Two challenges that face popular self-monitoring theories (SMTs) of auditory verbal hallucination (AVH) are that they cannot account for the auditory phenomenology of AVHs and that they cannot account for their variety. In this paper I show that both challenges can be met by adopting a predictive processing framework (PPF), and by viewing AVHs as arising from abnormalities in predictive processing. I show how, within the PPF, both the auditory phenomenology of AVHs, and three subtypes of AVH, can be accounted (...) for. (shrink)

In this Hypothesis and Theory paper, we consider the problem of learning deeply structured knowledge representations in the absence of predefined ontologies, and in the context of long-term learning. In particular, we consider this process as a sequence of re-representation steps, of various kinds. The Information Dynamics of Thinking theory (IDyOT) admits such learning, and provides a hypothetical mechanism for the human-like construction of hierarchical memory, with the provision of symbols constructed by the system that embodies the theory. The combination (...) of long-term learning and meaning construction in terms of symbols grounded in perceptual experience entails that the system, like a human, be capable of memory consolidation, to manage the complex and inconsistent structures that can result from learning of information that becomes more complete over time. Such consolidation changes memory structures, and thus changes their meaning. Therefore, memory consolidation entails re-representation, while re-representation entails changes of meaning. Ultimately, the theory proposes that the processes of learning and consolidation should be considered as repeated re-representation of what is learned. (shrink)

Paweł Gładziejewski has recently argued that the framework of predictive processing postulates genuine representations. His focus is on establishing that certain structures posited by PP actually play a representational role. The goal of this paper is to promote this discussion by exploring the contents of representations posited by PP. Gładziejewski already points out that structural theories of representational content can successfully be applied to PP. Here, I propose to make the treatment slightly more rigorous by invoking Francis Egan’s distinction between (...) mathematical and cognitive contents. Applying this distinction to representational contents in PP, I first show that cognitive contents in PP are determined by mathematical contents, at least in the sense that computational descriptions in PP put constraints on ascriptions of cognitive contents. After that, I explore to what extent these constraints are specific. I argue that the general mathematical contents posited by PP do not constrain ascriptions of cognitive content in a specific way. However, there are at least three aspects of PP that constrain ascriptions of cognitive contents in more specific ways: formal PP models posit specific mathematical contents that define more specific constraints; PP entails claims about how computational mechanisms underpin cognitive phenomena ; the processing hierarchy posited by PP goes along with more specific constraints. (shrink)

The Predictive Mind by Jakob Hohwy is the first monograph to address the philosophical significance of what Hohwy calls the prediction error minimization framework. The central claim of the book is that, on a conceptual level, perception, action, and cognition can be understood by reference to a single principle: prediction error minimization. The corresponding empirical hypothesis is that the brain implements a hierarchical generative model that generates predictions about sensory inputs and their hidden causes. When sensory signals arrive, only their (...) divergence from the predictions has to be further processed. The general strategy of using predictions derived from generative models to compress and transmit information is also known as predictive coding.Perception is thus not construed as a purely bottom–up process, but. (shrink)

According to active inference, action is enabled by a top-down modulation of sensory signals. Computational models of this mechanism complement ideomotor theories of action representation. Such theories postulate common neural representations for action and perception, without specifying how action is enabled by such representations. In active inference, motor commands are replaced by proprioceptive predictions. In order to initiate action through such predictions, sensory prediction errors have to be attenuated. This paper argues that such top-down modulation involves systematic misrepresentations. More specifically, (...) the paper first argues for the following conditional claim. If active inference provides an accurate computational description of how action is enabled in the brain, then action is enabled by systematic misrepresentations. Furthermore, it is argued that an inference to the best explanation provides reason for believing the antecedent is true: Firstly, active inference provides a crucial extension to ideomotor theories. Secondly, active inference explains otherwise puzzling phenomena related to sensory attenuation, e.g. in force-matching or self-tickling paradigms. Taken together, these reasons support the claim that action is indeed enabled by systematic misrepresentations. The claim casts doubt on the assumption that representations are systematically beneficial to the extent that they are true: if the argument in this paper is sound, systematically beneficial misrepresentations may lie at the heart of our neural architecture. (shrink)

Recent developments in contemporary natural science (including the evolutionary study of perception, cognitive science, and interpretations of quantum physics) incorporate central idealist positions relating to the nature of representation, the role our minds play in structuring our experience of the world, and the properties of the world behind our representations. This paper first describes what these positions are, and how they are introduced in the relevant theories in terms of precisely formulated scientific analogues. I subsequently consider how this way of (...) looking at philosophical idealism through selected parts of contemporary science can help us to pursue new ways of developing key idealist questions in a way that is integrated with a naturalistically supported endeavour to understand central features of reality. (shrink)

Causal theories of content, a popular family of approaches to defining the content of mental states, commonly run afoul of two related and serious problems that prevent them from providing an adequate theory of mental content—the misrepresentation problem and the disjunction problem. In this paper, I present a causal theory of content, built on information theoretic tools, that solves these problems and provides a viable model of mental content. This is the greatest surprise reduction theory of content, which identifies the (...) content of a signal as the event the surprisal of which is most reduced by that signal. Conceptually, this amounts to the claim that the content of a signal is the event the probability of which has increased by the largest proportion, or the event that the signal makes the most less surprising to us. I develop the greatest surprise reduction theory of content in four stages. First, I introduce the general project of causal theories of content, and the challenges presented to this project by the misrepresentation and disjunction problems. Next, I review two recent and prominent causal theories of content and demonstrate the serious challenges faced by these approaches, both clarifying the need for a solution to the misrepresentation and disjunction problems and providing a conceptual background for the greatest surprise reduction theory. Then, I develop the greatest surprise reduction theory of content, demonstrate its ability to resolve the misrepresentation and disjunction problems, and explore some additional applications it may have. Finally, I conclude with a discussion of a particularly difficult challenge that remains to be addressed—the partition problem—and sketch a path to a potential solution. (shrink)

Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised learning (...) methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies. (shrink)

Daniel Dennett’s Consciousness Explained is probably the most widely read book about consciousness ever written by a philosopher. Despite this, the book has had a surprisingly small influence on how most philosophers of mind view consciousness. This might be because many philosophers badly misunderstand the book. They claim it does not even attempt to explain consciousness, but instead denies its very existence. Outside of philosophy the book has had more influence, but is saddled by the same misunderstanding. Now, 30 years (...) after publication, Consciousness Explained deserves reconsideration from anyone interested in consciousness. Here I make a case for this. To start, I will clear up the central misunderstanding of the book. With that done, I will explain and update Dennett’s tantalizing approach to consciousness and the mind. The result brings us very, very close to explaining consciousness. Or so I will argue. (shrink)

Though predictive processing approaches to the mind were originally applied to exteroceptive perception, i.e., vision and action, recent work has started to explore the role of interoceptive perception, i.e., emotion and affect. This article builds on this work by extending PP beyond emotion to the construction of emotional dispositions. I employ principles from dynamical systems theory and PP to provide a model of how dispositional anger can develop in response to early experiences of psychosocial stress. The model is then deployed (...) to explain the established link between psychosocial stress in early life and the appearance of certain organic disease phenotypes in later life. This phenomenon can appear mysterious when viewed through the standard biomedical explanatory lens, which has difficulty accounting for the causal influence of subjective perceptions and evaluations of the social and material environment on the development of organic disease processes. The model provided presents such cases as instances of developmental mismatch. They occur when an organism develops an emotional disposition that leads them to make habitually-biased appraisals of what the social environment affords. The model provides a novel explanation of certain organic disease phenotypes with top-down and developmental causes, and demystifies one class of cases involving apparently spooky ‘mind-to-matter’ causation. (shrink)

The nature of consciousness is considered one of science’s most perplexing and persistent mysteries. We all know the subjective experience of consciousness, but where does it arise? What is its purpose? What are its full capacities? The assumption within today’s neuroscience is that all aspects of consciousness arise solely from interactions among neurons in the brain. However, the origin and mechanisms of qualia are not understood. David Chalmers coined the term “the hard problem” to describe the difficulties in elucidating the (...) origins of subjectivity from the point of view of reductive materialism. We propose that the hard problem arises because one or more assumptions within a materialistic worldview are either wrong or incomplete. If consciousness entails more than the activity of neurons, then we can contemplate new ways of thinking about the hard problem. This review examines phenomena that apparently contradict the notion that consciousness is exclusively dependent on brain activity, including phenomena where consciousness appears to extend beyond the physical brain and body in both space and time. The mechanisms underlying these “non-local” properties are vaguely suggestive of quantum entanglement in physics, but how such effects might manifest remains highly speculative. The existence of these non-local effects appears to support the proposal that post-materialistic models of consciousness may be required to break the conceptual impasse presented by the hard problem of consciousness. (shrink)

Cognitive ecology as a research tradition in cognitive science: The article presents cognitive ecology as a research tradition in cognitive science, under which studies on embodied cognition and various forms of situated cognition are conducted. At the same time, the basic heuristic of cognitive ecology and its relationship to methodological individualism are identified. The paper includes the history of the concept of “cognitive ecology”, historical approaches preceding this research tradition, as well as an outline of contemporary research related to it. (...) At the end of the article, the role of the ecological heuristic is summarized. (shrink)

It has been pointed out that Sensorimotor Enactivism, a theory that claims that perception is enacted and brought about by movement, says very little about the neural mechanisms that enable perception. For the proponents of the predictive approach to Sensorimotor Enactivism, this is a challenge that can be met by introducing predictive processing into the picture. However, the compatibility between these theories is not straightforward. Firstly, because they seem to differ in their stand towards representations: while Sensorimotor Enactivism is said (...) to belong to the non-representational wing of cognitive science, predictive processing has a representational profile. And secondly, because they exhibit different explanatory strategies: while Sensorimotor Enactivism prioritizes the interactions of the embodied agent, predictive processing has internalist commitments. The aim of this paper is to address these concerns and show that a predictive approach to Sensorimotor Enactivism is viable. More specifically, I focus on the Free-Energy approach, a theory that falls within the ballpark of predictive processing. In this paper I argue for the following claims. I argue that both Sensorimotor Enactivism and the Free-Energy approach may be understood for some systems in representational terms. The non-representational reading of Sensorimotor Enactivism is not mandatory and neither is the representational reading of the Free-Energy approach. Sensorimotor Enactivism is, in this respect, compatible with both representational and non-representational interpretations of the FEA. So, the position towards representations of these frameworks should not stand in the way of a predictive approach to Sensorimotor Enactivism. I also show that the Free-Energy approach allows for an account that prioritizes the interaction of the embodied agent with the environment. This is the explanatory strategy followed by Sensorimotor Enactivism. To justify this strategy and following other proponents of Sensorimotor Enactivism, I argue that by referring to the interactions of the embodied agent a better account of the phenomena in question is provided. On this basis, I claim that Sensorimotor Enactivism and the Free-Energy approach are compatible in what concerns their explanatory strategy as well. Thus, making the case for the viability of the predictive approach to Sensorimotor Enactivism. (shrink)

According to Gilead and colleagues, to be efficient abstraction requires a hierarchical organization of information into long-term memory. But, how and when are abstract representations consolidated into long-term memory and how are they integrated with pre-existing abstracta are questions not discussed by Gilead and colleagues. Here, we propose that these processes occur preferentially during offline periods such as sleep.

Skepticism toward the existence of neonatal differential imitation is fostered by views that assign it an excessive significance, making it foundational for social cognition. Moreover, a misleading theoretical framework may generate unwarranted expectations about the kinds of findings experimentalists are supposed to look for. Hence we propose a theoretical analysis that may help experimentalists address the empirical question of whether early differential imitation really exists. We distinguish three models of early imitation. The first posits automatic visuo-motor links evolved for sociocognitive (...) functions and we call it Genetically Programmed Direct Matching. The second is Meltzoff and Moore’s Active Intermodal Matching, which postulates a comparison between the acts of self and other. The third is the alternative we propose and we call it “Association by Similarity Theory”, as it relies on the tacit functioning of this domain-general process. AST describes early imitation merely as the differential induction or elicitation of behaviors that already tend to occur spontaneously. We focus on the contrast between AIM and AST, and argue that AST is preferable to AIM for two reasons. First, AST is more parsimonious and more plausible, especially because it does not require infants to be able to recognize self-other similarities. Second, whereas the extant findings tend to disqualify AIM, AST can account for them adequately. Furthermore, we suggest that AST has the potential to give new impulse to empirical research because it discriminates promising lines of inquiry from unproductive ones. (shrink)

Psychedelics are experiencing a renaissance in mental healthcare. In recent years, more and more early phase trials on psychedelic-assisted therapy have been conducted, with promising results overall. However, ethical analyses of this rediscovered form of treatment remain rare. The present paper contributes to the ethical inquiry of psychedelic-assisted therapy by analysing the ethical implications of its therapeutic mechanisms proposed by the relaxed beliefs under psychedelics (REBUS) hypothesis. In short, the REBUS hypothesis states that psychedelics make rigid beliefs revisable by increasing (...) the influence of bottom-up input. Put differently, patients become highly suggestible and sensitive to context during a psychedelic session, amplifying therapeutic influence and effects. Due to that, patients are more vulnerable in psychedelic-assisted therapy than in other therapeutic interventions; they lose control during a psychedelic session and become dependent on the therapeutic setting (including the therapist). This enhanced vulnerability is ethically relevant and has been exploited by some therapists in the past. Therefore, patients in current research settings and starting mainstream medical settings need to be well informed about psychedelics’ mechanisms and their implications to give valid informed consent to treatment. Furthermore, other security measures are warranted to protect patients from the vulnerability coming with psychedelic-assisted therapy. (shrink)

According to L. A. Paul, the subjective value of an outcome is normally assessed by running a cognitive model of what it would be like if that outcome were to occur. However, cognitive models, along with the expectations in which they result, are unreliable for application to transformative experiences because we cannot know what it would be like for an outcome to occur if we have never experienced it before. This paper argues that despite their unreliability, expectations are still important (...) in the case of chosen and unchosen transformative experiences because expectations about an outcome can systematically influence the very experience of that outcome. More precisely, empirical research shows that affective experiences tend to assimilate to affective expectations. In turn, more positive affective experiences lead, ceteris paribus, to higher subjective value. Therefore, rational agents confronting transformative outcomes should form or cultivate positive/optimistic affective expectations since, all else being equal, that maximizes subjective value. (shrink)

Stereotypes are often described as being generally inaccurate and irrational. However, for years, a minority of social psychologists has been proclaiming that stereotype accuracy is among the most robust findings in the field. This same minority also opposes the majority by questioning the power of self-fulfilling prophecies and thereby the construction of social reality. The present paper examines this long-standing debate from the perspective of predictive processing, an increasingly influential cognitive science theory. In this theory, stereotype accuracy and self-fulfilling prophecies (...) are two sides of the same coin, namely prediction error minimisation, pointing to a new middle course between the two existing views. On the one hand, predictive processing indicates that depicting stereotypes as generally inaccurate runs counter to their actual purpose of making the social world predictable, which supports the minority view. On the other hand, predictive processing supposes that expectations, including stereotypes, permanently affect perception and behaviour and thereby co-construct social reality, which supports the majority view. Therefore, from a predictive processing perspective, stereotypes are largely rational and not per se inaccurate, and self-fulfilling prophecies are omnipresent and greatly affect social reality. This new middle course appears to fit the empirical data better than the two existing views. (shrink)

Cognitive modules are internal mental structures. Some theorists and empirical researchers hypothesise that the human mind is either partially or massively comprised of structures that are modular in nature. Is the massive modularity of mind hypothesis a cogent view about the ontological nature of human mind or is it, rather, an effective/ineffective adaptationist discovery heuristic for generating predictively successful hypotheses about both heretofore unknown psychological traits and unknown properties of already identified psychological traits? Considering the inadequacies of the case in (...) favour of massive modularity as an ontological hypothesis, I suggest approaching and valuing massive modularity as an adaptationist discovery heuristic. (shrink)

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 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 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. (shrink)

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

There has been much criticism of the idea that Friston's free-energy principle can unite the life and mind sciences. Here, we argue that perhaps the greatest problem for the totalizing ambitions of its proponents is a failure to recognize the importance of evolutionary dynamics and to provide a convincing adaptive story relating free-energy minimization to organismal fitness.

In this paper I investigate the epistemic implications of a recent theory of religious cognition that draws on predictive coding. The theory argues that certain experiences are heavily shaped by a subject’s prior (religious) beliefs and thereby makes religious believers prone to detect invisible agents. The theory is an update of older theories of religious cognition but departs from them in crucial ways. I will assess the epistemic implications by reformulating existing arguments based on other (older) theories of religious cognition.

Many compelling examples have recently been provided in which people can achieve impressive epistemic success, e.g. draw highly accurate inferences, by using simple heuristics and very little information. This is possible by taking advantage of the features of the environment. The examples suggest an easy and appealing naturalization of rationality: on the one hand, people clearly can apply simple heuristics, and on the other hand, they intuitively ought do so when this brings them high accuracy at little cost.. The ‘ought-can’ (...) principle is satisfied, and rationality is meaningfully normative. We show, however, that this naturalization program is endangered by a computational wrinkle in the adaptation process taken to be responsible for this heuristics-based (‘ecological’) rationality: for the adaptation process to guarantee even minimal rationality, it requires astronomical computational resources, making the problem intractable. We consider various plausible auxiliary assumptions in attempt to remove this obstacle, and show that they do not succeed; intractability is a robust property of adaptation. We discuss the implications of our findings for the project of naturalizing rationality. (shrink)

Predictive processing is an increasingly popular approach to cognition, perception and action. It says that the brain is essentially a hierarchical prediction machine. It is typically construed in a representationalist and inferentialist fashion so that the brain makes contentful inferences on the basis of representational models. In this paper, I argue that the predictive processing framework is inconsistent with this epistemic position. In particular, I argue that the combination of hierarchical modeling, contentful inferentialism and representationalism entail an internal inconsistency. Specifically, (...) for a particular set of states, there will be both a representation requirement and not. Yet a system cannot both be required to represent a certain set of states and not be required to represent those states. Due to this contradiction, I propose to reject the standard view. I suggest that predictive processing is best interpreted in terms of reliable covariation instead, entailing an instrumentalist approach to the statistical machinery. (shrink)

The free energy principle (FEP) portends to provide a unifying principle for the biological and cognitive sciences. It states that for a system to maintain non-equilibrium steady-state with its environment it must minimise its (information-theoretic) free energy. Under the FEP, to minimise free energy is equivalent to engaging in approximate Bayesian inference. According to the FEP, therefore, inference is at the explanatory base of biology and cognition. In this paper, we discuss a specific challenge to this inferential formulation of adaptive (...) self-organisation. We call it the universal ethology challenge: it states that the FEP cannot unify biology and cognition, for life itself (or adaptive self-organisation) does not require inferential routines to select adaptive solutions to environmental pressures (as mandated by the FEP). We show that it is possible to overcome the universal ethology challenge by providing a cautious and exploratory treatment of inference under the FEP. We conclude that there are good reasons for thinking that the FEP can unify biology and cognition under the notion of approximate Bayesian inference, even if further challenges must be addressed to properly draw such a conclusion. (shrink)

Enculturation is known to shape the perception of meter in music but this is not explicitly accounted for by current cognitive models of meter perception. We hypothesize that meter perception is a strategy for increasing the predictability of rhythmic patterns and that the way in which it is shaped by the cultural environment can be understood in terms of probabilistic predictive coding. Based on this hypothesis, we present a probabilistic model of meter perception that uses statistical properties of the relation (...) between rhythm and meter to infer meter from quantized rhythms. We show that our model can successfully predict annotated time signatures from quantized rhythmic patterns derived from folk melodies. Furthermore, we show that by inferring meter, our model can better predict the onsets of future events than a similar probabilistic model that does not infer meter. Finally, we demonstrate how our model can be used in a proof-of-concept simulation of enculturation. From this simulation, we derive a class of rhythms that are likely to be interpreted differently by enculturated listeners with different histories of exposure to rhythms. (shrink)

The recognition and incorporation of evidence-based neuroscientific concepts into creative arts therapeutic knowledge and practice seem valuable and advantageous for the purpose of integration and professional development. Moreover, exhilarating insights from the field of neuroscience coincide with the nature, conceptualization, goals, and methods of Creative Arts Therapies, enabling comprehensive understandings of the clinical landscape, from a translational perspective. This paper contextualizes and discusses dynamic brain functions that have been suggested to lie at the heart of intra- and inter-personal processes. Touching (...) upon fundamental aspects of the self and self-other interaction, the state-of-the-art neuroscientific-informed views will shed light on mechanisms of the embodied, predictive and relational brain. The conceptual analysis introduces and interweaves the following contemporary perspectives of brain function: firstly, the grounding of mental activity in the lived, bodily experience will be delineated; secondly, the enactive account of internal models, or generative predictive representations, shaped by experience, will be defined and extensively deliberated; and thirdly, the interpersonal simulation and synchronization mechanisms that support empathy and mentalization will be thoroughly considered. Throughout the paper, the cross-talks between the brain and the body, within the brain through functionally connected neural networks and in the context of agent-environment dynamics, will be addressed. These communicative patterns will be elaborated on to unfold psychophysiological linkage, as well as psychopathological shifts, concluding with the neuroplastic change associated with the formulation of CATs. The manuscript suggests an integrative view of the brain-body-mind in contexts relevant to the therapeutic potential of the expressive creative arts and the main avenues by which neuroscience may ground, enlighten and enrich the clinical psychotherapeutic practice. (shrink)

What psychological mechanisms enable people to reappraise a situation to change its emotional impact? We propose that reappraisal works by shifting appraisal outcomes—abstract representations of ho...

This paper offers a renewed construction grammar analysis of linguistic constructions in a diachronic perspective. The present theory, termedAgentive Cognitive Construction Grammar(AgCCxG), is informed byactive inference(AIF), a process theory for the comprehension of intelligent agency. AgCCxG defends the idea that language bear traces of non-linguistic, bodily-acquired information that reflects sémiotico-biological processes of energy exchange and conservation. One of the major claims of the paper is that embodied cognition has evolved to facilitate ontogenic mental alignment among humans. This is demonstrated by (...) the results of a corpus study in which the patterns of association between verbs, the particle UP and argument structure in Old and Middle English have been studied. The conclusion is that, similar to biological systems, the linguistic sign system displays patterns of equilibrium and non-equilibrium. In other words, while in Old English usage near equilibrium was reached through the use of a conservative set of constructional semiotic templates (attachment patterns), associated with motor modalities, Middle English displays high rates of randomness resulting in a less stable, yet distinct, system of constructional attachment. (shrink)

This paper explores the challenges posed by the rapid advancement of artificial intelligence specifically Large Language Models (LLMs). I show that traditional linguistic theories and corpus studies are being outpaced by LLMs’ computational sophistication and low perplexity levels. In order to address these challenges, I suggest a focus on language as a cognitive tool shaped by embodied-environmental imperatives in the context of Agentive Cognitive Construction Grammar. To that end, I introduce an Embodied Human Language Model (EHLM), inspired by Active Inference (...) research, as a promising alternative that integrates sensory input, embodied representations, and adaptive strategies for contextualized analysis and conceptual utility maximization. By incorporating Active Inference, which sees perception as inferring the world's state from sensory data, the findings reveal that the characterization of the English modal be able to, as a triadic construction encoding biological intelligent agency, introduces a more plausible theoretical basis for the positing of linguistic constructions. This emphasizes the crucial role of embodied human language models in the comprehension of how humans construct preferred futures through language. (shrink)

This paper introduces a novel perspective on Agentive Cognitive Construction Grammar (AgCCxG) by examining the intricate interplay between mind and language through the lens of both Active Inference and Peircean semiotics. AgCCxG emphasizes the impact of intention and purpose on linguistic choices as a cognitive imperative to balance the symbolic Self (Intelligent Agent) with the dynamics of the environment. Among other things, the paper posits that linguistic constructions, particularly Constructional Attachment Patterns (CAPs), like argument structure constructions, embody experienced interactions with (...) the world through reenactment routines via the integration of multisensory channels. Unlike traditional usage-based approaches (e.g., construction grammars), AgCCxG embraces a robust theory of signs that reveals human representation as a continuous process of semiotic hybridization for the creative prediction of uncertain scenarios. Importantly, the paper challenges the notion of the mind as a unified, rational, uncertainty-reducing machine by asserting that physical processes governing open biological systems profoundly influence the linguistic sign system. Intelligent agents’ adaptability in expressing incongruous realities thus highlights the role of semiotic hybridization in preserving an agent’s autonomy and semiotic boundary. (shrink)

Numerous species use different forms of communication in order to successfully interact in their respective environment. This article seeks to elucidate limitations of the classical conduit metaphor by investigating communication from the perspectives of biology and artificial neural networks. First, communication is a biological natural phenomenon, found to be fruitfully grounded in an organism’s embodied structures and memory system, where specific abilities are tied to procedural, semantic, and episodic long-term memory as well as to working memory. Second, the account explicates (...) differences between non-verbal and verbal communication and shows how artificial neural networks can communicate by means of ontologically non-committal modelling. This approach enables new perspectives of communication to emerge regarding both sender and receiver. It is further shown that communication features gradient properties that are plausibly divided into a reflexive and a reflective form, parallel to knowledge and reflection. (shrink)

“Perception is controlled hallucination,” according to proponents of predictive processing accounts of vision. I say they are right that something like this is a consequence of their view but wrong in how they have pursued the idea. The focus of my counterproposal is the causal theory of perception, which I develop in terms of a productive concept of causation. Cases of what otherwise seem like successful perception are instead mere veridical hallucination if predictive processing accounts are correct, I argue, because (...) of the role played within such accounts by absences, which cannot enter into productive causal relations. -/- I offer two arguments in support of the productive theory of perception. The first is loosely Kantian, focusing on the role that receptivity and spontaneity play in perception. The second focuses on what perception and hallucination have in common. I conclude with a series of objections and replies. (shrink)

Bounded rationality gets a bad rap in epistemology. It is argued that theories of bounded rationality are overly context‐sensitive; conventionalist; or dependent on ordinary language (Carr, 2022; Pasnau, 2013). In this paper, I have three aims. The first is to set out and motivate an approach to bounded rationality in epistemology inspired by traditional theories of bounded rationality in cognitive science. My second aim is to show how this approach can answer recent challenges raised for theories of bounded rationality. My (...) third aim is to clarify the role of rational ideals in bounded rationality. (shrink)

The question of whether cognition can influence perception has a long history in neuroscience and philosophy. Here, we outline a novel approach to this issue, arguing that it should be viewed within the framework of top-down information-processing. This approach leads to a reversal of the standard explanatory order of the cognitive penetration debate: we suggest studying top-down processing at various levels without preconceptions of perception or cognition. Once a clear picture has emerged about which processes have influences on those at (...) lower levels, we can re-address the extent to which they should be considered perceptual or cognitive. Using top-down processing within the visual system as a model for higher-level influences, we argue that the current evidence indicates clear constraints on top-down influences at all stages of information processing; it does, however, not support the notion of a boundary between specific types of information-processing as proposed by the cognitive impenetrability hypothesis. (shrink)

Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine, a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual (...) information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models. We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. (shrink)