Center for Life Nano- and Neuro-Science@Sapienza, Istituto Italiano di Tecnologia (IIT), Rome, Italy.
D-tails s.r.l., Rome, Italy.
PLoS One. 2024 Mar 22;19(3):e0300628. doi: 10.1371/journal.pone.0300628. eCollection 2024.
In the emerging field of whole-brain imaging at single-cell resolution, which represents one of the new frontiers to investigate the link between brain activity and behavior, the nematode Caenorhabditis elegans offers one of the most characterized models for systems neuroscience. Whole-brain recordings consist of 3D time series of volumes that need to be processed to obtain neuronal traces. Current solutions for this task are either computationally demanding or limited to specific acquisition setups. Here, we propose See Elegans, a direct programming algorithm that combines different techniques for automatic neuron segmentation and tracking without the need for the RFP channel, and we compare it with other available algorithms. While outperforming them in most cases, our solution offers a novel method to guide the identification of a subset of head neurons based on position and activity. The built-in interface allows the user to follow and manually curate each of the processing steps. See Elegans is thus a simple-to-use interface aimed at speeding up the post-processing of volumetric calcium imaging recordings while maintaining a high level of accuracy and low computational demands. (Contact: enrico.lanza@iit.it).
在单细胞分辨率的全脑成像这一新兴领域中,线虫秀丽隐杆线虫是神经系统科学中最具代表性的模型之一,它代表了研究大脑活动和行为之间联系的新前沿之一。全脑记录由需要进行处理以获得神经元轨迹的 3D 时间序列体积组成。目前,针对此任务的解决方案要么计算要求高,要么仅限于特定的采集设置。在这里,我们提出了 See Elegans,这是一种直接编程算法,它结合了自动神经元分割和跟踪的不同技术,而无需 RFP 通道,我们将其与其他可用算法进行了比较。虽然在大多数情况下都优于它们,但我们的解决方案提供了一种新的方法,可以根据位置和活动来引导对头神经元子集的识别。内置的界面允许用户跟踪和手动编辑每个处理步骤。因此,See Elegans 是一个简单易用的界面,旨在加快体积钙成像记录的后处理,同时保持高精度和低计算需求。(联系人:enrico.lanza@iit.it)。