As Interfaces Cérebro-Computador (do inglês Brain-Computer Interfaces BCI) são sistemas que visam permitir a interação entre usuários e máquinas por meio do monitoramento das atividades cerebrais. Sistemas de BCI são considerados como uma alternativa para que pessoas com perda severa ou total do controle motor, tais como as que sofrem de Esclerose Lateral Amiotrófica, possam contar com algum controle sobre o ambiente externo. Para mapear intenções individuais em operações de máquina, os sistemas de BCI empregam um conjunto de etapas que envolvem a captura e pré-processamento dos sinais cerebrais, a extração e seleção de suas características mais relevantes e a classificação das intenções. O projeto e a implementação de sistemas de BCI viáveis ainda são questões em aberto devido aos grandes desafios encontrados em cada uma de suas etapas. Esta lacuna motivou este trabalho de mestrado o qual apresenta uma avaliação dos principais extratores de características utilizados para classificar ensaios de imagética motora, cujos dados foram obtidos por meio de eletroencefalografia (EEG) e apresentam influências de artefatos, mais precisamente daqueles produzidos por interferências provenientes de atividades oculares (monitoradas por eletrooculografia EOG). Foram considerados sinais coletados pela BCI Competition IV-2b, os quais contêm informações sobre três canais de EEG e três outros de EOG. Como primeira etapa, foi realizado o pré-processamento desses canais utilizando a técnica de Análise de Componentes Independentes (ICA) em conjunto com um limiar de correlação para a remoção de componentes associados a artefatos oculares. Posteriormente, foram avaliadas diferentes abordagens para a extração de características, a mencionar: i) Árvore Diádica de Bandas de Frequências (ADBF); ii) Padrões Espaciais Comuns (CSP); iii) Padrões Espectro-Espaciais Comuns (CSSP); iv) Padrões Esparsos Espectro-Espaciais Comuns (CSSSP); v) CSP com banco de filtros (FBCSP); vi) CSSP com banco de filtros (FBCSSP); e, finalmente, vii) CSSSP com banco de filtros (FBCSSSP). Contudo, como essas técnicas podem produzir espaços de exemplos com alta dimensionalidade, considerou-se, também, a técnica de Seleção de Características baseada em Informação Mútua (MIFS) para escolher os atributos mais relevantes para o conjunto de dados adotado na etapa de classificação. Finalmente, as Máquinas de Vetores de Suporte (SVM) foram utilizadas para a classificação das intenções de usuários. Experimentos permitem concluir que os resultados do CSSSP e FBCSSSP são equiparáveis àqueles produzidos pelo estado da arte, considerando o teste de significância estatística de Wilcoxon bilateral com confiança de 0, 95. Apesar disso o CSSSP tem sido negligenciado pela área devido ao fato de sua parametrização ser considerada complexa, algo que foi automatizado neste trabalho. Essa automatização reduziu custos computacionais envolvidos na adaptação das abordagens para indivíduos específicos. Ademais, conclui-se que os extratores de características FBCSP, CSSP, CSSSP, FBCSSP e FBCSSSP não necessitam da etapa de remoção de artefatos oculares, pois efetuam filtragens por meio de modelos autoregressivos. / Brain-Computer Interfaces (BCI) employ brain imaging to enable human-machine interaction without physical control. BCIs are an alternative so that people suffering from severe or complete loss of motor control, like those with Amyotrophic Lateral Sclerosis (ALS), may have some interaction with the external environment. To transform individual intentions onto machine operations, BCIs rely on a series of steps that include brain signal acquisition and preprocessing, feature extraction, selection and classification. A viable BCI implementation is still an open question due to the great challenges involved in each one of these steps. This gap motivated this work, which presents an evaluation of themain feature extractors used to classify Motor Imagery trials, whose data were obtained through Electroencephalography (EEG) influenced by ocular activity, monitored by Electrooculography (EOG). In this sense, signals acquired by BCI Competition IV-2b, were considered. As first step the preprocessing was performed through Independent Component Analysis (ICA) together with a correlation threshold to identify components associated with ocular artifacts. Afterwards, different feature extraction approaches were evaluated: i) Frequency Subband Dyadic Three; ii) Common Spatial Patterns (CSP); iii) Common Spectral-Spatial Patterns (CSSP); iv) Common Sparse Spectral-Spatial Patterns (CSSSP); v) Filter Bank Common Spatial Patterns (FBCSP); vi) Filter Bank Common Sectral-Spatial Patterns (FBCSSP); and, finally, vii) Filter Bank Sparse Spectral- Spatial Patterns (FBCSSSP). These techniques tend to produce high-dimensional spaces, so a Mutual Information-based Feature Selection was considered to select signal attributes. Finally, Support Vector Machines were trained to tackle the Motor Imagery classification. Experimental results allow to conclude that CSSSP and FBCSSSP are statistically equivalent the state of the art, when two-sided Wilcoxon test with 0, 95 confidence is considered. Nevertheless, CSSSP has been neglected by this area due to its complex parametrization, which is addressed in this work using an automatic approach. This automation reduced computational costs involved in adapting the BCI system to specific individuals. In addition, the FBCSP, CSSP, CSSSP, FBCSSP and FBCSSSP confirm to be robust to artifacts as they implicitly filter the signals through autoregressive models.

Les Accidents Vasculaires Cérébraux (AVC) représentent la première cause de handicap moteur acquis chez l'adulte. La récupération s'appuie en grande partie sur des mécanismes de plasticité cérébrale. La rééducation a pour principal objectif d'optimiser ces mécanismes. Les travaux sur la plasticité cérébrale ont permis de développer de nouvelles techniques de modulation de la plasticité cérébrale à partir de stimulations cérébrales non-invasives (Non-invasive Brain Stimulation, NIBS) : la PAS (Paired Associative Stimulation) est une de ces techniques de stimulation permettant de moduler de façon la plasticité cérébrale. Le PAS consiste à coupler une stimulation électrique périphérique et une stimulation magnétique corticale de type TMS (Transcranial Magnetic Stimulation). Dans des études précédentes, nous avons montré, sur une session de 30 minutes, une facilitation durable (60mn) et spécifique du potentiel évoqué moteur (PEM) du long extenseur radial du carpe (ECRL) chez des patients hémiparétiques. Le protocole CIPASS (Chronic Interventional PAS in Stroke) a pour but d'étudier les effets d'une répétition quotidienne de sessions PAS (pendant 5 jours) et de prouver un effet durable (3 jours) de l'augmentation de la plasticité cérébrale pour le muscle ECRL chez le patient hémiparétique. Vingt-quatre patients ont été inclus dans une étude randomisée, en double-aveugle contre placebo. Aucune différence significative n'a été trouvée entre les groupes PAS et Sham, ni sur le plan électrophysiologique ni sur le plan moteur. Cependant, un sous-groupe de patients semble répondre à l'intervention ; la répétition de sessions PAS semble avoir un impact plus important chez les patients ayant un PEM initial (baseline) bas associé à une importante intensité de stimulation TMS. Cette étude est venue confirmer la variabilité des effets du PAS retrouvée chez le sujet sain et le patient victime d'AVC. Plusieurs études ont montré un effet adjuvant des NIBS lorsqu'elles sont associées à l'apprentissage d'une tâche motrice. Concernant le PAS, quelques études ont montré une facilitation plus importante lorsque celle-ci est associée à une contraction musculaire. L'imagerie motrice (IM) est le fait d'imaginer un mouvement sans le réaliser, elle partage des mécanismes similaires à ceux du mouvement réel. Cette technique a également montré ses effets en tant qu'adjuvant thérapeutique chez le patient hémiparétique, ils restent cependant moins importants que ceux obtenus après un entraînement moteur. L'utilisation de l'IM auprès de patients n'ayant aucune motricité en fait sa singularité et sa force. Le protocole MIPAS a quant à lui pour but d'étudier les effets de l'association du PAS à des exercices d'IM chez le patient hémiparétique et de démontrer l'intérêt thérapeutique de cette association. / Stroke represents the first cause of acquired disability in adults. Recovery relies mainly on brain plasticity mechanisms. The main goal of rehabilitation is to optimize those mechanisms. In recent decades, studies on brain plasticity have led to develop new techniques of noninvasive brain stimulation (NIBS) such as the Paired Associative Stimulation (PAS), which is a non-invasive brain stimulation method that modulates cortical plasticity. PAS consists of a combination of peripheral electrical stimulation and cortical TMS (Transcranial Magnetic Stimulation). In previous studies, we have shown that a session of 30 min targeting the extensor wrist muscles (ECRL) on stroke patient can lead to a motor evoked potential (MEP) specific facilitation of 60 min. The trial CIPASS (Chronic Interventional PAS in Stroke) is a new neuromodulation protocol where a PAS session targeting the extensor wrist muscles (ECRL) is performed on a daily basis during 5 days to hemiparetic patients with a stroke (less than 6 months). Our goal is to demonstrate a lasting increase (3 days) of motor cortical plasticity for ECRL muscle. Twenty-four patients were included in a double-blind, placebo-controlled trial and randomly assigned to one of two groups (PAS or sham). No significant difference was observed between the two groups on either electrophysiological or motor parameters. However, a patient profile appears to respond to the intervention; repetitive PAS sessions seems to have a more important impact on patients with a low initial MEP (baseline) associated to a high TMS intensity. This trial has confirmed the variability of PAS effects already found in healthy subjects and stroke patients. Moreover, many studies have shown the adjuvant effect of NIBS when associated to motor leaning. Regarding PAS, some studies have demonstrated an important facilitation when it was combined with muscle contraction. Motor imagery (MI) is the fact to imagine a movement without realising it; it relies on similar mechanisms to those of a real movement. This technique has also shown its interest as a therapeutic adjunct for stroke patients. Its use for patients with a severe paralysis makes it a very interesting technique. The protocol MIPAS (Motor Imagery and Paired Associative Stimulation) that combine PAS with motor imagery exercises for stroke patients aims to demonstrate the therapeutic interest of such an association for stroke patients.

Les ruminations mentales sont majoritairement exprimées sous forme verbale et il a été proposé de les considérer, par conséquent, comme une forme dysfonctionnelle de parole intérieure (i.e., production mentale de parole). D’autre part, les recherches sur la psychophysiologie de la parole intérieure ont révélé que les processus neuronaux impliqués dans la parole à voix haute et dans la parole intérieure sont similaires. Ces observations sont cohérentes avec l’idée que certaines formes de parole intérieure pourraient être considérées comme une forme de simulation de la parole à voix haute, de la même manière que certaines actions imaginées peuvent être considérées comme le résultat d’une simulation de l’action correspondante (par exemple, marcher et s’imaginer en train de marcher). En d’autres termes, l’hypothèse de la simulation motrice suggère que le système moteur de la parole devrait également être impliqué lors de la production de parole intérieure. L’hypothèse corollaire peut être formulée, selon laquelle la production de parole intérieure (et de ruminations) devrait être perturbée par une perturbation du système moteur de la parole. Nous avons mené une série de cinq études visant à sonder le rôle du système moteur de la parole dans les ruminations. Dans l’ensemble, nos résultats soulignent que, bien que la rumination verbale puisse être considérée comme une forme de parole intérieure, elle ne semble pas recruter spécifiquement le système moteur de la parole. Plus précisément, nous soutenons que la rumination peut être considérée comme une forme de parole intérieure particulièrement condensée, qui s’exprimerait sous la forme d’une représentation phonologique, et dont les traits articulatoires ne seraient pas complètements spécifiés. Nous faisons le lien entre ces résultats et l’hypothèse théorique du cadre “habitude-but” de la rumination dépressive et nous discutons de leurs implications pour les théories de la production de parole intérieure. / Rumination is known to be a predominantly verbal process and has been proposed to be considered as such as a dysfunctional form of inner speech (i.e., the silent production of words in one’s mind). On the other hand, research on the psychophysiology of inner speech revealed that the neural processes involved in overt and covert speech tend to be very similar. This is coherent with the idea that some forms of inner speech could be considered as a kind of simulation of overt speech, in the same way as imagined actions can be considered as the result of a simulation of the corresponding overt action (e.g., walking and imagined walking). In other words, the motor simulation hypothesis suggests that the speech motor system should be involved as well during inner speech production. The corollary hypothesis might be drawn, according to which the production of inner speech (and rumination) should be disrupted by a disruption of the speech motor system. We conducted a series of five studies aiming to probe the role of the speech motor system in rumination. Overall, our results highlight that although verbal rumination may be considered as a form of inner speech, it might not specifically involve the speech motor system. More precisely, we argue that rumination might be considered as a particularly strongly condensed form of inner speech that does not systematically involve fully specified articulatory features. We discuss these findings in relation to the habit-goal framework of depressive rumination and we discuss the implications of these findings for theories of inner speech production.

Shepard and Metzler (1971) argued that mental rotation is analogous to the real world in that people imagine the rotation of an object as if it were being physically rotated. This study tested this assertion by exposing participants to physical shapes that increased in size and weight. Participants interacted with blocks designed after Shepard and Metzler mental rotation size that differed in size and weight then performed subsequent mental rotation. We found no difference in reaction time but found that increased size reduced accuracy. We discuss the implications of this study as they pertain to embodied cognition.

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NeuroGaze is a novel Virtual Reality (VR) interface that integrates electroencephalogram (EEG) and eye tracking technologies to enhance user interaction within virtual environments (VEs). Diverging from traditional VR input devices, NeuroGaze allows users to select objects in a VE through gaze direction and cognitive intent captured via EEG signals. The research assesses the performance of the NeuroGaze system against conventional input devices such as VR controllers and eye gaze combined with hand gestures. The experiment, conducted with 20 participants, evaluates task completion time, accuracy, cognitive load through the NASA-TLX surveys, and user preference through a post-evaluation survey. Results indicate that while NeuroGaze presents a learning curve, evidenced by longer average task durations, it potentially offers a more accurate selection method with lower cognitive load, as suggested by its lower error rate and significant differences in the physical demand and temporal NASA-TLX subscale scores. This study highlights the viability of incorporating biometric inputs for more accessible and less demanding VR interactions. Future work aims to explore a multimodal EEG-Functional near-infrared spectroscopy (fNIRS) input device, further develop machine learning models for EEG signal classification, and extend system capabilities to dynamic object selection, highlighting the progressive direction for the use of Brain-Computer Interfaces (BCI) in virtual environments.

Nos travaux portent sur les mécanismes nerveux qui sous-tendent la perception de notre corps en mouvement. Chacune de nos actions est caractérisée par l'intention motrice qui en est à l'origine et par le feedback multi-modalitaire que son exécution évoque. Dans ce cadre, nous avons formalisé le codage proprioceptif du mouvement et nous avons exploré deux types d'images motrices et leur interaction perceptive à travers l'étude des mouvements imaginés et des illusions kinesthésiques.Sur la base de données neurosensorielles, nous avons contribué à développer une méthode « propriomimétique » inspirée du modèle vectoriel de population permettant de prédire les patterns proprioceptifs afférents évoqués lors de mouvements complexes. Ces patterns modélisés ont ensuite été utilisés pour activer les voies de la proprioception musculaire chez des sujets immobiles grâce à la méthode des vibrations tendineuses. / This thesis deals with the neural mechanisms involved in body movement perception. We contributed to developing a "propriomimetic" method based on neurosensory data and drawn from the population vector model for predicting the afferent proprioceptive patterns evoked during complex movements.The main contribution of this work is that it extends the scope of the method to include the whole set of possible human actions by showing that it can be used to accurately predict the proprioceptive patterns and to generate the kinaesthetic experiences associated with movements involving one or more joints, performed in 2- or 3-dimensional space, regardless of which muscles are involved.Other motor images were intentionally generated by the subjects in subsequent experiments and combined with those imposed by the vibratory stimulation. The results obtained here show that the images of both kinds were completely integrated when evoked simultaneously and that they gave rise to a unique and original perceptual experience, in which their spatio-temporal characteristics were combined. From the theoretical point of view, these findings confirm that proprioceptive afferents play an important role, along with the motor intention itself, in the elaboration of kinaesthetic perception. From the clinical point of view, the possibility of evoking motor images quite "naturally" using the method presented here to activate the peripheral receptors and/or the command centers, and thus the whole sensorimotor loop in the absence of any real movements, opens some promising perspectives for rehabilitation purposes.

Dans la littérature, de nombreuses recherches dans le domaine du contrôle moteur, des sciences du sport ou encore de la rééducation se sont intéressées à l’apprentissage moteur consécutif à un entrainement mental. Cependant, plusieurs mécanismes, qu’ils soient comportementaux ou neurophysiologiques, demeurent encore aujourd’hui peu étudiés. Dans notre première étude, nous avons montré qu’il était impossible de prédire la future amélioration de la performance suite à un entrainement mental aigu, sur une tâche de vitesse-précision, par la simple évaluation subjective des capacités d’imagerie chez une population jeune. Il apparait cependant essentiel de produire des images claires et précises tout au long de l’entrainement pour obtenir de meilleures performances in fine. De plus, par l’analyse fine de la performance, nos résultats ont montré, dans notre seconde étude, les véritables effets des répétitions imaginées sur la mémorisation des habiletés motrices. L’entrainement mental est également apparu efficace pour compenser le déficit de mémoire motrice rapidement observable dans la population âgée. Enfin, une troisième étude a révélé que les répétitions d’un mouvement imaginé pouvaient modifier, de façon transitoire, le codage des réseaux neuronaux impliqués dans le processus de mémoire motrice. / For many years, research in motor control, sport science and rehabilitation focused on the performance improvement following mental practice. However, some mechanisms, behavioral and neurophysiological, remain insufficiently understood. In our first study, we demonstrated the impossibility to predict the future performance improvement following imagined repetitions of a speed accuracy trade-off task, with a subjective evaluation of imagery ability of young healthy individuals. However, it is essential to produce clear and vivid mental simulations throughout the training to obtain a better performance improvement. Besides, by a further analysis of performance, the results of our second study have shown the real impact of mental training on the memorization of motor skills. Motor imagery training also appeared to be effective to compensate the motor memory deficit observed in the elderly. Finally, a third study revealed that the repetitions of imagined movements could modify, temporarily, the coding of neural networks involved in the motor memory process.

Orientadores: Gabriela Castellano, Romis Ribeiro de Faissol Attux / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-09-06T19:40:58Z (GMT). No. of bitstreams: 1 StefanoFilho_CarlosAlberto_M.pdf: 6581881 bytes, checksum: fb23f8cb938a72e69a97b2bf2ff14cab (MD5) Previous issue date: 2016 / Resumo: Interfaces cérebro-computador (BCIs, brain-computer interfaces) são sistemas cuja finalidade é fornecer um canal de comunicação direto entre o cérebro e um dispositivo externo, como um computador, uma prótese ou uma cadeira de rodas. Por não utilizarem as vias fisiológicas convencionais, BCIs podem constituir importantes tecnologias assistivas para pessoas que sofreram algum tipo de lesão e, por isso, tiveram sua interação com o ambiente externo comprometida. Os sinais cerebrais a serem extraídos para utilização nestes sistemas devem ser gerados mediante estratégias específicas. Nesta dissertação, trabalhamos com a estratégia de imaginação motora (MI, motor imagery), e extraímos a resposta cerebral correspondente a partir de dados de eletroencefalografia (EEG). Os objetivos do trabalho foram caracterizar as redes cerebrais funcionais oriundas das tarefas de MI das mãos e explorar a viabilidade de utilizar métricas da teoria de grafos para a classificação dos padrões mentais, gerados por esta estratégia, de usuários de um sistema BCI. Para isto, fez-se a hipótese de que as alterações no espectro de frequências dos sinais de eletroencefalografia devidas à MI das mãos deveria, de alguma forma, se refletir nos grafos construídos para representar as interações cerebrais corticais durante estas tarefas. Em termos de classificação, diferentes conjuntos de pares de eletrodos foram testados, assim como diferentes classificadores (análise de discriminantes lineares ¿ LDA, máquina de vetores de suporte ¿ SVM ¿ linear e polinomial). Os três classificadores testados tiveram desempenho similar na maioria dos casos. A taxa média de classificação para todos os voluntários considerando a melhor combinação de eletrodos e classificador foi de 78%, sendo que alguns voluntários tiveram taxas de acerto individuais de até 92%. Ainda assim, a metodologia empregada até o momento possui várias limitações, sendo a principal como encontrar os pares ótimos de eletrodos, que variam entre voluntários e aquisições; além do problema da realização online da análise / Abstract: Brain-computer interfaces (BCIs) are systems that aim to provide a direct communication channel between the brain and an external device, such as a computer, a prosthesis or a wheelchair. Since BCIs do not use the conventional physiological pathways, they can constitute important assistive technologies for people with lesions that compromised their interaction with the external environment. Brain signals to be extracted for these systems must be generated according to specific strategies. In this dissertation, we worked with the motor imagery (MI) strategy, and we extracted the corresponding cerebral response from electroencephalography (EEG) data. Our goals were to characterize the functional brain networks originating from hands¿ MI and investigate the feasibility of using metrics from graph theory for the classification of mental patterns, generated by this strategy, of BCI users. We hypothesized that frequency alterations in the EEG spectra due to MI should reflect themselves, in some manner, in the graphs representing cortical interactions during these tasks. For data classification, different sets of electrode pairs were tested, as well as different classifiers (linear discriminant analysis ¿ LDA, and both linear and polynomial support vector machines ¿ SVMs). All three classifiers tested performed similarly in most cases. The mean classification rate over subjects, considering the best electrode set and classifier, was 78%, while some subjects achieved individual hit rates of up to 92%. Still, the employed methodology has yet some limitations, being the main one how to find the optimum electrode pairs¿ sets, which vary among subjects and among acquisitions; in addition to the problem of performing an online analysis / Mestrado / Física / Mestre em Física / 165742/2014-3 / 1423625/2014 / CNPQ / CAPES