Study On Correlation And Phase Synchrony Of Epilepsy Seizure Prediction Based On Intracranial EEG

Epilepsy, one of the most common neurological diseases, which is mainly due tothe excessive synchronous discharge from brain neurons. Epilepsy affects over50million people worldwide, it’s recurrent and bursts, resulting in mental disorders,accident and sudden death occurs in patients, attacking seriously hurt patient’sphysical and mental health. If we can predict seizures before the upcoming seizure,even for a short time, it is possible to make certain that we take epilepsy treatmentinterventions so that seizures hurt is greatly eased.Studies have shown that epilepsy is a gradual process over time, especially itmay have certain regularity before the seizure onset, which makes it possible topredict seizures. Currently, the most commonly used prediction method is to analyzeepilepsy patients’ EEG, and apply statistical methods. EEG can be divided into thescalp EEG (EEG) and intracranial EEG (iEEG), compared to the EEG signal, iEEGsignal is less susceptible to environmental noise and artifacts, the use of iEEG signalsin epileptic patients has received great attention.In this study, we use microelectrodes implanted in patients with intracranialcollected intracranial EEG (MiE) as epilepsy forecast data. This is due tomicroelectrode is contacted more close to neurons than macroelectrode and thus it ismore sensitive to neuron activity changes than macroelectrode. Microwire iEEGrecordings are inevitably advantageous over macrowire iEEG recordings to revealneuronal mechanisms contributing to the generation of seizures.In this study, we investigate the seizure generation from microwire iEEGrecordings and discuss synchronization of microwire iEEGs in four frequency bands:alpha (1-30Hz), gamma (30-80Hz), ripple (80–250Hz), and fast ripple ([250Hz) viatwo measures: correlation and phase synchrony. We find that an increase trend ofcorrelation or phase synchrony exists before the macroseizure onset mostly in gammaand ripple bands where the duration of the preictal states varied in different seizuresranging up to a few seconds (minutes). This finding is contrast to the well-knownresult that a decrease of synchronization in macro domains exists before themacroseizure onset. The finding demonstrates that it is only when the seizure hasrecruited enough surrounding brain tissue does the signal become strong enough to beobserved on the clinical macroelectrode and as a result support the hypothesis of progressive coalescence of microseizure domains. The potential ramifications of suchan early detection of microscale seizure activity may open a new window on treatmentby making possible disruption of seizure activity before it becomes fully established.