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Sökning: WFRF:(Roudi Yasser) > (2009) > Ising model for neu...

  • Roudi, Yasser (författare)

Ising model for neural data : Model quality and approximate methods for extracting functional connectivity

  • Artikel/kapitelEngelska2009

Förlag, utgivningsår, omfång ...

  • 2009
  • printrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:DiVA.org:su-60058
  • https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-60058URI
  • https://doi.org/10.1103/PhysRevE.79.051915DOI

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  • Språk:engelska
  • Sammanfattning på:engelska

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  • Ämneskategori:ref swepub-contenttype
  • Ämneskategori:art swepub-publicationtype

Anmärkningar

  • authorCount :3
  • We study pairwise Ising models for describing the statistics of multineuron spike trains, using data from a simulated cortical network. We explore efficient ways of finding the optimal couplings in these models and examine their statistical properties. To do this, we extract the optimal couplings for subsets of size up to 200 neurons, essentially exactly, using Boltzmann learning. We then study the quality of several approximate methods for finding the couplings by comparing their results with those found from Boltzmann learning. Two of these methods-inversion of the Thouless-Anderson-Palmer equations and an approximation proposed by Sessak and Monasson-are remarkably accurate. Using these approximations for larger subsets of neurons, we find that extracting couplings using data from a subset smaller than the full network tends systematically to overestimate their magnitude. This effect is described qualitatively by infinite-range spin-glass theory for the normal phase. We also show that a globally correlated input to the neurons in the network leads to a small increase in the average coupling. However, the pair-to-pair variation in the couplings is much larger than this and reflects intrinsic properties of the network. Finally, we study the quality of these models by comparing their entropies with that of the data. We find that they perform well for small subsets of the neurons in the network, but the fit quality starts to deteriorate as the subset size grows, signaling the need to include higher-order correlations to describe the statistics of large networks.

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  • Tyrcha, JoannaStockholms universitet,Matematiska institutionen(Swepub:su)joanna (författare)
  • Hertz, John (författare)
  • Stockholms universitetMatematiska institutionen (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:Physical Review E. Statistical, Nonlinear, and Soft Matter Physics79:5, s. 51915-1539-37551550-2376

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Av författaren/redakt...
Roudi, Yasser
Tyrcha, Joanna
Hertz, John
Om ämnet
NATURVETENSKAP
NATURVETENSKAP
och Matematik
Artiklar i publikationen
Physical Review ...
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Stockholms universitet

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