Computational brain & behavior最新文献

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The Limits of Marginality 边缘性的极限
Computational brain & behavior Pub Date : 2021-09-22 DOI: 10.1007/s42113-021-00120-3
A. Heathcote, D. Matzke
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引用次数: 3
Publisher Correction to: A Computational Dual-Process Model of Fixation-Duration Control in Natural Scene Viewing 自然场景观看中注视-持续时间控制的计算双过程模型
Computational brain & behavior Pub Date : 2021-09-01 DOI: 10.1007/s42113-021-00119-w
R. C. Walshe, A. Nuthmann
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引用次数: 1
Sample Size Determination for Bayesian Hierarchical Models Commonly Used in Psycholinguistics 心理语言学中常用贝叶斯层次模型的样本量确定
Computational brain & behavior Pub Date : 2021-09-01 DOI: 10.1007/s42113-021-00125-y
S. Vasishth, Himanshu Yadav, D. Schad, Bruno Nicenboim
{"title":"Sample Size Determination for Bayesian Hierarchical Models Commonly Used in Psycholinguistics","authors":"S. Vasishth, Himanshu Yadav, D. Schad, Bruno Nicenboim","doi":"10.1007/s42113-021-00125-y","DOIUrl":"https://doi.org/10.1007/s42113-021-00125-y","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"12 3 1","pages":"102-126"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90391827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
A Computational Dual-Process Model of Fixation-Duration Control in Natural Scene Viewing 自然景物注视-持续时间控制的计算双过程模型
Computational brain & behavior Pub Date : 2021-09-01 DOI: 10.1007/s42113-021-00111-4
R. C. Walshe, A. Nuthmann
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引用次数: 4
Wheel of Fortune: a Cross-cultural Examination of How Expertise Shapes the Mental Representations of Familiar and Unfamiliar Numerals 幸运之轮:专业知识如何塑造熟悉和不熟悉数字的心理表征的跨文化研究
Computational brain & behavior Pub Date : 2021-08-31 DOI: 10.1007/s42113-021-00122-1
P. Garrett, Murray Bennett, Yu-Tzu Hsieh, Zachary L. Howard, Cheng-Ta, Daniel R. Little, A. Eidels
{"title":"Wheel of Fortune: a Cross-cultural Examination of How Expertise Shapes the Mental Representations of Familiar and Unfamiliar Numerals","authors":"P. Garrett, Murray Bennett, Yu-Tzu Hsieh, Zachary L. Howard, Cheng-Ta, Daniel R. Little, A. Eidels","doi":"10.1007/s42113-021-00122-1","DOIUrl":"https://doi.org/10.1007/s42113-021-00122-1","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"28 2","pages":"45 - 59"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72412445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reconstructing the Einstellung Effect 重建爱因斯坦效应
Computational brain & behavior Pub Date : 2021-08-10 DOI: 10.1007/s42113-022-00161-2
Marcel Binz, Eric Schulz
{"title":"Reconstructing the Einstellung Effect","authors":"Marcel Binz, Eric Schulz","doi":"10.1007/s42113-022-00161-2","DOIUrl":"https://doi.org/10.1007/s42113-022-00161-2","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"106 1","pages":"526 - 542"},"PeriodicalIF":0.0,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79293275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Approximating the Manifold Structure of Attributed Incentive Salience from Large-scale Behavioural Data 从大规模行为数据中逼近归因激励显著性的流形结构
Computational brain & behavior Pub Date : 2021-08-03 DOI: 10.1007/s42113-022-00147-0
Valerio Bonometti, Mathieu J. Ruiz, Anders Drachen, Alex R. Wade
{"title":"Approximating the Manifold Structure of Attributed Incentive Salience from Large-scale Behavioural Data","authors":"Valerio Bonometti, Mathieu J. Ruiz, Anders Drachen, Alex R. Wade","doi":"10.1007/s42113-022-00147-0","DOIUrl":"https://doi.org/10.1007/s42113-022-00147-0","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"7 1","pages":"280 - 315"},"PeriodicalIF":0.0,"publicationDate":"2021-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74670098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
On the Measure-Theoretic Premises of Bayes Factor and Full Bayesian Significance Tests: a Critical Reevaluation 贝叶斯因子和全贝叶斯显著性检验的测度论前提:一个关键性的再评价
Computational brain & behavior Pub Date : 2021-07-07 DOI: 10.1007/s42113-021-00110-5
Riko Kelter
{"title":"On the Measure-Theoretic Premises of Bayes Factor and Full Bayesian Significance Tests: a Critical Reevaluation","authors":"Riko Kelter","doi":"10.1007/s42113-021-00110-5","DOIUrl":"https://doi.org/10.1007/s42113-021-00110-5","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"1 1","pages":"572 - 582"},"PeriodicalIF":0.0,"publicationDate":"2021-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90765717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Statistics in the Service of Science: Don’t Let the Tail Wag the Dog 为科学服务的统计学:不要本末倒置
Computational brain & behavior Pub Date : 2021-06-20 DOI: 10.1007/s42113-022-00129-2
H. Singmann, David Kellen, Gregory E. Cox, Suyog H. Chandramouli, C. Davis-Stober, J. Dunn, Q. Gronau, M. Kalish, Sara D McMullin, D. Navarro, R. Shiffrin
{"title":"Statistics in the Service of Science: Don’t Let the Tail Wag the Dog","authors":"H. Singmann, David Kellen, Gregory E. Cox, Suyog H. Chandramouli, C. Davis-Stober, J. Dunn, Q. Gronau, M. Kalish, Sara D McMullin, D. Navarro, R. Shiffrin","doi":"10.1007/s42113-022-00129-2","DOIUrl":"https://doi.org/10.1007/s42113-022-00129-2","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"33 1","pages":"64-83"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76373033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
Scale-Dependent Relationships in Natural Language. 自然语言中的尺度依赖关系。
Computational brain & behavior Pub Date : 2021-06-01 Epub Date: 2021-01-04 DOI: 10.1007/s42113-020-00094-8
Aakash Sarkar, Marc W Howard
{"title":"Scale-Dependent Relationships in Natural Language.","authors":"Aakash Sarkar,&nbsp;Marc W Howard","doi":"10.1007/s42113-020-00094-8","DOIUrl":"10.1007/s42113-020-00094-8","url":null,"abstract":"<p><p>Language, like other natural sequences, exhibits statistical dependencies at a wide range of scales (Lin & Tegmark, 2016). However, many statistical learning models applied to language impose a sampling scale while extracting statistical structure. For instance, Word2Vec creates vector embeddings by sampling context in a window around each word, the size of which defines a strong scale; relationships over much larger temporal scales would be invisible to the algorithm. This paper examines the family of Word2Vec embeddings generated while systematically manipulating the size of the context window. The primary result is that different linguistic relationships are preferentially encoded at different scales. Different scales emphasize different syntactic and semantic relations between words, as assessed both by analogical reasoning tasks in the Google Analogies test set and human similarity rating datasets WordSim-353 and SimLex-999. Moreover, the neighborhoods of a given word in the embeddings change considerably depending on the scale. These results suggest that sampling at any individual scale can only identify a subset of the meaningful relationships a word might have, and point toward the importance of developing scale-free models of semantic meaning.</p>","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"4 ","pages":"164-177"},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s42113-020-00094-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39268103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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