The triple-network model of psychopathology is a framework to explain the functional and structural neuroimaging phenotypes of psychiatric and neurological disorders. It describes the interactions within and between three distributed networks: the salience, default-mode, and central executive networks. These have been associated with brain disorder traits in patients. Homologous networks have been proposed in animal models, but their integration into a triple-network organization has not yet been determined. Using resting-state datasets, we demonstrate conserved spatio-temporal properties between triple-network elements in human, macaque, and mouse. The model predictions were also shown to apply in a mouse model for depression. To validate spatial homologies, we developed a data-driven approach to convert mouse brain maps into human standard coordinates. Finally, using high-resolution viral tracers in the mouse, we refined an anatomical model for these networks and validated this using optogenetics in mice and tractography in humans. Unexpectedly, we find serotonin involvement within the salience rather than the default-mode network. Our results support the existence of a triple-network system in the mouse that shares properties with that of humans along several dimensions, including a disease condition. Finally, we demonstrate a method to humanize mouse brain networks that opens doors to fully data-driven trans-species comparisons.

精神病理学的三重网络模型是解释精神和神经障碍的功能和结构神经影像学表型的框架。它描述了三个分布式网络内部和之间的交互：突出网络、默认模式网络和中央执行网络。这些与患者的脑部疾病特征有关。已经在动物模型中提出了同源网络，但尚未确定将它们整合到三重网络组织中。使用静止状态数据集，我们展示了人类、猕猴和小鼠三重网络元素之间守恒的时空属性。模型预测也被证明适用于抑郁症小鼠模型。为了验证空间同源性，我们开发了一种数据驱动的方法来将小鼠脑图转换为人类标准坐标。最后，我们在小鼠中使用高分辨率病毒示踪剂，为这些网络改进了解剖模型，并使用小鼠光遗传学和人类纤维束成像技术验证了这一点。出乎意料的是，我们发现血清素参与了显着性而不是默认模式网络。我们的结果支持小鼠中存在一个三重网络系统，该系统在多个维度上与人类共享属性，包括疾病状况。最后，我们展示了一种使小鼠大脑网络人性化的方法，该方法为完全数据驱动的跨物种比较打开了大门。我们为这些网络改进了解剖模型，并使用小鼠光遗传学和人类纤维束成像技术验证了这一点。出乎意料的是，我们发现血清素参与了显着性而不是默认模式网络。我们的结果支持小鼠中存在一个三重网络系统，该系统在多个维度上与人类共享属性，包括疾病状况。最后，我们展示了一种使小鼠大脑网络人性化的方法，该方法为完全数据驱动的跨物种比较打开了大门。我们为这些网络改进了解剖模型，并使用小鼠光遗传学和人类纤维束成像技术验证了这一点。出乎意料的是，我们发现血清素参与了显着性而不是默认模式网络。我们的结果支持小鼠中存在一个三重网络系统，该系统在多个维度上与人类共享属性，包括疾病状况。最后，我们展示了一种使小鼠大脑网络人性化的方法，该方法为完全数据驱动的跨物种比较打开了大门。