Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement.Segmentation of blood vessels from two-photon microscopy(2PM)angiograms of brains has important applications in hemodynamic analysis and disease diagnosis.Here,we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups.The technique is computationally efficient,thus ideal for large-scale neurovascular analysis.Introduction.Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature.Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms.In this work,we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms.Methods.We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network’s output.Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808×808×702μm.Results.To demonstrate the superior generalizability of our framework,we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning.Overall,our method demonstrates 10×faster computation in terms of voxels-segmented-per-second and 3×larger depth compared to the state-of-the-art.Conclusion.Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature,which consists of deep learning-based vascular segmentation followed by graphing.It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before.

EventLFM:event camera integrated Fourier light field microscopy for ultrafast 3D imaging

Ultrafast 3D imaging is indispensable for visualizing complex and dynamic biological processes.Conventional scanning-based techniques necessitate an inherent trade-off between acquisition speed and space-bandwidth product(SBP).Emerging single-shot 3D wide-field techniques offer a promising alternative but are bottlenecked by the synchronous readout constraints of conventional CMOS systems,thus restricting data throughput to maintain high SBP at limited frame rates.To address this,we introduce EventLFM,a straightforward and cost-effective system that overcomes these challenges by integrating an event camera with Fourier light field microscopy(LFM),a state-of-theart single-shot 3D wide-field imaging technique.The event camera operates on a novel asynchronous readout architecture,thereby bypassing the frame rate limitations inherent to conventional CMOS systems.We further develop a simple and robust event-driven LFM reconstruction algorithm that can reliably reconstruct 3D dynamics from the unique spatiotemporal measurements captured by EventLFM.Experimental results demonstrate that EventLFM can robustly reconstruct fast-moving and rapidly blinking 3D fluorescent samples at kHz frame rates.Furthermore,we highlight EventLFM’s capability for imaging of blinking neuronal signals in scattering mouse brain tissues and 3D tracking of GFP-labeled neurons in freely moving C.elegans.We believe that the combined ultrafast speed and large 3D SBP offered by EventLFM may open up new possibilities across many biomedical applications.

Non-genetic photoacoustic stimulation of single neurons by a tapered fiber optoacoustic emitter

Neuromodulation at high spatial resolution poses great significance in advancing fundamental knowledge in the field of neuroscience and offering novel clinical treatments.Here,we developed a tapered fiber optoacoustic emitter(TFOE)generating an ultrasound field with a high spatial precision of 39.6 pm,enabling optoacoustic activation of single neurons or subcellular structures,such as axons and dendrites.Temporally,a single acoustic pulse of sub-microsecond converted by the TFOE from a single laser pulse of 3 ns is shown as the shortest acoustic stimuli so far for successful neuron activation.The precise ultrasound generated by the TFOE enabled the integration of the optoacoustic stimulation with highly stable patch-clamp recording on single neurons.Direct measurements of the electrical response of single neurons to acoustic stimulation,which is difficult for conventional ultrasound stimulation,have been demonstrated.By coupling TFOE with ex vivo brain slice electrophysiology,we unveil cell-type-specific responses of excitatory and inhibitory neurons to acoustic stimulation.These results demonstrate that TFOE is a non-genetic single-cell and sub-cellular modulation technology,which could shed new insights into the mechanism of ultrasound neurostimulation.