Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction de la Recherche Fondamentale, NeuroSpin Center, Gif-sur-Yvette, France; Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale U992, Gif-sur-Yvette, France; Université Paris Sud, Université Paris-Saclay, Orsay, France.
Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction de la Recherche Fondamentale, NeuroSpin Center, Gif-sur-Yvette, France; Analysis and Information Treatment Unit, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Gif-sur-Yvette, France.
Neuroimage. 2020 Feb 15;207:116353. doi: 10.1016/j.neuroimage.2019.116353. Epub 2019 Nov 16.
Non-human primate functional MRI (fMRI) is a growing field in neuroscience. However, there is no standardized method for monkey fMRI data analysis, specifically for data preprocessing. The preprocessing of monkey fMRI data is challenged by several technical and experimental specificities of the monkey research such as artifacts related to body movements or to intracranial leads. Here we propose to address these challenges by developing a new versatile pipeline for macaque fMRI preprocessing. We developed a Python module, Pypreclin, to process raw images using state of the art algorithms embedded in a fully automatic pipeline. To evaluate its robustness, we applied Pypreclin to fMRI data acquired at 3T in both awake and anesthetized macaques, with or without iron oxide contrast agent, using single loop or multichannel phased-array coils, combined or not with intracranial implanted electrodes. We performed both resting-state and auditory evoked fMRI and compared the results of Pypreclin to a previously employed preprocessing pipeline. Pypreclin successfully achieved the registration of the fMRI data to the macaque brain template in all the experimental conditions. Moreover, Pypreclin enables more accurate locations of auditory evoked activations in relation to the gray matter at corrected level in the awake fMRI condition. Finally, using the Primate neuroimaging Data-Exchange open access platform, we could further validate Pypreclin for monkey fMRI images that were acquired at ultra-high fields, from other institutions and using different protocols. Pypreclin is a validated preprocessing tool that adapts to diverse experimental and technical situations of monkey fMRI. Pypreclin code is available on open source data sharing platform.
非人类灵长类动物功能磁共振成像(fMRI)是神经科学领域的一个新兴领域。然而,针对猴子 fMRI 数据分析,特别是数据预处理,还没有标准化的方法。猴子 fMRI 数据的预处理受到猴子研究中几个技术和实验特异性的挑战,例如与身体运动或颅内导联相关的伪影。在这里,我们通过开发一种新的用于猕猴 fMRI 预处理的通用管道来解决这些挑战。我们开发了一个 Python 模块 Pypreclin,使用嵌入在全自动管道中的最先进算法处理原始图像。为了评估其稳健性,我们将 Pypreclin 应用于在 3T 下采集的清醒和麻醉猕猴的 fMRI 数据,无论是否使用氧化铁对比剂,使用单环或多通道相控阵线圈,是否结合颅内植入电极。我们进行了静息态和听觉诱发 fMRI,并将 Pypreclin 的结果与之前使用的预处理管道进行了比较。Pypreclin 成功地在所有实验条件下将 fMRI 数据注册到猕猴大脑模板。此外,在清醒 fMRI 条件下,Pypreclin 能够更准确地定位听觉诱发激活相对于灰质的位置。最后,使用灵长类动物神经影像学数据交换开放访问平台,我们可以进一步验证 Pypreclin 对来自其他机构和使用不同协议在超高场采集的猴子 fMRI 图像的适用性。Pypreclin 是一种经过验证的预处理工具,可适应猴子 fMRI 的各种实验和技术情况。Pypreclin 代码可在开源数据共享平台上获得。