Multimodal identification of the mouse brain using simultaneous Ca 2+ imaging and fMRI.

Francesca Mandino, Corey Horien, Xilin Shen, Gabriel Desrosiers-Grégoire, Wendy Luo, Marija Markicevic, R Todd Constable, Xenophon Papademetris, Mallar M Chakravarty, Richard F Betzel, Evelyn M R Lake
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Abstract

Individual differences in neuroimaging are of interest to clinical and cognitive neuroscientists based on their potential for guiding the personalized treatment of various heterogeneous neurological conditions and diseases. Despite many advantages, the workhorse in this arena, BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI) suffers from low spatiotemporal resolution and specificity as well as a propensity for noise and spurious signal corruption. To better understand individual differences in BOLD-fMRI data, we can use animal models where fMRI, alongside complementary but more invasive contrasts, can be accessed. Here, we apply simultaneous wide-field fluorescence calcium imaging and BOLD-fMRI in mice to interrogate individual differences using a connectome-based identification framework adopted from the human fMRI literature. This approach yields high spatiotemporal resolution cell-type specific signals (here, from glia, excitatory, as well as inhibitory interneurons) from the whole cortex. We found mouse multimodal connectome-based identification to be successful and explored various features of these data.

利用同步 Ca 2+ 成像和 fMRI 对小鼠大脑进行多模式识别。
临床和认知神经科学家对神经成像中的个体差异很感兴趣,因为这些差异有可能指导对各种不同神经状况和疾病的个性化治疗。尽管BOLD(血氧水平依赖性)功能磁共振成像(fMRI)有很多优点,但它的时空分辨率和特异性较低,而且容易产生噪声和虚假信号。为了更好地理解 BOLD-fMRI 数据中的个体差异,我们可以使用动物模型,在这些动物模型中,fMRI 与互补但更具侵入性的对比可以被访问。在这里,我们采用基于连接体的识别框架(该框架借鉴了人类 fMRI 文献),在小鼠中同时应用宽场荧光钙成像和 BOLD-fMRI 来研究个体差异。这种方法能从整个皮层获得高时空分辨率的细胞类型特异性信号(这里包括来自神经胶质、兴奋性和抑制性中间神经元的信号)。我们发现基于小鼠多模态连接体的识别是成功的,并探索了这些数据的各种特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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