Electro- Hemodynamic Activity in Children: Combined Analysis by Video -EEG Spectroscopy and Near-infrared (NIRS )

Epilepsy in children is a major public health issue. It is the first neurological disease of the child. The specific incidence of epilepsy rates were highest during the first year of life, between 75,105 and 250,105 hab.an hab. year and remain high in the age group between 0 and 10 years. Epilepsies predictions are varied. They can be spontaneously benign, drug-, chemically dependent or drug-resistant. These, refractory epilepsies, represent 20% of epilepsy as a child and adolescent than adult is about 1200 children and 1200 adults Picardy. The validation of non-invasive investigative tools is becoming a necessity in the management of drug-resistant epilepsies especially when a surgical decision is envisaged. The aftermath (motor, cognitive, sensory) appear to rule early; but they are sometimes limited to learning deficits detected later in the school curriculum. The investigators know that defects in neuronal electrical activity (eg critical discharges) induce a metabolic response and conversely metabolic disturbances can cause abnormal electrical activity. It is therefore important to have tools to better characterize the interactions between these two mechanisms to better understand brain function in the brain during development and during pathological situations. The investigators lack quantitative criteria regarding the impact of crises on the metabolic activity and thus predictive criteria consequences of crises on brain function. The deleterious hazard must be considered at all ages in both structures to causing seizures than in those where the crisis spread. The functional characterization, electrical, metabolic and anatomic pathology of these networks is necessary and contributes to a better understanding of physiological and pathological brain function, and helps to define the most appropriate treatment strategy.

About childhood epilepsy, analysis of the EEG allows in 75% of cases to find predictive patterns characteristic of becoming. However in 25% of cases, we lack predictive objective criteria. This highlights the importance of developing analysis tools for more accurate and efficient brain function and to improve the management and evaluation of the prognosis of these children.