liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Reducing inter-subject anatomical variation: Effect of normalization method on sensitivity of functional magnetic resonance imaging data anaysis in auditory cortex and the superior temporal region.
Queen’s University, Kingston, ON, Canada.
Queen’s University, Kingston, ON, Canada.
Queen’s University, Kingston, ON, Canada.
Queen’s University, Kingston, ON, Canada.
Show others and affiliations
2009 (English)In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 47, no 4, 1522-1531 p.Article in journal (Refereed) Published
Abstract [en]

Conventional group analysis of functional MRI (fMRI) data usually involves spatial alignment of anatomy across participants by registering every brain image to an anatomical reference image. Due to the high degree of inter-subject anatomical variability, a low-resolution average anatomical model is typically used as the target template, and/or smoothing kernels are applied to the fMRI data to increase the overlap among subjects’ image data. However, such smoothing can make it difficult to resolve small regions such as subregions of auditory cortex when anatomical morphology varies among subjects. Here, we use data from an auditory fMRI study to show that using a high-dimensional registration technique (HAMMER) results in an enhanced functional signal-to-noise ratio (fSNR) for functional data analysis within auditory regions, with more localized activation patterns. The technique is validated against DARTEL, a high-dimensional diffeomorphic registration, as well as against commonly used low-dimensional normalization techniques such as the techniques provided with SPM2 (cosine basis functions) and SPM5 (unified segmentation) software packages. We also systematically examine how spatial resolution of the template image and spatial smoothing of the functional data affect the results. Only the high-dimensional technique (HAMMER) appears to be able to capitalize on the excellent anatomical resolution of a single-subject reference template, and, as expected, smoothing increased fSNR, but at the cost of spatial resolution. In general, results demonstrate significant improvement in fSNR using HAMMER compared to analysis after normalization using DARTEL, or conventional normalization such as cosine basis function and unified segmentation in SPM, with more precisely localized activation foci, at least for activation in the region of auditory cortex.

Place, publisher, year, edition, pages
2009. Vol. 47, no 4, 1522-1531 p.
National Category
Psychology
Identifiers
URN: urn:nbn:se:liu:diva-78208DOI: 10.1016/j.neuroimage.2009.05.047OAI: oai:DiVA.org:liu-78208DiVA: diva2:531713
Available from: 2012-06-07 Created: 2012-06-07 Last updated: 2017-12-07

Open Access in DiVA

No full text

Other links

Publisher's full text

Authority records BETA

Johnsrude, Ingrid

Search in DiVA

By author/editor
Johnsrude, Ingrid
In the same journal
NeuroImage
Psychology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 65 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf