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向一个估计的神经信息的大胆的信号

Towards an Estimate of the Neural Information of the BOLD Signal
课程网址: http://videolectures.net/bbci2012_biessmann_neural_information/  
主讲教师: Felix Bießmann
开课单位: 柏林工业大学
开课时间: 2012-12-03
课程语种: 英语
中文简介:
功能磁共振成像(fmri)测量的血氧水平相关(bold)信号已成为神经活动的标准标志。神经活动与其血流动力学反应的关系具有复杂的时空动力学特征。大多数分析依赖于简单的神经血管耦合模型,从而低估了粗体信号中的神经信息。我们使用机器学习方法从高分辨率fmri信号和颅内测量的神经带功率信号同时记录的对比数据中获得神经信息的无模型估计。这些估计值有助于指导fmri研究中的参数选择,以便对刺激信息进行最佳解码,并可作为无颅内神经测量的研究的基线。
课程简介: The blood oxygen level dependent (BOLD) signal as measured by functional magnetic resonance imaging (fMRI) has become a standard marker of neural activity. The relationship between neural activity and its hemodynamic response is characterized by complex spatiotemporal dynamics. Most analyses rely on simple models of neurovascular coupling and thus underestimate the neural information in the BOLD signal. We use machine learning methods to obtain a model free estimate of the neural information in BOLD contrast data from simultaneous recordings of high resolution fMRI signals and intracranially measured neural bandpower signals. These estimates can help to guide parameter selection in fMRI studies for optimal decoding of stimulus information and might serve as a baseline to which studies without intracranial neural measurements can be compared.
关 键 词: 技术; 神经技术; 神经信息
课程来源: 视频讲座网
最后编审: 2019-12-17:lxf
阅读次数: 40