Constraining the general linear model for sensible hemodynamic response function waveforms.
We propose a method to do constrained parameter estimation and inference from neuroimaging data using general linear model (GLM). Constrained approach precludes unrealistic hemodynamic response function (HRF) estimates to appear at the outcome of the GLM analysis. The permissible ranges of waveform...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 46; no. 8; pp. 779 - 788 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Aug2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105626369&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105626369 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Aug2008 vid: 46 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105626369 NLM18427851 2010157211 10.1007/s11517-008-0347-6 NLM18427851 105626369 ppf: 779 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Constraining the general linear model for sensible hemodynamic response function waveforms. aug: au: Ciftçi K Sankur B Kahya YP Akin A Ciftçi, Koray Sankur, Bülent Kahya, Yasemin P Akin, Ata affil: Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Turkey sug: subj: Hemodynamics Linear Regression Signal Processing, Computer Assisted Adult Female Frontal Lobe Physiology Male Probability Spectroscopy, Near-Infrared Methods Human Adult: 19-44 years Female Male ab: We propose a method to do constrained parameter estimation and inference from neuroimaging data using general linear model (GLM). Constrained approach precludes unrealistic hemodynamic response function (HRF) estimates to appear at the outcome of the GLM analysis. The permissible ranges of waveform parameters were determined from the study of a repertoire of plausible waveforms. These parameter intervals played the role of prior distributions in the subsequent Bayesian analysis of the GLM, and Gibbs sampling was used to derive posterior distributions. The method was applied to artificial null data and near infrared spectroscopy (NIRS) data. The results show that constraining the GLM eliminates unrealistic HRF waveforms and decreases false activations, without affecting the inference for "realistic" activations, which satisfy the constraints. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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