Identification of non-linear models of neural activity in bold fmri

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    295 Downloads (Pure)


    Non-linear hemodynamic models express the BOLD signal as a nonlinear, parametric functional of the temporal sequence of local neural activity. Several models have been proposed for this neural activity. We identify one such parametric model by estimating the distribution of its parameters. These distributions are themselves stochastic, therefore we estimate their variance by epoch based leave-one-out cross validation, using a Metropolis-Hastings algorithm for sampling of the posterior parameter distribution.
    Original languageEnglish
    Title of host publication3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano
    Publication date2006
    ISBN (Print)0-7803-9576-X
    Publication statusPublished - 2006
    Event2006 IEEE International Symposium on Biomedical Imaging: Nano to Macro - Arlington, United States
    Duration: 6 Apr 20069 Apr 2006
    Conference number: 3


    Conference2006 IEEE International Symposium on Biomedical Imaging
    Country/TerritoryUnited States

    Bibliographical note

    Copyright: 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE


    • model comparison
    • BOLD fMRI
    • Bayes
    • learning
    • MCMC


    Dive into the research topics of 'Identification of non-linear models of neural activity in bold fmri'. Together they form a unique fingerprint.

    Cite this