Ha, OK (or, as they say in Italy, OK).

Re. the correlation conundrum:

Ah, I see. Indeed, that is a bit tricky. So, you want region-to-voxelwise correlation, not within-network-of-regions correlation? Well, at least 3dNetCorr can output all the time series at once:

-ts_out          :switch to output the mean time series of the ROIs that
                      have been used to generate the correlation matrices.
                      Output filenames mirror those of the correlation
                      matrix files, with a '.netts' postfix.

    -ts_label        :additional switch when using '-ts_out'. Using this
                      option will insert the integer ROI label at the start
                      of each line of the *.netts file created. Thus, for
                      a time series of length N, each line will have N+1
                      numbers, where the first is the integer ROI label
                      and the subsequent N are scientific notation values.

    -ts_indiv        :switch to create a directory for each network that
                      contains the average time series for each ROI in
                      individual files (each file has one line).
                      The directories are labelled PREFIX_000_INDIV/,
                      PREFIX_001_INDIV/, etc. (one per network). Within each
                      directory, the files are labelled ROI_001.netts,
                      ROI_002.netts, etc., with the numbers given by the
                      actual ROI integer labels.

... and it can even do the set of region-to-voxelwise correlation map calculation for you:

-ts_wb_corr      :switch to perform whole brain correlation for each
                      ROI's average time series; this will automatically
                      create a directory for each network that contains the
                      set of whole brain correlation maps (Pearson 'r's).
                      The directories are labelled as above for '-ts_indiv'
                      Within each directory, the files are labelled
                      WB_CORR_ROI_001+orig, WB_CORR_ROI_002+orig, etc., with
                      the numbers given by the actual ROI integer labels.

but I take your point about the role of smoothing in effectively reducing some distortion effects.

Part of me wonders about doing region-to-voxelwise calculations, and then applying a blur to those maps. The correlation process is not linear, so it isn't exchangeable with the linear process of blurring, but probably that would fairly closely approximate having a separate dataset that was blurred and calculating the correlation maps "properly". Unfortunately verifying that hypothesis does the full amount of dual-processing that one would hope to avoid.

Will have to ponder a bit...

--pt