[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-156894-105":3,"detail-sidebar-cat-0-en-105":85,"doc-detail-156894-en":135},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":78,"head_meta":80,"extra_data":82,"updated_unix":84},105,"en","dissociation-between-recognition-and-detection-advantage-for-facial-expressions-meta-analysis","Dissociation Between Recognition and Detection Advantage for Facial Expressions - Meta-Analysis","","The meta-analysis resolves a discrepancy between facial-expression advantages in recognition versus visual detection for positive (happy) and negative emotions. Using effect sizes derived from 34 recognition studies (3,561 participants) and 37 visual search studies (2,455 participants), random-effects models estimated population-level effects for recognition accuracy, recognition speed, and visual-search speed. Happy faces showed consistent recognition advantages across stimulus types. In contrast, detection advantages depended on stimulus features: happy detection favored photographic faces, while angry advantages appeared for schematic and “smiley” faces. The findings suggest category/affective processing supports recognition advantages, whereas visual-feature-driven search underlies detection patterns.",{"@graph":14,"@context":77},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/dissociation-between-recognition-and-detection-advantage-for-facial-expressions-meta-analysis/156894/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/dissociation-between-recognition-and-detection-advantage-for-facial-expressions-meta-analysis/156894.png","ImageObject",300,407,{"name":42,"@type":43},"Bill Black","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-30","2026-08-29",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",11,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69,73],{"name":60,"@type":61,"acceptedAnswer":62},"How did the study address the mismatch between recognition and detection advantages?","Question",{"text":63,"@type":64},"It used meta-analytic techniques to compare positive (happy) versus negative facial-expression advantages across recognition tasks and visual search tasks, estimating effect sizes with random-effects models.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What pattern did the results show for recognition tasks?",{"text":68,"@type":64},"Across all stimulus types, happy expressions showed advantages in both recognition accuracy and recognition speed.",{"name":70,"@type":61,"acceptedAnswer":71},"How did detection advantages differ in visual search tasks?",{"text":72,"@type":64},"Moderator analysis showed happy-face detection advantage was limited to photographic faces, while clear angry-face advantages emerged for schematic and “smiley” faces.",{"name":74,"@type":61,"acceptedAnswer":75},"What do the findings suggest about the mechanism behind detection vs recognition?",{"text":76,"@type":64},"Recognition advantages for happy faces reflect genuine category and valence processing, whereas detection advantages depend on visual stimulus features and may not require categorical or affective processing.","https://schema.org",{"og:url":32,"og:type":79,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":81,"canonical":32},"index,follow",{"doc_id":83,"site_id":7},156894,1787968547,{"code":4,"msg":86,"data":87},"success",[88,92,96,100,105,110,115,119,124,127,131],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},"Exam",70,"exam",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},5,"Comic",60,"comic",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},6,"Technology",50,"technology",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":112,"show_sort_weight":113,"slug":114},7,"Healthcare",40,"healthcare",{"id":116,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":117,"slug":118},8,30,"research-report",{"id":120,"doc_module":4,"doc_module_name":25,"category_name":121,"show_sort_weight":122,"slug":123},9,"Religion & Spirituality",20,"religion-spirituality",{"id":122,"doc_module":4,"doc_module_name":25,"category_name":125,"show_sort_weight":122,"slug":126},"World Cup","world-cup",{"id":128,"doc_module":4,"doc_module_name":25,"category_name":129,"show_sort_weight":128,"slug":130},10,"Lifestyle","lifestyle",{"id":132,"doc_module":4,"doc_module_name":25,"category_name":133,"show_sort_weight":101,"slug":134},19,"General","general",{"code":4,"msg":86,"data":136},{"doc_id":83,"user_id":137,"nickname":42,"user_avatar":138,"doc_module":4,"category_id":116,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":139,"file_id":140,"file_url":141,"file_type":142,"file_size":143,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":144,"language":145,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":146,"faqs":147,"seo_title":148,"seo_description":12,"update_tm":84,"read_time":149,"preview_page_count":4},24189269381491,"https://ap-avatar.wpscdn.com/avatar/160000cf11732dd8392?x-image-process=image/resize,m_fixed,w_180,h_180&k=1788146458752108895","This document is copyrighted by the American Psychological Association or one of its allied publishers . This article is intended solely for the personal use of the individual user and is not to be disseminated broadly .  \nEmotion © 2015 American Psychological Association  \n1528-3542/15/$12.00 [http://dx.doi.org/10.1037/emo0000042](http://dx.doi.org/10.1037/emo0000042)  \nDissociation Between Recognition and Detection Advantage for Facial  \nExpressions: A Meta-Analysis  \nLauri Nummenmaa  \nAalto University and University of Turku  \nManuel G. Calvo University of La Laguna  \nHappy facial expressions are recognized faster and more accurately than other expressions in categorization tasks, whereas detection in visual search tasks is widely believed to be faster for angry than happy faces. We used meta-analytic techniques for resolving this categorization versus detection advantage discrepancy for positive versus negative facial expressions. Effect sizes were computed on the basis of the r statistic for a total of 34 recognition studies with 3,561 participants and 37 visual search studies with 2,455 participants, yielding a total of 41 effect sizes for recognition accuracy, 25 for recognition speed, and 125 for visual search speed. Random effects meta-analysis was conducted to estimate effect sizes at population level. For recognition tasks, an advantage in recognition accuracy and speed for happy expressions was found for all stimulus types. In contrast, for visual search tasks, moderator analysis revealed that a happy face detection advantage was restricted to photographic faces, whereas a clear angry face advantage was found for schematic and “smiley” faces. Robust detection advantage for nonhappy faces was observed even when stimulus emotionality was distorted by inversion or rearrangement of the facial features, suggesting that visual features primarily drive the search. We conclude that the recognition advantage for happy faces is a genuine phenomenon related to processing of facial expression category and affective valence. In contrast, detection advantages toward either happy (photographic stimuli) or nonhappy (schematic) faces is contingent on visual stimulus features rather than facial expression, and may not involve categorical or affective processing.  \nKeywords: facial expression, emotion, recognition, visual search, meta-analysis  \nSupplemental materials: [http://dx.doi.org/10.1037/emo0000042.supp](http://dx.doi.org/10.1037/emo0000042.supp)  \nHumans communicate their emotions using facial signals, some of which are thought to be basic and culturally more or less invariant (Ekman, 1992) . These signals convey messages regarding the relationship between the expresser and their environment. Happy smiles can be perceived as invitations for engaging in cooperation and pleasurable interaction, whereas angry snarls provide warning signals of possible psychological or physical threat (Scherer & Wallbott, 1994) . Neurocognitive models of emotional processing have postulated that emotional signals conveyed by facial expressions are processed by specialized brain circuits, and that processing of emotional over neutral information would be facilitated at both detection and recognition stages (Öhman & Mineka, 2001; Vuilleumier, 2005). This ensures that information conveyed by emotional signals is brought  \nLauri Nummenmaa, Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, Department of Psychology, University of Turku; Manuel G. Calvo, Department of Cognitive Psychology, University of La Laguna.  \nThis research was supported by the aivoAALTO project of the Aalto University, Academy of Finland Grant \\#251125 to LN and ERC Starting Grant \\#313000 to LN.  \nCorrespondence concerning this article should be addressed to Prof. Lauri Nummenmaa, Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, FI-00076 AALTO, Espoo, Finland. E-mail: [lauri.nummenmaa@aalto.fi]","cbCairisU8VIiFcb","https://ap.wps.com/l/cbCairisU8VIiFcb","pdf",493303,14,"English","# Dissociation between recognition and detection advantage\n## Recognition advantage for happy facial expressions\n## Detection advantage in visual search tasks\n## Moderator analysis by stimulus type\n## Conclusions and theoretical implications","[{\"question\":\"How did the study address the mismatch between recognition and detection advantages?\",\"answer\":\"It used meta-analytic techniques to compare positive (happy) versus negative facial-expression advantages across recognition tasks and visual search tasks, estimating effect sizes with random-effects models.\"},{\"question\":\"What pattern did the results show for recognition tasks?\",\"answer\":\"Across all stimulus types, happy expressions showed advantages in both recognition accuracy and recognition speed.\"},{\"question\":\"How did detection advantages differ in visual search tasks?\",\"answer\":\"Moderator analysis showed happy-face detection advantage was limited to photographic faces, while clear angry-face advantages emerged for schematic and “smiley” faces.\"},{\"question\":\"What do the findings suggest about the mechanism behind detection vs recognition?\",\"answer\":\"Recognition advantages for happy faces reflect genuine category and valence processing, whereas detection advantages depend on visual stimulus features and may not require categorical or affective processing.\"}]","Dissociation Between Recognition and Detection Advantage for Facial Expressions - Meta-Analysis | PDF",35]