Tuesday, June 27, 2017: 12:45 PM
Monday, June 26 & Tuesday, June 27
Johan Jansma1, Geert-Jan Rutten1
1Elisabeth-TweeSteden Hospital, Tilburg, Netherlands
In many fMRI studies, individual brain activity maps are averaged in order to test hypotheses at group-level. For this purpose, individual scans are spatially normalized to a brain model in a standard data space, often MNI space. Using this method, an informative group map can be created by averaging signals for each voxel separately. It has become common practice to test hypothesis in each voxel separately, using a mass univariate testing approach. Because of the high number of results that are generated (i.e. the number of tested voxels), test results are communicated in graphical form, and each voxel that shows a significant signal change is displayed on top of a standard anatomy. This visual illustration is typically combined with a table providing the MNI coordinates and t-statistic of the voxel with the highest test result within each region. This approach is attractive because it provides an intuitive and fairly complete overview of the results of a study. Unfortunately, scientifically speaking, this approach also has some important disadvantages, that are sometimes overlooked. The most important disadvantage is that the resolution at which the results are published is too high to provide quantitative information about all the tested data. The most important consequence is that it is not possible to objectively determine if an fMRI study replicates or falsifies previous studies. Another consequence is that this method limits the possibilities to quantitatively compare signal changes between different regions in the brain. Last, but not least, this approach limits the possibility to quantitatively combine results from different studies to build more complex theories.
We propose to introduce a system to quantitatively communicate group averaged fMRI results, by adding an extra layer to the MNI atlas, specifically designed for fMRI results. Starting at the MNI origin coordinate, the MNI brain is divided in isotropic regions of 20*20*20 mm (see figure 1). If needed, a region can be subdivided in 8 sub-regions of 10*10*10 mm, decoded A-H. This fMRI-MNI coordinate system can be used to communicate and replicate exact regions where a signal change was measured. Thus, it enables quantitative replication or falsification of previous fMRI studies, the combining quantitative results of several studies to build and test more complex cognitive models. We tested the potential value of this system on a dataset gathered in seven MRI centers in Europe. Scanners differed in brand (Philips, Siemens, GE) and field strength (1.5 – 3.0 T). Scans differed in repetition time (0.75 – 2.5 sec) as well as pulse sequence (PRESTO, EPI). Each center conducted a verb generation (VG) study in six subjects (M/V: 3/3). For each center, we compared the signal change in the left and right hemisphere in identical ROIs based on the proposed fMRI coordinate system ROIs were relevant for activity associated with Broca and its right hemisphere homologue (see figure 1, grey square, |t| > 5; N = 42).
In all 7 centers, we observed a significantly higher signal change in the left hemisphere compared to the right (p < 0.01; left hemisphere: 0.05%, right hemisphere: 0.52%, difference: 0.47%, sd: 0.07). Signal change differed more over centers than signal changes in the language task (motor: 1.15%, sd: 0.44; language:).
·Figure 1: fMRI coordinate system overlay on verb generation activation pattern (N = 42)verb gemneration
·Figure 2: signal change (SEM) in Broca and homologue right hemisphere for each site
We propose a new system to communicate group-averaged fMRI results that allows for quantitative comparison and verification of fMRI studies. Our multi-site study results confirm the potential value of this system. Signal changes measured with fMRI in identical regions appear to be highly reproducible over centers, even for small sample sizes. Our proposed system provides the possibility to quantitative compare, replicate, and falsify fMRI results, and can thus considerably aid in advancing the scientific quality of fMRI.
Higher Cognitive Functions:
Higher Cognitive Functions Other
BOLD fMRI 1
Brain Atlases 2
Databasing and Data Sharing
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multisite: 1.5 - 3.0T
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