<p> Animal studies have shown that the tonotopic organization of the auditory cortex is not statically fixed, but can be remodeled by experience. The purpose of this study was to investigate whether or not frequency discrimination training can induce changes in the cortical representation of a selected frequency in humans. Six human subjects were trained for approximately 3 weeks to detect a change in pitch between two tones (40Hz amplitude modulated) using a standard frequency of 2040 Hz. Each subject was tested on his/her discriminative ability before and after training using three different standards (2040Hz, 1840Hz, and 2240Hz). EEG data were recorded both before and after training and changes in transient and steady-state responses were investigated. Behaviourally, every subject improved at the discrimination task using the trained frequency. However, only three subjects demonstrated transfer to both untrained frequencies. In the EEG data, the P2-Nl amplitude increased in five of the six subjects and the Nllatency decreased in all six for the 2040Hz set. These two findings were statistically significant (p<0.05) for the group. There were no statistically significant findings for the side frequencies. The change in the 40 Hz steady-state response was also not significant, increasing in three subjects and decreasing in the other three. These findings indicate that changes are expressed in the secondary auditory cortex. These findings may also be applicable to the treatment of tinnitus. </p> / Thesis / Master of Science (MSc)

This thesis is concerned with the variations which occur in the electroencephalograms, eye-movements, and neck-muscle potentials of three species, the pigeon, rat, and chicken during prolonged recording under normal conditions, under conditions in which the animals were fatigued, and after drugs had been administered. While the recordings from the rat showed the two stages of deep sleep typical of animals, no distinctive ’’sleep” patterns were observed in the records from birds except after Nembutal had been given. The results seem to support the idea that birds do not sleep. / Thesis / Master of Arts (MA)

An approach based on the estimation of the coherence using wavelet analysis is applied to EEG and ERP signals for the detection of pathological patterns related with dyslexia. Coherence can be defined as the correlation of two signals in the frequency domain. The continuous wavelet transform was used for the computation of spectral characteristics since it provides highly overlapping windows which improve the reliability of the coherence estimate. This is achieved by increasing the number of segments over which the spectrum is averaged and thereby half of the amount of data is needed. Statistical analysis of the results revealed significant differences between controls and dyslexics in EEG(F3 gamma band), ERP-P50H(F3 gamma band) and attentive ERP-N100L(F3, C3 and Cz alpha band). It has also been shown that there are significant differences related with handiness and age. It is believed that signal recording from these electrodes may reflect brain areas concerning auditory and memory processing. / -

This work proposes the quantitative analysis of electroencephalographic (EEG) signals, comparing normal subjects to patients in coma state under brain death protocol, by means of a software platform developed in MATLAB. This analysis involved peak frequencies, median frequencies, average, standard deviation and modular index. This last one relates to the bilaterality, i.e. how equidistant electrodes are on the same frequency. Results outlined that patients in coma present lower average median frequency (11.89 Hz), when compared to normal subjects (30.69 Hz). Moreover, with regard the analysis of bilaterality based on modular index, patients in coma also presented lower average standard deviation of the average median frequency (4.72 Hz) than the normal individuals (13 , 67 Hz), e.g., comatose patients presented higher bilaterality. Therefore, results suggests the possibility of applying these quantifications as biomarkers of brain death. / Este trabalho apresenta uma análise quantitativa dos sinais de exames de Eletroencefalografia comparando pacientes normais e pacientes em estado de coma, a partir de análises visuais das amplitudes pelo Neurologista. O estudo comparou dois grupos distintos, sendo um grupo formado por pacientes em estado de coma sob protocolo de morte encefálica e outro composto por pacientes normais. Foi analisado e comparado dados gerados por um software desenvolvido na plataforma MATLAB. Estes dados foram Frequências de Pico, Frequências Medianas, Média, Desvio Padrão e Índice Modular, que se relaciona à bilateralidade, ou seja, o quanto os pontos equidistantes no couro cabeludo representado pela posição dos eletrodos estão em mesma frequência. Pode-se comprovar que pacientes em estado de coma apresentam médias de frequências medianas (11,89 Hz) menores tanto em relação aos canais quanto às épocas, quando comparado aos pacientes normais (30,69 Hz). Além disso, com relação à análise de bilateralidade a partir do cálculo do Índice Modular derivado da média da frequência mediana e da media do Desvio padrão, os pacientes em estado de coma (4.72 Hz) também apresentaram média menor do que os pacientes normais (13,67 Hz), ou seja, os pacientes em coma apresentaram maior bilateralidade. Portanto, pode-se cogitar a aplicação desta ferramenta para auxiliar no diagnóstico de morte encefálica, sendo assim uma ferramenta a mais de auxílio aos profissionais de saúde. / Mestre em Ciências

No description available.

Recentemente, a teoria de grafos aleatórios vem sendo aplicada para modelar interações neurais do cérebro. Enquanto as propriedades dos grafos aleatórios vem sendo vastamente estudadas na literatura, o desenvolvimento de métodos de inferência estatística para essa classe de objetos tem recebido menos atenção. Nesse trabalho propomos um teste de hipóteses não paramétrico para testar se duas amostras de grafos aleatórios provém da mesma distribuição de probabilidade. Nós provamos como computar de maneira eficiente a estatística do teste e estudamos o desempenho do teste em dados simulados de grafos. A principal motivação deste trabalho é a aplicação do teste proposto em dados de eletroencefalograma. / The theory of random graphs has been successfully applied in recent years to model neural interactions in the brain. While the probabilistic properties of random graphs has been extensively studied in the literature, the development of statistical inference methods for this class of objects has received less attention. In this work we propose a non parametric test of hypotheses to decide if two samples of random graphs are originated from the same probability distribution. We show how to compute efficiently the test statistic and we study the performance of the test on simulated data. The main motivation of this work is to apply this test to analyze neural networks constructed from electroencephalographic data.

Recentemente, a teoria de grafos aleatórios vem sendo aplicada para modelar interações neurais do cérebro. Enquanto as propriedades dos grafos aleatórios vem sendo vastamente estudadas na literatura, o desenvolvimento de métodos de inferência estatística para essa classe de objetos tem recebido menos atenção. Nesse trabalho propomos um teste de hipóteses não paramétrico para testar se duas amostras de grafos aleatórios provém da mesma distribuição de probabilidade. Nós provamos como computar de maneira eficiente a estatística do teste e estudamos o desempenho do teste em dados simulados de grafos. A principal motivação deste trabalho é a aplicação do teste proposto em dados de eletroencefalograma. / The theory of random graphs has been successfully applied in recent years to model neural interactions in the brain. While the probabilistic properties of random graphs has been extensively studied in the literature, the development of statistical inference methods for this class of objects has received less attention. In this work we propose a non parametric test of hypotheses to decide if two samples of random graphs are originated from the same probability distribution. We show how to compute efficiently the test statistic and we study the performance of the test on simulated data. The main motivation of this work is to apply this test to analyze neural networks constructed from electroencephalographic data.

No description available.

Previous studies have suggested that mechanisms for neural compensation involve a reorganisation to right hemisphere processing in people with post-traumatic stress disorder (PTSD), and are associated with functional alterations in the capacity for behavioural flexibility. However, research has not established a direct relationship between the complex physiological and psychological processes of the heterogeneous disorder and right hemisphere cortical activity. The present study examined cognitive information processing in people with PTSD, reaction patterns associated with perceived traumatic stressors, and quantitative electroencephalographic (qEEG) indices of hemispheric asymmetry. Individuals with PTSD (N=34) and age and sex-matched normal controls (N=136) completed standardised web-based self-report questionnaires assessing traumatic stressor events and reaction patterns to those events. Neuropsychological indices of verbal, visuospatial, sensori-motor performance, and electrophysiological recordings, were examined for right hemisphere coding. The relationships among traumatic characteristic reaction patterns of numbing and avoidance, cognitive performance, and frontal and posterior EEG alpha asymmetry were also investigated. Structural and functional alterations were shown in those with PTSD, using indices of working memory for the retrieval of verbal and psychomotor information, indicating a reduced speed of processing and alterations to background cortical arousal in left hemisphere frontal regions. The study supported and extended previous findings of verbal working memory abnormality, alterations to left frontal cortical rhythmic oscillations, and low EEG alpha amplitudes in those diagnosed with PTSD. Results indicated a pattern of compensatory mechanisms associated with reduced speed of information processing and right-sided activation patterns in PTSD participants and control participants who experienced strong reactions to perceived traumatic events. Findings support the impact of traumatic events on psychobiological health in high-risk populations, implicating an association with specific patterns of neural and cognitive functioning in characteristic numbing and avoidance behaviours. / Thesis (Ph.D.) -- University of Adelaide, School of Population Health and Clinical Practice, 2008

Elektroencefalografický záznamový systém slouží k vyšetření mozkové aktivity. Na základě tohoto vyšetření lze stanovit diagnózu některých nemocí, například epilepsie. Účelem této práce bylo zpracování signálu z toho systému a vytvoření modelového signálu, který bude s reálným signálem porovnán. Uměle vytvořený signál vychází z Jansenova matematického modelu, který byl dále implementován v prostředí MATLAB a rozšířen ze základního modelu na komplexnější zahrnující nelinearity a model rozhraní elektroda – elektrolyt. Dále bylo provedeno měření signálů na EEG fantomu a následná identifikace parametrů naměřených signálu. V první fázi byly testovány jednoduché signály. Identifikace parametrů těchto signálů sloužila k validaci daného EEG fantomu. V druhé fázi bylo přistoupeno k testování EEG signálů navržených podle matematického Jansenova modelu. Analýza veškerých signálů zahrnuje mimo jiné časově frekvenční analýzu či ověření platnosti principu superpozice.