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Consistent hemodynamic response function estimation in functional MRI by first order differencing

机译:一阶微分法在功能性MRI中一致的血流动力学反应功能估计

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Non-parametric hemodynamic response function (HRF) estimation in noisy functional Magnetic Resonance Imaging (fMRI) plays an important role when investigating the temporal dynamic of a brain region response during activations. Assuming the drift Lipschitz continuous; a new algorithm for non-parametric HRF estimation is derived in this paper. The proposed algorithm estimates the HRF by applying a first order differencing to the fMRI time series samples. It is shown that the proposed HRF estimator is √(N) consistent. Its performance is assessed using both simulated and a real fMRI data sets obtained from an event-related fMRI experiment. The application results reveal that the proposed HRF estimation method is efficient both computationally and in term of accuracy.
机译:当研究激活过程中大脑区域反应的时间动态时,在嘈杂的功能性磁共振成像(fMRI)中,非参数血液动力学反应功能(HRF)估计起着重要作用。假设Lipschitz的漂移是连续的;本文推导了一种新的非参数HRF估计算法。所提出的算法通过对fMRI时间序列样本应用一阶差分来估计HRF。结果表明,提出的HRF估计量是√(N)一致的。使用从事件相关的fMRI实验获得的模拟和真实fMRI数据集评估其性能。应用结果表明,提出的HRF估计方法在计算和准确性方面都是有效的。

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