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Brain cells are arranged in laminar, nuclear, or columnar structures, spanning a range of scales. Here, we construct a reliable cell census in the frontal lobe of human cerebral cortex at micrometer resolution in a magnetic resonance imaging (MRI)-referenced system using innovative imaging and analysis methodologies. MRI establishes a macroscopic reference coordinate system of laminar and cytoarchitectural boundaries. Cell counting is obtained with a digital stereological approach on the 3D reconstruction at cellular resolution from a custom-made inverted confocal light-sheet fluorescence microscope (LSFM). Mesoscale optical coherence tomography enables the registration of the distorted histological cell typing obtained with LSFM to the MRI-based atlas coordinate system. The outcome is an integrated high-resolution cellular census of Broca's area in a human postmortem specimen, within a whole-brain reference space atlas.

Two-photon (2P) excitation is a cornerstone approach widely employed in neuroscience microscopy for deep optical access and sub-micrometric-resolution light targeting into the brain. However, besides structural and functional imaging, 2P optogenetic stimulations are less routinary, especially in 3D. This is because of the adopted scanning systems, often feebly effective, slow and mechanically constricted. Faster illumination can be achieved through acousto-optic deflectors (AODs) although their applicability to large volumes excitation has been limited by large efficiency drop along the optical axis. Here, we present a new AOD-based scheme for 2P 3D scanning that improves the power delivery between different illumination planes. We applied this approach to photostimulate an optogenetic actuator in zebrafish larvae, demonstrating the method efficiency observing increased activity responses and uniform activation probabilities from neuronal clusters addressed in the volume. This novel driving scheme can open to new AOD applications in neuroscience, allowing more effective 3D interrogation in large neuronal networks., (© 2022 The Authors. Journal of Biophotonics published by Wiley-VCH GmbH.)