Low-Dimensional Maps Encoding Dynamics in Entorhinal Cortex and Hippocampus
Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I . In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippoc...
Gespeichert in:
Veröffentlicht in: | Neural computation 2006-11, Vol.18 (11), p.2617-2650 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 2650 |
---|---|
container_issue | 11 |
container_start_page | 2617 |
container_title | Neural computation |
container_volume | 18 |
creator | Pervouchine, Dmitri D. Netoff, Theoden I. Rotstein, Horacio G. White, John A. Cunningham, Mark O. Whittington, Miles A. Kopell, Nancy J. |
description | Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I
. In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippocampus) in networks with fast-spiking (FS) interneurons. The model we use for stellate cells and O-LM cells is the same, but the stellate cells are excitatory and the O-LM cells are inhibitory, with inhibitory postsynaptic potential considerably longer than those from FS interneurons. We use spike time response curve methods (STRC), expanding that technique to three-cell networks and giving two different ways in which the analysis of the three-cell network reduces to that of a two-cell network. We show that adding FS cells to a network of stellate cells can desynchronize the stellate cells, while adding them to a network of O-LM cells can synchronize the O-LM cells. These synchronization and desynchronization properties critically depend on I
. The analysis of the deterministic system allows us to understand some effects of noise on the phase relationships in the stellate networks. The dynamic clamp experiments use biophysical stellate cells and in silico FS cells, with connections that mimic excitation or inhibition, the latter with decay times associated with FS cells or O-LM cells. The results obtained in the dynamic clamp experiments are in a good agreement with the analytical framework. |
doi_str_mv | 10.1162/neco.2006.18.11.2617 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_68889903</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>68889903</sourcerecordid><originalsourceid>FETCH-LOGICAL-c442t-b0907b9c6e89abd281f04fd2096250aff3dbed080b7502e3f2710a7c2e180b833</originalsourceid><addsrcrecordid>eNp9kEFP3DAQha2qiN0C_6Cqcim3LGM7cexjtVBYsYhLK3GzHMdpjRI7tRMo_Hqc7kpcoKeRnr55b-Yh9BnDCmNGzpzRfkUA2ArzpKwIw9UHtMQlhZxzfvcRLYELkVeMVQv0KcZ7SDCG8hAtMBNClBVdouutf8zPbW9ctN6pLrtRQ8wunPaNdb-y8yeneqtjZl0SRx9-2xla-zCav5lyTXZlh8Fr1Q9TPEYHreqiOdnPI_Tz-8WP9VW-vb3crL9tc10UZMxrEFDVQjPDhaobwnELRdsQEIyUoNqWNrVpgENdlUAMbUmFQVWaGJw0TukROt35DsH_mUwcZW-jNl2nnPFTlCy9LwTMYLEDdfAxBtPKIdhehSeJQc4lyrlEOZcoMU-KnEtMa1_2_lPdm-Z1ad9aAr7uARW16tqgnLbxleO4FJTPRpsd19tR3vsppO7iv8wHzG2Ko0AKmlKB4DkduHy2w3tHwRte__3jBSMPoNs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>68889903</pqid></control><display><type>article</type><title>Low-Dimensional Maps Encoding Dynamics in Entorhinal Cortex and Hippocampus</title><source>MEDLINE</source><source>MIT Press Journals</source><creator>Pervouchine, Dmitri D. ; Netoff, Theoden I. ; Rotstein, Horacio G. ; White, John A. ; Cunningham, Mark O. ; Whittington, Miles A. ; Kopell, Nancy J.</creator><creatorcontrib>Pervouchine, Dmitri D. ; Netoff, Theoden I. ; Rotstein, Horacio G. ; White, John A. ; Cunningham, Mark O. ; Whittington, Miles A. ; Kopell, Nancy J.</creatorcontrib><description>Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I
. In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippocampus) in networks with fast-spiking (FS) interneurons. The model we use for stellate cells and O-LM cells is the same, but the stellate cells are excitatory and the O-LM cells are inhibitory, with inhibitory postsynaptic potential considerably longer than those from FS interneurons. We use spike time response curve methods (STRC), expanding that technique to three-cell networks and giving two different ways in which the analysis of the three-cell network reduces to that of a two-cell network. We show that adding FS cells to a network of stellate cells can desynchronize the stellate cells, while adding them to a network of O-LM cells can synchronize the O-LM cells. These synchronization and desynchronization properties critically depend on I
. The analysis of the deterministic system allows us to understand some effects of noise on the phase relationships in the stellate networks. The dynamic clamp experiments use biophysical stellate cells and in silico FS cells, with connections that mimic excitation or inhibition, the latter with decay times associated with FS cells or O-LM cells. The results obtained in the dynamic clamp experiments are in a good agreement with the analytical framework.</description><identifier>ISSN: 0899-7667</identifier><identifier>EISSN: 1530-888X</identifier><identifier>DOI: 10.1162/neco.2006.18.11.2617</identifier><identifier>PMID: 16999573</identifier><language>eng</language><publisher>One Rogers Street, Cambridge, MA 02142-1209, USA: MIT Press</publisher><subject>Action Potentials - physiology ; Action Potentials - radiation effects ; Animals ; Applied sciences ; Artificial intelligence ; Biological and medical sciences ; Brain Mapping ; Computer science; control theory; systems ; Connectionism. Neural networks ; Electric Stimulation - methods ; Entorhinal Cortex - cytology ; Exact sciences and technology ; Fundamental and applied biological sciences. Psychology ; General aspects. Models. Methods ; Global analysis, analysis on manifolds ; Hippocampus - cytology ; Interneurons - physiology ; Learning and adaptive systems ; Letters ; Mathematics ; Models, Neurological ; Neural Networks (Computer) ; Nonlinear Dynamics ; Sciences and techniques of general use ; Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds ; Vertebrates: nervous system and sense organs</subject><ispartof>Neural computation, 2006-11, Vol.18 (11), p.2617-2650</ispartof><rights>2006 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c442t-b0907b9c6e89abd281f04fd2096250aff3dbed080b7502e3f2710a7c2e180b833</citedby><cites>FETCH-LOGICAL-c442t-b0907b9c6e89abd281f04fd2096250aff3dbed080b7502e3f2710a7c2e180b833</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://direct.mit.edu/neco/article/doi/10.1162/neco.2006.18.11.2617$$EHTML$$P50$$Gmit$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,53984,53985</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18159387$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16999573$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pervouchine, Dmitri D.</creatorcontrib><creatorcontrib>Netoff, Theoden I.</creatorcontrib><creatorcontrib>Rotstein, Horacio G.</creatorcontrib><creatorcontrib>White, John A.</creatorcontrib><creatorcontrib>Cunningham, Mark O.</creatorcontrib><creatorcontrib>Whittington, Miles A.</creatorcontrib><creatorcontrib>Kopell, Nancy J.</creatorcontrib><title>Low-Dimensional Maps Encoding Dynamics in Entorhinal Cortex and Hippocampus</title><title>Neural computation</title><addtitle>Neural Comput</addtitle><description>Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I
. In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippocampus) in networks with fast-spiking (FS) interneurons. The model we use for stellate cells and O-LM cells is the same, but the stellate cells are excitatory and the O-LM cells are inhibitory, with inhibitory postsynaptic potential considerably longer than those from FS interneurons. We use spike time response curve methods (STRC), expanding that technique to three-cell networks and giving two different ways in which the analysis of the three-cell network reduces to that of a two-cell network. We show that adding FS cells to a network of stellate cells can desynchronize the stellate cells, while adding them to a network of O-LM cells can synchronize the O-LM cells. These synchronization and desynchronization properties critically depend on I
. The analysis of the deterministic system allows us to understand some effects of noise on the phase relationships in the stellate networks. The dynamic clamp experiments use biophysical stellate cells and in silico FS cells, with connections that mimic excitation or inhibition, the latter with decay times associated with FS cells or O-LM cells. The results obtained in the dynamic clamp experiments are in a good agreement with the analytical framework.</description><subject>Action Potentials - physiology</subject><subject>Action Potentials - radiation effects</subject><subject>Animals</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Biological and medical sciences</subject><subject>Brain Mapping</subject><subject>Computer science; control theory; systems</subject><subject>Connectionism. Neural networks</subject><subject>Electric Stimulation - methods</subject><subject>Entorhinal Cortex - cytology</subject><subject>Exact sciences and technology</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects. Models. Methods</subject><subject>Global analysis, analysis on manifolds</subject><subject>Hippocampus - cytology</subject><subject>Interneurons - physiology</subject><subject>Learning and adaptive systems</subject><subject>Letters</subject><subject>Mathematics</subject><subject>Models, Neurological</subject><subject>Neural Networks (Computer)</subject><subject>Nonlinear Dynamics</subject><subject>Sciences and techniques of general use</subject><subject>Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds</subject><subject>Vertebrates: nervous system and sense organs</subject><issn>0899-7667</issn><issn>1530-888X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEFP3DAQha2qiN0C_6Cqcim3LGM7cexjtVBYsYhLK3GzHMdpjRI7tRMo_Hqc7kpcoKeRnr55b-Yh9BnDCmNGzpzRfkUA2ArzpKwIw9UHtMQlhZxzfvcRLYELkVeMVQv0KcZ7SDCG8hAtMBNClBVdouutf8zPbW9ctN6pLrtRQ8wunPaNdb-y8yeneqtjZl0SRx9-2xla-zCav5lyTXZlh8Fr1Q9TPEYHreqiOdnPI_Tz-8WP9VW-vb3crL9tc10UZMxrEFDVQjPDhaobwnELRdsQEIyUoNqWNrVpgENdlUAMbUmFQVWaGJw0TukROt35DsH_mUwcZW-jNl2nnPFTlCy9LwTMYLEDdfAxBtPKIdhehSeJQc4lyrlEOZcoMU-KnEtMa1_2_lPdm-Z1ad9aAr7uARW16tqgnLbxleO4FJTPRpsd19tR3vsppO7iv8wHzG2Ko0AKmlKB4DkduHy2w3tHwRte__3jBSMPoNs</recordid><startdate>20061101</startdate><enddate>20061101</enddate><creator>Pervouchine, Dmitri D.</creator><creator>Netoff, Theoden I.</creator><creator>Rotstein, Horacio G.</creator><creator>White, John A.</creator><creator>Cunningham, Mark O.</creator><creator>Whittington, Miles A.</creator><creator>Kopell, Nancy J.</creator><general>MIT Press</general><scope>IQODW</scope><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>20061101</creationdate><title>Low-Dimensional Maps Encoding Dynamics in Entorhinal Cortex and Hippocampus</title><author>Pervouchine, Dmitri D. ; Netoff, Theoden I. ; Rotstein, Horacio G. ; White, John A. ; Cunningham, Mark O. ; Whittington, Miles A. ; Kopell, Nancy J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-b0907b9c6e89abd281f04fd2096250aff3dbed080b7502e3f2710a7c2e180b833</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Action Potentials - physiology</topic><topic>Action Potentials - radiation effects</topic><topic>Animals</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Biological and medical sciences</topic><topic>Brain Mapping</topic><topic>Computer science; control theory; systems</topic><topic>Connectionism. Neural networks</topic><topic>Electric Stimulation - methods</topic><topic>Entorhinal Cortex - cytology</topic><topic>Exact sciences and technology</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects. Models. Methods</topic><topic>Global analysis, analysis on manifolds</topic><topic>Hippocampus - cytology</topic><topic>Interneurons - physiology</topic><topic>Learning and adaptive systems</topic><topic>Letters</topic><topic>Mathematics</topic><topic>Models, Neurological</topic><topic>Neural Networks (Computer)</topic><topic>Nonlinear Dynamics</topic><topic>Sciences and techniques of general use</topic><topic>Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds</topic><topic>Vertebrates: nervous system and sense organs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pervouchine, Dmitri D.</creatorcontrib><creatorcontrib>Netoff, Theoden I.</creatorcontrib><creatorcontrib>Rotstein, Horacio G.</creatorcontrib><creatorcontrib>White, John A.</creatorcontrib><creatorcontrib>Cunningham, Mark O.</creatorcontrib><creatorcontrib>Whittington, Miles A.</creatorcontrib><creatorcontrib>Kopell, Nancy J.</creatorcontrib><collection>Pascal-Francis</collection><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>Neural computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pervouchine, Dmitri D.</au><au>Netoff, Theoden I.</au><au>Rotstein, Horacio G.</au><au>White, John A.</au><au>Cunningham, Mark O.</au><au>Whittington, Miles A.</au><au>Kopell, Nancy J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Low-Dimensional Maps Encoding Dynamics in Entorhinal Cortex and Hippocampus</atitle><jtitle>Neural computation</jtitle><addtitle>Neural Comput</addtitle><date>2006-11-01</date><risdate>2006</risdate><volume>18</volume><issue>11</issue><spage>2617</spage><epage>2650</epage><pages>2617-2650</pages><issn>0899-7667</issn><eissn>1530-888X</eissn><abstract>Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I
. In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippocampus) in networks with fast-spiking (FS) interneurons. The model we use for stellate cells and O-LM cells is the same, but the stellate cells are excitatory and the O-LM cells are inhibitory, with inhibitory postsynaptic potential considerably longer than those from FS interneurons. We use spike time response curve methods (STRC), expanding that technique to three-cell networks and giving two different ways in which the analysis of the three-cell network reduces to that of a two-cell network. We show that adding FS cells to a network of stellate cells can desynchronize the stellate cells, while adding them to a network of O-LM cells can synchronize the O-LM cells. These synchronization and desynchronization properties critically depend on I
. The analysis of the deterministic system allows us to understand some effects of noise on the phase relationships in the stellate networks. The dynamic clamp experiments use biophysical stellate cells and in silico FS cells, with connections that mimic excitation or inhibition, the latter with decay times associated with FS cells or O-LM cells. The results obtained in the dynamic clamp experiments are in a good agreement with the analytical framework.</abstract><cop>One Rogers Street, Cambridge, MA 02142-1209, USA</cop><pub>MIT Press</pub><pmid>16999573</pmid><doi>10.1162/neco.2006.18.11.2617</doi><tpages>34</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0899-7667 |
ispartof | Neural computation, 2006-11, Vol.18 (11), p.2617-2650 |
issn | 0899-7667 1530-888X |
language | eng |
recordid | cdi_proquest_miscellaneous_68889903 |
source | MEDLINE; MIT Press Journals |
subjects | Action Potentials - physiology Action Potentials - radiation effects Animals Applied sciences Artificial intelligence Biological and medical sciences Brain Mapping Computer science control theory systems Connectionism. Neural networks Electric Stimulation - methods Entorhinal Cortex - cytology Exact sciences and technology Fundamental and applied biological sciences. Psychology General aspects. Models. Methods Global analysis, analysis on manifolds Hippocampus - cytology Interneurons - physiology Learning and adaptive systems Letters Mathematics Models, Neurological Neural Networks (Computer) Nonlinear Dynamics Sciences and techniques of general use Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds Vertebrates: nervous system and sense organs |
title | Low-Dimensional Maps Encoding Dynamics in Entorhinal Cortex and Hippocampus |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T12%3A08%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Low-Dimensional%20Maps%20Encoding%20Dynamics%20in%20Entorhinal%20Cortex%20and%20Hippocampus&rft.jtitle=Neural%20computation&rft.au=Pervouchine,%20Dmitri%20D.&rft.date=2006-11-01&rft.volume=18&rft.issue=11&rft.spage=2617&rft.epage=2650&rft.pages=2617-2650&rft.issn=0899-7667&rft.eissn=1530-888X&rft_id=info:doi/10.1162/neco.2006.18.11.2617&rft_dat=%3Cproquest_cross%3E68889903%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=68889903&rft_id=info:pmid/16999573&rfr_iscdi=true |