Brainways: An Open-Source AI-based Software For Registration and Analysis of Fluorescent Markers on Coronal Brain Slices

Registration and quantification of stained histological brain slices is a central step in the study of a vast array of neural mechanisms across species. These analyses are often done manually or require the integration of several different softwares which often do not work well together, resulting in laborintensive and cumbersome workflows, or requiring significant coding skills. The main challenge in this type of analysis is to correctly outline the region of interest (ROI), achieve inter-rater validity, especially when targeting multiple ROIs, an approach which is becoming common practice. We developed Brainways, a simple AI-based software for biologists that automatically registers coronal brain slices to a 3D atlas and provides brain-wide quantification of fluorescent markers across subjects, and supports co-labelling of multiple stains (via QuPath file import). Here we demonstrate the use of Brainways on a dataset from a previously published experiment investigating the neural network involved in empathic helping behavior of rats towards trapped ingroup or outgroup members. The re-analysis, which covered over a 100-fold more brain tissue compared to the original, replicated the manually quantified results, providing support for the reliability of Brainways, which is also highly cost-effective compared to manual methods. The automatic registration algorithm achieved 80% accuracy for correct slice matching to the Waxholm rat atlas. Increased accuracy can be obtained manually via high throughput visual scanning and adjustment using the Brainways GUI. Brainways functionality is exposed through a python-based API, and can be trained on any atlas (e.g. mice, zebrafish, human), as well as enhanced for different applications. ### Competing Interest Statement The authors have declared no competing interest.