Extraction of Synaptic Input Properties in Vivo
Knowledge of synaptic input is crucial for understanding synaptic integration and ultimately neural function. However, , the rates at which synaptic inputs arrive are high, so that it is typically impossible to detect single events. We show here that it is nevertheless possible to extract the proper...
Gespeichert in:
| Veröffentlicht in: | Neural computation 2017-07, Vol.29 (7), p.1745-1768 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1768 |
|---|---|
| container_issue | 7 |
| container_start_page | 1745 |
| container_title | Neural computation |
| container_volume | 29 |
| creator | Puggioni, Paolo Jelitai, Marta Duguid, Ian van Rossum, Mark C.W. |
| description | Knowledge of synaptic input is crucial for understanding synaptic integration and ultimately neural function. However,
, the rates at which synaptic inputs arrive are high, so that it is typically impossible to detect single events. We show here that it is nevertheless possible to extract the properties of the events and, in particular, to extract the event rate, the synaptic time constants, and the properties of the event size distribution from
voltage-clamp recordings. Applied to cerebellar interneurons, our method reveals that the synaptic input rate increases from 600 Hz during rest to 1000 Hz during locomotion, while the amplitude and shape of the synaptic events are unaffected by this state change. This method thus complements existing methods to measure neural function
. |
| doi_str_mv | 10.1162/NECO_a_00975 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1162_NECO_a_00975</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1927113458</sourcerecordid><originalsourceid>FETCH-LOGICAL-c513t-3500f6c771722b3765dc306239ab82eaa68e4fe840c20f690220f2ef61b9bcb73</originalsourceid><addsrcrecordid>eNpt0M1LHDEYBvBQKnW13nouA714cPTNm8nXrbKsHyC10A-8hUzMQGR3Mk1mRP3rTV2VRTzlkB_P-_AQ8oXCIaUCj34s5pfGGgAt-Qcyo5xBrZS6-khmoLSupRBym-zkfAMAggL_RLZRcYGIMCNHi7sxWTeG2Fexq37d93YYg6vO-2Eaq58pDj6Nwecq9NXfcBs_k63OLrPfe353yZ-Txe_5WX1xeXo-P76oHadsrBkH6ISTkkrElknBrx0DgUzbVqG3VijfdF414LBADaVMh74TtNWtayXbJfvr3CHFf5PPo1mF7PxyaXsfp2yohkaDEtgU-u0NvYlT6ku7olBSyhquijpYK5dizsl3ZkhhZdO9oWD-D2k2hyz863Po1K789St-Wa6A72uwChsHe-_iLeogDQPkXBkEpCXegDYPYXj637ix_07Eu3UeAck0jXg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1927113458</pqid></control><display><type>article</type><title>Extraction of Synaptic Input Properties in Vivo</title><source>MIT Press Journals</source><creator>Puggioni, Paolo ; Jelitai, Marta ; Duguid, Ian ; van Rossum, Mark C.W.</creator><creatorcontrib>Puggioni, Paolo ; Jelitai, Marta ; Duguid, Ian ; van Rossum, Mark C.W.</creatorcontrib><description>Knowledge of synaptic input is crucial for understanding synaptic integration and ultimately neural function. However,
, the rates at which synaptic inputs arrive are high, so that it is typically impossible to detect single events. We show here that it is nevertheless possible to extract the properties of the events and, in particular, to extract the event rate, the synaptic time constants, and the properties of the event size distribution from
voltage-clamp recordings. Applied to cerebellar interneurons, our method reveals that the synaptic input rate increases from 600 Hz during rest to 1000 Hz during locomotion, while the amplitude and shape of the synaptic events are unaffected by this state change. This method thus complements existing methods to measure neural function
.</description><identifier>ISSN: 0899-7667</identifier><identifier>EISSN: 1530-888X</identifier><identifier>DOI: 10.1162/NECO_a_00975</identifier><identifier>PMID: 28562220</identifier><language>eng</language><publisher>One Rogers Street, Cambridge, MA 02142-1209, USA: MIT Press</publisher><subject>Brain ; Constants ; In vivo methods and tests ; Knowledge ; Locomotion ; Measurement methods ; Neural networks ; Neurons ; Particle size distribution ; Properties (attributes)</subject><ispartof>Neural computation, 2017-07, Vol.29 (7), p.1745-1768</ispartof><rights>Copyright MIT Press Journals Jul 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c513t-3500f6c771722b3765dc306239ab82eaa68e4fe840c20f690220f2ef61b9bcb73</citedby><cites>FETCH-LOGICAL-c513t-3500f6c771722b3765dc306239ab82eaa68e4fe840c20f690220f2ef61b9bcb73</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_a_00975$$EHTML$$P50$$Gmit$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54009,54010</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28562220$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Puggioni, Paolo</creatorcontrib><creatorcontrib>Jelitai, Marta</creatorcontrib><creatorcontrib>Duguid, Ian</creatorcontrib><creatorcontrib>van Rossum, Mark C.W.</creatorcontrib><title>Extraction of Synaptic Input Properties in Vivo</title><title>Neural computation</title><addtitle>Neural Comput</addtitle><description>Knowledge of synaptic input is crucial for understanding synaptic integration and ultimately neural function. However,
, the rates at which synaptic inputs arrive are high, so that it is typically impossible to detect single events. We show here that it is nevertheless possible to extract the properties of the events and, in particular, to extract the event rate, the synaptic time constants, and the properties of the event size distribution from
voltage-clamp recordings. Applied to cerebellar interneurons, our method reveals that the synaptic input rate increases from 600 Hz during rest to 1000 Hz during locomotion, while the amplitude and shape of the synaptic events are unaffected by this state change. This method thus complements existing methods to measure neural function
.</description><subject>Brain</subject><subject>Constants</subject><subject>In vivo methods and tests</subject><subject>Knowledge</subject><subject>Locomotion</subject><subject>Measurement methods</subject><subject>Neural networks</subject><subject>Neurons</subject><subject>Particle size distribution</subject><subject>Properties (attributes)</subject><issn>0899-7667</issn><issn>1530-888X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNpt0M1LHDEYBvBQKnW13nouA714cPTNm8nXrbKsHyC10A-8hUzMQGR3Mk1mRP3rTV2VRTzlkB_P-_AQ8oXCIaUCj34s5pfGGgAt-Qcyo5xBrZS6-khmoLSupRBym-zkfAMAggL_RLZRcYGIMCNHi7sxWTeG2Fexq37d93YYg6vO-2Eaq58pDj6Nwecq9NXfcBs_k63OLrPfe353yZ-Txe_5WX1xeXo-P76oHadsrBkH6ISTkkrElknBrx0DgUzbVqG3VijfdF414LBADaVMh74TtNWtayXbJfvr3CHFf5PPo1mF7PxyaXsfp2yohkaDEtgU-u0NvYlT6ku7olBSyhquijpYK5dizsl3ZkhhZdO9oWD-D2k2hyz863Po1K789St-Wa6A72uwChsHe-_iLeogDQPkXBkEpCXegDYPYXj637ix_07Eu3UeAck0jXg</recordid><startdate>20170701</startdate><enddate>20170701</enddate><creator>Puggioni, Paolo</creator><creator>Jelitai, Marta</creator><creator>Duguid, Ian</creator><creator>van Rossum, Mark C.W.</creator><general>MIT Press</general><general>MIT Press Journals, The</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope></search><sort><creationdate>20170701</creationdate><title>Extraction of Synaptic Input Properties in Vivo</title><author>Puggioni, Paolo ; Jelitai, Marta ; Duguid, Ian ; van Rossum, Mark C.W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c513t-3500f6c771722b3765dc306239ab82eaa68e4fe840c20f690220f2ef61b9bcb73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Brain</topic><topic>Constants</topic><topic>In vivo methods and tests</topic><topic>Knowledge</topic><topic>Locomotion</topic><topic>Measurement methods</topic><topic>Neural networks</topic><topic>Neurons</topic><topic>Particle size distribution</topic><topic>Properties (attributes)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Puggioni, Paolo</creatorcontrib><creatorcontrib>Jelitai, Marta</creatorcontrib><creatorcontrib>Duguid, Ian</creatorcontrib><creatorcontrib>van Rossum, Mark C.W.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Neural computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Puggioni, Paolo</au><au>Jelitai, Marta</au><au>Duguid, Ian</au><au>van Rossum, Mark C.W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Extraction of Synaptic Input Properties in Vivo</atitle><jtitle>Neural computation</jtitle><addtitle>Neural Comput</addtitle><date>2017-07-01</date><risdate>2017</risdate><volume>29</volume><issue>7</issue><spage>1745</spage><epage>1768</epage><pages>1745-1768</pages><issn>0899-7667</issn><eissn>1530-888X</eissn><abstract>Knowledge of synaptic input is crucial for understanding synaptic integration and ultimately neural function. However,
, the rates at which synaptic inputs arrive are high, so that it is typically impossible to detect single events. We show here that it is nevertheless possible to extract the properties of the events and, in particular, to extract the event rate, the synaptic time constants, and the properties of the event size distribution from
voltage-clamp recordings. Applied to cerebellar interneurons, our method reveals that the synaptic input rate increases from 600 Hz during rest to 1000 Hz during locomotion, while the amplitude and shape of the synaptic events are unaffected by this state change. This method thus complements existing methods to measure neural function
.</abstract><cop>One Rogers Street, Cambridge, MA 02142-1209, USA</cop><pub>MIT Press</pub><pmid>28562220</pmid><doi>10.1162/NECO_a_00975</doi><tpages>24</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0899-7667 |
| ispartof | Neural computation, 2017-07, Vol.29 (7), p.1745-1768 |
| issn | 0899-7667 1530-888X |
| language | eng |
| recordid | cdi_crossref_primary_10_1162_NECO_a_00975 |
| source | MIT Press Journals |
| subjects | Brain Constants In vivo methods and tests Knowledge Locomotion Measurement methods Neural networks Neurons Particle size distribution Properties (attributes) |
| title | Extraction of Synaptic Input Properties in Vivo |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T04%3A47%3A18IST&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=Extraction%20of%20Synaptic%20Input%20Properties%20in%20Vivo&rft.jtitle=Neural%20computation&rft.au=Puggioni,%20Paolo&rft.date=2017-07-01&rft.volume=29&rft.issue=7&rft.spage=1745&rft.epage=1768&rft.pages=1745-1768&rft.issn=0899-7667&rft.eissn=1530-888X&rft_id=info:doi/10.1162/NECO_a_00975&rft_dat=%3Cproquest_cross%3E1927113458%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=1927113458&rft_id=info:pmid/28562220&rfr_iscdi=true |