Characterization of Brain Noise using Multimodal Mutual Information

描述(由申请人提供)：本项目的目标是利用功能磁共振成像(FMRI)、近红外光学(NIRS)和系统生理学测量的并行多模式记录，以区分这些类型的噪声中的每一种。这个项目的新奇之处在于，为了识别大脑成像信号中的噪声源，将使用这些并行测量之间共享的相互信息。这将使我们能够更好地了解这种噪音的性质，更好地设计过滤器和分析以消除它，并改进对大脑活动微小变化的检测。我们假设i)并行的光信号和fMRI信号之间的互信息将在这些模式中生成更真实的噪声结构模型，以及ii)对该噪声的更好的定量理解将导致识别当前分析过程中的局限性并优化改进的统计技术。目的1.使用并行的多模式光学和fMRI记录，确定仪器和系统噪声源对fMRI BOLD(血氧水平依赖)信号的贡献。目的2.在正中神经刺激与NIRS和fMRI同时进行的受试者间和受试者内测试-重测实验中，表征基线生理学在系统偏差中的作用。目的3.研究受试者注意在调节fMRI BOLD信号单次试验变异性中的作用。目的4.比较fMRI和NIRS中降低生理噪声的方法，并确定现实噪声对标准分析模型假设的影响。

DESCRIPTION (provided by applicant): The objective of this project is to utilize concurrent multimodal recordings using functional magnetic resonance imaging (fMRI), near-infrared optical (NIRS) and measures of systemic physiology in order to separate the contributions of each of these types of noise. The novelty of this project will be the use of mutual information shared between these concurrent measurements in order to identify the sources of noise in the brain-imaging signal. This will allow us to better understand the nature of this noise, to better design filters and analysis to remove it, and to improve the detection of small changes in activity in the brain. We hypothesize that i) mutual information between concurrent optical and fMRI signals will generate more realistic models of the noise structure in these modalities and ii) that a better quantitative understanding of this noise will lead to the identification of limitations in current analysis procedures and to the optimization of improved statistical techniques. Aim 1. Identify the contributions of instrumental and systemic sources of noise to the fMRI BOLD (blood oxygen level dependent) signal using concurrent multimodal optical and fMRI recordings. Aim 2. Characterize the role of baseline physiology in systematic biases during inter- and intra-subject test-retest experiments using median-nerve stimulation with concurrent NIRS and fMRI. Aim 3. Investigate the role of subject attention in mediating single-trial variability in the fMRI BOLD signal. Aim 4. Compare approaches for reducing physiological noise in fMRI and NIRS and determine the effect of realistic noise on the assumptions of the standard analysis model.