I argue that our current practice of ascribing the term “ memory ” to mental states and processes lacks epistemic warrant. Memory, according to the “received view”, is any state or process that results from the sequential stages of encoding, storage and retrieval. By these criteria, memory, or its footprint, can be seen in virtually every mental state we are capable of having. This, I argue, stretches the term to the breaking point. I draw on phenomenological, historical and conceptual considerations (...) to make the case that an act of memory entails a direct, non-inferential feeling of re-acquaintance with one’s past. It does so by linking content retrieved from storage with autonoetic awareness during retrieval. On this view, memory is not the content of experience, but the manner in which that content is experienced. I discuss some theoretical and practical implications and advantages of adopting this more nuanced view of memory. -/-. (shrink)

Neural structural representations are cerebral map- or model-like structures that structurally resemble what they represent. These representations are absolutely central to the “cognitive neuroscience revolution”, as they are the only type of representation compatible with the revolutionaries’ mechanistic commitments. Crucially, however, these very same commitments entail that structural representations can be observed in the swirl of neuronal activity. Here, I argue that no structural representations have been observed being present in our neuronal activity, no matter the spatiotemporal scale of observation. (...) My argument begins by introducing the “cognitive neuroscience revolution” (Sect. 1 ) and sketching a prominent, widely adopted account of structural representations (Sect. 2 ). Then, I will consult various reports that describe our neuronal activity at various spatiotemporal scales, arguing that none of them reports the presence of structural representations (Sect. 3 ). After having deflected certain intuitive objections to my analysis (Sect. 4 ), I will conclude that, in the absence of neural structural representations, representationalism and mechanism can’t go together, and so the “cognitive neuroscience revolution” is forced to abandon one of its commitments (Sect. 5 ). (shrink)

Intelligence in current AI research is measured according to designer-assigned tasks that lack any relevance for an agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than the possible intelligence of agents that we design and evaluate. As a possible first step in remedying this, this article introduces the notion of “self-concern,” a property of a complex system that describes its tendency to bring about states that are compatible with its continued self-maintenance. Self-concern, as (...) argued, is the foundation of the kind of basic intelligence found across all biological systems, because it reflects any such system's existential task of continued viability. This article aims to cautiously progress a few steps closer to a better understanding of some necessary organisational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence. (shrink)

Under the assumption that anticipatory models are required for anticipatory behavior, an important question arises about the different manners in which organisms acquire anticipatory models. This article aims to articulate four different non-exhaustive ways that anticipatory models might possibly be acquired over both phylogenetic and ontogenetic timescales and explore the relationships among them. To articulate these different model-acquisition mechanisms, four schematics will be introduced, each of which represents a particular acquisition structure that can be used for the purposes of comparison, (...) analysis, and hypothesis formulation. By bringing to the fore the differences and similarities between each of the four ways that anticipatory models are acquired, a more complete picture of both anticipatory behavior and its pervasive role in biological self-maintenance can be offered. In doing so, this article helps not only to shed light on how anticipatory behavior might arise in the wide range of organisms that it has been observed in but also to throw into relief the subtle and often still overlooked causal interplay between ontogenetic and phylogenetic plasticity. (shrink)

Biogenic approaches investigate cognition from the standpoint of evolutionary function, asking what cognition does for a living system and then looking for common principles and exhibitions of cognitive strategies in a vast array of living systems—non-neural to neural. One worry which arises for the biogenic approach is that it is overly permissive in terms of what it construes as cognition. In this paper I critically engage with a recent instance of this way of criticising biogenic approaches in order to clarify (...) their theoretical commitments and prospects. In his critique of the biogenic approach, Fred Adams uses the presence of intentional states with conceptual content as a criterion to demarcate cognition-driven behaviour from mere sensory response. In this paper I agree with Adams that intentionality is the mark of the cognitive, but simultaneously reject his overly restrictive conception of intentionality. I argue that understanding intentionality simpliciter as the mark of the mental is compatible with endorsing the biogenic approach. I argue that because cognitive science is not exclusively interested in behaviour driven by intentional states with the kind of content Adams demands, the biogenic approach’s status as an approach to cognition is not called into question. I then go on to propose a novel view of intentionality whereby it is seen to exist along a continuum which increases in the degree of representational complexity: how far into the future representational content can be directed and drive anticipatory behaviour. Understanding intentionality as existing along a continuum allows biogenic approaches and anthropogenic approaches to investigate the same overarching capacity of cognition as expressed in its different forms positioned along the continuum of intentionality. Even if all organisms engage in some behaviour that is driven by weak intentional dynamics, this does not suggest that every behaviour of all organisms is so driven. As such, the worry that the biogenic approach is overly permissive can be avoided. (shrink)

Many philosophers claim that the neurocomputational framework of predictive processing entails a globally inferentialist and representationalist view of cognition. Here, I contend that this is not correct. I argue that, given the theoretical commitments these philosophers endorse, no structure within predictive processing systems can be rightfully identified as a representational vehicle. To do so, I first examine some of the theoretical commitments these philosophers share, and show that these commitments provide a set of necessary conditions the satisfaction of which allows (...) us to identify representational vehicles. Having done so, I introduce a predictive processing system capable of active inference, in the form of a simple robotic “brain”. I examine it thoroughly, and show that, given the necessary conditions highlighted above, none of its components qualifies as a representational vehicle. I then consider and allay some worries my claim could raise. I consider whether the anti-representationalist verdict thus obtained could be generalized, and provide some reasons favoring a positive answer. I further consider whether my arguments here could be blocked by allowing the same representational vehicle to possess multiple contents, and whether my arguments entail some extreme form of revisionism, answering in the negative in both cases. A quick conclusion follows. (shrink)

Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks an adequate justification. I examine the only argument (...) offered to establish that generative models are structural representations, and argue that it does not substantiate the desired conclusion. Having so done, I consider a number of alternative arguments aimed at showing that the relevant structural similarity obtains, and argue that all these arguments are unconvincing for a variety of reasons. I then conclude the paper by briefly highlighting three themes that might be relevant for further investigation on the matter. (shrink)

Structural representations are increasingly popular in philosophy of cognitive science. A key virtue they seemingly boast is that of meeting Ramsey's job description challenge. For this reason, structural representations appear tailored to play a clear representational role within cognitive architectures. Here, however, I claim that structural representations do not meet the job description challenge. This is because even our most demanding account of their functional profile is satisfied by at least some receptors, which paradigmatically fail the job description challenge. Hence, (...) the functional profile typically associated with structural representations does not identify representational posits. After a brief introduction, I present, in the second section of the paper, the job description challenge. I clarify why receptors fail to meet it and highlight why, as a result, they should not be considered representations. In the third section I introduce what I take to be the most demanding account of structural representations at our disposal, namely Gładziejewski's account. Provided the necessary background, I turn from exposition to criticism. In the first half of the fourth section, I equate the functional profile of structural representations and receptors. To do so, I show that some receptors boast, as a matter of fact, all the functional features associated with structural representations. Since receptors function merely as causal mediators, I conclude structural representations are mere causal mediators too. In the second half of the fourth section I make this conclusion intuitive with a toy example. I then conclude the paper, anticipating some objections my argument invites. (shrink)

In this chapter we examine the tendency to view future-oriented mental time travel as a unitary faculty that, despite task-driven surface variation, ultimately reduces to a common phenomenological state. We review evidence that FMTT is neither unitary nor beholden to episodic memory: Rather, it is varied both in its memorial underpinnings and experiential realization. We conclude that the phenomenological diversity characterizing FMTT is dependent not on the type of memory activated during task performance, but on the kind of subjective temporality (...) associated with the memory in play. (shrink)

I applaud Huang & Bargh's theory that places goals at the center of cognition, and I discuss two ingredients missing from that theory. First, I argue that the brains of organisms much simpler than those of humans are already configured for goal achievement in situated interactions. Second, I propose a mechanistic view of the “reconfiguration principle” that links the theory with current views in computational neuroscience.

Purpose: Constructivism postulates that the perceived reality is a complex construct formed during development. Depending on the particular school, these inner constructs take on different forms and structures and affect cognition in different ways. The purpose of this article is to address the questions of how and, even more importantly, why we form such inner constructs. Approach: This article proposes that brain development is controlled by an inherent anticipatory drive, which biases learning towards the formation of forward predictive structures and (...) inverse goal-oriented control structures. This drive, in combination with increasingly complex environmental interactions during cognitive development, enforces the structuring of our conscious self, which is embedded in a constructed inner reality. Essentially, the following questions are addressed: Which basic mechanisms lead us to the construction of inner realities? How are these emergent inner realities structured? How is the self represented within the inner realities? And consequently, which cognitive structures constitute the media for conscious thought and selfconsciousness? Findings: Due to the anticipatory drive, representations in the brain shape themselves predominantly purposefully or intentionally. Taking a developmental, evolutionary perspective, we show how the brain is forced to develop progressively complex and abstract representations of the self embedded in the constructed inner realities. These self representations can evoke different stages of self-consciousness. Implications: The anticipatory drive shapes brain structures and cognition during the development of progressively more complex, competent, and flexible goal-oriented bodyenvironment interactions. Self-consciousness develops because increasingly abstract, individualizing self representations are necessary to realize these progressively more challenging environmental interactions. (shrink)

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

Why is interaction so simple? This article presents a theory of interaction based on the use of shared representations as “coordination tools” (e.g., roundabouts that facilitate coordination of drivers). By aligning their representations (intentionally or unintentionally), interacting agents help one another to solve interaction problems in that they remain predictable, and offer cues for action selection and goal monitoring. We illustrate how this strategy works in a joint task (building together a tower of bricks) and discuss its requirements from a (...) computational viewpoint. (shrink)

What is the function of cognition? On one influential account, cognition evolved to co-ordinate behaviour with environmental change or complexity. Liberal interpretations of this view ascribe cognition to an extraordinarily broad set of biological systems—even bacteria, which modulate their activity in response to salient external cues, would seem to qualify as cognitive agents. However, equating cognition with adaptive flexibility per se glosses over important distinctions in the way biological organisms deal with environmental complexity. Drawing on contemporary advances in theoretical biology (...) and computational neuroscience, we cash these distinctions out in terms of different kinds of generative models, and the representational and uncertainty-resolving capacities they afford. This analysis leads us to propose a formal criterion for delineating cognition from other, more pervasive forms of adaptive plasticity. On this view, biological cognition is rooted in a particular kind of functional organisation; namely, that which enables the agent to detach from the present and engage in counterfactual inference. (shrink)

Cognitive science and its philosophy have been far too long consumed with representation. This concern is indicative of a creeping Cartesianism that many scientists and philosophers wish to evade. However, their naturalism is often insufficiently evolutionary to fully appreciate the lessons of pragmatism. If cognitive neuroscience and pragmatism are to be mutually beneficial, the representational-friendly scientists and the anti-representational pragmatists need an alternative to representation that still accounts for what many find so attractive about representation, namely intentionality. I propose that (...) instead of representations we philosophers and scientists begin thinking in terms of cultural affordances. Like Gibsonian affordances, cultural affordances are opportunities for action. However, unlike Gibsonian affordances, which are merely biological and available for immediate action in the immediately present environment, cultural affordances also present opportunities for thinking about the past and acting into the future—tasks typically attributed to representations. (shrink)

We propose a view of embodied representations that is alternative to both symbolic/linguistic approaches and purely sensorimotor views of cognition, and can account for procedural and declarative knowledge manipulation. In accordance with recent evidence in cognitive neuroscience and psychology, we argue that anticipatory and simulative mechanisms, which arose during evolution for action control and not for cognition, determined the first form of representational content and were exapted for increasingly sophisticated cognitive uses. In particular, procedural and declarative forms of knowledge can (...) be explained, respectively, in terms of on-line sensorimotor anticipation and off-line simulations of potential actions, which can give access to tacit knowledge and make it explicit. That is, mechanisms that evolved for the on-line prediction of the consequences of one's own actions (i.e. forward models) determine a (procedural) form of representation, and became exapted for off-line use. They can therefore be used to produce (declarative) knowledge of the world, by running a simulation of the action that would produce the relevant information. We conclude by discussing how embodied representations afford a form of internal manipulation that can be described as internalized situated action. (shrink)

The future harbours the potential for myriad threats to the fitness of organisms, and many species prepare accordingly based on indicators of hazards. Here, we distinguish between defensive responses on the basis of sensed cues and those based on autocues generated by mental simulations of the future in humans. Whereas sensed threat cues usually induce specific responses with reference to particular features of the environment or generalized responses to protect against diffuse threats, autocues generated by mental simulations of the future (...) enable strategic preparation for hazards that may not require an immediate response. The overlap of these mechanisms makes defence effective and versatile, yet can manifest as contemporary anxiety disorders in humans. (shrink)

Understanding the role of ‘‘representations’’ in cognitive science is a fundamental problem facing the emerging framework of embodied, situated, dynamical cognition. To make progress, I follow the approach proposed by an influential representational skeptic, Randall Beer: building artificial agents capable of minimally cognitive behaviors and assessing whether their internal states can be considered to involve representations. Hence, I operationalize the concept of representing as ‘‘standing in,’’ and I look for representations in embodied agents involved in simple categorization tasks. In a (...) first experiment, no representation can be found, but the relevance of the task is undermined by the fact that agents with no internal states can reach high performance. A simple modification makes the task more “representationally hungry,” and in this case, agents’ internal states are found to qualify as representations. I conclude by discussing the benefits of reconciling the embodied-dynamical approach with the notion of representation. (shrink)