神经习惯化可增强新奇感检测:快速呈现单词的脑电图研究。

Computational brain & behavior Pub Date : 2020-06-01 Epub Date: 2019-12-18 DOI:10.1007/s42113-019-00071-w
Len P L Jacob, David E Huber
{"title":"神经习惯化可增强新奇感检测:快速呈现单词的脑电图研究。","authors":"Len P L Jacob, David E Huber","doi":"10.1007/s42113-019-00071-w","DOIUrl":null,"url":null,"abstract":"<p><p>Huber and O'Reilly (2003) proposed that neural habituation aids perceptual processing, separating neural responses to currently viewed objects from recently viewed objects. However, synaptic depression has costs, producing repetition deficits. Prior work confirmed the transition from repetition benefits to deficits with increasing duration of a prime object, but the prediction of enhanced novelty detection was not tested. The current study examined this prediction with a same/different word priming task, using support vector machine (SVM) classification of EEG data, ERP analyses focused on the N400, and dynamic neural network simulations fit to behavioral data to provide a priori predictions of the ERP effects. Subjects made same/different judgements to a response word in relation to an immediately preceding brief target word; prime durations were short (50ms) or long (400ms), and long durations decreased P100/N170 responses to the target word, suggesting that this manipulation increased habituation. Following long duration primes, correct \"different\" judgments of primed response words increased, evidencing enhanced novelty detection. An SVM classifier predicted trial-by-trial behavior with 66.34% accuracy on held-out data, with greatest predictive power at a time pattern consistent with the N400. The habituation model was augmented with a maintained semantics layer (i.e., working memory) to generate behavior and N400 predictions. A second experiment used response-locked ERPs, confirming the model's assumption that residual activation in working memory is the basis of novelty decisions. These results support the theory that neural habituation enhances novelty detection, and the model assumption that the N400 reflects updating of semantic information in working memory.</p>","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"3 2","pages":"208-227"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7447193/pdf/nihms-1546975.pdf","citationCount":"0","resultStr":"{\"title\":\"Neural habituation enhances novelty detection: an EEG study of rapidly presented words.\",\"authors\":\"Len P L Jacob, David E Huber\",\"doi\":\"10.1007/s42113-019-00071-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Huber and O'Reilly (2003) proposed that neural habituation aids perceptual processing, separating neural responses to currently viewed objects from recently viewed objects. However, synaptic depression has costs, producing repetition deficits. Prior work confirmed the transition from repetition benefits to deficits with increasing duration of a prime object, but the prediction of enhanced novelty detection was not tested. The current study examined this prediction with a same/different word priming task, using support vector machine (SVM) classification of EEG data, ERP analyses focused on the N400, and dynamic neural network simulations fit to behavioral data to provide a priori predictions of the ERP effects. Subjects made same/different judgements to a response word in relation to an immediately preceding brief target word; prime durations were short (50ms) or long (400ms), and long durations decreased P100/N170 responses to the target word, suggesting that this manipulation increased habituation. Following long duration primes, correct \\\"different\\\" judgments of primed response words increased, evidencing enhanced novelty detection. An SVM classifier predicted trial-by-trial behavior with 66.34% accuracy on held-out data, with greatest predictive power at a time pattern consistent with the N400. The habituation model was augmented with a maintained semantics layer (i.e., working memory) to generate behavior and N400 predictions. A second experiment used response-locked ERPs, confirming the model's assumption that residual activation in working memory is the basis of novelty decisions. These results support the theory that neural habituation enhances novelty detection, and the model assumption that the N400 reflects updating of semantic information in working memory.</p>\",\"PeriodicalId\":72660,\"journal\":{\"name\":\"Computational brain & behavior\",\"volume\":\"3 2\",\"pages\":\"208-227\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7447193/pdf/nihms-1546975.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational brain & behavior\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s42113-019-00071-w\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2019/12/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational brain & behavior","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s42113-019-00071-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/12/18 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

Huber 和 O'Reilly(2003 年)提出,神经习惯化有助于感知处理,将神经对当前观看物体和最近观看物体的反应分离开来。然而,突触抑制是有代价的,它会产生重复障碍。先前的研究证实,随着主要对象持续时间的增加,重复的益处会转变为缺陷,但对新奇事物检测增强的预测却没有进行测试。本研究利用支持向量机(SVM)对脑电图数据进行分类,对 N400 进行ERP分析,并对行为数据进行动态神经网络模拟,从而对ERP效应进行先验预测。受试者根据紧随其后的简短目标词对反应词做出相同/不同的判断;prime 持续时间有短(50 毫秒)和长(400 毫秒)之分,长持续时间会降低目标词的 P100/N170 反应,表明这种操作会增加习惯性。在长持续时间引物之后,对引物反应词的正确 "不同 "判断增加了,这证明新颖性检测增强了。SVM 分类器对保留数据的逐次试验行为预测准确率为 66.34%,在与 N400 一致的时间模式下预测能力最强。习惯化模型通过一个保持语义层(即工作记忆)来生成行为和 N400 预测结果。第二个实验使用了反应锁定的 ERPs,证实了该模型的假设,即工作记忆中的残余激活是新奇决定的基础。这些结果支持了神经习惯性增强新奇事物检测的理论,以及 N400 反映了工作记忆中语义信息更新的模型假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Neural habituation enhances novelty detection: an EEG study of rapidly presented words.

Huber and O'Reilly (2003) proposed that neural habituation aids perceptual processing, separating neural responses to currently viewed objects from recently viewed objects. However, synaptic depression has costs, producing repetition deficits. Prior work confirmed the transition from repetition benefits to deficits with increasing duration of a prime object, but the prediction of enhanced novelty detection was not tested. The current study examined this prediction with a same/different word priming task, using support vector machine (SVM) classification of EEG data, ERP analyses focused on the N400, and dynamic neural network simulations fit to behavioral data to provide a priori predictions of the ERP effects. Subjects made same/different judgements to a response word in relation to an immediately preceding brief target word; prime durations were short (50ms) or long (400ms), and long durations decreased P100/N170 responses to the target word, suggesting that this manipulation increased habituation. Following long duration primes, correct "different" judgments of primed response words increased, evidencing enhanced novelty detection. An SVM classifier predicted trial-by-trial behavior with 66.34% accuracy on held-out data, with greatest predictive power at a time pattern consistent with the N400. The habituation model was augmented with a maintained semantics layer (i.e., working memory) to generate behavior and N400 predictions. A second experiment used response-locked ERPs, confirming the model's assumption that residual activation in working memory is the basis of novelty decisions. These results support the theory that neural habituation enhances novelty detection, and the model assumption that the N400 reflects updating of semantic information in working memory.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.30
自引率
0.00%
发文量
0
期刊最新文献
Quantifying Individual Variability in Neural Control Circuit Regulation Using Single-Subject fMRI Towards Dependent Race Models for the Stop-Signal Paradigm Modeling Time Cell Neuron-Level Dynamics Probabilistic Choice Induced by Strength of Preference An Extension and Clinical Application of the SIMPLE Model to the Free Recall of Repeated and Semantically Related Items
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1