Centre for Neurotechnology and Department of Bioengineering, Imperial College, South Kensington, London SW7 2AZ, United Kingdom.
J Neural Eng. 2018 Apr;15(2):025003. doi: 10.1088/1741-2552/aa99e2.
Multi-photon laser scanning microscopy provides a powerful tool for monitoring the spatiotemporal dynamics of neural circuit activity. It is, however, intrinsically a point scanning technique. Standard raster scanning enables imaging at subcellular resolution; however, acquisition rates are limited by the size of the field of view to be scanned. Recently developed scanning strategies such as travelling salesman scanning (TSS) have been developed to maximize cellular sampling rate by scanning only select regions in the field of view corresponding to locations of interest such as somata. However, such strategies are not optimized for the mechanical properties of galvanometric scanners. We thus aimed to develop a new scanning algorithm which produces minimal inertia trajectories, and compare its performance with existing scanning algorithms.
We describe here the adaptive spiral scanning (SSA) algorithm, which fits a set of near-circular trajectories to the cellular distribution to avoid inertial drifts of galvanometer position. We compare its performance to raster scanning and TSS in terms of cellular sampling frequency and signal-to-noise ratio (SNR).
Using surrogate neuron spatial position data, we show that SSA acquisition rates are an order of magnitude higher than those for raster scanning and generally exceed those achieved by TSS for neural densities comparable with those found in the cortex. We show that this result also holds true for in vitro hippocampal mouse brain slices bath loaded with the synthetic calcium dye Cal-520 AM. The ability of TSS to 'park' the laser on each neuron along the scanning trajectory, however, enables higher SNR than SSA when all targets are precisely scanned. Raster scanning has the highest SNR but at a substantial cost in number of cells scanned. To understand the impact of sampling rate and SNR on functional calcium imaging, we used the Cramér-Rao Bound on evoked calcium traces recorded simultaneously with electrophysiology traces to calculate the lower bound estimate of the spike timing occurrence.
The results show that TSS and SSA achieve comparable accuracy in spike time estimates compared to raster scanning, despite lower SNR. SSA is an easily implementable way for standard multi-photon laser scanning systems to gain temporal precision in the detection of action potentials while scanning hundreds of active cells.
多光子激光扫描显微镜为监测神经回路活动的时空动态提供了强大的工具。然而，它本质上是一种点扫描技术。标准的光栅扫描可实现亚细胞分辨率的成像；然而，采集率受到要扫描的视场大小的限制。最近开发的扫描策略，如旅行商扫描（TSS），已经被开发出来，通过仅扫描视场中对应于感兴趣位置（如体细胞）的选择区域来最大化细胞采样率。然而，这些策略并不是针对检流计扫描仪的机械特性进行优化的。因此，我们旨在开发一种新的扫描算法，该算法产生最小惯性轨迹，并将其性能与现有的扫描算法进行比较。
我们在这里描述了自适应螺旋扫描（SSA）算法，该算法将一组近圆形轨迹拟合到细胞分布中，以避免检流计位置的惯性漂移。我们比较了它在细胞采样频率和信噪比（SNR）方面的性能与光栅扫描和 TSS 的性能。
使用替代神经元空间位置数据，我们表明 SSA 的采集率比光栅扫描高一个数量级，并且通常超过 TSS 的采集率，对于与皮层中发现的类似的神经密度。我们表明，这一结果也适用于在体外海马鼠脑片浴中加载合成钙染料 Cal-520 AM 的情况。然而，当所有目标都被精确扫描时，TSS 能够将激光“停”在扫描轨迹上的每个神经元上，从而实现比 SSA 更高的 SNR。光栅扫描具有最高的 SNR，但代价是扫描的细胞数量大幅减少。为了了解采样率和 SNR 对功能钙成像的影响，我们使用 Cramér-Rao 边界对同时记录的电生理轨迹进行了诱发钙迹线的计算，以计算出尖峰时间发生的下限估计。
结果表明，TSS 和 SSA 与光栅扫描相比，在尖峰时间估计方面实现了相当的准确性，尽管 SNR 较低。SSA 是一种简单的方法，可以为标准的多光子激光扫描系统在扫描数百个活动细胞时获得动作电位检测的时间精度。
