Raw fMRI data: prospective study of MR MinMo efficacy

In the present study, we test the efficacy of a new head motion reduction device called “MR-MinMo” (Patent number GB 2205139.5 filed on 07 April 2022). This device has been designed to address the shortcomings of previous approaches and to offer a general solution to reducing head motion and discomfort during both clinical and research MRI scanning. Two separate studies will be conducted. The first is a new experimental study (Study 1: Active Head Motion Study) where we use the motion registration output from whole-head EPI to measure the efficacy of the MR-MinMo device in reducing head displacements during cued body movements and during short movie watching. Using a within-subjects design, we compare MR-MinMo performance to that of widely-used head cushions. In the second study (Study 2: Retrospective Comparison of MR-MinMo Efficacy), we utilize two large pre-existing fMRI datasets (originally acquired for different purposes) to test whether the MR-MinMo device reduces head movement in long fMRI experiments with healthy adults. In the first dataset, participants (N=84) watched different movies using standard padding (without the “MR-MinMo” device). In the second dataset, participants (N=40) watched a movie with the “MR-MinMo” device. The comparison of these two datasets allows us to assess whether the MR-MinMo device reduces the degree of small head movements, and long term positional drift. This type of fMRI data is increasingly of interest for clinical and research purposes, and analyses using such data have been shown to be particularly sensitive to subtle head motion. In both studies, we expect to see less head movement in the condition where “MR-MinMo” was used compared, to when loose comfortable head cushions were used. The device was developed by engineers and researchers at UCL, Kings College London, and Birkbeck College with primary support from the National Institute for Heath Research i4i programme, grant NIHR204201.The prereg protocol is available on OSF: https://osf.io/a6qbu/files/ujkt4