Thank you Steve!
Yes - I was speaking about the group-ICA spatial maps. I have noticed that I can threshold the group-ICA spatial maps for each component at a much higher level than other ICAs that I have done on non-HCP data. Your explanation about strong CNR makes sense. I am still a little unclear about the relationship of instantiating a strong threshold on the group-ICA spatial maps relative to the time series. For example, if I threshold a component's spatial map at a lower level, more areas of activation will naturally show up. Does the time series represent all voxels in the spatial map when there is no thresholding? Or, does the time series represent only the strongest voxels of activation? Thus, when I apply a strong threshold for image presentation to "clean up" the image a little, does the time series also include those voxels that are not visible due to high thresholding? Thanks again! Jason ________________________________ From: Stephen Smith <st...@fmrib.ox.ac.uk> Sent: Saturday, April 11, 2015 3:29 AM To: Nomi, Jason Cc: hcp-users@humanconnectome.org Subject: Re: [HCP-Users] Parcellated Connectome Hi - there are many factors that affect overall scaling - more below: On 10 Apr 2015, at 14:22, Nomi, Jason <jxn...@miami.edu<mailto:jxn...@miami.edu>> wrote: Dear Experts, I have noticed that the time-series for individual subjects from the dual regression output in the parcellated connectome (100 comp ICA) has a much larger range than I am used to seeing. The range for time series values are approximately -800 to 800 while dual regression outputs that I have conducted myself are usually around -5 to 5. I also notice that I can set the threshold much higher for the independent components when isolating activation compared to dual regression analyses that I have done myself. This "cleans up" the component representation substantially. My questions are: 1) Is there a particular reason for this large increase in ranges? In this case most likely because we set the max of the group maps used in dualreg stage 1 to be 1. This causes output timeseries to have larger scaling - but the overall scaling is arbitrary anyway. 2) Does the larger threshold for component activation have any influence on the time series that is being produced? Does the time series from the dual regression output only represent the areas from the independent component with the most intense activation? I would like to ensure that my presentation of component images using a much higher threshold is actually representative of the time series that I am analyzing. Do you mean the group-ICA spatial maps or maps output by diualreg stage 2? The group-ICA maps have high peaks (compared with the background scaling) for a couple of reasons: a) because there are so many subjects being combined that the ICA components are strong, and b) the group-PCA reduction has removed a lot of unstructured noise before the PCA+ICA step. But despite the maps having strong "CNR", they are still valid maps. Cheers, Steve. Thanks! Jason _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org<mailto:HCP-Users@humanconnectome.org> http://lists.humanconnectome.org/mailman/listinfo/hcp-users --------------------------------------------------------------------------- Stephen M. Smith, Professor of Biomedical Engineering Associate Director, Oxford University FMRIB Centre FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK +44 (0) 1865 222726 (fax 222717) st...@fmrib.ox.ac.uk<mailto:st...@fmrib.ox.ac.uk> http://www.fmrib.ox.ac.uk/~steve --------------------------------------------------------------------------- Stop the cultural destruction of Tibet<http://smithinks.net> _______________________________________________ HCP-Users mailing list HCP-Users@humanconnectome.org http://lists.humanconnectome.org/mailman/listinfo/hcp-users
