Conflicting emergences. Weak vs. strong emergence for the modelling of brain function.
Neuroscience and Biobehavioral Reviews April 1, 2019 Federico Turkheimer, Peter J. Hellyer, Angie A. Kehagia et al.
Emergence describes how complex systems exhibit properties not easily explained by their individual parts, seen in ant colonies, bird flocks, or brain function. This paper clarifies the concept, distinguishing strong emergence (where properties are irreducible to lower-level mechanisms) from weak emergence (where properties arise from but are explainable by lower-level interactions). It argues that models based on strong emergence, such as the free energy principle and integrated information theory, risk metaphysical implausibility and overdetermination, making them only one of many possible explanations. In contrast, weakly emergent computational models like oscillatory networks, which start from biologically plausible elementary units, are ontologically sound and offer a powerful approach for future neuroscientific research.