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A Hierarchy of Functional States in Working Memory
Extensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behavior. We addressed this question by combining human electrophysiology (50 subjects, male and female) with pattern analyses, cognitive modeling, and a task requirin...
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Published in: | The Journal of neuroscience 2021-05, Vol.41 (20), p.4461-4475 |
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creator | Muhle-Karbe, Paul S Myers, Nicholas E Stokes, Mark G |
description | Extensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behavior. We addressed this question by combining human electrophysiology (50 subjects, male and female) with pattern analyses, cognitive modeling, and a task requiring the prolonged maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for memories that were selected to guide the next decision from states coding for concurrently held memories that were maintained for later use, and to examine how these states contribute to WM-based decisions. Selected memories were encoded in a functionally active state. This state was reflected in spontaneous brain activity during the delay period, closely tracked moment-to-moment fluctuations in the quality of evidence integration, and also predicted when memories would interfere with each other. In contrast, concurrently held memories were encoded in a functionally latent state. This state was reflected only in stimulus-evoked brain activity, tracked memory precision at longer timescales, but did not engage with ongoing decision dynamics. Intriguingly, the two functional states were highly flexible, as priority could be dynamically shifted back and forth between memories without degrading their precision. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision circuits to guide flexible behavior.
Working memory enables maintenance of information that is no longer available in the environment. Abundant neuroscientific work has examined where in the brain working memories are stored, but it remains unknown how they are represented and used to guide behavior. Our study shows that working memories are represented in qualitatively different formats, depending on behavioral priorities. Memories that are selected for guiding behavior are encoded in an active state that transforms sensory input into decision variables, whereas other concurrently held memories are encoded in a latent state that supports precise maintenance without affecting ongoing cognition. These results dissociate mechanisms supporting memory storage and usage, and open the door to reveal not only where memories are stored but also how. |
doi_str_mv | 10.1523/JNEUROSCI.3104-20.2021 |
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Working memory enables maintenance of information that is no longer available in the environment. Abundant neuroscientific work has examined where in the brain working memories are stored, but it remains unknown how they are represented and used to guide behavior. Our study shows that working memories are represented in qualitatively different formats, depending on behavioral priorities. Memories that are selected for guiding behavior are encoded in an active state that transforms sensory input into decision variables, whereas other concurrently held memories are encoded in a latent state that supports precise maintenance without affecting ongoing cognition. These results dissociate mechanisms supporting memory storage and usage, and open the door to reveal not only where memories are stored but also how.</description><identifier>ISSN: 0270-6474</identifier><identifier>EISSN: 1529-2401</identifier><identifier>DOI: 10.1523/JNEUROSCI.3104-20.2021</identifier><identifier>PMID: 33888611</identifier><language>eng</language><publisher>United States: Society for Neuroscience</publisher><subject>Adolescent ; Adult ; Brain ; Brain - physiology ; Coding ; Cognitive ability ; Electrophysiology ; Female ; Humans ; Maintenance ; Male ; Memory ; Memory, Short-Term - physiology ; Models, Neurological ; Neural coding ; Pattern analysis ; Short term memory ; Young Adult</subject><ispartof>The Journal of neuroscience, 2021-05, Vol.41 (20), p.4461-4475</ispartof><rights>Copyright © 2021 Muhle-Karbe et al.</rights><rights>Copyright Society for Neuroscience May 19, 2021</rights><rights>Copyright © 2021 Muhle-Karbe et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c442t-4bad312f5557137860de279c548801204dd1bfc0926ae1884c63df21ec08261d3</citedby><cites>FETCH-LOGICAL-c442t-4bad312f5557137860de279c548801204dd1bfc0926ae1884c63df21ec08261d3</cites><orcidid>0000-0002-8749-2815 ; 0000-0001-5599-3044</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/PMC8152603/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8152603/$$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/33888611$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Muhle-Karbe, Paul S</creatorcontrib><creatorcontrib>Myers, Nicholas E</creatorcontrib><creatorcontrib>Stokes, Mark G</creatorcontrib><title>A Hierarchy of Functional States in Working Memory</title><title>The Journal of neuroscience</title><addtitle>J Neurosci</addtitle><description>Extensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behavior. We addressed this question by combining human electrophysiology (50 subjects, male and female) with pattern analyses, cognitive modeling, and a task requiring the prolonged maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for memories that were selected to guide the next decision from states coding for concurrently held memories that were maintained for later use, and to examine how these states contribute to WM-based decisions. Selected memories were encoded in a functionally active state. This state was reflected in spontaneous brain activity during the delay period, closely tracked moment-to-moment fluctuations in the quality of evidence integration, and also predicted when memories would interfere with each other. In contrast, concurrently held memories were encoded in a functionally latent state. This state was reflected only in stimulus-evoked brain activity, tracked memory precision at longer timescales, but did not engage with ongoing decision dynamics. Intriguingly, the two functional states were highly flexible, as priority could be dynamically shifted back and forth between memories without degrading their precision. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision circuits to guide flexible behavior.
Working memory enables maintenance of information that is no longer available in the environment. Abundant neuroscientific work has examined where in the brain working memories are stored, but it remains unknown how they are represented and used to guide behavior. Our study shows that working memories are represented in qualitatively different formats, depending on behavioral priorities. Memories that are selected for guiding behavior are encoded in an active state that transforms sensory input into decision variables, whereas other concurrently held memories are encoded in a latent state that supports precise maintenance without affecting ongoing cognition. These results dissociate mechanisms supporting memory storage and usage, and open the door to reveal not only where memories are stored but also how.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Brain</subject><subject>Brain - physiology</subject><subject>Coding</subject><subject>Cognitive ability</subject><subject>Electrophysiology</subject><subject>Female</subject><subject>Humans</subject><subject>Maintenance</subject><subject>Male</subject><subject>Memory</subject><subject>Memory, Short-Term - physiology</subject><subject>Models, Neurological</subject><subject>Neural coding</subject><subject>Pattern analysis</subject><subject>Short term memory</subject><subject>Young Adult</subject><issn>0270-6474</issn><issn>1529-2401</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNpdkU1PwzAMhiMEgvHxF1AlLlw6bCdNswsSmvjUAIkPcYyyNIVC10DSIu3f02kwAScf_PiV7YexfYQhZsSPrm5OH-9u78eXQ44gUoIhAeEaG_TdUUoCcJ0NgHJIpcjFFtuO8RUAcsB8k21xrpSSiANGJ8lF5YIJ9mWe-DI56xrbVr4xdXLfmtbFpGqSJx_equY5uXYzH-a7bKM0dXR733WHPZ6dPowv0snt-eX4ZJJaIahNxdQUHKnMsixHnisJhaN8ZDOhFCCBKAqclhZGJI1DpYSVvCgJnQVFEgu-w46Xue_ddOYK65o2mFq_h2pmwlx7U-m_naZ60c_-U6v-BxJ4H3D4HRD8R-diq2dVtK6uTeN8FzVlqDIhlaQePfiHvvou9F9YUByAVC6xp-SSssHHGFy5WgZBL7TolRa90KIJ9EJLP7j_-5TV2I8H_gV9gIfD</recordid><startdate>20210519</startdate><enddate>20210519</enddate><creator>Muhle-Karbe, Paul S</creator><creator>Myers, Nicholas E</creator><creator>Stokes, Mark G</creator><general>Society for Neuroscience</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>7QG</scope><scope>7QR</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-8749-2815</orcidid><orcidid>https://orcid.org/0000-0001-5599-3044</orcidid></search><sort><creationdate>20210519</creationdate><title>A Hierarchy of Functional States in Working Memory</title><author>Muhle-Karbe, Paul S ; Myers, Nicholas E ; Stokes, Mark G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-4bad312f5557137860de279c548801204dd1bfc0926ae1884c63df21ec08261d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Brain</topic><topic>Brain - physiology</topic><topic>Coding</topic><topic>Cognitive ability</topic><topic>Electrophysiology</topic><topic>Female</topic><topic>Humans</topic><topic>Maintenance</topic><topic>Male</topic><topic>Memory</topic><topic>Memory, Short-Term - physiology</topic><topic>Models, Neurological</topic><topic>Neural coding</topic><topic>Pattern analysis</topic><topic>Short term memory</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Muhle-Karbe, Paul S</creatorcontrib><creatorcontrib>Myers, Nicholas E</creatorcontrib><creatorcontrib>Stokes, Mark G</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Animal Behavior Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>The Journal of neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Muhle-Karbe, Paul S</au><au>Myers, Nicholas E</au><au>Stokes, Mark G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Hierarchy of Functional States in Working Memory</atitle><jtitle>The Journal of neuroscience</jtitle><addtitle>J Neurosci</addtitle><date>2021-05-19</date><risdate>2021</risdate><volume>41</volume><issue>20</issue><spage>4461</spage><epage>4475</epage><pages>4461-4475</pages><issn>0270-6474</issn><eissn>1529-2401</eissn><abstract>Extensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behavior. We addressed this question by combining human electrophysiology (50 subjects, male and female) with pattern analyses, cognitive modeling, and a task requiring the prolonged maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for memories that were selected to guide the next decision from states coding for concurrently held memories that were maintained for later use, and to examine how these states contribute to WM-based decisions. Selected memories were encoded in a functionally active state. This state was reflected in spontaneous brain activity during the delay period, closely tracked moment-to-moment fluctuations in the quality of evidence integration, and also predicted when memories would interfere with each other. In contrast, concurrently held memories were encoded in a functionally latent state. This state was reflected only in stimulus-evoked brain activity, tracked memory precision at longer timescales, but did not engage with ongoing decision dynamics. Intriguingly, the two functional states were highly flexible, as priority could be dynamically shifted back and forth between memories without degrading their precision. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision circuits to guide flexible behavior.
Working memory enables maintenance of information that is no longer available in the environment. Abundant neuroscientific work has examined where in the brain working memories are stored, but it remains unknown how they are represented and used to guide behavior. Our study shows that working memories are represented in qualitatively different formats, depending on behavioral priorities. Memories that are selected for guiding behavior are encoded in an active state that transforms sensory input into decision variables, whereas other concurrently held memories are encoded in a latent state that supports precise maintenance without affecting ongoing cognition. These results dissociate mechanisms supporting memory storage and usage, and open the door to reveal not only where memories are stored but also how.</abstract><cop>United States</cop><pub>Society for Neuroscience</pub><pmid>33888611</pmid><doi>10.1523/JNEUROSCI.3104-20.2021</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-8749-2815</orcidid><orcidid>https://orcid.org/0000-0001-5599-3044</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Brain Brain - physiology Coding Cognitive ability Electrophysiology Female Humans Maintenance Male Memory Memory, Short-Term - physiology Models, Neurological Neural coding Pattern analysis Short term memory Young Adult |
title | A Hierarchy of Functional States in Working Memory |
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