Abstract
This study evaluates the effects of spatial smoothing on inter-subject correlation (ISC) analysis for FMRI data using the traditional model based analysis as a reference. So far within ISC analysis the effects of smoothing have not been studied systematically and linear Gaussian filters with varying kernel widths have been used without better knowledge about the effects of filtering. Instead, with the traditional general linear model (GLM) based analysis, the effects of smoothing have been studied extensively.In this study, ISC and GLM analyses were computed with two experimental and one simulated block-design datasets. The test statistics and the detected activation areas were compared numerically with correlation and Dice similarity measures, respectively. The study verified that 1) the choice of the filter substantially affected the activations detected by ISC analysis, 2) the detected activations according to ISC and GLM methods were highly similar regardless of the smoothing kernel and 3) the effect of spatial smoothing was mildly smaller on ISC than GLM analysis. Our results indicated that a good selection of the full width at half maximum of the Gaussian smoothing kernel for ISC was slightly larger than double the original voxel size.
| Original language | English |
|---|---|
| Pages (from-to) | 1114-1124 |
| Number of pages | 11 |
| Journal | Magnetic Resonance Imaging |
| Volume | 32 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 1 Nov 2014 |
| MoE publication type | A1 Journal article-refereed |
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Keywords
- Block-design
- Filtering
- Functional magnetic resonance imaging
- FWHM
- Gaussian filter
- General linear model
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Effects of spatial smoothing on inter-subject correlation based analysis of FMRI. / Pajula, Juha; Tohka, Jussi.
In: Magnetic Resonance Imaging, Vol. 32, No. 9, 01.11.2014, p. 1114-1124.Research output: Contribution to journal › Article › Scientific › peer-review
TY - JOUR
T1 - Effects of spatial smoothing on inter-subject correlation based analysis of FMRI
AU - Pajula, Juha
AU - Tohka, Jussi
PY - 2014/11/1
Y1 - 2014/11/1
N2 - This study evaluates the effects of spatial smoothing on inter-subject correlation (ISC) analysis for FMRI data using the traditional model based analysis as a reference. So far within ISC analysis the effects of smoothing have not been studied systematically and linear Gaussian filters with varying kernel widths have been used without better knowledge about the effects of filtering. Instead, with the traditional general linear model (GLM) based analysis, the effects of smoothing have been studied extensively.In this study, ISC and GLM analyses were computed with two experimental and one simulated block-design datasets. The test statistics and the detected activation areas were compared numerically with correlation and Dice similarity measures, respectively. The study verified that 1) the choice of the filter substantially affected the activations detected by ISC analysis, 2) the detected activations according to ISC and GLM methods were highly similar regardless of the smoothing kernel and 3) the effect of spatial smoothing was mildly smaller on ISC than GLM analysis. Our results indicated that a good selection of the full width at half maximum of the Gaussian smoothing kernel for ISC was slightly larger than double the original voxel size.
AB - This study evaluates the effects of spatial smoothing on inter-subject correlation (ISC) analysis for FMRI data using the traditional model based analysis as a reference. So far within ISC analysis the effects of smoothing have not been studied systematically and linear Gaussian filters with varying kernel widths have been used without better knowledge about the effects of filtering. Instead, with the traditional general linear model (GLM) based analysis, the effects of smoothing have been studied extensively.In this study, ISC and GLM analyses were computed with two experimental and one simulated block-design datasets. The test statistics and the detected activation areas were compared numerically with correlation and Dice similarity measures, respectively. The study verified that 1) the choice of the filter substantially affected the activations detected by ISC analysis, 2) the detected activations according to ISC and GLM methods were highly similar regardless of the smoothing kernel and 3) the effect of spatial smoothing was mildly smaller on ISC than GLM analysis. Our results indicated that a good selection of the full width at half maximum of the Gaussian smoothing kernel for ISC was slightly larger than double the original voxel size.
KW - Block-design
KW - Filtering
KW - Functional magnetic resonance imaging
KW - FWHM
KW - Gaussian filter
KW - General linear model
UR - http://www.scopus.com/inward/record.url?scp=84921928093&partnerID=8YFLogxK
U2 - 10.1016/j.mri.2014.06.001
DO - 10.1016/j.mri.2014.06.001
M3 - Article
C2 - 24970023
AN - SCOPUS:84921928093
VL - 32
SP - 1114
EP - 1124
JO - Magnetic Resonance Imaging
JF - Magnetic Resonance Imaging
SN - 0730-725X
IS - 9
ER -