NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis improves brain activity detection across rodent and human functional MRI contexts.

Imaging neuroscience (Cambridge, Mass.) Pub Date : 2024-10-24 eCollection Date: 2024-10-01 DOI:10.1162/imag_a_00325
Russell W Chan, Giles Hamilton-Fletcher, Bradley J Edelman, Muneeb A Faiq, Thajunnisa A Sajitha, Steen Moeller, Kevin C Chan
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Abstract

NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis (PCA) has been shown to selectively suppress thermal noise and improve the temporal signal-to-noise ratio (tSNR) in human functional magnetic resonance imaging (fMRI). However, the feasibility to improve data quality for rodent fMRI using NORDIC PCA remains uncertain. NORDIC PCA may also be particularly beneficial for improving topological brain mapping, as conventional mapping requires precise spatiotemporal signals from large datasets (ideally ~1 hour acquisition) for individual representations. In this study, we evaluated the effects of NORDIC PCA compared with "Standard" processing in various rodent fMRI contexts that range from task-evoked optogenetic fMRI to resting-state fMRI. We also evaluated the effects of NORDIC PCA on human resting-state and retinotopic mapping fMRI via population receptive field (pRF) modeling. In rodent optogenetic fMRI, apart from doubling the tSNR, NORDIC PCA resulted in a larger number of activated voxels and a significant decrease in the variance of evoked brain responses without altering brain morphology. In rodent resting-state fMRI, we found that NORDIC PCA induced a nearly threefold increase in tSNR and preserved task-free relative cerebrovascular reactivity (rCVR) across cortical depth. NORDIC PCA further improved the detection of TGN020-induced aquaporin-4 inhibition on rCVR compared with Standard processing without NORDIC PCA. NORDIC PCA also increased the tSNR for both human resting-state and pRF fMRI, and for the latter also increased activation cluster sizes while retaining retinotopic organization. This suggests that NORDIC PCA preserves the spatiotemporal precision of fMRI signals needed for pRF analysis, and effectively captures small activity changes with high sensitivity. Taken together, these results broadly demonstrate the value of NORDIC PCA for the enhanced detection of neural dynamics across various rodent and human fMRI contexts. This can in turn play an important role in improving fMRI image quality and sensitivity for translational and preclinical neuroimaging research.

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经分布校正的噪声降低(NORDIC)主成分分析提高了啮齿类动物和人类功能磁共振成像的大脑活动检测能力。
经分布校正的噪声降低(NORDIC)主成分分析(PCA)已被证明能选择性地抑制热噪声并改善人类功能磁共振成像(fMRI)中的时间信噪比(tSNR)。然而,使用 NORDIC PCA 提高啮齿动物 fMRI 数据质量的可行性仍不确定。NORDIC PCA 还可能特别有利于改善拓扑脑图谱,因为传统的脑图谱需要从大型数据集(理想情况下采集约 1 小时)中获取单个表征的精确时空信号。在本研究中,我们评估了 NORDIC PCA 与 "标准 "处理相比在各种啮齿类 fMRI 情境下的效果,这些情境包括任务诱发光遗传 fMRI 和静息态 fMRI。我们还通过群体感受野(pRF)建模评估了 NORDIC PCA 对人类静息态和视网膜位点映射 fMRI 的影响。在啮齿动物光遗传 fMRI 中,NORDIC PCA 除了使 tSNR 增加一倍外,还增加了激活体素的数量,并显著降低了大脑诱发反应的方差,而不会改变大脑形态。在啮齿动物静息态 fMRI 中,我们发现 NORDIC PCA 使 tSNR 增加了近三倍,并保留了整个皮层深度的无任务相对脑血管反应性(rCVR)。与不使用 NORDIC PCA 的标准处理相比,NORDIC PCA 进一步提高了 TGN020 诱导的水通道蛋白-4 抑制对 rCVR 的检测能力。NORDIC PCA 还提高了人类静息态和 pRF fMRI 的 tSNR,后者还在保留视网膜视向组织的同时增加了激活集群的大小。这表明 NORDIC PCA 保留了 pRF 分析所需的 fMRI 信号的时空精度,并能以高灵敏度有效捕捉微小的活动变化。综上所述,这些结果广泛证明了 NORDIC PCA 在各种啮齿动物和人类 fMRI 环境中增强神经动态检测的价值。这反过来又能在提高转化和临床前神经成像研究的 fMRI 图像质量和灵敏度方面发挥重要作用。
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Synthetic data in generalizable, learning-based neuroimaging. Processing, evaluating, and understanding FMRI data with afni_proc.py. NOise Reduction with DIstribution Corrected (NORDIC) principal component analysis improves brain activity detection across rodent and human functional MRI contexts. Measurement variability of blood-brain barrier permeability using dynamic contrast-enhanced magnetic resonance imaging. ECCENTRIC: A fast and unrestrained approach for high-resolution in vivo metabolic imaging at ultra-high field MR.
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