Open MikiBii opened 2 years ago
For the best nRegions, look at Figure 3B(i) of the paper (https://www.nature.com/articles/s41598-018-21640-2 ), which shows that over a range of nRegions, FISSA performs quite well at separating the true signal (correlation between source and extracted signal is high). You can try adjusting this parameter for your data, but in general set this value ≥ 4.
Hi everyone! I am exporting the data in Matlab, and - according to your documentation - I should have:
result.cell0.trial0(1,:)
which should be the final extracted cell signalresult.cell0.trial0(2,:)
which should be the contaminating signal (sometimes zeroed - what does it mean?)However, I also have others 3 lines of reulsts which are zeroed or non-zeroed. What these lines of data represents? Which one is the neuropil? The same is then also applied on the df_result (obtained by running calc_deltaf(3)).
Furthermore, how you "choose the best nRegions"? - At the moment I am running with nRegions = 4 (given by default?).
Thank you a lot for helping me and for this amazing tool !! (: