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首页> 外文期刊>Human brain mapping >Robust Bayesian estimation of the hemodynamic response function in event-related BOLD fMRI using basic physiological information.
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Robust Bayesian estimation of the hemodynamic response function in event-related BOLD fMRI using basic physiological information.

机译：使用基本生理信息对事件相关BOLD fMRI中血液动力学响应功能的稳健贝叶斯估计。

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In BOLD fMRI data analysis, robust and accurate estimation of the Hemodynamic Response Function (HRF) is still under investigation. Parametric methods assume the shape of the HRF to be known and constant throughout the brain, whereas non-parametric methods mostly rely on artificially increasing the signal-to-noise ratio. We extend and develop a previously proposed method that makes use of basic yet relevant temporal information about the underlying physiological process of the brain BOLD response in order to infer the HRF in a Bayesian framework. A general hypothesis test is also proposed, allowing to take advantage of the knowledge gained regarding the HRF to perform activation detection. The performances of the method are then evaluated by simulation. Great improvement is shown compared to the Maximum-Likelihood estimate in terms of estimation error, variance, and bias. Robustness of the estimators with regard to the actual noise structure or level, as well as the stimulus sequence, is also proven. Lastly, fMRI data with an event-related paradigm are analyzed. As suspected, the regions selected from highly discriminating activation maps resulting from the method exhibit a certain inter-regional homogeneity in term of HRF shape, as well as noticeable inter-regional differences.
机译：在BOLD fMRI数据分析中，仍在研究对血流动力学响应函数（HRF）的可靠而准确的估计。参数化方法假设HRF的形状在整个大脑中是已知的并且恒定，而非参数化方法主要依赖于人为地增加信噪比。我们扩展并开发了一种先前提出的方法，该方法利用有关脑BOLD反应的潜在生理过程的基本但相关的时间信息，以推断贝叶斯框架中的HRF。还提出了一般的假设检验，从而可以利用有关HRF的知识来执行激活检测。然后通过仿真评估该方法的性能。与最大似然估计相比，在估计误差，方差和偏差方面显示出很大的改进。还证明了估计器相对于实际噪声结构或级别以及刺激序列的鲁棒性。最后，分析具有事件相关范例的fMRI数据。如所怀疑的，从该方法产生的高度区分的激活图中选择的区域在HRF形状方面表现出一定的区域间同质性，以及明显的区域间差异。

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