Academic Journal
Προβολή σε EDS

Neuronal arithmetic.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Neuronal arithmetic.
Συγγραφείς: Silver, R. Angus1 a.silver@ucl.ac.uk
Πηγή: Nature Reviews Neuroscience. Jul2010, Vol. 11 Issue 7, p474-489. 16p. 1 Diagram, 1 Graph.
Θεματικοί όροι: *Brain -- Mathematical models, *Neural transmission, *Biological neural networks, *Arithmetic, *Neuroplasticity, *Brain research, *Brain physiology, *Neural physiology, *Dendritic cells, *Mathematics, *Neurophysiology, *Research funding
Περίληψη: The vast computational power of the brain has traditionally been viewed as arising from the complex connectivity of neural networks, in which an individual neuron acts as a simple linear summation and thresholding device. However, recent studies show that individual neurons utilize a wealth of nonlinear mechanisms to transform synaptic input into output firing. These mechanisms can arise from synaptic plasticity, synaptic noise, and somatic and dendritic conductances. This tool kit of nonlinear mechanisms confers considerable computational power on both morphologically simple and more complex neurons, enabling them to perform a range of arithmetic operations on signals encoded ina variety of different ways. [ABSTRACT FROM AUTHOR]
Βάση Δεδομένων: Academic Search Index
FullText Text:
  Availability: 0
Header DbId: asx
DbLabel: Academic Search Index
An: 51485886
RelevancyScore: 1204
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 1203.7705078125
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Neuronal arithmetic.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Silver%2C+R%2E+Angus%22">Silver, R. Angus</searchLink><relatesTo>1</relatesTo><i> a.silver@ucl.ac.uk</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Nature+Reviews+Neuroscience%22">Nature Reviews Neuroscience</searchLink>. Jul2010, Vol. 11 Issue 7, p474-489. 16p. 1 Diagram, 1 Graph.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Brain+--+Mathematical+models%22">Brain -- Mathematical models</searchLink><br />*<searchLink fieldCode="DE" term="%22Neural+transmission%22">Neural transmission</searchLink><br />*<searchLink fieldCode="DE" term="%22Biological+neural+networks%22">Biological neural networks</searchLink><br />*<searchLink fieldCode="DE" term="%22Arithmetic%22">Arithmetic</searchLink><br />*<searchLink fieldCode="DE" term="%22Neuroplasticity%22">Neuroplasticity</searchLink><br />*<searchLink fieldCode="DE" term="%22Brain+research%22">Brain research</searchLink><br />*<searchLink fieldCode="DE" term="%22Brain+physiology%22">Brain physiology</searchLink><br />*<searchLink fieldCode="DE" term="%22Neural+physiology%22">Neural physiology</searchLink><br />*<searchLink fieldCode="DE" term="%22Dendritic+cells%22">Dendritic cells</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematics%22">Mathematics</searchLink><br />*<searchLink fieldCode="DE" term="%22Neurophysiology%22">Neurophysiology</searchLink><br />*<searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The vast computational power of the brain has traditionally been viewed as arising from the complex connectivity of neural networks, in which an individual neuron acts as a simple linear summation and thresholding device. However, recent studies show that individual neurons utilize a wealth of nonlinear mechanisms to transform synaptic input into output firing. These mechanisms can arise from synaptic plasticity, synaptic noise, and somatic and dendritic conductances. This tool kit of nonlinear mechanisms confers considerable computational power on both morphologically simple and more complex neurons, enabling them to perform a range of arithmetic operations on signals encoded ina variety of different ways. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asx&AN=51485886
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1038/nrn2864
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 474
    Subjects:
      – SubjectFull: Brain -- Mathematical models
        Type: general
      – SubjectFull: Neural transmission
        Type: general
      – SubjectFull: Biological neural networks
        Type: general
      – SubjectFull: Arithmetic
        Type: general
      – SubjectFull: Neuroplasticity
        Type: general
      – SubjectFull: Brain research
        Type: general
      – SubjectFull: Brain physiology
        Type: general
      – SubjectFull: Neural physiology
        Type: general
      – SubjectFull: Dendritic cells
        Type: general
      – SubjectFull: Mathematics
        Type: general
      – SubjectFull: Neurophysiology
        Type: general
      – SubjectFull: Research funding
        Type: general
    Titles:
      – TitleFull: Neuronal arithmetic.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Silver, R. Angus
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: Jul2010
              Type: published
              Y: 2010
          Identifiers:
            – Type: issn-print
              Value: 1471003X
          Numbering:
            – Type: volume
              Value: 11
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Nature Reviews Neuroscience
              Type: main
ResultId 1