Multiscale integration: beyond internalism and externalism

Ramstead, Maxwell J. D.; Kirchhoff, Michael D.; Constant, Axel; Friston, Karl J.

doi:10.1007/s11229-019-02115-x

Cited by 107 publications

(99 citation statements)

References 78 publications

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“…In their impressive synthesis, Veissière and colleagues argue that enactive social interaction is a prime ground for generating higher-order prior beliefs (both implicit and explicit). We share this enthusiasm for social-cultural patterning of priors, and also their comprehensive embrasure of the enactive and embodied turn within the larger predictive processing movement (Allen & Friston 2018;Barrett & Simmons 2015;Gallagher & Allen 2018;Ramstead et al 2019b;2019c;Seth 2013). As they elegantly argue, ontogenetic development provides a wealth of knowledge about how to behave in a given context.…”

Section: Open Peer Commentarymentioning

confidence: 78%

Thinking through other minds: A variational approach to cognition and culture

et al. 2019

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The processes underwriting the acquisition of culture remain unclear. How are shared habits, norms, and expectations learned and maintained with precision and reliability across large-scale sociocultural ensembles? Is there a unifying account of the mechanisms involved in the acquisition of culture? Notions such as “shared expectations,” the “selective patterning of attention and behaviour,” “cultural evolution,” “cultural inheritance,” and “implicit learning” are the main candidates to underpin a unifying account of cognition and the acquisition of culture; however, their interactions require greater specification and clarification. In this article, we integrate these candidates using the variational (free-energy) approach to human cognition and culture in theoretical neuroscience. We describe the construction by humans of social niches that afford epistemic resources called cultural affordances. We argue that human agents learn the shared habits, norms, and expectations of their culture through immersive participation in patterned cultural practices that selectively pattern attention and behaviour. We call this process “thinking through other minds” (TTOM) – in effect, the process of inferring other agents’ expectations about the world and how to behave in social context. We argue that for humans, information from and about other people's expectations constitutes the primary domain of statistical regularities that humans leverage to predict and organize behaviour. The integrative model we offer has implications that can advance theories of cognition, enculturation, adaptation, and psychopathology. Crucially, this formal (variational) treatment seeks to resolve key debates in current cognitive science, such as the distinction between internalist and externalist accounts of theory of mind abilities and the more fundamental distinction between dynamical and representational accounts of enactivism.

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Section: Open Peer Commentarymentioning

confidence: 78%

Thinking through other minds: A variational approach to cognition and culture

et al. 2019

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“…This speaks directly to embodied and enactive approaches in cognitive neuroscience, and provides a computationally tractable framework for the metaphors mobilised by these paradigms (e.g., Gallagher, 2017 ; Noë, 2004 ; Thompson, 2010 ; Varela et al, 1991 ). The notion of entailment captures the fact that the generative model is entailed by the dynamics of a living system under active inference ( Kirchhoff, 2018 ; Kirchhoff & Froese, 2017 ; Kirchhoff & Robertson, 2018 ; Ramstead, Kirchhoff, et al, 2019 ). This interpretation of the generative and recognition models allows us to model the dialectic between embodiment (what an organism is ) and enactment (what an organism does ).…”

Section: Enactive Inferencementioning

confidence: 99%

“…In this sense, the active inference scheme is enactive ( Thompson, 2010 ; Varela, Thompson, & Rosch, 1991 ), in the enactive sense of being for action ( Bruineberg & Rietveld, 2014 ; Kirchhoff, 2018 ; Kirchhoff & Froese, 2017 ; Kirchhoff & Kiverstein, 2019 ; Ramstead et al, 2018 ; Ramstead, Kirchhoff, Constant, & Friston, 2019 ). Our enactive interpretation of active inference – what might be called enactive inference – follows what has been called the pragmatic turn in cognitive science ( Engel, Friston, & Kragic, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

A tale of two densities: active inference is enactive inference

2019

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The aim of this article is to clarify how best to interpret some of the central constructs that underwrite the free-energy principle (FEP) -and its corollary, active inference -in theoretical neuroscience and biology: namely, the role that generative models and variational densities play in this theory. We argue that these constructs have been systematically misrepresented in the literature, because of the conflation between the FEP and active inference, on the one hand, and distinct (albeit closely related) Bayesian formulations, centred on the brain -variously known as predictive processing, predictive coding or the prediction error minimisation framework. More specifically, we examine two contrasting interpretations of these models: a structural representationalist interpretation and an enactive interpretation. We argue that the structural representationalist interpretation of generative and recognition models does not do justice to the role that these constructs play in active inference under the FEP. We propose an enactive interpretation of active inferencewhat might be called enactive inference. In active inference under the FEP, the generative and recognition models are best cast as realising inference and control -the self-organising, belief-guided selection of action policies -and do not have the properties ascribed by structural representationalists.

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“…In this way, beliefs about the consequences of different possible actions can be evaluated against preferred (typically phenotype-congruent) consequences to inform action selection. In active inference, every organism enacts an implicit phenotype-congruent model of its embodied existence (Ramstead et al, 2019), which has been referred to as self-evidencing (Hohwy, 2016). Active inference has been used to develop neural process theories and explain the acquisition of epistemic habits (e.g., Friston, FitzGerald et al 2016, Friston, FitzGerald et al 2017.…”

Section: A Bayesian View On Life: Survival Of the Fittest Modelmentioning

confidence: 99%

Deeply Felt Affect: The Emergence of Valence in Deep Active Inference

Hesp¹,

Smith²,

Parr³

et al. 2019

Preprint

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The positive-negative axis of emotional valence has long been recognised as fundamental to adaptive behaviour, but its domain-generality has largely eluded formal theories and modelling. Using deep active inference – a hierarchical inference scheme that rests on inverting a model of how sensory data are generated – we develop a principled Bayesian account of emotional valence. This formulation associates valence with subjective fitness and exploits the domain-generality of second-order beliefs (i.e., beliefs about beliefs). We construct an affective agent that infers its valence state from the expected precision of its phenotype-congruent action model (i.e., subjective fitness) in any given environment. The ensuing affective states then optimise that confidence pre-emptively. The evidence for inferred (i.e., ‘felt’) valenced states depends upon the (Bayes-optimal) updating term for subjective fitness, which we label affective charge (AC). We simulate affective inference in a T-maze paradigm requiring context learning, followed by context reversal. The result is a deep (biologically plausible) agent that infers its affective state and reduces its uncertainty through internal action (i.e., optimises prior beliefs that underwrite confidence). Thus, we demonstrate the potential of active inference in providing a formal and computationally tractable account of the link between affect, (mental) action, and implicit meta-cognition.

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Multiscale integration: beyond internalism and externalism

Cited by 107 publications

References 78 publications

Thinking through other minds: A variational approach to cognition and culture

Thinking through other minds: A variational approach to cognition and culture

A tale of two densities: active inference is enactive inference

Deeply Felt Affect: The Emergence of Valence in Deep Active Inference

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