- Email: [email protected]
On the anatomical resolution of group studies
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SYSTEMS, MULTISCALE
& MULTIMODAL
MAPPING
On the anatomical resolution of group studies Anders Ledberg* *Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden [email protected] Introduction Most brain imaging studies are so called group studies, meaning that data is pooled over a number of individuals. One potential problem with these studies is that the location and spatial extent of the detected activations are influenced by the anatomical and functional differences between subjects. To be able to properly interpret group studies it is important to have an estimate of how this between subject variability influences the results. The purpose of this study is to investigate the impact of the between subject anatomical variability on functional data. Simulated imaging data was created from cytoarchite&ually defined areas obtained from nine post mortem brains. The data was analyzed with standard methods. The analysis shows that activations originating from area 4 (primary motor cortex) are to a large extent OverIapping activations originating from area 3b (primary sotnatosensory cortex). Cytoarchitectual areas 4 (4a and 4p) and 3b were delimited in nine post mortem brains and subsequently transformed into a common anatomical space (l-4). From each MR image of the post mortem brains, simulated data were generated as follows: four “acans” with random values representing baseline, four “scans” with random values plus a signal added to the VOX& belonging to area 4 and four “scans” with random values plus a signal added to the voxels belonging to area 3b. In this way each “subject” had four baseline “scans”, four “scans” with activity in area 4 and four “scans” with activity in area 3b. The data was then filtered with a Gaussian kernel with FWHM of three times the voxel size (2~2x2 mm). This was done to mimic the smoothing normally applied in group studies. A fixed effects linear model, with task and subject as factors, was used to derive statistical images from the comparisons:(area 4)-(baseline) and (area 3b)-(baseline). Both cluster size and maximum voxel value statistics were used (5). The threshold for clustering was set to (p < 0.01). Results and Conclusion The figure shows the outlines of the activations superimposed on the template brain used in the normalizations, black is area 3b and white area 4. The activations from the two areas am to a large extent overlapping. If the chrster size statistic is used 67% of the activation from area 3b overlaps the activation from area 4 and 39% of the activation from area 4 overlaps the activation of area 3b. If the maximum voxel value statistic is used the overlap is reduced to 35% snd 5% respectively. In conclusion: The anatomical variability between subjects makes it difficult to draw conclusions about the exact anatomical location and extent of activations obtained in group studies. References 1. Schleicher A, Amunts K, Geyer S, Morosan P, Zilles K. Neuroimage. 1999 9:165-77. 2. Geyer S, Schleicher A, Zilles K. Neuroimage. 1999 10:63-83. 3. Geyer S, et al, Nature. 1996 382805-7. 4. Schormann T, Zilles K. Hum Brain Mapp. 1998;6:339-47. 5. Ledberg A, Hum Brain Mapp. 2000;9:143-55.
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SYSTEMS, MULTISCALE
& MULTIMODAL
MAPPING
On the anatomical resolution of group studies Anders Ledberg* *Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden [email protected] Introduction Most brain imaging studies are so called group studies, meaning that data is pooled over a number of individuals. One potential problem with these studies is that the location and spatial extent of the detected activations are influenced by the anatomical and functional differences between subjects. To be able to properly interpret group studies it is important to have an estimate of how this between subject variability influences the results. The purpose of this study is to investigate the impact of the between subject anatomical variability on functional data. Simulated imaging data was created from cytoarchite&ually defined areas obtained from nine post mortem brains. The data was analyzed with standard methods. The analysis shows that activations originating from area 4 (primary motor cortex) are to a large extent OverIapping activations originating from area 3b (primary sotnatosensory cortex). Cytoarchitectual areas 4 (4a and 4p) and 3b were delimited in nine post mortem brains and subsequently transformed into a common anatomical space (l-4). From each MR image of the post mortem brains, simulated data were generated as follows: four “acans” with random values representing baseline, four “scans” with random values plus a signal added to the VOX& belonging to area 4 and four “scans” with random values plus a signal added to the voxels belonging to area 3b. In this way each “subject” had four baseline “scans”, four “scans” with activity in area 4 and four “scans” with activity in area 3b. The data was then filtered with a Gaussian kernel with FWHM of three times the voxel size (2~2x2 mm). This was done to mimic the smoothing normally applied in group studies. A fixed effects linear model, with task and subject as factors, was used to derive statistical images from the comparisons:(area 4)-(baseline) and (area 3b)-(baseline). Both cluster size and maximum voxel value statistics were used (5). The threshold for clustering was set to (p < 0.01). Results and Conclusion The figure shows the outlines of the activations superimposed on the template brain used in the normalizations, black is area 3b and white area 4. The activations from the two areas am to a large extent overlapping. If the chrster size statistic is used 67% of the activation from area 3b overlaps the activation from area 4 and 39% of the activation from area 4 overlaps the activation of area 3b. If the maximum voxel value statistic is used the overlap is reduced to 35% snd 5% respectively. In conclusion: The anatomical variability between subjects makes it difficult to draw conclusions about the exact anatomical location and extent of activations obtained in group studies. References 1. Schleicher A, Amunts K, Geyer S, Morosan P, Zilles K. Neuroimage. 1999 9:165-77. 2. Geyer S, Schleicher A, Zilles K. Neuroimage. 1999 10:63-83. 3. Geyer S, et al, Nature. 1996 382805-7. 4. Schormann T, Zilles K. Hum Brain Mapp. 1998;6:339-47. 5. Ledberg A, Hum Brain Mapp. 2000;9:143-55.
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