Endre søk
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Quantifying neurotransmission reliability through metrics-based information analysis
Université Pierre et Marie Curie, Paris.
Umeå universitet, Medicinska fakulteten, Institutionen för integrativ medicinsk biologi (IMB), Fysiologi.
Université Pierre et Marie Curie, Paris.
2011 (engelsk)Inngår i: Neural Computation, ISSN 0899-7667, E-ISSN 1530-888X, Vol. 23, nr 4, s. 852-881Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We set forth an information-theoretical measure to quantify neurotransmission reliability while taking into full account the metrical properties of the spike train space. This parametric information analysis relies on similarity measures induced by the metrical relations between neural responses as spikes flow in. Thus, in order to assess the entropy, the conditional entropy, and the overall information transfer, this method does not require any a priori decoding algorithm to partition the space into equivalence classes. It therefore allows the optimal parameters of a class of distances to be determined with respect to information transmission. To validate the proposed information-theoretical approach, we study precise temporal decoding of human somatosensory signals recorded using microneurography experiments. For this analysis, we employ a similarity measure based on the Victor-Purpura spike train metrics. We show that with appropriate parameters of this distance, the relative spike times of the mechanoreceptors? responses convey enough information to perform optimal discrimination?defined as maximum metrical information and zero conditional entropy?of 81 distinct stimuli within 40 ms of the first afferent spike. The proposed information-theoretical measure proves to be a suitable generalization of Shannon mutual information in order to consider the metrics of temporal codes explicitly. It allows neurotransmission reliability to be assessed in the presence of large spike train spaces (e.g., neural population codes) with high temporal precision.

sted, utgiver, år, opplag, sider
2011. Vol. 23, nr 4, s. 852-881
HSV kategori
Identifikatorer
URN: urn:nbn:se:umu:diva-41342DOI: 10.1162/NECO_a_00099PubMedID: 21222522OAI: oai:DiVA.org:umu-41342DiVA, id: diva2:405705
Tilgjengelig fra: 2011-03-23 Laget: 2011-03-23 Sist oppdatert: 2018-06-08bibliografisk kontrollert

Open Access i DiVA

Fulltekst mangler i DiVA

Andre lenker

Forlagets fulltekstPubMed

Søk i DiVA

Av forfatter/redaktør
Johansson, Roland S
Av organisasjonen
I samme tidsskrift
Neural Computation

Søk utenfor DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric

doi
pubmed
urn-nbn
Totalt: 267 treff
RefereraExporteraLink to record
Permanent link

Direct link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf