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  4. Multiphoton GRIN‐Lens Microendoscopy for Living Brains
 
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Multiphoton GRIN‐Lens Microendoscopy for Living Brains

Journal
Laser and Photonics Reviews
Journal Issue
Online Version of Record before inclusion in an issue
Start Page
e01461
ISSN
1863-8880
1863-8899
Date Issued
2025-10-25
Author(s)
Wang, Chien‐Sheng
Lai, Xiaomin
Yeh, Po‐Ting
Liao, Pin‐Chun
Kitamura, Risa
Liu, Yuanyuan
SHIH-KUO CHEN  
Cui, Meng
SHI-WEI CHU  
DOI
10.1002/lpor.202501461
URI
https://www.scopus.com/record/display.uri?eid=2-s2.0-105019575330&origin=resultslist
https://scholars.lib.ntu.edu.tw/handle/123456789/733476
Abstract
Exploration of neural activity at high spatiotemporal resolution in live animals is essential for advancing the understanding of brain function. Multiphoton microscopy has emerged over the past three decades as a powerful tool for in vivo neuroimaging, providing 3D subcellular spatial resolution and sub-second temporal resolution. However, its imaging depth is fundamentally limited to approximately 2 mm due to light scattering, leaving most subcortical brain regions inaccessible in mammals. Gradient refractive index (GRIN) lens-based multiphoton microendoscopy offers a minimally invasive approach that extends imaging depth up to 10 cm while maintaining 3D µm resolution. The technique, however, remains constrained by intrinsic optical aberrations of GRIN lenses, which degrade image quality and limit both the field of view and the imaging volume. Recent advances, including adaptive optics, aspheric correctors, and geometric transformation techniques, provide state-of-the-art aberration correction and expand the volume of view to the cubic millimeter scale. Applications of GRIN multiphoton microendoscopy in functional neuroimaging demonstrate its potential for high-throughput volumetric imaging with enhanced spatiotemporal resolution. These innovations enable longitudinal studies of large-scale neural dynamics and support the development of next-generation photonic systems for deep brain connectome mapping.
Subjects
aberration correction
chronic functional connectomics
GRIN lens
high-speed volumetric imaging
machine learning
neural networks
SDGs

[SDGs]SDG3

Publisher
Wiley
Type
review

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