scholarly journals Symptom Perception From a Predictive Processing Perspective

2019 ◽  
Vol 1 (4) ◽  
Author(s):  
Giovanni Pezzulo ◽  
Domenico Maisto ◽  
Laura Barca ◽  
Omer Van den Bergh
Keyword(s):  
Predictive Coding ◽  
Disease Model ◽  
Action Selection ◽  
Predictive Processing ◽  
Central Feature ◽  
Symptom Perception ◽  
Asthma Symptoms ◽  
Physical Diseases ◽  
Specific Disorders ◽  
The Brain

Bodily symptoms are highly prevalent in psychopathology, and in some specific disorders, such as somatic symptom disorder, they are a central feature. In general, the mechanisms underlying these symptoms are poorly understood. However, also in well-known physical diseases there seems to be a variable relationship between physiological dysfunction and self-reported symptoms challenging traditional assumptions of a biomedical disease model. Recently, a new, predictive processing conceptualization of how the brain works has been used to understand this variable relationship. According to this predictive processing view, the experience of a symptom results from an integration of both interoceptive sensations as well as from predictions about these sensations from the brain. In the present paper, we introduce the predictive processing perspective on perception (predictive coding) and action (active inference), and apply it to asthma in order to understand when and why asthma symptoms are sometimes strongly, moderately or weakly related to physiological disease parameters. Our predictive processing view of symptom perception contributes to understanding under which conditions misperceptions and maladaptive action selection may arise. There is a variable relationship between physiological dysfunction and self-reported symptoms. We conceptualize symptom perception (and misperception) within a predictive processing perspective. In this view, symptom perception integrates sensations and predictions about these sensations. Failures of such integration can produce misperceptions and maladaptive action selection. We use the perception (and misperception) of asthma symptoms as an example. There is a variable relationship between physiological dysfunction and self-reported symptoms. We conceptualize symptom perception (and misperception) within a predictive processing perspective. In this view, symptom perception integrates sensations and predictions about these sensations. Failures of such integration can produce misperceptions and maladaptive action selection. We use the perception (and misperception) of asthma symptoms as an example.

Epidemiology of schizophrenia. The disease model of schizophrenia in the light of current epidemiological knowledge

1995 ◽  
Vol 10 (5) ◽  
pp. 217-227 ◽  
Author(s):  
H Häfner
Keyword(s):  
Age Of Onset ◽  
Disease Model ◽  
Sound Studies ◽  
Prodromal Phase ◽  
Early Course ◽  
Brain Anomalies ◽  
Specific Disorders ◽  
Core Symptoms ◽  
The Brain ◽  
Control Study

SummaryAttempting an update of the epidemiology of schizophrenia, it is pointed out that schizophrenia seems to occur with the same core symptoms and almost at the same frequency in all countries and cultures studied. Methodologically sound studies have failed to produce evidence for a secular trend of the morbid risk. The genotype of schizophrenia is expressed as psychosis, personality disorders and non-specific disorders or it goes without manifest psychopathology. Minor brain anomalies are present in most cases. The British Child Development Study showed that behavioural, cognitive, emotional and neuromotor antecedents occur in 50% of cases, thus pointing to disordered brain development, very likely not specific to schizophrenia, since found in many other mental disorders as well. A look into the hidden early course of schizophrenia revealed a significant sex difference in age of onset and a prodromal phase of some 3 to 4 years throughout the cases. A case-control study showed that it is mainly during this early course before first admission that social disadvantage in schizophrenia arises. In the prephase a disease-related lack of social ascent plays a greater role than steps of social decline. The early social course differs between the sexes mainly due to an earlier onset of the disorder in males. The actual disease variables, that is, core symptoms and type of course, do not show any essential differences between males and females. These results indicate that schizophrenia is one of the rare uniform patterns of response of the brain, capable of being triggered by a large number of causes or favoured by non-specific risk factors. In this context the protective effect of estrogens will be discussed.

scholarly journals A tale of two densities: active inference is enactive inference

2019 ◽  
Vol 28 (4) ◽  
pp. 225-239 ◽  
Author(s):  
Maxwell JD Ramstead ◽  
Michael D Kirchhoff ◽  
Karl J Friston
Keyword(s):  
Predictive Coding ◽  
Generative Models ◽  
Predictive Processing ◽  
Active Inference ◽  
Energy Principle ◽  
Free Energy Principle ◽  
The One ◽  
And Control ◽  
The Brain ◽  
Selection Of

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 inference – what 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.

scholarly journals Disentangling predictive processing in the brain: a meta-analytic study in favour of a predictive network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Linda Ficco ◽  
Lorenzo Mancuso ◽  
Jordi Manuello ◽  
Alessia Teneggi ◽  
Donato Liloia ◽  
...  
Keyword(s):  
Large Scale ◽  
Inferior Frontal Gyrus ◽  
Predictive Coding ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Predictive Processing ◽  
Spatial Convergence ◽  
Large Scale Networks ◽  
The Brain

AbstractAccording to the predictive coding (PC) theory, the brain is constantly engaged in predicting its upcoming states and refining these predictions through error signals. Despite extensive research investigating the neural bases of this theory, to date no previous study has systematically attempted to define the neural mechanisms of predictive coding across studies and sensory channels, focussing on functional connectivity. In this study, we employ a coordinate-based meta-analytical approach to address this issue. We first use the Activation Likelihood Estimation (ALE) algorithm to detect spatial convergence across studies, related to prediction error and encoding. Overall, our ALE results suggest the ultimate role of the left inferior frontal gyrus and left insula in both processes. Moreover, we employ a meta-analytic connectivity method (Seed-Voxel Correlations Consensus). This technique reveals a large, bilateral predictive network, which resembles large-scale networks involved in task-driven attention and execution. In sum, we find that: (i) predictive processing seems to occur more in certain brain regions than others, when considering different sensory modalities at a time; (ii) there is no evidence, at the network level, for a distinction between error and prediction processing.

scholarly journals Multistability in auditory stream segregation: a predictive coding view

2012 ◽  
Vol 367 (1591) ◽  
pp. 1001-1012 ◽  
Author(s):  
István Winkler ◽  
Susan Denham ◽  
Robert Mill ◽  
Tamás M. Bőhm ◽  
Alexandra Bendixen
Keyword(s):  
Predictive Coding ◽  
Stream Segregation ◽  
Predictive Processing ◽  
Conscious Perception ◽  
Auditory Streaming ◽  
Sound Sources ◽  
Auditory Stream ◽  
Auditory Stream Segregation ◽  
Perceptual Stability ◽  
The Brain

Auditory stream segregation involves linking temporally separate acoustic events into one or more coherent sequences. For any non-trivial sequence of sounds, many alternative descriptions can be formed, only one or very few of which emerge in awareness at any time. Evidence from studies showing bi-/multistability in auditory streaming suggest that some, perhaps many of the alternative descriptions are represented in the brain in parallel and that they continuously vie for conscious perception. Here, based on a predictive coding view, we consider the nature of these sound representations and how they compete with each other. Predictive processing helps to maintain perceptual stability by signalling the continuation of previously established patterns as well as the emergence of new sound sources. It also provides a measure of how well each of the competing representations describes the current acoustic scene. This account of auditory stream segregation has been tested on perceptual data obtained in the auditory streaming paradigm.

scholarly journals Disentangling Predictive Processing in the Brain: A Meta-analytic Study in Favour of a Predictive Network

2021 ◽  
Author(s):  
Linda Ficco ◽  
Lorenzo Mancuso ◽  
Jordi Manuello ◽  
Alessia Teneggi ◽  
Donato Liloia ◽  
...  
Keyword(s):  
Large Scale ◽  
Inferior Frontal Gyrus ◽  
Predictive Coding ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Predictive Processing ◽  
Spatial Convergence ◽  
Large Scale Networks ◽  
The Brain

Abstract According to the predictive coding (PC) theory, the brain is constantly engaged in predicting its upcoming states and refining these predictions through error signal. Despite extensive research has investigated the neural bases of this theory, to date no previous study has systematically attempted to define the neural mechanisms of predictive coding across studies and sensory channels, focussing on functional connectivity. In this study, we employ a coordinate-based meta-analytical approach to address this issue. We first use the Activation Likelihood Estimation (ALE) algorithm to detect spatial convergence across studies, related to prediction error and encoding. Overall, our ALE results suggest the ultimate role of the left inferior frontal gyrus and left insula in both processes. Moreover, we employ a task-based meta-analytic connectivity method (Seed-Voxel Correlations Consensus). This technique reveals a large, bilateral predictive network, which resembles large-scale networks involved in task-driven attention and execution. In sum, we find that: i) predictive processing seems to occur more in certain brain regions than others, when considering different sensory modalities at a time; ii) there is no evidence, at the network level, for a distinction between error and prediction processing.

scholarly journals Cerebral hierarchies: predictive processing, precision and the pulvinar

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140169 ◽  
Author(s):  
Ryota Kanai ◽  
Yutaka Komura ◽  
Stewart Shipp ◽  
Karl Friston
Keyword(s):  
Prediction Error ◽  
Message Passing ◽  
Predictive Coding ◽  
Gain Control ◽  
Predictive Processing ◽  
Special Focus ◽  
First Order ◽  
Neuronal Populations ◽  
Neurobiological Substrates ◽  
The Brain

This paper considers neuronal architectures from a computational perspective and asks what aspects of neuroanatomy and neurophysiology can be disclosed by the nature of neuronal computations? In particular, we extend current formulations of the brain as an organ of inference—based upon hierarchical predictive coding—and consider how these inferences are orchestrated. In other words, what would the brain require to dynamically coordinate and contextualize its message passing to optimize its computational goals? The answer that emerges rests on the delicate (modulatory) gain control of neuronal populations that select and coordinate (prediction error) signals that ascend cortical hierarchies. This is important because it speaks to a hierarchical anatomy of extrinsic (between region) connections that form two distinct classes, namely a class of driving (first-order) connections that are concerned with encoding the content of neuronal representations and a class of modulatory (second-order) connections that establish context—in the form of the salience or precision ascribed to content. We explore the implications of this distinction from a formal perspective (using simulations of feature–ground segregation) and consider the neurobiological substrates of the ensuing precision-engineered dynamics, with a special focus on the pulvinar and attention.

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.

From many to one: Meditation and the plasticity of the predictive mind

2020 ◽  
Author(s):  
Ruben Laukkonen ◽  
Heleen A Slagter
Keyword(s):  
Cognitive Enhancement ◽  
The Self ◽  
Predictive Processing ◽  
Focused Attention ◽  
Conceptual Processing ◽  
Current State ◽  
Contemplative Science ◽  
Open Monitoring ◽  
Living Organisms ◽  
The Brain

How profoundly can humans change their own minds? In this paper we offer a unifying account of meditation under the predictive processing view of living organisms. We start from relatively simple axioms. First, the brain is an organ that serves to predict based on past experience, both phylogenetic and ontogenetic. Second, meditation serves to bring one closer to the here and now by disengaging from anticipatory processes. We propose that practicing meditation therefore gradually reduces predictive processing, in particular counterfactual cognition—the tendency to construct abstract and temporally deep representations—until all conceptual processing falls away. Our Many- to-One account also places three main styles of meditation (focused attention, open monitoring, and non-dual meditation) on a single continuum, where each technique progressively relinquishes increasingly engrained habits of prediction, including the self. This deconstruction can also make the above processes available to introspection, permitting certain insights into one’s mind. Our review suggests that our framework is consistent with the current state of empirical and (neuro)phenomenological evidence in contemplative science, and is ultimately illuminating about the plasticity of the predictive mind. It also serves to highlight that contemplative science can fruitfully go beyond cognitive enhancement, attention, and emotion regulation, to its more traditional goal of removing past conditioning and creating conditions for potentially profound insights. Experimental rigor, neurophenomenology, and no-report paradigms combined with neuroimaging are needed to further our understanding of how different styles of meditation affect predictive processing and the self, and the plasticity of the predictive mind more generally.

Interoception, categorization, and symptom perception

2018 ◽  
Author(s):  
Omer Van den Bergh ◽  
Nadia Zacharioudakis ◽  
Sibylle Petersen
Keyword(s):  
Decision Making ◽  
Medical Practice ◽  
Disease Model ◽  
Clinical Implications ◽  
Symptom Perception ◽  
Symptom Reports ◽  
The Relationship ◽  
Accurate Reflection

Medical practice and the disease model importantly rely on the accuracy assumption of symptom perception: patients’ symptom reports are a direct and accurate reflection of physiological dysfunction. This implies that symptoms can be used as a read-out of dysfunction and that remedying the dysfunction removes the symptoms. While this assumption is viable in many instances of disease, the relationship between symptoms and physiological dysfunction is highly variable and, in a substantial number of cases, completely absent. This chapter considers symptom perception as a form of unconscious inferential somatic decision-making that compellingly produces consciously experienced symptoms. At a mechanistic level, this perspective removes the categorical distinction between symptoms that are closely associated with physiological dysfunction and those that are not. In addition, it brings symptom perception in accordance with general theories of perception. Some clinical implications to understand and treat symptoms poorly related to physiological dysfunction are discussed.

scholarly journals Extending the extended consciousness debate: perception, imagination, and the common kind assumption

2021 ◽  
Author(s):  
James Deery
Keyword(s):  
Perceptual Experience ◽  
Phenomenal Consciousness ◽  
Psychological Theory ◽  
Predictive Processing ◽  
Mental Event ◽  
The World ◽  
Predictive Approach ◽  
The Common ◽  
The Relationship ◽  
The Brain

AbstractFor some, the states and processes involved in the realisation of phenomenal consciousness are not confined to within the organismic boundaries of the experiencing subject. Instead, the sub-personal basis of perceptual experience can, and does, extend beyond the brain and body to implicate environmental elements through one’s interaction with the world. These claims are met by proponents of predictive processing, who propose that perception and imagination should be understood as a product of the same internal mechanisms. On this view, as visually imagining is not considered to be world-involving, it is assumed that world-involvement must not be essential for perception, and thus internalism about the sub-personal basis is true. However, the argument for internalism from the unity of perception and imagination relies for its strength on a questionable conception of the relationship between the two experiential states. I argue that proponents of the predictive approach are guilty of harbouring an implicit commitment to the common kind assumption which does not follow trivially from their framework. That is, the assumption that perception and imagination are of the same fundamental kind of mental event. I will argue that there are plausible alternative ways of conceiving of this relationship without drawing internalist metaphysical conclusions from their psychological theory. Thus, the internalist owes the debate clarification of this relationship and further argumentation to secure their position.

Sign in / Sign up

Export Citation Format

Share Document