Optical Neuroimage Studio (OptiNiSt): Intuitive, scalable, extendable framework for optical neuroimage data analysis

Yukako Yamane, Yuzhe Li, Keita Matsumoto, Ryota Kanai, Miles Desforges, Carlos Enrique Gutierrez and Kenji Doya

PLOS Computational Biology, 2025, vol. 21, issue 5, 1-14

Abstract: Advancements in calcium indicators and optical techniques have made optical neural recording common in neuroscience. As data volumes grow, streamlining the analysis pipelines for image preprocessing, signal extraction, and subsequent neural activity analyses becomes essential. Challenges in analysis includes 1) ensuring data quality of original and processed data at each step. 2) Selecting optimal algorithms and their parameters from numerous options, each with its own pros and cons, by implementing or installing them manually. 3) systematically recording each analysis step for reproducibility 4) adopting standard data formats for data sharing and meta-analyses. To address these challenges, we developed Optical Neuroimage Studio (OptiNiSt), a scalable, extendable, and reproducible framework for creating calcium data analysis pipelines. OptiNiSt includes the following features. 1) Researchers can easily create analysis pipelines by selecting multiple processing modules, tuning their parameters, and visualizing the results at each step through a graphic user interface in a web browser. 2) In addition to pre-installed tools, new analysis algorithms can be easily added. 3) Once a processing pipeline is designed, the entire workflow with its modules and parameters are stored in a YAML file, which makes the pipeline reproducible and deployable on high-performance computing clusters. 4) OptiNiSt can read image data in a variety of file formats and store the analysis results in NWB (Neurodata Without Borders), a standard data format for data sharing. We expect that this framework will be helpful in standardizing optical neural data analysis protocols.Author summary: Streamlining data analysis workflows in optical neural recording is essential as data volumes increase. Challenges include ensuring data quality, selecting optimal algorithms for analyses, and maintaining reproducibility. To address these, we developed Optical Neuroimage Studio (OptiNiSt), a framework for creating scalable, reproducible calcium imaging analysis pipelines. OptiNiSt allows users to design analysis workflows by selecting processing modules, tuning parameters, and visualizing results through an intuitive web-based interface. In addition to pre-installed analysis tools, new algorithms can be easily added. The stored entire analysis pipeline ensures reproducibility and enable deployment on high-performance computing clusters. This framework aims to facilitate the standardization of data analysis, improving reproducibility, and collaboration within the neuroscience community.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1013087

DOI: 10.1371/journal.pcbi.1013087

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