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Intersubject analysis of fMRI data using spatial normalization
ABSTRACTS
Intersubject Analysis of fMRI Data Using Spatial Normalization J . W . V a n M e t e r 1, G.F. Eden 2, J . S . K i p p e n h a n I and T.A. Zeffiro 1'3
1Sensor Systems, Inc, Sterling, VA, 2SFBI, NIMH, NIH, 3Laboratory of Diagnostic Radiology Research, OD, National Institutes of Health, Bethesda, MD Introduction
Most approaches to the analysis of functional magnetic resonance imaging (fMRI) datasets have employed single-subject statistical analysis. These provide no mechanism to test statistical hypotheses concerning the behavior of the subject group as a whole or for comparisons between subject groups. Anatomical response localization is usually accomplished by examining the location and extent of the observed signal change with reference to a coplanar image of higher resolution in which sulcal and gyral landmarks are easily identified. Although accurate, this approach limits the range of signal amplitude changes studied to those detectable in every subject and cannot take advantage of the increased sensitivity possible with intersubject averaging techniques. Spatial normalization of brain images to a common stereotaxic coordinate system allows intersubject statistical analysis. We describe a procedure for performing intersubject hypothesis testing with fMRI data and use this method to compare results with previous rCBF measurements made using PET ~'2. Methods Multislice fMRI data were acquired in 8 healthy volunteers using echo planar imaging (EPI) on a GE Signa 1.5T system with a 5" surface coil positioned at the occiput. Fourteen contiguous 5ram slices (32cm FOV, 64x64 matrix, 40 msec TE) were collected in 2 sec., resulting in volumes of 5ram cubic voxels. In the control condition the subject viewed a fixation point. In the visual stimulation condition an 8Hz reversing red and black checkerboard (1.7 cycles/deg) was projected with the fixation point. Three cycles of 12 fixation and 12 visual stimulation scans were presented (ABABAB). To minimize temporal autocorrelation, data were collected with a 60 sec delay between time points. MEDx (Sensor Systems, Sterling, VA) was used for data analysis. First, signal intensity variations due to surface-coil sensitivity gradients were removed and scans realigned to compensate for interscan motion. Next, spatial normalization into the Talairach atlas space was performed for each subject using a high resolution SPGR MRI to identify the landmarks specifying rotational, translational, and second-order polynomial scaling transformations. The resulting transformation matrix was saved for later application to the EPI data. Next, a high-resolution MRI acquired coplanar to the EPI scans was registered to a high-resolution MRI using an intramodality automated registration algorithm. Prior to transforming the EPI scans into Talairach space, each EPI scan was registered to the first EPI scan. Each of the realigned EPI scans were then transformed into Talairach space by first applying the transformation matrix required to get the from coplanar SPGR MRI to the high resolution MRI and then applying the Talairach transformation matrix. The critical threshold was chosen as z > 5 . 4 (p < 10-9). There were 57,344 voxels in the EPI volume (64x64x14). Making a conservative correction for multiple comparisons this corresponds to a corrected probability of p < .001. Results Task-related activity was observed in the calcarine sulcus bilaterally, the fusiform gyrus bilaterally and the right lingual gyrus (Table 1). The spatial extent of the task-related signal increases were smaller than those commonly seen with PET rCBF studies due to the higher spatial resolution of MRI and the lack of spatial filtering in our spatial normalization. We found good correspondence between the local maxima coordinates detected in the calcarine cortex in this study and those reported in two previous rCBF studies using a similar stimulus ~'2, but completely different methods of Talairach spatial normalization. These results demonstrate that accurate spatial normalization of incomplete EPI brain volumes allows identification of task-related activity common to the entire group of subjects studied.
References 1. Fox,P.T. et al., J Neurosci, 7:913-922, 1987 2. Sergent,J., et al., Brain, 115:15-36,1992 Location
x
y
z
z-score
Calcarine Sulcus
-14 +09
-79 -80
+08 +06
5.81 5.79
Lingual Gyrus
+05
-78
-07
5.77
Fusiforrn Gyms
-22 +33
-103 -102
-12 -12
5.6 5.75
Table 1. Local maxima of reversing checkerboard versus fixation contrast in Talairach coordinates.
$104
Intersubject Analysis of fMRI Data Using Spatial Normalization J . W . V a n M e t e r 1, G.F. Eden 2, J . S . K i p p e n h a n I and T.A. Zeffiro 1'3
1Sensor Systems, Inc, Sterling, VA, 2SFBI, NIMH, NIH, 3Laboratory of Diagnostic Radiology Research, OD, National Institutes of Health, Bethesda, MD Introduction
Most approaches to the analysis of functional magnetic resonance imaging (fMRI) datasets have employed single-subject statistical analysis. These provide no mechanism to test statistical hypotheses concerning the behavior of the subject group as a whole or for comparisons between subject groups. Anatomical response localization is usually accomplished by examining the location and extent of the observed signal change with reference to a coplanar image of higher resolution in which sulcal and gyral landmarks are easily identified. Although accurate, this approach limits the range of signal amplitude changes studied to those detectable in every subject and cannot take advantage of the increased sensitivity possible with intersubject averaging techniques. Spatial normalization of brain images to a common stereotaxic coordinate system allows intersubject statistical analysis. We describe a procedure for performing intersubject hypothesis testing with fMRI data and use this method to compare results with previous rCBF measurements made using PET ~'2. Methods Multislice fMRI data were acquired in 8 healthy volunteers using echo planar imaging (EPI) on a GE Signa 1.5T system with a 5" surface coil positioned at the occiput. Fourteen contiguous 5ram slices (32cm FOV, 64x64 matrix, 40 msec TE) were collected in 2 sec., resulting in volumes of 5ram cubic voxels. In the control condition the subject viewed a fixation point. In the visual stimulation condition an 8Hz reversing red and black checkerboard (1.7 cycles/deg) was projected with the fixation point. Three cycles of 12 fixation and 12 visual stimulation scans were presented (ABABAB). To minimize temporal autocorrelation, data were collected with a 60 sec delay between time points. MEDx (Sensor Systems, Sterling, VA) was used for data analysis. First, signal intensity variations due to surface-coil sensitivity gradients were removed and scans realigned to compensate for interscan motion. Next, spatial normalization into the Talairach atlas space was performed for each subject using a high resolution SPGR MRI to identify the landmarks specifying rotational, translational, and second-order polynomial scaling transformations. The resulting transformation matrix was saved for later application to the EPI data. Next, a high-resolution MRI acquired coplanar to the EPI scans was registered to a high-resolution MRI using an intramodality automated registration algorithm. Prior to transforming the EPI scans into Talairach space, each EPI scan was registered to the first EPI scan. Each of the realigned EPI scans were then transformed into Talairach space by first applying the transformation matrix required to get the from coplanar SPGR MRI to the high resolution MRI and then applying the Talairach transformation matrix. The critical threshold was chosen as z > 5 . 4 (p < 10-9). There were 57,344 voxels in the EPI volume (64x64x14). Making a conservative correction for multiple comparisons this corresponds to a corrected probability of p < .001. Results Task-related activity was observed in the calcarine sulcus bilaterally, the fusiform gyrus bilaterally and the right lingual gyrus (Table 1). The spatial extent of the task-related signal increases were smaller than those commonly seen with PET rCBF studies due to the higher spatial resolution of MRI and the lack of spatial filtering in our spatial normalization. We found good correspondence between the local maxima coordinates detected in the calcarine cortex in this study and those reported in two previous rCBF studies using a similar stimulus ~'2, but completely different methods of Talairach spatial normalization. These results demonstrate that accurate spatial normalization of incomplete EPI brain volumes allows identification of task-related activity common to the entire group of subjects studied.
References 1. Fox,P.T. et al., J Neurosci, 7:913-922, 1987 2. Sergent,J., et al., Brain, 115:15-36,1992 Location
x
y
z
z-score
Calcarine Sulcus
-14 +09
-79 -80
+08 +06
5.81 5.79
Lingual Gyrus
+05
-78
-07
5.77
Fusiforrn Gyms
-22 +33
-103 -102
-12 -12
5.6 5.75
Table 1. Local maxima of reversing checkerboard versus fixation contrast in Talairach coordinates.
$104