Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN) for cross-modal individual analysis of the whole brain.
Yuwen ChenHaoyu YangYan LuoYijun NiuMuzhou YuShanjun DengXuanhao WangHandi DengHaichao ChenLi-Xia GaoXinjian LiPingyong XuFudong XueJing MiaoSong-Hai ShiYi ZhongCheng MaBo LeiPublished in: Nature communications (2024)
Cross-modal analysis of the same whole brain is an ideal strategy to uncover brain function and dysfunction. However, it remains challenging due to the slow speed and destructiveness of traditional whole-brain optical imaging techniques. Here we develop a new platform, termed Photoacoustic Tomography with Temporal Encoding Reconstruction (PATTERN), for non-destructive, high-speed, 3D imaging of ex vivo rodent, ferret, and non-human primate brains. Using an optimally designed image acquisition scheme and an accompanying machine-learning algorithm, PATTERN extracts signals of genetically-encoded probes from photobleaching-based temporal modulation and enables reliable visualization of neural projection in the whole central nervous system with 3D isotropic resolution. Without structural and biological perturbation to the sample, PATTERN can be combined with other whole-brain imaging modalities to acquire the whole-brain image with both high resolution and morphological fidelity. Furthermore, cross-modal transcriptome analysis of an individual brain is achieved by PATTERN imaging. Together, PATTERN provides a compatible and versatile strategy for brain-wide cross-modal analysis at the individual level.
Keyphrases
- high resolution
- resting state
- white matter
- machine learning
- high speed
- functional connectivity
- cerebral ischemia
- deep learning
- mass spectrometry
- endothelial cells
- fluorescence imaging
- computed tomography
- high throughput
- small molecule
- single cell
- artificial intelligence
- photodynamic therapy
- single molecule
- cerebrospinal fluid
- subarachnoid hemorrhage
- big data
- visible light