Coherence in the Visual Imagination
An incoherent visualization is when aspects of different senses of a word (e.g., the biological “mouse” vs. the computer “mouse”) are present in the same visualization (e.g., a visualization of a biological mouse in the same image with a computer tower). We describe and implement a new model of crea...
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Veröffentlicht in: | Cognitive science 2018-04, Vol.42 (3), p.885-917 |
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creator | Vertolli, Michael O. Kelly, Matthew A. Davies, Jim |
description | An incoherent visualization is when aspects of different senses of a word (e.g., the biological “mouse” vs. the computer “mouse”) are present in the same visualization (e.g., a visualization of a biological mouse in the same image with a computer tower). We describe and implement a new model of creating contextual coherence in the visual imagination called Coherencer, based on the SOILIE model of imagination. We show that Coherencer is able to generate scene descriptions that are more coherent than SOILIE's original approach as well as a parallel connectionist algorithm that is considered competitive in the literature on general coherence. We also show that co‐occurrence probabilities are a better association representation than holographic vectors and that better models of coherence improve the resulting output independent of the association type that is used. Theoretically, we show that Coherencer is consistent with other models of cognitive generation. In particular, Coherencer is a similar, but more cognitively plausible model than the C3 model of concept combination created by Costello and Keane (2000). We show that Coherencer is also consistent with both the modal schematic indices of perceptual symbol systems theory (Barsalou, 1999) and the amodal contextual constraints of Thagard's (2002) theory of coherence. Finally, we describe how Coherencer is consistent with contemporary research on the hippocampus, and we show evidence that the process of making a visualization coherent is serial. |
doi_str_mv | 10.1111/cogs.12569 |
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We show that Coherencer is also consistent with both the modal schematic indices of perceptual symbol systems theory (Barsalou, 1999) and the amodal contextual constraints of Thagard's (2002) theory of coherence. 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We describe and implement a new model of creating contextual coherence in the visual imagination called Coherencer, based on the SOILIE model of imagination. We show that Coherencer is able to generate scene descriptions that are more coherent than SOILIE's original approach as well as a parallel connectionist algorithm that is considered competitive in the literature on general coherence. We also show that co‐occurrence probabilities are a better association representation than holographic vectors and that better models of coherence improve the resulting output independent of the association type that is used. Theoretically, we show that Coherencer is consistent with other models of cognitive generation. In particular, Coherencer is a similar, but more cognitively plausible model than the C3 model of concept combination created by Costello and Keane (2000). We show that Coherencer is also consistent with both the modal schematic indices of perceptual symbol systems theory (Barsalou, 1999) and the amodal contextual constraints of Thagard's (2002) theory of coherence. Finally, we describe how Coherencer is consistent with contemporary research on the hippocampus, and we show evidence that the process of making a visualization coherent is serial.</description><subject>Animal models</subject><subject>Association (Psychology)</subject><subject>Cognitive ability</subject><subject>Cognitive modeling</subject><subject>Coherence</subject><subject>Concept Formation</subject><subject>Hippocampus</subject><subject>Humans</subject><subject>Imagination</subject><subject>Schemata (Cognition)</subject><subject>Serial Learning</subject><subject>System theory</subject><subject>Visual Perception</subject><subject>Visualization</subject><issn>0364-0213</issn><issn>1551-6709</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kL1PwzAQxS0EoqWwsIMqdUFIKXbs2PGIolKKKnXgY7Uc59KmykexG6H-97ikdGDglhveT-_dPYSuCR4TPw-mWboxCSMuT1CfRBEJuMDyFPUx5SzAIaE9dOHcGmPMOZXnqBdKEjIhRB-NkmYFFmoDw6Ieblcw_Chcq8vhrNLLotbboqkv0VmuSwdXhz1A70-Tt-Q5mC-ms-RxHhgqmAwkBcONSYlkOckE4VzriKSZziFNWZZlMtMYgzYmSg2FnMeaapbGGQeOwV85QHed78Y2ny24raoKZ6AsdQ1N6xSRnIYiorHw6OgPum5aW_vrVOi_piGLGfPUfUcZ2zhnIVcbW1Ta7hTBal-d2lenfqrz8O3Bsk0ryI7ob1ceuOkAsIU5ypMXQkRMZex10ulfRQm7f6JUspi-dqHfOdyBeg</recordid><startdate>201804</startdate><enddate>201804</enddate><creator>Vertolli, Michael O.</creator><creator>Kelly, Matthew A.</creator><creator>Davies, Jim</creator><general>Wiley-Blackwell</general><general>Wiley Subscription Services, Inc</general><scope>7SW</scope><scope>BJH</scope><scope>BNH</scope><scope>BNI</scope><scope>BNJ</scope><scope>BNO</scope><scope>ERI</scope><scope>PET</scope><scope>REK</scope><scope>WWN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>7X8</scope></search><sort><creationdate>201804</creationdate><title>Coherence in the Visual Imagination</title><author>Vertolli, Michael O. ; Kelly, Matthew A. ; Davies, Jim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3749-93ec6ccb194f1d7166aa51bdafebb4ddd9da00eacc5bc3ef68a3a4b8d6e60e213</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Animal models</topic><topic>Association (Psychology)</topic><topic>Cognitive ability</topic><topic>Cognitive modeling</topic><topic>Coherence</topic><topic>Concept Formation</topic><topic>Hippocampus</topic><topic>Humans</topic><topic>Imagination</topic><topic>Schemata (Cognition)</topic><topic>Serial Learning</topic><topic>System theory</topic><topic>Visual Perception</topic><topic>Visualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vertolli, Michael O.</creatorcontrib><creatorcontrib>Kelly, Matthew A.</creatorcontrib><creatorcontrib>Davies, Jim</creatorcontrib><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Cognitive science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vertolli, Michael O.</au><au>Kelly, Matthew A.</au><au>Davies, Jim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1178398</ericid><atitle>Coherence in the Visual Imagination</atitle><jtitle>Cognitive science</jtitle><addtitle>Cogn Sci</addtitle><date>2018-04</date><risdate>2018</risdate><volume>42</volume><issue>3</issue><spage>885</spage><epage>917</epage><pages>885-917</pages><issn>0364-0213</issn><eissn>1551-6709</eissn><abstract>An incoherent visualization is when aspects of different senses of a word (e.g., the biological “mouse” vs. the computer “mouse”) are present in the same visualization (e.g., a visualization of a biological mouse in the same image with a computer tower). We describe and implement a new model of creating contextual coherence in the visual imagination called Coherencer, based on the SOILIE model of imagination. We show that Coherencer is able to generate scene descriptions that are more coherent than SOILIE's original approach as well as a parallel connectionist algorithm that is considered competitive in the literature on general coherence. We also show that co‐occurrence probabilities are a better association representation than holographic vectors and that better models of coherence improve the resulting output independent of the association type that is used. Theoretically, we show that Coherencer is consistent with other models of cognitive generation. In particular, Coherencer is a similar, but more cognitively plausible model than the C3 model of concept combination created by Costello and Keane (2000). We show that Coherencer is also consistent with both the modal schematic indices of perceptual symbol systems theory (Barsalou, 1999) and the amodal contextual constraints of Thagard's (2002) theory of coherence. Finally, we describe how Coherencer is consistent with contemporary research on the hippocampus, and we show evidence that the process of making a visualization coherent is serial.</abstract><cop>United States</cop><pub>Wiley-Blackwell</pub><pmid>29124777</pmid><doi>10.1111/cogs.12569</doi><tpages>33</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Animal models Association (Psychology) Cognitive ability Cognitive modeling Coherence Concept Formation Hippocampus Humans Imagination Schemata (Cognition) Serial Learning System theory Visual Perception Visualization |
title | Coherence in the Visual Imagination |
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