Computational Tools to Support the Study of the Brain
This work applies computing tools for supporting the study of the brain. We followed an interdisciplinary approach in the interface between computer science and neuroscience. We used computing tools for the controlled sensory stimulation of the volunteers during a verb recognizing task, brain recordings through electroencephalograms, pre-processing of the data for filtering noise caused by the electrical supply, noise from eye blinks, chews and movement of the head. The brain data recorded from alcoholic and non-alcoholic volunteers was separated by evoked response potentials (ERPs) pooled in a group of alcoholic ERPs and another of non-alcoholic ERPs. We used the technique of artificial neural network for classifying the dataset in alcoholic and non-alcoholics. The results showed that it is possible to separate the alcoholic and non-alcoholic subjects based on their ERP signals.