Cheadle Jacob E, Davidson-Turner K J, Goosby Bridget J
Department of Sociology, Population Research Center, and The Center on Aging and Population Sciences, The University of Texas at Austin, 305 E. 23rd St., 78712 Austin, TX USA.
The University of Texas at Austin, 305 E. 23rd St., 78712 Austin, TX USA.
Kolner Z Soz Sozpsychol. 2024;76(3):317-350. doi: 10.1007/s11577-024-00936-4. Epub 2024 Mar 19.
Although research including biological concepts and variables has gained more prominence in sociology, progress assimilating the organ of experience, the brain, has been theoretically and technically challenging. Formal uptake and assimilation have thus been slow. Within psychology and neuroscience, the traditional brain, which has made brief appearances in sociological research, is a "bottom-up" processor in which sensory signals are passed up the neural hierarchy where they are eventually cognitively and emotionally processed, after which actions and responses are generated. In this paper, we introduce the Active Inference Framework (AIF), which casts the brain as a Bayesian "inference engine" that tests its "top-down" predictive models against "bottom-up" sensory error streams in its attempts to resolve uncertainty and make the world more predictable. After assembling and presenting key concepts in the AIF, we describe an integrated neuro-bio-social model that prioritizes the microsociological assertion that the scene of action is the situation, wherein brains enculturate. Through such social dynamics, enculturated brains share models of the world with one another, enabling collective realities that disclose the actions afforded in those times and places. We conclude by discussing this neuro-bio-social model within the context of exemplar sociological research areas, including the sociology of stress and health, the sociology of emotions, and cognitive cultural sociology, all areas where the brain has received some degree of recognition and incorporation. In each case, sociological insights that do not fit naturally with the traditional brain model emerge intuitively from the predictive AIF model, further underscoring the interconnections and interdependencies between these areas, while also providing a foundation for a probabilistic sociology.
尽管包含生物学概念和变量的研究在社会学中已变得更加突出,但在理论和技术层面,将经验器官——大脑——纳入其中仍具有挑战性。因此,正式的接纳和吸收进展缓慢。在心理学和神经科学领域,传统的大脑(在社会学研究中曾有过短暂露面)是一个“自下而上”的处理器,其中感官信号沿着神经层级向上传递,最终在那里进行认知和情感处理,之后产生行动和反应。在本文中,我们引入了主动推理框架(AIF),该框架将大脑视为一个贝叶斯“推理引擎”,它将其“自上而下”的预测模型与“自下而上”的感官误差流进行比对,试图解决不确定性并使世界更具可预测性。在汇集并呈现了AIF中的关键概念之后,我们描述了一个综合的神经 - 生物 - 社会模型,该模型优先考虑微观社会学的观点,即行动场景就是情境,大脑在其中实现文化适应。通过这种社会动态,经过文化适应的大脑相互分享世界模型,从而形成集体现实,揭示在那些时间和地点所提供的行动。我们通过在典型社会学研究领域的背景下讨论这个神经 - 生物 - 社会模型来得出结论,这些领域包括压力与健康社会学、情感社会学以及认知文化社会学,在所有这些领域中大脑都已获得了一定程度的认可和纳入。在每种情况下,与传统大脑模型不太契合的社会学见解都能从预测性的AIF模型中直观地呈现出来,这进一步凸显了这些领域之间的相互联系和相互依存关系,同时也为概率社会学奠定了基础。