The concept of “emergence” has become commonplace in the modelling of complex systems, both natural and man-made; a functional property” emerges” from a system when it cannot be readily explained by the properties of the system’s sub-units. A bewildering array of adaptive and sophisticated behaviours can be observed from large ensembles of elementary agents such as ant colonies, bird flocks or by the interactions of elementary material units such as molecules or weather elements. Ultimately, emergence has been adopted as the ontological support of a number of attempts to model brain function. This manuscript aims to clarify the ontology of emergence and delve into its many facets, particularly into its “strong” and “weak” versions that underpin two different approaches to the modelling of behaviour. The first group of models is here represented by the “free energy” principle of brain function and the “integrated information theory” of consciousness. The second group is instead represented by computational models such as oscillatory networks that use mathematical scalable representations to generate emergent behaviours and are then able to bridge neurobiology with higher mental functions. Drawing on the epistemological literature, we observe that due to their loose mechanistic links with the underlying biology, models based on strong forms of emergence are at risk of metaphysical implausibility. This, in practical terms, translates into the over determination that occurs when the proposed model becomes only one of a large set of possible explanations for the observable phenomena. On the other hand, computational models that start from biologically plausible elementary units, hence are weakly emergent, are not limited by ontological faults and, if scalable and able to realistically simulate the hierarchies of brain output, represent a powerful vehicle for future neuroscientific research programmes.

在自然和人为复杂系统的建模中，“涌现”的概念已变得司空见惯。当无法通过系统子单元的属性轻易解释时，“功能属性”就会从系统中“出现”。从大量的基本因子（如蚁群，鸟群）或基本物质单元（如分子或天气元素）的相互作用中，可以观察到令人困惑的适应性和复杂行为。最终，出现已被采用作为对脑功能建模的许多尝试的本体论支持。该手稿旨在阐明出现的本体，并深入探讨其出现的各个方面，尤其是其“强”和“弱”版本，它们是行为建模的两种不同方法的基础。第一组模型在这里以大脑功能的“自由能”原理和意识的“综合信息论”为代表。相反，第二组由诸如振动网络之类的计算模型表示，该模型使用数学可缩放表示形式来生成紧急行为，然后能够将神经生物学与更高的心理功能联系起来。利用认识论文献，我们观察到由于它们与基础生物学的松散的机械联系，基于强出现形式的模型存在形而上学难以置信的风险。实际上，这转化为当确定的模型仅成为可观察现象的大量可能解释之一时发生的过度确定。另一方面，