Bridging the gap: umIT makes complex imaging data accessible to scientists of all backgrounds.

Significance: In recent years, numerous open-source tools have been developed to facilitate data analysis in neuroscience, significantly encouraging the use of high-throughput approaches and promoting standardizing methods. Tools for macroscopic mapping (e.g., magnetic resonance imaging, electroencephalogram) and microscopic techniques (e.g., multi-electrode electrophysiology, calcium imaging) are now widely available. Aim: However, at the intermediate spatial level, the mesoscopic scale, there is a lack of equivalent open-source resources even though this scale is crucial for understanding the function of cortical maps. Optical techniques such as calcium imaging are well suited to investigate this scale, enabling measurements of cortical responses and functional connectivity. Yet, analyzing complex, multiparameter datasets remains challenging. Existing toolboxes are restricted in handling the complexity of such data, limiting their utility for mesoscale studies. Approach: To address these challenges, we propose the Universal Mesoscale Imaging Toolbox (umIT), an open-source MATLAB-based platform developed to analyze large-scale imaging datasets. Results: umIT supports a comprehensive, streamlined workflow accessible via both a graphical user interface and command-line interface, eliminating the need for third-party software. Conclusions: This toolbox aims to make mesoscale imaging more accessible and transparent, facilitating robust comparisons across regions, groups, and time points (longitudinal studies). Importantly, umIT was also designed to facilitate intuitive interaction with mesoscale data, an aspect that may be particularly valuable for trainees who are just beginning to work with wide-field optical imaging.