{"title":"启动实验的脑磁图潜伏期差测量。","authors":"A Matani, T Hayakawa, S Munetsuna, N Fujimaki","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Latency analysis of magnetoencephalography (MEG) for priming experiments, not in motor readiness level but in cognition level, may be useful for identification of the brain system. We performed a masked priming experiment for repetitive presentation of visual words. The subjects of the experiment were asked to perform a categorization task and button-pressing. The stimuli of the experiment consisted of mask (duration: 700 ms) - prime (70 ms) - target (1000 ms). There were four types of experiment which depended on the combinations of primes and targets: #1) in-category/in-category; #2) pseudo-characters/in-category; #3) out-category/out-category; and #4) pseudo-characters/out-category. As a result, the order of reaction times (RTs) were #1 < #2 < #3 approximately #4. We performed MEG recording with the above experiment simultaneously. Due to such a short stimulus onset asynchrony (SOA) of 70 ms and higher-order brain activity for language processing, the MEG activity continued for several hundred milliseconds, did not have conspicuous peaks, and could not be separated in the prime and target responses. This kind of MEG data is difficult to investigate with conventional signal processing methods, such as subtraction or signal source estimation. We applied a pattern analyzing method that measured the similarity time course between two sets of MEG data. The similarity time courses between experiments #3 and #4 and the other experiments were calculated. The order of the peak latencies of the time course was the same as that of RTs.</p>","PeriodicalId":83814,"journal":{"name":"Neurology & clinical neurophysiology : NCN","volume":"2004 ","pages":"54"},"PeriodicalIF":0.0000,"publicationDate":"2004-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MEG latency difference measurement for priming experiments.\",\"authors\":\"A Matani, T Hayakawa, S Munetsuna, N Fujimaki\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Latency analysis of magnetoencephalography (MEG) for priming experiments, not in motor readiness level but in cognition level, may be useful for identification of the brain system. We performed a masked priming experiment for repetitive presentation of visual words. The subjects of the experiment were asked to perform a categorization task and button-pressing. The stimuli of the experiment consisted of mask (duration: 700 ms) - prime (70 ms) - target (1000 ms). There were four types of experiment which depended on the combinations of primes and targets: #1) in-category/in-category; #2) pseudo-characters/in-category; #3) out-category/out-category; and #4) pseudo-characters/out-category. As a result, the order of reaction times (RTs) were #1 < #2 < #3 approximately #4. We performed MEG recording with the above experiment simultaneously. Due to such a short stimulus onset asynchrony (SOA) of 70 ms and higher-order brain activity for language processing, the MEG activity continued for several hundred milliseconds, did not have conspicuous peaks, and could not be separated in the prime and target responses. This kind of MEG data is difficult to investigate with conventional signal processing methods, such as subtraction or signal source estimation. We applied a pattern analyzing method that measured the similarity time course between two sets of MEG data. The similarity time courses between experiments #3 and #4 and the other experiments were calculated. The order of the peak latencies of the time course was the same as that of RTs.</p>\",\"PeriodicalId\":83814,\"journal\":{\"name\":\"Neurology & clinical neurophysiology : NCN\",\"volume\":\"2004 \",\"pages\":\"54\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurology & clinical neurophysiology : NCN\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurology & clinical neurophysiology : NCN","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MEG latency difference measurement for priming experiments.
Latency analysis of magnetoencephalography (MEG) for priming experiments, not in motor readiness level but in cognition level, may be useful for identification of the brain system. We performed a masked priming experiment for repetitive presentation of visual words. The subjects of the experiment were asked to perform a categorization task and button-pressing. The stimuli of the experiment consisted of mask (duration: 700 ms) - prime (70 ms) - target (1000 ms). There were four types of experiment which depended on the combinations of primes and targets: #1) in-category/in-category; #2) pseudo-characters/in-category; #3) out-category/out-category; and #4) pseudo-characters/out-category. As a result, the order of reaction times (RTs) were #1 < #2 < #3 approximately #4. We performed MEG recording with the above experiment simultaneously. Due to such a short stimulus onset asynchrony (SOA) of 70 ms and higher-order brain activity for language processing, the MEG activity continued for several hundred milliseconds, did not have conspicuous peaks, and could not be separated in the prime and target responses. This kind of MEG data is difficult to investigate with conventional signal processing methods, such as subtraction or signal source estimation. We applied a pattern analyzing method that measured the similarity time course between two sets of MEG data. The similarity time courses between experiments #3 and #4 and the other experiments were calculated. The order of the peak latencies of the time course was the same as that of RTs.