1
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Zeller D, Hiew S, Odorfer T, Nguemeni C. Considering the response in addition to the challenge - a narrative review in appraisal of a motor reserve framework. Aging (Albany NY) 2024; 16:5772-5791. [PMID: 38499388 PMCID: PMC11006496 DOI: 10.18632/aging.205667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 01/04/2024] [Indexed: 03/20/2024]
Abstract
The remarkable increase in human life expectancy over the past century has been achieved at the expense of the risk of age-related impairment and disease. Neurodegeneration, be it part of normal aging or due to neurodegenerative disorders, is characterized by loss of specific neuronal populations, leading to increasing clinical impairment. The individual course may be described as balance between aging- or disease-related pathology and intrinsic mechanisms of adaptation. There is plenty of evidence that the human brain is provided with exhaustible resources to maintain function in the face of adverse conditions. While a reserve concept has mainly been coined in cognitive neuroscience, emerging evidence suggests similar mechanisms to underlie individual differences of adaptive capacity within the motor system. In this narrative review, we summarize what has been proposed to date about a motor reserve (mR) framework. We present current evidence from research in aging subjects and people with neurological conditions, followed by a description of what is known about potential neuronal substrates of mR so far. As there is no gold standard of mR quantification, we outline current approaches which describe various indicators of mR. We conclude by sketching out potential future directions of research. Expediting our understanding of differences in individual motor resilience towards aging and disease will eventually contribute to new, individually tailored therapeutic strategies. Provided early diagnosis, enhancing the individual mR may be suited to postpone disease onset by years and may be an efficacious contribution towards healthy aging, with an increased quality of life for the elderly.
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Affiliation(s)
- Daniel Zeller
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
| | - Shawn Hiew
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
| | - Thorsten Odorfer
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
| | - Carine Nguemeni
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
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2
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Pamplona GSP, Heldner J, Langner R, Koush Y, Michels L, Ionta S, Salmon CEG, Scharnowski F. Preliminary findings on long-term effects of fMRI neurofeedback training on functional networks involved in sustained attention. Brain Behav 2023; 13:e3217. [PMID: 37594145 PMCID: PMC10570501 DOI: 10.1002/brb3.3217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 07/25/2023] [Accepted: 07/29/2023] [Indexed: 08/19/2023] Open
Abstract
INTRODUCTION Neurofeedback based on functional magnetic resonance imaging allows for learning voluntary control over one's own brain activity, aiming to enhance cognition and clinical symptoms. We previously reported improved sustained attention temporarily by training healthy participants to up-regulate the differential activity of the sustained attention network minus the default mode network (DMN). However, the long-term brain and behavioral effects of this training have not yet been studied. In general, despite their relevance, long-term learning effects of neurofeedback training remain under-explored. METHODS Here, we complement our previously reported results by evaluating the neurofeedback training effects on functional networks involved in sustained attention and by assessing behavioral and brain measures before, after, and 2 months after training. The behavioral measures include task as well as questionnaire scores, and the brain measures include activity and connectivity during self-regulation runs without feedback (i.e., transfer runs) and during resting-state runs from 15 healthy individuals. RESULTS Neurally, we found that participants maintained their ability to control the differential activity during follow-up sessions. Further, exploratory analyses showed that the training increased the functional connectivity between the DMN and the occipital gyrus, which was maintained during follow-up transfer runs but not during follow-up resting-state runs. Behaviorally, we found that enhanced sustained attention right after training returned to baseline level during follow-up. CONCLUSION The discrepancy between lasting regulation-related brain changes but transient behavioral and resting-state effects raises the question of how neural changes induced by neurofeedback training translate to potential behavioral improvements. Since neurofeedback directly targets brain measures to indirectly improve behavior in the long term, a better understanding of the brain-behavior associations during and after neurofeedback training is needed to develop its full potential as a promising scientific and clinical tool.
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Affiliation(s)
- Gustavo Santo Pedro Pamplona
- Sensory‐Motor Laboratory (SeMoLa), Jules‐Gonin Eye Hospital/Fondation Asile des AveuglesDepartment of Ophthalmology/University of LausanneLausanneSwitzerland
- InBrain Lab, Department of PhysicsUniversity of Sao PauloRibeirao PretoBrazil
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric HospitalUniversity of ZurichZurichSwitzerland
- Rehabilitation Engineering Laboratory (RELab), Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Jennifer Heldner
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric HospitalUniversity of ZurichZurichSwitzerland
| | - Robert Langner
- Institute of Systems NeuroscienceHeinrich Heine University DusseldorfDusseldorfGermany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM‐7)Research Centre JulichJulichGermany
| | - Yury Koush
- Department of Radiology and Biomedical Imaging, Yale School of MedicineYale UniversityNew HavenConnecticutUSA
| | - Lars Michels
- Department of NeuroradiologyUniversity Hospital ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and Swiss Federal Institute of TechnologyZurichSwitzerland
| | - Silvio Ionta
- Sensory‐Motor Laboratory (SeMoLa), Jules‐Gonin Eye Hospital/Fondation Asile des AveuglesDepartment of Ophthalmology/University of LausanneLausanneSwitzerland
| | | | - Frank Scharnowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric HospitalUniversity of ZurichZurichSwitzerland
- Neuroscience Center ZurichUniversity of Zurich and Swiss Federal Institute of TechnologyZurichSwitzerland
- Department of Cognition, Emotion, and Methods in Psychology, Faculty of PsychologyUniversity of ViennaViennaAustria
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3
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Iwama S, Morishige M, Kodama M, Takahashi Y, Hirose R, Ushiba J. High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing. Sci Data 2023; 10:385. [PMID: 37322080 PMCID: PMC10272177 DOI: 10.1038/s41597-023-02260-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 05/22/2023] [Indexed: 06/17/2023] Open
Abstract
Real-time functional imaging of human neural activity and its closed-loop feedback enable voluntary control of targeted brain regions. In particular, a brain-computer interface (BCI), a direct bridge of neural activities and machine actuation is one promising clinical application of neurofeedback. Although a variety of studies reported successful self-regulation of motor cortical activities probed by scalp electroencephalogram (EEG), it remains unclear how neurophysiological, experimental conditions or BCI designs influence variability in BCI learning. Here, we provide the EEG data during using BCIs based on sensorimotor rhythm (SMR), consisting of 4 separate datasets. All EEG data were acquired with a high-density scalp EEG setup containing 128 channels covering the whole head. All participants were instructed to perform motor imagery of right-hand movement as the strategy to control BCIs based on the task-related power attenuation of SMR magnitude, that is event-related desynchronization. This dataset would allow researchers to explore the potential source of variability in BCI learning efficiency and facilitate follow-up studies to test the explicit hypotheses explored by the dataset.
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Affiliation(s)
- Seitaro Iwama
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Tokyo, Kanagawa, Japan
| | - Masumi Morishige
- Graduate School of Science and Technology, Keio University, Tokyo, Kanagawa, Japan
| | - Midori Kodama
- Graduate School of Science and Technology, Keio University, Tokyo, Kanagawa, Japan
| | - Yoshikazu Takahashi
- Graduate School of Science and Technology, Keio University, Tokyo, Kanagawa, Japan
| | - Ryotaro Hirose
- Graduate School of Science and Technology, Keio University, Tokyo, Kanagawa, Japan
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Tokyo, Kanagawa, Japan.
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4
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Onagawa R, Muraoka Y, Hagura N, Takemi M. An investigation of the effectiveness of neurofeedback training on motor performance in healthy adults: A systematic review and meta-analysis. Neuroimage 2023; 270:120000. [PMID: 36870431 DOI: 10.1016/j.neuroimage.2023.120000] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/26/2023] [Accepted: 02/28/2023] [Indexed: 03/06/2023] Open
Abstract
Neurofeedback training (NFT) refers to a training where the participants voluntarily aim to manipulate their own brain activity using the sensory feedback abstracted from their brain activity. NFT has attracted attention in the field of motor learning due to its potential as an alternative or additional training method for general physical training. In this study, a systematic review of NFT studies for motor performance improvements in healthy adults and a meta-analysis on the effectiveness of NFT were conducted. A computerized search was performed using the databases Web of Science, Scopus, PubMed, JDreamIII, and Ichushi-Web to identify relevant studies published between January 1st, 1990, and August 3rd, 2021. Thirty-three studies were identified for the qualitative synthesis and 16 randomized controlled trials (374 subjects) for the meta-analysis. The meta-analysis, including all trials found in the search, revealed significant effects of NFT for motor performance improvement examined at the timing after the last NFT session (standardized mean difference = 0.85, 95% CI [0.18-1.51]), but with the existence of publication biases and substantial heterogeneity among the trials. Subsequent meta-regression analysis demonstrated the dose-response gradient between NFTs and motor performance improvements; more than 125 min of cumulative training time may benefit for the subsequent motor performance. For each motor performance measure (e.g., speed, accuracy, and hand dexterity), the effectiveness of NFT remains inconclusive, mainly due to its small sample sizes. More empirical NFT studies for motor performance improvement may be needed to show beneficial effects on motor performance and to safely incorporate NFT into real-world scenarios.
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Affiliation(s)
- Ryoji Onagawa
- Faculty of Science and Engineering, Waseda University, Tokyo, Japan.
| | - Yoshihito Muraoka
- Graduate School of Science and Technology, Keio University, Kanagawa, Japan
| | - Nobuhiro Hagura
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, Osaka, Japan; Graduate School of Frontiers Biosciences, Osaka University, Osaka, Japan
| | - Mitsuaki Takemi
- Graduate School of Science and Technology, Keio University, Kanagawa, Japan.
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5
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Kodama M, Iwama S, Morishige M, Ushiba J. Thirty-minute motor imagery exercise aided by EEG sensorimotor rhythm neurofeedback enhances morphing of sensorimotor cortices: a double-blind sham-controlled study. Cereb Cortex 2023:6967448. [PMID: 36600612 DOI: 10.1093/cercor/bhac525] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/15/2022] [Accepted: 12/16/2022] [Indexed: 01/06/2023] Open
Abstract
Neurofeedback training using electroencephalogram (EEG)-based brain-computer interfaces (BCIs) combined with mental rehearsals of motor behavior has demonstrated successful self-regulation of motor cortical excitability. However, it remains unclear whether the acquisition of skills to voluntarily control neural excitability is accompanied by structural plasticity boosted by neurofeedback. Here, we sought short-term changes in cortical structures induced by 30 min of BCI-based neurofeedback training, which aimed at the regulation of sensorimotor rhythm (SMR) in scalp EEG. When participants performed kinesthetic motor imagery of right finger movement with online feedback of either event-related desynchronisation (ERD) of SMR magnitude from the contralateral sensorimotor cortex (SM1) or those from other participants (i.e. placebo), the learning rate of SMR-ERD control was significantly different. Although overlapped structural changes in gray matter volumes were found in both groups, significant differences revealed by group-by-group comparison were spatially different; whereas the veritable neurofeedback group exhibited sensorimotor area-specific changes, the placebo exhibited spatially distributed changes. The white matter change indicated a significant decrease in the corpus callosum in the verum group. Furthermore, the learning rate of SMR regulation was correlated with the volume changes in the ipsilateral SM1, suggesting the involvement of interhemispheric motor control circuitries in BCI control tasks.
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Affiliation(s)
- Midori Kodama
- Graduate School of Science and Technology, Keio University, Kanagawa 108-0073, Japan
| | - Seitaro Iwama
- Graduate School of Science and Technology, Keio University, Kanagawa 108-0073, Japan.,Japan Society for the Promotion of Science, Tokyo 102-0082, Japan
| | - Masumi Morishige
- Graduate School of Science and Technology, Keio University, Kanagawa 108-0073, Japan
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Kanagawa 108-0073, Japan
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6
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Penalver-Andres JA, Buetler KA, Koenig T, Müri RM, Marchal-Crespo L. Resting-State Functional Networks Correlate with Motor Performance in a Complex Visuomotor Task: An EEG Microstate Pilot Study on Healthy Individuals. Brain Topogr 2022:10.1007/s10548-022-00934-9. [PMID: 36566448 DOI: 10.1007/s10548-022-00934-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Accepted: 12/05/2022] [Indexed: 12/26/2022]
Abstract
Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners' functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks-the Attention Network (AN) and the Default Mode Network (DMN)-affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN-linked to internally diverted attention and mind-wandering-would be detrimental for posterior motor performance. We extracted seven widely accepted microstates-representing participants mind states at rest-out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN-imaged using EEG microstates-as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.
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Affiliation(s)
- Joaquin A Penalver-Andres
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
- Psychosomatic Medicine, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
| | - Karin A Buetler
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Thomas Koenig
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - René M Müri
- Perception and Eye Movement Laboratory, Department of Biomedical Research (DBMR) and Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Gerontechnology and Rehabilitation Group, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Laura Marchal-Crespo
- Motor Learning and Neurorehabilitation Laboratory, ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
- Department of Cognitive Robotics, Delft University of Technology, Delft, The Netherlands
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7
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Oda K, Colman R, Koshiba M. Simplified Attachable EEG Revealed Child Development Dependent Neurofeedback Brain Acute Activities in Comparison with Visual Numerical Discrimination Task and Resting. SENSORS (BASEL, SWITZERLAND) 2022; 22:7207. [PMID: 36236305 PMCID: PMC9572555 DOI: 10.3390/s22197207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
The development of an easy-to-attach electroencephalograph (EEG) would enable its frequent use for the assessment of neurodevelopment and clinical monitoring. In this study, we designed a two-channel EEG headband measurement device that could be used safely and was easily attachable and removable without the need for restraint or electrode paste or gel. Next, we explored the use of this device for neurofeedback applications relevant to education or neurocognitive development. We developed a prototype visual neurofeedback game in which the size of a familiar local mascot changes in the PC display depending on the user's brain wave activity. We tested this application at a local children's play event. Children at the event were invited to experience the game and, upon agreement, were provided with an explanation of the game and support in attaching the EEG device. The game began with a consecutive number visual discrimination task which was followed by an open-eye resting condition and then a neurofeedback task. Preliminary linear regression analyses by the least-squares method of the acquired EEG and age data in 30 participants from 5 to 20 years old suggested an age-dependent left brain lateralization of beta waves at the neurofeedback stage (p = 0.052) and of alpha waves at the open-eye resting stage (p = 0.044) with potential involvement of other wave bands. These results require further validation.
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Affiliation(s)
- Kazuyuki Oda
- Engineering Department, Graduate School of Sciences and Technology for Innovation Yamaguchi University, Yamaguchi 755-8611, Japan
| | - Ricki Colman
- Department of Cell and Regenerative Biology, University of Wisconsin, Madison, Madison, WI 53706, USA
| | - Mamiko Koshiba
- Engineering Department, Graduate School of Sciences and Technology for Innovation Yamaguchi University, Yamaguchi 755-8611, Japan
- Department of Pediatrics, Saitama Medical University, Saitama 350-0495, Japan
- Graduate School of Information Sciences, Tohoku University, Sendai 980-8579, Japan
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8
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Loriette C, Amengual JL, Ben Hamed S. Beyond the brain-computer interface: Decoding brain activity as a tool to understand neuronal mechanisms subtending cognition and behavior. Front Neurosci 2022; 16:811736. [PMID: 36161174 PMCID: PMC9492914 DOI: 10.3389/fnins.2022.811736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
One of the major challenges in system neurosciences consists in developing techniques for estimating the cognitive information content in brain activity. This has an enormous potential in different domains spanning from clinical applications, cognitive enhancement to a better understanding of the neural bases of cognition. In this context, the inclusion of machine learning techniques to decode different aspects of human cognition and behavior and its use to develop brain–computer interfaces for applications in neuroprosthetics has supported a genuine revolution in the field. However, while these approaches have been shown quite successful for the study of the motor and sensory functions, success is still far from being reached when it comes to covert cognitive functions such as attention, motivation and decision making. While improvement in this field of BCIs is growing fast, a new research focus has emerged from the development of strategies for decoding neural activity. In this review, we aim at exploring how the advanced in decoding of brain activity is becoming a major neuroscience tool moving forward our understanding of brain functions, providing a robust theoretical framework to test predictions on the relationship between brain activity and cognition and behavior.
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9
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Sanders ZB, Fleming MK, Smejka T, Marzolla MC, Zich C, Rieger SW, Lührs M, Goebel R, Sampaio-Baptista C, Johansen-Berg H. Self-modulation of motor cortex activity after stroke: a randomized controlled trial. Brain 2022; 145:3391-3404. [PMID: 35960166 PMCID: PMC9586541 DOI: 10.1093/brain/awac239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 06/01/2022] [Accepted: 06/20/2022] [Indexed: 11/14/2022] Open
Abstract
Real-time functional MRI neurofeedback allows individuals to self-modulate their ongoing brain activity. This may be a useful tool in clinical disorders that are associated with altered brain activity patterns. Motor impairment after stroke has previously been associated with decreased laterality of motor cortex activity. Here we examined whether chronic stroke survivors were able to use real-time fMRI neurofeedback to increase laterality of motor cortex activity and assessed effects on motor performance and on brain structure and function. We carried out a randomized, double-blind, sham-controlled trial (ClinicalTrials.gov: NCT03775915) in which 24 chronic stroke survivors with mild to moderate upper limb impairment experienced three training days of either Real (n = 12) or Sham (n = 12) neurofeedback. Assessments of brain structure, brain function and measures of upper-limb function were carried out before and 1 week after neurofeedback training. Additionally, measures of upper-limb function were repeated 1 month after neurofeedback training. Primary outcome measures were (i) changes in lateralization of motor cortex activity during movements of the stroke-affected hand throughout neurofeedback training days; and (ii) changes in motor performance of the affected limb on the Jebsen Taylor Test (JTT). Stroke survivors were able to use Real neurofeedback to increase laterality of motor cortex activity within (P = 0.019), but not across, training days. There was no group effect on the primary behavioural outcome measure, which was average JTT performance across all subtasks (P = 0.116). Secondary analysis found improvements in the performance of the gross motor subtasks of the JTT in the Real neurofeedback group compared to Sham (P = 0.010). However, there were no improvements on the Action Research Arm Test or the Upper Extremity Fugl–Meyer score (both P > 0.5). Additionally, decreased white-matter asymmetry of the corticospinal tracts was detected 1 week after neurofeedback training (P = 0.008), indicating that the tracts become more similar with Real neurofeedback. Changes in the affected corticospinal tract were positively correlated with participants neurofeedback performance (P = 0.002). Therefore, here we demonstrate that chronic stroke survivors are able to use functional MRI neurofeedback to self-modulate motor cortex activity in comparison to a Sham control, and that training is associated with improvements in gross hand motor performance and with white matter structural changes.
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Affiliation(s)
- Zeena Britt Sanders
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Melanie K Fleming
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Tom Smejka
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Marilien C Marzolla
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Catharina Zich
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Sebastian W Rieger
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
| | - Michael Lührs
- Department of Cognitive Neuroscience, Maastricht University, 6229 EV Maastricht, The Netherlands.,Research Department, Brain Innovation B.V., 6229 EV Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, 6229 EV Maastricht, The Netherlands.,Research Department, Brain Innovation B.V., 6229 EV Maastricht, The Netherlands
| | - Cassandra Sampaio-Baptista
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK.,Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G61 1QH, UK
| | - Heidi Johansen-Berg
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford OX3 9DU, UK
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10
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Whitehead JC, Neeman R, Doniger GM. Preliminary Real-World Evidence Supporting the Efficacy of a Remote Neurofeedback System in Improving Mental Health: Retrospective Single-Group Pretest-Posttest Study. JMIR Form Res 2022; 6:e35636. [PMID: 35802411 PMCID: PMC9308076 DOI: 10.2196/35636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 05/31/2022] [Accepted: 06/09/2022] [Indexed: 11/13/2022] Open
Abstract
Background
Neurofeedback training (NFT) has been shown to be effective in treating several disorders (eg, attention-deficit/hyperactivity disorder [ADHD], anxiety, and depression); however, little is currently known regarding the effectiveness of remote NFT systems.
Objective
This retrospective study provides real-world data (N=593) to assess the efficacy of app-based remote NFT in improving brain health and cognitive performance.
Methods
Improvement was measured from pre- to postintervention of in-app assessments that included validated symptom questionnaires (the 12-item General Health Questionnaire, the ADHD Rating Scale IV, the Adult ADHD Self-Report Scale, the 7-item Generalized Anxiety Disorder scale, and the 9-item Patient Health Questionnaire), a cognitive test of attention and executive functioning (ie, continuous performance task), and resting electroencephalography (EEG) markers. Clinically significant improvement was evaluated using standard approaches.
Results
The greatest improvement was reported for the anxiety questionnaire, for which 69% (68/99) of participants moved from abnormal to healthy score ranges. Overall, adult and child participants who engaged in neurofeedback to improve attention and executive functions demonstrated improved ADHD scores and enhanced performance on a cognitive (ie, response inhibition) task. Adults with ADHD additionally demonstrated elevated delta/alpha and theta/alpha ratios at baseline and a reduction in the delta/alpha ratio indicator following neurofeedback.
Conclusions
Preliminary findings suggest the efficacy of app-based remote neurofeedback in improving mental health, given the reduced symptom severity from pre- to postassessment for general psychological health, ADHD, anxiety, and depression, as well as adjusted resting EEG neural markers for individuals with symptoms of ADHD. Collectively, this supports the utility of the in-app assessment in monitoring behavioral and neural indices of mental health.
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Affiliation(s)
- Jocelyne C Whitehead
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
- Myndlift Ltd, Tel Aviv, Israel
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11
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De Filippi E, Marins T, Escrichs A, Gilson M, Moll J, Tovar-Moll F, Deco G. One session of fMRI-Neurofeedback training on motor imagery modulates whole-brain effective connectivity and dynamical complexity. Cereb Cortex Commun 2022; 3:tgac027. [PMID: 36072710 PMCID: PMC9441014 DOI: 10.1093/texcom/tgac027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 06/28/2022] [Accepted: 07/03/2022] [Indexed: 11/23/2022] Open
Abstract
In the past decade, several studies have shown that Neurofeedback (NFB) by functional magnetic resonance imaging can alter the functional coupling of targeted and non-targeted areas. However, the causal mechanisms underlying these changes remain uncertain. Here, we applied a whole-brain dynamical model to estimate Effective Connectivity (EC) profiles of resting-state data acquired before and immediately after a single-session NFB training for 17 participants who underwent motor imagery NFB training and 16 healthy controls who received sham feedback. Within-group and between-group classification analyses revealed that only for the NFB group it was possible to accurately discriminate between the 2 resting-state sessions. NFB training-related signatures were reflected in a support network of direct connections between areas involved in reward processing and implicit learning, together with regions belonging to the somatomotor, control, attention, and default mode networks, identified through a recursive-feature elimination procedure. By applying a data-driven approach to explore NFB-induced changes in spatiotemporal dynamics, we demonstrated that these regions also showed decreased switching between different brain states (i.e. metastability) only following real NFB training. Overall, our findings contribute to the understanding of NFB impact on the whole brain’s structure and function by shedding light on the direct connections between brain areas affected by NFB training.
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Affiliation(s)
- Eleonora De Filippi
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Carrer de Ramon Trias Fargas , 25-27, 08005 Barcelona, Catalonia, Spain
| | - Theo Marins
- D’Or Institute for Research and Education (IDOR), Rua Diniz Cordeiro 30, Botafogo-Rio de Janeiro , 22281-100, Brazil
- Post-Graduate Program in Morphological Sciences, Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Citade universitaria da Universidade Federal do Rio de Janeiro , 21941-590, Brazil
| | - Anira Escrichs
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Carrer de Ramon Trias Fargas , 25-27, 08005 Barcelona, Catalonia, Spain
| | - Matthieu Gilson
- Computational Neuroscience Group, Center for Brain and Cognition, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Carrer de Ramon Trias Fargas , 25-27, 08005 Barcelona, Catalonia, Spain
| | - Jorge Moll
- D’Or Institute for Research and Education (IDOR), Rua Diniz Cordeiro 30, Botafogo-Rio de Janeiro , 22281-100, Brazil
| | - Fernanda Tovar-Moll
- D’Or Institute for Research and Education (IDOR), Rua Diniz Cordeiro 30, Botafogo-Rio de Janeiro , 22281-100, Brazil
- Post-Graduate Program in Morphological Sciences, Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Citade universitaria da Universidade Federal do Rio de Janeiro , 21941-590, Brazil
| | - Gustavo Deco
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig de Lluis Companys , 23, 08010, Barcelona, Catalonia, Spain
- Department of Neuropsychology, Max Planck Institute for human Cognitive and Brain Sciences , Stephanstrasse 1a, 04103, Leipzig, Germany
- Turner Institute for Brain and Mental Health, Monash University level 5 , 18 Innovation Walk, Clayton Campus. Wellington Road, Clayton VIC 3800, Australia
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12
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Marins T, Tovar-Moll F. Using neurofeedback to induce and explore brain plasticity. Trends Neurosci 2022; 45:415-416. [DOI: 10.1016/j.tins.2022.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 03/27/2022] [Indexed: 10/18/2022]
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13
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Pitsik EN, Frolov NS, Shusharina N, Hramov AE. Age-Related Changes in Functional Connectivity during the Sensorimotor Integration Detected by Artificial Neural Network. SENSORS 2022; 22:s22072537. [PMID: 35408153 PMCID: PMC9003057 DOI: 10.3390/s22072537] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 03/21/2022] [Accepted: 03/24/2022] [Indexed: 02/01/2023]
Abstract
Large-scale functional connectivity is an important indicator of the brain’s normal functioning. The abnormalities in the connectivity pattern can be used as a diagnostic tool to detect various neurological disorders. The present paper describes the functional connectivity assessment based on artificial intelligence to reveal age-related changes in neural response in a simple motor execution task. Twenty subjects of two age groups performed repetitive motor tasks on command, while the whole-scalp EEG was recorded. We applied the model based on the feed-forward multilayer perceptron to detect functional relationships between five groups of sensors located over the frontal, parietal, left, right, and middle motor cortex. Functional dependence was evaluated with the predicted and original time series coefficient of determination. Then, we applied statistical analysis to highlight the significant features of the functional connectivity network assessed by our model. Our findings revealed the connectivity pattern is consistent with modern ideas of the healthy aging effect on neural activation. Elderly adults demonstrate a pronounced activation of the whole-brain theta-band network and decreased activation of frontal–parietal and motor areas of the mu-band. Between-subject analysis revealed a strengthening of inter-areal task-relevant links in elderly adults. These findings can be interpreted as an increased cognitive demand in elderly adults to perform simple motor tasks with the dominant hand, induced by age-related working memory decline.
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Affiliation(s)
- Elena N. Pitsik
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, Kaliningrad 236041, Russia; (E.N.P.); (N.S.F.); (N.S.)
- Neuroscience and Cognitive Technology Laboratory, Innopolis University, Kazan 420500, Russia
| | - Nikita S. Frolov
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, Kaliningrad 236041, Russia; (E.N.P.); (N.S.F.); (N.S.)
- Neuroscience and Cognitive Technology Laboratory, Innopolis University, Kazan 420500, Russia
| | - Natalia Shusharina
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, Kaliningrad 236041, Russia; (E.N.P.); (N.S.F.); (N.S.)
| | - Alexander E. Hramov
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, Kaliningrad 236041, Russia; (E.N.P.); (N.S.F.); (N.S.)
- Neuroscience and Cognitive Technology Laboratory, Innopolis University, Kazan 420500, Russia
- Correspondence:
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14
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Mirifar A, Keil A, Ehrlenspiel F. Neurofeedback and neural self-regulation: a new perspective based on allostasis. Rev Neurosci 2022; 33:607-629. [PMID: 35122709 DOI: 10.1515/revneuro-2021-0133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/13/2022] [Indexed: 11/15/2022]
Abstract
The field of neurofeedback training (NFT) has seen growing interest and an expansion of scope, resulting in a steadily increasing number of publications addressing different aspects of NFT. This development has been accompanied by a debate about the underlying mechanisms and expected outcomes. Recent developments in the understanding of psychophysiological regulation have cast doubt on the validity of control systems theory, the principal framework traditionally used to characterize NFT. The present article reviews the theoretical and empirical aspects of NFT and proposes a predictive framework based on the concept of allostasis. Specifically, we conceptualize NFT as an adaptation to changing contingencies. In an allostasis four-stage model, NFT involves (a) perceiving relations between demands and set-points, (b) learning to apply collected patterns (experience) to predict future output, (c) determining efficient set-points, and (d) adapting brain activity to the desired ("set") state. This model also identifies boundaries for what changes can be expected from a neurofeedback intervention and outlines a time frame for such changes to occur.
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Affiliation(s)
- Arash Mirifar
- Department of Sport and Health Sciences, Chair of Sport Psychology, Technische Universität München, Munich, Bavaria, Germany.,Institute of Sports Science, Leibniz University Hannover, Germany
| | - Andreas Keil
- Center for the Study of Emotion & Attention, University of Florida, Gainesville, Florida, United States of America
| | - Felix Ehrlenspiel
- Department of Sport and Health Sciences, Chair of Sport Psychology, Technische Universität München, Munich, Bavaria, Germany
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15
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Hu B, Yu Y, Yan L, Qi G, Wu D, Li Y, Shi A, Liu C, Shang Y, Li Z, Cui G, Wang W. Intersubject correlation analysis reveals the plasticity of cerebral functional connectivity in the long‐term use of social media. Hum Brain Mapp 2022; 43:2262-2275. [PMID: 35072320 PMCID: PMC8996346 DOI: 10.1002/hbm.25786] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/27/2021] [Accepted: 01/08/2022] [Indexed: 12/18/2022] Open
Abstract
Owing to the limitations of cross‐sectional studies, it is unclear whether social media induce brain changes, or if individuals with certain biological traits are more likely to use social media. Functional connectivity (FC) can reflect cerebral functional plasticity, and if social media can influence cerebral FC, then the FC of light social media users should be more similar to that of heavy users after they “heavily” used social media for a long period. We combined longitudinal study design and intersubject correlation (ISC) analysis to investigate this similarity. Thirty‐five heavy and 21 light social media users underwent cognitive tests and functional MRIs. The 21 light social media users underwent another functional MRI scan after completing an additional four‐week social media task. We conducted the ISC at the group, individual, and brain‐region levels to investigate the similarity of FC and locate the brain regions most affected by social media. The FC of light social media users was more similar to that of heavy social media users after they completed the four‐week social media task. Then, social media had an impact on half of the brain, involving almost all brain networks. Finally, cerebral FC that mostly affected by social media was associated with selective attention. We concluded that the impact of social media use on cerebral functional connectivity changes is revealed by ISC method and longitudinal design, which may provide guidance for clinical practice. The methods used in the current research could also be applied to similar domains.
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Affiliation(s)
- Bo Hu
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Ying Yu
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Lin‐Feng Yan
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Guo‐Qing Qi
- Institution of Basic Medicine, Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Dong Wu
- Institution of Basic Medicine, Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Yu‐Ting Li
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - An‐Ping Shi
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Chen‐Xi Liu
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Yu‐Xuan Shang
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Ze‐Yang Li
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Guang‐Bin Cui
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
| | - Wen Wang
- Department of Radiology, Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital Fourth Military Medical University (Air Force Medical University) Xi’an Shaanxi China
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16
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Bloom MS, Orthmann-Murphy J, Grinspan JB. Motor Learning and Physical Exercise in Adaptive Myelination and Remyelination. ASN Neuro 2022; 14:17590914221097510. [PMID: 35635130 PMCID: PMC9158406 DOI: 10.1177/17590914221097510] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 04/07/2022] [Accepted: 04/12/2022] [Indexed: 11/17/2022] Open
Abstract
The idea that myelination is driven by both intrinsic and extrinsic cues has gained much traction in recent years. Studies have demonstrated that myelination occurs in an intrinsic manner during early development and continues through adulthood in an activity-dependent manner called adaptive myelination. Motor learning, the gradual acquisition of a specific novel motor skill, promotes adaptive myelination in both the healthy and demyelinated central nervous system (CNS). On the other hand, exercise, a physical activity that involves planned, structured and repetitive bodily movements that expend energy and benefits one's fitness, promotes remyelination in pathology, but it is less clear whether it promotes adaptive myelination in healthy subjects. Studies on these topics have also investigated whether the timing of motor learning or physical exercise is important for successful addition of myelin. Here we review our current understanding of the relationship of motor skill learning and physical exercise on myelination.
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Affiliation(s)
- Mara S. Bloom
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jennifer Orthmann-Murphy
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Judith B. Grinspan
- Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
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17
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Stefano Filho CA, Attux RRDF, Castellano G. Motor imagery practice and feedback effects on functional connectivity. J Neural Eng 2021; 18:066048. [PMID: 34933292 DOI: 10.1088/1741-2552/ac456d] [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] [Indexed: 01/01/2023]
Abstract
- Objective: the use of motor imagery (MI) in motor rehabilitation protocols has been increasingly investigated as a potential technique for enhancing traditional treatments, yielding better clinical outcomes. However, since MI performance can be challenging, practice is usually required. This demands appropriate training, actively engaging the MI-related brain areas, consequently enabling the user to properly benefit from it. The role of feedback is central for MI practice. Yet, assessing which underlying neural changes are feedback-specific or purely due to MI practice is still a challenging effort, mainly due to the difficulty in isolating their contributions. In this work, we aimed to assess functional connectivity (FC) changes following MI practice that are either extrinsic or specific to feedback. APPROACH to achieve this, we investigated FC, using graph theory, in electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, during MI performance and at resting-state (rs), respectively. Thirty healthy subjects were divided into three groups, receiving no feedback (control), "false" feedback (sham) or actual neurofeedback (active). Participants underwent 12 to 13 hands-MI EEG sessions and pre- and post-MI training fMRI exams. MAIN RESULTS following MI practice, control participants presented significant increases in degree and in eigenvector centrality for occipital nodes at rs-fMRI scans, whereas sham-feedback produced similar effects, but to a lesser extent. Therefore, MI practice, by itself, seems to stimulate visual information processing mechanisms that become apparent during basal brain activity. Additionally, only the active group displayed decreases in inter-subject FC patterns, both during MI performance and at rs-fMRI. SIGNIFICANCE hence, actual neurofeedback impacted FC by disrupting common inter-subject patterns, suggesting that subject-specific neural plasticity mechanisms become important. Future studies should consider this when designing experimental NFBT protocols and analyses.
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Affiliation(s)
| | - Romis Ribeiro de Faisol Attux
- Laboratory of Signal Processing for Communications, School of Electrical and Computer Engineering, University of Campinas, Laboratório de Processamento de Sinais para Comunicações, Campinas, São Paulo, 13083-852, BRAZIL
| | - Gabriela Castellano
- Department of Cosmic Rays and Chronology, University of Campinas - UNICAMP, Institute of Physics Gleb Wataghin, R. Sérgio Buarque de Holanda, nº 777, Cidade Universitária, Campinas, SP, 13083-859, BRAZIL
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18
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fMRI neurofeedback in the motor system elicits bidirectional changes in activity and in white matter structure in the adult human brain. Cell Rep 2021; 37:109890. [PMID: 34706229 PMCID: PMC8961413 DOI: 10.1016/j.celrep.2021.109890] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/06/2021] [Accepted: 10/05/2021] [Indexed: 02/07/2023] Open
Abstract
White matter (WM) plasticity supports skill learning and memory. Up- and downregulation of brain activity in animal models lead to WM alterations. But can bidirectional brain-activity manipulation change WM structure in the adult human brain? We employ fMRI neurofeedback to endogenously and directionally modulate activity in the sensorimotor cortices. Diffusion tensor imaging is acquired before and after two separate conditions, involving regulating sensorimotor activity either up or down using real or sham neurofeedback (n = 20 participants × 4 scans). We report rapid opposing changes in corpus callosum microstructure that depend on the direction of activity modulation. Our findings show that fMRI neurofeedback can be used to endogenously and directionally alter not only brain-activity patterns but also WM pathways connecting the targeted brain areas. The level of associated brain activity in connected areas is therefore a possible mediator of previously described learning-related changes in WM.
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19
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Neurofeedback for cognitive enhancement and intervention and brain plasticity. Rev Neurol (Paris) 2021; 177:1133-1144. [PMID: 34674879 DOI: 10.1016/j.neurol.2021.08.004] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 08/27/2021] [Indexed: 12/18/2022]
Abstract
In recent years, neurofeedback has been used as a cognitive training tool to improve brain functions for clinical or recreational purposes. It is based on providing participants with feedback about their brain activity and training them to control it, initiating directional changes. The overarching hypothesis behind this method is that this control results in an enhancement of the cognitive abilities associated with this brain activity, and triggers specific structural and functional changes in the brain, promoted by learning and neuronal plasticity effects. Here, we review the general methodological principles behind neurofeedback and we describe its behavioural benefits in clinical and experimental contexts. We review the non-specific effects of neurofeedback on the reinforcement learning striato-frontal networks as well as the more specific changes in the cortical networks on which the neurofeedback control is exerted. Last, we analyse the current challenges faces by neurofeedback studies, including the quantification of the temporal dynamics of neurofeedback effects, the generalisation of its behavioural outcomes to everyday life situations, the design of appropriate controls to disambiguate placebo from true neurofeedback effects and the development of more advanced cortical signal processing to achieve a finer-grained real-time modelling of cognitive functions.
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20
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Chakraborty S, Saetta G, Simon C, Lenggenhager B, Ruddy K. Could Brain-Computer Interface Be a New Therapeutic Approach for Body Integrity Dysphoria? Front Hum Neurosci 2021; 15:699830. [PMID: 34456696 PMCID: PMC8385143 DOI: 10.3389/fnhum.2021.699830] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 07/09/2021] [Indexed: 12/11/2022] Open
Abstract
Patients suffering from body integrity dysphoria (BID) desire to become disabled, arising from a mismatch between the desired body and the physical body. We focus here on the most common variant, characterized by the desire for amputation of a healthy limb. In most reported cases, amputation of the rejected limb entirely alleviates the distress of the condition and engenders substantial improvement in quality of life. Since BID can lead to life-long suffering, it is essential to identify an effective form of treatment that causes the least amount of alteration to the person's anatomical structure and functionality. Treatment methods involving medications, psychotherapy, and vestibular stimulation have proven largely ineffective. In this hypothesis article, we briefly discuss the characteristics, etiology, and current treatment options available for BID before highlighting the need for new, theory driven approaches. Drawing on recent findings relating to functional and structural brain correlates of BID, we introduce the idea of brain-computer interface (BCI)/neurofeedback approaches to target altered patterns of brain activity, promote re-ownership of the limb, and/or attenuate stress and negativity associated with the altered body representation.
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Affiliation(s)
- Stuti Chakraborty
- Occupational Therapy, Department of Physical Medicine and Rehabilitation, Christian Medical College and Hospital, Vellore, India
| | - Gianluca Saetta
- Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Colin Simon
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | | | - Kathy Ruddy
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Dublin, Ireland
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21
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An improved version of local activities estimation to enhance motor imagery classification. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102485] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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22
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Aliakbaryhosseinabadi S, Lontis R, Farina D, Mrachacz-Kersting N. Effect of motor learning with different complexities on EEG spectral distribution and performance improvement. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102447] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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23
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MRI correlates of cognitive improvement after home-based EEG neurofeedback training in patients with multiple sclerosis: a pilot study. J Neurol 2021; 268:3808-3816. [PMID: 33786666 PMCID: PMC8463344 DOI: 10.1007/s00415-021-10530-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 10/25/2022]
Abstract
OBJECTIVE Neurofeedback training may improve cognitive function in patients with neurological disorders. However, the underlying cerebral mechanisms of such improvements are poorly understood. Therefore, we aimed to investigate MRI correlates of cognitive improvement after EEG-based neurofeedback training in patients with MS (pwMS). METHODS Fourteen pwMS underwent ten neurofeedback training sessions within 3-4 weeks at home using a tele-rehabilitation system. Half of the pwMS (N = 7, responders) learned to self-regulate sensorimotor rhythm (SMR, 12-15 Hz) by visual feedback and improved cognitively after training, whereas the remainder (non-responders, n = 7) did not. Diffusion-tensor imaging and resting-state fMRI of the brain was performed before and after training. We analyzed fractional anisotropy (FA) and functional connectivity (FC) of the default-mode, sensorimotor (SMN) and salience network (SAL). RESULTS At baseline, responders and non-responders were comparable regarding sex, age, education, disease duration, physical and cognitive impairment, and MRI parameters. After training, compared to non-responders, responders showed increased FA and FC within the SAL and SMN. Cognitive improvement correlated with increased FC in SAL and a correlation trend with increased FA was observed. CONCLUSIONS This exploratory study suggests that successful neurofeedback training may not only lead to cognitive improvement, but also to increases in brain microstructure and functional connectivity.
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24
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Mencel J, Jaskólska A, Marusiak J, Kamiński Ł, Kurzyński M, Wołczowski A, Jaskólski A, Kisiel-Sajewicz K. Motor Imagery Training of Reaching-to-Grasp Movement Supplemented by a Virtual Environment in an Individual With Congenital Bilateral Transverse Upper-Limb Deficiency. Front Psychol 2021; 12:638780. [PMID: 33828507 PMCID: PMC8019807 DOI: 10.3389/fpsyg.2021.638780] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/03/2021] [Indexed: 11/30/2022] Open
Abstract
This study explored the effect of kinesthetic motor imagery training on reaching-to-grasp movement supplemented by a virtual environment in a patient with congenital bilateral transverse upper-limb deficiency. Based on a theoretical assumption, it is possible to conduct such training in this patient. The aim of this study was to evaluate whether cortical activity related to motor imagery of reaching and motor imagery of grasping of the right upper limb was changed by computer-aided imagery training (CAIT) in a patient who was born without upper limbs compared to a healthy control subject, as characterized by multi-channel electroencephalography (EEG) signals recorded before and 4, 8, and 12 weeks after CAIT. The main task during CAIT was to kinesthetically imagine the execution of reaching-to-grasp movements without any muscle activation, supplemented by computer visualization of movements provided by a special headset. Our experiment showed that CAIT can be conducted in the patient with higher vividness of imagery for reaching than grasping tasks. Our results confirm that CAIT can change brain activation patterns in areas related to motor planning and the execution of reaching and grasping movements, and that the effect was more pronounced in the patient than in the healthy control subject. The results show that CAIT has a different effect on the cortical activity related to the motor imagery of a reaching task than on the cortical activity related to the motor imagery of a grasping task. The change observed in the activation patterns could indicate CAIT-induced neuroplasticity, which could potentially be useful in rehabilitation or brain-computer interface purposes for such patients, especially before and after transplantation. This study was part of a registered experiment (ID: NCT04048083).
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Affiliation(s)
- Joanna Mencel
- Department of Kinesiology, Faculty of Physiotherapy, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Anna Jaskólska
- Department of Kinesiology, Faculty of Physiotherapy, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Jarosław Marusiak
- Department of Kinesiology, Faculty of Physiotherapy, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Łukasz Kamiński
- Department of Kinesiology, Faculty of Physiotherapy, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Marek Kurzyński
- Department of Systems and Computer Networks, Faculty of Electronics, Wrocław University of Science and Technology, Wrocław, Poland
| | - Andrzej Wołczowski
- Department of Fundamental Cybernetics and Robotics, Institute of Computer Engineering, Control and Robotics, Wrocław University of Science and Technology, Wrocław, Poland
| | - Artur Jaskólski
- Department of Kinesiology, Faculty of Physiotherapy, University School of Physical Education in Wrocław, Wrocław, Poland
| | - Katarzyna Kisiel-Sajewicz
- Department of Kinesiology, Faculty of Physiotherapy, University School of Physical Education in Wrocław, Wrocław, Poland
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25
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Yu L, Long Q, Tang Y, Yin S, Chen Z, Zhu C, Chen A. Improving Emotion Regulation Through Real-Time Neurofeedback Training on the Right Dorsolateral Prefrontal Cortex: Evidence From Behavioral and Brain Network Analyses. Front Hum Neurosci 2021; 15:620342. [PMID: 33815078 PMCID: PMC8010650 DOI: 10.3389/fnhum.2021.620342] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 02/24/2021] [Indexed: 11/15/2022] Open
Abstract
We investigated if emotion regulation can be improved through self-regulation training on non-emotional brain regions, as well as how to change the brain networks implicated in this process. During the training period, the participants were instructed to up-regulate their right dorsolateral prefrontal cortex (rDLPFC) activity according to real-time functional near-infrared spectroscopy (fNIRS) neurofeedback signals, and there was no emotional element. The results showed that the training significantly increased emotion regulation, resting-state functional connectivity (rsFC) within the emotion regulation network (ERN) and frontoparietal network (FPN), and rsFC between the ERN and amygdala; however, training did not influence the rsFC between the FPN and the amygdala. However, self-regulation training on rDLPFC significantly improved emotion regulation and generally increased the rsFCs within the networks; the rsFC between the ERN and amygdala was also selectively increased. The present study also described a safe approach that may improve emotion regulation through self-regulation training on non-emotional brain regions.
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Affiliation(s)
- Linlin Yu
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Quanshan Long
- Faculty of Education, Yunnan Normal University, Kunming, China
| | - Yancheng Tang
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Shouhang Yin
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Zijun Chen
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.,IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Antao Chen
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
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26
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Seiger R, Gryglewski G, Klöbl M, Kautzky A, Godbersen GM, Rischka L, Vanicek T, Hienert M, Unterholzner J, Silberbauer LR, Michenthaler P, Handschuh P, Hahn A, Kasper S, Lanzenberger R. The Influence of Acute SSRI Administration on White Matter Microstructure in Patients Suffering From Major Depressive Disorder and Healthy Controls. Int J Neuropsychopharmacol 2021; 24:542-550. [PMID: 33667309 PMCID: PMC8299824 DOI: 10.1093/ijnp/pyab008] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 01/20/2021] [Accepted: 02/25/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Selective serotonin reuptake inhibitors (SSRIs) are predominantly prescribed for people suffering from major depressive disorder. These antidepressants exert their effects by blocking the serotonin transporter (SERT), leading to increased levels of serotonin in the synaptic cleft and subsequently to an attenuation of depressive symptoms and elevation in mood. Although long-term studies investigating white matter (WM) alterations after exposure to antidepressant treatment exist, results on the acute effects on the brain's WM microstructure are lacking. METHODS In this interventional longitudinal study, 81 participants were included (33 patients and 48 healthy controls). All participants underwent diffusion weighted imaging on 2 separate days, receiving either citalopram or placebo using a randomized, double-blind, cross-over design. Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated within the FMRIB software library and analyzed using tract-based spatial statistics. RESULTS The repeated-measures ANOVA model revealed significant decreases after SSRI administration in mean diffusivity, axial diffusivity, and radial diffusivity regardless of the group (P < .05, family-wise error [FWE] corrected). Results were predominantly evident in frontal WM regions comprising the anterior corona radiata, corpus callosum, and external capsule and in distinct areas of the frontal blade. No increases in diffusivity were found, and no changes in fractional anisotropy were present. CONCLUSIONS Our investigation provides the first evidence, to our knowledge, that fast WM microstructure adaptations within 1 hour after i.v. SSRI administration precede elevations in mood due to SSRI treatment. These results add a new facet to the complex mode of action of antidepressant therapy. This study was registered at clinicaltrials.gov with the identifier NCT02711215.
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Affiliation(s)
- R Seiger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - G Gryglewski
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - M Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - A Kautzky
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - G M Godbersen
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - L Rischka
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - T Vanicek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - M Hienert
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - J Unterholzner
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - L R Silberbauer
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - P Michenthaler
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - P Handschuh
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - A Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - S Kasper
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - R Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria,Correspondence: Prof. Rupert Lanzenberger, PD MD, Neuroimaging Labs (NIL) – PET, MRI, EEG, TMS and Chemical Lab, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Waehringer Guertel 18–20, 1090 Vienna, Austria ()
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The Next 50 Years of Neuroscience. J Neurosci 2020; 40:101-106. [PMID: 31896564 DOI: 10.1523/jneurosci.0744-19.2019] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 12/03/2019] [Accepted: 12/03/2019] [Indexed: 02/06/2023] Open
Abstract
On the 50th anniversary of the Society for Neuroscience, we reflect on the remarkable progress that the field has made in understanding the nervous system, and look forward to the contributions of the next 50 years. We predict a substantial acceleration of our understanding of the nervous system that will drive the development of new therapeutic strategies to treat diseases over the course of the next five decades. We also see neuroscience at the nexus of many societal topics beyond medicine, including education, consumerism, and the justice system. In combination, advances made by basic, translational, and clinical neuroscience research in the next 50 years have great potential for lasting improvements in human health, the economy, and society.
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Peng Y, Wang Z, Wong CM, Nan W, Rosa A, Xu P, Wan F, Hu Y. Changes of EEG phase synchronization and EOG signals along the use of steady state visually evoked potential-based brain computer interface. J Neural Eng 2020; 17:045006. [DOI: 10.1088/1741-2552/ab933e] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Caria A, da Rocha JLD, Gallitto G, Birbaumer N, Sitaram R, Murguialday AR. Brain-Machine Interface Induced Morpho-Functional Remodeling of the Neural Motor System in Severe Chronic Stroke. Neurotherapeutics 2020; 17:635-650. [PMID: 31802435 PMCID: PMC7283440 DOI: 10.1007/s13311-019-00816-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Brain-machine interfaces (BMI) permit bypass motor system disruption by coupling contingent neuroelectric signals related to motor activity with prosthetic devices that enhance afferent and proprioceptive feedback to the somatosensory cortex. In this study, we investigated neural plasticity in the motor network of severely impaired chronic stroke patients after an EEG-BMI-based treatment reinforcing sensorimotor contingency of ipsilesional motor commands. Our structural connectivity analysis revealed decreased fractional anisotropy in the splenium and body of the corpus callosum, and in the contralesional hemisphere in the posterior limb of the internal capsule, the posterior thalamic radiation, and the superior corona radiata. Functional connectivity analysis showed decreased negative interhemispheric coupling between contralesional and ipsilesional sensorimotor regions, and decreased positive intrahemispheric coupling among contralesional sensorimotor regions. These findings indicate that BMI reinforcing ipsilesional brain activity and enhancing proprioceptive function of the affected hand elicits reorganization of contralesional and ipsilesional somatosensory and motor-assemblies as well as afferent and efferent connection-related motor circuits that support the partial re-establishment of the original neurophysiology of the motor system even in severe chronic stroke.
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Affiliation(s)
- Andrea Caria
- Department of Psychology and Cognitive Sciences, University of Trento, Corso Bettini 33, 38068, Rovereto, Italy.
- Istituto di Ricovero e Cura a Carattere Scientifico, Fondazione Ospedale San Camillo, Venice, Italy.
- Institut für Medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen, Tübingen, Germany.
| | - Josué Luiz Dalboni da Rocha
- Brain and Language Laboratory, Department of Clinical Neuroscience, University of Geneva, Geneva, Switzerland
| | - Giuseppe Gallitto
- Department of Psychology and Cognitive Sciences, University of Trento, Corso Bettini 33, 38068, Rovereto, Italy
| | - Niels Birbaumer
- Institut für Medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen, Tübingen, Germany
| | - Ranganatha Sitaram
- Institute of Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychiatry, Section of Neuroscience, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Laboratory for Brain-Machine Interfaces and Neuromodulation, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ander Ramos Murguialday
- Institut für Medizinische Psychologie und Verhaltensneurobiologie, Universität Tübingen, Tübingen, Germany
- Health Technologies Department, TECNALIA, San Sebastian, Spain
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Maziero D, Rondinoni C, Marins T, Stenger VA, Ernst T. Prospective motion correction of fMRI: Improving the quality of resting state data affected by large head motion. Neuroimage 2020; 212:116594. [PMID: 32044436 DOI: 10.1016/j.neuroimage.2020.116594] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 12/30/2019] [Accepted: 01/29/2020] [Indexed: 11/19/2022] Open
Abstract
The quality of functional MRI (fMRI) data is affected by head motion. It has been shown that fMRI data quality can be improved by prospectively updating the gradients and radio-frequency pulses in response to head motion during image acquisition by using an MR-compatible optical tracking system (prospective motion correction, or PMC). Recent studies showed that PMC improves the temporal Signal to Noise Ratio (tSNR) of resting state fMRI data (rs-fMRI) acquired from subjects not moving intentionally. Besides that, the time courses of Independent Components (ICs), resulting from Independent Component Analysis (ICA), were found to present significant temporal correlation with the motion parameters recorded by the camera. However, the benefits of applying PMC for improving the quality of rs-fMRI acquired under large head movements and its effects on resting state networks (RSN) and connectivity matrices are still unknown. In this study, subjects were instructed to cross their legs at will while rs-fMRI data with and without PMC were acquired, which generated head motion velocities ranging from 4 to 30 mm/s. We also acquired fMRI data without intentional motion. Independent component analysis of rs-fMRI was performed to evaluate IC maps and time courses of RSNs. We also calculated the temporal correlation among different brain regions and generated connectivity matrices for the different motion and PMC conditions. In our results we verified that the crossing leg movements reduced the tSNR of sessions without and with PMC by 45 and 20%, respectively, when compared to sessions without intentional movements. We have verified an interaction between head motion speed and PMC status, showing stronger attenuation of tSNR for acquisitions without PMC than for those with PMC. Additionally, the spatial definition of major RSNs, such as default mode, visual, left and right central executive networks, was improved when PMC was enabled. Furthermore, motion altered IC-time courses by decreasing power at low frequencies and increasing power at higher frequencies (typically associated with artefacts). PMC partially reversed these alterations of the power spectra. Finally, we showed that PMC provides temporal correlation matrices for data acquired under motion conditions more comparable to those obtained by fMRI sessions where subjects were instructed not to move.
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Affiliation(s)
- Danilo Maziero
- MR Research Program, Department of Medicine, John A. Burns School of Medicine, University of Hawai'i, HI, USA.
| | - Carlo Rondinoni
- Department of Radiology, University of São Paulo, São Paulo, S.P, Brazil
| | - Theo Marins
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, RJ, Brazil
| | - Victor Andrew Stenger
- MR Research Program, Department of Medicine, John A. Burns School of Medicine, University of Hawai'i, HI, USA
| | - Thomas Ernst
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
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Affiliation(s)
- Michelle Hampson
- Department of Radiology and Biomedical Imaging, Department of Psychiatry, and the Child Study Center, Yale University School of Medicine, New Haven, CT, USA.
| | - Sergio Ruiz
- Department of Psychiatry, Medicine School, and Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile.
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, Japan.
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32
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Wang H, Xu G, Wang X, Sun C, Zhu B, Fan M, Jia J, Guo X, Sun L. The Reorganization of Resting-State Brain Networks Associated With Motor Imagery Training in Chronic Stroke Patients. IEEE Trans Neural Syst Rehabil Eng 2019; 27:2237-2245. [DOI: 10.1109/tnsre.2019.2940980] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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