Computational brain & behavior最新文献

{"title":"Bayes Factors for Mixed Models: a Discussion","authors":"Johnny van Doorn, J. Haaf, A. Stefan, E. Wagenmakers, Gregory E. Cox, C. Davis-Stober, A. Heathcote, D. Heck, M. Kalish, David Kellen, D. Matzke, R. Morey, Bruno Nicenboim, D. van Ravenzwaaij, Jeffrey N. Rouder, D. Schad, R. Shiffrin, H. Singmann, S. Vasishth, J. Veríssimo, F. Bockting, Suyog H. Chandramouli, J. Dunn, Q. Gronau, M. Linde, Sara D McMullin, Danielle Navarro, Martin Schnuerch, Himanshu Yadav, F. Aust","doi":"10.1007/s42113-022-00160-3","DOIUrl":"https://doi.org/10.1007/s42113-022-00160-3","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"15 1","pages":"140-158"},"PeriodicalIF":0.0,"publicationDate":"2023-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85223065","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}

{"title":"Convolutional Neural Networks Trained to Identify Words Provide a Surprisingly Good Account of Visual Form Priming Effects","authors":"Dong Yin, Valerio Biscione, J. Bowers","doi":"10.1007/s42113-023-00172-7","DOIUrl":"https://doi.org/10.1007/s42113-023-00172-7","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"48 1","pages":"457 - 472"},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85919312","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}

{"title":"Stimulus Selection in a Q-learning Model Using Fisher Information and Monte Carlo Simulation","authors":"Kazuya Fujita, Kensuke Okada, K. Katahira","doi":"10.1007/s42113-022-00163-0","DOIUrl":"https://doi.org/10.1007/s42113-022-00163-0","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"50 1","pages":"1-18"},"PeriodicalIF":0.0,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74353601","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}

{"title":"Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For?","authors":"Marlou Nadine Perquin, Marieke K van Vugt, Craig Hedge, Aline Bompas","doi":"10.1007/s42113-022-00162-1","DOIUrl":"10.1007/s42113-022-00162-1","url":null,"abstract":"<p><p>Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures - to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (<i>d</i>) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s42113-022-00162-1.</p>","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":" ","pages":"1-38"},"PeriodicalIF":0.0,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810256/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10564231","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}

{"title":"Bayes Factors for Mixed Models: Perspective on Responses.","authors":"Johnny van Doorn, Frederik Aust, Julia M Haaf, Angelika M Stefan, Eric-Jan Wagenmakers","doi":"10.1007/s42113-022-00158-x","DOIUrl":"10.1007/s42113-022-00158-x","url":null,"abstract":"<p><p>In van Doorn et al. (2021), we outlined a series of open questions concerning Bayes factors for mixed effects model comparison, with an emphasis on the impact of aggregation, the effect of measurement error, the choice of prior distributions, and the detection of interactions. Seven expert commentaries (partially) addressed these initial questions. Surprisingly perhaps, the experts disagreed (often strongly) on what is best practice-a testament to the intricacy of conducting a mixed effect model comparison. Here, we provide our perspective on these comments and highlight topics that warrant further discussion. In general, we agree with many of the commentaries that in order to take full advantage of Bayesian mixed model comparison, it is important to be aware of the specific assumptions that underlie the to-be-compared models.</p>","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"6 1","pages":"127-139"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9424467","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}

{"title":"What Happens After a Fast Versus Slow Error, and How Does It Relate to Evidence Accumulation?","authors":"K. Damaso, Paul G. Williams, A. Heathcote","doi":"10.1007/s42113-022-00137-2","DOIUrl":"https://doi.org/10.1007/s42113-022-00137-2","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"26 1","pages":"527 - 546"},"PeriodicalIF":0.0,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78773371","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}

{"title":"Discovering Common Hidden Causes in Sequences of Events","authors":"Simon Valentin, Neil R. Bramley, Christopher G. Lucas","doi":"10.1007/s42113-022-00156-z","DOIUrl":"https://doi.org/10.1007/s42113-022-00156-z","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"38 1","pages":"377 - 399"},"PeriodicalIF":0.0,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75621272","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}

{"title":"AI-Assisted Decision-making: a Cognitive Modeling Approach to Infer Latent Reliance Strategies","authors":"Heliodoro Tejeda, Aakriti Kumar, Padhraic Smyth, M. Steyvers","doi":"10.1007/s42113-022-00157-y","DOIUrl":"https://doi.org/10.1007/s42113-022-00157-y","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"144 1","pages":"491 - 508"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82620558","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}

{"title":"Measure-Theoretic Musings Cannot Salvage the Full Bayesian Significance Test as a Measure of Evidence","authors":"A. Ly, E. Wagenmakers","doi":"10.1007/s42113-022-00154-1","DOIUrl":"https://doi.org/10.1007/s42113-022-00154-1","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"28 1","pages":"583-589"},"PeriodicalIF":0.0,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80376655","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}

{"title":"Traveling Salesperson Problem with Simple Obstacles: The Role of Multidimensional Scaling and the Role of Clustering","authors":"Jacob VanDrunen, Kevin Nam, Mark Beers, Z. Pizlo","doi":"10.1007/s42113-022-00155-0","DOIUrl":"https://doi.org/10.1007/s42113-022-00155-0","url":null,"abstract":"","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"20 1","pages":"513 - 525"},"PeriodicalIF":0.0,"publicationDate":"2022-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76114062","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}