Open Access
1 March 2023 Open-source statistical and data processing tools for wide-field optical imaging data in mice
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Abstract

Significance

Wide-field optical imaging (WOI) can produce concurrent hemodynamic and cell-specific calcium recordings across the entire cerebral cortex in animal models. There have been multiple studies using WOI to image mouse models with various environmental or genetic manipulations to understand various diseases. Despite the utility of pursuing mouse WOI alongside human functional magnetic resonance imaging (fMRI), and the multitude of analysis toolboxes in the fMRI literature, there is not an available open-source, user-friendly data processing and statistical analysis toolbox for WOI data.

Aim

To assemble a MATLAB toolbox for processing WOI data, as described and adapted to combine techniques from multiple WOI groups and fMRI.

Approach

We outline our MATLAB toolbox on GitHub with multiple data analysis packages and translate a commonly used statistical approach from the fMRI literature to the WOI data. To illustrate the utility of our MATLAB toolbox, we demonstrate the ability of the processing and analysis framework to detect a well-established deficit in a mouse model of stroke and plot activation areas during an electrical paw stimulus experiment.

Results

Our processing toolbox and statistical methods isolate a somatosensory-based deficit 3 days following photothrombotic stroke and cleanly localize sensory stimulus activations.

Conclusions

The toolbox presented here details an open-source, user-friendly compilation of WOI processing tools with statistical methods to apply to any biological question investigated with WOI techniques.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Lindsey M. Brier and Joseph P. Culver "Open-source statistical and data processing tools for wide-field optical imaging data in mice," Neurophotonics 10(1), 016601 (1 March 2023). https://doi.org/10.1117/1.NPh.10.1.016601
Received: 16 August 2022; Accepted: 2 February 2023; Published: 1 March 2023
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CITATIONS
Cited by 5 scholarly publications.
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KEYWORDS
Data processing

Functional magnetic resonance imaging

Statistical analysis

Optical imaging

Visualization

Calcium

MATLAB

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