Encoding Chaos in Neural Spike Trains
A recent theoretical study showed that with a chaotically driven integrate-and-fire neutron model, there can be a one-to-one correspondence between the system states of the chaotic input and the interspike intervals (ISIs) from the model. In this investigation, an attempt is made to extend the previ...
Gespeichert in:
| Veröffentlicht in: | Physical review letters 1998-03, Vol.80 (11), p.2485-2488 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 2488 |
|---|---|
| container_issue | 11 |
| container_start_page | 2485 |
| container_title | Physical review letters |
| container_volume | 80 |
| creator | Richardson, Kristen A. Imhoff, Thomas T. Grigg, Peter Collins, James J. |
| description | A recent theoretical study showed that with a chaotically driven integrate-and-fire neutron model, there can be a one-to-one correspondence between the system states of the chaotic input and the interspike intervals (ISIs) from the model. In this investigation, an attempt is made to extend the previous work to in vitro studies on rat cutaneous afferents. In particular, the hypothesis that the deterministic structure of a chaotic input signal can be preserved when the signal is converted into a spike train by a sensory neuron is tested. Ten neurons are included in the investigation. Determinism of the ISI series is assessed using a nonlinear prediction algorithm. |
| doi_str_mv | 10.1103/PhysRevLett.80.2485 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_21350452</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>328799</sourcerecordid><originalsourceid>FETCH-LOGICAL-c278t-c97edd4c4e8a17581ccc59ce7f5dcd4a5b83d8553b6d41dcd089f566ad0c2f03</originalsourceid><addsrcrecordid>eNpNkEFPgzAYhhujiTj9BV646A38PtrScjRkThOiRrk3XVscygBbMNm_d8s8eHqTN0-ew0PINUKKCPTudbMLb-6nctOUSkgzJvkJiRBEkQhEdkoiAIpJASDOyUUInwCAWS4jcrPszWDb_iMuN3oIcdvHz272uovfx_bLxbXXbR8uyVmju-Cu_nZB6odlXT4m1cvqqbyvEpMJOSWmEM5aZpiTGgWXaIzhhXGi4dZYpvlaUis5p-vcMtxfIIuG57m2YLIG6ILcHrWjH75nFya1bYNxXad7N8xBZUg5MJ7tQXoEjR9C8K5Ro2-32u8UgjoUUf-KKAnqUIT-AnREVtE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>21350452</pqid></control><display><type>article</type><title>Encoding Chaos in Neural Spike Trains</title><source>American Physical Society Journals</source><creator>Richardson, Kristen A. ; Imhoff, Thomas T. ; Grigg, Peter ; Collins, James J.</creator><creatorcontrib>Richardson, Kristen A. ; Imhoff, Thomas T. ; Grigg, Peter ; Collins, James J.</creatorcontrib><description>A recent theoretical study showed that with a chaotically driven integrate-and-fire neutron model, there can be a one-to-one correspondence between the system states of the chaotic input and the interspike intervals (ISIs) from the model. In this investigation, an attempt is made to extend the previous work to in vitro studies on rat cutaneous afferents. In particular, the hypothesis that the deterministic structure of a chaotic input signal can be preserved when the signal is converted into a spike train by a sensory neuron is tested. Ten neurons are included in the investigation. Determinism of the ISI series is assessed using a nonlinear prediction algorithm.</description><identifier>ISSN: 0031-9007</identifier><identifier>EISSN: 1079-7114</identifier><identifier>DOI: 10.1103/PhysRevLett.80.2485</identifier><language>eng</language><subject>Actuators ; Algorithms ; Forecasting ; Fourier transforms ; Mathematical models ; Neurology ; Position control ; Random processes ; Signal encoding ; Vectors</subject><ispartof>Physical review letters, 1998-03, Vol.80 (11), p.2485-2488</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c278t-c97edd4c4e8a17581ccc59ce7f5dcd4a5b83d8553b6d41dcd089f566ad0c2f03</citedby><cites>FETCH-LOGICAL-c278t-c97edd4c4e8a17581ccc59ce7f5dcd4a5b83d8553b6d41dcd089f566ad0c2f03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,2876,2877,27924,27925</link.rule.ids></links><search><creatorcontrib>Richardson, Kristen A.</creatorcontrib><creatorcontrib>Imhoff, Thomas T.</creatorcontrib><creatorcontrib>Grigg, Peter</creatorcontrib><creatorcontrib>Collins, James J.</creatorcontrib><title>Encoding Chaos in Neural Spike Trains</title><title>Physical review letters</title><description>A recent theoretical study showed that with a chaotically driven integrate-and-fire neutron model, there can be a one-to-one correspondence between the system states of the chaotic input and the interspike intervals (ISIs) from the model. In this investigation, an attempt is made to extend the previous work to in vitro studies on rat cutaneous afferents. In particular, the hypothesis that the deterministic structure of a chaotic input signal can be preserved when the signal is converted into a spike train by a sensory neuron is tested. Ten neurons are included in the investigation. Determinism of the ISI series is assessed using a nonlinear prediction algorithm.</description><subject>Actuators</subject><subject>Algorithms</subject><subject>Forecasting</subject><subject>Fourier transforms</subject><subject>Mathematical models</subject><subject>Neurology</subject><subject>Position control</subject><subject>Random processes</subject><subject>Signal encoding</subject><subject>Vectors</subject><issn>0031-9007</issn><issn>1079-7114</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><recordid>eNpNkEFPgzAYhhujiTj9BV646A38PtrScjRkThOiRrk3XVscygBbMNm_d8s8eHqTN0-ew0PINUKKCPTudbMLb-6nctOUSkgzJvkJiRBEkQhEdkoiAIpJASDOyUUInwCAWS4jcrPszWDb_iMuN3oIcdvHz272uovfx_bLxbXXbR8uyVmju-Cu_nZB6odlXT4m1cvqqbyvEpMJOSWmEM5aZpiTGgWXaIzhhXGi4dZYpvlaUis5p-vcMtxfIIuG57m2YLIG6ILcHrWjH75nFya1bYNxXad7N8xBZUg5MJ7tQXoEjR9C8K5Ro2-32u8UgjoUUf-KKAnqUIT-AnREVtE</recordid><startdate>19980316</startdate><enddate>19980316</enddate><creator>Richardson, Kristen A.</creator><creator>Imhoff, Thomas T.</creator><creator>Grigg, Peter</creator><creator>Collins, James J.</creator><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>19980316</creationdate><title>Encoding Chaos in Neural Spike Trains</title><author>Richardson, Kristen A. ; Imhoff, Thomas T. ; Grigg, Peter ; Collins, James J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c278t-c97edd4c4e8a17581ccc59ce7f5dcd4a5b83d8553b6d41dcd089f566ad0c2f03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Actuators</topic><topic>Algorithms</topic><topic>Forecasting</topic><topic>Fourier transforms</topic><topic>Mathematical models</topic><topic>Neurology</topic><topic>Position control</topic><topic>Random processes</topic><topic>Signal encoding</topic><topic>Vectors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Richardson, Kristen A.</creatorcontrib><creatorcontrib>Imhoff, Thomas T.</creatorcontrib><creatorcontrib>Grigg, Peter</creatorcontrib><creatorcontrib>Collins, James J.</creatorcontrib><collection>CrossRef</collection><jtitle>Physical review letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Richardson, Kristen A.</au><au>Imhoff, Thomas T.</au><au>Grigg, Peter</au><au>Collins, James J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Encoding Chaos in Neural Spike Trains</atitle><jtitle>Physical review letters</jtitle><date>1998-03-16</date><risdate>1998</risdate><volume>80</volume><issue>11</issue><spage>2485</spage><epage>2488</epage><pages>2485-2488</pages><issn>0031-9007</issn><eissn>1079-7114</eissn><abstract>A recent theoretical study showed that with a chaotically driven integrate-and-fire neutron model, there can be a one-to-one correspondence between the system states of the chaotic input and the interspike intervals (ISIs) from the model. In this investigation, an attempt is made to extend the previous work to in vitro studies on rat cutaneous afferents. In particular, the hypothesis that the deterministic structure of a chaotic input signal can be preserved when the signal is converted into a spike train by a sensory neuron is tested. Ten neurons are included in the investigation. Determinism of the ISI series is assessed using a nonlinear prediction algorithm.</abstract><doi>10.1103/PhysRevLett.80.2485</doi><tpages>4</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0031-9007 |
| ispartof | Physical review letters, 1998-03, Vol.80 (11), p.2485-2488 |
| issn | 0031-9007 1079-7114 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_21350452 |
| source | American Physical Society Journals |
| subjects | Actuators Algorithms Forecasting Fourier transforms Mathematical models Neurology Position control Random processes Signal encoding Vectors |
| title | Encoding Chaos in Neural Spike Trains |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T10%3A29%3A49IST&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=Encoding%20Chaos%20in%20Neural%20Spike%20Trains&rft.jtitle=Physical%20review%20letters&rft.au=Richardson,%20Kristen%20A.&rft.date=1998-03-16&rft.volume=80&rft.issue=11&rft.spage=2485&rft.epage=2488&rft.pages=2485-2488&rft.issn=0031-9007&rft.eissn=1079-7114&rft_id=info:doi/10.1103/PhysRevLett.80.2485&rft_dat=%3Cproquest_cross%3E328799%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=21350452&rft_id=info:pmid/&rfr_iscdi=true |