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Generative models, linguistic communication and active inference

Friston, KJ; Parr, T; Yufik, Y; Sajid, N; Price, CJ; Holmes, E; (2020) Generative models, linguistic communication and active inference. Neuroscience & Biobehavioral Reviews , 118 pp. 42-64. 10.1016/j.neubiorev.2020.07.005. Green open access

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Abstract

This paper presents a biologically plausible generative model and inference scheme that is capable of simulating communication between synthetic subjects who talk to each other. Building on active inference formulations of dyadic interactions, we simulate linguistic exchange to explore generative models that support dialogues. These models employ high-order interactions among abstract (discrete) states in deep (hierarchical) models. The sequential nature of language processing mandates generative models with a particular factorial structure—necessary to accommodate the rich combinatorics of language. We illustrate linguistic communication by simulating a synthetic subject who can play the ‘Twenty Questions’ game. In this game, synthetic subjects take the role of the questioner or answerer, using the same generative model. This simulation setup is used to illustrate some key architectural points and demonstrate that many behavioural and neurophysiological correlates of linguistic communication emerge under variational (marginal) message passing, given the right kind of generative model. For example, we show that theta-gamma coupling is an emergent property of belief updating, when listening to another.

Type: Article
Title: Generative models, linguistic communication and active inference
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neubiorev.2020.07.005
Publisher version: https://doi.org/10.1016/j.neubiorev.2020.07.005
Language: English
Additional information: This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).
Keywords: Bayesian, Language, connectivity, free energy, hierarchical, inference, message passing, neuronal
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
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 > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Speech, Hearing and Phonetic Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
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 > Faculty of Population Health Sciences > Institute of Epidemiology and Health
URI: https://discovery.ucl.ac.uk/id/eprint/10106855
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