Performing the ICA analysis across multiple trials has some issues because of the random nature of the ICA decomposition. Running the analysis, even on the same data, does not mean that the same components will be the same source. One solution to this problem is to concatenate the trials, and perform ICA on the trials as if they were a single acquisition. In order for this to work, however, the pixels must stay aligned with the sources of the signals. The ImageComponentParser includes an image registration algorithm that can account for shifts in the imaging data across trials, which is a necessary step to perform concatenated trial ICA (ctICA).
This registration algorithm can only perform an affine transformation on the entire image. If there is motion of a cell or a sub-region that is different from the macro-motion, then the algorithm cannot compensate for these changes. This will hinder the results of ctICA, but it can still give some good results as long as most pixels over a source remain over the source.
The left is the raw image data, and the right is the data after each trial was aligned using the ImageComponentParser. The algorithm that is built into ICP only does full frame affine motion correction. This means that if a cell were to move relative to the ganglion, it would not be aligned as it should. Some better motion correction that can fix sub-regions of the image would improve the results, but this does a fairly good job. ICP automatically removes the edge pixels that are missing in some trials after the motion correction, giving only the region of the data that is present in all trials.