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Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields
Iksung Kang1,2, Hyeonggeon Kim3, Ryan Natan4
1Department of Neuroscience, University of California, Berkeley, Berkeley, CA, USA. iksung.kang@kaist.ac.kr.
Nature Methods
|April 13, 2026
Summary
NeAT is a new computational framework for adaptive optics two-photon fluorescence microscopy. It corrects optical aberrations and sample motion in real-time for clearer in vivo imaging of the mouse brain.
Area of Science:
- Neuroscience
- Biophysics
- Optical Engineering
Background:
- Adaptive optics (AO) corrects optical aberrations to improve imaging in complex biological samples.
- Traditional AO systems often require custom microscopes and are sensitive to sample movement.
Purpose of the Study:
- To introduce NeAT, a computational framework for adaptive optics two-photon fluorescence microscopy.
- To enable real-time aberration correction and motion compensation for in vivo imaging.
Main Methods:
- NeAT utilizes neural fields to estimate wavefront aberrations and reconstruct 3D image stacks without external training data.
- The framework incorporates motion correction and corrects conjugation errors common in commercial microscopes.
- Performance was validated using both custom-built and commercial two-photon microscopes.
Main Results:
- NeAT successfully estimated aberrations and recovered sample structure under various signal-to-noise, aberration, and motion conditions.
- Real-time aberration correction was demonstrated on a commercial microscope for in vivo imaging of the living mouse brain.
- NeAT enhanced the signal and accuracy of glutamate and calcium imaging at the synaptic and neuronal levels.
Conclusions:
- NeAT offers a deployable computational solution for adaptive optics in biological laboratories.
- The framework improves the quality and reliability of in vivo two-photon microscopy for neuroscience research.
- NeAT facilitates advanced morphological and functional imaging in live animal models.
