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The evolution of brain architectures for predictive coding and active inference

Pezzulo, Giovanni; Parr, Thomas; Friston, Karl; (2022) The evolution of brain architectures for predictive coding and active inference. Philosophical Transactions of the Royal Society B: Biological Sciences , 377 (1844) , Article 20200531. 10.1098/rstb.2020.0531. Green open access

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Abstract

This article considers the evolution of brain architectures for predictive processing. We argue that brain mechanisms for predictive perception and action are not late evolutionary additions of advanced creatures like us. Rather, they emerged gradually from simpler predictive loops (e.g. autonomic and motor reflexes) that were a legacy from our earlier evolutionary ancestors-and were key to solving their fundamental problems of adaptive regulation. We characterize simpler-to-more-complex brains formally, in terms of generative models that include predictive loops of increasing hierarchical breadth and depth. These may start from a simple homeostatic motif and be elaborated during evolution in four main ways: these include the multimodal expansion of predictive control into an allostatic loop; its duplication to form multiple sensorimotor loops that expand an animal's behavioural repertoire; and the gradual endowment of generative models with hierarchical depth (to deal with aspects of the world that unfold at different spatial scales) and temporal depth (to select plans in a future-oriented manner). In turn, these elaborations underwrite the solution to biological regulation problems faced by increasingly sophisticated animals. Our proposal aligns neuroscientific theorising-about predictive processing-with evolutionary and comparative data on brain architectures in different animal species. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Type: Article
Title: The evolution of brain architectures for predictive coding and active inference
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1098/rstb.2020.0531
Publisher version: https://doi.org/10.1098/rstb.2020.0531
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & Technology, Life Sciences & Biomedicine, Biology, Life Sciences & Biomedicine - Other Topics, predictive processing, active inference, brain evolution, brain architecture, model selection, natural selection, BASAL GANGLIA, COMPETITION, MECHANISMS, FRAMEWORK, SELECTION, CORTEX, MODEL
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
URI: https://discovery.ucl.ac.uk/id/eprint/10148464
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