A Rat fMRI multi-center study
In this international collaborative project, we seek to gather the rodent imaging community toward performing a rat fMRI multi-center comparison, within the same template as Grandjean et al. NIMG 2020. We want to examine functional connectivity (FC) parameter distribution at the population level within key networks (somatosensory and default-mode network) of the rat brain, as well as establish connectivity sensitivity and specificity in the collected datasets. To do so, we will gather rat BOLD fMRI datasets from individual labs (n=10, any protocol). In a desire to push further, we seek to obtain additional datasets pertaining to within-laboratory test-retest (i.e. scans that were collected in the same control animals within a period of 6 months or less), as well as datasets in sensory-stimulation fMRI (limb or whisker stimulation). Finally, we would like to organize a standardized data collection arm of this study for laboratories interested. This would include the de-novo acquisition of a dataset (n=10) using predefined, mutually-agreed, and standardized parameters consistent across all participating laboratories. The end-goal is to make this as an available resource to researchers and to publish an extensive description of the collective dataset in a peer-reviewed journal.
1. Environment preparation
2. Asset preparation
3. Dataset description
4. Preprocessing code
5. Quality control
6. Analysis tSNR and motion
7. Analysis seed-based analysis
8. Analysis de novo datasets
License and permissions
Collaborative model and project details
Preregistration DOI: 10.17605/OSF.IO/EMQ4B
Lab webpage
Twitter
RABIES, rodent fMRI preprocessing and analysis
BkrRaw, convert bruker data to BIDS format
SIGMA template
SAMRI, another rodent fMRI preprocessing pipeline
nirodent, a toolbox for rodent MRI processing
11.12.2020 - Use SIGMA template instead of WHS
11.04.2021 - Changed analysis to Python
11.04.2021 - Analysis using tSNR instead of SNR, because former is readily output in RABIES.
11.04.2021 - reduced number volumes -> 1200 for ds 1001 (too long preprocessing time)
11.04.2021 - cropped FOV for ds 1029, 1030, 1036 (improve registrations)
12.04.2021 - Reduced number of seeds to S1bf, MOp, CPu, ACA because not all dataset had coverage along A-P axis, and this seemed to cause RABIES crashes. (spoiler, it wasn't the reason)
06.06.2021 - cropped FOV for ds 1023, 1038, 1039
22.11.2021 - added dataset 01051 even though it lacked anatomicals. Generated pseudo-anatomicals using motion-corrected temporally averaged EPI.
09.12.2021 - cropped FOV for sub-0100106, sub-0100107, sub-0100108, sub-0100109, sub-0100306, sub-0100400, sub-0100401, sub-0100404, sub-0100505, sub-0100602, sub-0100603, sub-0100608, sub-0100805
12.12.2021 - replaced T1 anat with motion-corrected temporally averaged EPI for ds 1021. cropped FOV for ds 1015, 1017, 1021, 1031, 1043, 1044, 1048, 1050. Additionally cropped FOV for sub-0101007, sub-0101202, sub-0101305, sub-0101307, sub-0101309, sub-0101607, sub-0101608, sub-0102203, sub-0102303, sub-0102306, sub-0102307, sub-0102502, sub-0102600, sub-0102601, sub-0102605, sub-0102708, sub-0103004, sub-0103006, sub-0103409, sub-0103700, sub-0103801, sub-0103906, sub-0104104, sub-0104106, sub-0104600, sub-0104601, sub-0104604, sub-0104605, sub-0105201, sub-0105206, sub-0105207,sub-0105208, sub-0105302, sub-0105303, sub-0105304, sub-0105308