Dear FSL experts,

I have run preprocessing with FEAT, single ICA estimation for every individual (n = 115). The next step would be to manual label the noisy IC for every single participant but I have found two problems.

1. It is being hard for me to decide as looking at the power spectrum and at the activations, there is a lot of noisy, mainly related with movement. I thought there was no task or signal related to the task. Then I run group ICA to see if there was any pattern and I see that the first component of the group ica output was the task, clearly defined in the timeseries and time fit line and in the power spectrum as well. I cannot pick the components from there, as I have to denoise every single participant prior to run group ICA. My question is, how could I denoise my participants so I can get clearer IC?

2. Also, the dimensionality estimation for every participant is really high and I wonder if there is any other way to estimate the dimensionality for every participant. I know that it is not recommended to select the number of IC at this stage, but I do not see the need to estimate so many IC for every single participant.

I would much appreciate any help on this.

Yours sincerely,

Rosalia