Frontal mechanisms underlying primate calls recognition by humans

Leonardo Ceravolo, Coralie Debracque, Eva Pool, Thibaud Gruber, Didier Grandjean
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Abstract

Abstract The ability to process verbal language seems unique to humans and relies not only on semantics but on other forms of communication such as affective vocalisations, that we share with other primate species—particularly great apes (Hominidae). To better understand these processes at the behavioural and brain level, we asked human participants to categorize vocalizations of four primate species including human, great apes (chimpanzee and bonobo), and monkey (rhesus macaque) during MRI acquisition. Classification was above chance level for all species but bonobo vocalizations. Imaging analyses were computed using a participant-specific, trial-by-trial fitted probability categorization value in a model-based style of data analysis. Model-based analyses revealed the implication of the bilateral orbitofrontal cortex and inferior frontal gyrus pars triangularis (IFGtri) respectively correlating and anti-correlating with the fitted probability of accurate species classification. Further conjunction analyses revealed enhanced activity in a sub-area of the left IFGtri specifically for the accurate classification of chimpanzee calls compared to human voices. Our data—that are controlled for acoustic variability between species—therefore reveal distinct frontal mechanisms that shed light on how the human brain evolved to process vocal signals.
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灵长类动物呼叫被人类识别背后的额叶机制
处理口头语言的能力似乎是人类独有的,不仅依赖于语义学,还依赖于其他形式的交流,如情感发声,这是我们与其他灵长类动物(尤其是类人猿)共有的。为了在行为和大脑层面上更好地理解这些过程,我们要求人类参与者在MRI采集过程中对四种灵长类动物的发声进行分类,包括人类、类人猿(黑猩猩和倭黑猩猩)和猴子(恒河猴)。除倭黑猩猩发声外,所有物种的分类都高于偶然水平。在基于模型的数据分析风格中,使用参与者特定的、逐个试验拟合的概率分类值来计算成像分析。基于模型的分析揭示了双侧眶额皮质和额下三角回(IFGtri)分别与准确物种分类的拟合概率相关和反相关的含义。进一步的联合分析显示,与人类声音相比,左侧IFGtri的一个子区域的活动增强,专门用于黑猩猩叫声的准确分类。我们的数据——控制了不同物种之间的声音差异——因此揭示了不同的额叶机制,揭示了人类大脑是如何进化到处理声音信号的。
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