99 research outputs found
Conception et étude préliminaire d'un protocole de neurofeedback visant à autoréguler un marqueur EEG de la somnolence
International audienceNeurofeedback (NF) consists in using electroencephalographic (EEG) measurements to guide users to perform a cognitive learning using information coming from their own brain activity, by means of a real-time sensory feedback (e.g., visual or auditory). Many NF approaches have been studied to improve atten-tional abilities, notably for attention deficit hyper activity disorder. However, to our knowledge, no NF solution has been proposed to specifically reduce drowsiness. Thus, we propose an EEG-NF solution to train users to self-regulate an EEG marker of drowsiness, and evaluate it with a preliminary study. Results with five healthy subjects showed that three of them could learn to self-regulate this EEG marker with a relatively short number of NF sessions (up to 8 sessions of 40 min). Clinical trials with sleep-deprived subjects should begin in 2019 to study possible cognitive and clinical benefits of this self-regulation. This NF solution implementation is available for free, with the OpenViBE platform, under the AGPL-3.0 license.Le neurofeedback (NF) consiste à utiliser des mesures électroencéphalographiques (EEG) pour aider les utilisateurs à effectuer un apprentissage cognitif en utilisant des informations provenant de leur propre activité cérébrale, au moyen d'un retour sensoriel en temps réel (visuel ou auditif, par exemple). De nombreuses approches du NF ont été étudiées pour améliorer les capacités d'attention, notamment pour le trouble d'hyperactivité avec déficit de l'attention. Cependant, à notre connaissance, aucune solution de NF n'a été proposée pour réduire spécifiquement la somnolence. Ainsi, nous proposons une solution de NF-EEG pour former les utilisateurs à l’autorégulation d’un marqueur EEG de la somnolence et l’évaluer avec une étude préliminaire. Les résultats, avec cinq sujets sains, ont montré que trois d'entre eux pourraient apprendre à autoréguler ce marqueur EEG avec un nombre relativement court de séances de NF (jusqu'à 8 séances de 40 min). Les essais cliniques sur des sujets privés de sommeil devraient commencer en 2019 pour étudier les avantages cognitifs et cliniques possibles de cette autorégulation. Cette mise en œuvre de la solution de NF est disponible gratuitement, avec la plateforme OpenViBE, sous la licence AGPL-3.0
Design and Preliminary Study of a Neurofeedback Protocol to reduce Drowsiness
International audienceNeuroFeedback (NF) consists in using electroencephalographic (EEG) measurements to guide users to perform a cognitive learning using information coming from their own brain activity, by means of a real-time sensory feedback (e.g., visual or auditory)[4]. Many NF approaches have been studied to improve attentional abilities, notably for Attention Deficit Hy-peractivity Disorder [1, 2]. However, to our knowledge, no NF solution has been proposed to specifically reduce drowsiness. Thus, we propose a complete EEG-NF solution to train users to self-regulate an EEG marker of drowsiness. This marker is based on a ratio of beta over theta/alpha power in Cz electrode. In addition to this EEG marker of drowsiness, we also carefully selected and designed the duration, the sequencing, the objective evaluation metrics and the visual and audio feedback to use in for each NF session. Preliminary study with five healthy subjects showed that three of them could learn to self-regulate this EEG marker with a relatively short number of NF sessions (up to 8 sessions of 40 min). Clinical trials with sleep-deprived subjects are expected to begin in 2019 to study possible cognitive and clinical benefits of this self-regulation. The implementation of this NF solution is available for free 1 , with the OpenViBE platform [3], under the AGPL-3.0 license
Neurofeedback Therapy for Enhancing Visual Attention: State-of-the-Art and Challenges
We have witnessed a rapid development of brain-computer interfaces (BCIs) linking the brain to external devices. BCIs can be utilized to treat neurological conditions and even to augment brain functions. BCIs offer a promising treatment for mental disorders, including disorders of attention. Here we review the current state of the art and challenges of attention-based BCIs, with a focus on visual attention. Attention-based BCIs utilize electroencephalograms (EEGs) or other recording techniques to generate neurofeedback, which patients use to improve their attention, a complex cognitive function. Although progress has been made in the studies of neural mechanisms of attention, extraction of attention-related neural signals needed for BCI operations is a difficult problem. To attain good BCI performance, it is important to select the features of neural activity that represent attentional signals. BCI decoding of attention-related activity may be hindered by the presence of different neural signals. Therefore, BCI accuracy can be improved by signal processing algorithms that dissociate signals of interest from irrelevant activities. Notwithstanding recent progress, optimal processing of attentional neural signals remains a fundamental challenge for the development of efficient therapies for disorders of attention
A subject-specific neurofeedback approach for cognitive enhancement
La técnica de neurofeedback (NF) permite el aprendizaje de la auto-regulación de la actividad cerebral, por la cual los usuarios pueden aprender a modificar (hasta un cierto grado) patrones de la actividad cerebral. Un punto clave del NF en la práctica es la técnica de registro de la actividad cerebral, donde el electroencefalograma (EEG) es la más usada debido a que es no invasiva, portátil y tiene una buena resolución temporal. La investigación en neurociencia ha reportado en repetidas ocasiones la relación de determinadas funciones cognitivas y desórdenes psiquiátricos con las oscilaciones del EEG. Por lo tanto, no es sorprendente que la regulación de estas oscilaciones conlleve efectos en comportamiento. Por ejemplo, muchos estudios han aplicado esta técnica de NF para aumentar funciones cognitivas como memoria de trabajo, atención y habilidades visuoespaciales, usualmente evaluadas en usuarios sanos. Además se ha aplicado NF para el tratamiento de desórdenes psiquiátricos tales como el trastorno por déficit de atención con hiperactividad (TDAH), depresión, epilepsia y tinitus, entre otros. El EEG es una señal no estacionaria que presenta una variabilidad inherente entre usuarios en los correlatos de procesos mentales. Sin embargo, la gran mayorÃa de técnicas de NF desarrolladas hasta el momento son genéricas en el sentido de que no se adaptan a los patrones individuales de EEG de cada usuario. En este sentido ha habido una tendencia en los últimos años hacia el uso de técnicas de NF especÃficas por medio de la adaptación de algunos métodos involucrados en el procedimiento. Esta tesis aborda el diseño de una técnica de NF dentro de un framework unificado, y muestra su viabilidad por medio de la implementación de tres estudios de NF consistentes en el incremento de la actividad en alpha superior para mejora cognitiva, evaluada en usuarios sanos, pacientes con depresión mayor y niños con TDAH. Una disciplina que viene a la mente cuando pensamos en cómo individualizar la técnica de NF son las interfaces cerebro-computador (BCIs). Las BCIs es una tecnologÃa reciente cuyo objetivo es abrir un canal de comunicación entre un humano y un dispositivo usando únicamente la actividad cerebral para mejor la calidad de vida de personas con graves deficiencias motoras. Un punto clave de las BCIs es que los métodos de procesamiento de la señal se adaptan a cada usuario y momento de utilización de la tecnologÃa. Esto se logra usualmente por medio de una fase de calibración ejecutada antes de la operación en lÃnea. En esta fase de calibración los usuarios realizan tareas mentales que permiten medir algunos correlatos de EEG que son usados para calcular filtros individualizados, por ejemplo en términos de filtrado de artefactos y detección de tareas mentales. Después estos filtros se aplican en lÃnea al EEG para decodificar las tareas mentales, accionando en consecuencia el dispositivo. Tomando el framework de BCI como referencia, proponemos los siguientes métodos individualizados: (1) un método de filtrado de artefactos en tiempo real (usando separación ciega de fuentes) para eliminar los artefactos de los patrones cerebrales de interés; (2) un método novedoso para la individualización de los patrones cerebrales de acuerdo a la combinación de registros de EEG en dos condiciones (estado de reposo y tarea activa); (3) un método para calcular el nivel de trabajo de los patrones cerebrales (baseline) por sujeto y sesión; y (4) una variedad de métodos y métricas para evaluar los efectos del NF en los patrones cerebrales (post-análisis). Para evaluar la viabilidad y validez experimental de esta técnica de NF, llevamos a cabo una implementación de un protocolo de NF basado en el incremento de la actividad en alpha superior para mejora cognitiva, evaluada en tres estudios distintos de NF involucrando usuarios sanos, pacientes con depresión y niños con TDAH. Estos estudios investigaron si individuos sanos, con depresión y ADHD son capaces de incrementar la potencia en alpha superior por medio de NF y, si es asÃ, si estos efectos están relacionados con efectos en comportamiento (rendimiento cognitivo o escalas clÃnicas). 1. El primer estudio investigó los efectos de una única sesión de NF en usuarios sanos (N = 19) en un diseño experimental con falso feedback. Este estudio mostró un incremento en la potencia en alpha superior en la tarea activa (inmediatamente después del NF) asà como un incremento en potencia en alpha superior durante la tarea de rotación mental (intervalo preestÃmulo), únicamente para el grupo experimental. Ambos grupos mejoraron en rendimiento cognitivo, con una mejora superior para el grupo experimental. Sin embargo una única sesión parece insuficiente para producir diferencias significativas entre grupos. 2. El segundo estudio investigó los efectos de ocho sesiones de NF en pacientes con depresión (N = 60) en un estudio controlado. Este estudio mostró un incremento en la potencia en alpha superior en la tarea activa (pre-post estudio) para el grupo experimental. Estos efectos no estuvieron restringidos espacialmente o espectralmente al parámetro de NF. Se encontró un incremento de actividad a nivel de las fuentes cerebrales en alpha para el grupo experimental, localizado en el giro cingulado anterior (sgACC, BA 25). El grupo experimental mostró un incremento en rendimiento asà como un incremento en velocidad de procesamiento medido por un test de memoria de trabajo después del NF, sugiriendo por tanto que los sÃntomas cognitivos de pacientes con depresión pueden aliviarse por medio de este procedimiento. 3. El tercer estudio investigó los efectos de 18 sesiones de NF en niños con TDAH (N = 20) en un estudio preliminar no controlado. Este estudio mostró un incremento en la potencia (relativa y absoluta) en alpha superior en la tarea activa (pre-post estudio). Mientras que los cambios pre-post estudio estuvieron restringidos mayormente a la banda alpha superior, los efectos dentro de la sesión mostraron un decremento en potencia absoluta en las bajas frecuencias (se debe notar que los niños con TDAH usualmente tienen un exceso de actividad en bajas frecuencias). Los padres indicaron una mejora clÃnica en los niños con respecto a inatención e hiperactividad/impulsividad, y los tests neuropsicológicos mostraron una mejora en memoria de trabajo. En resumen, estos resultados muestran que la técnica de NF se adaptó a la gran variabilidad de los patrones cerebrales entre sujetos y sesiones. Además, estas tres poblaciones fueron capaces de auto-regular los patrones cerebrales con una consecuente mejora tanto en rendimiento cognitivo y como en escalas clÃnicas (en el caso de niños con TDAH). Aunque la principal contribución de esta tesis está en los métodos y en la implementación de una técnica individualizada de NF, los estudios de NF aquà presentados son novedosos en sà mismos y los resultados que se extraen de ellos constituyen una contribución añadida de esta tesis.Neurofeedback (NF) promotes the learning of the self-regulation of brain activity, where subjects can learn to shape (to a certain degree) some patterns of brain activity. A key practical point of NF is the recording technique of brain activity, where the electroencephalogram (EEG) is the most widely used one as it is non-invasive, portable and presents a good temporal resolution. Neuroscience research has repeatedly reported the relation of cognitive functions and some psychiatric disorders to EEG oscillations. Thus, it is not surprising that the regulation of EEG oscillations yields behavioral effects. For instance, a large body of research has applied NF for the enhancement of cognitive functions such as working memory, attention and visuospatial abilities, usually applied to healthy subjects. NF has been also applied for the treatment of psychiatric disorders such as attention-deficit/hyperactive disorder (ADHD), depression, epilepsy and tinnitus, among others. EEG is a non-stationary signal that presents an inherent variability among subjects in the EEG correlates of brain processes. However, the large majority of NF procedures developed to date are subject-generic in the sense that they are not adapted to the individual EEG patterns of each subject. In this direction, there has been a trend in recent years towards the use of subject-specific NF procedures by adapting some methods involved in that procedure. This thesis addresses the design of a subject-specific NF approach in a unified framework, and shows its feasibility by implementing three different NF studies of upper alpha up-regulation for cognitive enhancement in healthy subjects, patients with major depressive disorder and children diagnosed with ADHD. One discipline that comes to mind when thinking about how to individualize EEG-based NF procedures is the brain-computer interfaces (BCIs). BCIs is a recent technology whose objective is to open a communication channel between a human and a device using only brain activity to improve the quality of life of people with severe motor disability. A key point of BCIs is that the signal processing methods are adapted for each subject and time of use of the technology. This is commonly achieved by a calibration phase before the online operation. In this calibration phase, the subjects perform metal tasks that allow to measure some EEG correlates that are used to compute subject-specific filters, for example in terms of filtering the EEG artifacts and detecting the mental tasks. These filters are then applied during the online operation phase to the ongoing EEG to decode the mental tasks, actuating the devices accordingly. Taking the BCI framework as a reference, we propose the following individualized methods: (1) a real-time artifact filtering method (using blind source separation) to remove the artifacts from the brain patterns of interest; (2) a novel method for the individualization of the brain patterns according to the combination of EEG recordings in two conditions (resting state and task-related activity); (3) a method for computing the baseline working level of the brain patterns per subject and session; and (4) a variety of methods and metrics to assess the effects of NF on the brain patterns (post-analysis). In order to demonstrate the feasibility and experimental validity of this subject-specific NF approach, we carried out an implementation of a NF protocol of upper alpha up-regulation for cognitive enhancement, evaluated in three different NF studies involving healthy subjects, depressed patients and ADHD children. These studies investigated whether healthy, depressed and ADHD individuals could learn to increase the individual upper alpha power by means of NF, and whether these effects were related to behavioral effects on either cognition or clinical outcome. 1. The first study investigated the effects of a single NF session on healthy participants (N = 19) following a sham-controlled experimental design. This study showed increased upper alpha power in task-related activity (immediately after training), as well as increased pre-stimulus upper alpha power during the execution of a mental rotation task, apparen only for the experimental group. Both groups improved cognitive performance, with a more prominent improvement for the experimental group. However a single session seems to be insufficient to yield significant differences between groups. 2. The second study investigated the effects of eight NF sessions on depressed patients (N = 60) in a controlled study. This study showed increased upper alpha power in task-related activity (pre-post study) for the experimental group, not spatially or spectrally restricted to the trained parameter. A current density increase appeared at brain source level in alpha for the experimental group, localized in the subgenual anterior cingulate cortex (sgACC, BA 25). The experimental group showed increased performance as well as improved processing speed in a working memory test after the training, thus suggesting that the cognitive symptoms of depressed patients could be alleviated by this typeof procedure. 3. The third study investigated the effects of 18 NF sessions on ADHD children (N = 20) in a preliminary uncontrolled study. This study showed increased relative and absolute upper alpha power in task-related activity (pre-post study). While the pre-post study effects were mainly restricted to upper alpha, within-session analysis showed an absolute power decrease in slow-frequency oscillations (note that ADHD children commonly show an excess of slow-frequency activity). Parents rated a clinical improvement in children regarding inattention and hyperactivity/impulsivity, and neurophysiological tests showed an improvement in working memory. In summary, these results show that the NF technique was able to accommodate the large variability of the brain patterns among subjects and over sessions. In addition, these three populations were able to self-regulate the targeted brain patterns with a consequent improvement in cognitive performance and clinical outcome (in the case of ADHD children). Although the main contribution of the thesis is on the methods and on the implementation of the subject-specific NF procedure, the NF studies herein presented are novel and the results extracted from them constitute an added contribution of this thesis
Smart Biofeedback
Smart biofeedback is receiving attention because of the widespread availability of advanced technologies and smart devices that are used in effective collection, analysis, and feedback of physiologic data. Researchers and practitioners have been working on various aspects of smart biofeedback methodologies and applications by using wireless communications, the Internet of Things (IoT), wearables, biomedical sensors, artificial intelligence, big data analytics, clinical virtual reality, smartphones, and apps, among others. The current paradigm shift in information and communication technologies (ICT) has been propelling the rapid pace of innovation in smart biofeedback. This book addresses five important topics of the perspectives and applications in smart biofeedback: brain networks, neuromeditation, psychophysiological psychotherapy, physiotherapy, and privacy, security, and integrity of data
Optimising perceptuo-motor performance and learning with EEG neurofeedback
The neurobiological functions of an organism serve to assist its adaptation to behaviourally challenging environments, which commonly involves the learning and refinement of perceptuo-motor skills. The intensity and time scale at which this occurs is critical towards survival. Previous work has observed that the neurochemical and neuroelectric (EEG) operation of specific functional systems is upregulated during so-called ‘activated’ states of behaviour. Thus it has recently been shown that artificial (i.e. exogenous) stimulation of such systems via pharmacological or electrical means can successfully modulate as well as enhance learning and associated behavioural performance. We hypothesized that neurofeedback, which is implemented through non-invasive volitional control of electrocortical rhythms (EEG), offers an alternate and natural (i.e. endogenous) way to modulate and thereby stimulate analogous systems. Study 1 shows that neurofeedback is a viable and beneficial method for improving the acquisition and performance of perceptuo-motor skills in trainee microsurgeons, when compared to a wait-list control group. With the aid of transcranial magnetic stimulation (TMS), Study 2 demonstrates for the first time that 30 minutes of a single neurofeedback session directly leads to a robust and correlated change in corticomotor plasticity which is usually associated with learning or observed after exogenous stimulation. Lastly, Study 3 investigates the short-term modulation of one session of‘excitatory’ neurofeedback on the subsequent performance of a serial reaction-time task (SRTT), an experimental paradigm widely used as a model for procedural perceptuo-motor learning. In conclusion, this thesis contributes original evidence of direct as well as long-term functional enhancements following EEG neurofeedback, and supports its use as a safe, non-invasive and natural method for improving human perceptuo-motor performance and learning.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
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Spectral Dynamics and Therapeutic Implications of the Theta/Alpha Crossover in Alpha-Theta Neurofeedback
Article describes study examining 182 alpha-theta session graphs from 10 subject case files for interactions between frequency band activity and subject reports of imagery or biographical memories during crossovers, as well as treatment outcomes
The EEG Profile of Hemispatial Neglect and Neurofeedback as an Intervention
There is evidence to suggest that interventions targeting alertness could be effective in the rehabilitation of hemispatial neglect. Alertness correlates in the EEG with decreased theta and increased beta activity and training up beta/theta ratios using EEG neurofeedback has resulted in particularly beneficial results in children with ADHD with recognised deficits of alertness. Experiment I showed that neglect patients had significantly reduced beta activity compared to age-matched controls, consistent with an alertness deficit underpinning neglect and suggesting that the symptoms of neglect could be ameliorated by the same neurofeedback training protocol applied in ADHD.
The effectiveness of EEG neurofeedback training of beta power with a theta inhibit has not been investigated in older adults or stroke patients. Therefore, Experiment II used EEG neurofeedback training to enhance beta in older adults. Compared to controls, the neurofeedback group showed significantly increased beta activity in the post-assessment quantitative EEG, demonstrating that older adults can modulate their EEG through neurofeedback training and laying the foundations for extending training to neglect patients.
Experiment III employed the same training protocol in seven neglect patients. EEG activity was monitored in regular training sessions conducted over a six-week period and it was found that normalization of baseline EEG activity was associated with a remediation of impairments across several outcome assessments. Detailed analysis of across- and within-session EEG data found that a sub-group of patients showed evidence of spontaneous increases in beta activity that were related to additional improvements in outcome measures. However, there was no evidence that EEG modulation was due to the neurofeedback training.
In sum, this thesis reports two novel findings. Firstly, neglect is associated with an EEG profile that is consistent with an alertness deficit. Secondly, recovery in severely impaired neglect patients is associated with enhanced beta activity
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Real-Time Electroencephalogram Sonification for Neurofeedback
Electroencephalography (EEG) is the measurement via the scalp of the electrical activity of the brain. The established therapeutic intervention of neurofeedback involves presenting people with their own EEG in real-time to enable them to modify their EEG for purposes of improving performance or health.
The aim of this research is to develop and validate real-time sonifications of EEG for use in neurofeedback and methods for assessing such sonifications. Neurofeedback generally uses a visual display. Where auditory feedback is used, it is mostly limited to pre-recorded sounds triggered by the EEG activity crossing a threshold. However, EEG generates time-series data with meaningful detail at fine temporal resolution and with complex temporal dynamics. Human hearing has a much higher temporal resolution than human vision, and auditory displays do not require people to focus on a screen with their eyes open for extended periods of time – e.g. if they are engaged in some other task. Sonification of EEG could allow more rapid, contingent, salient and temporally detailed feedback. This could improve the efficiency of neurofeedback training and reduce the number and duration of sessions for successful neurofeedback.
The same two deliberately simple sonification techniques were used in all three experiments of this research: Amplitude Modulation (AM) sonification, which maps the fluctuations in the power of the EEG to the volume of a pure tone; and Frequency Modulation (FM) sonification, which uses the changes in the EEG power to modify the frequency. Measures included, a listening task, NASA task load index; a measure of how much work it was to do the task, Pre & post measures of mood, and EEG.
The first experiment used pre-recorded single channel EEG and participants were asked to listen to the sound of the sonified EEG and try and track the activity that they could hear by moving a slider on a computer screen using a computer mouse. This provided a quantitative assessment of how well people could perceive the sonified fluctuations in EEG level. The tracking accuracy scores were higher for the FM sonification but self-assessments of task load rated the AM sonification as easier to track.
The second experiment used the same two sonifications, in a real neurofeedback task using participants own live EEG. Unbeknownst to the participants the neurofeedback task was designed to improve mood. A Pre-Post questionnaire showed that participants changed their self-rated mood in the intended direction with the EEG training, but there was no statistically significant change in EEG. Again the FM sonification showed a better performance but AM was rated as less effortful. The performance of sonifications in the tracking task in experiment 1 was found to predict their relative efficacy at blind self-rated mood modification in experiment 2.
The third experiment used both the tracking as in experiment 1 and neurofeedback tasks as in experiment 2, but with modified versions of the AM and FM sonifications to allow two-channel EEG sonifications. This experiment introduced a physical slider as opposed to a mouse for the tracking task. Tracking accuracy increased, but this time no significant difference was found between the two sonification techniques on the tracking task. In the training task, once more the blind self-rated mood did improve in the intended direction with the EEG training, but as again there was no significant change in EEG, this cannot necessarily be attributed to the neurofeedback. There was only a slight difference between the two sonification techniques in the effort measure.
In this way, a prototype method has been devised and validated for the quantitative assessment of real-time EEG sonifications. Conventional evaluations of neurofeedback techniques are expensive and time consuming. By contrast, this method potentially provides a rapid, objective and efficient method for evaluating the suitability of candidate sonifications for EEG neurofeedback
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