Stimulus-choice (mis)alignment in primate area MT
For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animal's perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The i...
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description | For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animal's perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal (MT) area during perceptual-decision-making, we extracted low-dimensional latent factors that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the latent factors strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population. |
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This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal (MT) area during perceptual-decision-making, we extracted low-dimensional latent factors that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the latent factors strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1007614</identifier><identifier>PMID: 32421716</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Animal care ; Animals ; Behavior ; Biology and Life Sciences ; Cerebral Cortex ; Choice Behavior - physiology ; Circuits ; Computational biology ; Control ; Correlation ; Decision making ; Decision Making - physiology ; Depth Perception - physiology ; Engineering and Technology ; Feedback ; Feedback, Sensory - physiology ; Female ; Hypotheses ; Information processing ; Macaca mulatta ; Male ; Management ; Medicine and Health Sciences ; Models, Theoretical ; Motor skill learning ; Neurobiology ; Neurons ; Neurosciences ; Noise ; Optimization ; Photic Stimulation - methods ; Physiological aspects ; Population ; Population (statistical) ; Primates ; Sensorimotor integration ; Sensory neurons ; Sensory Receptor Cells ; Signal processing ; Social Sciences ; Statistical analysis ; Stimuli (Psychology) ; Temporal Lobe - physiology ; Temporal lobes ; Visual Perception - physiology</subject><ispartof>PLoS computational biology, 2020-05, Vol.16 (5), p.e1007614-e1007614</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Zhao et al 2020 Zhao et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5084-63e1d2ef06fbd748b0d59dcc43af7291c8aac30769b15144e9392fa5cd31cae33</citedby><cites>FETCH-LOGICAL-c5084-63e1d2ef06fbd748b0d59dcc43af7291c8aac30769b15144e9392fa5cd31cae33</cites><orcidid>0000-0001-8322-5982 ; 0000-0002-6123-8579</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7259805/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7259805/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,862,883,2098,2917,23849,27907,27908,53774,53776,79351,79352</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32421716$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Marinazzo, Daniele</contributor><creatorcontrib>Zhao, Yuan</creatorcontrib><creatorcontrib>Yates, Jacob L</creatorcontrib><creatorcontrib>Levi, Aaron J</creatorcontrib><creatorcontrib>Huk, Alexander C</creatorcontrib><creatorcontrib>Park, Il Memming</creatorcontrib><title>Stimulus-choice (mis)alignment in primate area MT</title><title>PLoS computational biology</title><addtitle>PLoS Comput Biol</addtitle><description>For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animal's perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal (MT) area during perceptual-decision-making, we extracted low-dimensional latent factors that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the latent factors strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population.</description><subject>Analysis</subject><subject>Animal care</subject><subject>Animals</subject><subject>Behavior</subject><subject>Biology and Life Sciences</subject><subject>Cerebral Cortex</subject><subject>Choice Behavior - physiology</subject><subject>Circuits</subject><subject>Computational biology</subject><subject>Control</subject><subject>Correlation</subject><subject>Decision making</subject><subject>Decision Making - physiology</subject><subject>Depth Perception - physiology</subject><subject>Engineering and Technology</subject><subject>Feedback</subject><subject>Feedback, Sensory - physiology</subject><subject>Female</subject><subject>Hypotheses</subject><subject>Information processing</subject><subject>Macaca mulatta</subject><subject>Male</subject><subject>Management</subject><subject>Medicine and Health Sciences</subject><subject>Models, Theoretical</subject><subject>Motor skill learning</subject><subject>Neurobiology</subject><subject>Neurons</subject><subject>Neurosciences</subject><subject>Noise</subject><subject>Optimization</subject><subject>Photic Stimulation - methods</subject><subject>Physiological aspects</subject><subject>Population</subject><subject>Population (statistical)</subject><subject>Primates</subject><subject>Sensorimotor integration</subject><subject>Sensory neurons</subject><subject>Sensory Receptor Cells</subject><subject>Signal processing</subject><subject>Social Sciences</subject><subject>Statistical analysis</subject><subject>Stimuli (Psychology)</subject><subject>Temporal Lobe - physiology</subject><subject>Temporal lobes</subject><subject>Visual Perception - physiology</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNptUstu1DAUjRCIPuAPEIzEpiwy-P3YVKqqApWKWFDW1o1jTz1K4sFOkPh7nE5adVDlha3rc8895-pU1TuM1phK_HkbpzRAt97ZJqwxQlJg9qI6xpzTWlKuXj55H1UnOW8RKk8tXldHlDCCJRbHFf45hn7qplzbuxisW531IX-CLmyG3g3jKgyrXQo9jG4FycHq--2b6pWHLru3y31a_fpydXv5rb758fX68uKmthwpVgvqcEucR8I3rWSqQS3XrbWMgpdEY6sALC2qdYM5ZsxpqokHbluKLThKT6sPe95dF7NZ3GZDmECSa6VUQVzvEW2ErbmXmf6aCMHcF2LaGEhjsJ0zWFBEHYCUQjFQRBGwZQOSUK6Rt75wnS_TpqZ3rS3eE3QHpIc_Q7gzm_jHSFLEIF4IzhaCFH9PLo-mLNK6roPBxWnWjZigmvIZ-vE_6PPuFtQGioEw-Fjm2pnUXAhKNEMS44JaP4Mqp3V9sHFwPpT6QQPbN9gUc07OP3rEyMzBehBj5mCZJVil7f3T_Tw2PSSJ_gN7JMgn</recordid><startdate>20200501</startdate><enddate>20200501</enddate><creator>Zhao, Yuan</creator><creator>Yates, Jacob L</creator><creator>Levi, Aaron J</creator><creator>Huk, Alexander C</creator><creator>Park, Il Memming</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-8322-5982</orcidid><orcidid>https://orcid.org/0000-0002-6123-8579</orcidid></search><sort><creationdate>20200501</creationdate><title>Stimulus-choice (mis)alignment in primate area MT</title><author>Zhao, Yuan ; Yates, Jacob L ; Levi, Aaron J ; Huk, Alexander C ; Park, Il Memming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5084-63e1d2ef06fbd748b0d59dcc43af7291c8aac30769b15144e9392fa5cd31cae33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Analysis</topic><topic>Animal care</topic><topic>Animals</topic><topic>Behavior</topic><topic>Biology and Life Sciences</topic><topic>Cerebral Cortex</topic><topic>Choice Behavior - physiology</topic><topic>Circuits</topic><topic>Computational biology</topic><topic>Control</topic><topic>Correlation</topic><topic>Decision making</topic><topic>Decision Making - physiology</topic><topic>Depth Perception - physiology</topic><topic>Engineering and Technology</topic><topic>Feedback</topic><topic>Feedback, Sensory - physiology</topic><topic>Female</topic><topic>Hypotheses</topic><topic>Information processing</topic><topic>Macaca mulatta</topic><topic>Male</topic><topic>Management</topic><topic>Medicine and Health Sciences</topic><topic>Models, Theoretical</topic><topic>Motor skill learning</topic><topic>Neurobiology</topic><topic>Neurons</topic><topic>Neurosciences</topic><topic>Noise</topic><topic>Optimization</topic><topic>Photic Stimulation - methods</topic><topic>Physiological aspects</topic><topic>Population</topic><topic>Population (statistical)</topic><topic>Primates</topic><topic>Sensorimotor integration</topic><topic>Sensory neurons</topic><topic>Sensory Receptor Cells</topic><topic>Signal processing</topic><topic>Social Sciences</topic><topic>Statistical analysis</topic><topic>Stimuli (Psychology)</topic><topic>Temporal Lobe - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhao, Yuan</au><au>Yates, Jacob L</au><au>Levi, Aaron J</au><au>Huk, Alexander C</au><au>Park, Il Memming</au><au>Marinazzo, Daniele</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stimulus-choice (mis)alignment in primate area MT</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2020-05-01</date><risdate>2020</risdate><volume>16</volume><issue>5</issue><spage>e1007614</spage><epage>e1007614</epage><pages>e1007614-e1007614</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animal's perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal (MT) area during perceptual-decision-making, we extracted low-dimensional latent factors that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the latent factors strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32421716</pmid><doi>10.1371/journal.pcbi.1007614</doi><orcidid>https://orcid.org/0000-0001-8322-5982</orcidid><orcidid>https://orcid.org/0000-0002-6123-8579</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Animal care Animals Behavior Biology and Life Sciences Cerebral Cortex Choice Behavior - physiology Circuits Computational biology Control Correlation Decision making Decision Making - physiology Depth Perception - physiology Engineering and Technology Feedback Feedback, Sensory - physiology Female Hypotheses Information processing Macaca mulatta Male Management Medicine and Health Sciences Models, Theoretical Motor skill learning Neurobiology Neurons Neurosciences Noise Optimization Photic Stimulation - methods Physiological aspects Population Population (statistical) Primates Sensorimotor integration Sensory neurons Sensory Receptor Cells Signal processing Social Sciences Statistical analysis Stimuli (Psychology) Temporal Lobe - physiology Temporal lobes Visual Perception - physiology |
title | Stimulus-choice (mis)alignment in primate area MT |
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