Pupillometry is sensitive to speech masking during story listening: A commentary on the critical role of modeling temporal trends
An increase in pupil size is an important index of listening effort, for example, when listening to speech masked by noise. Specifically, the pupil dilates as the signal-to-noise ratio decreases. A growing body of work aims to assess listening effort under naturalistic conditions using continuous sp...
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Veröffentlicht in: | Journal of neuroscience methods 2025-01, Vol.413, p.110299, Article 110299 |
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description | An increase in pupil size is an important index of listening effort, for example, when listening to speech masked by noise. Specifically, the pupil dilates as the signal-to-noise ratio decreases. A growing body of work aims to assess listening effort under naturalistic conditions using continuous speech, such as spoken stories. However, a recent study found that pupil size was sensitive to speech masking only when listening to sentences but not under naturalistic conditions when listening to stories. The pupil typically constricts with increasing time on task during an experimental block or session, and it may be necessary to account for this temporal trend in experimental design and data analysis in paradigms using longer, continuous stimuli. In the current work, we re-analyze the previously published pupil data, taking into account a problematic constraint of randomization and time-on-task, and use the data to outline methodological solutions for accounting for temporal trends in physiological data using linear mixed models. The results show that, in contrast to the previous work, pupil size is indeed sensitive to speech masking even during continuous story listening. Furthermore, accounting for the temporal trend allowed modeling the dynamic changes in the speech masking effect on pupil size over time as the continuous story unfolded. After demonstrating the importance of accounting for temporal trends in the analysis of empirical data, we provide simulations, methodological considerations, and user recommendations for the analysis of temporal trends in experimental data using linear mixed models.
•Pupil size is sensitive to speech masking under naturalistic listening conditions.•Confounding temporal trends in pupil size data can be addressed with LMMs.•We modeled changes in effort during story listening including time-on-task.•Recommendations for considering temporal trends in data analysis are summarized. |
doi_str_mv | 10.1016/j.jneumeth.2024.110299 |
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•Pupil size is sensitive to speech masking under naturalistic listening conditions.•Confounding temporal trends in pupil size data can be addressed with LMMs.•We modeled changes in effort during story listening including time-on-task.•Recommendations for considering temporal trends in data analysis are summarized.</description><identifier>ISSN: 0165-0270</identifier><identifier>ISSN: 1872-678X</identifier><identifier>EISSN: 1872-678X</identifier><identifier>DOI: 10.1016/j.jneumeth.2024.110299</identifier><identifier>PMID: 39433179</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Adult ; Female ; Humans ; Male ; Perceptual Masking - physiology ; Pupil - physiology ; Speech Perception - physiology ; Time Factors ; Young Adult</subject><ispartof>Journal of neuroscience methods, 2025-01, Vol.413, p.110299, Article 110299</ispartof><rights>2024 Elsevier B.V.</rights><rights>Copyright © 2024 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c293t-4cff8f5e2bef8c4b7bc9a5eccfbd32fee000b1f709b74fec7612fa858b2463383</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jneumeth.2024.110299$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39433179$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Widmann, Andreas</creatorcontrib><creatorcontrib>Herrmann, Björn</creatorcontrib><creatorcontrib>Scharf, Florian</creatorcontrib><title>Pupillometry is sensitive to speech masking during story listening: A commentary on the critical role of modeling temporal trends</title><title>Journal of neuroscience methods</title><addtitle>J Neurosci Methods</addtitle><description>An increase in pupil size is an important index of listening effort, for example, when listening to speech masked by noise. Specifically, the pupil dilates as the signal-to-noise ratio decreases. A growing body of work aims to assess listening effort under naturalistic conditions using continuous speech, such as spoken stories. However, a recent study found that pupil size was sensitive to speech masking only when listening to sentences but not under naturalistic conditions when listening to stories. The pupil typically constricts with increasing time on task during an experimental block or session, and it may be necessary to account for this temporal trend in experimental design and data analysis in paradigms using longer, continuous stimuli. In the current work, we re-analyze the previously published pupil data, taking into account a problematic constraint of randomization and time-on-task, and use the data to outline methodological solutions for accounting for temporal trends in physiological data using linear mixed models. The results show that, in contrast to the previous work, pupil size is indeed sensitive to speech masking even during continuous story listening. Furthermore, accounting for the temporal trend allowed modeling the dynamic changes in the speech masking effect on pupil size over time as the continuous story unfolded. After demonstrating the importance of accounting for temporal trends in the analysis of empirical data, we provide simulations, methodological considerations, and user recommendations for the analysis of temporal trends in experimental data using linear mixed models.
•Pupil size is sensitive to speech masking under naturalistic listening conditions.•Confounding temporal trends in pupil size data can be addressed with LMMs.•We modeled changes in effort during story listening including time-on-task.•Recommendations for considering temporal trends in data analysis are summarized.</description><subject>Adult</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Perceptual Masking - physiology</subject><subject>Pupil - physiology</subject><subject>Speech Perception - physiology</subject><subject>Time Factors</subject><subject>Young Adult</subject><issn>0165-0270</issn><issn>1872-678X</issn><issn>1872-678X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkEtP3DAUha2qqExp_wLykk2mfmTiuCsQ4lEJqV2A1J2VONcdT_1IbQeJJf8cjwa6RV5c2f7OuToHoVNK1pTQ7ttuvQuweCjbNSOsXVNKmJQf0Ir2gjWd6H9_RKsKbhrCBDlGn3PeEUJaSbpP6JjLlnMq5Ao9_1pm61ysTukJ24wzhGyLfQRcIs4zgN5iP-S_NvzB05L2I5dYWWdzgVDv3_EF1tF7CGWo7zHgsgWsU3XRg8MpOsDRYB8ncHt5AT_HVH9KgjDlL-jIDC7D19d5gh6ur-4vb5u7nzc_Li_uGs0kL02rjenNBtgIptftKEYthw1obcaJMwNQ043UCCJH0RrQoqPMDP2mH1nbcd7zE3R28J1T_LdALsrbrMG5IUBcsuKUynpEyyraHVCdYs4JjJqT9TWcokTt61c79Va_2tevDvVX4enrjmX0MP2XvfVdgfMDADXpo4WksrYQNEw2gS5qiva9HS9k054x</recordid><startdate>202501</startdate><enddate>202501</enddate><creator>Widmann, Andreas</creator><creator>Herrmann, Björn</creator><creator>Scharf, Florian</creator><general>Elsevier B.V</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></search><sort><creationdate>202501</creationdate><title>Pupillometry is sensitive to speech masking during story listening: A commentary on the critical role of modeling temporal trends</title><author>Widmann, Andreas ; Herrmann, Björn ; Scharf, Florian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-4cff8f5e2bef8c4b7bc9a5eccfbd32fee000b1f709b74fec7612fa858b2463383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Adult</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Perceptual Masking - physiology</topic><topic>Pupil - physiology</topic><topic>Speech Perception - physiology</topic><topic>Time Factors</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Widmann, Andreas</creatorcontrib><creatorcontrib>Herrmann, Björn</creatorcontrib><creatorcontrib>Scharf, Florian</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><jtitle>Journal of neuroscience methods</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Widmann, Andreas</au><au>Herrmann, Björn</au><au>Scharf, Florian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pupillometry is sensitive to speech masking during story listening: A commentary on the critical role of modeling temporal trends</atitle><jtitle>Journal of neuroscience methods</jtitle><addtitle>J Neurosci Methods</addtitle><date>2025-01</date><risdate>2025</risdate><volume>413</volume><spage>110299</spage><pages>110299-</pages><artnum>110299</artnum><issn>0165-0270</issn><issn>1872-678X</issn><eissn>1872-678X</eissn><abstract>An increase in pupil size is an important index of listening effort, for example, when listening to speech masked by noise. Specifically, the pupil dilates as the signal-to-noise ratio decreases. A growing body of work aims to assess listening effort under naturalistic conditions using continuous speech, such as spoken stories. However, a recent study found that pupil size was sensitive to speech masking only when listening to sentences but not under naturalistic conditions when listening to stories. The pupil typically constricts with increasing time on task during an experimental block or session, and it may be necessary to account for this temporal trend in experimental design and data analysis in paradigms using longer, continuous stimuli. In the current work, we re-analyze the previously published pupil data, taking into account a problematic constraint of randomization and time-on-task, and use the data to outline methodological solutions for accounting for temporal trends in physiological data using linear mixed models. The results show that, in contrast to the previous work, pupil size is indeed sensitive to speech masking even during continuous story listening. Furthermore, accounting for the temporal trend allowed modeling the dynamic changes in the speech masking effect on pupil size over time as the continuous story unfolded. After demonstrating the importance of accounting for temporal trends in the analysis of empirical data, we provide simulations, methodological considerations, and user recommendations for the analysis of temporal trends in experimental data using linear mixed models.
•Pupil size is sensitive to speech masking under naturalistic listening conditions.•Confounding temporal trends in pupil size data can be addressed with LMMs.•We modeled changes in effort during story listening including time-on-task.•Recommendations for considering temporal trends in data analysis are summarized.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>39433179</pmid><doi>10.1016/j.jneumeth.2024.110299</doi><oa>free_for_read</oa></addata></record> |
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subjects | Adult Female Humans Male Perceptual Masking - physiology Pupil - physiology Speech Perception - physiology Time Factors Young Adult |
title | Pupillometry is sensitive to speech masking during story listening: A commentary on the critical role of modeling temporal trends |
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