弥合差距:umIT使所有背景的科学家都能获取复杂的成像数据。

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

作者信息

Ferreira de Souza Bruno Oliveira, Samantzis Montana, Albert Catherine, Belanger Samuel, Bouchard Jean-Francois, Balbi Matilde, Vanni Matthieu P

机构信息

Labeo Technologie Inc., Montréal, Québec, Canada.

The University of Queensland, Queensland Brain Institute, Brisbane, Queensland, Australia.

出版信息

Neurophotonics. 2025 Jan;12(Suppl 1):S14616. doi: 10.1117/1.NPh.12.S1.S14616. Epub 2025 Aug 22.

Abstract

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.

摘要

意义

近年来,已经开发了许多开源工具来促进神经科学中的数据分析,极大地鼓励了高通量方法的使用并推动了方法的标准化。用于宏观映射的工具(例如磁共振成像、脑电图)和微观技术(例如多电极电生理学、钙成像)现在已广泛可用。

目的

然而,在中间空间尺度,即介观尺度上,尽管这个尺度对于理解皮层图谱的功能至关重要,但却缺乏同等的开源资源。诸如钙成像之类的光学技术非常适合研究这个尺度,能够测量皮层反应和功能连接性。然而,分析复杂的多参数数据集仍然具有挑战性。现有的工具箱在处理此类数据的复杂性方面受到限制,限制了它们在中尺度研究中的效用。

方法

为了应对这些挑战,我们提出了通用介观成像工具箱(umIT),这是一个基于MATLAB开发的开源平台,用于分析大规模成像数据集。

结果

umIT支持通过图形用户界面和命令行界面访问的全面、简化的工作流程,无需第三方软件。

结论

这个工具箱旨在使介观成像更容易获得和透明,便于跨区域、组和时间点进行有力的比较(纵向研究)。重要的是,umIT还旨在促进与介观数据的直观交互,这对于刚开始使用宽场光学成像的学员来说可能特别有价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c38/12371479/0ebd88151f31/NPh-012-S14616-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索