On Jan 30, 2015, at 5:52 AM, Stephen Smith <[log in to unmask]> wrote:Hi DavidIf I understand you correctly, it seems that the group-ICA spatial-maps might not necessarily map well onto distinct areas of interest wrt the task activation? I'm not quite sure I follow the details.....:On 30 Jan 2015, at 05:23, David V. Smith <[log in to unmask]> wrote:Hello,
I'm having trouble interpreting how my independent component maps relate to my task.
I used the dual_regression script to obtain subject-specific time courses for all the components in my group ICA. The component/network I care about in the group ICA contains voxels that are significantly negative and voxels that are significantly positive (in roughly equal proportions). When I regress the dr_stage1 time courses onto my task design matrices (which have two main conditions), the positive/negative component of interest is significantly associated with both conditions, but the association is much stronger for one condition compared to the other condition....right - don't forget that when you have multiple conditions, there's no guarantee (or necessarily even expecation) that ICA will separate out components according to those different conditions/contrasts - as they are likely to be spatially quite overlapping if they are similar tasks.You might want to start by looking at how the ICA maps relate to maps from FEAT GLM analysis?Cheers.
It seems like the difference I'm observing could arise due to how the conditions modulate a) the positive portion of the component, b) the negative portion of the component, or c) both the positive and negative portion of the component. Is that correct? If so, what sort of tests could I run to distinguish between these alternatives?
Thanks!
David
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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director, Oxford University FMRIB Centre
FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
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