S. Hafizovic, F. Heer, U. Frey, T. Ugniwenko, A. Blau, C. Ziegler, A. Hierlemann
{"title":"基于cmos的自然神经元信息处理微电极阵列","authors":"S. Hafizovic, F. Heer, U. Frey, T. Ugniwenko, A. Blau, C. Ziegler, A. Hierlemann","doi":"10.1109/CNE.2007.369767","DOIUrl":null,"url":null,"abstract":"We report on a complementary-metal-oxide-semiconductor-based system that is capable of bidirectionally communicating (stimulation and recording) with electrogenic cells such as neurons or cardiomyocytes. It is is targeted at investigating electrical signal propagation within cellular networks in vitro. Experiments including the stimulation of neurons with two different spatio-temporal patterns and the recording of the triggered spiking activity have been carried out. The neuronal response patterns have been successfully classified (83% correct classifications) with respect to the different stimulation patterns. It will be demonstrated that information processing using natural neuronal networks may be possible","PeriodicalId":427054,"journal":{"name":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A CMOS-based Microelectrode Array for Information Processing with Natural Neurons\",\"authors\":\"S. Hafizovic, F. Heer, U. Frey, T. Ugniwenko, A. Blau, C. Ziegler, A. Hierlemann\",\"doi\":\"10.1109/CNE.2007.369767\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We report on a complementary-metal-oxide-semiconductor-based system that is capable of bidirectionally communicating (stimulation and recording) with electrogenic cells such as neurons or cardiomyocytes. It is is targeted at investigating electrical signal propagation within cellular networks in vitro. Experiments including the stimulation of neurons with two different spatio-temporal patterns and the recording of the triggered spiking activity have been carried out. The neuronal response patterns have been successfully classified (83% correct classifications) with respect to the different stimulation patterns. It will be demonstrated that information processing using natural neuronal networks may be possible\",\"PeriodicalId\":427054,\"journal\":{\"name\":\"2007 3rd International IEEE/EMBS Conference on Neural Engineering\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-05-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 3rd International IEEE/EMBS Conference on Neural Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CNE.2007.369767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 3rd International IEEE/EMBS Conference on Neural Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CNE.2007.369767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A CMOS-based Microelectrode Array for Information Processing with Natural Neurons
We report on a complementary-metal-oxide-semiconductor-based system that is capable of bidirectionally communicating (stimulation and recording) with electrogenic cells such as neurons or cardiomyocytes. It is is targeted at investigating electrical signal propagation within cellular networks in vitro. Experiments including the stimulation of neurons with two different spatio-temporal patterns and the recording of the triggered spiking activity have been carried out. The neuronal response patterns have been successfully classified (83% correct classifications) with respect to the different stimulation patterns. It will be demonstrated that information processing using natural neuronal networks may be possible