Deep and Fast Imaging Using Adaptive Excitation Sources

NIH RePORTER · NIH · U01 · $659,268 · view on reporter.nih.gov ↗

Abstract

Optical recordings of activity are critical to probe neural systems because they provide high-resolution, non-invasive measurements, ranging from single neurons to entire populations in intact nervous systems, and are readily combined with genetic methods to provide cell type-specific recordings. Nevertheless, the limited penetration depth, spatial scale and temporal resolution remain major challenges for optical imaging. Cellular resolution imaging in scattering brains is typically achieved with multiphoton microscopy (MPM). Because of the nonlinear excitation process, the development of multiphoton imaging depends critically on ultrafast technologies, particularly femtosecond sources. From the first demonstrations of second harmonic generation (SHG) and 2-photon fluorescence (ruby laser), the first 2-photon imaging (mode-locked femtosecond laser), to the deepest 3-photon imaging so far (long wavelength optical parametric amplifiers), advances in multiphoton imaging have been largely propelled by the innovations in laser technologies. This research proposal aims to continue this trend. We will develop and disseminate a new generation of ultrafast lasers and multiphoton imaging tools that will enable deep, fast, and large-scale imaging of structure and function with cellular and subcellular resolution. To approach the fundamental limits defined by the “photon budget”, we will develop an adaptive excitation source (AES) at 1300 nm for deep tissue 3-photon microscopy (3PM). By feeding the structural information of the sample to the laser source, the AES generates on-demand pulses only within regions of interest (ROIs) and transforms a conventional multiphoton microscope into a “random-access” microscope for the ROIs. We will integrate the AES with high speed scanners and optimize the photon budget and scanning systems. We will further test and validate the performance of the new imaging technology in three proof-of-concept experiments in animal models. The research involves close interactions between the PI (Chris Xu) and Co-investigators (Alex Kwan, Frank Wise, Nilay Yapici, and Rafael Yuste). Furthermore, we will work with industry partners to explore commercialization of the technology, which will provide a direct path to broad dissemination. The combination of 1300 nm AES and 3PM will transform our ability to image deep and fast and will have a broad impact on neuroscience where high resolution, high speed imaging deep within an intact brain is required.

Key facts

NIH application ID
10904852
Project number
5U01NS128660-03
Recipient
CORNELL UNIVERSITY
Principal Investigator
CHRIS XU
Activity code
U01
Funding institute
NIH
Fiscal year
2024
Award amount
$659,268
Award type
5
Project period
2022-09-01 → 2026-08-31