讲座题目：物理学校级学术系列报告——The Human Connectome: Topological and Spatial Features of Brain Networks
主讲人：Marcus Kaiser
开始时间：2012-07-06 9:30
讲座地址：中山北路校区老图书馆二楼2032室
报告人简介：
Marcus Kaiser studied biology and computer science at the Ruhr-University Bochum and the Distance University Hagen finishing with a master degree in 2002. He obtained his PhD, funded by a fellowship from the German National Merit Foundation, from Jacobs University Bremen in 2005. Directly after finishing his PhD, he started a tenure-track position at Newcastle University and became initiator and co-director of the Wellcome Trust PhD programme in Systems Neuroscience. He is leader of the UK INCF Special Interest Group in Image-based Neuroinformatics. He is author of the first major review (Trends in Cognitive Sciences, 2004; cited 650+ times) and of more than 40 other publications in the field of brain connectivity. Research interests are understanding the link between brain architecture and processing by modelling brain development, neural dynamics, and recovery after stroke (seehttp://www.biological-networks.org/ ).
报告内容简介：
The human brain consists of connections between neurons at the local level and of connections between brain regions at the global level. The study of the entire network, the connectome, has become a recent focus in neuroscience research. Using routines from physics and the social sciences, neuronal networks were found to show properties of scale-free networks, making them robust towards random damage, and of small-world systems leading to better information integration. I will show ongoing research in my lab on brain development and robustness. Next, I will describe ways to analyze the topological and spatial organization of the connectome at the macroscopic level of connectivity between brain regions as well as the microscopic level of connectivity between neurons. Finally, the connectome also has a spatial organization and we describe methods for analyzing wiring lengths of neural systems. As an introduction for new researchers in the field of connectome analysis, I will discuss the benefits and limitations of each analysis approach