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The purpose of analyzing the different stages of sleep by means of functional connectivity metrics is due to the overwhelming unlikelihood of seizures occurring during REM sleep. The functional connectivity metrics are computational algorithms run on a computer that determine if the signal from one node is similar to another in any way. These nodes record the electrical potentials from the brain and are arranged around the head in a certain pattern making up an electroencephalogram (EEG) recording. Determining the proper steps of manipulating the signals to reduce any anomalies from the signal is ideal for obtaining a truly reputable result. Through this work these algorithms can be adopted by the Health Sciences Centre to improve research in the field.
Marcus Ng;Zahra Kazem-Moussavi
Health Sciences Centre Foundation
University of Manitoba
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