Comprehensive mapping of neural circuits at cellular and subcellular resolution is essential for revealing the structure and function of the brain. Traditional optical imaging methods, such as two-photon microscopy1, fluorescence micro-optical sectioning tomography (fMOST)2,3,4, and the VISoR system5, have enabled mesoscale neuronal imaging and in vivo functional imaging. However, due to their reliance on sparse labeling, they fail to capture the complete cellular population. On the other hand, label-free optical imaging techniques, such as functional photoacoustic microscopy (fPAM)6,7, optical coherence tomography (OCT)8, and quantitative phase microscopy9, hold the potential to visualize all neurons within the field of view simultaneously. Nevertheless, these methods are typically limited by low axial resolution and shallow imaging depth, and their hardware complexity hampers widespread application in brain atlas construction. In contrast, serial-section electron microscopy (ssEM) techniques, including serial block-face SEM (SBF-SEM)10,11, focused ion beam SEM (FIB-SEM)12,13,14, and automated tape-collecting ultramicrotomy SEM (ATUM-SEM)15,16,17, can reveal dense synaptic connectivity networks at nanometer resolution, providing essential tools for high-resolution connectomics. However, these techniques suffer from low throughput, long acquisition times, limited fields of view, and high data processing and hardware costs18.
To overcome the above limitations, we developed an imaging method named Optical Multilayer Interference Tomography (OMLIT), which offers a low-cost and high-throughput solution for indiscriminate, high-contrast, wide-field imaging of all cells on ultrathin sections, achieving submicron resolution across large tissue areas. At the same time, OMLIT is inherently compatible with serial-section SEM workflows: before high-resolution electron microscopy, OMLIT provides structural information on the same sections, allowing precise ROI navigation and significantly reducing the area and data volume required for subsequent EM imaging. OMLIT offers unique advantages at the mesoscale imaging level and serves as a critical bridge connecting neural structural maps across different spatial scales. Its non-destructive nature preserves the potential for future integration with specific labeling strategies, such as the use of osmium-resistant fluorescent proteins19 for sample preparation and imaging. This method enables mesoscale imaging of selected brain regions, allowing rapid acquisition of neuronal morphology, quantity, distribution, and density in the regions. It also facilitates quantitative characterization of axonal projections and dendrite distribution between neurons in different brain areas. For specific regions of interest in the imaging results, in situ ultrastructural details can be further investigated using electron microscopy.
The imaging principle of OMLIT has been described in the work by Hao Fan20. Briefly, during imaging, the ultrathin section, coated layer, collection tape, conductive tape, and wafer form a multilayer thin-film structure. When a plane wave interacts with this structure, reflected waves are generated at various interfaces and overlap in the detection space, resulting in optical interference due to differences in reflectance, refractive index, and absorption among the materials. A MATLAB-based simulation program developed based on this principle demonstrated reasonable agreement with experimental results.
The OMLIT imaging scheme can be categorized into two types based on the tape processing strategy. The first is the high-reflectivity strategy, in which metals such as Cr, Cu, Al, or Ag are used to coat the tape surface, resulting in higher optical intensities in cytoplasmic regions and resin-filled vascular lumens compared to surrounding areas. The second is the low-reflectivity strategy, which employs uncoated Kapton tape, D-50 tape, or CNT-coated PET tape. In this case, the optical imaging outcome is the reverse of the first: resin-rich membrane-free regions (e.g., cytoplasm and vascular lumens) appear with lower intensity.
We systematically summarize and establish standardized protocols tailored to two distinct imaging strategies. The protocols presented here offer comprehensive and detailed experimental procedures. Additionally, common issues encountered during the experiments are summarized, along with proposed solutions. We focus on presenting a dataset of mouse cortex acquired using the low-reflectivity strategy (805 × 857.5 × 11.66 µm³), illustrating the distinctive features and advantages of the OMLIT imaging approach.