Spike Code Flow in Cultured Neuronal Networks
We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then...
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creator | Tamura, Shinichi Nishitani, Yoshi Hosokawa, Chie Miyoshi, Tomomitsu Sawai, Hajime Kamimura, Takuya Yagi, Yasushi Mizuno-Matsumoto, Yuko Chen, Yen-Wei |
description | We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network. |
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Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2016/7267691</identifier><identifier>PMID: 27217825</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Limiteds</publisher><subject>Accuracy ; Action Potentials - physiology ; Animals ; Arrays ; Cell Culture Techniques ; Codes ; Communication ; Constants ; Electric Stimulation ; Electrodes ; Embryo, Mammalian ; Hippocampus - cytology ; Intelligence ; Models, Neurological ; Nerve Net - physiology ; Neural circuitry ; Neural networks ; Neurons ; Neurons - physiology ; Physiological aspects ; Pseudorandom sequences ; Rats ; Rats, Wistar ; Spikes ; Wave propagation</subject><ispartof>Computational Intelligence and Neuroscience, 2016-01, Vol.2016 (2016), p.478-488</ispartof><rights>Copyright © 2016 Shinichi Tamura et al.</rights><rights>COPYRIGHT 2016 John Wiley & Sons, Inc.</rights><rights>Copyright © 2016 Shinichi Tamura et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><rights>Copyright © 2016 Shinichi Tamura et al. 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a657t-484fffea7e2cc6083aad653bdfacfe32ce6fb73075b09e44c3d152efde4d81833</cites><orcidid>0000-0002-0289-4680</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/PMC4863084/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4863084/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27217825$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Maex, Reinoud</contributor><creatorcontrib>Tamura, Shinichi</creatorcontrib><creatorcontrib>Nishitani, Yoshi</creatorcontrib><creatorcontrib>Hosokawa, Chie</creatorcontrib><creatorcontrib>Miyoshi, Tomomitsu</creatorcontrib><creatorcontrib>Sawai, Hajime</creatorcontrib><creatorcontrib>Kamimura, Takuya</creatorcontrib><creatorcontrib>Yagi, Yasushi</creatorcontrib><creatorcontrib>Mizuno-Matsumoto, Yuko</creatorcontrib><creatorcontrib>Chen, Yen-Wei</creatorcontrib><title>Spike Code Flow in Cultured Neuronal Networks</title><title>Computational Intelligence and Neuroscience</title><addtitle>Comput Intell Neurosci</addtitle><description>We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.</description><subject>Accuracy</subject><subject>Action Potentials - physiology</subject><subject>Animals</subject><subject>Arrays</subject><subject>Cell Culture Techniques</subject><subject>Codes</subject><subject>Communication</subject><subject>Constants</subject><subject>Electric Stimulation</subject><subject>Electrodes</subject><subject>Embryo, Mammalian</subject><subject>Hippocampus - cytology</subject><subject>Intelligence</subject><subject>Models, Neurological</subject><subject>Nerve Net - physiology</subject><subject>Neural circuitry</subject><subject>Neural networks</subject><subject>Neurons</subject><subject>Neurons - physiology</subject><subject>Physiological aspects</subject><subject>Pseudorandom sequences</subject><subject>Rats</subject><subject>Rats, Wistar</subject><subject>Spikes</subject><subject>Wave propagation</subject><issn>1687-5265</issn><issn>1687-5273</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkk1v1DAQhiMEoh9w44wicUEqaT3-zgWpWlGotKJIwNnyJuPWbTZe7IQV_x6nu922XOhpxvKjR5p3pijeADkGEOKEEpAnikola3hW7IPUqhJUsee7Xoq94iCla0KEEoS-LPaooqA0FftF9X3lb7CchRbLsy6sS9-Xs7Ebxoht-RXHGHrb5WZYh3iTXhUvnO0Svt7Ww-Ln2acfsy_V_OLz-ex0Xlkp1FBxzZ1zaBXSppFEM2tbKdiidbZxyGiD0i0UI0osSI2cN6wFQdG1yFsNmrHD4uPGuxoXS2wb7IdoO7OKfmnjHxOsN49_en9lLsNvw7VkRPMseL8VxPBrxDSYpU8Ndp3tMYzJgAZJBKNcPAElWuZ4gf4fVTUwqnPGGX33D3odxpiznCituKAU-D11aTs0vnchT9NMUnMqgPAcBkCmPmyoJoaUIrpdEEDMdANmugGzvYGMv30Y3g6-W3oGjjbAle9bu_ZP1GFm0NkHdF0rXmdgvgGsj37w94N-mzwk3yIh9NYJt0WRbCW5Pn5wpfP6NPsLDLPUnw</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Tamura, Shinichi</creator><creator>Nishitani, Yoshi</creator><creator>Hosokawa, Chie</creator><creator>Miyoshi, Tomomitsu</creator><creator>Sawai, Hajime</creator><creator>Kamimura, Takuya</creator><creator>Yagi, Yasushi</creator><creator>Mizuno-Matsumoto, Yuko</creator><creator>Chen, Yen-Wei</creator><general>Hindawi Limiteds</general><general>Hindawi Publishing Corporation</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>188</scope><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</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>3V.</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TK</scope><scope>7U5</scope><scope>7X7</scope><scope>7XB</scope><scope>8AL</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</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>CWDGH</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>LK8</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-0289-4680</orcidid></search><sort><creationdate>20160101</creationdate><title>Spike Code Flow in Cultured Neuronal Networks</title><author>Tamura, Shinichi ; Nishitani, Yoshi ; Hosokawa, Chie ; Miyoshi, Tomomitsu ; Sawai, Hajime ; Kamimura, Takuya ; Yagi, Yasushi ; Mizuno-Matsumoto, Yuko ; Chen, Yen-Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a657t-484fffea7e2cc6083aad653bdfacfe32ce6fb73075b09e44c3d152efde4d81833</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Accuracy</topic><topic>Action Potentials - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computational Intelligence and Neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tamura, Shinichi</au><au>Nishitani, Yoshi</au><au>Hosokawa, Chie</au><au>Miyoshi, Tomomitsu</au><au>Sawai, Hajime</au><au>Kamimura, Takuya</au><au>Yagi, Yasushi</au><au>Mizuno-Matsumoto, Yuko</au><au>Chen, Yen-Wei</au><au>Maex, Reinoud</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spike Code Flow in Cultured Neuronal Networks</atitle><jtitle>Computational Intelligence and Neuroscience</jtitle><addtitle>Comput Intell Neurosci</addtitle><date>2016-01-01</date><risdate>2016</risdate><volume>2016</volume><issue>2016</issue><spage>478</spage><epage>488</epage><pages>478-488</pages><issn>1687-5265</issn><eissn>1687-5273</eissn><abstract>We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Limiteds</pub><pmid>27217825</pmid><doi>10.1155/2016/7267691</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-0289-4680</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Action Potentials - physiology Animals Arrays Cell Culture Techniques Codes Communication Constants Electric Stimulation Electrodes Embryo, Mammalian Hippocampus - cytology Intelligence Models, Neurological Nerve Net - physiology Neural circuitry Neural networks Neurons Neurons - physiology Physiological aspects Pseudorandom sequences Rats Rats, Wistar Spikes Wave propagation |
title | Spike Code Flow in Cultured Neuronal Networks |
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