Understanding the effects of anesthetic agents on the EEG through neural field theory

Anesthetic and analgesic agents act through a diverse range of pharmacological mechanisms. Existing empirical data clearly shows that such "microscopic" pharmacological diversity is reflected in their "macroscopic" effects on the human electroencephalogram (EEG). Based on a detailed mesoscopic neural field model we theoretically posit that anesthetic induced EEG activity is due to selective parametric changes in synaptic efficacy and dynamics. Specifically, on the basis of physiologically constrained modeling, it is speculated that the selective modification of inhibitory or excitatory synaptic activity may differentially effect the EEG spectrum. Such results emphasize the importance of neural field theories of brain electrical activity for elucidating the principles whereby pharmacological agents effect the EEG. Such insights will contribute to improved methods for monitoring depth of anesthesia using the EEG.

Proposal of a floating mechanism based on magnetic levitation method toward EEG-driven robotic system

We discussed a floating mechanism based on quasi-magnetic levitation method that can be attached at the endpoint of a robot arm in order to construct a novel redundant robot arm for producing compliant motions. The floating mechanism can be composed of magnets and a constraint mechanism such that the repelling force of the magnets floats the endpoint part of the mechanism stable for the guided motions. The analytical and experimental results show that the proposed floating mechanism can produce stable floating motions with small inertia and viscosity. The results also show that the proposed mechanism can detect small force applied to the endpoint part because the friction force of the mechanism is very small.

Novel single trial movement classification based on temporal dynamics of EEG

Various complex oscillatory processes are involved in the generation of the motor command. The temporal dynamics of these processes were studied for movement detection from single trial electroencephalogram (EEG). Autocorrelation analysis was performed on the EEG signals to find robust markers of movement detection. The evolution of the autocorrelation function was characterised via the relaxation time of the autocorrelation by exponential curve fitting. It was observed that the decay constant of the exponential curve increased during movement, indicating that the autocorrelation function decays slowly during motor execution. Significant differences were observed between movement and no moment tasks. Additionally, a linear discriminant analysis (LDA) classifier was used to identify movement trials with a peak accuracy of 74%.

Neural correlates of emotional responses to music: an EEG study

This paper presents an EEG study into the neural correlates of music-induced emotions. We presented participants with a large dataset containing musical pieces in different styles, and asked them to report on their induced emotional responses. We found neural correlates of music-induced emotion in a number of frequencies over the pre-frontal cortex. Additionally, we found a set of patterns of functional connectivity, defined by inter-channel coherence measures,to be significantly different between groups of music-induced emotional responses.

Motor imagery-induced EEG patterns in individuals with spinal cord injury and their impact on brain–computer interface accuracy

Objective. Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no ‘cure’ at the present time. Brain–computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI. Approach. Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups. Main results. It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%). Significance. The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals

Motor imagery induced EEG patterns in spinal cord injury patients and their impact on Brain-Computer Interface accuracy

OBJECTIVE: Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no 'cure' at the present time. Brain-computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI. APPROACH: Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups. MAIN RESULTS: It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%). SIGNIFICANCE: The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals.

Low-cost HMD and EEG: using visual stimulation by the Oculus Rift® to detect stronger ERDs induced by motion imagery

Virtual Reality (VR) can provide visual stimuli for EEG studies that can be altered in real time and can produce effects that are difficult or impossible to reproduce in a non-virtual experimental platform. As part of this experiment the Oculus Rift, a commercial-grade, low-cost, Head Mounted Display (HMD) was assessed as a visual stimuli platform for experiments recording EEG. Following, the device was used to investigate the effect of congruent visual stimuli on Event Related Desynchronisation (ERD) due to motion imagery.

Feasibility study on EEG driven robotic system to realize efficient stroke rehabilitation

We aim to develop an efficient robotic system for stroke rehabilitation, in which a robotic arm moves the hemiplegic upper limb when the patient tries to move it. In order to achieve this goal we have considered a method to detect the patient's intended motion using EEG (Electroencephalogram), and have designed a rehabilitation robot based on a Redundant Drive Method. In this paper, we propose an EEG driven rehabilitation robot system and present initial results evaluating the feasibility of the proposed system.

Multiple Pathways Analysis of Brain Functional Networks from EEG Signals: An Application to Real Data

In the present study, we propose a theoretical graph procedure to investigate multiple pathways in brain functional networks. By taking into account all the possible paths consisting of h links between the nodes pairs of the network, we measured the global network redundancy R (h) as the number of parallel paths and the global network permeability P (h) as the probability to get connected. We used this procedure to investigate the structural and dynamical changes in the cortical networks estimated from a dataset of high-resolution EEG signals in a group of spinal cord injured (SCI) patients during the attempt of foot movement. In the light of a statistical contrast with a healthy population, the permeability index P (h) of the SCI networks increased significantly (P < 0.01) in the Theta frequency band (3-6 Hz) for distances h ranging from 2 to 4. On the contrary, no significant differences were found between the two populations for the redundancy index R (h) . The most significant changes in the brain functional network of SCI patients occurred mainly in the lower spectral contents. These changes were related to an improved propagation of communication between the closest cortical areas rather than to a different level of redundancy. This evidence strengthens the hypothesis of the need for a higher functional interaction among the closest ROIs as a mechanism to compensate the lack of feedback from the peripheral nerves to the sensomotor areas.

Implementação de classificador de tarefas mentais baseado em EEG

BARBOSA, André F. ; SOUZA, Bryan C. ; PEREIRA JUNIOR, Antônio ; MEDEIROS, Adelardo A. D.de, . Implementação de Classificador de Tarefas Mentais Baseado em EEG. In: CONGRESSO BRASILEIRO DE REDES NEURAIS, 9., 2009, Ouro Preto, MG. Anais... Ouro Preto, MG, 2009

Um sistema inteligente de classificação de sinais de EEG para Interface Cérebro-Computador

The Brain-Computer Interfaces (BCI) have as main purpose to establish a communication path with the central nervous system (CNS) independently from the standard pathway (nervous, muscles), aiming to control a device. The main objective of the current research is to develop an off-line BCI that separates the different EEG patterns resulting from strictly mental tasks performed by an experimental subject, comparing the effectiveness of different signal-preprocessing approaches. We also tested different classification approaches: all versus all, one versus one and a hierarchic classification approach. No preprocessing techniques were found able to improve the system performance. Furthermore, the hierarchic approach proved to be capable to produce results above the expected by literature

Realidade virtual na atividade cerebral: um estudo comparativo entre estados emocionais de adultos jovens e idosos

The association of Virtual Reality (VR) to clinical practice has become common in the recent years, showing to be an additional tool on health care, especially for elderly. Its use has been related to higher therapeutic adhesion levels and well being sensation. Such emotional based aspects are often observed by subjective tools of relative validity. This study analyzed the immediate effects of varied VR contexts balance training over emotional behavior, which was observed under peaks of maximum expression of EEG waves. Methodology: 40 individuals, divided in two groups, both gender, 20 young and 20 elderly, were submitted to a 60 minutes intervention, including balance training under VR. The first 25 minutes referred to initial evaluation, general orientation and cognitive assessment by the use of Mini Mental. The next ten minutes were designated to the avatar creation and tutorial video presentation. Through the following 20 minutes, the individuals from both groups were exposed to the exact same sequence of games under virtual contexts, while submitted to electroencephalography by Emotiv EPOC® focusing Adhesion, Frustration and Meditation states. The virtual interface was provided by the Nintendo® game, Wii Fit Plus, with the scenarios Balance Bubble (1), Penguin (2), Soccer (3), Tight Rope (4) and Table Tilt (5). Finally, a questionnaire of personal impressions was applied on the 5 minutes left. Results: data collected showed 64,7% of individuals from both groups presented higher concentration of adhesion peaks on Balance Bubble game. Both groups also presented similar behavior regarding meditation state, with marks close to 40%, each, on the same game, Table Tilt. There was divergence related to the frustration state, being the maximum concentration for the young group on the Soccer game (29,3%), whilst the elderly group referred highest marks to Tight Rope game (35,2%). Conclusion: Findings suggest virtual contexts can be favorable to adhesion and meditation emotional patterns induction, regardless age and for both sexes, whilst frustration seems to be more related to cognitive motor affordance, likely to be influenced by age. This information is relevant and contributes to the orientation for the best choice of games applied in clinical practice, as for other studies regarding this topic

Correlato eletroencefalográfico do estado vibracional

O estado vibracional (EV) é descrito como uma sensação de vibração intensa por todo o corpo, em que o sujeito se mantém num estado de relaxamento psicofisiológico que pode ser gerado de forma espontânea ou autoinduzida. Pessoas que aplicam esta técnica relatam alterações do estado mental e emocional, tais como: relaxamento, disposição, limpidez de pensamento, equilíbrio emocional, melhoria do raciocínio, bemestar, entre outros. Estas são, entretanto observações subjetivas, sendo a mensuração deste fenômeno uma lacuna e um desafio para a ciência. O objetivo desta pesquisa é explorar sistematicamente o estado vibracional no âmbito da neurociência. Desta forma, medidas eletroencefalográficas (EEG) foram utilizadas para observar se a sensação subjetiva de EV é acompanhada por mudanças na atividade elétrica cerebral. Além disso, para avaliar se o EV provoca algum efeito positivo em funções cognitivas como atenção e memória, foi utilizado um teste de reconhecimento de palavras antes e depois da aplicação da técnica de EV. Foram também aplicados questionários de dados gerais socioeconômicos e de saúde, do perfil de estados de humor, de qualidade do sono, além de inventários psicológicos. O foco inicial do trabalho foi a análise estatística dos dados de EEG, ficando as outras análises para uma etapa posterior. Dois grupos de voluntários foram analisados, o primeiro formado por 14 sujeitos que praticam a técnica de EV há pelo menos 10 anos (Grupo Experiente - GEXP), e o segundo formado por 11 sujeitos que nunca haviam realizado a técnica (Grupo Controle - GCONT). O GCONT obteve instruções sobre a técnica de EV antes dos experimentos. Foram realizadas análises estatísticas dos registros eletroencefalográficos, para comparar os grupos, em quatro condições: Basal, Relaxamento, Não-EV (período em que o sujeito está engajado na tarefa, mas ainda não percebe o EV) e EV (período em que o sujeito percebe o EV). Uma vez que os sujeitos do GCONT relataram não ter conseguido atingir a condição de EV propriamente, a comparação entre grupos foi feita apenas nas três condições, Basal, Relaxamento e Não-EV. Para isso, foi usado o teste de Mann-Whitney U com um limiar estatístico de p<0,05. De forma geral, o GEXP apresentou maior potência na banda de frequência alfa 2 (9,5-11,0 Hz) em todas as condições. Durante o período Não-EV, o GEXP também apresentou uma maior potência na banda de frequência alfa 3 (11,5-13,0 Hz) na região temporal esquerda, e gama 1 (30,5-55,0 Hz) e gama 2 (65,0-80,0 Hz) em regiões central, parietal e temporal esquerda, mas menor potência na banda de frequência teta 1 (3,5 - 5,0 Hz), em regiões centro-parietais. Para a análise estatística intragrupo, entre as condições, utilizou-se o teste estatístico Wilcoxon pareado. Observaram-se diferenças significativas (p<0,005), principalmente em regiões centrais, em teta 1 (3,5-5,0 Hz), sendo maior no Relaxamento, quando comparado com as condições Basal e Não-EV, no GCONT, e com o Não-EV e EV, no GEXP. No GEXP, a potência de gama 1 (30,5-55,0 Hz) e gama 2 (65,0-80,0 Hz) foi difusamente maior durante o EV, se comparado às outras três condições. Para o GCONT, apenas a condição Basal apresentou maior potência de gama 1 (30,5-55,0 Hz) e gama 2 (65,0- 80,0 Hz), se comparado com o Relaxamento. O aumento de teta 1 no Relaxamento, principalmente no GCONT, pode estar associado a uma maior sonolência deste grupo durante esta condição. Já o aumento de alfa 2 durante o Não-EV e o EV, pode estar associado com processos de atenção e cognição (DOLPPERMAYR et al., 2002; FELL et al., 2010; KLIMESCH et al., 1999; RAY E COLE, 1985). Por outro lado, o aumento da potência de gama em sujeitos experientes na técnica de EV encontrado aqui e em trabalhos anteriores, em meditadores experientes (FELL et al., 2010; LEHMANN et al., 2001; LUTZ et al., 2004), poderia estar associado a alterações nos processos mentais e cognitivos destes praticantes, tais como atenção, memória operacional, aprendizagem e percepção consciente embora, análises adicionais devam ser realizadas para excluir a possibilidade de interferência de artefatos musculares nos dados de EEG. Estes resultados suscitam a hipótese de que no engajamento da tarefa do EV e durante o EV, os sujeitos do GEXP conseguem manter-se em um estado de alerta, porém com maior nível de relaxamento e concentração. Uma inspeção mais detalhada dos dados, além de outros experimentos com diferentes protocolos, um maior número de sujeitos e pesquisas longitudinais são necessários para que testar esta hipótese

Monitorização vídeo-EEG prolongada em crises não epilépticas: semiologia clínica

O objetivo deste estudo foi mostrar a contribuição da monitorização vídeo-EEG prolongada (MVEP) no diagnóstico de crises não epilépticas (CNE) e estimar sua prevalência em um centro terciário de atendimento à Epilepsia (EP). Foram observados 47 pacientes com diagnóstico de CNE com crises espontâneas ou provocadas. Foram instituídos protocolos direcionados à história clínica e à semiologia das crises. A análise estatística baseou-se no teste de Fisher e na análise de cluster. Os resultados evidenciaram prevalência de 10% de CNE. Houve predominância do sexo feminino (63,8%); em 57% dos pacientes as crises foram espontâneas. A média de idade foi 32,5 ± 11anos. O sinal semiológico mais freqüente foi o sono aparente (87,2%). em 9% dos pacientes observaram-se tanto EP como CNE. Três agrupamentos resultaram da análise de cluster: CNE hipermotora das extremidades com alteração de tônus; CNE com automatismos e CNE axial com movimentos oculares. em conclusão, o estudo da semiologia clínica das CNE durante a MVEP contribui para o diagnóstico desta entidade nosológica e para o diagnóstico diferencial com EP; o teste provocativo auxilia na obtenção das crises.