Extending predictive processing to the body: Emotion as interoceptive inference

2013 ◽  
Vol 36 (3) ◽  
pp. 227-228 ◽  
Author(s):  
Anil K. Seth ◽  
Hugo D. Critchley
Keyword(s):  
Psychiatric Disorders ◽  
Physiological Condition ◽  
Predictive Coding ◽  
The Body ◽  
Predictive Processing ◽  
Bayesian Brain ◽  
New View

AbstractThe Bayesian brain hypothesis provides an attractive unifying framework for perception, cognition, and action. We argue that the framework can also usefully integrate interoception, the sense of the internal physiological condition of the body. Our model of “interoceptive predictive coding” entails a new view of emotion as interoceptive inference and may account for a range of psychiatric disorders of selfhood.

scholarly journals The epistemic and pragmatic value of non-action: a predictive coding perspective on meditation

2019 ◽  
Author(s):  
Antoine Lutz ◽  
Jérémie Mattout ◽  
Giuseppe Pagnoni
Keyword(s):  
Mindfulness Meditation ◽  
Explanatory Power ◽  
Predictive Coding ◽  
The Body ◽  
Predictive Processing ◽  
Voluntary Attention ◽  
Mind And Body ◽  
Psychological Models ◽  
Spontaneous Thought ◽  
The Mind

The surge of interest about mindfulness meditation is associated with a growing empirical evidence about its impact on the mind and body. Yet, despite promising phenomenological or psychological models of mindfulness, a general mechanistic understanding of meditation steeped in neuroscience is still lacking. In parallel, predictive processing approaches to the mind are rapidly developing in the cognitivesciences with an impressive explanatory power: processes apparently as diverse as perception, action, attention and learning, can be seen as unfolding and being coherently orchestrated according to the single general mandate of free-energy minimization. Here we briefly explore the possibility to supplement previous phenomenological models of focused attention meditation by formulating them in terms of active inference. We first argue that this perspective can account for how paying voluntary attention to the body in meditation helps settling the mind by downweighting habitual and automatic trajectories of (pre)motor and autonomic reactions, as well as the pull of distracting spontaneous thought at the same time. Secondly, we discuss a possible relationship between phenomenological notions such as opacity and de-reification, and the deployment of precision-weighting via the voluntary allocation of attention. We propose the adoption of this theoretical framework as a promising strategy for contemplative research. Explicit computational simulations and comparisons with experimental and phenomenological data will be critical to fully develop this approach.

scholarly journals A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective

2019 ◽  
Author(s):  
Zina-Mary Manjaly ◽  
Sandra Iglesias
Keyword(s):  
Cognitive Therapy ◽  
Theoretical Perspective ◽  
Predictive Coding ◽  
Computational Modelling ◽  
Behavioural Therapy ◽  
The Body ◽  
Prediction Errors ◽  
Recurrent Depression ◽  
Bayesian Brain ◽  
Core Concepts

Mindfulness Based Cognitive Therapy (MBCT) was developed to combine methods from cognitive behavioural therapy and meditative techniques, with the specific goal of preventing relapse in recurrent depression. While supported by empirical evidence from multiple clinical trials, the cognitive mechanisms behind the effectiveness of MBCT are not well understood in computational (information processing) or biological terms.This article introduces a testable theory about the computational mechanisms behind MBCT that is grounded in “Bayesian brain” concepts of perception from cognitive neuroscience, such as predictive coding. These concepts regard the brain as embodying a model of its environment (including the external world and the body) which predicts future sensory inputs and is updated by prediction errors, depending on how precise these error signals are.This article offers a concrete proposal how core concepts of MBCT – the being mode, decentring, and reactivity – could be understood in terms of perceptual and metacognitive processes that draw on specific computational mechanisms of the “Bayesian brain”. Importantly, the proposed theory can be tested experimentally, using a combination of behavioural paradigms, computational modelling, and neuroimaging. The novel theoretical perspective on MBCT described in this paper may offer opportunities for finessing the conceptual and practical aspects of MBCT.

A challenge for predictive coding: Representational or experiential diversity?

2020 ◽  
Vol 43 ◽  
Author(s):  
Martina G. Vilas ◽  
Lucia Melloni
Keyword(s):  
Brain Function ◽  
Predictive Coding ◽  
Predictive Processing ◽  
Process Theory

Abstract To become a unifying theory of brain function, predictive processing (PP) must accommodate its rich representational diversity. Gilead et al. claim such diversity requires a multi-process theory, and thus is out of reach for PP, which postulates a universal canonical computation. We contend this argument and instead propose that PP fails to account for the experiential level of representations.

How to grow a self: development of the self in a Bayesian brain

2019 ◽  
Author(s):  
Mateusz Wozniak
Keyword(s):  
Conceptual Development ◽  
Human Life ◽  
Predictive Coding ◽  
Body Representation ◽  
Developmental Trajectory ◽  
The Self ◽  
Learning Mechanisms ◽  
Bayesian Brain ◽  
Third Person ◽  
Complex Forms

The last two decades have brought several attempts to explain the self as a part of the Bayesian brain, typically within the framework of predictive coding. However, none of these attempts have looked comprehensively at the developmental aspect of self-representation. The goal of this paper is to argue that looking at the developmental trajectory is crucial for understanding the structure of an adult self-representation. The paper argues that the emergence of the self should be understood as an instance of conceptual development, which in the context of a Bayesian brain can be understood as a process of acquisition of new internal models of hidden causes of sensory input. The paper proposes how such models might emerge and develop over the course of human life by looking at different stages of development of bodily and extra-bodily self-representations. It argues that the self arises gradually in a series of discrete steps: from first-person multisensory representations of one’s body to third-person multisensory body representation, and from basic forms of the extended and social selves to progressively more complex forms of abstract self-representation. It discusses how each of them might emerge based on domain-general learning mechanisms, while also taking into account the potential role of innate representations. Finally it suggests how the conceptual structure of self-representation might inform the debate about the structure of self-consciousness.

scholarly journals Toward the unity of pathological and exertional fatigue: A predictive processing model

2021 ◽  
Author(s):  
A. Greenhouse-Tucknott ◽  
J. B. Butterworth ◽  
J. G. Wrightson ◽  
N. J. Smeeton ◽  
H. D. Critchley ◽  
...  
Keyword(s):  
Prediction Error ◽  
Conscious Experience ◽  
Physical Exertion ◽  
Generative Models ◽  
The Body ◽  
Predictive Processing ◽  
Research Fields ◽  
Common Foundation ◽  
Health And Disease ◽  
Sensory Evidence

AbstractFatigue is a common experience in both health and disease. Yet, pathological (i.e., prolonged or chronic) and transient (i.e., exertional) fatigue symptoms are traditionally considered distinct, compounding a separation between interested research fields within the study of fatigue. Within the clinical neurosciences, nascent frameworks position pathological fatigue as a product of inference derived through hierarchical predictive processing. The metacognitive theory of dyshomeostasis (Stephan et al., 2016) states that pathological fatigue emerges from the metacognitive mechanism in which the detection of persistent mismatches between prior interoceptive predictions and ascending sensory evidence (i.e., prediction error) signals low evidence for internal generative models, which undermine an agent’s feeling of mastery over the body and is thus experienced phenomenologically as fatigue. Although acute, transient subjective symptoms of exertional fatigue have also been associated with increasing interoceptive prediction error, the dynamic computations that underlie its development have not been clearly defined. Here, drawing on the metacognitive theory of dyshomeostasis, we extend this account to offer an explicit description of the development of fatigue during extended periods of (physical) exertion. Accordingly, it is proposed that a loss of certainty or confidence in control predictions in response to persistent detection of prediction error features as a common foundation for the conscious experience of both pathological and nonpathological fatigue.

scholarly journals Neuropsychological assessment and virtual reality training of social prediction in patients with cerebellar malformation

2021 ◽  
Author(s):  
Cosimo Urgesi ◽  
Niccolò Butti ◽  
Alessandra Finisguerra ◽  
Emilia Biffi ◽  
Enza Maria Valente ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Social Cognition ◽  
Contextual Information ◽  
Predictive Coding ◽  
Predictive Processing ◽  
Cerebellar Malformation ◽  
Use Context ◽  
Predictive Role ◽  
Social Prediction

AbstractIt has been proposed that impairments of the predictive function exerted by the cerebellum may account for social cognition deficits. Here, we integrated cerebellar functions in a predictive coding framework to elucidate how cerebellar alterations could affect the predictive processing of others’ behavior. Experiment 1 demonstrated that cerebellar patients were impaired in relying on contextual information during action prediction, and this impairment was significantly associated with social cognition abilities. Experiment 2 indicated that patients with cerebellar malformation showed a domain-general deficit in using contextual information to predict both social and physical events. Experiment 3 provided first evidence that a social-prediction training in virtual reality could boost the ability to use context-based predictions to understand others’ intentions. These findings shed new light on the predictive role of the cerebellum and its contribution to social cognition, paving the way for new approaches to the rehabilitation of the Cerebellar Cognitive Affective Syndrome.

scholarly journals Implementing Predictive Processing and Active Inference: Preliminary Steps and Results

2019 ◽  
Author(s):  
Beren Millidge
Keyword(s):  
Predictive Coding ◽  
Predictive Processing ◽  
Active Inference ◽  
Inference Models ◽  
Perceptual Model ◽  
Challenging Tasks ◽  
Generalised Coordinates

Initial and preliminary implementations of predictive processing and active inference models are presented. These include the baseline hierarchical predictive coding models of (Friston 2003, 2005), and dynamical predictive coding models using generalised coordinates (Friston 2008, 2010, Buckley 2017). Additionally, we re-implement and experiment with the active inference thermostat presented in (Buckley 2017) and also implement an active inference agent with a hierarchical predictive coding perceptual model on the more challenging cart-pole task from OpanAI gym. We discuss the initial performance, capabilities, and limitations of these models in their preliminary stages and consider how they might be further scaled up to tackle more challenging tasks.

scholarly journals Sensory Attenuation in the Auditory Modality as a Window Into Predictive Processing

2021 ◽  
Vol 15 ◽  
Author(s):  
Fabian Kiepe ◽  
Nils Kraus ◽  
Guido Hesselmann
Keyword(s):  
Predictive Coding ◽  
Research Area ◽  
Predictive Processing ◽  
Auditory Modality ◽  
Auditory Input ◽  
Current State ◽  
Recent Developments ◽  
Sensory Attenuation ◽  
The Impact ◽  
Predictive Mechanisms

Self-generated auditory input is perceived less loudly than the same sounds generated externally. The existence of this phenomenon, called Sensory Attenuation (SA), has been studied for decades and is often explained by motor-based forward models. Recent developments in the research of SA, however, challenge these models. We review the current state of knowledge regarding theoretical implications about the significance of Sensory Attenuation and its role in human behavior and functioning. Focusing on behavioral and electrophysiological results in the auditory domain, we provide an overview of the characteristics and limitations of existing SA paradigms and highlight the problem of isolating SA from other predictive mechanisms. Finally, we explore different hypotheses attempting to explain heterogeneous empirical findings, and the impact of the Predictive Coding Framework in this research area.

EXPRESS: “Run to the hills”: Specific contributions of anticipated energy expenditure during active spatial learning

2022 ◽  
pp. 174702182210765
Author(s):  
Simon Lhuillier ◽  
Pascale Piolino ◽  
Serge Nicolas ◽  
Valérie Gyselinck
Keyword(s):  
Energy Expenditure ◽  
Spatial Learning ◽  
Walking Speed ◽  
Predictive Coding ◽  
Space Perception ◽  
The Body ◽  
Spatial Representations ◽  
Immersive Virtual Reality ◽  
Locomotion Cost ◽  
Constructivist Approaches

Grounded views of cognition consider that space perception is shaped by the body and its potential for action. These views are substantiated by observations such as the distance-on-hill effect, described as the overestimation of visually perceived uphill distances. An interpretation of this phenomenon is that slanted distances are overestimated because of the integration of energy expenditure cues. The visual perceptual processes involved are however usually tackled through explicit estimation tasks in passive situations. The goal of this study was to consider instead more ecological active spatial processing. Using immersive virtual reality and an omnidirectional treadmill, we investigated the effect of anticipated implicit physical locomotion cost by comparing spatial learning for uphill and downhill routes, while maintaining actual physical cost and walking speed constant. In the first experiment, participants learnt city layouts by exploring uphill or downhill routes. They were then tested using a landmark positioning task on a map. In the second experiment, the same protocol was used with participants who wore loaded ankle weights. Results from the first experiment showed that walking uphill routes led to a global underestimation of distances compared to downhill routes. This inverted distance-of-hill effect was not observed in the second experiment, where an additional effort was applied. These results suggest that the underestimation of distances observed in experiment one emerged from recalibration processes whose function was to solve the transgression of proprioceptive predictions linked with uphill energy expenditure. Results are discussed in relation to constructivist approaches on spatial representations and predictive coding theories.

Placebos in chronic pain: evidence, theory, ethics, and use in clinical practice

BMJ ◽  
2020 ◽  
pp. m1668 ◽  
Author(s):  
Ted J Kaptchuk ◽  
Christopher C Hemond ◽  
Franklin G Miller
Keyword(s):  
Chronic Pain ◽  
Clinical Practice ◽  
Predictive Coding ◽  
Evidence Theory ◽  
Placebo Treatment ◽  
Placebo Effects ◽  
Unified Framework ◽  
Open Label ◽  
Double Blind ◽  
Bayesian Brain

ABSTRACTDespite their ubiquitous presence, placebos and placebo effects retain an ambiguous and unsettling presence in biomedicine. Specifically focused on chronic pain, this review examines the effect of placebo treatment under three distinct frameworks: double blind, deception, and open label honestly prescribed. These specific conditions do not necessarily differentially modify placebo outcomes. Psychological, clinical, and neurological theories of placebo effects are scrutinized. In chronic pain, conscious expectation does not reliably predict placebo effects. A supportive patient-physician relationship may enhance placebo effects. This review highlights “predictive coding” and “bayesian brain” as emerging models derived from computational neurobiology that offer a unified framework to explain the heterogeneous evidence on placebos. These models invert the dogma of the brain as a stimulus driven organ to one in which perception relies heavily on learnt, top down, cortical predictions to infer the source of incoming sensory data. In predictive coding/bayesian brain, both chronic pain (significantly modulated by central sensitization) and its alleviation with placebo treatment are explicated as centrally encoded, mostly non-conscious, bayesian biases. The review then evaluates seven ways in which placebos are used in clinical practice and research and their bioethical implications. In this way, it shows that placebo effects are evidence based, clinically relevant, and potentially ethical tools for relieving chronic pain.

Sign in / Sign up

Export Citation Format

Share Document