Deviance detection in physiologically identified cell types in the rat auditory cortex
Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, whi...
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Veröffentlicht in: | Hearing research 2021-01, Vol.399, p.107997-107997, Article 107997 |
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description | Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, which evokes an event-related potential known as mismatch negativity (MMN). The same stimulation paradigms are used in animal studies that aim to elucidate the neuronal mechanisms underlying deviance detection. In order to understand the circuitry responsible for deviance detection in the auditory cortex (AC), it is necessary to determine the properties of excitatory and inhibitory neurons separately. Measuring the spike widths of neurons recorded extracellularly from the anaesthetized rat AC, we classified them as fast spiking or regular spiking units. These two neuron types are generally considered as putative inhibitory or excitatory, respectively. In response to an oddball paradigm, we found that both types of units showed similar amounts of deviance detection overall. When considering each AC field separately, we found that only in A1 fast spiking neurons showed higher deviance detection levels than regular spiking neurons, while in the rest of the fields there was no such distinction. Interpreting these responses in the context of the predictive coding framework, we found that the responses of both types of units reflect mainly prediction error signaling (i.e., genuine deviance detection) rather than repetition suppression.
•Single units from the auditory cortex were classified as excitatory or inhibitory.•Both inhibitory and excitatory units showed deviance detection.•Inhibitory units showed larger deviance detection than excitatory units in A1 only.•The responses indicated prediction error rather than repetition suppression.•Both types of neurons may contribute to the deviance detection cortical circuits. |
doi_str_mv | 10.1016/j.heares.2020.107997 |
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•Single units from the auditory cortex were classified as excitatory or inhibitory.•Both inhibitory and excitatory units showed deviance detection.•Inhibitory units showed larger deviance detection than excitatory units in A1 only.•The responses indicated prediction error rather than repetition suppression.•Both types of neurons may contribute to the deviance detection cortical circuits.</description><identifier>ISSN: 0378-5955</identifier><identifier>EISSN: 1878-5891</identifier><identifier>DOI: 10.1016/j.heares.2020.107997</identifier><identifier>PMID: 32482383</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Acoustic Stimulation ; Animals ; Auditory Cortex ; Electroencephalography ; Evoked Potentials, Auditory ; Fast spiking neurons ; Inhibitory ; Predictive coding ; Pyramidal ; Rats ; Reaction Time ; Regular spiking neurons ; Spike width analysis ; Stimulus-specific adaptation</subject><ispartof>Hearing research, 2021-01, Vol.399, p.107997-107997, Article 107997</ispartof><rights>2020 Elsevier B.V.</rights><rights>Copyright © 2020 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-8bbe8c509d7334751cdd2def031f002ed669363c091f7aaf936d288a60203bb33</citedby><cites>FETCH-LOGICAL-c362t-8bbe8c509d7334751cdd2def031f002ed669363c091f7aaf936d288a60203bb33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.heares.2020.107997$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32482383$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pérez-González, David</creatorcontrib><creatorcontrib>Parras, Gloria G.</creatorcontrib><creatorcontrib>Morado-Díaz, Camilo J.</creatorcontrib><creatorcontrib>Aedo-Sánchez, Cristian</creatorcontrib><creatorcontrib>Carbajal, Guillermo V.</creatorcontrib><creatorcontrib>Malmierca, Manuel S.</creatorcontrib><title>Deviance detection in physiologically identified cell types in the rat auditory cortex</title><title>Hearing research</title><addtitle>Hear Res</addtitle><description>Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, which evokes an event-related potential known as mismatch negativity (MMN). The same stimulation paradigms are used in animal studies that aim to elucidate the neuronal mechanisms underlying deviance detection. In order to understand the circuitry responsible for deviance detection in the auditory cortex (AC), it is necessary to determine the properties of excitatory and inhibitory neurons separately. Measuring the spike widths of neurons recorded extracellularly from the anaesthetized rat AC, we classified them as fast spiking or regular spiking units. These two neuron types are generally considered as putative inhibitory or excitatory, respectively. In response to an oddball paradigm, we found that both types of units showed similar amounts of deviance detection overall. When considering each AC field separately, we found that only in A1 fast spiking neurons showed higher deviance detection levels than regular spiking neurons, while in the rest of the fields there was no such distinction. Interpreting these responses in the context of the predictive coding framework, we found that the responses of both types of units reflect mainly prediction error signaling (i.e., genuine deviance detection) rather than repetition suppression.
•Single units from the auditory cortex were classified as excitatory or inhibitory.•Both inhibitory and excitatory units showed deviance detection.•Inhibitory units showed larger deviance detection than excitatory units in A1 only.•The responses indicated prediction error rather than repetition suppression.•Both types of neurons may contribute to the deviance detection cortical circuits.</description><subject>Acoustic Stimulation</subject><subject>Animals</subject><subject>Auditory Cortex</subject><subject>Electroencephalography</subject><subject>Evoked Potentials, Auditory</subject><subject>Fast spiking neurons</subject><subject>Inhibitory</subject><subject>Predictive coding</subject><subject>Pyramidal</subject><subject>Rats</subject><subject>Reaction Time</subject><subject>Regular spiking neurons</subject><subject>Spike width analysis</subject><subject>Stimulus-specific adaptation</subject><issn>0378-5955</issn><issn>1878-5891</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEtPwzAMgCMEYmPwDxDKkctGHn2kFyQ0ntIkLsA1ShOXZeqakmQT_fe06uDIyXb02Y4_hC4pWVBCs5vNYg3KQ1gwwoanvCjyIzSlIhfzVBT0GE0JH_IiTSfoLIQNITTlCTtFE84SwbjgU_RxD3urGg3YQAQdrWuwbXC77oJ1tfu0WtV1h62BJtrKgsEa6hrHroUwgHEN2KuI1c7Y6HyHtfMRvs_RSaXqABeHOEPvjw9vy-f56vXpZXm3mmuesTgXZQlCp6QwOedJnlJtDDNQEU4rQhiYLCt4xjUpaJUrVfWFYUKorD-ZlyXnM3Q9zm29-9pBiHJrw_BD1YDbBckSIgRjCU16NBlR7V0IHirZertVvpOUyMGo3MjRqByMytFo33Z12LArt2D-mn4V9sDtCEB_596Cl0Fb6I0a63uh0jj7_4YfqzqJlA</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Pérez-González, David</creator><creator>Parras, Gloria G.</creator><creator>Morado-Díaz, Camilo J.</creator><creator>Aedo-Sánchez, Cristian</creator><creator>Carbajal, Guillermo V.</creator><creator>Malmierca, Manuel S.</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>202101</creationdate><title>Deviance detection in physiologically identified cell types in the rat auditory cortex</title><author>Pérez-González, David ; Parras, Gloria G. ; Morado-Díaz, Camilo J. ; Aedo-Sánchez, Cristian ; Carbajal, Guillermo V. ; Malmierca, Manuel S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-8bbe8c509d7334751cdd2def031f002ed669363c091f7aaf936d288a60203bb33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Acoustic Stimulation</topic><topic>Animals</topic><topic>Auditory Cortex</topic><topic>Electroencephalography</topic><topic>Evoked Potentials, Auditory</topic><topic>Fast spiking neurons</topic><topic>Inhibitory</topic><topic>Predictive coding</topic><topic>Pyramidal</topic><topic>Rats</topic><topic>Reaction Time</topic><topic>Regular spiking neurons</topic><topic>Spike width analysis</topic><topic>Stimulus-specific adaptation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pérez-González, David</creatorcontrib><creatorcontrib>Parras, Gloria G.</creatorcontrib><creatorcontrib>Morado-Díaz, Camilo J.</creatorcontrib><creatorcontrib>Aedo-Sánchez, Cristian</creatorcontrib><creatorcontrib>Carbajal, Guillermo V.</creatorcontrib><creatorcontrib>Malmierca, Manuel S.</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>Hearing research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pérez-González, David</au><au>Parras, Gloria G.</au><au>Morado-Díaz, Camilo J.</au><au>Aedo-Sánchez, Cristian</au><au>Carbajal, Guillermo V.</au><au>Malmierca, Manuel S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deviance detection in physiologically identified cell types in the rat auditory cortex</atitle><jtitle>Hearing research</jtitle><addtitle>Hear Res</addtitle><date>2021-01</date><risdate>2021</risdate><volume>399</volume><spage>107997</spage><epage>107997</epage><pages>107997-107997</pages><artnum>107997</artnum><issn>0378-5955</issn><eissn>1878-5891</eissn><abstract>Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, which evokes an event-related potential known as mismatch negativity (MMN). The same stimulation paradigms are used in animal studies that aim to elucidate the neuronal mechanisms underlying deviance detection. In order to understand the circuitry responsible for deviance detection in the auditory cortex (AC), it is necessary to determine the properties of excitatory and inhibitory neurons separately. Measuring the spike widths of neurons recorded extracellularly from the anaesthetized rat AC, we classified them as fast spiking or regular spiking units. These two neuron types are generally considered as putative inhibitory or excitatory, respectively. In response to an oddball paradigm, we found that both types of units showed similar amounts of deviance detection overall. When considering each AC field separately, we found that only in A1 fast spiking neurons showed higher deviance detection levels than regular spiking neurons, while in the rest of the fields there was no such distinction. Interpreting these responses in the context of the predictive coding framework, we found that the responses of both types of units reflect mainly prediction error signaling (i.e., genuine deviance detection) rather than repetition suppression.
•Single units from the auditory cortex were classified as excitatory or inhibitory.•Both inhibitory and excitatory units showed deviance detection.•Inhibitory units showed larger deviance detection than excitatory units in A1 only.•The responses indicated prediction error rather than repetition suppression.•Both types of neurons may contribute to the deviance detection cortical circuits.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>32482383</pmid><doi>10.1016/j.heares.2020.107997</doi><tpages>1</tpages></addata></record> |
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subjects | Acoustic Stimulation Animals Auditory Cortex Electroencephalography Evoked Potentials, Auditory Fast spiking neurons Inhibitory Predictive coding Pyramidal Rats Reaction Time Regular spiking neurons Spike width analysis Stimulus-specific adaptation |
title | Deviance detection in physiologically identified cell types in the rat auditory cortex |
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