Please use this identifier to cite or link to this item: https://app.uff.br/riuff/handle/1/18775
Title: Topografia da coerência espectral dos potenciais eletroencencefalográficos relacionados a eventos musculares
Keywords: Epilepsia;  Processamento de sinais;  Computação gráfica;  Interface (Computador);  Coerência cortical;  Mioclonia;  Mapeamento cerebral;  Signal processing;  Computer graphics;  Interface (Computer);  cortical coherence;  Myoclonus;  Brain Map
Issue Date: 12-Nov-2007
Abstract: Myoclonus consists of a sudden brief jerk caused by a muscular and involuntary contraction with a very brief duration. It can be restricted to a group of muscular fibers or involving the whole muscle or it can also affect a group of muscles. Myoclonus can be a symptom of a serie of neurological diseases. Probably, the most common causes are not from epileptic sources. Although, in sleep-related epilepsy patients, the discharges originated from the motor cortex during the phases of the sleep, can be linked to the generalization of the convulsive crises. However, the location of the original zone, the classification of the crisis and the consequent therapeutic strategy are complex and imprecise tasks. It is based on these discharges that medical diagnosticians try to discover where the epileptic focus is, if there is a functional or structural lesion and the connection between them with the disease focus. Corticomuscular coherence measure by using electroencephalography (EEG) and electromyography (EMG) are helpful to understand the cortical control movement. The here methodology presented aims to answer if the observed muscular events came from the cerebral cortex. In affirmative cases, it seeks identify the corticomuscular discharges causers of such shocks. The final purpose is to establish a topographical mapping that allows experts to visualize the sources of neuronal discharges which are responsible for such events. The graphic representation of this mapping uses a twodimensional head model where the muscular events are correlated to a cerebral cortex map concerned with the involved motion regions. The present research was divided into 3 studies groups. The first group performed a set of 12 EEG and EMG computational signals simulated in 440 different terms, without human beings participation. In the second group the EEG recordings were made from over the motor cortex of one adult subjects, healthy who performed repeated periods of maintained fingers and wrist extension and flexion. The group 3 consisted of one patient male, with age of 8 month, presented myoclonic seizures or spasms, it was based on VideoEEG recordings. Electrical activity was recorded bipolarly from pairs of adjacent cortical electrodes together with EMG from upper and lower limb muscles. The signals were then analyzed in the frequency domain to reveal patterns of significant coherence. Levels from 0.3 to 0.6 were correspondents to the frequency range up to 50 Hz. Simulations involving temporal delay and coherence index demonstrated that the performed algorithm is able to detect coherence between EEG and EMG recordings from these muscles, with temporal displacement up to 0.4 seconds. The results provide clear evidence of a cortical drive synchronizing muscle discharge over a broad range of frequencies. Fourier analysis seems to be a good technique in the diagnosis and investigation of patients with cortical myoclonus. Once corticomuscular coherence is a noninvasive procedure useful to investigate specific corticomotoneuronal frequency in a medical application, this approach could be useful in tremor and myoclonus research.
URI: https://app.uff.br/riuff/handle/1/18775
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