Electroencephalography is a medical diagnosis technique. It consists in measuring the biopotentials produced by the upper layers of the brain at various standardized places on the skull. Since the biopotentials produced by the upper parts of the brain have an amplitude of about one microvolt, the measurements performed by an EEG are exposed to many risks. Moreover, since the present tendency is measure those signals over periods of several hours, or even several days, human analysis of the recording becomes extremely long and difficult. The use of signal analysis techniques for the help of paroxysm detection with clinical interest within the electroencephalogram becomes therefore almost essential. However the performance of many automatic detection algorithms becomes significantly degraded by the presence of interference: the quality of the recordings is therefore fundamental. This thesis explores the benefits that electronics and signal processing could bring to electroencephalography, aiming at improving the signal quality and semi-automating the data processing. These two aspects are interdependent because the performance of any semi-automation of the data processing depends on the quality of the acquired signal. Special attention is focused on the interaction between these two goals and attaining the optimal hardware/software pair. This thesis offers an overview of the medical electroencephalographic acquisition chain and also of its possible improvements. The conclusions of this work may be extended to some other cases of biological signal amplification such as the electrocardiogram (ECG) and the electromyogram (EMG). Moreover, such a generalization would be easier, because their signals have a wider amplitude and are therefore more resistant toward interference.

The goal of this study was to evaluate whether Electroencephalography (EEG) estimates of attention and cognitive workload captured as students solved math problems could be used to predict success or failure at solving the problems. Students solved a series of SAT math problems while wearing an EEG headset that generated estimates of sustained attention and cognitive workload each second. Students also reported on their level of frustration and the perceived difficulty of each problem. Results from a Support Vector Machine (SVM) training indicated that problem outcomes could be correctly predicted from the combination of attention and workload signals at rates better than chance. The EEG data was also correlated with students' self-report of problem difficulty. Findings suggest that relatively non-intrusive EEG technologies could be used to improve the efficacy of tutoring systems.

In the present study, we conducted an event-related potentials (ERP) study to examine episodic and semantic memory. We focused on two well-known patterns: the semantic N400 and the old/new fN400. Some researchers have argued that they reflect the same neuropsychological response (Voss & Federmeier, 2011). Others have suggested that they have distinct spatial-temporal signatures and reflect different psychological processes (Bridger, Bader, Kriukova, Unger, & Mecklinger, 2012). In the present study, we analyzed data using the basic N400/fN400 paradigm. We expect to find similar results to Bridger et al. (2012) in that the N400 and fN400 to be reliably different in topography and function.

M.A. (Psychology) / Attention deficit/hyperactivity disorder (ADHD), characterised by problems relating to attention, impulsive behaviour and hyperactivity, has become widely accepted to be a neurodevelopmental disorder that persists into adulthood for a large proportion of the ADHD population. ADHD symptoms are reported to undergo developmental transformation from childhood to adulthood, resulting in a significantly different clinical picture of adult ADHD. This signals a need to move away from reliance on childhood models of the disorder. Current conceptions of both childhood and adult ADHD do not discuss the occurrence of hyperfocus (or flow), a symptom which seems to connote an extreme form of sustained attention and which has been noted in clinical work. The possibility that hyperfocus could occur in ADHD is unexpected and poses a challenge to current formulations of inattention in ADHD. Media settings have been identified as providing the conditions needed for one to enter the hyperfocus state. This study set out to explore the possible symptom of hyperfocus in ADHD and to attempt to identify the neural correlates thereof, using electroencephalograph (EEG). A sample of 10 participants (5 ADHD, 5 non-ADHD) was recruited using the Adult ADHD Self Report Scale V-1.1 (ASRS V-1.1) Screener and a biographical questionnaire. A quasi-experimental research design was employed, whereby EEG recordings of frontal, frontal midline and parietal regions were taken for each participant during resting states (Eyes Closed and Eyes Open) and whilst playing a first person shooter game. Post-test survey questionnaires were also administered to examine the participants’ time perception during game play. Between-group and within-group differences in absolute and relative power scores were examined, using non-parametric statistical methods (Mann-Whitney-U test and Wilcoxon Signed Rank Test) to analyse the data. Possible markers for hyperfocus were identified, namely significantly lower alpha and beta levels in the ADHD group, as well as a decrease in slow-wave activity over time, as well as post-test survey data that indicated a greater degree of distorted time perception in the ADHD group during game play. Significant between- and within-group differences found in the parietal region highlight the need for further research into the role of the parietal lobe in attention functions and in ADHD. Further, significant changes in cortical activity in the progression from Eyes Closed to Eyes Open in both groups warrant further investigation.

Thesis advisor: Robert Signorile / It has long been known that as neurons fire within the brain they produce measurable electrical activity. Electroencephalography (EEG) is the measurement and recording of these electrical signals using sensors arrayed across the scalp. Though there is copious research in using EEG technology in the fields of neuroscience and cognitive psychology, it is only recently that the possibility of utilizing EEG measurements as inputs in the control of computers has emerged. The idea of Brain-Computer Interfaces (BCIs) which allow the control of devices using brain signals evolved from the realm of science fiction to simple devices that currently exist. BCIs naturally present themselves to many extremely useful applications including prosthetic devices, restoring or aiding in communication and hearing, military applications, video gaming and virtual reality, and robotic control, and have the possibility of significantly improving the quality of life of many disabled individuals. However, current BCIs suffer from many problems including inaccuracies, delays between thought, detection, and action, exorbitant costs, and invasive surgeries. The purpose of this research is to examine the Emotiv EPOC© System as a cost-effective gateway to non-invasive portable EEG measurements and utilize it to build a thought-based BCI to control the Parallax Scribbler® robot. This research furthers the analysis of the current pros and cons of EEG technology as it pertains to BCIs and offers a glimpse of the future potential capabilities of BCI systems. / Thesis (BA) — Boston College, 2010. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Computer Science Honors Program. / Discipline: Computer Science.

Orientador: José Luiz Rybarczyk Filho / Resumo: O objetivo deste trabalho foi produzir um dispositivo coletor de biopotenciais por EEG de baixo custo. Como características o protótipo apresentou alta imunidade a ruído, faixa de frequência de trabalho e tensão, seguindo as especificações necessárias para a coleta dos sinais EEG. O circuito eletrônico e o roteamento foram desenvolvidos no software Eagle R e então a placa foi construída pelo método fotográfico com posterior corrosão por percloreto de ferro e solda-gem manual dos componentes. O circuito montado é composto por: amplificadores diferenciais configurados com um ganho na ordem de 169,66, filtros de frequência intercalados e um mi-crocontrolador ESP32@ que munido de conversor analógico-digital foi configurado para uma amostragem de 356 amostras por segundo e resolução de 12 bits, o que possibilitou leituras com passos de 2,198x10-4 V. Os filtros foram projetados para atuar na redução de ruidos contidos na faixa de 50 a 60Hz. O funcionamento do dispositivo móvel microcontrolado teve seu funciona-mento comprovado através do método de detecção de ondas alfa, ondas estas que alteram suas intensidade quando nos encontramos concentrados com os olhos abertos ou fechados. A captura de ondas alfa compreendidas entre 8 a 13 Hz foi validada nas seguintes condições: 1 minuto com os olhos fechados (alta atividade) e 1 minuto com os olhos abertos (baixa atividade). O dispositivo produzido mostrou-se promissor como uma alternativa de baixo custo e com simpli-cidade de produção, qu... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The objective of this work was to produce a low cost EEG biopotential collecting device. As characteristics the prototype presented high immunity to noise, working frequency range and voltage, following the specifications required for the collection of EEG signals. Electronic circuit and routing were developed in the Eagle R software and the plate was then constructed by the photographic method with subsequent iron perchloride corrosion and manual soldering of the components. The assembled circuit consists of: differential amplifiers configured with a gain of the order of 169.66, frequency filters interleaved and an ESP32 @ microcontroller which has an analog-to-digital converter configured for a sampling of 356 samples per second and resolution of 12 bits, which allowed for readings with steps of 2.198x10-4 V. The filters were designed to act in the reduction of noise contained in the range of 50 to 60Hz. The operation of the microcontrolled mobile device has proven its function through the method of detecting alpha waves, waves that change their intensity when we are concentrated with the eyes open or closed. The capture of alpha waves between 8 and 13 Hz was validated under the following conditions: 1 minute with eyes closed (high activity) and 1 minute with eyes open (low activity). The device produced was promising as a low-cost, simplified production alternative when compared to models available on the market for EEG signal capture. / Mestre

A inclusão da eletroencefalografia nos protocolos de pesquisa diagnóstica para DA é plenamente justificada por sua larga disponibilidade, baixo custo, alta sensibilidade, o que possibilita a realização de exames seriados e o acompanhamento da evolução do estudo neurológico. Objetivo: Determinar um índice de corte, para utilizaçào na prática clínica, no auxilio diagnóstico da doença de Alzheimer. Metodologia: Avaliamos dois grupos de indivíduos compostos por 57 voluntários normais e idade superior a 50 anos comparados a 50 indivíduos com DA provável. Realizamos registros de EEG em vigília, olhos fechados e repouso por 30 minutos e computamos as potências espectrais das bandas de frequência alfa e teta, para todos os eletrodos, e calculamos a razão alfa/teta. Realizamos a regressão logística das variáveis razão alfa/teta da potência média do eletrodo C3 e do eletrodo O1e calculamos uma fórmula para o auxílio no diagnóstico da DA com um acerto cuja, sensibilidade para DA de 76, 4 % e especificidadede 84,6 % e a área sob a curva ROC 0.92. Conclusão: A regressão logística da razão alfa/teta do Espectro da potência média do EEG é um bom marcador para discriminar pacientes com doença de Alzheimer de controles normais / The inclusion of electroencephalography in diagnostic research protocols for AD is fully justified given EEG\'s wide availability, low cost and high sensitivity, allowing serial exams and neurological evolution follow-ups. Objective: To determine a screening index for use in routine clinical practice to aid the diagnosis of Alzheimer\'s disease. Methodology: Two groups of individuals older than 50 years, comprising a control group of 57 normal volunteers and a study group of 50 patients with probable AD, were compared. EEG recordings were performed of subjects in a wake state with eyes closed at rest for 30 mins. Spectral potentials of the alpha and theta bands were computed for all electrodes and the alpha/theta ratio calculated. Logistic regression of the variables alpha/theta of the mean potential of the C3 and O1 electrodes was carried out. A formula was calculated to aid the diagnosis of AD yielding 76.4 % sensitivity and 84.6 specificity for AD with an area under the ROC curve of 0.92. Conclusion: Logistic regression of the alpha/theta of the Spectrum of the mean potential of EEG represents a good marker for discriminating between AD patients and normal controls

A Neuroimagem Funcional evoluiu muito nos últimos anos com o aparecimento de técnicas como Positron Emission Tomography ou PET (Tomógrafo por Emissão de Pósitrons) e Functional Magnetic Ressonance Image ou fMRI (Imagem de RessonÂncia Magnética Funcional) [Belliveau et al., 1991]. Elas permitem a observação de atividade no cérebro com uma resolução de alguns milímetros, e devido a natureza do sinal medido, com uma resolução temporal da ordem de 5 segundos [Kim et al., 1997]. Magnetoencefalografia e Eletroencefalografia (M/EEG), por outro lado, possuem uma resoluçao temporal da ordem de milissegundos, já que o sinal é produzido pela movimentação do íons através das membranas celulares [Nunez and Srinivasan, 2006]. Porém a sua resoluçeo espacial é muito baixa jé que tipicamente são problemas mal postos, com muito mais variáveis do que dados. Um equipamento de M/EEG de alta resolução possui da ordem de O(200) canais, que permitem medidas do campo magnético (para o MEG) ou do potencial elétrico (para o EEG) em O(200) posições em torno da cabeça. Para uma escala com resolução de ordem l existem (L /l )3 variáveis, onde L = aprox. 15cm. Neste trabalho procuramos estudar métodos para aumentar a resolução espacial das técnicas de EEG, pois o mapeamento funcional do cérebro humano esta intimamente relacionado à localização da atividade no espaço bem como no tempo [Friston, 2009] (muitas relativo ao momento de um estímulo externo). Todo o trabalho de localização de fontes para EEG pode ser facilmente estendido para MEG. Métodos Bayesianos são o cenário natural para lidar com problemas mal postos [Wipf and Nagarajan, 2009]. Existem, essencialmente, duas direções nas quais os algoritmos Bayesianos podem ser melhoradas, através da construção de uma melhor verossimilhança ou uma distribuição a Priori. Embora reconheçamos que avanços importantes podem ser feitos no direção anterior, aqui nos concentramos na segunda. Neste trabalho nós introduzimos um método multiescala para construir uma melhor distribuição a Priori. Uma idéia similar foi estudada dentro do contexto mais simples de fMRI [Amaral et al., 2004]. Muitos novos problemas aparecem ao lidar com o caráter vetorial do EEG. O mais importante, é a construção de um conjunto de superfícies renormalizadas que aproximam a região cortical onde a fonte de atividade esta localizada e o problema relacionado de de nir as variáveis relevantes para representar o cérebro em uma escala com menor resolução. A validação do novo algoritmo é sempre um problema essencial. Nós apresentamos resultados que sugerem, em dados simulados, que nosso método pode ser uma alternativa válida para os atuais algoritmos, julgando ambos pela taxa de erros na localização de fontes bem como pelo tempo que eles levam para convergir. / Functional Neuroimaging has evolved in the last few decades with the introduction of techniques such as Positron Emission Tomography or PET and Functional Magnetic Ressonance Image or fMRI [Belliveau et al., 1991]. These allow observing brain activity with a resolution of a few millimeters and, due to the nature of the signal, a time resolution of the order of 5 seconds [Kim et al., 1997]. M/EEG, on the other hand, have a millisecond time resolution, since the signal is produced by the transport of ions through cell membranes [Nunez and Srinivasan, 2006]. However their space resolution is much lower since these are typically ill posed problems with many more unknowns than data points. A high resolution M/EEG has of the order of O(200) data channels, which allow measuring the magnetic or electric field at O(200) positions around the head. For a resolution scale of order l there are O(L l )3 variables, where L = 15cm. In this work we aim at studying methods to increase the spatial resolution of EEG techniques, since functional mapping of the human brain is intimately related to the localization of the activity in space as well as in time [Friston, 2009] (often relative to the time of external stimuli). Any advance in the inverse problem of source localization for EEG can rather easily be extended to deal with MEG. Bayesian methods are the natural setting to deal with ill posed problems [Wipf and Nagarajan, 2009]. There are essentially two directions in which Bayesian algorithms can be improved, by building a better likelihood or a prior distribution. While we recognize that important advances can be done in the former direction we here concentrate in the latter. In this work we introduce a multiscale method to build an improved prior distribution. A similar idea has been studied within an easier context of fMRI [Amaral et al., 2004]. Several new problems appear in dealing with the vectorial character of EEG. The most important, is the construction of a set of renormalized lattices that approximate the cortex region where the source activity is located and the related problem of de ning the relevant variables in coarser scale representation of the cortex. Validation of a new algorithm is always an essential problem. We present results which suggest on simulated data, that our method might be a valid alternative to current algorithms, judged both by the rate of errors in source localization as well as by the time it takes to converge.

Com intuito de avaliar o processo cognitivo cerebral e o desempenho de médicos veterinários especializados em radiologia, este estudo proporcionou, através de um sistema computacional, tarefas de questões radiológicas. Os 29 voluntários foram divididos por gênero: homens (n=13) e mulheres (n=16); e por tempo de especialidade: iniciantes (n=13), experientes (n=8) e seniores (n=8). Quatorze casos foram selecionados com diferentes níveis de dificuldade a partir de imagens radiográficas de cães e gatos e foram escaneadas e colocadas em um programa chamado Enscer®, adaptado para a realização deste estudo. Os casos eram divididos em três partes, nomeadas, história clínica, imagem radiográfica e decisão diagnóstica. Durante as etapas, foram realizados eletroencefalogramas dos voluntários, que resultaram em mapeamentos cerebrais. Além disso, foi feita avaliação das respostas corretas, incorretas e dos tempos utilizados para as tarefas. Através das avaliações estatísticas dos resultados foi possível concluir que radiologistas veterinários com maior tempo de especialidade foram estatisticamente mais rápidos nas tarefas e tiveram melhor desempenho diagnóstico; voluntários com maior tempo de especialidade ativaram áreas cerebrais diferentes dos menos experientes; o desempenho diagnóstico foi quantitativamente igual em voluntários de ambos os gêneros e o mapeamento cerebral do grupo masculino foi diferente do grupo feminino, mesmo com desempenho igual nas atividades / With intention to evaluate the cerebral cognitive process and the performance of medical veterinarians specialized in radiology, this study provided, through a computerized system, tasks of radiological questions. The 29 volunteers were divided by gender: man (n=13) and woman (n=16); and by time of experience: beginners (n=13), experienced (n=8) and seniors (n=8). Fourteen cases were selected with different levels of difficulty from radiographic images of dogs and cats and had been scanned and processed by a software called Enscer®, adapted for the accomplishment of this study. The cases were divided into three parts, namely, clinical history, radiographic image and diagnostic decision. During the stages the electroencephalography was carried through, which resulted in the cerebral mapping. Moreover, evaluation of the correct and incorrect answers and of the times used for the tasks was made. Through the statistical evaluations of the results it was possible to conclude that radiologists veterinarians with more time of experience had been statistically faster in the tasks and had had better diagnostic performance; volunteers with more time of experience had activated different cerebral areas than volunteer with less experience; the diagnostic performance was quantitatively equal in volunteers of both genders and the cerebral mapping of the masculine group was different of the feminine group, even with equal performance in the activities

The human brain consists of billions of neurons and these neurons pool together in groups at different scales. On one hand, these neural entities tend to behave as single units and on the other hand show collective macroscopic patterns of activity. The neural units communicate with each other and process information over time. This communication is through small electrical impulses which at the macroscopic scale are measurable as brain waves. The electric field that is produced collectively by macroscopic groups of neurons within the brain can be measured on the surface of the skull via a brain imaging modality called Electroencephalography (EEG). The brain as a neural system has variant connection topology, in which an area might not only be connected to its adjacent neighbors homogeneously but also distant areas can directly transfer brain activity [16]. Timing of these brain activity communications between different neural units bring up overall emerging spatiotemporal patterns. The dynamics of these patterns and formation of neural activities in cortical surface is influenced by the presence of long-range connections between heterogeneous neural units. Brain activity at large-scale is thought to be involved in the information processing and the implementation of cognitive functions of the brain. This research aims to determine how the spatiotemporal pattern formation phenomena in the brain depend on its connection topology. This connection topology consists of homogeneous connections in local cortical areas alongside the couplings between distant functional units as heterogeneous connections. Homogeneous connectivity or synaptic weight distribution representing the large-scale anatomy of cortex is assumed to depend on the Euclidean distance between interacting neural units. Altering characteristics of inhomogeneous pathways as control parameters guide the brain pattern formation through phase transitions at critical points. In this research, linear stability analysis is applied to a macroscopic neural field in a one-dimensional circular and a twodimensional spherical model of the brain in order to find destabilization mechanism and subsequently emerging patterns. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection