Modeling nucleus accumbens
Nucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and...
Gespeichert in:
| Veröffentlicht in: | Journal of computational neuroscience 2021-02, Vol.49 (1), p.21-35 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 35 |
|---|---|
| container_issue | 1 |
| container_start_page | 21 |
| container_title | Journal of computational neuroscience |
| container_volume | 49 |
| creator | Elibol Rahmi Şengör, Neslihan Serap |
| description | Nucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and depression but also for developing therapeutic treatments for them. Building a computational model would expand our comprehension of nucleus accumbens. In this work, we are focusing on establishing a model of nucleus accumbens which has not been considered as much as dorsal striatum in computational neuroscience. We will begin by modeling the behavior of single cells and then build a holistic model of nucleus accumbens considering the effect of synaptic currents. We will verify the validity of the model by showing the consistency of simulation results with the empirical data. Furthermore, the simulation results reveal the joint effect of cortical stimulation and dopaminergic modulation on the activity of medium spiny neurons. This effect differentiates with the type of dopamine receptors. |
| doi_str_mv | 10.1007/s10827-020-00769-y |
| format | Article |
| fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2488036788</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2488036788</sourcerecordid><originalsourceid>FETCH-proquest_journals_24880367883</originalsourceid><addsrcrecordid>eNqNirsOgjAUQG-MJuLjB5hInKu3rbSX2Whc3NgJ1mokWJRrB_9eBj_A6eTkHIBU4loi2g1LJGUFKhSDmkJ8RpDI3GphyOoxJFioQuRa6inMmBtEJCsxgfTUXXx7D7csRNf6yFntXHycfeAFTK51y3754xxWh325O4pn372i53fVdLEPQ6rUlgi1sUT6v-sLbqoyHw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2488036788</pqid></control><display><type>article</type><title>Modeling nucleus accumbens</title><source>SpringerLink Journals - AutoHoldings</source><creator>Elibol Rahmi ; Şengör, Neslihan Serap</creator><creatorcontrib>Elibol Rahmi ; Şengör, Neslihan Serap</creatorcontrib><description>Nucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and depression but also for developing therapeutic treatments for them. Building a computational model would expand our comprehension of nucleus accumbens. In this work, we are focusing on establishing a model of nucleus accumbens which has not been considered as much as dorsal striatum in computational neuroscience. We will begin by modeling the behavior of single cells and then build a holistic model of nucleus accumbens considering the effect of synaptic currents. We will verify the validity of the model by showing the consistency of simulation results with the empirical data. Furthermore, the simulation results reveal the joint effect of cortical stimulation and dopaminergic modulation on the activity of medium spiny neurons. This effect differentiates with the type of dopamine receptors.</description><identifier>ISSN: 0929-5313</identifier><identifier>EISSN: 1573-6873</identifier><identifier>DOI: 10.1007/s10827-020-00769-y</identifier><language>eng</language><publisher>New York: Springer Nature B.V</publisher><subject>Addictions ; Animal behavior ; Animal memory ; Animal training ; Basal ganglia ; Caudate-putamen ; Cognitive ability ; Computational neuroscience ; Dopamine ; Dopamine receptors ; Ganglia ; Information processing ; Mental disorders ; Motivation ; Neostriatum ; Nervous system ; Nuclei (cytology) ; Nucleus accumbens ; Reinforcement ; Simulation ; Spiny neurons</subject><ispartof>Journal of computational neuroscience, 2021-02, Vol.49 (1), p.21-35</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Elibol Rahmi</creatorcontrib><creatorcontrib>Şengör, Neslihan Serap</creatorcontrib><title>Modeling nucleus accumbens</title><title>Journal of computational neuroscience</title><description>Nucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and depression but also for developing therapeutic treatments for them. Building a computational model would expand our comprehension of nucleus accumbens. In this work, we are focusing on establishing a model of nucleus accumbens which has not been considered as much as dorsal striatum in computational neuroscience. We will begin by modeling the behavior of single cells and then build a holistic model of nucleus accumbens considering the effect of synaptic currents. We will verify the validity of the model by showing the consistency of simulation results with the empirical data. Furthermore, the simulation results reveal the joint effect of cortical stimulation and dopaminergic modulation on the activity of medium spiny neurons. This effect differentiates with the type of dopamine receptors.</description><subject>Addictions</subject><subject>Animal behavior</subject><subject>Animal memory</subject><subject>Animal training</subject><subject>Basal ganglia</subject><subject>Caudate-putamen</subject><subject>Cognitive ability</subject><subject>Computational neuroscience</subject><subject>Dopamine</subject><subject>Dopamine receptors</subject><subject>Ganglia</subject><subject>Information processing</subject><subject>Mental disorders</subject><subject>Motivation</subject><subject>Neostriatum</subject><subject>Nervous system</subject><subject>Nuclei (cytology)</subject><subject>Nucleus accumbens</subject><subject>Reinforcement</subject><subject>Simulation</subject><subject>Spiny neurons</subject><issn>0929-5313</issn><issn>1573-6873</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNirsOgjAUQG-MJuLjB5hInKu3rbSX2Whc3NgJ1mokWJRrB_9eBj_A6eTkHIBU4loi2g1LJGUFKhSDmkJ8RpDI3GphyOoxJFioQuRa6inMmBtEJCsxgfTUXXx7D7csRNf6yFntXHycfeAFTK51y3754xxWh325O4pn372i53fVdLEPQ6rUlgi1sUT6v-sLbqoyHw</recordid><startdate>20210201</startdate><enddate>20210201</enddate><creator>Elibol Rahmi</creator><creator>Şengör, Neslihan Serap</creator><general>Springer Nature B.V</general><scope>3V.</scope><scope>7QO</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</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>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope></search><sort><creationdate>20210201</creationdate><title>Modeling nucleus accumbens</title><author>Elibol Rahmi ; Şengör, Neslihan Serap</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_24880367883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Addictions</topic><topic>Animal behavior</topic><topic>Animal memory</topic><topic>Animal training</topic><topic>Basal ganglia</topic><topic>Caudate-putamen</topic><topic>Cognitive ability</topic><topic>Computational neuroscience</topic><topic>Dopamine</topic><topic>Dopamine receptors</topic><topic>Ganglia</topic><topic>Information processing</topic><topic>Mental disorders</topic><topic>Motivation</topic><topic>Neostriatum</topic><topic>Nervous system</topic><topic>Nuclei (cytology)</topic><topic>Nucleus accumbens</topic><topic>Reinforcement</topic><topic>Simulation</topic><topic>Spiny neurons</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Elibol Rahmi</creatorcontrib><creatorcontrib>Şengör, Neslihan Serap</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of computational neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Elibol Rahmi</au><au>Şengör, Neslihan Serap</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling nucleus accumbens</atitle><jtitle>Journal of computational neuroscience</jtitle><date>2021-02-01</date><risdate>2021</risdate><volume>49</volume><issue>1</issue><spage>21</spage><epage>35</epage><pages>21-35</pages><issn>0929-5313</issn><eissn>1573-6873</eissn><abstract>Nucleus accumbens is part of the neural structures required for reward based learning and cognitive processing of motivation. Understanding its cellular dynamics and its role in basal ganglia circuits is important not only in diagnosing behavioral disorders and psychiatric problems as addiction and depression but also for developing therapeutic treatments for them. Building a computational model would expand our comprehension of nucleus accumbens. In this work, we are focusing on establishing a model of nucleus accumbens which has not been considered as much as dorsal striatum in computational neuroscience. We will begin by modeling the behavior of single cells and then build a holistic model of nucleus accumbens considering the effect of synaptic currents. We will verify the validity of the model by showing the consistency of simulation results with the empirical data. Furthermore, the simulation results reveal the joint effect of cortical stimulation and dopaminergic modulation on the activity of medium spiny neurons. This effect differentiates with the type of dopamine receptors.</abstract><cop>New York</cop><pub>Springer Nature B.V</pub><doi>10.1007/s10827-020-00769-y</doi></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0929-5313 |
| ispartof | Journal of computational neuroscience, 2021-02, Vol.49 (1), p.21-35 |
| issn | 0929-5313 1573-6873 |
| language | eng |
| recordid | cdi_proquest_journals_2488036788 |
| source | SpringerLink Journals - AutoHoldings |
| subjects | Addictions Animal behavior Animal memory Animal training Basal ganglia Caudate-putamen Cognitive ability Computational neuroscience Dopamine Dopamine receptors Ganglia Information processing Mental disorders Motivation Neostriatum Nervous system Nuclei (cytology) Nucleus accumbens Reinforcement Simulation Spiny neurons |
| title | Modeling nucleus accumbens |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T14%3A02%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Modeling%20nucleus%20accumbens&rft.jtitle=Journal%20of%20computational%20neuroscience&rft.au=Elibol%20Rahmi&rft.date=2021-02-01&rft.volume=49&rft.issue=1&rft.spage=21&rft.epage=35&rft.pages=21-35&rft.issn=0929-5313&rft.eissn=1573-6873&rft_id=info:doi/10.1007/s10827-020-00769-y&rft_dat=%3Cproquest%3E2488036788%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2488036788&rft_id=info:pmid/&rfr_iscdi=true |