Supplementary Material for: Brain Connectivity in Ateles geoffroyi: Resting-State Functional Magnetic Resonance Imaging of Working Memory and Executive Control

The objective of this research was to describe the organization and connectivity of the working memory (WM) and executive control (EC) networks in Ateles geoffroyi in resting-state conditions. Recent studies have shown that resting-state activity may underlie rudimentary brain functioning, showing that several brain regions can be tonically active at rest, maximizing the efficiency of information transfer while preserving a low physical connection cost. Whole-brain resting-state images were acquired from three healthy adult Ateles monkeys (2 females, 1 male; mean age 10.5 ± SD 2.5 years). Data were analyzed with independent component analysis, and results were grouped together using the GIFT software. The present study compared the EC and WM networks obtained with human data and with results found in the literature in other primate species. Nine resting-state networks were found, which were similar to resting networks found in healthy human adults in the prefrontal basal portion and frontopolar area. Additionally, components of the WM network were found to be extending into the hypothalamus and the olfactory areas. A key finding was the discovery of connections in the WM and EC networks to the hypothalamus, the motor cortex, and the entorhinal cortex, suggesting that information is integrated from larger brain areas. The correlated areas suggest that many elements of WM and EC may be conserved across primate species. Characterization of these networks in resting-state conditions in nonhuman primate brains is a fundamental prerequisite for understanding of the neural bases underlying the evolution and function of this cognitive system.本研究旨在描述静息态（resting-state）条件下黑掌蜘蛛猴（Ateles geoffroyi）工作记忆（working memory, WM）与执行控制（executive control, EC）网络的组织架构与连接特性。既往研究表明，静息态活动是大脑基础功能的核心支撑，诸多脑区可在静息状态下保持紧张性激活，在维持较低物理连接成本的同时，最大化信息传递效率。本研究从3只健康成年蜘蛛猴（2雌1雄，平均年龄10.5±标准差2.5岁）中采集全脑静息态影像数据，采用独立成分分析（independent component analysis, ICA）对数据进行分析，并通过GIFT软件完成组水平结果整合。本研究将本次识别得到的EC与WM网络，与人类影像数据及其他灵长类物种的相关文献报道结果进行了对比。本研究共检出9个静息态网络，其特征与健康成人前额叶基底区及额极区的静息态网络高度相似。此外，研究发现工作记忆网络的成分可延伸至下丘脑与嗅觉脑区。本研究的关键发现为：WM与EC网络可与下丘脑、运动皮层及内嗅皮层建立连接，提示大脑可从更广范围的脑区整合信息。上述相关脑区表明，工作记忆与执行控制的诸多核心特征可能在灵长类物种间具有演化保守性。对非人类灵长类动物大脑静息态下的此类网络进行特征解析，是解析该认知系统演化与功能背后神经基础的核心前提。