{"title":"N400 Repetition Effects on Olfactory Memory Learning","authors":"Sricheta Parui, Lidia Ghosh, A. Konar","doi":"10.1109/ICCCI.2018.8441387","DOIUrl":null,"url":null,"abstract":"The present work aims at classifying the 3 different learning levels of a subject during olfactory memory learning task based on the N400 repetition effects. The paper proposes a simple feature extraction technique to detect the N400 signal from the captured electroencephalographic waveform and an Interval type-2 Fuzzy Classifier is then designed to classify the learning levels using the extracted features. The paper also proposes a way to detect the early Alzheimer and schizophrenic patients using an event-related potential named N400. Here it is shown that the repetition effect of the N400 signal is different for the Alzheimer patients and healthy person. An N400 peak is noticed for both the Alzheimer patients and the healthy person but the amplitude of the curve is different for two different cases. The other aspect of this present work reveals that the increased latency of N400 signal can help us to detect a schizophrenic patient.","PeriodicalId":141663,"journal":{"name":"2018 International Conference on Computer Communication and Informatics (ICCCI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Computer Communication and Informatics (ICCCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCI.2018.8441387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The present work aims at classifying the 3 different learning levels of a subject during olfactory memory learning task based on the N400 repetition effects. The paper proposes a simple feature extraction technique to detect the N400 signal from the captured electroencephalographic waveform and an Interval type-2 Fuzzy Classifier is then designed to classify the learning levels using the extracted features. The paper also proposes a way to detect the early Alzheimer and schizophrenic patients using an event-related potential named N400. Here it is shown that the repetition effect of the N400 signal is different for the Alzheimer patients and healthy person. An N400 peak is noticed for both the Alzheimer patients and the healthy person but the amplitude of the curve is different for two different cases. The other aspect of this present work reveals that the increased latency of N400 signal can help us to detect a schizophrenic patient.