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A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

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Voltage Imaging with Periodic Structured Illumination.

Forest Speed¹, Alec Teel², Gregory L Futia¹

¹Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

Biorxiv : the Preprint Server for Biology

|August 6, 2025

Summary

This summary is machine-generated.

We introduce pseudo-HiLo (pHiLo) imaging to improve in vivo voltage imaging by reducing out-of-focus signals. This technique enhances clarity for studying neural activity in awake mice.

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Area of Science:

Neuroscience
Optical Imaging
Biophysics

Background:

In vivo voltage imaging is crucial for understanding neural circuit dynamics.
Out-of-focus fluorescence contaminates signals in traditional widefield recordings.
Improving signal clarity is essential for high-speed neural activity studies.

Purpose of the Study:

To evaluate the efficacy of periodic structured illumination with pseudo-HiLo (pHiLo) image reconstruction for in vivo voltage imaging.
To compare pHiLo with traditional widefield and pseudo-widefield (pWF) methods in reducing out-of-focus signal contamination.
To analyze the trade-offs associated with pHiLo for high-speed imaging in awake mice.

Main Methods:

Utilized periodic structured illumination with pseudo-HiLo (pHiLo) image reconstruction.
Performed in vivo voltage imaging experiments.
Compared pHiLo reconstructions with traditional widefield recordings and pseudo-widefield (pWF) reconstructions.

Main Results:

pHiLo significantly reduced signal from out-of-focus cells compared to traditional widefield recordings.
Reduced out-of-focus signal contamination improved the clarity of voltage activity from in-focus cells.
Demonstrated the application of pHiLo in high-speed voltage imaging of awake mice.

Conclusions:

pHiLo image reconstruction is an effective method for enhancing in vivo voltage imaging.
pHiLo offers improved signal-to-background ratio by minimizing out-of-focus light.
Further investigation into signal-to-noise ratio and temporal resolution trade-offs is warranted for optimizing pHiLo in high-speed applications.