Automated Neuron Tracing and 3D Reconstruction Software

描述（由申请人提供）：我们建议开发NeuroAutomatica，这是一种创新的自动神经元重建软件平台，为神经元结构的自动定量分析提供分析工具。该软件将提供有关多个邻近神经元的多标量信息，包括树突棘。提供这种创新功能将有助于神经退行性疾病、学习和记忆等重要领域的研究。NeuroAutomatica将能够对目前无法获得的神经元结构进行复杂而详细的分析。此外，它还将通过自动化一些现在辛苦地手动执行的分析来加快研究技术的步伐。 公共卫生相关性：最近的研究已经指出了神经元结构中最小的元素树突棘的重要性，假设关键的结构变化发生在负责处理连续涌入和存储信息的细胞功能变化的基础上。因此，树突棘已成为研究的中心目标，重点是学习和记忆，特别是预防神经退行性疾病的认知能力下降。此外，成像和生理实验的新进展导致了对神经元回路的研究。我们提出的软件将使这些网络的结构分析。NeuroAutomatica将通过提供一个独立于观察者的软件系统来加速基础神经科学研究的发现和理解的步伐，该系统能够准确有效地重建密集网络中的神经元，包括树突棘。

DESCRIPTION (provided by applicant): We propose to develop NeuroAutomatica, an innovative, automated neuron reconstruction software platform that provides analysis tools for automated quantitative analysis of neuronal structure. The software will provide multi-scalar information about multiple individual neurons in close proximity, including dendritic spines. Providing this innovative functionality will help research in important fields such as neurodegenerative diseases, learning, and memory. NeuroAutomatica will enable sophisticated and detailed analysis of neuronal structure that is currently unavailable. Furthermore, it will increase the pace of research technology by automating some analyses which are now painstakingly manually performed. PUBLIC HEALTH RELEVANCE: Recent research has pointed to the importance of the smallest element of a neuron's architecture-the dendritic spine-where it is hypothesized that critical structural changes occur to underlie changes in cellular function responsible for processing a continuous influx and storage of information. Thus, dendritic spines have become a central target in research focusing on learning and memory and, in particular, on the prevention of cognitive decline in neurodegenerative diseases. Furthermore, new advances in imaging and physiological experiments have led to investigations into neuronal circuits. Our proposed software will enable the structural analysis of these networks. NeuroAutomatica will accelerate the pace of discovery and understanding in basic neuroscience research by providing an observer independent software system capable of accurately and efficiently reconstructing neurons, including dendritic spines, in dense networks.