讲座题目：Planning invasive and non-invasive brain network disorder treatments using computational models 主讲人：Marcus Kaiser 教授 主持人：尹大志 研究员 开始时间🫶🏽：2019-12-23 15:00:00 讲座地址：老图书馆2032 主办单位：心理与认知科学学院
报告人简介🌯： Marcus Kaiser博士于2005年在德国不来梅雅各布斯大学获得神经科学博士学位🥗，现任英国纽卡斯尔大学计算学院神经信息学教授🫅，首尔国立大学和上海交通大学客座教授、英国皇家生物学学会会士、以及英国神经信息学主席📿，研究兴趣主要是通过计算模拟大脑发育😳、神经动力学和临床干预治疗来理解大脑结构和功能的关系🧑🏻🚀，已在《Neuron》、《Trends in Cognitive Sciences》、《Brain》、《NeuroImage》等期刊上发表了70余篇研究论文和综述文章🧝🏻♀️，任PLOS Computational Biology，Network Neuroscience (MIT Press)等领域著名学术期刊的编委🦢。
报告内容： Our work on connectomics over the last 15 years has shown a small-world, modular, and hub architecture of brain networks. Small-world features enable the brain to rapidly integrate and bind information while the modular architecture, present at different hierarchical levels, allows separate processing of various kinds of information (e.g. visual or auditory) while preventing wide-scale spreading of activation. Hub nodes play critical roles in information processing and are involved in many brain diseases. After discussing the organisation of brain networks, I will show how connectivity in combination with machine learning and computer simulations can identify the progression towards dementia before the onset of symptoms informing interventions that can delay disease progression. For epilepsy patients, connectome-based simulations can also be used to predict the outcome of surgical interventions as well as alternative target regions. While these models rely on the network between brain regions, we also developed models of tissue within a brain region (http://www.vertexsimulator.org). Such models can observe the effects of invasive or non-invasive electrical brain stimulation. I will finally outline how these models could, in the future, inform invasive interventions, such as optogenetic stimulation in epilepsy patients (http://www.cando.ac.uk) or non-invasive interventions using electrical, magnetic or focused ultrasound stimulation. |
