Model for a robust neural integrator.
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| Title: | Model for a robust neural integrator. |
|---|---|
| Authors: | Koulakov, Alexei A., Raghavachari, Sridhar, Kepecs, Adam, Lisman, John E. |
| Source: | Nature Neuroscience. Aug2002, Vol. 5 Issue 8, p775. 8p. |
| Subjects: | Neural circuitry, Short-term memory |
| Abstract: | Integrator circuits in the brain show persistent firing that reflects the sum of previous excitatory and inhibitory inputs from external sources. Integrator circuits have been implicated in parametric working memory, decision making and motor control. Previous work has shown that stable integrator function can be achieved by an excitatory recurrent neural circuit, provided synaptic strengths are tuned with extreme precision (better than 1% accuracy). Here we show that integrator circuits can function without fine tuning if the neuronal units have bistable properties. Two specific mechanisms of bistability are analyzed, one based on local recurrent excitation, and the other on the voltage-dependence of the NMDA (N-methyl-D-aspartate) channel. Neither circuit requires fine tuning to perform robust integration, and the latter actually exploits the variability of neuronal conductances. [ABSTRACT FROM AUTHOR] |
| Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 9511747 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Model for a robust neural integrator. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Koulakov%2C+Alexei+A%2E%22">Koulakov, Alexei A.</searchLink><br /><searchLink fieldCode="AR" term="%22Raghavachari%2C+Sridhar%22">Raghavachari, Sridhar</searchLink><br /><searchLink fieldCode="AR" term="%22Kepecs%2C+Adam%22">Kepecs, Adam</searchLink><br /><searchLink fieldCode="AR" term="%22Lisman%2C+John+E%2E%22">Lisman, John E.</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Nature+Neuroscience%22">Nature Neuroscience</searchLink>. Aug2002, Vol. 5 Issue 8, p775. 8p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Neural+circuitry%22">Neural circuitry</searchLink><br /><searchLink fieldCode="DE" term="%22Short-term+memory%22">Short-term memory</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Integrator circuits in the brain show persistent firing that reflects the sum of previous excitatory and inhibitory inputs from external sources. Integrator circuits have been implicated in parametric working memory, decision making and motor control. Previous work has shown that stable integrator function can be achieved by an excitatory recurrent neural circuit, provided synaptic strengths are tuned with extreme precision (better than 1% accuracy). Here we show that integrator circuits can function without fine tuning if the neuronal units have bistable properties. Two specific mechanisms of bistability are analyzed, one based on local recurrent excitation, and the other on the voltage-dependence of the NMDA (N-methyl-D-aspartate) channel. Neither circuit requires fine tuning to perform robust integration, and the latter actually exploits the variability of neuronal conductances. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=9511747 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1038/nn893 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 775 Subjects: – SubjectFull: Neural circuitry Type: general – SubjectFull: Short-term memory Type: general Titles: – TitleFull: Model for a robust neural integrator. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Koulakov, Alexei A. – PersonEntity: Name: NameFull: Raghavachari, Sridhar – PersonEntity: Name: NameFull: Kepecs, Adam – PersonEntity: Name: NameFull: Lisman, John E. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2002 Type: published Y: 2002 Identifiers: – Type: issn-print Value: 10976256 Numbering: – Type: volume Value: 5 – Type: issue Value: 8 Titles: – TitleFull: Nature Neuroscience Type: main |
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