Hi Monty
This is something common, patients move more. For this reason I suggest you do what others will and have suggested. You need to do scrubbing of the data as a preprocessing step. You can use the ART Toolbox or fmriqa.py for this. Or you can use fsl _motion_outliers for each subject and add the motion outliers into the model at the first level.
Then you can compare both analysis and see if your connectivity changes still apply. So you will have to do everything again but it is a good idea if the data was not scrubbed from the beginning.
Kind regards
Eduardo
El Friday, March 13, 2015, Monty Waite <
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Thanks Eduardo
What I have is a set of resting fMRI data between patient and control
I have run a dual regression and randomise between the two groups (unpaired t test) and that has shown altered connectivity between the groups
What I would like to be able to show is that this is unlikely to be a cause of increased head motion between the groups
If I look at the absolute RMS values for the two groups, there is a difference suggesting that the patients were moving more in the scanner (no surprise)
How can I add the MCFLIRT outputs to randomise as a voxel specific EV??
Thanking you as always
Monty
--
Eduardo A. Garza Villarreal, M.D., Ph.D.
- Investigador, Subdirección de Investigaciones Clínicas, Instituto Nacional de Psiquiatría.
- Catedrático, Consejo Nacional de Ciencia y Tecnología (CONACYT).
- Investigador Asociado, Center of Functionally Integrative Neuroscience, Universidad de Aarhus, Dinamarca.
- Profesor-Investigador, Servicio de Neurología, UANL.
- Coordinador, Unidad de Neurociencias, Centro de Investigación y Desarrollo en Ciencias de la Salud, UANL.
