Generative models, linguistic communication and active inference. (November 2020)

• Record Type: Journal Article
• Authors: Friston, Karl J.; Parr, Thomas; Yufik, Yan; Sajid, Noor; Price, Catherine J.; Holmes, Emma
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 118(2020)
• Page Start: 42
• Page End: 64
• Publication Date: 2020-11
• Subjects: Message passing -- Inference -- Connectivity -- Free energy -- Neuronal -- Hierarchical -- Bayesian -- Language; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2020.07.005
• Languages: English
• ISSNs: 0149-7634

Abstract

Highlights: New (hierarchical) generative model for linguistic interactions. Builds on active inference formulations of dyadic interactions. We simulate agents that ask and answer questions together. Theta-gamma coupling emerges from belief updating under this framework. 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.