Neural Mass Model-Based Different EEG Signal Generation and Analysis in Simulink

The electroencephalogram (EEG) is an electrophysiological monitoring strategy that records the spontaneous electrical movement of brain coming about from ionic current inside neurons brain. importance EEG signal mainly diagnosis different mental and neurodegenerative diseases abnormalities like seizure disorder, encephalopathy, dementia, memory problem, sleep stroke, etc. very useful for someone in case a coma to determine level activity. So, it important study generation analysis. To reduce complexity understanding pathophysiological mechanism their changes, simulation-based modeling has been developed which are based on anatomical equivalent data. In this paper, Instead detailed model neural mass used implement models refers simplified straightforward method. This paper aims introduce obtained signals own implementation Lopes da Silva model, Jansen-Rit Wendling Simulink compare characteristic features with real better especially seizure-like pattern.