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In vivo two-photon microscopy permits simultaneous recording of the activity of the same neuronal population across multiple sessions in days or weeks, which is crucial for addressing many fundamental questions of neuroscience. The field-of-view (FOV) alignment is a necessary step for identifying the same neurons across multiple imaging sessions. Accurate FOV alignment becomes challenging in the situations of image blurring, insufficient common neurons, or uneven background brightness. The existing methods largely fail to align FOV pairs in these situations. The fully affine invariant approach has been applied in computer vision to register real scene images with different backgrounds. However, its performance in calcium imaging data is unknown. We explored the feasibility of using the fully affine invariant approach to align calcium FOV images across multiple sessions by examining the performance of five methods. Further, we compared their performance with common feature-based methods as well as some classical methods with or without adaptive contrast enhancement. Using cellular resolution calcium imaging data recorded from two areas of the mouse motor cortex over weeks, we show that all fully affine invariant methods provide more accurate FOV alignment results than other methods in general and in the case of a few common neurons identified, uneven background brightness or image blurring. This study demonstrated the feasibility and reliability of the fully affine invariant methods in cross-session FOV alignment. These methods could be useful for neuroscience research, especially on questions that involve experience-dependent plasticity spanning over days or weeks.

Fully Affine Invariant Methods for Cross-Session Registration of Calcium Imaging Data