scholarly journals Toward an Embodied, Embedded Predictive Processing Account

2021 ◽  
Vol 12 ◽  
Author(s):  
Elmarie Venter
Keyword(s):  
Free Energy ◽  
Prediction Error ◽  
The Body ◽  
The Other ◽  
Predictive Processing ◽  
Error Minimization ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Prediction Error Minimization

In this paper, I argue for an embodied, embedded approach to predictive processing and thus align the framework with situated cognition. The recent popularity of theories conceiving of the brain as a predictive organ has given rise to two broad camps in the literature that I call free energy enactivism and cognitivist predictive processing. The two approaches vary in scope and methodology. The scope of cognitivist predictive processing is narrow and restricts cognition to brain processes and structures; it does not consider the body-beyond-brain and the environment as constituents of cognitive processes. Free energy enactivism, on the other hand, includes all self-organizing systems that minimize free energy (including non-living systems) and thus does not offer any unique explanations for more complex cognitive phenomena that are unique to human cognition. Furthermore, because of its strong commitment to the mind-life continuity thesis, it does not provide an explanation of what distinguishes more sophisticated cognitive systems from simple systems. The account that I develop in this paper rejects both of these radical extremes. Instead, I propose a compromise that highlights the necessary components of predictive processing by making use of a mechanistic methodology of explanation. The starting point of the argument in this paper is that despite the interchangeable use of the terms, prediction error minimization and the free energy principle are not identical. But this distinction does not need to disrupt the status quo of the literature if we consider an alternative approach: Embodied, Embedded Predictive Processing (EEPP). EEPP accommodates the free energy principle, as argued for by free energy enactivism, but it also allows for mental representations in its explanation of cognition. Furthermore, EEPP explains how prediction error minimization is realized but, unlike cognitivist PP, it allocates a constitutive role to the body in cognition. Despite highlighting concerns regarding cognitivist PP, I do not wish to discredit the role of the neural domain or representations as free energy enactivism does. Neural structures and processes undeniably contribute to the minimization of prediction error but the role of the body is equally important. On my account, prediction error minimization and free energy minimization are deeply dependent on the body of an agent, such that the body-beyond-brain plays a constitutive role in cognitive processing. I suggest that the body plays three constitutive roles in prediction error minimization: The body regulates cognitive activity, ensuring that cognition and action are intricately linked. The body acts as distributor in the sense that it carries some of the cognitive load by fulfilling the function of minimizing prediction error. Finally, the body serves to constrain the information that is processed by an agent. In fulfilling these three roles, the agent and environment enter into a bidirectional relation through influencing and modeling the structure of the other. This connects EEPP to the free energy principle because the whole embodied agent minimizes free energy in virtue of being a model of its econiche. This grants the body a constitutive role as part of the collection of mechanisms that minimize prediction error and free energy. The body can only fulfill its role when embedded in an environment, of which it is a model. In this sense, EEPP offers the most promising alternative to cognitivist predictive processing and free energy enactivism.

Mechanistic unity of the predictive mind

2019 ◽  
Vol 29 (5) ◽  
pp. 657-675 ◽  
Author(s):  
Paweł Gładziejewski
Keyword(s):  
Prediction Error ◽  
Scientific Explanation ◽  
Error Minimization ◽  
Cognitive Mechanisms ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Prediction Error Minimization ◽  
Epistemic Role ◽  
The Brain ◽  
Mechanistic View

It has recently been argued that cognitive scientists should embrace explanatory pluralism rather than pursue the search for a unificatory framework or theory. This stance dovetails with the mechanistic view of cognitive-scientific explanation. However, one recently proposed theory—based on an idea that the brain is a predictive engine—opposes pluralism with its unificatory ambitions. My aim here is to investigate those pretentions to elucidate what sort of unification is on offer. I challenge the idea that explanatory unification of cognitive science follows from the Free Energy Principle. I claim that if the predictive story is to provide a unification, it is by proposing that many distinct cognitive mechanisms fall under a single prediction-error-minimization schema. I also argue that even though unification is not an absolute evaluative criterion for mechanistic explanations, it may play an epistemic role in evaluating the relative credibility of an explanation.

scholarly journals Modelling ourselves: what the free energy principle reveals about our implicit notions of representation

Synthese ◽  
2021 ◽  
Author(s):  
Matt Sims ◽  
Giovanni Pezzulo
Keyword(s):  
Free Energy ◽  
Philosophy Of Mind ◽  
Predictive Processing ◽  
Energy Principle ◽  
Philosophical Debate ◽  
Free Energy Principle ◽  
Self Organized ◽  
Functional Aspects ◽  
Structural Content ◽  
Unified View

AbstractPredictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle (FEP)—a normative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., representational versus non-representational. Here we argue that these different interpretations depend on implicit assumptions about what qualifies (or fails to qualify) as representational. We deploy the Free Energy Principle (FEP) instrumentally to distinguish four main notions of representation, which focus on organizational, structural, content-related and functional aspects, respectively. The various ways that these different aspects matter in arriving at representational or non-representational interpretations of the Free Energy Principle are discussed. We also discuss how the Free Energy Principle may be seen as a unified view where terms that traditionally belong to different ontologies—e.g., notions of model and expectation versus notions of autopoiesis and synchronization—can be harmonized. However, rather than attempting to settle the representationalist versus non-representationalist debate and reveal something about what representations are simpliciter, this paper demonstrates how the Free Energy Principle may be used to reveal something about those partaking in the debate; namely, what our hidden assumptions about what representations are—assumptions that act as sometimes antithetical starting points in this persistent philosophical debate.

scholarly journals Why should any body have a self?

2017 ◽  
Author(s):  
Jakob Hohwy ◽  
John Michael
Keyword(s):  
Brain Function ◽  
Prediction Error ◽  
The Body ◽  
The Self ◽  
Error Minimization ◽  
Computational Framework ◽  
Key Characteristics ◽  
Prediction Error Minimization ◽  
Hierarchical Bayesian Inference

We use a general computational framework for brain function to develop a theory of the self. The theory is that the self is an inferred model of endogenous, deeply hidden causes of behavior. The general framework for brain function on which we base this theory is that the brain is fundamentally an organ for prediction error minimization.There are three related parts to this project. In the first part (Sections 2-3), we explain how prediction error minimization must lead to the inference of a network of deeply hidden endogenous causes. The key concept here is that prediction error minimization in the long term approximates hierarchical Bayesian inference, where the hierarchy is critical to understand the place of the self, and the body, in the world.In the second part (Sections 4-5), we discuss why such a set of hidden endogenous causes should qualify as a self. We show how a comprehensive prediction error minimization account can accommodate key characteristics of the self. It turns out that, though the modelled endogenous causes are just some among other inferred causes of sensory input, the model is special in being, in a special sense, a model of itself.The third part (Sections 6-7) identifies a threat from such self-modelling: how can a self-model be accurate if it represents itself? We propose that we learn to be who we are through a positive feedback loop: from infancy onward, humans apply agent-models to understand what other agents are up to in their environment, and actively align themselves with those models. Accurate self-models arise and are sustained as a natural consequence of humans’ skill in modeling and interacting with each other. The concluding section situates this inferentialist yet realist theory of the self with respect to narrative conceptions of the self.

scholarly journals Integrated World Modeling Theory (IWMT) Implemented: Towards Reverse Engineering Consciousness with the Free Energy Principle and Active Inference

2020 ◽  
Author(s):  
Adam Safron
Keyword(s):  
Free Energy ◽  
Reference Frames ◽  
Phenomenal Consciousness ◽  
Predictive Processing ◽  
Active Inference ◽  
Perceptual Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
World Modeling ◽  
Modeling Theory

Integrated World Modeling Theory (IWMT) is a synthetic model that attempts to unify theories of consciousness within the Free Energy Principle and Active Inference framework, with particular emphasis on Integrated Information Theory (IIT) and Global Neuronal Workspace Theory (GNWT). IWMT further suggests predictive processing in sensory hierarchies may be well-modeled as (folded, sparse, partially disentangled) variational autoencoders, with beliefs discretely-updated via the formation of synchronous complexes—as self-organizing harmonic modes (SOHMs)—potentially entailing maximal a posteriori (MAP) estimation via turbo coding. In this account, alpha-synchronized SOHMs across posterior cortices may constitute the kinds of maximal complexes described by IIT, as well as samples (or MAP estimates) from multimodal shared latent space, organized according to egocentric reference frames, entailing phenomenal consciousness as mid-level perceptual inference. When these posterior SOHMs couple with frontal complexes, this may enable various forms of conscious access as a kind of mental act(ive inference), affording higher order cognition/control, including the kinds of attentional/intentional processing and reportability described by GNWT. Across this autoencoding heterarchy, intermediate-level beliefs may be organized into spatiotemporal trajectories by the entorhinal/hippocampal system, so affording episodic memory, counterfactual imaginings, and planning.

Social Active Inference

2021 ◽  
pp. 58-72
Author(s):  
El Hassan Bezzazi
Keyword(s):  
Free Energy ◽  
Real Life ◽  
Dynamic Logic ◽  
Negotiation Process ◽  
The Other ◽  
Optimal Decision ◽  
Embodied Perception ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle

The free energy principle and its corollary, active inference, were introduced by Karl Friston as an explanation embodied perception and action in neuroscience, and since, it has been used to address many other issues in different fields mainly related to cognitive science like learning, optimal decision, or interpersonal inference. Negotiation is a process where each negotiator has conflicting motivation is aiming to maximize his utility and where agreement is reached when the opposing interests are balanced. The purpose of this chapter is to illustrate how the free energy principle might be used through active inference in modeling a negotiation process based on an example of real life. The work is an attempt to bring together a dynamic logic framework with appropriate operators to consider motivation among agents on one hand and the active inference framework on the other hand.

Predictive Processing

2018 ◽  
Author(s):  
Wanja Wiese
Keyword(s):  
Free Energy ◽  
Bayesian Inference ◽  
General Framework ◽  
External World ◽  
Predictive Processing ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Action And Perception ◽  
Conceptual Distinction ◽  
The Mind

This chapter provides an introduction to predictive processing (PP), with a focus on its relation to Bayesian inference and the more general framework provided by Karl Friston’s free-energy principle (FEP). Philosophical implications of PP and FEP are discussed. In particular, it is argued that PP posits genuine representations, and that FEP questions whether the conceptual distinction between action and perception is useful when it comes to understanding their neuro-computational underpinnings. Finally, it is argued that PP supports the view that the mind is to some extent secluded from the external world and that perception is indirect because it is based on genuinely inferential processes.

scholarly journals The predictive brain in action: Involuntary actions reduce body prediction errors

2020 ◽  
Author(s):  
Pablo Lanillos ◽  
Sae Franklin ◽  
David W. Franklin
Keyword(s):  
Prediction Error ◽  
Sensory Information ◽  
The Body ◽  
Predictive Processing ◽  
Body Ownership ◽  
Prediction Errors ◽  
Uncertain Information ◽  
Energy Principle ◽  
Virtual Hand ◽  
The Brain

AbstractThe perception of our body in space is flexible and manipulable. The predictive brain hypothesis explains this malleability as a consequence of the interplay between incoming sensory information and our body expectations. However, given the interaction between perception and action, we might also expect that actions would arise due to prediction errors, especially in conflicting situations. Here we describe a computational model, based on the free-energy principle, that forecasts involuntary movements in sensorimotor conflicts. We experimentally confirm those predictions in humans by means of a virtual reality rubber-hand illusion. Participants generated movements (forces) towards the virtual hand, regardless of its location with respect to the real arm, with little to no forces produced when the virtual hand overlaid their physical hand. The congruency of our model predictions and human observations shows that the brain-body is generating actions to reduce the prediction error between the expected arm location and the new visual arm. This observed unconscious mechanism is an empirical validation of the perception-action duality in body adaptation to uncertain situations and evidence of the active component of predictive processing.Author SummaryHumans’ capacity to perceive and control their body in space is central in awareness, adaptation and safe interaction. From low-level body perception to body-ownership, discovering how the brain represents the body and generates actions is of major importance for cognitive science and also for robotics and artificial intelligence. The present study shows that humans move their body to match the expected location according to other (visual) sensory input, which corresponds to reducing the prediction error. This means that the brain adapts to conflicting or uncertain information from the senses by unconsciously acting in the world.

scholarly journals Affect-Logic, Embodiment, Synergetics, and the Free Energy Principle: New Approaches to the Understanding and Treatment of Schizophrenia

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1619
Author(s):  
Luc Ciompi ◽  
Wolfgang Tschacher
Keyword(s):  
Free Energy ◽  
Open Systems ◽  
The Body ◽  
Psychotic Symptoms ◽  
Energy Principle ◽  
Free Energy Principle ◽  
Emotional Tension ◽  
Sustained Reduction ◽  
Logic Approach ◽  
Body Self

This theoretical paper explores the affect-logic approach to schizophrenia in light of the general complexity theories of cognition: embodied cognition, Haken’s synergetics, and Friston’s free energy principle. According to affect-logic, the mental apparatus is an embodied system open to its environment, driven by bioenergetic inputs of emotions. Emotions are rooted in goal-directed embodied states selected by evolutionary pressure for coping with specific situations such as fight, flight, attachment, and others. According to synergetics, nonlinear bifurcations and the emergence of new global patterns occur in open systems when control parameters reach a critical level. Applied to the emergence of psychotic states, synergetics and the proposed energetic understanding of emotions lead to the hypothesis that critical levels of emotional tension may be responsible for the transition from normal to psychotic modes of functioning in vulnerable individuals. In addition, the free energy principle through learning suggests that psychotic symptoms correspond to alternative modes of minimizing free energy, which then entails distorted perceptions of the body, self, and reality. This synthetic formulation has implications for novel therapeutic and preventive strategies in the treatment of psychoses, among these are milieu-therapeutic approaches of the Soteria type that focus on a sustained reduction of emotional tension and phenomenologically oriented methods for improving the perception of body, self, and reality.

scholarly journals Bayesian theories of consciousness: a review in search for a minimal unifying model

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Wiktor Rorot
Keyword(s):  
Free Energy ◽  
Conscious Experience ◽  
Generative Model ◽  
Predictive Processing ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle

Abstract The goal of the paper is to review existing work on consciousness within the frameworks of Predictive Processing, Active Inference, and Free Energy Principle. The emphasis is put on the role played by the precision and complexity of the internal generative model. In the light of those proposals, these two properties appear to be the minimal necessary components for the emergence of conscious experience—a Minimal Unifying Model of consciousness.

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