Decode your brain: signal processing and machine learning for analyzing brain activity patterns



讲座时间:201861日   14:00-16:00


讲座主题:Decode your brain: signal processing and machine learning for analyzing brain activity patterns




Brain decoding has become a hot topic in many recent brain studies. It usually focuses on classification, identification and reconstruction of external stimuli from brain activities. Commonly used systems for acquiring such brain activity data non-invasively include electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). The traditional analysis of neurophysiological data relies on finding statistical relationship between activity changes and experimental conditions. Advanced signal processing and machine learning techniques, in contrast, are capable of distinguishing complex and subtle data patterns, distributed across numerous image voxels or on a single-trial basis. With these benefits, better brain decoding performance can be achieve for developing reliable brain-computer interfaces and understanding knowledge representation in the human brain.



娄彬博士,西门子医疗美国研究院担任高级研发科学家。20067月本科毕业于清华大学生物医学工程专业,20097月于清华大学生物医学工程专业获得工学硕士学位,20151月于美国哥伦比亚大学获得生物医学工程专业博士学位。长期从事神经工程、神经成像和神经信号处理的研究,研究兴趣包括脑-机接口、脑电信号处理和基于功能性核磁共振脑成像的脑解码方法。娄彬博士在哥伦比亚大学毕业后加入西门子美国研究院,近三年内主要负责的《神经系统中的知识表达》项目获美国情报高级研究计划局(IARPA)逾300万美元的资助。在《Nature Communications》、《Neuroimage》、《Journal of Neuroscience》等知名国际期刊和学术会议上发表学术论文10余篇,并担任《IEEE Transactions on Biomedical Engineering》、《IEEE Transactions on Image Processing》、《Pattern Recognition》等10余个期刊和国际会议的审稿人。

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