Understanding the rat neurochemical connectome is fundamental for exploring neuronal information processing. By using advanced data mining, supervised machine learning, and network analysis, this study integrates over 5 decades of neuroanatomical investigations into a multiscale, multilayer neurochemical connectome of the rat brain. This neurochemical connectivity database (ChemNetDB) is supported by comprehensive systematically-determined receptor distribution maps. The rat connectome has an onion-type structural organization and shares a number of structural features with mesoscale connectomes of mouse and macaque. Furthermore, we demonstrate that extremal values of graph theoretical measures (e.g., degree and betweenness) are associated with evolutionary-conserved deep brain structures such as amygdala, bed nucleus of the stria terminalis, dorsal raphe, and lateral hypothalamus, which regulate primitive, yet fundamental functions, such as circadian rhythms, reward, aggression, anxiety, and fear. The ChemNetDB is a freely available resource for systems analysis of motor, sensory, emotional, and cognitive information processing.

了解大鼠神经化学连接组是探索神经元信息处理的基础。通过使用先进的数据挖掘、监督机器学习和网络分析，这项研究将 5 年来的神经解剖学研究整合到大鼠大脑的多尺度、多层神经化学连接组中。该神经化学连接数据库 (ChemNetDB) 由全面、系统确定的受体分布图支持。大鼠连接体具有洋葱型结构组织，与小鼠和猕猴的中尺度连接体具有许多结构特征。此外，我们证明图论测量的极值（例如度和介数）与进化保守的深层大脑结构有关，例如杏仁核、终纹床核、中缝背侧和下丘脑外侧，它们调节原始的，但基本功能，例如昼夜节律、奖励、攻击性、焦虑和恐惧。 ChemNetDB 是一个免费资源，用于运动、感觉、情感和认知信息处理的系统分析。