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Life
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Applications of EEG in Neural Rehabilitation
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Applications of EEG in Neural Rehabilitation

A special issue of Life (ISSN 2075-1729). This special issue belongs to the section "Radiobiology and Nuclear Medicine".

Deadline for manuscript submissions: closed (28 April 2023) | Viewed by 10766

Special Issue Editors

Dr. Jorge Bosch-Bayard

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Guest Editor
McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
Interests: EEG; neuroinformatics; neural rehabilitation; brain connectivity
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Giuseppe Augusto Chiarenza

E-Mail Website
Guest Editor
Centro Internazionale dei Disturbi di Apprendimento, Attenzione e Iperattività, (CIDAAI), Milano, Italy
Interests: developmental neuropsychology; neurophysiology and psychophysiology of learning disabilities; dyslexia and attention deficit hyperactivity disorder
Special Issues, Collections and Topics in MDPI journals
Dr. Alessandra Anzolin

E-Mail Website
Guest Editor
Spaulding Rehabilitation Hospital, Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA 02115, USA
Interests: brain networks; hyperscanning; signal-processing
Special Issues, Collections and Topics in MDPI journals
Dr. Rubén Pérez-Elvira

E-Mail Website
Guest Editor
Facultad de Psicología, Universidad Pontificia de Salamanca, Salamanca, Spain
Interests: cognitive neuropsychology; cognitive neuroscience; neuroimaging; neuropsychological rehabilitation; clinical neuropsychology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Neurorehabilitation is a type of therapy designed for the recovery of brain-functional alterations or disabilities that are consequences of a neurological disorder or an acute insult to the nervous system. In some cases, this process may not in fact produce recovery but the compensation of lost functionalities and a reduction in the associated symptoms, which positively impact the improvement of the person’s quality of life.

Electroencephalography (EEG), as a functional measurement of the brain, is affordable and non-invasive and has a high temporal resolution. It has been widely used both as a therapeutic technique for rehabilitation and as a tool for the assessment of the results of the rehabilitation process. As a rehabilitation tool, EEG's high temporal resolution makes it very well suited for measurement, able to provide near-real-time feedback to the damaged brain to stimulate neural-rehabilitation processes and neuroplastic mechanisms. Recently, several new methodologies to support neuro-rehabilitative technologies such as brain–computer interfaces (BCI) have been developed.

EEG-based approaches go from measuring the activation of brain regions, or connectivity between brain areas, using both scalp measurements and the distribution of primary sources at the cortex through inverse solution methods. Connectivity methods include coherence, causality, phase-lag indexes, or effective connectivity at the sources. Methods have been developed in either the time or the frequency domains. As anticipated, neurofeedback is also a widely used technique for this purpose. Other methods use a combination of EEG with electromyographical (EMG) signals to determine the appropriate time for providing adequate feedback to the brain (e.g., exoskeletons, BCI for motor rehabilitation). EEG-based virtual reality games are also employed as neuro-rehabilitation tools. Many algorithms have been developed to extract EEG-based synthetic indices associated with mood disorders such as depression, emotions such as sadness and happiness, and mental states such as alertness, workload, and others. Such markers can be used as feedback to enhance the therapeutic process. In recent years, the use of the hyper-scanning techniques (i.e., the simultaneous recording of the EEG activity from two or more interactive persons) has been proposed as a model providing insights into the neural dynamics underlying clinical interactions allowing for the optimization of rehabilitation strategies.

In this issue, we invite original and review research highlighting the brain mechanisms activated by EEG-based neurorehabilitation treatments, as well as ways of objectively measuring their efficacy. We also welcome papers on the future of neurorehabilitation, perspectives, strengths, new methodologies, and more efficient mechanisms for providing feedback to the brain. We encourage papers using EEG to develop methodologies for the assessment of the effectiveness of intervention processes. Review papers that analyze and summarize the state of the art in the field, giving an integrated vision of different approaches, analyzing reproducibility of the results, and comparing methodologies contributing to shedding light on the brain mechanisms behind neurorehabilitation processes are also very well received.

Dr. Jorge Bosch-Bayard
Prof. Dr. Giuseppe Augusto Chiarenza
Dr. Alessandra Anzolin
Dr. Rubén Pérez-Elvira
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Life is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neurorehabilitation
  • neuroplasticity
  • EEG
  • ERPs
  • qEEG, EEG mediated patient-therapist interaction
  • BCI
  • exoskeleton
  • cognitive rehabilitation
  • brain rewiring

Published Papers (5 papers)

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Research

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17 pages, 5255 KiB  
Article
Cerebral Projection of Mirrored Touch via sLORETA Imaging
by Dita Dubová, Dominika Dvořáčková, Dagmar Pavlů and David Pánek
Life 2023, 13(5), 1201; https://doi.org/10.3390/life13051201 - 17 May 2023
Cited by 1 | Viewed by 1481
Abstract
Touch is one of the primary communication tools. Interestingly, the sensation of touch can also be experienced when observed in another person. Due to the system of mirror neurons, it is, in fact, being mapped on the somatosensory cortex of the observer. This [...] Read more.
Touch is one of the primary communication tools. Interestingly, the sensation of touch can also be experienced when observed in another person. Due to the system of mirror neurons, it is, in fact, being mapped on the somatosensory cortex of the observer. This phenomenon can be triggered not only by observing touch in another individual, but also by a mirror reflection of the contralateral limb. Our study aims to evaluate and localize changes in the intracerebral source activity via sLORETA imaging during the haptic stimulation of hands, while modifying this contact by a mirror illusion. A total of 10 healthy volunteers aged 23–42 years attended the experiment. The electrical brain activity was detected via scalp EEG. First, we registered the brain activity during resting state with open and with closed eyes, each for 5 min. Afterwards, the subjects were seated at a table with a mirror reflecting their left hand and occluding their right hand. The EEG was then recorded in 2 min sequencies during four modifications of the experiment (haptic contact on both hands, stimulation of the left hand only, right hand only and without any tactile stimuli). We randomized the order of the modifications for each participant. The obtained EEG data were converted into the sLORETA program and evaluated statistically at the significance level of p ≤ 0.05. The subjective experience of all the participants was registered using a survey. A statistically significant difference in source brain activity occurred during all four modifications of our experiment in the beta-2, beta-3 and delta frequency bands, resulting in the activation of 10 different Brodmann areas varying by modification. The results suggest that the summation of stimuli secured by interpersonal haptic contact modified by mirror illusion can activate the brain areas integrating motor, sensory and cognitive functions and further areas related to communication and understanding processes, including the mirror neuron system. We believe these findings may have potential for therapy. Full article
(This article belongs to the Special Issue Applications of EEG in Neural Rehabilitation)
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21 pages, 3581 KiB  
Article
On the Influence of Aging on Classification Performance in the Visual EEG Oddball Paradigm Using Statistical and Temporal Features
by Nina Omejc, Manca Peskar, Aleksandar Miladinović, Voyko Kavcic, Sašo Džeroski and Uros Marusic
Life 2023, 13(2), 391; https://doi.org/10.3390/life13020391 - 31 Jan 2023
Cited by 3 | Viewed by 1429
Abstract
The utilization of a non-invasive electroencephalogram (EEG) as an input sensor is a common approach in the field of the brain–computer interfaces (BCI). However, the collected EEG data pose many challenges, one of which may be the age-related variability of event-related potentials (ERPs), [...] Read more.
The utilization of a non-invasive electroencephalogram (EEG) as an input sensor is a common approach in the field of the brain–computer interfaces (BCI). However, the collected EEG data pose many challenges, one of which may be the age-related variability of event-related potentials (ERPs), which are often used as primary EEG BCI signal features. To assess the potential effects of aging, a sample of 27 young and 43 older healthy individuals participated in a visual oddball study, in which they passively viewed frequent stimuli among randomly occurring rare stimuli while being recorded with a 32-channel EEG set. Two types of EEG datasets were created to train the classifiers, one consisting of amplitude and spectral features in time and another with extracted time-independent statistical ERP features. Among the nine classifiers tested, linear classifiers performed best. Furthermore, we show that classification performance differs between dataset types. When temporal features were used, maximum individuals’ performance scores were higher, had lower variance, and were less affected overall by within-class differences such as age. Finally, we found that the effect of aging on classification performance depends on the classifier and its internal feature ranking. Accordingly, performance will differ if the model favors features with large within-class differences. With this in mind, care must be taken in feature extraction and selection to find the correct features and consequently avoid potential age-related performance degradation in practice. Full article
(This article belongs to the Special Issue Applications of EEG in Neural Rehabilitation)
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23 pages, 3592 KiB  
Article
Quasi-Movements and “Quasi-Quasi-Movements”: Does Residual Muscle Activation Matter?
by Anatoly N. Vasilyev, Artem S. Yashin and Sergei L. Shishkin
Life 2023, 13(2), 303; https://doi.org/10.3390/life13020303 - 21 Jan 2023
Cited by 2 | Viewed by 2272
Abstract
Quasi-movements (QM) are observed when an individual minimizes a movement to an extent that no related muscle activation is detected. Likewise to imaginary movements (IM) and overt movements, QMs are accompanied by the event-related desynchronization (ERD) of EEG sensorimotor rhythms. Stronger ERD was [...] Read more.
Quasi-movements (QM) are observed when an individual minimizes a movement to an extent that no related muscle activation is detected. Likewise to imaginary movements (IM) and overt movements, QMs are accompanied by the event-related desynchronization (ERD) of EEG sensorimotor rhythms. Stronger ERD was observed under QMs compared to IMs in some studies. However, the difference could be caused by the remaining muscle activation in QMs that could escape detection. Here, we re-examined the relation between the electromyography (EMG) signal and ERD in QM using sensitive data analysis procedures. More trials with signs of muscle activation were observed in QMs compared with a visual task and IMs. However, the rate of such trials was not correlated with subjective estimates of actual movement. Contralateral ERD did not depend on the EMG but still was stronger in QMs compared with IMs. These results suggest that brain mechanisms are common for QMs in the strict sense and “quasi-quasi-movements” (attempts to perform the same task accompanied by detectable EMG elevation) but differ between them and IMs. QMs could be helpful in research aimed at better understanding motor action and at modeling the use of attempted movements in the brain-computer interfaces with healthy participants. Full article
(This article belongs to the Special Issue Applications of EEG in Neural Rehabilitation)
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Review

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22 pages, 1073 KiB  
Review
Assessing Consciousness through Neurofeedback and Neuromodulation: Possibilities and Challenges
by Martina Vatrano, Idan Efim Nemirovsky, Paolo Tonin and Francesco Riganello
Life 2023, 13(8), 1675; https://doi.org/10.3390/life13081675 - 02 Aug 2023
Cited by 1 | Viewed by 1287
Abstract
Neurofeedback is a non-invasive therapeutic approach that has gained traction in recent years, showing promising results for various neurological and psychiatric conditions. It involves real-time monitoring of brain activity, allowing individuals to gain control over their own brainwaves and improve cognitive performance or [...] Read more.
Neurofeedback is a non-invasive therapeutic approach that has gained traction in recent years, showing promising results for various neurological and psychiatric conditions. It involves real-time monitoring of brain activity, allowing individuals to gain control over their own brainwaves and improve cognitive performance or alleviate symptoms. The use of electroencephalography (EEG), such as brain–computer interface (BCI), transcranial direct current stimulation (tDCS), and transcranial magnetic stimulation (TMS), has been instrumental in developing neurofeedback techniques. However, the application of these tools in patients with disorders of consciousness (DoC) presents unique challenges. In this narrative review, we explore the use of neurofeedback in treating patients with DoC. More specifically, we discuss the advantages and challenges of using tools such as EEG neurofeedback, tDCS, TMS, and BCI for these conditions. Ultimately, we hope to provide the neuroscientific community with a comprehensive overview of neurofeedback and emphasize its potential therapeutic applications in severe cases of impaired consciousness levels. Full article
(This article belongs to the Special Issue Applications of EEG in Neural Rehabilitation)
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10 pages, 411 KiB  
Review
EEG-Neurofeedback as a Potential Therapeutic Approach for Cognitive Deficits in Patients with Dementia, Multiple Sclerosis, Stroke and Traumatic Brain Injury
by Irini Vilou, Aikaterini Varka, Dimitrios Parisis, Theodora Afrantou and Panagiotis Ioannidis
Life 2023, 13(2), 365; https://doi.org/10.3390/life13020365 - 29 Jan 2023
Cited by 8 | Viewed by 3160
Abstract
Memory deficits are common in patients with dementia, such as Alzheimer’s disease, but also in patients with other neurological and psychiatric disorders, such as brain injury, multiple sclerosis, ischemic stroke and schizophrenia. Memory loss affects patients’ functionality and, by extension, their quality of [...] Read more.
Memory deficits are common in patients with dementia, such as Alzheimer’s disease, but also in patients with other neurological and psychiatric disorders, such as brain injury, multiple sclerosis, ischemic stroke and schizophrenia. Memory loss affects patients’ functionality and, by extension, their quality of life. Non-invasive brain training methods, such as EEG neurofeedback, are used to address cognitive deficits and behavioral changes in dementia and other neurological disorders by training patients to alter their brain activity via operant activity. In this review paper, we analyze various protocols of EEG neurofeedback in memory rehabilitation in patients with dementia, multiple sclerosis, strokes and traumatic brain injury. The results from the studies show the effectiveness of the ΕΕG-NFB method in improving at least one cognitive domain, regardless of the number of sessions or the type of protocol applied. In future research, it is important to address methodological weaknesses in the application of the method, its long-term effects as well as ethical issues. Full article
(This article belongs to the Special Issue Applications of EEG in Neural Rehabilitation)
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