Validating the efficacy of neurofeedback for optimising performance.

The field of neurofeedback training has largely proceeded without validation. Here we review our studies directed at validating SMR, beta and alpha–theta protocols for improving attention, memory, mood and music and dance performance in healthy participants. Important benefits were demonstrable with cognitive and neurophysiological measures which were predicted on the basis of regression models of learning. These are initial steps in providing a much needed scientific basis to neurofeedback, but much remains to be done

EEG data processing in ADHD diagnosis and neurofeedback

In this paper, EEG data processing was conducted in order to define the parameters for neurofeedback. A new survey was conducted based on a brief review of previous research. Two groups of participants were chosen: ADHD (3) and nonADHD (14). The main part of this study includes EEG signal data pre-processing and processing. We have outlined statistical features of observed EEG signals such as mean value, grand-mean value and their ratios. It can be concluded that an increase in grand-mean values of power theta-low beta ratio on Cz electrode gives confirmation of previous research. The value of alpha-delta power ratio higher than 1 on C3, Cz, P3, Pz, P4 in ADHD group is proposed as a new approach to classification. Based on these conclusions we will design a neurofeedback protocol as a continuation of this work

Effects of EEG-neurofeedback training on brain functional connectivity

Tese de Mestrado Integrado, Engenharia Biomédica e Biofísica, 2022, Universidade de Lisboa, Faculdade de CiênciasO neurofeedback (NF) consiste em medir a atividade cerebral, usando técnicas como a eletroencefalografia (EEG) ou a imagem por ressonância magnética funcional (fMRI), e apresentar ao participante, em tempo real, uma representação de um padrão de atividade de interesse, enquanto lhe é pedido para manipular essa mesma representação através da autorregulação da atividade cerebral (Sitaram et al., 2017). As bases neurofisiológicas desta técnica ainda não são conhecidas na sua totalidade, apesar de vários estudos terem demonstrado que o treino através de NF tende a reorganizar as redes cerebrais. Posto isto, existem poucos estudos que tentam comparar a influência da utilização de diferentes modalidades sensoriais de apresentação do “feedback” nos resultados do treino por NF em EEG, e os poucos estudos existentes não investigam possíveis efeitos nas métricas de conectividade funcional do cérebro. Neste projeto, pretendemos avaliar o efeito da utilização de diferentes modalidades de “feedback” no treino de NF através EEG (EEG-NF) para o incremento da amplitude relativa da banda alfa superior no canal Cz, e investigar se existe um efeito significativo nos padrões de conectividade funcional do cérebro. Para esse fim, será efetuada a análise de dados previamente recolhidos em 20 participantes saudáveis que realizaram quatro sessões de treino por EEG-NF, que visava incrementar a densidade espectral na banda alfa superior, e que utilizaram diferentes modalidades de feedback (visual, realidade virtual (VR), e auditiva). Os dados de EEG foram pré-processados, com remoção de artefactos através de análise de componentes independentes. Adicionalmente, duas técnicas de re-referenciação do sinal EEG foram utilizadas para comparação posterior, sendo estas a re-referenciação para a média de todos os canais EEG, e a re-referenciação através da aplicação de um Laplaciano de Superfície com parâmetro de rigidez de valores 4 e 3, respetivamente. A avaliação dos resultados foi efetuada a diversos níveis, com a análise: i) das variações intra-sessão da amplitude relativa da banda alfa superior no canal Cz, ii) da distribuição topológica da banda alfa superior no decorrer do treino, iii) das variações intrasessão dos padrões de conectividade funcional da banda alfa superior, utilizando a parte imaginária da coerência como métrica de conectividade, e iv) por fim, em termos de uma análise de redes, que visava avaliar a importância de nodos de rede, verificada através das métricas como betweeness centrality e força, da atividade segregada, verificada através da métrica de transitividade, e da atividade integrada, verificada através de métricas como caminho característico e eficiência global da rede cerebral. Relativamente aos resultados para a análise espectral e topológica, encontram-se correlações estatisticamente significativas entre o valor da amplitude relativa da banda alfa superior e o número de set, em todos os grupos, principalmente nas duas primeiras sessões, sendo cada set composto por 6 trials com duração de 30 segundos Posto isto, não são registadas diferenças estatisticamente significativas intra-sessão, isto é, do set 1 para o set 5 de cada sessão. Para a análise topológica, não se realizaram testes de significância, mas é possível visualizar uma acentuação da amplitude relativa da banda alfa superior em zonas parietais/occipitais, e é também possível verificar que o treino realizado, não afetou somente a banda de interesse mas também a banda theta, cuja atividade não focal diminui, a banda alfa inferior, cuja amplitude relativa parece incrementar. Relativamente aos resultados da análise de conetividade, os mesmos sugerem que o treino de EEG-NF para o incremento da banda alfa superior resulta num incremento mais pronunciado nas fases iniciais do treino, isto é, nas duas primeiras sessões de treino. Este incremento é representado pelo do número de canais que apresentam conectividade funcional com a zona parietal central, com canais como o Pz, e com a zona parietal direita, CP6, P4, entre outros, independentemente da modalidade de feedback, ou seja, para a generalidade dos "Learners”. De facto, os próprios canais parietais direitos, P4, P8, CP6, TP10 aumentam de forma estatisticamente significativa a conectividade entre eles. Isto parece indiciar a criação de um complexo focado na zona parietal direita. Em todas as modalidades, à exceção da VR, verifica-se ainda um aumento significativo intra-sessão da transitividade e eficiência global enquanto uma diminuição estatisticamente significativa intra-sessão é observada para a métrica caminho característico. Posto isto, a metodologia de neurofeedback no contexto experimental que foi implementado, parece promover a atividade cerebral segregada, isto é, a atividade que resulta de uma atividade cerebral mais localizada, e também integrada, isto é, que resulta da integração da atividade de áreas cerebrais dispersas. A não existência de variações significativas na modalidade VR não parece estar relacionada com a modalidade em si, mas sim devido a uma menor amostra do respetivo grupo. Assim, futuramente será necessário aumentar a amostra, pelo menos para este grupo, por forma a poderem ser extraídos resultados significativos da análise do mesmo. Interessantemente, e independentemente do método de rereferenciação utilizado, enquanto para o grupo do treino NF para a modalidade visual se observa a partir da terceira sessão de treino a estabilização do número de conexões funcionais entre os diferentes elétrodos, ou seja deixa de haver um crescimento acentuado da transitividade e da eficiência global com diminuição simultânea do caminho característico, para o grupo do treino NF com a modalidade auditiva a generalidade dos incrementos verificados, estão presentes em todas as sessões, incluindo a última sessão. No referente ao estudo sobre o método de re-referenciação dos dados EEG, com interesse específico na utilização de um Laplaciano de superfície comparativamente à simples utilização da média dos sinais EEG, a análise topológica das diferentes bandas cerebrais confirma que a utilização do Laplaciano de superfície contribuiu para aumento da resolução espacial dos dados de EEG, uma vez que atenuou para as diferentes bandas a amplitude relativa da atividade periférica, ou seja não focal, que estará relacionada com frequências espaciais mais baixas. Relativamente à análise da conectividade funcional intra-sessão, verifica-se que a aplicação do Laplaciano se reflete na mudança das configurações de variações de conexões funcionais no cérebro, nomeadamente eliminando determinados aumentos estatisticamente significativos, por exemplo para a sessão 1 dos “Learners”, após a aplicação do Laplaciano de superfície, o incremento da conectividade funcional entre Pz e O2 deixa de ser estatisticamente significativo. Possivelmente, isto poderá estar relacionado com uma eliminação de conexões espúrias. Também na análise de redes, a aplicação do Laplaciano afeta a configuração dos dados e outputs embora não se consiga precisar uma relação causa efeito. Posto isto, a variação da própria configuração do Laplaciano, no que se refere à rigidez do mesmo, de parâmetro m=4 para m=3, não se traduz em resultados tão diferentes, pese embora algumas alterações notadas na análise de redes. De facto, para análise de conectividade funcional, os heatmaps resultantes da aplicação de Laplaciano de superfície com m=4, são exatamente iguais aos heatmaps resultantes da aplicação de Laplaciano de superfície com m=3. Quanto à análise de redes, nomeadamente nas métricas de transitividade, caminho característico e eficiência global, se verificarmos os gráficos e tabelas apresentadas, apesar de serem notados ligeiros desvios quer nas curvas quer em valores de correlação ou variação intra-sessão, o nível de significância é quase sempre atingido, independentemente da rigidez do Laplaciano aplicado, para a mesma sessão. Posto isto, não é possível reportar claramente uma relação causa-efeito vantajosa decorrente da aplicação do Laplaciano de superfície nos dados aqui tratados. De facto, reitera-se que, pela análise topológica se confirma que este possa estar associado a um filtro espacial, mas nas restantes análises não se consegue confirmar se este “melhorou ou não” os nossos dados.Neurofeedback (NF) consists in measuring brain activity and presenting a real-time representation of a brain activity pattern of interest to an individual, while instructing him to manipulate the feedback representation through self-regulation. The neurophysiological basis for NF remains to be fully elucidated, whereas several studies support that NF training tends to reorganize the brain networks. Only a handful of studies compare how different feedback sensory modalities affect the outcomes of EEG-based NF training, and none of them analyzes such effect on the functional connectivity or network metrics. In this project, we evaluate how using different feedback modalities on the EEG-based NFtraining will affect the brain’s functional connectivity, by analyzing previously collected data from a total of 20 healthy subjects, who underwent four sessions of upper-alpha (UA) band EEG-based NF training, with different feedback modalities (visual, auditory, or virtual reality (VR)). The EEG data was preprocessed and re-referenced with three different methods for posterior comparison, the common average reference (avgREF), and spline lines Surface Laplacian with stiffness parameters equals 4 and 3. The data were evaluated in terms of: i) the within-sessions’ variations of the relative amplitude of the UA at the Cz channel, ii) relative band amplitude topological distribution across sets and sessions, iii) the within-sessions’ variations of the UA functional connectivity patterns, computed with the imaginary part of coherency, and iv) an UA band network analysis of the metrics betweenness centrality, strength, transitivity, charpath and global efficiency. Our results suggest that the UA EEG-based NF-training is associated with an early increment of functional connections with channels over parietal areas (e.g. Pz), independently of the feedback sensory modality. All the modalities, except the VR, which had a reduced sample, verify statistically significant intra-session increases in the transitivity and global efficiency, while showing statistically significant intra-session decreases of the charpath, suggesting that this protocol promotes both clustered and integrated brain activity. While for the visual NF-training group the third session seems to be a breakthrough point, where the number of functional connections stabilize, for the auditory NF-training group longer lasting “variations” are reported. Through the topological analysis we confirm that the application of Laplacian leads to higher spatial resolutions on the EEG data. Regarding the connectivity analysis and network analysis, we note that the application of the Surface Laplacian creates different values when compared to the avgREF data, yet no advantageous outcome can be reported

Comparing EEG-neurofeedback visual modalities between screen-based and immersive head-mounted VR

Tese de Mestrado Integrado, Engenharia Biomédica e Biofísica (Sinais e Imagens Médicas), 2022, Universidade de Lisboa, Faculdade de CiênciasNeurofeedback (NF) can be defined as a form of biofeedback that trains subjects to have self-control over brain their functions, by providing real-time feedback of their own cerebral activity. This activity can be presented in various forms, with auditory and visual feedback being the most common. Recently, NF has been investigated as a potential treatment for various clinical conditions associated with abnormal brain activity or cognitive capacities. However, the greater research focus is not discussing how the feedback should be presented. The chosen modality for any NF training system may strongly influence the training protocol and consequently the outcome of the experiment. In this thesis, a systematical comparison between two different type of visual modalities (ScreenBased vs. immersive-virtual reality (VR) ) was performed with the goal to evaluate the effectiveness of each modality on the NF training results. Data from two previous studies, recorded on healthy participants, in protocols that targeted the increase in the upper alpha (UA) band power measured at the EEG electrode Cz was used. This was then divided into two modality groups: Screen-Based modality group (N = 8) and the Immersive-VR group (N = 4). An extensive data processing and cleaning protocol was applied to both groups and the training effectiveness was measured through band power calculation, the definition of learning ability indexes and the application of statistical tests. Results showed that, both groups had a generally positive training effect within sessions, however data regarding different sessions is inconclusive and does not show clear evidence of up-regulation of the target feature. Additionally, when only considering within-session evolution, only the Immersive-VR modality group was able to maintain an increasing trend in all sessions. One of the main limitations of this study was the sample size, which was too small to determine the precise effect of NF training. Future work requires, not only an increase in sample size but also, the definition and incorporation of learning predictors that allow the pre-selection of subjects before the training sessions, in order to prevent high number of non-learners

Source-based neurofeedback methods using EEG recordings: training altered brain activity in a functional brain source derived from blind source separation

A developing literature explores the use of neurofeedback in the treatment of a range of clinical conditions, particularly ADHD and epilepsy, whilst neurofeedback also provides an experimental tool for studying the functional significance of endogenous brain activity. A critical component of any neurofeedback method is the underlying physiological signal which forms the basis for the feedback. While the past decade has seen the emergence of fMRI-based protocols training spatially confined BOLD activity, traditional neurofeedback has utilized a small number of electrode sites on the scalp. As scalp EEG at a given electrode site reflects a linear mixture of activity from multiple brain sources and artifacts, efforts to successfully acquire some level of control over the signal may be confounded by these extraneous sources. Further, in the event of successful training, these traditional neurofeedback methods are likely influencing multiple brain regions and processes. The present work describes the use of source-based signal processing methods in EEG neurofeedback. The feasibility and potential utility of such methods were explored in an experiment training increased theta oscillatory activity in a source derived from Blind Source Separation of EEG data obtained during completion of a complex cognitive task (spatial navigation). Learned increases in theta activity were observed in two of the four participants to complete 20 sessions of neurofeedback targeting this individually defined functional brain source. Source-based EEG neurofeedback methods using Blind Source Separation may offer important advantages over traditional neurofeedback, by targeting the desired physiological signal in a more functionally and spatially specific manner. Having provided preliminary evidence of the feasibility of these methods, future work may study a range of clinically and experimentally relevant brain processes targeting individual brain sources by source-based EEG neurofeedback

Mind over chatter: plastic up-regulation of the fMRI alertness network by EEG neurofeedback

EEG neurofeedback (NFB) is a brain-computer interface (BCI) approach used to shape brain oscillations by means of real-time feedback from the electroencephalogram (EEG), which is known to reflect neural activity across cortical networks. Although NFB is being evaluated as a novel tool for treating brain disorders, evidence is scarce on the mechanism of its impact on brain function. In this study with 34 healthy participants, we examined whether, during the performance of an attentional auditory oddball task, the functional connectivity strength of distinct fMRI networks would be plastically altered after a 30-min NFB session of alpha-band reduction (n=17) versus a sham-feedback condition (n=17). Our results reveal that compared to sham, NFB induced a specific increase of functional connectivity within the alertness/salience network (dorsal anterior and mid cingulate), which was detectable 30 minutes after termination of training. Crucially, these effects were significantly correlated with reduced mind-wandering 'on-task' and were coupled to NFB-mediated resting state reductions in the alpha-band (8-12 Hz). No such relationships were evident for the sham condition. Although group default-mode network (DMN) connectivity was not significantly altered following NFB, we observed a positive association between modulations of resting alpha amplitude and precuneal connectivity, both correlating positively with frequency of mind-wandering. Our findings demonstrate a temporally direct, plastic impact of NFB on large-scale brain functional networks, and provide promising neurobehavioral evidence supporting its use as a noninvasive tool to modulate brain function in health and disease

Induced brain activity as indicator of cognitive processes: experimental-methodical analyses and algorithms for online-applications

Die Signalverarbeitung von elektroenzephalographischen (EEG) Signalen ist ein entscheidendes Werkzeug, um die kognitiven Prozessen verstehen zu können. Beispielweise wird induzierte Hirnaktivität in mehreren Untersuchungen mit kognitiver Leistung assoziiert. Deshalb ist die Gewinnung von elektrophysiologischen Parametern grundlegend für die Charakterisierung von kognitiven Prozessen sowie von kognitiven Dysfunktionen in neurologischen Erkrankungen. Besonders bei Epilepsie treten häufig Störungen wie Gedächtnis-, oder Aufmerksamkeitsprobleme auf, zusätzlich zu Anfällen. Neurofeedback (bzw. EEG-Biofeedback) ist eine Therapiemethode, die zusätzlich zu medikamentösen- und chirurgischen Therapien bei der Behandlung vieler neurologischer Krankheiten, einschließlich Epilepsie, erfolgreich praktiziert wird. Neurofeedback wird jedoch meist dafür angewendet, eine Anfallsreduzierung zu erzielen. Dagegen wird eine Verbesserung kognitiver Fähigkeiten auf der Basis elektrophysiologischer Änderungen selten vorgesehen. Darüber hinaus sind die aktuellen Neurofeedbackstrategien für diesen Zweck ungeeignet. Der Grund dafür sind unter anderem nicht adäquate Verfahren für die Gewinnung und Quantifizierung induzierter Hirnaktivität. Unter Berücksichtigung der oben genannten Punkten wurden die kognitiven Leistungen von einer Patientengruppe (Epilepsie) und einer Probandengruppe anhand der ereignisbezogenen De-/Synchronisation (ERD/ERS) Methode untersucht. Signifikante Unterschiede wurden im Theta bzw. Alpha Band festgestellt. Diese Ergebnisse unterstützen die Verwertung von auf ERD/ERS basierten kognitiven Parametern bei Epilepsie. Anhand einer methodischen Untersuchung von dynamischen Eigenschaften wurde ein onlinefähiger ERD/ERS Algorithmus für zukünftige Neurofeedback Applikationen ausgewählt. Basierend auf dem ausgewählten Parameter wurde eine Methodik für die online Gewinnung und Quantifizierung von kognitionsbezogener induzierter Hirnaktivität entwickelt. Die dazugehörigen Prozeduren sind in Module organisiert, um die Prozessapplikabilität zu erhöhen. Mehrere Bestandteile der Methodik, einschließlich der Rolle von Elektrodenmontagen sowie die Eliminierung bzw. Reduktion der evozierten Aktivität, wurden anhand kognitiver Aufgaben evaluiert und optimiert. Die Entwicklung einer geeigneten Neurofeedback Strategie sowie die Bestätigung der psychophysiologischen Hypothese anhand einer Pilotstudie sollen Gegenstand der zukünftigen Arbeitschritte sein.Processing of electroencephalographic (EEG) signals is a key step towards understanding cognitive brain processes. Particularly, there is growing evidence that the analysis of induced brain oscillations is a powerful tool to analyze cognitive performance. Thus, the extraction of electrophysiological features characterizing not only cognitive processes but also cognitive dysfunctions by neurological diseases is fundamental. Especially in the case of epilepsy, cognitive dysfunctions such as memory or attentional problems are often present additionally to seizures. Neurofeedback (or EEG-biofeedback) is a psychological technique that, as a supplement to medication and surgical therapies, has been demonstrated to provide further improvement in many neurological diseases, including epilepsy. However, most efforts of neurofeedback have traditionally been dedicated to the reduction of seizure frequency, and little attention has been paid for improving cognitive deficits by means of specific electrophysiological changes. Furthermore, current neurofeedback approaches are not suitable for these purposes because the parameters used do not take into consideration the relationship between memory performance and event-induced brain activity. Considering all these aspects, the cognitive performance of a group of epilepsy patients and a group of healthy controls was analyzed based on the event-related de /synchronization (ERD/ERS) method. Significant differences between both populations in the theta and upper alpha bands were observed. These findings support the possible exploitation of cognitive quantitative parameters in epilepsy based on ERD/ERS. An algorithm for the online ERD/ERS calculation was selected for future neurofeedback applications, as the result of a comparative dynamic study. Subsequently, a methodology for the online extraction and quantification of cognitive-induced brain activity was developed based on the selected algorithm. The procedure is functionally organized in blocks of algorithms in order to increase applicability. Several aspects, including the role of electrode montages and the reduction or minimization of the evoked activity, were examined based on cognitive studies as part of the optimization process. Future steps should include the design of a special training paradigm as well as a pilot study for confirming the theoretical approach proposed in this work

Comparison of visual and auditory modalities for Upper-Alpha EEG-Neurofeedback

Electroencephalography (EEG) neurofeedback (NF) training has been shown to produce long-lasting effects on the improvement of cognitive function as well as the normalization of aberrant brain activity in disease. However, the impact of the sensory modality used as the NF reinforcement signal on training effectiveness has not been systematically investigated. In this work, an EEG-based NF training system was developed targeting the individual upper alpha (UA) band and using either a visual or an auditory reinforcement signal, so as to compare the effects of the two sensory modalities. Sixteen healthy volunteers were randomly assigned to the Visual or Auditory group, where a radius varying sphere or a volume-varying sound, respectively, reflected the relative amplitude of UA measured at EEG electrode Cz. Each participant underwent a total of four NF sessions, of approximately 40 min each, on consecutive days. Both groups showed significant increases in UA at Cz within sessions, and also across sessions. Effects subsequent to NF training were also found beyond the target frequency UA and scalp location Cz, namely in the lower-alpha and theta bands and in posterior brain regions, respectively. Only small differences were found on the EEG between the Visual and Auditory groups, suggesting that auditory reinforcement signals may be as effective as the more commonly used visual signals. The use of auditory NF may potentiate training protocols conducted under mobile conditions, which are now possible due to the increasing availability of wireless EEG systems.info:eu-repo/semantics/publishedVersio