Neuroscience Graduate Program and USC Brain Project, University of Southern California, Los Angeles, CA, USA,
Neuroinformatics. 2014 Jan;12(1):93-109. doi: 10.1007/s12021-013-9182-5.
This paper introduces dyadic brain modeling - the simultaneous, computational modeling of the brains of two interacting agents - to explore ways in which our understanding of macaque brain circuitry can ground new models of brain mechanisms involved in ape interaction. Specifically, we assess a range of data on gestural communication of great apes as the basis for developing an account of the interactions of two primates engaged in ontogenetic ritualization, a proposed learning mechanism through which a functional action may become a communicative gesture over repeated interactions between two individuals (the 'dyad'). The integration of behavioral, neural, and computational data in dyadic (or, more generally, social) brain modeling has broad application to comparative and evolutionary questions, particularly for the evolutionary origins of cognition and language in the human lineage. We relate this work to the neuroinformatics challenges of integrating and sharing data to support collaboration between primatologists, neuroscientists and modelers that will help speed the emergence of what may be called comparative neuro-primatology.
本文介绍了对偶脑建模——同时对两个相互作用的主体的大脑进行计算建模——以探索我们对猕猴大脑回路的理解如何为涉及类人猿相互作用的大脑机制的新模型提供基础。具体来说，我们评估了大量关于类人猿手势交流的数据集，以此来构建一个关于两只灵长类动物在个体发生仪式化过程中相互作用的模型，这是一种被提议的学习机制，通过这种机制，一个功能动作可能会在两个个体之间的重复相互作用中变成一个交际手势（“对偶体”）。在对偶体（或更一般地说，社会）大脑建模中整合行为、神经和计算数据，对比较和进化问题具有广泛的应用，特别是对于人类谱系中认知和语言的进化起源。我们将这项工作与神经信息学的挑战联系起来，即整合和共享数据以支持灵长类动物学家、神经科学家和建模者之间的合作，这将有助于加快比较神经灵长类学的出现。
