Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA.
J Neurophysiol. 2011 Feb;105(2):964-80. doi: 10.1152/jn.00702.2010. Epub 2010 Nov 17.
The advent of methods for optical imaging of large-scale neural activity at cellular resolution in behaving animals presents the problem of identifying behavior-encoding cells within the resulting image time series. Rapid and precise identification of cells with particular neural encoding would facilitate targeted activity measurements and perturbations useful in characterizing the operating principles of neural circuits. Here we report a regression-based approach to semiautomatically identify neurons that is based on the correlation of fluorescence time series with quantitative measurements of behavior. The approach is illustrated with a novel preparation allowing synchronous eye tracking and two-photon laser scanning fluorescence imaging of calcium changes in populations of hindbrain neurons during spontaneous eye movement in the larval zebrafish. Putative velocity-to-position oculomotor integrator neurons were identified that showed a broad spatial distribution and diversity of encoding. Optical identification of integrator neurons was confirmed with targeted loose-patch electrical recording and laser ablation. The general regression-based approach we demonstrate should be widely applicable to calcium imaging time series in behaving animals.
在行为动物中以细胞分辨率进行大规模神经活动光学成像方法的出现，提出了在产生的图像时间序列中识别行为编码细胞的问题。快速准确地识别具有特定神经编码的细胞，将有助于有针对性地进行活动测量和干扰，从而有助于描述神经回路的工作原理。在这里，我们报告了一种基于回归的半自动识别神经元的方法，该方法基于荧光时间序列与行为的定量测量之间的相关性。该方法通过一种新颖的准备来进行说明，该准备允许在幼虫斑马鱼的自发眼球运动期间同步眼球追踪和双光子激光扫描荧光成像后脑神经元的钙变化。鉴定出了具有广泛空间分布和编码多样性的假定速度到位置眼球运动整合器神经元。通过靶向性宽松贴片电记录和激光烧蚀对整合器神经元的光学识别进行了验证。我们演示的基于广义回归的方法应该广泛适用于行为动物的钙成像时间序列。
