Predictive Processing

While the notion of the brain as a prediction machine has been extremely influential and productive in cognitive science, there are competing accounts of how best to model and understand the predictive capabilities of brains. One prominent framework is of a "Bayesian brain" that explicitly generates predictions and uses resultant errors to guide adaptation. We suggest that the prediction-generation component of this framework may involve little more than a pattern completion process. We first describe pattern completion in the domain of visual perception, highlighting its temporal extension, and show how this can entail a form of prediction in time. Next, we describe the forward momentum of entrained dynamical systems as a model for the emergence of predictive processing in non-predictive systems. Then, we apply this reasoning to the domain of language, where explicitly predictive models are perhaps most popular. Here, we demonstrate how a connectionist model, TRACE, exhibits hallmarks of predictive processing without any representations of predictions or errors. Finally, we present a novel neural network model, inspired by reservoir computing models, that is entirely unsupervised and memoryless, but nonetheless exhibits prediction-like behavior in its pursuit of homeostasis. These explorations demonstrate that brain-like systems can get prediction "for free," without the need to posit formal logical representations with Bayesian probabilities or an inference machine that holds them in working memory.

Abstract

Die in kommunikationstechnologischen Medien vermittelten Immersionswelten durchdringen und überwölben zunehmend die Lebenswelt. Apparative Immersionen bestehen in erster Linie aus dem Erlebnis hergestellter Atmosphären, die Befindlichkeiten auslösen, durch welche die abstrakt-symbolischen Interaktionsräume überhaupt erst leibliche Relevanz erhalten. Eine Klärung des Verhältnisses von Immersion und Atmosphäre steht bislang noch aus. Hierzu wird ein Atmosphärenbegriff entwickelt, der an die Phänomene des Immersiven anschließbar ist. Das Erleben von Atmosphären hat einige besondere Merkmale, die von den vorliegenden Atmosphärenkonzepten nicht berücksichtigt werden. Besonders der Aspekt der Zeitlichkeit, der sich als zentral für die Entstehung von Atmosphären erweist, wird nicht hinreichend in die Entwürfe einbezogen. Darauf reagiert eine Atmosphärenkonzeption, die auf drei an den Paradigmen des Em-bodiment und Enaktivismus orientierten Theoriemodulen aufbaut. Diese erlauben die Affizierung der leiblichen Befindlichkeit durch Umweltwahrnehmungen zu konzeptualisieren, wie sie für Atmosphären typisch ist. Atmosphären können hernach als ein Gemütszustand neben Emotionen und Stimmungen verortet werden. Es zeigt sich, dass Atmosphären als eine eigene Kognitionsform für imaginär vollendete Zukünfte organischer Zustände auffassbar sind, die dem Subjekt im Latenten verborgene Handlungen und imaginäre Körper-Umwelt-Relationen vermitteln. Immersionswelten können nunmehr aus der Leiblichkeit des Menschen verstanden werden, womit auch die Medientheorie und Soziologie eine neue Untersuchungsperspektive gewinnt. Im Zeitalter der Immersion tritt eine neue Art von Vergesellschaftung auf, die atmosphärisch vermittelte Intensitäten zum Gegenstand hat.

Abstract (English)

Immersive worlds provided by technological media are more and more protruding and overarching the lifeworld. Technologically enabled immersions essentially consist of the experience of atmospheres which trigger states of mind and thereby establish a connection between abstractsymbolic realms and bodily relevancies. A profound analysis of the relation between immersion and atmospheres is still outstanding. In this paper a concept of atmospheres is presented that relates this type of experience to the phenomena of immersivity. The perception of atmospheres is characterized by some specific cognitive attributes that are not taken into account by the current concepts of atmospheres. In particular, temporality, which proves to be central to the constitution of atmospheric experience, is not sufficiently credited. In order to address this conceptual challenge, the concept of atmospheres developed in this work is based on three theoretical modules that are derived from the paradigms of embodiment and enactivism. The synthesis of the modules allows for a conceptualization of the affection of bodily and mental states by the perception of environmental objects and situations, as is typical for atmospheres. In this way, atmospheres can be considered certain states of mind, alongside moods and emotions. It is shown that the atmospherical colouring of perception can be understood as the type of cognition for the arousal of implicit readiness to act and for potential future operations or body-environment relations. By showing that immersive realms are based on atmospheric cognition, media theory and sociology also gain new perspectives. With the upcoming age of immersion a new type of socialisation emerges that is based on atmospherically mediated intensities.

In this paper we present an approach to detect whether an MRI scan of a brain contains a tumor or not using machine learning. Once detected, it will then classify the type of tumor as either benign or malignant. In any medical field, the most important resource used by doctors is Medical Images which is a tool with high accuracy. In this work, the system correctly classifies MRI images into images with tumor and images without tumor. This has to be done with no human intervention. In order to apply several types of classifiers, there is a need to pre-process several aspects of the images such as the color, area of interest, image file extension, and contrast level.

The question of noise may not seem immediately relevant to recent upheavals in the political economy of music. But since I was asked to speak about streaming at the 'Ebbing Sounds' conference that zweikommasieben co-hosted last May in San Francisco and since my research is focused on the concept of noise, I put together some thoughts on that basis. Noise has a specific sharply defined computational meaning in several different theoretical frameworks in science, most centrally information theory, where it is defined in terms of uncertainty and interference. It also has a variety of social and cultural understandings that are more open to interpretation, related to perceptual and affective states and to general notions like randomness, unpredictability, disorder, resistance, and excess. Many of these concepts – information, randomness, noise – which have very specific scientific and mathematical meanings, are routinely employed to describe phenomena at the cultural level. There, they are at best problematically overextended, and more often serve as tools in ideologically motivated justifications for the continuing march of neoliberalism's creative destruction. The central claim of my work on noise is pretty straightforward: noise is relative to theoretical framework, level of description, and scale of analysis. Its well known that first the printing press, then early sound recording and transmission technologies – phonograph and radio – induced a scale transformation in the political economy of music, and that digital sound, file sharing, and now streaming have given rise to similarly radical transitions. Each of these technical developments profoundly altered the sonic domain, changing not only the distribution of music but also its composition and production, the ecology of listening, and the understanding of noise. This is also the case in the recent consolidation of the streaming economy, which needs to be thought of in terms of platform capitalism and the transition from ICT to AI. This is a shift from centralized broadcast media to interactive media, user generated content, and targeted advertising. But it is also a concurrent shift in the management of noise, as relatively fixed exclusionary frameworks based on robustness to noise give way to data-driven fluid modulation of relevance and resilience to noise. Lossy compression formats like the mp3, which made file-sharing and now streaming possible, are based on perceptual coding – which uses a model of the auditory system to compress a signal by exploiting redundancies in the way that auditory information is processed. Like noise, compression is relative to 1 theoretical framework: that is, the adequacy of a compressed representation to its object, or its utility for a subject, is dependent on the goal that it serves and the context in which it arises. In general it is computational resource allocation problems that dictate the pertinent level of compression in a given economy, whether cognitive-perceptual, or digital-financial. It is common knowledge that the huge impact of the mp3 format was due to achieving a reduction in the computational cost of storing and transmitting auditory data. But we can also talk of evolutionary biology as a process of generating compact representations, or of perception as a form of lossy source compression. This generalized notion of 2 compression is precisely the model of thought underlying recent theoretical developments in AI and cognitive science, a model that is undoubtedly now driving decisions in boardroom meetings at tech startups. Understanding political economy in general and platform capitalism in particular requires engagement with the problem of naturalization (explanation according to natural laws). Mainstream, or orthodox, economic theory is a naturalization of economic activity according to principles taken from physics. This is a brutal abstraction relying on a number of simplifying assumptions, so it treats various details as noise (most notably mainstream economics forgets asymmetries, historicity, and communication). More recent heterodox theories move to a biological or ecological paradigm, which accounts for some non-equilibrium 1 Sterne, J. (2012) MP3 – The Meaning of a Format. Duke University Press.

Anil Seth’s target paper connects the framework of PP (predictive processing) and the FEP (free-energy principle) to cybernetic principles. Exploiting an analogy to theory of science, Seth draws a distinction between three types of active inference. The first type involves confirmatory hypothesis-testing. The other types involve seeking disconfirming and disambiguating evidence, respectively. Furthermore, Seth applies PP to various fascinating phenomena, including perceptual presence. In this commentary, I explore how far we can take the analogy between explanation in perception and explanation in science.
In the first part, I draw a slightly broader analogy between PP and concepts in theory of science, by asking whether the Bayesian brain is Kuhnian or Popperian. While many aspects of PP are in line with Karl Popper’s falsificationism, other aspects of PP conform to how Thomas Kuhn described scientific revolutions. Thus, there is both a sense in which the Bayesian brain is Kuhnian, and a sense in which it is Popperian. The upshot of these considerations is that falsification in PP can take many different forms. In particular, active inference can be used to falsify a model in more ways than identified by Seth.
In the second part of this commentary, I focus on Seth’s PPSMCT (predictive processing account of sensorimotor contingency theory) and its application to perceptual presence, which assigns a crucial role to counterfactual richness. In my discussion, I question the significance of counterfactual richness for perceptual presence. First, I highlight an ambiguity inherent in Seth’s descriptions of the target phenomenon (perceptual presence vs. objecthood). Then I suggest that counterfactual richness may not be the crucial underlying feature (of either perceptual presence of objecthood). Giving a series of examples, I argue that the degree of represented causal integration is an equally good candidate for accounting for perceptual presence (or objecthood), although more work needs to be done.

As recent developments in autism research offer alternative explanations to the mainstream options, it can now be argued that the so-called cognitive deficits in the social domain associated with autism have been mischaracte-rized or, at least, oversimplified. We will use predictive models within a 4E (i.e., embodied, embedded, enactive and extended) conception of cognition to address the question of cognitive impairment in psychiatrics and autism. Such models force us to reassess what "cognitive deficit" means by integrating the environment not only in its usual sense (evo-developmental), but by understanding all cognitive performances as embedded in environments (or fields of affordances) that shape and sustain them. By adopting a predictive 4E perspective, we aim to show that the "cognitive deficits" associated with autism are in fact mismatches between environmental resources and the particular form of neurological functioning of autistic people (neurodiversity), brought about by the fact that the cultural niches that set up the relevant fields of affordances are structured by and for neurotypicals. This mismatch leads to epistemic injustices, both testimonial and hermeneutic, that feed back into research on autism and clinical approaches, thereby making the "defi-cits" appear based on individual shortcomings. In this context, autism interventions should partly focus on the development of social policies aimed at modifying those aspects of cultural niches that make environments unsuitable for the full development of all individuals.

The dominant mode of societal operation in today’s world, in its pursuit of the good life through economic growth and consumption, is destroying the planet’s ecosystems and accelerating towards an inhospitable climate regime, with mixed results for even short-term human well-being. This pathological mode of societal operation is based in discredited worldviews. However, important aspects of a coherent, updated worldview have not been articulated and thus have not been integrated into the efforts of scholarship to steer society away from collapse and toward sustainable, desirable futures. In particular, there is a need for an explanatory framework that makes sense of seemingly incompatible perspectives on the human being (e.g., between the natural and social sciences) and on human well-being (WB; e.g., between hedonic and other perspectives)—and that situates human WB in the context of planetary WB. This thesis lays the foundation of such a framework. Previous researchers taking a complex-systems approach have argued convincingly that self-regulatory capacity is the underlying basis of WB, providing a key premise for this thesis. I synthesize evolutionary, neurobiological, psychological, and social lines of investigation into a coherent, broadly consistent understanding of the development and dynamics of self-regulatory capacity, focusing on various interdependent levels of regulation (e.g., physiological, psychological, and social) and showing many of their impacts on WB. With the help of predictive processing models of perception, this thesis explores how self-regulatory dynamics are affected by the qualities of three key relationships fundamental to the human situation: relationship with one’s body (embodiment), relationship with other humans (sociality), and relationship with the more-than-human world (terrestriality).

This work suggests a number of conclusions. First, all three of these relational contexts (embodiment, sociality, terrestriality) are fundamental to both our existence and our well-being. It follows that any coherent worldview must account for these dynamic interrelations. Second, human well-being may be proximally defined by the capacity for integrated, non-defensive functioning, which is a developmental achievement dependent on supportive conditions. Third, beyond material sufficiency, the most important factors for WB seem to be attentional, collective, and mutualistic, rather than consumptive, individual, and rival.

This thesis, by synthesizing a variety of scientific disciplines into a coherent framework for an embedded, complex-systems understanding of whole-person health and well-being, is the first part of a research agenda toward understanding—and achieving—whole-systems well-being, from person to planet.

Recent work has sought to explain how meditation functions by accounting for the practice within the predictive processing framework. However, current accounts are somewhat limited either in the breadth of processes covered and their relationship to each other, or in the mechanistic depth with which they are described. Here, I attempt to address such limitations. I provide a predictive processing account of how meditation can change one's capacity to learn. I do so by constructing an argument which draws upon research on neuroplasticity, meditation, perception and from the literature on predictive processing. In the paper I review the research on neuroplasticity and learning. Then I discuss the research on meditation and neuroplasticity. After doing so, I present predictive processing as a framework for understanding the brain and mind. I review the literature on accounts of meditation within the framework, and proceed to synthesize and extend their core elements in order to provide an account with increased mechanistic breadth and depth. This synthesis is then used as a lens through which I argue that the altered perception found in studies on long-term meditators can be accounted for. Such meditators benefit from increased attentional availability closer to the sensory processing stream. I further argue that this has consequences for neuroplasticity, and therefore learning, as it allows higher-level priors in the hierarchical generative model to update more easily due to increased new evidence accumulation made possible at the lower levels of the hierarchy. This essentially allows the mind to maintain a tighter fit with its environment as it is kept more up-to-date through an increased capacity to update resistant-to-change priors.

We distinguish between three philosophical views on the neuroscience of predictive models: predictive coding (associated with internal Bayesian models and prediction error minimization), predictive processing (associated with radical con-nectionism and 'simple' embodiment) and predictive engagement (associated with enactivist approaches to cognition). We examine the concept of active inference under each model and then ask how this concept informs discussions of social cognition. In this context we consider Frith and Friston's proposal for a neural hermeneutics, and we explore the alternative model of enactivist hermeneutics.

More than 40 years ago, pioneering social psychologist Robert Zajonc (1980) published his seminal work titled "Preferences need no inferences" in which he argued for the primacy of affect over cognition. Affective evaluation (the preference) comes first, he claimed, and only then do cognitive processes (the inferences) kick in. The view is, of course, untenable in light of recent predictive processing accounts which hold that all mental functioning is built from (approximate) Bayesian inference. Predictive processing casts perception, action, and learning as inference, but, perhaps counterintuitively, valuation too. I will discuss specifically how valuation-understood as the process of how we come to value, prefer, or like things-emerges as a function of inference, and how this conception may help us resolve traditional conundrums in the science of aesthetic experience, such as the nature of the beholder's share, the link between curiosity and appreciation, and the tension between the mere exposure principle and the goldilocks principle.

Many philosophers hold that phenomenally conscious experiences involve a sense of mineness, since experiences like pain or hunger are immediately presented as mine. What can be said about this mineness, and does acceptance of this feature commit us to the existence of a subject or self? If yes, how should we characterize this subject? This paper considers the possibility that, (1) to the extent that we accept this feature, it provides us with a minimal notion of a subject of experience, and that (2) the phenomenological subject of experience, as it is represented in conscious experience, is the organism. While many philosophers agree that the metaphysical subject of experience is the animal, this claim is much less widespread, maybe even counterintuitive. The argument for this claim alludes to the structure of phenomenal consciousness and to recent work in cognitive science concerning the embodied character of consciousness and cognition. To illustrate the problems of current controversies, not only several recent rejections of a subject of experience are critically discussed, but also Hume's famous rejection of a subject is criticized making use of epistemological aspects from Kant's Philosophy of Mind. The final section situates the present discussion in the context of recently popular predictive coding accounts of perception and perceptual experience. Phenomenal consciousness is typically characterized in terms of 'what it is like' to be in a given mental state (Nagel 1974). For example, there is something that it is like for me to see something red, and this differs from the way it feels like for me to have a toothache. Phenomenally conscious experiences differ with respect to their quality. 1 Philosophers from different camps have attempted to explain conscious experiences solely by explaining this feature. For example, representationalists like Tye (1995) provide an explanation for the quality of seeing red in terms of surface features of the object perceived, and an explanation for the quality of feeling a toothache in terms of features of the tooth. He alludes to the alleged transparency of experience to support the notion that his explanation is exhaustive and that there is no remaining explanatory gap. Similarly, proponents of sensorimotor theories of consciousness like Noë (2004) and O'Regan and Noë (2001) provide an explanation for the quality of seeing red in terms of laws governing the contingencies between the sensorimotor capacities of the experiencing agent and the environment; such laws could be different with respect to the different 1 Some philosophers prefer to use the notion of " qualia " in this context, but since this term is more problematic than useful it will be ignored in this paper. See Dennett 1991 for a criticism of the coherence of this notion in contrast to the acceptance of the subjective impression that it feels like something to experience a sound or taste or smell. While there may be widespread disagreement about how to explain this subjective feeling, most philosophers of mind at least accept that there is something to be explained with respect to phenomenal consciousness. This minimal agreement of the majority is the starting point of this paper.

Despite the seemingly neutral vantage of using nature for widely-distributed computational purposes, neither post-biological nor post-humanist teleology simply concludes with the real "end of nature" as entailed in the loss of the specific ontological status embedded in the identifier "natural." As evinced by the ecological crises of the Anthropocene—of which the 2019 Brazil Amazon rainforest fires are only the most recent—our epoch has transfixed the “natural order" and imposed entropic artificial integration, producing living species that become “anoetic,” made to serve as automated exosomatic residues, or digital flecks. I further develop Gilles Deleuze’s description of control societies to upturn Foucauldian biopower, replacing its spacio-temporal bounds with the exographic excesses in psycho-power; culling and further detailing Bernard Stiegler’s framework of transindividuation and hyper-control, I examine how becoming-subject is predictively facilitated within cognitive capitalism and what Alexander Galloway terms “deep digitality.” Despite the loss of material vestiges qua virtualization—which I seek to trace in an historical review of industrialization to postindustrialization—the drive-based and reticulated "internet of things" facilitates a closed loop from within the brain to the outside environment, such that the aperture of thought is mediated and compressed. The human brain, understood through its material constitution, is susceptible to total datafication’s laminated process of “becoming-mnemotechnical,” and, as neuroplasticity is now a valid description for deep-learning and neural nets, we are privy to the rebirth of the once-discounted metaphor of the “cybernetic brain.” Probing algorithmic governmentality while posing noetic dreaming as both technical and pharmacological, I seek to analyze how spirit is blithely confounded with machine-thinking’s gelatinous cognition, as prosthetic organ-adaptation becomes probabilistically molded, networked, and agentially inflected (rather than simply externalized).

In "Psychopower and Ordinary Madness" my ambition, as it relates to Bernard Stiegler's recent literature, was twofold: 1) critiquing Stiegler's work on exosomatization and artefactual posthumanism-or, more specifically, nonhumanism-to problematize approaches to media archaeology that rely upon technical exteriorization; 2) challenging how Stiegler engages with Giuseppe Longo and Francis Bailly's conception of negative entropy. These efforts were directed by a prevalent techno-cultural qualifier: the rise of Synthetic Intelligence (including neural nets, deep learning, predictive processing and Bayesian models of cognition). This paper continues this project but first directs a critical analytic lens at the Derridean practice of the ontologization of grammatization from which Stiegler emerges while also distinguishing how metalanguages operate in relation to object-oriented environmental interaction by way of inferentialism. Stalking continental (Kapp, Simondon, Leroi-Gourhan, etc.) and analytic traditions (e.g., Carnap, Chalmers, Clark, Sutton, Novaes, etc.), we move from artefacts to AI and Predictive Processing so as to link theories related to technicity with philosophy of mind. Simultaneously drawing forth Robert Brandom's conceptualization of the roles that commitments play in retrospectively reconstructing the social experiences that lead to our endorsement(s) of norms, we compliment this account with Reza Negarestani's deprivatized account of intelligence while analyzing the equipollent role between language and media (both digital and analog).

Predictive processing and its apparent commitment to explaining cognition in terms of Bayesian inference over hierarchical generative models seems to flatly contradict the pragmatist conception of mind and experience. Against this, I argue that this appearance results from philosophical overlays at odd with the science itself, and that the two frameworks are in fact well-poised for mutually beneficial theoretical exchange. Specifically, I argue: first, that predictive processing illuminates pragmatism's commitment to both the primacy of pragmatic coping in accounts of the mind and the profound organism-relativity of experience; second, that this pragmatic, narcissistic character of prediction error minimization undermines its ability to explain the distinctive normativity of intentionality; and third, that predictive processing therefore mandates an extra-neural account of intentional content of exactly the sort that pragmatism's communitarian vision of human thought can provide.

Friston, K., Fortier, M. & Friedman, D. A. (2018). Of woodlice and men: A Bayesian account of cognition, life and consciousness. An interview with Kark Friston. ALIUS Bulletin, 2,
17-43.

The entire issue of the ALIUS Bulletin can be downloaded for free here: https://www.aliusresearch.org/bulletin.html

We argue that one important aspect of the "cognitive neuroscience revolution" identified by Boone and Piccinini (2015) is a dramatic shift away from thinking of cognitive representations as arbitrary symbols towards thinking of them as icons that replicate structural characteristics of their targets. We argue that this shift has been driven both "from below" and "from above" — that is, from a greater appreciation of what mechanistic explanation of information-processing systems involves ("from below"), and from a greater appreciation of the problems solved by bio-cognitive systems, chiefly regulation and prediction ("from above"). We illustrate these arguments by reference to examples from cognitive neuroscience, principally representational similarity analysis and the emergence of (predictive) dynamical models as a central postulate in neurocognitive research.

Clark has recently suggested that predictive processing advances a theory of neural function with the resources to put an ecumenical end to the ''representation wars'' of recent cognitive science. In this paper I defend and develop this suggestion. First, I broaden the representation wars to include three foundational challenges to representational cognitive science. Second, I articulate three features of predictive processing's account of internal representation that distinguish it from more orthodox representationalist frameworks. Specifically, I argue that it posits a resemblance-based representational architecture with organism-relative contents that functions in the service of pragmatic success, not veridical representation. Finally , I argue that internal representation so understood is either impervious to the three anti-representationalist challenges I outline or can actively embrace them.

As a philosophical paradigm, differential heterogenesis offers us a novel descriptive vantage with which to inscribe Deleuze's virtuality within the terrain of "differential becoming," conjugating "pure saliences" so as to parse economies, microhistories, insurgencies, and epistemological evolutionary processes that can be conceived of independently from their representational form. Unlike Gestalt theory's oppositional constructions, the advantage of this aperture is that it posits a dynamic context to both media and its analysis, rendering them functionally tractable and set in relation to other objects , rather than as sedentary identities. Surveying the genealogy of differential heterogenesis with particular interest in the legacy of Lautman's dialectic, I make the case for a reading of the Deleuzean virtual that departs from an event-oriented approach, galvanizing Sarti and Citti's dynamic a priori vis-à-vis Deleuze's philosophy of difference. Specifically, I posit differential heterogenesis as frame with which to examine our contemporaneous epistemic shift as it relates to multi-scalar computational modeling while paying particular attention to neuro-inferential modes of inductive learning and homologous cognitive architecture. Carving a bricolage between Mark Wilson's work on the "greediness of scales" and Deleuze's "scales of reality", this project threads between static ecologies and active externalism vis-à-vis endocentric frames of reference and syntactical scaffolding.

ABSTRACT: The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception , learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment , life, and mind, its epistemic status is unclear. Also unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences.

Predictive processing (PP) is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of authors have remarked that aspects of PP seem reminiscent of the work of 18th century philosopher Immanuel Kant. To date there have not been any substantive discussions of how exactly PP links back to Kant. In this article, I argue that several core aspects of PP were anticipated by Kant (1996/1787) in his works on perception and cognition. Themes from Kant active in PP include: (1) the emphasis on " top-down " generation of percepts; (2) the role of " hyperpriors " ; (3) the general function of " generative models " ; (4) the process of " analysis-by-synthesis " and (5) the crucial role of imagination in perception. In addition to these, I also point out that PP echoes Kant's general project in that it aims to explain how minds track causal structure in the world using only sensory data, and that it uses a reverse-engineer or " top-down " method of analysis. I then locate a possible source of Kant's influence on PP by tracing the paradigm back to Hermann von Helmholtz, who saw himself as providing a scientific implementation of Kant's conclusions. I conclude by arguing that PP should not be regarded as a new paradigm, but is more appropriately understood as the latest incarnation of an approach to perception and cognition initiated by Kant and refined by Helmholtz.

In general, I defend the view that the predictions are normative due to their constitutive role in guiding actions. In this sense, I claim normativity is such a real property that can be assigned to a given mechanism or object due to the function it performs in a given organism, cognitive system or decision-making process, and which cannot be reduced to some evaluation practice. In other words, the condition for assigning normativity is that the mechanism or object in question is normative per se. (There you will find an English version of Summary and Table of contents).

Pre-proof version of a response to Stark et al. focusing on avoiding that PP accounts of autistic difference become yet another theory of autistic deficit under the label 'intolerance of uncertainty'.

Final version:
https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(21)00223-0?rss=yes

We offer an account of mental health and well-being using the predictive processing framework (PPF). According to this framework, the difference between mental health and psychopathology can be located in the goodness of the predictive model as a regulator of action. What is crucial for avoiding the rigid patterns of thinking, feeling and acting associated with psychopathology is the regulation of action based on the valence of affective states. In PPF, valence is modelled as error dynamics-the change in prediction errors over time. Our aim in this paper is to show how error dynamics can account for both momentary happiness and longer term wellbeing. What will emerge is a new neurocomputational framework for making sense of human flourishing.

READ FOR FREE PUBLISHED VERSION HERE https://rdcu.be/cRSqM
I discuss Clark’s predictive processing/extended mind hybrid, diagnosing a problem: Clark’s hybrid suggests that, when we use them, we pay attention to mind-extending external resources. This clashes with a commonly accepted necessary condition of cognitive extension; namely, that mind-extending resources must be phenomenally transparent when used. I then propose a solution to this problem claiming that the phenomenal transparency condition should be rejected. To do so, I put forth a parity argument to the effect that phenomenal transparency cannot be a necessary condition on cognitive extension: roughly, since internal cognitive resources can fail to be transparent when used, by parity, external resources can fail to be phenomenally transparent too. Further, I argue that phenomenal transparency is not even a reliable indicator of cognitive extension; hence its absence should not be considered a problem for Clark's extended mind-predictive processing hybrid. Lastly, I consider and allay a number of worries my proposal might raise, and conclude the paper.
Keywords: Extended Mind, Predictive processing, Phenomenal transparency, Attention, Active inference, Recruitment puzzle.

Predictive processing has recently been advanced as a global cognitive architecture for the brain. I argue that its commitments concerning the nature and format of cognitive representation are unable to account for two basic characteristics of conceptual thought: first, its generality--the fact that we can think and flexibly reason about phenomena at any level of spatiotemporal scale and abstraction; second, its rich compositionality--the specific way in which concepts productively combine to yield our thoughts. I consider two strategies for avoiding these objections and I argue that both confront formidable challenges.

I identify three lessons from Kenneth Craik's landmark book "The Nature of Explanation" for contemporary debates surrounding the existence, importance, and nature of mental representation: first, an account of mental representations as neural structures that function analogously to public models; second, an appreciation of prediction as the central component of intelligence in demand of such models; and third, a metaphor for understanding the brain as an engineer, not a scientist. I then relate these insights to discussions surrounding the representational status of predictive processing—which, I argue, provides a contemporary vindication of Craik's extremely prescient "hypothesis on the nature of thought."

In this article, we investigate the foundations for a Gibsonian neurosci-
ence. There is an increasingly influential current in neuroscience based
on pragmatic and selectionist principles, which we think can contrib-
ute to ecological psychology. Starting from ecological psychology, we
identify three basic constraints any Gibsonian neuroscience needs to
adhere to: nonreconstructive perception, vicarious functioning, and
selectionist self-organization. We discuss two previous attempts to
integrate affordances with neuroscience: Reed’s ecological rendering of Edelman’s selectionism as well as Dreyfus’ phenomenological inter- pretation of Freeman’s neurodynamics. Reed and Dreyfus face the problem of how to account for “value.”
We then show how the free-energy principle, an increasingly dominant framework in theoretical neuroscience, is rooted  in both Freeman’s  neurodynamics and Edelman’s selectionism. The free-energy principle accounts for value in terms of selective anticipation. The selection pressures at work on the agent shape its selective sensitivity to the relevant affordances in the environment. By being responsive to the relevant affordances in the environment, an agent comes to have grip on its interactions
with the environment and can thrive in its ecological niche.

This chapter explores to what extent some core ideas of predictive processing can be applied to the phenomenology of time consciousness. The focus is on the experienced continuity of consciously perceived, temporally extended phenomena (such as enduring processes and successions of events). The main claim is that the hierarchy of representations posited by hierarchical predictive processing models can contribute to a deepened understanding of the continuity of consciousness. Computationally, such models show that sequences of events can be represented as states of a hierarchy of dynamical systems. Phenomenologically, they suggest a more fine-grained analysis of the perceptual contents of the specious present, in terms of a hierarchy of temporal wholes. Visual perception of static scenes not only contains perceived objects and regions but also spatial gist; similarly, auditory perception of temporal sequences, such as melodies, involves not only perceiving individual notes but also slightly more abstract features (temporal gist), which have longer temporal durations (e.g., emotional character or rhythm). Further investigations into these elusive contents of conscious perception may be facilitated by findings regarding its neural underpinnings. Predictive processing models suggest that sensorimotor areas may influence these contents.

The aim of the present article is (1) to analyse the normative character of anticipations described by phenomenology; (2) to demonstrate, within the framework of the predictive processing approach, that predictions fulfill a specific normative function in the perceptual process; and (3) to justify the thesis according to which the analyses of normative mechanisms performed by investigators of predictive processing are more effective and give better explanations of normativity than those offered by phenomenology. I would like to justify the thesis that explanations in the predictive processing approach are normative in nature. They are like that because prediction mechanisms themselves are normative.

Researchers in the field of computational psychiatry have recently sought to model the formation and retention of
delusions in terms of dysfunctions in a process of hierarchical Bayesian inference. I present a systematic review of
such models and raise two challenges that have not received sufficient attention in the literature. First, the
characteristic that is supposed to most sharply distinguish hierarchical Bayesian models from their competitors is their
abandonment of the distinction between perception and cognition in favour of a unified inferential hierarchy. Standard
ways of characterising this hierarchy, however, are inconsistent with the range of phenomena that delusions can
represent. Second, there is little evidence that belief fixation in the healthy population is Bayesian, and an abundance of evidence that it is not. Given this, attempts to model delusions in terms of dysfunctions in a process of
Bayesian inference are of dubious theoretical value.

A cognitivist account of decision-making views choice behaviour as a serial process of deliberation and commitment, which is separate from perception and action. By contrast, recent work in embodied decision-making has argued that this account is incompatible with emerging neurophysiological data. We argue that this account has significant overlap with an embodied account of predictive processing, and that both can offer mutual development for the other. However, more importantly, by demonstrating this close connection we uncover an alternative perspective on the nature of decision-making, and the mechanisms that underlie our choice behaviour. This alternative perspective allows us to respond to a challenge for predictive processing, which claims that the satisfaction of distal goal-states is underspecified. Answering this challenge requires the adoption of an embodied perspective.

There is a growing sense among scholars working in cognitive literary studies that their assumptions and methodologies increasingly align them with another paradigmatically interdisciplinary field: comparative literature. This introduction to the special issue on cognitive approaches to comparative literature explores points of alignment between the two fields, outlining possible cognitivist interventions into debates that have been animating comparative literature, such as those concerning “universals,” politics of translatability (especially in the context of world literature), and practices of thinking across the boundaries of media. It discusses both fields’ indebtedness to cultural studies, as well as cognitive literary theorists’ commitment to historicizing and their sustained focus on the embodied social mind.