PREPROCESSING STEPS IN fMRI: SMOOTHING
Year 2019,
, 161 - 171, 01.12.2019
Hacer Daşgın
Ali Yaman
,
Yılmaz Akdi
Abstract
Functional
magnetic resonance imaging is a technique with a primary and dominant effect in
the investigation of the cognitive functions of the brain since it has a
complex structure. In this study, data obtained from single subject was
examined. First statistical parametric mapping results were obtained after
applying the standard preprocessing steps with including smoothness. Spatial
smoothing was performed using a 3 mm Gaussian kernel which is twice of the
voxel size. Second, statistical parametric mapping results were obtained with
applying standard preprocessing steps without smoothing. The effects of these
two applications on the mapping results were compared for selected slices and
locations in terms of statistical and pattern.
References
- Ogawa, S.T., Lee, M., Kay, A.R. and Tank, D.W., Brain Magnetic Resonance Imaging with Contrast Dependent on Blood Oxygenation. Proc. NatI. Acad. Sci., Biophysics (87), (1990), 9868-9872.
- Ugurbil, K., Garwood, M., Hendrich, K., Hinke, R., Hu, X., Menon, R.S., Merkle, H., Ogawa, S. and Salmi, R., Imaging at High Magnetic Fields; Initial Experiences at 4 Tesla. Magn Reson Quarterly, (9), (1993), 259 – 277.
Kwong, K.K., Belliveau, J.W., Chesler, D.A., Goldberg, I.E., Weisskoff, R.M., Poncelet, B.P., Kennedy, D.N., Hoppel, B.E., Cohen, M.S. and Turner, R., Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc. Nadl. Acad. Sci., (89), (1992), 5675-5679.
- Huettel, S.A., Song, A.W. and McCarthy, G., Functional Magnetic Resonance Imaging, Second Edition. Sinauer Associates Inc, Sunderland, Massachusetts USA, 2008.
- Friston, K.J., Holmes, A.P., Poline, J.B., Grasby, P.J., Williams, S.C., Frackowiak, R.S. et al. Analysis of fMRI time-series revisited, Neuroimage, 2(1), 1995, 45–53.
- Worsley, K.J., Marrett, S., Neelin P, Vandal, A.C., Friston KJ, Evans AC. A unified statistical approach for determining significant signals in images of cerebral activation. Hum Brain Mapp, 4(1), (1996), 58–73.
- Filippi, M., fMRI Techniques and Protocols. Humana Press, 830, New York, 2009.
- Worsley, K. J. and Friston, K.J., Analysis of fMRI Time-Series Revisited Again, Academic Press Inc., Neuroimage 2, (1995), 173-181.
- Anonymous, SPM By members & collaborators of the Wellcome Trust Centre for Neuroimaging, http://www.fil.ion.ucl.ac.uk/spm/.
- Mikla, M., Mareček, R., Hluštíkc, P., Pavlicová, M., Drasticha, A., Chlebus, P., Brázdil, M., Krupaf, P., Effects of spatial smoothing on fMRI group inferences. Magnetic Resonance Imaging 26, (2008), 490–503.
- Friston, K. J., Josephs, O., Zarahn E and Poline, P., To Smooth or Not to Smooth? Bias and Efficiency in fMRI Time-Series Analysis, NeuroImage 12, (2000), 196–208.
- Wilke, M. and Lidzba, K., LI-tool: A new toolbox to assess lateralization in functional MR-data. Journal of Neuroscience of Methods, (163), (2007), 128–136.
Year 2019,
, 161 - 171, 01.12.2019
Hacer Daşgın
Ali Yaman
,
Yılmaz Akdi
References
- Ogawa, S.T., Lee, M., Kay, A.R. and Tank, D.W., Brain Magnetic Resonance Imaging with Contrast Dependent on Blood Oxygenation. Proc. NatI. Acad. Sci., Biophysics (87), (1990), 9868-9872.
- Ugurbil, K., Garwood, M., Hendrich, K., Hinke, R., Hu, X., Menon, R.S., Merkle, H., Ogawa, S. and Salmi, R., Imaging at High Magnetic Fields; Initial Experiences at 4 Tesla. Magn Reson Quarterly, (9), (1993), 259 – 277.
Kwong, K.K., Belliveau, J.W., Chesler, D.A., Goldberg, I.E., Weisskoff, R.M., Poncelet, B.P., Kennedy, D.N., Hoppel, B.E., Cohen, M.S. and Turner, R., Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc. Nadl. Acad. Sci., (89), (1992), 5675-5679.
- Huettel, S.A., Song, A.W. and McCarthy, G., Functional Magnetic Resonance Imaging, Second Edition. Sinauer Associates Inc, Sunderland, Massachusetts USA, 2008.
- Friston, K.J., Holmes, A.P., Poline, J.B., Grasby, P.J., Williams, S.C., Frackowiak, R.S. et al. Analysis of fMRI time-series revisited, Neuroimage, 2(1), 1995, 45–53.
- Worsley, K.J., Marrett, S., Neelin P, Vandal, A.C., Friston KJ, Evans AC. A unified statistical approach for determining significant signals in images of cerebral activation. Hum Brain Mapp, 4(1), (1996), 58–73.
- Filippi, M., fMRI Techniques and Protocols. Humana Press, 830, New York, 2009.
- Worsley, K. J. and Friston, K.J., Analysis of fMRI Time-Series Revisited Again, Academic Press Inc., Neuroimage 2, (1995), 173-181.
- Anonymous, SPM By members & collaborators of the Wellcome Trust Centre for Neuroimaging, http://www.fil.ion.ucl.ac.uk/spm/.
- Mikla, M., Mareček, R., Hluštíkc, P., Pavlicová, M., Drasticha, A., Chlebus, P., Brázdil, M., Krupaf, P., Effects of spatial smoothing on fMRI group inferences. Magnetic Resonance Imaging 26, (2008), 490–503.
- Friston, K. J., Josephs, O., Zarahn E and Poline, P., To Smooth or Not to Smooth? Bias and Efficiency in fMRI Time-Series Analysis, NeuroImage 12, (2000), 196–208.
- Wilke, M. and Lidzba, K., LI-tool: A new toolbox to assess lateralization in functional MR-data. Journal of Neuroscience of Methods, (163), (2007), 128–136.