Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain.

中文翻译：

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迈向 HCP 型 Macaque 连接体：24 通道 3T 多阵列线圈、MRI 序列和预处理

猕猴是一种重要的动物模型，通过侵入性研究可以更好地了解包括人类在内的灵长类动物的皮层组织。然而，用于无创图像采集（例如 MRI RF 线圈和脉冲序列协议）和图像数据预处理的工具和方法已经落后于为人类开发的工具和方法。为了解决较小的猕猴大脑的结构和功能特征，需要高空间、时间和角度分辨率以及高信噪比来确保良好的图像质量。为了应对这些挑战，我们开发了一种用于 3-T MRI 的猕猴 24 通道接收线圈，具有并行成像能力。该线圈使人类连接组计划 (HCP) 图像采集协议能够适应体内猕猴大脑。此外，我们将 HCP 预处理方法应用于猕猴大脑，包括结构、功能 MRI (fMRI) 和扩散 MRI (dMRI) 的空间最小预处理。该线圈在数据采集中提供了必要的高信噪比和高效率，允许 dMRI 和 fMRI 的四倍和五倍加速度。皮质的自动 FreeSurfer 分割、皮质表面的重建、fMRI 中伪影和干扰信号的去除以及 dMRI 的失真校正都表现良好，基本神经生物学测量的整体质量与 HCP 相当。与来自公共共享数据集的相比，fMRI 中的功能连接分析显示出更高的灵敏度。基于 Tractography 的连通性估计与示踪剂连通性相关，类似于使用离体 dMRI 实现的连通性。