Hello!

This is more of a conceptual question about MRI voxel signal issues. We have a dataset of ~150 subjects who completed a variety of tasks as well as resting state. Across the whole sample, signal just isn't very robust at the voxel level. Even for well established task paradigms (and even resting state), basic contrasts in expected regions are not surviving correction (expected regions emerge in task contrasts, but they ultimately don't survive correction). We're seeing this semi-weird phenomenon that while clusters of expected regions are certainly large enough to meet 3dClustSim thresholds, the voxel-wise significance is almost never achieved. Voxels in these large expected clusters are not passing even p<0.01. Obviously there are possible hardware concerns that could have contributed to the low SNR in voxels, but since we're past the point of fixing any of those issues, I'm wondering if there are any things we can do in preprocessing/alternative thresholding procedures we can use.

I'm not suggesting we do any p-hacking here, because there are clear effects in all of the tasks we have and in the predicted regions/direction (I'd also like to add these are not novel or complex tasks, for example one task is a go/no-go task with symbols, another is basic fear conditioning/extinction, and another is aversive picture viewing)... there's just something across the board about signal strength in this sample that is limiting "significance".

Any thoughts/advice are greatly appreciated!!

Carissa