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Decomposing the Response Time in Amblyopia: A Drift Diffusion Model Analysis
Amblyopes are known to have delayed response times (RT) in various visual tasks. We aim to investigate whether any factor other than the sensory deficit contributes to the delayed RT in amblyopia. Fifteen amblyopic (26.0 ± 4.50 years) and 15 normal (25.6 ± 2.90 years) participants took part in this...
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Published in: | Investigative ophthalmology & visual science 2023-06, Vol.64 (7), p.25-25 |
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description | Amblyopes are known to have delayed response times (RT) in various visual tasks. We aim to investigate whether any factor other than the sensory deficit contributes to the delayed RT in amblyopia.
Fifteen amblyopic (26.0 ± 4.50 years) and 15 normal (25.6 ± 2.90 years) participants took part in this study. The responses and RTs in an orientation identification task were collected for each participant with stimulus contrast adjusted to the multiples of individual's threshold. A drift diffusion model was used to fit to the response and RT data and to estimate the RT components.
There was a significant difference in the RT between the amblyopic and normal groups (F(1, 28) = 6.75, P = 0.015) but no difference in the accuracy (F(1, 28) = 0.028, P = 0.868). The drift rate function in the amblyopic eye had a larger threshold (P = 0.001) and shallower slope (P = 0.006) than that of the fellow eye. The amblyopic group has a longer non-decision time than the normal group (F(1, 28) = 8.02, P = 0.008). The drift rate threshold correlated with the contrast sensitivity (P = 1.71 × 10-18) but the non-decision time did not (P = 0.393).
Both sensory and post-sensory factors contributed to the delayed RT in amblyopia. The effect of the sensory loss in V1 on RT can be compensated by increasing stimulus contrast, and the post-sensory delay provides evidence for higher-level deficits in amblyopia. |
doi_str_mv | 10.1167/iovs.64.7.25 |
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Fifteen amblyopic (26.0 ± 4.50 years) and 15 normal (25.6 ± 2.90 years) participants took part in this study. The responses and RTs in an orientation identification task were collected for each participant with stimulus contrast adjusted to the multiples of individual's threshold. A drift diffusion model was used to fit to the response and RT data and to estimate the RT components.
There was a significant difference in the RT between the amblyopic and normal groups (F(1, 28) = 6.75, P = 0.015) but no difference in the accuracy (F(1, 28) = 0.028, P = 0.868). The drift rate function in the amblyopic eye had a larger threshold (P = 0.001) and shallower slope (P = 0.006) than that of the fellow eye. The amblyopic group has a longer non-decision time than the normal group (F(1, 28) = 8.02, P = 0.008). The drift rate threshold correlated with the contrast sensitivity (P = 1.71 × 10-18) but the non-decision time did not (P = 0.393).
Both sensory and post-sensory factors contributed to the delayed RT in amblyopia. The effect of the sensory loss in V1 on RT can be compensated by increasing stimulus contrast, and the post-sensory delay provides evidence for higher-level deficits in amblyopia.</description><identifier>ISSN: 1552-5783</identifier><identifier>ISSN: 0146-0404</identifier><identifier>EISSN: 1552-5783</identifier><identifier>DOI: 10.1167/iovs.64.7.25</identifier><identifier>PMID: 37318443</identifier><language>eng</language><publisher>United States: The Association for Research in Vision and Ophthalmology</publisher><subject>Amblyopia ; Contrast Sensitivity ; Humans ; Reaction Time ; Visual Psychophysics and Physiological Optics</subject><ispartof>Investigative ophthalmology & visual science, 2023-06, Vol.64 (7), p.25-25</ispartof><rights>Copyright 2023 The Authors 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c385t-558381f95a326549ed7092c235f25f9e4be7e6d41ad8777ecba5d07f5cf292253</citedby><cites>FETCH-LOGICAL-c385t-558381f95a326549ed7092c235f25f9e4be7e6d41ad8777ecba5d07f5cf292253</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278554/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278554/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37318443$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ruan, Xiaowei</creatorcontrib><creatorcontrib>Lin, Liang</creatorcontrib><creatorcontrib>Ying, Xiaoxiao</creatorcontrib><creatorcontrib>Zhang, Hanyi</creatorcontrib><creatorcontrib>Yuan, Junli</creatorcontrib><creatorcontrib>Li, Cheng</creatorcontrib><creatorcontrib>Yang, Yan</creatorcontrib><creatorcontrib>Zhu, Jinli</creatorcontrib><creatorcontrib>Chen, Ruyin</creatorcontrib><creatorcontrib>Hou, Fang</creatorcontrib><title>Decomposing the Response Time in Amblyopia: A Drift Diffusion Model Analysis</title><title>Investigative ophthalmology & visual science</title><addtitle>Invest Ophthalmol Vis Sci</addtitle><description>Amblyopes are known to have delayed response times (RT) in various visual tasks. We aim to investigate whether any factor other than the sensory deficit contributes to the delayed RT in amblyopia.
Fifteen amblyopic (26.0 ± 4.50 years) and 15 normal (25.6 ± 2.90 years) participants took part in this study. The responses and RTs in an orientation identification task were collected for each participant with stimulus contrast adjusted to the multiples of individual's threshold. A drift diffusion model was used to fit to the response and RT data and to estimate the RT components.
There was a significant difference in the RT between the amblyopic and normal groups (F(1, 28) = 6.75, P = 0.015) but no difference in the accuracy (F(1, 28) = 0.028, P = 0.868). The drift rate function in the amblyopic eye had a larger threshold (P = 0.001) and shallower slope (P = 0.006) than that of the fellow eye. The amblyopic group has a longer non-decision time than the normal group (F(1, 28) = 8.02, P = 0.008). The drift rate threshold correlated with the contrast sensitivity (P = 1.71 × 10-18) but the non-decision time did not (P = 0.393).
Both sensory and post-sensory factors contributed to the delayed RT in amblyopia. The effect of the sensory loss in V1 on RT can be compensated by increasing stimulus contrast, and the post-sensory delay provides evidence for higher-level deficits in amblyopia.</description><subject>Amblyopia</subject><subject>Contrast Sensitivity</subject><subject>Humans</subject><subject>Reaction Time</subject><subject>Visual Psychophysics and Physiological Optics</subject><issn>1552-5783</issn><issn>0146-0404</issn><issn>1552-5783</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpVkc1Lw0AQxRdRrFZvnmWPHkzNzmaziRcprV9QEaSel00y264k2ZhNC_3vbW0t9TQD8-PN4z1Crlg4YCyWd9Yt_SCOBnIA4oicMSEgEDLhxwd7j5x7_xWGwBiEp6THJWdJFPEzMhlj7qrGeVvPaDdH-oG-cbVHOrUVUlvTYZWVK9dYfU-HdNxa09GxNWbhravpmyuwpMNalytv_QU5Mbr0eLmbffL59DgdvQST9-fX0XAS5DwRXSBEwhNmUqE5xCJKsZBhCjlwYUCYFKMMJcZFxHSRSCkxz7QoQmlEbiAFELxPHra6zSKrsMix7lpdqqa1lW5Xymmr_l9qO1czt1QsBJkIEa0VbnYKrfteoO9UZX2OZalrdAuvIIEYWBoDrNHbLZq3zvsWzf4PC9WmAbVpQMWRkurX2_Whtz38Fzn_AbkPgog</recordid><startdate>20230601</startdate><enddate>20230601</enddate><creator>Ruan, Xiaowei</creator><creator>Lin, Liang</creator><creator>Ying, Xiaoxiao</creator><creator>Zhang, Hanyi</creator><creator>Yuan, Junli</creator><creator>Li, Cheng</creator><creator>Yang, Yan</creator><creator>Zhu, Jinli</creator><creator>Chen, Ruyin</creator><creator>Hou, Fang</creator><general>The Association for Research in Vision and Ophthalmology</general><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>7X8</scope><scope>5PM</scope></search><sort><creationdate>20230601</creationdate><title>Decomposing the Response Time in Amblyopia: A Drift Diffusion Model Analysis</title><author>Ruan, Xiaowei ; Lin, Liang ; Ying, Xiaoxiao ; Zhang, Hanyi ; Yuan, Junli ; Li, Cheng ; Yang, Yan ; Zhu, Jinli ; Chen, Ruyin ; Hou, Fang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c385t-558381f95a326549ed7092c235f25f9e4be7e6d41ad8777ecba5d07f5cf292253</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Amblyopia</topic><topic>Contrast Sensitivity</topic><topic>Humans</topic><topic>Reaction Time</topic><topic>Visual Psychophysics and Physiological Optics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ruan, Xiaowei</creatorcontrib><creatorcontrib>Lin, Liang</creatorcontrib><creatorcontrib>Ying, Xiaoxiao</creatorcontrib><creatorcontrib>Zhang, Hanyi</creatorcontrib><creatorcontrib>Yuan, Junli</creatorcontrib><creatorcontrib>Li, Cheng</creatorcontrib><creatorcontrib>Yang, Yan</creatorcontrib><creatorcontrib>Zhu, Jinli</creatorcontrib><creatorcontrib>Chen, Ruyin</creatorcontrib><creatorcontrib>Hou, Fang</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Investigative ophthalmology & visual science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ruan, Xiaowei</au><au>Lin, Liang</au><au>Ying, Xiaoxiao</au><au>Zhang, Hanyi</au><au>Yuan, Junli</au><au>Li, Cheng</au><au>Yang, Yan</au><au>Zhu, Jinli</au><au>Chen, Ruyin</au><au>Hou, Fang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decomposing the Response Time in Amblyopia: A Drift Diffusion Model Analysis</atitle><jtitle>Investigative ophthalmology & visual science</jtitle><addtitle>Invest Ophthalmol Vis Sci</addtitle><date>2023-06-01</date><risdate>2023</risdate><volume>64</volume><issue>7</issue><spage>25</spage><epage>25</epage><pages>25-25</pages><issn>1552-5783</issn><issn>0146-0404</issn><eissn>1552-5783</eissn><abstract>Amblyopes are known to have delayed response times (RT) in various visual tasks. We aim to investigate whether any factor other than the sensory deficit contributes to the delayed RT in amblyopia.
Fifteen amblyopic (26.0 ± 4.50 years) and 15 normal (25.6 ± 2.90 years) participants took part in this study. The responses and RTs in an orientation identification task were collected for each participant with stimulus contrast adjusted to the multiples of individual's threshold. A drift diffusion model was used to fit to the response and RT data and to estimate the RT components.
There was a significant difference in the RT between the amblyopic and normal groups (F(1, 28) = 6.75, P = 0.015) but no difference in the accuracy (F(1, 28) = 0.028, P = 0.868). The drift rate function in the amblyopic eye had a larger threshold (P = 0.001) and shallower slope (P = 0.006) than that of the fellow eye. The amblyopic group has a longer non-decision time than the normal group (F(1, 28) = 8.02, P = 0.008). The drift rate threshold correlated with the contrast sensitivity (P = 1.71 × 10-18) but the non-decision time did not (P = 0.393).
Both sensory and post-sensory factors contributed to the delayed RT in amblyopia. The effect of the sensory loss in V1 on RT can be compensated by increasing stimulus contrast, and the post-sensory delay provides evidence for higher-level deficits in amblyopia.</abstract><cop>United States</cop><pub>The Association for Research in Vision and Ophthalmology</pub><pmid>37318443</pmid><doi>10.1167/iovs.64.7.25</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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title | Decomposing the Response Time in Amblyopia: A Drift Diffusion Model Analysis |
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