A complex way to compute fMRI activation
In functional magnetic resonance imaging, voxel time courses after Fourier or non-Fourier “image reconstruction” are complex valued as a result of phase imperfections due to magnetic field inhomogeneities. Nearly all fMRI studies derive functional “activation” based on magnitude voxel time courses [...
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| Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2004-11, Vol.23 (3), p.1078-1092 |
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| creator | Rowe, Daniel B. Logan, Brent R. |
| description | In functional magnetic resonance imaging, voxel time courses after Fourier or non-Fourier “image reconstruction” are complex valued as a result of phase imperfections due to magnetic field inhomogeneities. Nearly all fMRI studies derive functional “activation” based on magnitude voxel time courses [Bandettini, P., Jesmanowicz, A., Wong, E., Hyde, J.S., 1993. Processing strategies for time-course data sets in functional MRI of the human brain. Magn. Reson. Med. 30 (2): 161-173 and Cox, R.W., Jesmanowicz, A., Hyde, J.S., 1995. Real-time functional magnetic resonance imaging. Magn. Reson. Med. 33 (2): 230-236]. Here, we propose to directly model the entire complex or bivariate data rather than just the magnitude-only data. A nonlinear multiple regression model is used to model activation of the complex signal, and a likelihood ratio test is derived to determine activation in each voxel. We investigate the performance of the model on a real dataset, then compare the magnitude-only and complex models under varying signal-to-noise ratios in a simulation study with varying activation contrast effects. |
| doi_str_mv | 10.1016/j.neuroimage.2004.06.042 |
| format | Article |
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| subjects | Algorithms Brain Mapping Derivatives Efferent Pathways - physiology Fingers - physiology Fourier Analysis Fourier transforms Functional magnetic resonance imaging Humans Hypotheses Hypothesis testing Image Processing, Computer-Assisted - statistics & numerical data Likelihood Functions Magnetic field inhomogeneities Magnetic Resonance Imaging - statistics & numerical data Models, Statistical Motor Cortex - physiology Noise Nonlinear Dynamics Voxel time courses |
| title | A complex way to compute fMRI activation |
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