Representation in Neuroscience

Recent research suggests that human memories are stored not between neurons as synaptic weights, but within individual neurons themselves. This opens the possibility to replace the dominant paradigm of brain function – neural networks – with a new one. In this article, I explore how “identified neurons” could explain how memories are stored, and how human traits are implemented in the brain.

Many of us consider it uncontroversial that information processing is a natural function of the brain. Since functions in biology are only won through empirical investigation, there should be a significant body of unambiguous evidence that supports this functional claim. Before we can interpret the evidence, however, we must ask what it means for a biological system to process information. Although a concept of information is generally accepted in the neurosciences without critique, in other biological sciences applications of information, despite (...) careful analysis, remain controversial. In this work I will review classical stimulus-response studies in neuroscience and use Claude Shannon’s mathematical information theory as a starting point to interpret information processing as a function of the brain. I will illustrate a disanalogy between Shannon’s communication model (source, encode, channel, receiver, decode) and neural systems, and will argue that the neural code is not very code-like in comparison to genetic and engineered codes. I suggest that we have conflated the act of representing neuroscientific facts—which we do to summarize and communicate our findings with others—with taking experimental facts to be representations. (shrink)

Many cognitive scientists, neuroscientists, and philosophers of science consider it uncontroversial that the brain processes information. In this work we broadly consider the types of experimental evidence that would support this claim, and find that although physical features of specific brain areas selectively covary with external stimuli or abilities, there is no direct evidence supporting an information processing function of any particular brain area.

We explore the contribution made by oscillatory, synchronous neural activity to representation in the brain. We closely examine six prominent examples of brain function in which neural oscillations play a central role, and identify two levels of involvement that these oscillations take in the emergence of representations: enabling (when oscillations help to establish a communication channel between sender and receiver, or are causally involved in triggering a representation) and properly representational (when oscillations are a constitutive part of the representation). -/- (...) We show that even an idealized informational sender-receiver account of representation makes the representational status of oscillations a non-trivial matter, which depends on rather minute empirical details. (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)

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)

Over the last decades, network-based approaches have become highly popular in diverse fields of biology, including neuroscience, ecology, molecular biology and genetics. While these approaches continue to grow very rapidly, some of their conceptual and methodological aspects still require a programmatic foundation. This challenge particularly concerns the question of whether a generalized account of explanatory, organisational and descriptive levels of networks can be applied universally across biological sciences. To this end, this highly interdisciplinary theme issue focuses on the definition, motivation (...) and application of key concepts in biological network science, such as explanatory power of distinctively network explanations, network levels, and network hierarchies. (shrink)

Neuroclassicism is the view that cognition is explained by “classical” computing mechanisms in the nervous system that exhibit a clear demarcation between processing machinery and read–write memory. The psychologist C. R. Gallistel has mounted a sophisticated defense of neuroclassicism by drawing from ethology and computability theory to argue that animal brains necessarily contain read–write memory mechanisms. This argument threatens to undermine the “connectionist” orthodoxy in contemporary neuroscience, which does not seem to recognize any such mechanisms. In this paper I argue (...) that the neuroclassicist critique rests on a misunderstanding of how computability theory constrains theorizing about natural computing mechanisms. (shrink)

The concept of mental representation has long been considered to be central concept of philosophy of mind and cognitive science. But not everyone agrees. Neo-behaviorists aim to explain the mind without positing any representations. My aim here is not to assess the merits and demerits of neo-behaviorism, but to take their challenge seriously and ask the question: What justifies the attribution of representations to an agent? Both representationalists and neo-behaviorists tend to take it for granted that the real question about (...) representations is whether we should be realist about the theory of representationalism. This paper is an attempt to shift the emphasis from the debate concerning realism about theories to the one concerning realism about entities. My claim is that regardless of whether we are realist about representational theories of the mind, we have compelling reasons to endorse entity realism about mental representations. (shrink)

Os realistas diretos sobre a memória episódica alegam que um sujeito que lembra está em contato direto com um evento passado. No entanto, como seria possível estar em contato direto com um evento que deixou de existir? Este é o assim-chamado problema da cotemporalidade. A solução padrão para este problema, a qual foi proposta por Sven Bernecker, consiste em distinguir entre, por um lado, a ocorrência de um evento, e, por outro lado, a existência de um evento, de modo que (...) um evento deixa de ocorrer sem deixar de existir – esta é a solução eternista para o problema da cotemporalidade. No entanto, alguns filósofos da memória – notadamente Kourken Michaelian – alegam que a adoção de uma metafísica eternista do tempo seria um preço metafísico muito alto a ser pago para se defender as intuições dos realistas diretos sobre a memória. Ainda que eu concorde com essas críticas, buscarei mostrar duas coisas. Primeiro, que este tipo de “argumento do senso comum” não é decisivo. Segundo, que a proposta de Bernecker permanece sendo a melhor solução para o problema da cotemporalidade. (shrink)

Over the last 30 years, representationalist and dynamicist positions in the philosophy of cognitive science have argued over whether neurocognitive processes should be viewed as representational or not. Major scientific and technological developments over the years have furnished both parties with ever more sophisticated conceptual weaponry. In recent years, an enactive generalization of predictive processing – known as active inference – has been proposed as a unifying theory of brain functions. Since then, active inference has fueled both representationalist and dynamicist (...) campaigns. However, we believe that when diving into the formal details of active inference, one should be able to find a solution to the war; if not a peace treaty, surely an armistice of a sort. Based on an analysis of these formal details, this paper shows how both representationalist and dynamicist sensibilities can peacefully coexist within the new territory of active inference. (shrink)

Our access to computer-generated worlds changes the way we feel, how we think, and how we solve problems. In this review, we explore the utility of different types of virtual reality, immersive or non-immersive, for providing controllable, safe environments that enable individual training, neurorehabilitation, or even replacement of lost functions. The neurobiological effects of virtual reality on neuronal plasticity have been shown to result in increased cortical gray matter volumes, higher concentration of electroencephalographic beta-waves, and enhanced cognitive performance. Clinical application (...) of virtual reality is aided by innovative brain-computer interfaces, which allow direct tapping into the electric activity generated by different brain cortical areas for precise voluntary control of connected robotic devices. Virtual reality is also valuable to healthy individuals as a narrative medium for redesigning their individual stories in an integrative process of self-improvement and personal development. Future upgrades of virtual reality-based technologies promise to help humans transcend the limitations of their biological bodies and augment their capacity to mold physical reality to better meet the needs of a globalized world. (shrink)

The notion of “hierarchy” is one of the most commonly posited organizational principles in systems neuroscience. To this date, however, it has received little philosophical analysis. This is unfortunate, because the general concept of hierarchy ranges over two approaches with distinct empirical commitments, and whose conceptual relations remain unclear. We call the first approach the “representational hierarchy” view, which posits that an anatomical hierarchy of feed-forward, feed-back, and lateral connections underlies a signal processing hierarchy of input-output relations. Because the representational (...) hierarchy view holds that unimodal sensory representations are subsequently elaborated into more categorical and rule-based ones, it is committed to an increasing degree of abstraction along the hierarchy. The second view, which we call “topological hierarchy", is not committed to different representational functions or degrees of abstraction at different levels. Topological approaches instead posit that the hierarchical level of a part of the brain depends on how central it is to the pattern of connections in the system. Based on the current evidence, we argue that three conceptual relations between the two approaches are possible: topological hierarchies could substantiate the traditional representational hierarchy, conflict with it, or contribute to a plurality of approaches needed to understand the organization of the brain. By articulating each of these possibilities, our analysis attempts to open a conceptual space in which further neuroscientific and philosophical reasoning about neural hierarchy can proceed. (shrink)

Superposition: the 'reality' behind 'Reality.'.

Cracking the ‘universal’ code: the tokenization of Nature. (Think: representation, abstraction, realization.) A universal blockchain.

Cryptocurrency is just the tip of a never-melting iceberg…because everything in Nature is connected to everything else by an always-conserved (and uber-simple) circle. Giving us, finally, an explanation (and, technically, a use-case, and proof) for a 'self.'.

Abstract is a noun. Abstract is, also, a verb. Thus, abstraction. Explaining nouns. And verbs.

What modern physicists are 'discovering:' conservation of a circle is the basis for 'reality.'.

The power of representation and the representation of power, and, the exploding NFT market. Euclid's error and the mathematics behind representation, identification, and interpretation.

Reality is the conservation of a circle. Producing tokenization. Representation. Identification. The reference.

Philosophical proponents of predictive processing cast the novelty of predictive models of perception in terms of differences in the functional role and information content of neural signals. However, they fail to provide constraints on how the crucial semantic mapping from signals to their informational contents is determined. Beyond a novel interpretative gloss on neural signals, they have little new to say about the causal structure of the system, or even what statistical information is carried by the signals. That means that (...) the predictive framework for perception can be relabeled in traditional, non-predictive terms, with no empirical consequences relevant to existing or future data. To the extent that neuroscientific research based on predictive processing is both innovative and productive, it will be due to the framework’s suggestive heuristic effects, or perhaps auxiliary empirical claims about implementation, rather than a difference in the information-processing structure that it describes. (shrink)

Although there is a substantial philosophical literature on dynamical systems theory in the cognitive sciences, the same is not the case for neuroscience. This paper attempts to motivate increased discussion via a set of overlapping issues. The first aim is primarily historical and is to demonstrate that dynamical systems theory is currently experiencing a renaissance in neuroscience. Although dynamical concepts and methods are becoming increasingly popular in contemporary neuroscience, the general approach should not be viewed as something entirely new to (...) neuroscience. Instead, it is more appropriate to view the current developments as making central again approaches that facilitated some of neuroscience’s most significant early achievements, namely, the Hodgkin–Huxley and FitzHugh–Nagumo models. The second aim is primarily critical and defends a version of the “dynamical hypothesis” in neuroscience. Whereas the original version centered on defending a noncomputational and nonrepresentational account of cognition, the version I have in mind is broader and includes both cognition and the neural systems that realize it as well. In view of that, I discuss research on motor control as a paradigmatic example demonstrating that the concepts and methods of dynamical systems theory are increasingly and successfully being applied to neural systems in contemporary neuroscience. More significantly, such applications are motivating a stronger metaphysical claim, that is, understanding neural systems as being dynamical systems, which includes not requiring appeal to representations to explain or understand those phenomena. Taken together, the historical claim and the critical claim demonstrate that the dynamical hypothesis is undergoing a renaissance in contemporary neuroscience. (shrink)

Nick Shea’s Representation in Cognitive Science commits him to representations in perceptual processing that are about probabilities. This commentary concerns how to adjudicate between this view and an alternative that locates the probabilities rather in the representational states’ associated “attitudes”. As background and motivation, evidence for probabilistic representations in perceptual processing is adduced, and it is shown how, on either conception, one can address a specific challenge Ned Block has raised to this evidence.

Neural systems process information. This platitude contains an interesting ambiguity between multiple senses of the term “information.” According to a popular thought, the ambiguity is best resolved by reserving semantic concepts of information for the explication of neural activity at a high level of organization, and quantitative concepts of information for the explication of neural activity at a low level of organization. This article articulates the justification behind this view, and concludes that it is an oversimplification. An analysis of the (...) meaning of claims about Shannon information rates in the spiking activity of neurons is then developed. On the basis of that analysis, it is shown that quantitative conceptions of information are more intertwined with semantic concepts than they seem to be, and, partially for that reason, are also more philosophically interesting. (shrink)

It’s often claimed in the philosophical and scientific literature on temporal representation that there is no such thing as a genuine sensory system for time. In this paper, I argue for the opposite—many animals, including all mammals, possess a genuine sensory system for time based in the circadian system. In arguing for this conclusion, I develop a semantics and meta-semantics for explaining how the endogenous rhythms of the circadian system provide organisms with a direct information link to the temporal structure (...) of their environment. In doing so, I highlight the role of sensory systems in an information processing architecture. (shrink)

In the 1980s, a number of philosophers argued that perception is analog. In the ensuing years, these arguments were forcefully criticized, leaving the thesis in doubt. This paper draws on Weber’s Law, a well-entrenched finding from psychophysics, to advance a new argument that perception is analog. This new argument is an adaptation of an argument that cognitive scientists have leveraged in support of the contention that primitive numerical representations are analog. But the argument here is extended to the representation of (...) non-numerical magnitudes, such as luminance and distance, and shown to apply to perception and not just cognition. The relevant sense of ‘analog’ is also clarified, and two powerful objections are addressed. Finally, the question whether perception’s analog vehicles are located in conscious experience is explored and related to a well-known controversy within psychophysics. (shrink)

Joint actions often require agents to track others’ actions while planning and executing physically incongruent actions of their own. Previous research has indicated that this can lead to visuomotor interference effects when it occurs outside of joint action. How is this avoided or overcome in joint actions? We hypothesized that when joint action partners represent their actions as interrelated components of a plan to bring about a joint action goal, each partner’s movements need not be represented in relation to distinct, (...) incongruent proximal goals. Instead they can be represented in relation to a single proximal goal – especially if the movements are, or appear to be, mechanically linked to a more distal joint action goal. To test this, we implemented a paradigm in which participants produced finger movements that were either congruent or incongruent with those of a virtual partner, and either with or without a joint action goal (the joint flipping of a switch, which turned on two light bulbs). Our findings provide partial support for the hypothesis that visuomotor interference effects can be reduced when two physically incongruent actions are represented as mechanically interdependent contributions to a joint action goal. (shrink)

Introduction: The objective of this investigation is to analyse the informational circuits of the brain connections with the body from neurologic and neuroscience point of view, on the basis of the concepts of information promoted by the Informational Model of Consciousness. Analysis: Distinguishing between the virtual and matter-related information promoted by the Informational Model of Consciousness, the main specific features of consciousness are analyzed from the informational perspective, showing that the informational architecture of consciousness consists in seven groups of specific (...) activities, defined as cognitive centres, each of them with specific distinct tasks, but correlated each other: centre of acquisition and storing of information (memory), centre of decision and command (decision), centre of the emotional states (emotions), centre of the body maintenance (power and health), centre of the genetic elaboration/transmission (reproduction) and the info-genetic generator, inherited from the parents (predispositions, talents and skills). A special centre, dedicated to the connectivity with some extra-power properties of the mind is also introduced, assuring an intimate supra-sensitive detection of the world to explain the associated phenomena of the near-death experiences. Result: The activity of all these centres should be supported neurologically by the brain neuro-connectivity to the body and to external and internal info-signals. On the basis of the informational analysis, the neuro-connections of the brain regions associated to the main characteristics of the cognitive centres are highlighted, showing the anatomic and neuro-functional relation between the distinct components of the brain and the specific operating body regions. These connections describe in terms of information the brain-body neuro-activities as informational specific circuits, composed by the info-operational subsystems managed by the brain, and sensors, transducer and execution elements. Conclusion: The components and connections mind-body stipulated by the Informational Model of Consciousness are supported by the neurologic/neuroscience evidence. (shrink)

Mainstream teleosemantics is the view that mental representation should be understood in terms of biological functions, which, in turn, should be understood in terms of selection processes. One of the traditional criticisms of teleosemantics is the problem of novel contents: how can teleosemantics explain our ability to represent properties that are evolutionarily novel? In response, some have argued that by generalizing the notion of a selection process to include phenomena such as operant conditioning, and the neural selection that underlies it, (...) we can resolve this problem. Here, we do four things: we develop this suggestion in a rigorous way through a simple example, we draw on recent neurobiological research to support its empirical plausibility, we defend the move from a host of objections in the literature, and we sketch how the picture can be extended to help us think about more complex “conceptual” representations and not just perceptual ones. (shrink)

Similarity-based cognition is commonplace. It occurs whenever an agent or system exploits the similarities that hold between two or more items—e.g., events, processes, objects, and so on—in order to perform some cognitive task. This kind of cognition is of special interest to cognitive neuroscientists. This paper explicates how similarity-based cognition can be understood through the lens of radical enactivism and why doing so has advantages over its representationalist rival, which posits the existence of structural representations or S-representations. Specifically, it is (...) argued that there are problems both with accounting for the content of S-representations and with understanding how neurally-based structural similarities can work as representations in guiding intelligent behavior. Finally, with these clarifications in place, it is revealed how radical enactivism can commit to an account of similarity-based cognition in its understanding of neurodynamics. (shrink)

Barsalou has recently argued against the strategy of identifying amodal neural representations by using their cross-modal responses (i.e., their responses to stimuli from different modalities). I agree that there are indeed modal structures that satisfy this “cross-modal response” criterion (CM), such as distributed and conjunctive modal representations. However, I argue that we can distinguish between modal and amodal structures by looking into differences in their cross-modal responses. A component of a distributed cell assembly can be considered unimodal because its responses (...) to stimuli from a given modality are stable, whereas its responses to stimuli from any other modality are not (i.e., these are lost within a short time, plausibly as a result of cell assembly dynamics). In turn, conjunctive modal representations, such as superior colliculus cells in charge of sensory integration, are multimodal because they have a stable response to stimuli from different modalities. Finally, some prefrontal cells constitute amodal representations because they exhibit what has been called ‘adaptive coding’. This implies that their responses to stimuli from any given modality can be lost when the context and task conditions are modified. We cannot assign them a modality because they have no stable relation with any input type. (shrink)

We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we focus on views that attempt to render such ascriptions naturalistic by construing them in a deflationary or merely pragmatic way. We then contrast these views with staunchly realist views that attempt to naturalize intentionality by developing theories of content for representations in terms of information and biological function. (...) We echo several other philosophers by arguing that these theories over-generalize unless they are constrained by a theory of the functional role of representational vehicles. This leads to a discussion of the functional roles of representations, and how representations might be realized in the brain. We argue that there’s work to be done to identify a distinctively mental kind of representation. We close by sketching a way forward for the project of naturalizing intentionality. This will not be achieved simply by ascribing the content of mental states to generic neural representations, but by identifying specific neural representations that explain the puzzling intentional properties of mental states. (shrink)

The minimally conscious sta te (MCS) is usually ascribed when a patientwith brain damage exhibits obser vable volitional behaviors that predict recovery ofcognitive funct ions. Nevertheless, a patient with brain damage who lacks motorcapacit y might nonetheless be in MCS. For this reason, some clinicians use neuralsignals as a communicative means for MCS ascription. For instance, a vegetativestate patient is diagnosed with MCS if activity in the motor area is observed whenthe instruction to imagine wiggling toes is given. The validi (...) ty of using neuralsignals in ascribing MCS requires a special sort of inference. That is, no-reportparadigmatic assessments must have inductively strong ways of inferring a pur-ported informationa l content from the observed neural signal that grounds the factthat the patient has top-down cognitive control (or residual volition). Shannon’smathemat ical theory of communication and Bayes’ theorem reveals the formalstructure of neural communication. On the basis of relevant data from the neuro-science literature, I conclude that the formal structure combined with the data showsthat neural signals can be used as a communicative means for operational diagnosticcriteria for MCS ascription. (shrink)

The debate between the amodal and the grounded views of cognition seems to be stuck. Their only substantial disagreement is about the vehicle or format of concepts. Amodal theorists reject the grounded claim that concepts are couched in the same modality-specific format as representations in sensory systems. The problem is that there is no clear characterization of format or its neural correlate. In order to make the disagreement empirically meaningful and move forward in the discussion we need a neurocognitive criterion (...) for representational format. I argue that efficient coding models in computational neuroscience can be used to characterize modal codes: These are codes which satisfy special informational demands imposed by sensory tasks. Additionally, I examine recent studies on neural coding and argue that although they do not provide conclusive evidence for either the grounded or the amodal views, they can be used to determine what predictions these approaches can make and what experimental and theoretical developments would be required to settle the debate. (shrink)

It has been argued that the approximate number system constitutes a problem for the grounded approach to cognition because it implies that some conceptual tasks are performed by non-perceptual systems. The ANS is considered non-perceptual mainly because it processes stimuli from different modalities. Jones has recently argued that this system has many features which are characteristic of sensory systems. Additionally, he affirms that traditional sensory systems also process inputs from different modalities. This suggests that the ANS is a perceptual system (...) and therefore it is not problematic for the grounded view. In this paper, I defend the amodal approach to the ANS against these two arguments. In the first place, perceptual systems do not possess the properties attributed to the ANS and therefore these properties do not imply that the ANS is perceptual. In the second place, I will propose that a sensory system only needs to be dedicated to process modality-specific information, which is consistent with responding to inputs from different modalities. I argue that the cross-modal responses exhibited by traditional sensory systems are consistent with modality-specific information whereas some responses exhibited by the ANS are not. (shrink)

This paper engages critically with anti-representationalist arguments pressed by prominent enactivists and their allies. The arguments in question are meant to show that the “as-such” and “job-description” problems constitute insurmountable challenges to causal-informational theories of mental content. In response to these challenges, a positive account of what makes a physical or computational structure a mental representation is proposed; the positive account is inspired partly by Dretske’s views about content and partly by the role of mental representations in contemporary cognitive scientific (...) modeling. (shrink)

Half and whole articulate an always-conserved circle. Explaining symbols. Symbolic representation as a noun. Symbolic representation as a verb. (Circle as a noun and-or verb.).

Recently, a number of neuroscientists and philosophers have taken the so-called predictive coding approach to support a form of radical neuro-representationalism, according to which the content of our conscious experiences is a neural construct, a brain-generated simulation. There is remarkable similarity between this account and ideas found in and developed by German neo-Kantians in the mid-nineteenth century. Some of the neo-Kantians eventually came to have doubts about the cogency and internal consistency of the representationalist framework they were operating within. In (...) this paper, I will first argue that some of these concerns ought to be taken seriously by contemporary proponents of predictive coding. After having done so, I will turn to phenomenology. As we shall see, Husserl’s endorsement of transcendental idealism was partially motivated by his rejection of representationalism and phenomenalism and by his attempt to safeguard the objectivity of the world of experience. This confronts us with an intriguing question. Which position is best able to accommodate our natural inclination for realism: Contemporary neuro-representationalism or Husserl’s transcendental idealism? (shrink)

Essay Review of Andy Clark's 'Surfing Uncertainty: Prediction, Action, and the Embodied Brain'.

This paper centers around the notion that internal, mental representations are grounded in structural similarity, i.e., that they are so-called S-representations. We show how S-representations may be causally relevant and argue that they are distinct from mere detectors. First, using the neomechanist theory of explanation and the interventionist account of causal relevance, we provide a precise interpretation of the claim that in S-representations, structural similarity serves as a “fuel of success”, i.e., a relation that is exploitable for the representation using (...) system. Then, we discuss crucial differences between S-representations and indicators or detectors, showing that—contrary to claims made in the literature—there is an important theoretical distinction to be drawn between the two. (shrink)

I argue that there are no plausible non-representational explanations of episodes of hallucination. To make the discussion more specific, I focus on visual hallucinations in Charles Bonnet syndrome. I claim that the character of such hallucinatory experiences cannot be explained away non-representationally, for they cannot be taken as simple failures of cognizing or as failures of contact with external reality—such failures being the only genuinely non-representational explanations of hallucinations and cognitive errors in general. I briefly introduce a recent computational model (...) of hallucination, which relies on generative models in the brain, and argue that the model is a prime example of a representational explanation referring to representational mechanisms. The notion of the representational mechanism is elucidated, and it is argued that hallucinations—and other kinds of representations—cannot be exorcised from the cognitive sciences. (shrink)

This article presents and discusses one of the most prominent inferential strategies currently employed in cognitive neuropsychology, namely, reverse inference. Simply put, this is the practice of inferring, in the context of experimental tasks, the engagement of cognitive processes from locations or patterns of neural activation. This technique is notoriously controversial because, critics argue, it presupposes the problematic assumption that neural areas are functionally selective. We proceed as follows. We begin by introducing the basic structure of traditional “location-based” reverse inference (...) and discuss the influential lack of selectivity objection. Next, we rehearse various ways of responding to this challenge and provide some reasons for cautious optimism. The second part of the essay presents a more recent development: “pattern-decoding reverse inference”. This inferential strategy, we maintain, provides an even more convincing response to the lack of selectivity charge. Due to this and other methodological advantages, it is now a prominent component in the toolbox of cognitive neuropsychology. Finally, we conclude by drawing some implications for philosophy of science and philosophy of mind. (shrink)

I believe that the Buddhist paradigm of the phenomenal world—particularly, the Buddhist assertion that the phenomenal world is not as it appears—is supported by a scientific analysis of perception. When we consider carefully the basics of human perception, as understood by modern science, it becomes clear that phenomenal events are not represented as they truly are. This infidelity of information transfer from external phenomena to personal experience is consistent with the Buddhist view of the world as 'illusory'. Further, I would (...) argue that the creation of an illusory external world by our sensory instrumentation is compatible with the Buddhist doctrine of the non-duality of perception and perceiver. (shrink)

In this short paper I critically analyze Marc Leman’s embodied approach to musical meaning and representation, suggesting that its explanatory value is not sufficient in order to be a good alternative for theories encompassing the concept of representation.

First of all, we would like to gratefully thank all commentators for the attention and effort they have put into reading and responding to our review paper [this issue] and for useful observations that suggest novel applications for our framework. We understand and accept that some of our claims might appear controversial and raise skepticism, because the overall neural framework we have proposed is difficult to frame in established categories, given its strong multidisciplinary character. To make an example, Elsevier is (...) publishing the British Neuroscience Association (BNA) 2017 Special Issue Collection. However, our paper could not fully fit in any of their Special Issues—attention, motivation, behavior; sensory and motor systems; novel treatments and translational neuroscience; genetics and epigenetics; learning and memory; neurodegenerative disorders and ageing; developmental neuroscience; neuronal, glial and cellular mechanisms; neuroendocrine and autonomic nervous systems; psychiatry and mental health; methods and techniques. Perhaps because our paper was mathematically, physically, biologically (neuroscientifically), and phenomenologically motivated from the start? Nevertheless, venturing in novel, fresh, testable proposals is badly needed in contemporary neuroscience, so to break into “the utter darkness of the inner mechanism of psychic acts… during the production of the concomitant phenomena of perception and thought, namely, feelings, consciousness and volition”—as Cajal had already observed in his opus magnus ‘Textura’. But as he soberly confessed: “This ideal is still very distant” (Ramon y Cajal, 1899-1904, p. 1,141). In the pursuit of that very ideal, neuroscience and psychology have had, and continue to have, a plethora of movements and schools of thought: behaviorism, cognitivism, neural Darwinism, social constructivism, Bayesian optimization...In our paper, we propose to go a step further, via the notion of topodynamics, towards “projectionism.” In what follows, trying to elucidate the main features of this Emperor’s new clothing, we proceed with the responses to the comments received. (shrink)

The goal of this short chapter, aimed at philosophers, is to provide an overview and brief explanation of some central concepts involved in predictive processing (PP). Even those who consider themselves experts on the topic may find it helpful to see how the central terms are used in this collection. To keep things simple, we will first informally define a set of features important to predictive processing, supplemented by some short explanations and an alphabetic glossary. -/- The features described here (...) are not shared in all PP accounts. Some may not be necessary for an individual model; others may be contested. Indeed, not even all authors of this collection will accept all of them. To make this transparent, we have encouraged contributors to indicate briefly which of the features are necessary to support the arguments they provide, and which (if any) are incompatible with their account. For the sake of clarity, we provide the complete list here, very roughly ordered by how central we take them to be for “Vanilla PP” (i.e., a formulation of predictive processing that will probably be accepted by most researchers working on this topic). More detailed explanations will be given below. Note that these features do not specify individually necessary and jointly sufficient conditions for the application of the concept of “predictive processing”. All we currently have is a semantic cluster, with perhaps some overlapping sets of jointly sufficient criteria. The framework is still developing, and it is difficult, maybe impossible, to provide theory-neutral explanations of all PP ideas without already introducing strong background assumptions. (shrink)

The idea that only complex brains can possess genuine representations is an important element in mainstream philosophical thinking. An alternative view, which I label ‘liberal representationalism’, holds that we should accept the existence of many more full-blown representations, from activity in retinal ganglion cells to the neural states produced by innate releasing mechanisms in cognitively unsophisticated organisms. A promising way of supporting liberal representationalism is to show it to be a consequence of our best naturalistic theories of representation. However, several (...) philosophers and scientists have recently argued against this strategy. In the paper I counter these objections in defense of liberal representationalism. (shrink)

Naturalistic theories of representation seek to specify the conditions that must be met for an entity to represent another entity. Although these approaches have been relatively successful in certain areas, such as communication theory or genetics, many doubt that they can be employed to naturalize complex cognitive representations. In this essay I identify some of the difficulties for developing a teleosemantic theory of cognitive representations and provide a strategy for accommodating them: to look into models of signaling in evolutionary game (...) theory. I show how these models can be used to formulate teleosemantics and expand it in new directions. (shrink)

According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in (...) the sense that it postulates that our cognitive contact with the world is mediated by internal representations. However, the exact sense in which PCT is representational remains unclear; neither is it clear that it deserves such status—that is, whether it really invokes structures that are truly and nontrivially representational in nature. In the present article, I argue that the representational pretensions of PCT are completely justified. This is because the theory postulates cognitive structures—namely action-guiding, detachable, structural models that afford representational error detection—that play genuinely representational functions within the cognitive system. (shrink)