Temporal correlations and neural spike train entropy
Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limi...
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| Veröffentlicht in: | Physical review letters 2001-06, Vol.86 (25), p.5823-5826 |
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| container_end_page | 5826 |
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| container_title | Physical review letters |
| container_volume | 86 |
| creator | Schultz, S R Panzeri, S |
| description | Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a "brute force" approach. |
| doi_str_mv | 10.1103/PhysRevLett.86.5823 |
| format | Article |
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We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a "brute force" approach.</description><subject>Action Potentials</subject><subject>Animals</subject><subject>CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS</subject><subject>Computer simulation</subject><subject>Correlation methods</subject><subject>ENTROPY</subject><subject>Haplorhini</subject><subject>Mathematical models</subject><subject>Models, Neurological</subject><subject>MONKEYS</subject><subject>Neurons - physiology</subject><subject>Probability</subject><subject>SAMPLING</subject><subject>Visual Cortex - cytology</subject><subject>Visual Cortex - physiology</subject><issn>0031-9007</issn><issn>1079-7114</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2001</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1Lw0AQhhdRbK3-AkECgrfU2Y9sNkcpfkFBkXpeNpspjSbZuLsR-u9NaUFvngZmnvdleAi5pDCnFPjt62Yb3vB7iTHOlZxnivEjMqWQF2lOqTgmUwBO0wIgn5CzED4AgDKpTslkPNOMy3xKxArb3nnTJNZ5j42JtetCYroq6XDY7UNff2ISvam7BLvoXb89Jydr0wS8OMwZeX-4Xy2e0uXL4_PibplaLiGmJdoMkBa2NCzLDRdlYQua0QoFM1RwPr6gJAhEztDmkmVg1gpQcqCqUorPyPW-14VY62DriHZjXdehjVoAAyGLYqRu9lTv3deAIeq2DhabxnTohqBzKASAgn9BRoVgSmQjyPeg9S4Ej2vd-7o1fqsp6J17_ce9VlLv3I-pq0P9ULZY_WYOsvkPOgSA6w</recordid><startdate>20010618</startdate><enddate>20010618</enddate><creator>Schultz, S R</creator><creator>Panzeri, S</creator><general>The American Physical Society</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><scope>OTOTI</scope></search><sort><creationdate>20010618</creationdate><title>Temporal correlations and neural spike train entropy</title><author>Schultz, S R ; Panzeri, S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c360t-bec50e19cba257a34b9c9151de42a14335368604ee32ec76250af80e63018d883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Action Potentials</topic><topic>Animals</topic><topic>CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS</topic><topic>Computer simulation</topic><topic>Correlation methods</topic><topic>ENTROPY</topic><topic>Haplorhini</topic><topic>Mathematical models</topic><topic>Models, Neurological</topic><topic>MONKEYS</topic><topic>Neurons - physiology</topic><topic>Probability</topic><topic>SAMPLING</topic><topic>Visual Cortex - cytology</topic><topic>Visual Cortex - physiology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schultz, S R</creatorcontrib><creatorcontrib>Panzeri, 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><collection>OSTI.GOV</collection><jtitle>Physical review letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schultz, S R</au><au>Panzeri, S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Temporal correlations and neural spike train entropy</atitle><jtitle>Physical review letters</jtitle><addtitle>Phys Rev Lett</addtitle><date>2001-06-18</date><risdate>2001</risdate><volume>86</volume><issue>25</issue><spage>5823</spage><epage>5826</epage><pages>5823-5826</pages><issn>0031-9007</issn><eissn>1079-7114</eissn><abstract>Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. 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| ispartof | Physical review letters, 2001-06, Vol.86 (25), p.5823-5826 |
| issn | 0031-9007 1079-7114 |
| language | eng |
| recordid | cdi_osti_scitechconnect_40204699 |
| source | MEDLINE; American Physical Society Journals |
| subjects | Action Potentials Animals CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS Computer simulation Correlation methods ENTROPY Haplorhini Mathematical models Models, Neurological MONKEYS Neurons - physiology Probability SAMPLING Visual Cortex - cytology Visual Cortex - physiology |
| title | Temporal correlations and neural spike train entropy |
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