Neuronal Morphology Modeling Based on Microscopy Reconstruction Data in the Public Repositories

doi:http://link.springer.com/chapter/10.1007%2F978-3-319-09891-3_1

	Neuronal Morphology Modeling Based on Microscopy Reconstruction Data in the Public Repositories
	Yi Zeng(曾毅); Weida Bi(毕韦达); Xuan Tang(唐璇); Bo Xu(徐波)
	2014
会议名称	The 2014 International Conference on Brain Informatics and Health (BIH 2014)
会议录名称	Lecture Notes in Artificial Intelligence
卷号	8609
页码	1-11
会议日期	August 11-14
会议地点	Warsaw, Poland
出版者	Springer
摘要	Neuronal morphology modeling is one of the key steps for reverse engineering the brain at the micro level. It creates a realistic digital version of the neuron obtained by microscopy reconstruction in a visualized way so that the structure of the whole neuron (including soma, dendrite, axon, spin, etc.) is visible in different angles in a three dimensional space. Whether the modeled neuronal morphology matches the original neuron in vivo is closely related to the details captured by the manually sampled morphological points. Many data in public neuronal morphology data repositories (such as the NeuroMorpho project) focus more on the morphology of dendrites and axons, while there are only a few points to represent the neuron soma. The lack of enough details for neuron soma makes the modeling on the soma morphology a challenging task. In this paper, we provide a general method to neuronal morphology modeling (including the soma and its connections to surrounding dendrites, and axons, with a focus on how different components are connected) and handle the challenging task when there are not many detailed sample points for soma.
关键词	Neuron Morphology Reconstruction Neuronal Morphology Modeling Soma Reconstruction
DOI	http://link.springer.com/chapter/10.1007%2F978-3-319-09891-3_1
收录类别	EI
语种	英语
引用统计
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/10356
专题	脑图谱与类脑智能实验室_类脑认知计算
作者单位	Institute of Automation, Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Yi Zeng,Weida Bi,Xuan Tang,et al. Neuronal Morphology Modeling Based on Microscopy Reconstruction Data in the Public Repositories[C]:Springer,2014:1-11.