techniques for measuring brain activity in neuroscience and brain-computer interfaces (BCI).Objective. In this review, we focus on the use of EEG and fMRI in neurofeedback (NF) and discuss the challenges of combining the two modalities to improve understanding of brain activity and achieve more effective clinical outcomes. Advanced technologies have been developed to simultaneously record EEG and fMRI signals to provide a better understanding of the relationship between the two modalities. However, the complexity of brain processes and the heterogeneous nature of EEG and fMRI present challenges in extracting useful information from the combined data.Approach. We will survey existing EEG-fMRI combinations and recent studies that exploit EEG-fMRI in NF, highlighting the experimental and technical challenges.Main results. We made a classification of the different combination of EEG-fMRI for NF, we provide a review of multimodal analysis methods for EEG-fMRI features. We also survey the current state of research on EEG-fMRI in the different existing NF paradigms. Finally, we also identify some of the remaining challenges in this field.Significance. By exploring EEG-fMRI combinations in NF, we are advancing our knowledge of brain function and its applications in clinical settings. As such, this review serves as a valuable resource for researchers, clinicians, and engineers working in the field of neural engineering and rehabilitation, highlighting the promising future of EEG-fMRI-based NF.
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Affiliation(s)
- Mathis Fleury
- Univ Rennes, Inria, CNRS, Inserm, Empenn ERL U1228 Rennes, France
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Athanasios Vourvopoulos
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Anatole Lécuyer
- Univ Rennes, Inria, CNRS, Inserm, Empenn ERL U1228 Rennes, France
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Caetano G, Esteves I, Vourvopoulos A, Fleury M, Figueiredo P. NeuXus open-source tool for real-time artifact reduction in simultaneous EEG-fMRI. Neuroimage 2023; 280:120353. [PMID: 37652114 DOI: 10.1016/j.neuroimage.2023.120353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 09/02/2023] Open
Abstract
The simultaneous acquisition of electroencephalography and functional magnetic resonance imaging (EEG-fMRI) allows the complementary study of the brain's electrophysiology and hemodynamics with high temporal and spatial resolution. One application with great potential is neurofeedback training of targeted brain activity, based on the real-time analysis of the EEG and/or fMRI signals. This depends on the ability to reduce in real time the severe artifacts affecting the EEG signal acquired with fMRI, mainly the gradient and pulse artifacts. A few methods have been proposed for this purpose, but they are either slow, hardware-dependent, publicly unavailable, or proprietary software. Here, we present a fully open-source and publicly available tool for real-time EEG artifact reduction in simultaneous EEG-fMRI recordings that is fast and applicable to any hardware. Our tool is integrated in the Python toolbox NeuXus for real-time EEG processing and adapts to a real-time scenario well-established artifact average subtraction methods combined with a long short-term memory network for R peak detection. We benchmarked NeuXus on three different datasets, in terms of artifact power reduction and background signal preservation in resting state, alpha-band power reactivity to eyes closure, and event-related desynchronization during motor imagery. We showed that NeuXus performed at least as well as the only available real-time tool for conventional hardware setups (BrainVision's RecView) and a well-established offline tool (EEGLAB's FMRIB plugin). We also demonstrated NeuXus' real-time ability by reporting execution times under 250 ms. In conclusion, we present and validate the first fully open-source and hardware-independent solution for real-time artifact reduction in simultaneous EEG-fMRI studies.
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Affiliation(s)
- Gustavo Caetano
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Inês Esteves
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Athanasios Vourvopoulos
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Mathis Fleury
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico - Universidade de Lisboa, Lisbon, Portugal.
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Nunes JD, Vourvopoulos A, Blanco-Mora DA, Jorge C, Fernandes JC, Bermudez i Badia S, Figueiredo P. Brain activation by a VR-based motor imagery and observation task: An fMRI study. PLoS One 2023; 18:e0291528. [PMID: 37756271 PMCID: PMC10529559 DOI: 10.1371/journal.pone.0291528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 08/07/2023] [Indexed: 09/29/2023] Open
Abstract
Training motor imagery (MI) and motor observation (MO) tasks is being intensively exploited to promote brain plasticity in the context of post-stroke rehabilitation strategies. This may benefit from the use of closed-loop neurofeedback, embedded in brain-computer interfaces (BCI's) to provide an alternative non-muscular channel, which may be further augmented through embodied feedback delivered through virtual reality (VR). Here, we used functional magnetic resonance imaging (fMRI) in a group of healthy adults to map brain activation elicited by an ecologically-valid task based on a VR-BCI paradigm called NeuRow, whereby participants perform MI of rowing with the left or right arm (i.e., MI), while observing the corresponding movement of the virtual arm of an avatar (i.e., MO), on the same side, in a first-person perspective. We found that this MI-MO task elicited stronger brain activation when compared with a conventional MI-only task based on the Graz BCI paradigm, as well as to an overt motor execution task. It recruited large portions of the parietal and occipital cortices in addition to the somatomotor and premotor cortices, including the mirror neuron system (MNS), associated with action observation, as well as visual areas related with visual attention and motion processing. Overall, our findings suggest that the virtual representation of the arms in an ecologically-valid MI-MO task engage the brain beyond conventional MI tasks, which we propose could be explored for more effective neurorehabilitation protocols.
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Affiliation(s)
- João D. Nunes
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, and Faculty of Engineering, University of Porto, Porto, Portugal
| | - Athanasios Vourvopoulos
- Institute for Systems and Robotics - Lisboa, and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Diego Andrés Blanco-Mora
- Faculdade de Ciências Exatas e da Engenharia, N-LINCS Madeira — ARDITI, Universidade da Madeira, Funchal, Portugal
| | - Carolina Jorge
- Faculdade de Ciências Exatas e da Engenharia, N-LINCS Madeira — ARDITI, Universidade da Madeira, Funchal, Portugal
| | - Jean-Claude Fernandes
- Central Hospital of Funchal, Physical Medicine and Rehabilitation Service, Funchal, Portugal
| | - Sergi Bermudez i Badia
- Faculdade de Ciências Exatas e da Engenharia, N-LINCS Madeira — ARDITI, Universidade da Madeira, Funchal, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics - Lisboa, and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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Vourvopoulos A, Fleury M, Tonin L, Perdikis S. Editorial: Neurotechnologies and brain-computer interaction for neurorehabilitation. Front Neurogenom 2023; 4:1203934. [PMID: 38234475 PMCID: PMC10790924 DOI: 10.3389/fnrgo.2023.1203934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 06/08/2023] [Indexed: 01/19/2024]
Affiliation(s)
- Athanasios Vourvopoulos
- Department of Bioengineering, Institute for Systems and Robotics - Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Mathis Fleury
- Department of Bioengineering, Institute for Systems and Robotics - Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Luca Tonin
- Department of Information Engineering, Università degli Studi di Padova, Padua, Italy
| | - Serafeim Perdikis
- Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom
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Farabbi A, Figueiredo P, Ghiringhelli F, Mainardi L, Sanches JM, Moreno P, Santos-Victor J, Vourvopoulos A. Investigating the impact of visual perspective in a motor imagery-based brain-robot interaction: A pilot study with healthy participants. Front Neurogenom 2023; 4:1080794. [PMID: 38234500 PMCID: PMC10790830 DOI: 10.3389/fnrgo.2023.1080794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 03/08/2023] [Indexed: 01/19/2024]
Abstract
Introduction Motor Imagery (MI)-based Brain Computer Interfaces (BCI) have raised gained attention for their use in rehabilitation therapies since they allow controlling an external device by using brain activity, in this way promoting brain plasticity mechanisms that could lead to motor recovery. Specifically, rehabilitation robotics can provide precision and consistency for movement exercises, while embodied robotics could provide sensory feedback that can help patients improve their motor skills and coordination. However, it is still not clear whether different types of visual feedback may affect the elicited brain response and hence the effectiveness of MI-BCI for rehabilitation. Methods In this paper, we compare two visual feedback strategies based on controlling the movement of robotic arms through a MI-BCI system: 1) first-person perspective, with visual information that the user receives when they view the robot arms from their own perspective; and 2) third-person perspective, whereby the subjects observe the robot from an external perspective. We studied 10 healthy subjects over three consecutive sessions. The electroencephalographic (EEG) signals were recorded and evaluated in terms of the power of the sensorimotor rhythms, as well as their lateralization, and spatial distribution. Results Our results show that both feedback perspectives can elicit motor-related brain responses, but without any significant differences between them. Moreover, the evoked responses remained consistent across all sessions, showing no significant differences between the first and the last session. Discussion Overall, these results suggest that the type of perspective may not influence the brain responses during a MI- BCI task based on a robotic feedback, although, due to the limited sample size, more evidence is required. Finally, this study resulted into the production of 180 labeled MI EEG datasets, publicly available for research purposes.
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Affiliation(s)
- Andrea Farabbi
- B3Lab, Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy
| | - Patricia Figueiredo
- Institute for Systems and Robotics-Lisboa, Instituto Superior Tecnico, Lisbon, Portugal
| | - Fabiola Ghiringhelli
- B3Lab, Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy
| | - Luca Mainardi
- B3Lab, Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy
| | - Joao Miguel Sanches
- Institute for Systems and Robotics-Lisboa, Instituto Superior Tecnico, Lisbon, Portugal
| | - Plinio Moreno
- Institute for Systems and Robotics-Lisboa, Instituto Superior Tecnico, Lisbon, Portugal
| | - Jose Santos-Victor
- Institute for Systems and Robotics-Lisboa, Instituto Superior Tecnico, Lisbon, Portugal
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Blanco-Mora D, Aldridge A, Jorge C, Vourvopoulos A, Figueiredo P, Bermúdez I Badia S. Impact of age, VR, immersion, and spatial resolution on classifier performance for a MI-based BCI. Brain-Computer Interfaces 2022. [DOI: 10.1080/2326263x.2022.2054606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- D.A. Blanco-Mora
- NeuroRehabLab, Madeira Interactive Techonologies Institute, Universidade da Madeira, Funchal, Portugal
| | - A. Aldridge
- Department of Computer Science and Engineering, Mississippi State University, Starkville, Missippi, USA
| | - C. Jorge
- NeuroRehabLab, Madeira Interactive Techonologies Institute, Universidade da Madeira, Funchal, Portugal
| | - A. Vourvopoulos
- Institute for Systems and Robotics, Lisboa,Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - P. Figueiredo
- Institute for Systems and Robotics, Lisboa,Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - S. Bermúdez I Badia
- Faculdade de Ciências Exatas e da Engenharia, Universidade da Madeira, Funchal, Portugal
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Sánchez Cuesta FJ, Ferrer AA, Zamorano YG, Vourvopoulos A, Bermúdez i Badia S, Figuereido P, Serrano JI, Romero Muñoz JP. Clinical effects of immersive multimodal bci-vr training after bilateral stimulation with rtms on upper limb motor recovery after stroke. Brain Stimul 2021. [DOI: 10.1016/j.brs.2021.10.132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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Sánchez-Cuesta FJ, Arroyo-Ferrer A, González-Zamorano Y, Vourvopoulos A, Badia SBI, Figuereido P, Serrano JI, Romero JP. Clinical Effects of Immersive Multimodal BCI-VR Training after Bilateral Neuromodulation with rTMS on Upper Limb Motor Recovery after Stroke. A Study Protocol for a Randomized Controlled Trial. Medicina (Kaunas) 2021; 57:736. [PMID: 34440942 PMCID: PMC8401798 DOI: 10.3390/medicina57080736] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 07/19/2021] [Indexed: 01/31/2023]
Abstract
Background and Objectives: The motor sequelae after a stroke are frequently persistent and cause a high degree of disability. Cortical ischemic or hemorrhagic strokes affecting the cortico-spinal pathways are known to cause a reduction of cortical excitability in the lesioned area not only for the local connectivity impairment but also due to a contralateral hemisphere inhibitory action. Non-invasive brain stimulation using high frequency repetitive magnetic transcranial stimulation (rTMS) over the lesioned hemisphere and contralateral cortical inhibition using low-frequency rTMS have been shown to increase the excitability of the lesioned hemisphere. Mental representation techniques, neurofeedback, and virtual reality have also been shown to increase cortical excitability and complement conventional rehabilitation. Materials and Methods: We aim to carry out a single-blind, randomized, controlled trial aiming to study the efficacy of immersive multimodal Brain-Computer Interfacing-Virtual Reality (BCI-VR) training after bilateral neuromodulation with rTMS on upper limb motor recovery after subacute stroke (>3 months) compared to neuromodulation combined with conventional motor imagery tasks. This study will include 42 subjects in a randomized controlled trial design. The main expected outcomes are changes in the Motricity Index of the Arm (MI), dynamometry of the upper limb, score according to Fugl-Meyer for upper limb (FMA-UE), and changes in the Stroke Impact Scale (SIS). The evaluation will be carried out before the intervention, after each intervention and 15 days after the last session. Conclusions: This trial will show the additive value of VR immersive motor imagery as an adjuvant therapy combined with a known effective neuromodulation approach opening new perspectives for clinical rehabilitation protocols.
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Affiliation(s)
- Francisco José Sánchez-Cuesta
- Facultad de Ciencias Experimentales, Universidad Francisco de Vitoria, 28223 Pozuelo de Alarcón, Spain; (F.J.S.-C.); (A.A.-F.)
| | - Aida Arroyo-Ferrer
- Facultad de Ciencias Experimentales, Universidad Francisco de Vitoria, 28223 Pozuelo de Alarcón, Spain; (F.J.S.-C.); (A.A.-F.)
| | - Yeray González-Zamorano
- Escuela Internacional de Doctorado, Department of Physical Therapy, Occupational Therapy, Rehabilitation and Physical Medicine, Universidad Rey Juan Carlos, 28933 Alcorcón, Spain;
| | - Athanasios Vourvopoulos
- Institute for Systems and Robotics-Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal; (A.V.); (P.F.)
| | - Sergi Bermúdez i Badia
- Faculdade de Ciências Exatas e da Engenharia, Madeira Interactive Technologies Institute, NOVA LINCS, Universidade da Madeira, 9020-105 Funchal, Portugal;
| | - Patricia Figuereido
- Institute for Systems and Robotics-Lisboa, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal; (A.V.); (P.F.)
| | - José Ignacio Serrano
- Neural and Cognitive Engineering Group (gNeC), Centre for Automation and Robotics (CAR), Spanish National Research Council (CSIC-UPM), 28500 Arganda del Rey, Spain;
| | - Juan Pablo Romero
- Facultad de Ciencias Experimentales, Universidad Francisco de Vitoria, 28223 Pozuelo de Alarcón, Spain; (F.J.S.-C.); (A.A.-F.)
- Brain Damage Unit, Beata María Ana Hospital, 28007 Madrid, Spain
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Putze F, Vourvopoulos A, Lécuyer A, Krusienski D, Bermúdez I Badia S, Mullen T, Herff C. Editorial: Brain-Computer Interfaces and Augmented/Virtual Reality. Front Hum Neurosci 2020; 14:144. [PMID: 32477080 PMCID: PMC7235375 DOI: 10.3389/fnhum.2020.00144] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 03/30/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Felix Putze
- Cognitive Systems Lab, University of Bremen, Bremen, Germany
| | | | - Anatole Lécuyer
- Institut National de Recherche en Informatique et en Automatique (INRIA), Rocquencourt, France
| | - Dean Krusienski
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA, United States
| | | | | | - Christian Herff
- Department of Neurosurgery, School of Mental Health and Neurosciences, Maastricht University, Maastricht, Netherlands
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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) 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] [What about the content of this article? (0)] [Affiliation(s)] [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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Bucho T, Caetano G, Vourvopoulos A, Accoto F, Esteves I, I Badia SB, Rosa A, Figueiredo P. Comparison of Visual and Auditory Modalities for Upper-Alpha EEG-Neurofeedback .. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2019:5960-5966. [PMID: 31947205 DOI: 10.1109/embc.2019.8856671] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Electroencephalography (EEG) neurofeedback (NF) training has been shown to produce long-lasting effects on the improvement of cognitive function as well as the normalization of aberrant brain activity in disease. However, the impact of the sensory modality used as the NF reinforcement signal on training effectiveness has not been systematically investigated. In this work, an EEG-based NF-training system was developed targeting the individual upper-alpha (UA) band and using either a visual or an auditory reinforcement signal, so as to compare the effects of the two sensory modalities. Sixteen healthy volunteers were randomly assigned to the Visual or Auditory group, where a radius-varying sphere or a volume-varying sound, respectively, reflected the relative amplitude of UA measured at EEG electrode Cz. Each participant underwent a total of four NF sessions, of approximately 40 min each, on consecutive days. Both groups showed significant increases in UA at Cz within sessions, and also across sessions. Effects subsequent to NF training were also found beyond the target frequency UA and scalp location Cz, namely in the lower-alpha and theta bands and in posterior brain regions, respectively. Only small differences were found on the EEG between the Visual and Auditory groups, suggesting that auditory reinforcement signals may be as effective as the more commonly used visual signals. The use of auditory NF may potentiate training protocols conducted under mobile conditions, which are now possible due to the increasing availability of wireless EEG systems.
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Vourvopoulos A, Jorge C, Abreu R, Figueiredo P, Fernandes JC, Bermúdez I Badia S. Efficacy and Brain Imaging Correlates of an Immersive Motor Imagery BCI-Driven VR System for Upper Limb Motor Rehabilitation: A Clinical Case Report. Front Hum Neurosci 2019; 13:244. [PMID: 31354460 PMCID: PMC6637378 DOI: 10.3389/fnhum.2019.00244] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 06/28/2019] [Indexed: 11/13/2022] Open
Abstract
To maximize brain plasticity after stroke, a plethora of rehabilitation strategies have been explored. These include the use of intensive motor training, motor-imagery (MI), and action-observation (AO). Growing evidence of the positive impact of virtual reality (VR) techniques on recovery following stroke has been shown. However, most VR tools are designed to exploit active movement, and hence patients with low level of motor control cannot fully benefit from them. Consequently, the idea of directly training the central nervous system has been promoted by utilizing MI with electroencephalography (EEG)-based brain-computer interfaces (BCIs). To date, detailed information on which VR strategies lead to successful functional recovery is still largely missing and very little is known on how to optimally integrate EEG-based BCIs and VR paradigms for stroke rehabilitation. The purpose of this study was to examine the efficacy of an EEG-based BCI-VR system using a MI paradigm for post-stroke upper limb rehabilitation on functional assessments, and related changes in MI ability and brain imaging. To achieve this, a 60 years old male chronic stroke patient was recruited. The patient underwent a 3-week intervention in a clinical environment, resulting in 10 BCI-VR training sessions. The patient was assessed before and after intervention, as well as on a one-month follow-up, in terms of clinical scales and brain imaging using functional MRI (fMRI). Consistent with prior research, we found important improvements in upper extremity scores (Fugl-Meyer) and identified increases in brain activation measured by fMRI that suggest neuroplastic changes in brain motor networks. This study expands on the current body of evidence, as more data are needed on the effect of this type of interventions not only on functional improvement but also on the effect of the intervention on plasticity through brain imaging.
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Affiliation(s)
- Athanasios Vourvopoulos
- Neural Plasticity and Neurorehabilitation Laboratory, University of Southern California, Los Angeles, CA, United States
| | - Carolina Jorge
- Madeira Interactive Technologies Institute, Universidade da Madeira, Funchal, Portugal
| | - Rodolfo Abreu
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics, Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Jean-Claude Fernandes
- Central Hospital of Funchal, Physical Medicine and Rehabilitation Service, Funchal, Portugal
| | - Sergi Bermúdez I Badia
- Madeira Interactive Technologies Institute, Universidade da Madeira, Funchal, Portugal.,Faculdade de Ciências Exatas e da Engenharia, Universidade da Madeira, Funchal, Portugal
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Vourvopoulos A, Pardo OM, Lefebvre S, Neureither M, Saldana D, Jahng E, Liew SL. Effects of a Brain-Computer Interface With Virtual Reality (VR) Neurofeedback: A Pilot Study in Chronic Stroke Patients. Front Hum Neurosci 2019; 13:210. [PMID: 31275126 PMCID: PMC6593205 DOI: 10.3389/fnhum.2019.00210] [Citation(s) in RCA: 53] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 06/03/2019] [Indexed: 01/13/2023] Open
Abstract
Rehabilitation for stroke patients with severe motor impairments (e.g., inability to perform wrist or finger extension on the affected side) is burdensome and difficult because most current rehabilitation options require some volitional movement to retrain the affected side. However, although these patients participate in therapy requiring volitional movement, previous research has shown that they may receive modest benefits from action observation, virtual reality (VR), and brain-computer interfaces (BCIs). These approaches have shown some success in strengthening key motor pathways thought to support motor recovery after stroke, in the absence of volitional movement. The purpose of this study was to combine the principles of VR and BCI in a platform called REINVENT and assess its effects on four chronic stroke patients across different levels of motor impairment. REINVENT acquires post-stroke EEG signals that indicate an attempt to move and drives the movement of a virtual avatar arm, allowing patient-driven action observation neurofeedback in VR. In addition, synchronous electromyography (EMG) data were also captured to monitor overt muscle activity. Here we tested four chronic stroke survivors and show that this EEG-based BCI can be safely used over repeated sessions by stroke survivors across a wide range of motor disabilities. Finally, individual results suggest that patients with more severe motor impairments may benefit the most from EEG-based neurofeedback, while patients with more mild impairments may benefit more from EMG-based feedback, harnessing existing sensorimotor pathways. We note that although this work is promising, due to the small sample size, these results are preliminary. Future research is needed to confirm these findings in a larger and more diverse population.
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Affiliation(s)
- Athanasios Vourvopoulos
- Neural Plasticity and Neurorehabilitation Laboratory, Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Octavio Marin Pardo
- Neural Plasticity and Neurorehabilitation Laboratory, Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Stéphanie Lefebvre
- Neural Plasticity and Neurorehabilitation Laboratory, Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Meghan Neureither
- Neural Plasticity and Neurorehabilitation Laboratory, Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - David Saldana
- Neural Plasticity and Neurorehabilitation Laboratory, Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Esther Jahng
- Neural Plasticity and Neurorehabilitation Laboratory, Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Sook-Lei Liew
- Neural Plasticity and Neurorehabilitation Laboratory, Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
- Department of Neurology, Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States
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Vourvopoulos A, Bermúdez I Badia S. Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysis. J Neuroeng Rehabil 2016; 13:69. [PMID: 27503007 PMCID: PMC4977849 DOI: 10.1186/s12984-016-0173-2] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 07/12/2016] [Indexed: 11/17/2022] Open
Abstract
Background The use of Brain–Computer Interface (BCI) technology in neurorehabilitation provides new strategies to overcome stroke-related motor limitations. Recent studies demonstrated the brain's capacity for functional and structural plasticity through BCI. However, it is not fully clear how we can take full advantage of the neurobiological mechanisms underlying recovery and how to maximize restoration through BCI. In this study we investigate the role of multimodal virtual reality (VR) simulations and motor priming (MP) in an upper limb motor-imagery BCI task in order to maximize the engagement of sensory-motor networks in a broad range of patients who can benefit from virtual rehabilitation training. Methods In order to investigate how different BCI paradigms impact brain activation, we designed 3 experimental conditions in a within-subject design, including an immersive Multimodal Virtual Reality with Motor Priming (VRMP) condition where users had to perform motor-execution before BCI training, an immersive Multimodal VR condition, and a control condition with standard 2D feedback. Further, these were also compared to overt motor-execution. Finally, a set of questionnaires were used to gather subjective data on Workload, Kinesthetic Imagery and Presence. Results Our findings show increased capacity to modulate and enhance brain activity patterns in all extracted EEG rhythms matching more closely those present during motor-execution and also a strong relationship between electrophysiological data and subjective experience. Conclusions Our data suggest that both VR and particularly MP can enhance the activation of brain patterns present during overt motor-execution. Further, we show changes in the interhemispheric EEG balance, which might play an important role in the promotion of neural activation and neuroplastic changes in stroke patients in a motor-imagery neurofeedback paradigm. In addition, electrophysiological correlates of psychophysiological responses provide us with valuable information about the motor and affective state of the user that has the potential to be used to predict MI-BCI training outcome based on user’s profile. Finally, we propose a BCI paradigm in VR, which gives the possibility of motor priming for patients with low level of motor control.
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Affiliation(s)
- Athanasios Vourvopoulos
- Faculdade das Ciências Exatas e da Engenharia, Universidade da Madeira, Campus Universitário da Penteada, 9020-105, Funchal, Portugal. .,Madeira Interactive Technologies Institute, Polo Científico e Tecnológico da Madeira, Caminho da Penteada, 9020-105, Funchal, Portugal.
| | - Sergi Bermúdez I Badia
- Faculdade das Ciências Exatas e da Engenharia, Universidade da Madeira, Campus Universitário da Penteada, 9020-105, Funchal, Portugal.,Madeira Interactive Technologies Institute, Polo Científico e Tecnológico da Madeira, Caminho da Penteada, 9020-105, Funchal, Portugal
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Alves J, Vourvopoulos A, Bernardino A, Bermúdez I Badia S. Eye Gaze Correlates of Motor Impairment in VR Observation of Motor Actions. Methods Inf Med 2015; 55:79-83. [PMID: 26640834 DOI: 10.3414/me14-01-0125] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Accepted: 10/06/2015] [Indexed: 11/09/2022]
Abstract
INTRODUCTION This article is part of the Focus Theme of Methods of Information in Medicine on "Methodologies, Models and Algorithms for Patients Rehabilitation". OBJECTIVE Identify eye gaze correlates of motor impairment in a virtual reality motor observation task in a study with healthy participants and stroke patients. METHODS Participants consisted of a group of healthy subjects (N = 20) and a group of stroke survivors (N = 10). Both groups were required to observe a simple reach-and-grab and place-and-release task in a virtual environment. Additionally, healthy subjects were required to observe the task in a normal condition and a constrained movement condition. Eye movements were recorded during the observation task for later analysis. RESULTS For healthy participants, results showed differences in gaze metrics when comparing the normal and arm-constrained conditions. Differences in gaze metrics were also found when comparing dominant and non-dominant arm for saccades and smooth pursuit events. For stroke patients, results showed longer smooth pursuit segments in action observation when observing the paretic arm, thus providing evidence that the affected circuitry may be activated for eye gaze control during observation of the simulated motor action. CONCLUSIONS This study suggests that neural motor circuits are involved, at multiple levels, in observation of motor actions displayed in a virtual reality environment. Thus, eye tracking combined with action observation tasks in a virtual reality display can be used to monitor motor deficits derived from stroke, and consequently can also be used for rehabilitation of stroke patients.
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Affiliation(s)
- J Alves
- Júlio Alves, Madeira-ITI, Polo Científico e Tecnológico da Madeira, Floor -2, Caminho da Penteada, 9020-105 Funchal, Portugal, E-mail:
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