Conflicting emergences. Weak vs. strong emergence for the modelling of brain function
| Autor: | Federico Turkheimer, Paul Expert, Peter J. Hellyer, Jessica Dafflon, Jakub Vohryzek, Louis-David Lord, Mick Brammer, Robert Leech, Angie A. Kehagia |
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| Rok vydání: | 2019 |
| Předmět: |
Property (philosophy)
Consciousness Cognitive Neuroscience Energy (esotericism) media_common.quotation_subject Models Neurological Bayesian inference Complex system Emergence Article 03 medical and health sciences Behavioral Neuroscience 0302 clinical medicine Humans Computational models Natural (music) Computer Simulation Nervous System Physiological Phenomena Oscillators 0501 psychology and cognitive sciences 050102 behavioral science & comparative psychology Strong emergence Multi-scale media_common Cognitive science Computational model Integrated information theory 05 social sciences Brain Weak emergence Neuropsychology and Physiological Psychology Free energy principle Ontology Nerve Net 030217 neurology & neurosurgery |
| Zdroj: | Turkheimer, F E, Hellyer, P, Kehagia, A A, Expert, P, Lord, L-D, Vohryzek, J, De Faria Dafflon, J, Brammer, M & Leech, R 2019, ' Conflicting Emergences. Weak vs. strong emergence for the modelling of brain function ', Neuroscience and Biobehavioral Reviews, vol. 99, pp. 3-10 . https://doi.org/10.1016/j.neubiorev.2019.01.023 |
| ISSN: | 0149-7634 |
| Popis: | 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 overdetermination 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. |
| Databáze: | OpenAIRE |
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