Behavior Research Methods最新文献_第4页

The Pictures by Category and Similarity (PiCS) database: A multidimensional scaling database of 1200 images across 20 categories. 图片按类别和相似性（PiCS）数据库：一个多维缩放数据库，包含20个类别的1200张图像。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-30 DOI: 10.3758/s13428-025-02732-0

Arryn Robbins, Michael C Hout, Ashley Ercolino, Joseph Schmidt, Hayward J Godwin, Justin MacDonald

{"title":"The Pictures by Category and Similarity (PiCS) database: A multidimensional scaling database of 1200 images across 20 categories.","authors":"Arryn Robbins, Michael C Hout, Ashley Ercolino, Joseph Schmidt, Hayward J Godwin, Justin MacDonald","doi":"10.3758/s13428-025-02732-0","DOIUrl":"10.3758/s13428-025-02732-0","url":null,"abstract":"Visual similarity is an essential concept in vision science, and the methods used to quantify similarity have recently expanded in the areas of human-derived ratings and computer vision methodologies. Researchers who want to manipulate similarity between images (e.g., in a visual search, categorization, or memory task) often use the aforementioned methods, which require substantial, additional data collection prior to the primary task of interest. To alleviate this problem, we have developed an openly available database that uses multidimensional scaling (MDS) to model the similarity among 1200 items spread across 20 object categories, thereby allowing researchers to utilize similarity ratings within and between categories. In this article, we document the development of this database, including (1) collecting similarity ratings using the spatial arrangement method across two sites, (2) our computational approach with MDS, and (3) validation of the MDS space by comparing SpAM-derived distances to direct similarity ratings. The database and similarity data provided between items (and across categories) will be useful to researchers wanting to manipulate or control similarity in their studies.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 8","pages":"212"},"PeriodicalIF":4.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208956/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144526311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Japanese LDA model for automatic clustering analysis of semantic verbal fluency tests. 语义语言流畅性测试自动聚类分析的日文LDA模型。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-30 DOI: 10.3758/s13428-025-02696-1

Masahiro Yoshihara, Yoshihiro Itaguchi

{"title":"A Japanese LDA model for automatic clustering analysis of semantic verbal fluency tests.","authors":"Masahiro Yoshihara, Yoshihiro Itaguchi","doi":"10.3758/s13428-025-02696-1","DOIUrl":"10.3758/s13428-025-02696-1","url":null,"abstract":"In the semantic variant of verbal fluency tests (VFTs), clustering analysis has become popular for examining the semantic structure. While the computational psycholinguistics approach has recently drawn attention to increasing the reproducibility of clustering analysis, such an approach is not available in all languages. To make the computational approach available in the Japanese language, we constructed a Japanese latent Dirichlet allocation (LDA) model. Our LDA model enables researchers and clinicians to objectively quantify the associative relationships of words, thereby making it possible to automatically detect semantic clusters. We conducted the semantic VFT with healthy young Japanese adults to examine the validity of our LDA model. We performed clustering analyses using the computational approach with our LDA model and the conventional manual approach with human coders. The results showed that the LDA model identified semantic clusters, as did the human coders. In addition, we demonstrated for the first time that response intervals within a cluster were significantly shorter than those outside of clusters, regardless of the clustering approaches. This indicates that both approaches reflect a broadly accepted assumption that closer semantic relations require less processing time. However, LDA-based clustering produced, on average, larger clusters than human-based clustering did, indicating that the LDA model captured semantic relationships between words that human coders would not recognize. Taken together, the present results demonstrated the validity of our LDA model. We hope that our LDA model fosters the use of the computational linguistic approach in semantic VFTs with Japanese participants.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 8","pages":"209"},"PeriodicalIF":4.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12209035/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144526308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PoTeC: A German naturalistic eye-tracking-while-reading corpus. 德国自然主义的阅读时眼球追踪语料库。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-30 DOI: 10.3758/s13428-024-02536-8

Deborah N Jakobi, Thomas Kern, David R Reich, Patrick Haller, Lena A Jäger

{"title":"PoTeC: A German naturalistic eye-tracking-while-reading corpus.","authors":"Deborah N Jakobi, Thomas Kern, David R Reich, Patrick Haller, Lena A Jäger","doi":"10.3758/s13428-024-02536-8","DOIUrl":"10.3758/s13428-024-02536-8","url":null,"abstract":"The Potsdam Textbook Corpus (PoTeC) is a naturalistic eye-tracking-while-reading corpus containing data from 75 participants reading 12 scientific texts. PoTeC is the first naturalistic eye-tracking-while-reading corpus that contains eye-movements from domain experts as well as novices in a within-participant manipulation: It is based on a 2 <math><mo>×</mo></math> 2 <math><mo>×</mo></math> 2 fully crossed factorial design, which includes the participants' level of studies and the participants' discipline of studies as between-subjects factors and the text domain as a within-subjects factor. The participants' reading comprehension was assessed by a series of text comprehension questions and their domain knowledge was tested by text-independent background questions for each of the texts. The materials are annotated for a variety of linguistic features at different levels. We envision PoTeC to be used for a wide range of studies including but not limited to analyses of expert and non-expert reading strategies. The corpus and all the accompanying data at all stages of the preprocessing pipeline and all code used to preprocess the data is made available via GitHub: https://github.com/DiLi-Lab/PoTeC and OSF: https://osf.io/dn5hp/ . The data is furthermore integrated into the open-source package pymovements, which can be used in Python and R: https://github.com/aeye-lab/pymovements .","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 8","pages":"211"},"PeriodicalIF":4.6,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208991/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144526309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attentional control data collection: A resource for efficient data reuse. 注意力控制数据收集：有效数据重用的资源。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-24 DOI: 10.3758/s13428-025-02717-z

Julia M Haaf, Madlen Hoffstadt, Sven Lesche

{"title":"Attentional control data collection: A resource for efficient data reuse.","authors":"Julia M Haaf, Madlen Hoffstadt, Sven Lesche","doi":"10.3758/s13428-025-02717-z","DOIUrl":"10.3758/s13428-025-02717-z","url":null,"abstract":"Publicly available data are required to (1) assess the reproducibility of each individual findings in the literature, and (2) promote the reuse of data for a more efficient use of participants' time and public resources. Current data-sharing efforts are well suited for the first goal, yet they do not sufficiently address the second goal. Here, we show how structured collections of open data can be useful, as they allow a larger community of researchers easy access to a large body of data from their own research area. We introduce the Attentional Control Data Collection, a SQL database for attentional control experiments. We illustrate the structure of the database, how it can be easily accessed using a Shiny app and an R-package, and how researchers can contribute data from their studies to the database. Finally, we conduct our own initial analysis of the 64 data sets in our database, assessing the reliability of individual differences. The analysis highlights that reliability is generally low, and provides insights into planning future studies. For example, researchers should consider increasing the number of trials per person and condition to at least 400. The analysis highlights how an open database like ACDC can aid meta-analytic efforts as well as methodological innovation.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 8","pages":"208"},"PeriodicalIF":4.6,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12187800/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Examining the tradeoffs of exposure control and collateral information with multidimensional forced-choice computerized adaptive testing. 用多维强迫选择计算机自适应测试检验暴露控制和附带信息的权衡。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-23 DOI: 10.3758/s13428-025-02712-4

Naidan Tu, Sean Joo, Stephen Stark

{"title":"Examining the tradeoffs of exposure control and collateral information with multidimensional forced-choice computerized adaptive testing.","authors":"Naidan Tu, Sean Joo, Stephen Stark","doi":"10.3758/s13428-025-02712-4","DOIUrl":"10.3758/s13428-025-02712-4","url":null,"abstract":"Multidimensional forced-choice (MFC) testing has been proposed as an alternative to single-statement (SS) Likert-type measures to reduce response biases in noncognitive measurement. Research progress has been made on MFC computerized adaptive testing (CAT) to improve testing efficiency. CAT enhances efficiency by successively selecting items that are most informative at each respondent's trait estimate. In MFC CAT, this causes some forced-choice items and the statements composing them to be frequently exposed while others are rarely used, which adversely affects test security and costs. This research developed an exposure control method for MFC CAT based on the multi-unidimensional pairwise preference model (MUPP; Stark et al. Applied Psychological Measurement, 29,184-203, 2005). Because the method was intended to prevent the overuse of the most informative items and statements, it tended to decrease overall measurement accuracy and precision. Thus, a second purpose of this research was to examine the extent to which these losses in accuracy and precision might be offset by incorporating collateral information. The effectiveness of the exposure control method and the incorporation of collateral information in MFC CAT were investigated in a Monte Carlo study that also manipulated test length and the correlation between dimensions. A byproduct of this research was an MFC CAT algorithm that improves test security and cost-effectiveness, while simultaneously maintaining measurement accuracy and precision of noncognitive constructs.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 7","pages":"207"},"PeriodicalIF":4.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simplified Chinese lexicon project: A lexical decision database with 8105 characters and 4864 pseudocharacters. 简体汉语词汇项目：一个包含8105个字符和4864个伪字符的词汇决策数据库。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-23 DOI: 10.3758/s13428-025-02701-7

Yixia Wang, Yanxue Wang, Qi Chen, Emmanuel Keuleers

{"title":"Simplified Chinese lexicon project: A lexical decision database with 8105 characters and 4864 pseudocharacters.","authors":"Yixia Wang, Yanxue Wang, Qi Chen, Emmanuel Keuleers","doi":"10.3758/s13428-025-02701-7","DOIUrl":"10.3758/s13428-025-02701-7","url":null,"abstract":"This paper presents the Simplified Chinese Lexicon Project (SCLP), which collects lexical decision data for all 8105 characters in the List of Commonly Used Standard Chinese Characters and for 4864 pseudocharacters, which were generated using a novel method that leveraged the hierarchical nature of Chinese characters. We compared the collected data to existing megastudies on Chinese characters, and found that the newly collected data performed similarly in terms of reliability. The comprehensive coverage of simplified Chinese characters in the present study added to the existing studies by allowing for a more fine-grained investigation of the effects of a variety of character attributes on visual processing. We illustrated these advantages by performing virtual experiments on visual complexity and on the interplay between neighborhood size and regularity. Our results indicated that characters with higher visual complexity were harder to recognize, in line with previous findings, while regular characters took longer to process when the neighborhood size was small. In addition, we present a new evaluation of the interaction between character frequency and subcomponent frequency, resulting in a three-way interaction among character frequency, radical frequency, and residual component frequency. Extending the investigation of subcomponent frequency to the analysis of pseudocharacters, we found that the interaction of radical frequency and residual component frequency also modulated pseudocharacter rejection. To support researchers in conducting behavioral experiments or statistical modeling, we provide both trial-level data and experiment materials.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 7","pages":"206"},"PeriodicalIF":4.6,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12185670/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144473875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SPRAAKLAB - mobile laboratory for speech recorded acoustically and kinematically. SPRAAKLAB -移动实验室的语音记录声学和运动学。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-20 DOI: 10.3758/s13428-025-02726-y

Teja Rebernik, Jidde Jacobi, Raoul Buurke, Thomas B Tienkamp, Defne Abur, Martijn Wieling

引用次数: 0

MUSIFEAST-17: MUsic Stimuli for imagination, familiarity, emotion, and Aesthetic STudies across 17 genres. musifest -17: 17种类型的想象、熟悉、情感和美学研究的音乐刺激。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-20 DOI: 10.3758/s13428-025-02724-0

Hazel A van der Walle, Wei Wu, Elizabeth H Margulis, Kelly Jakubowski

{"title":"MUSIFEAST-17: MUsic Stimuli for imagination, familiarity, emotion, and Aesthetic STudies across 17 genres.","authors":"Hazel A van der Walle, Wei Wu, Elizabeth H Margulis, Kelly Jakubowski","doi":"10.3758/s13428-025-02724-0","DOIUrl":"10.3758/s13428-025-02724-0","url":null,"abstract":"Musical stimuli are commonly used in psychological research for investigating a range of emotional, cognitive, and physiological processes. Despite this widespread use, many studies continue to rely on ad hoc music stimulus selection, compromising experimental control, reliability, and comparability across studies. Existing musical stimulus sets tend to be limited in variability in terms of style (e.g. comprising 1-3 genres) and familiarity (e.g. focusing on highly familiar or unfamiliar music). In this paper, we introduce MUSIFEAST-17; a music stimulus set featuring 356 instrumental 30-s clips from commercially released music across 17 genres, aiming to increase the ecological validity of studies tailored for UK and US listeners. Designed to reflect the diversity of everyday Western musical experiences, MUSIFEAST-17 includes art music, popular music, and music composed for media. MUSIFEAST-17 includes normative data from 701 UK and US participants, sampled evenly across adulthood (ages 18-75), on familiarity, enjoyment, emotional expression, perceived contrast, genre recognition, thought types, and contextual associations evoked by each excerpt. Analyses indicated that, while some responses vary by genre, nationality, and age group, MUSIFEAST-17 constitutes a set of stimuli that exhibit stylistic diversity, span familiar to unfamiliar music, and cover a range of emotional expressions. The stimulus set prompted various thought types, including memories and fictional imaginings, and contextual associations such as \"movie\", \"club\", and \"concert\". This resource enables systematic stimuli selection for diverse applications within psychology (e.g. emotion studies, aesthetic experience, music-evoked imaginings) and supports Open Research practices.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 7","pages":"204"},"PeriodicalIF":4.6,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12181142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144336293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparing perceptual judgments in large multimodal models and humans. 比较大型多模态模型和人类的感知判断。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-19 DOI: 10.3758/s13428-025-02728-w

Billy Dickson, Sahaj Singh Maini, Craig Sanders, Robert Nosofsky, Zoran Tiganj

{"title":"Comparing perceptual judgments in large multimodal models and humans.","authors":"Billy Dickson, Sahaj Singh Maini, Craig Sanders, Robert Nosofsky, Zoran Tiganj","doi":"10.3758/s13428-025-02728-w","DOIUrl":"10.3758/s13428-025-02728-w","url":null,"abstract":"Cognitive scientists commonly collect participants' judgments regarding perceptual characteristics of stimuli to develop and evaluate models of attention, memory, learning, and decision-making. For instance, to model human responses in tasks of category learning and item recognition, researchers often collect perceptual judgments of images in order to embed the images in multidimensional feature spaces. This process is time-consuming and costly. Recent advancements in large multimodal models (LMMs) provide a potential alternative because such models can respond to prompts that include both text and images and could potentially replace human participants. To test whether the available LMMs can indeed be useful for this purpose, we evaluated their judgments on a dataset consisting of rock images that has been widely used by cognitive scientists. The dataset includes human perceptual judgments along 10 dimensions considered important for classifying rock images. Among the LMMs that we investigated, GPT-4o exhibited the strongest positive correlation with human responses and demonstrated promising alignment with the mean ratings from human participants, particularly for elementary dimensions such as lightness, chromaticity, shininess, and fine/coarse grain texture. However, its correlations with human ratings were lower for more abstract and rock-specific emergent dimensions such as organization and pegmatitic structure. Although there is room for further improvement, the model already appears to be approaching the level of consensus observed across human groups for the perceptual features examined here. Our study provides a benchmark for evaluating future LMMs on human perceptual judgment data.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 7","pages":"203"},"PeriodicalIF":4.6,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12178973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144324333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smartphone eye-tracking with deep learning: Data quality and field testing. 智能手机眼动追踪与深度学习：数据质量和现场测试。

IF 4.6 2区心理学

Behavior Research Methods Pub Date : 2025-06-18 DOI: 10.3758/s13428-025-02718-y

Gancheng Zhu, Zehao Huang, Xiaoting Duan, Shuai Zhang, Rong Wang, Yongkai Li, Zhiguo Wang

{"title":"Smartphone eye-tracking with deep learning: Data quality and field testing.","authors":"Gancheng Zhu, Zehao Huang, Xiaoting Duan, Shuai Zhang, Rong Wang, Yongkai Li, Zhiguo Wang","doi":"10.3758/s13428-025-02718-y","DOIUrl":"10.3758/s13428-025-02718-y","url":null,"abstract":"Eye-tracking is widely used to measure human attention in research, commercial, and clinical applications. With the rapid advancements in artificial intelligence and mobile computing, deep learning algorithms for computer vision-based eye tracking have become feasible for smartphones. This paper presents a real-time smartphone eye-tracking system built upon a deep neural network trained on a dataset of 7.4 million facial images. The tracking performance of the system was benchmarked against an industrial gold-standard EyeLink eye tracker using a reasonably large sample (N = 32). The benchmark test showed that, while the smartphone eye-tracking system was less precise (0.177° vs. 0.028°), its tracking accuracy was comparable to the EyeLink tracker (1.32° vs. 1.20°). To evaluate whether the smartphone eye-tracking system is sensitive enough for real-world application, a field test involving 98 volunteers assessed depressive symptoms using three simple visual tasks on a smartphone: fixation stability, free-viewing, and smooth pursuit. The results showed that using the smartphone eye-tracking system can achieve an accuracy of 76.67% in predicting depressive symptoms. These results demonstrate that smartphone eye-tracking can deliver quality data and has potential in scientific and clinical applications.","PeriodicalId":8717,"journal":{"name":"Behavior Research Methods","volume":"57 7","pages":"202"},"PeriodicalIF":4.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144324414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0