Marco Facchin

According to the extended cognition thesis, an agent’s cognitive system can sometimes include extracerebral components amongst its physical constituents. Here, we show that such a view of cognition has an unjustifiably anthropocentric focus, for it tends to depict cognitive extensions as a human-only affair. In contrast, we will argue that if human cognition extends, then the cognition of many non-human animals extends too, for many non-human animals rely on the same cognition-extending strategies humans rely on. To substantiate this claim, we will proceed as follows. First (Sect. 1), we will introduce the extended cognition thesis, exposing its anthropocentric bias. Then, we will show that humans and many non-human animals rely on the same cognition-extending strategies. To do so, we will discuss a variety of case studies, including “intrabodily” cognitive extensions such as the spinal cord (Sect. 2), the widespread reliance on epistemic actions to solve cognitive tasks (Sect. 3) and cases of animal cognitive offloading (Sect. 4). We’ll then allay some worries our claim might raise (Sect. 5) to then conclude the paper (Sect. 6).

Emoticons and facial emojis are ubiquitous in contemporary digital communication, where it has been proposed that they make up for the lack of social information from real faces. In this paper, I construe them as cultural artifacts that exploit the neurocognitive mechanisms for face perception. Building on a step-by-step comparison of psychological evidence on the perception of faces vis-à-vis the perception of emoticons/emojis, I assess to what extent they do effectively vicariate real faces with respect to the following four domains: (1) the expression of emotions, (2) the cultural norms for expressing emotions, (3) conveying non-affective social information, and (4) attention prioritization.

The mechanism underlying action potentials is routinely used to explicate the mechanistic model of explanation in the philosophy of science. However, characterisations of action potentials often fixate on neurons, mentioning plant cells in passing or ignoring them entirely. The plant sciences are also prone to neglecting non-neuronal action potentials and their role in plant biology. This oversight is significant because plant action potentials bear instructive similarities to those generated by neurons. This paper helps correct the imbalance in representations of action potentials by offering an overview of the mechanism for plant action potentials and highlighting their similarity to those in neurons. Furthermore, it affirms the role of plant action potentials in discovering the evolution and function of mechanisms of action potentials more broadly. We stress the potential of plants for producing generalisations about action potentials and the possible role of plants as experimental organisms.

Predictive coding – sometimes also known as ‘predictive processing’, ‘free energy minimisation’, or ‘prediction error minimisation’ – claims to offer a complete, unified theory of cognition that stretches all the way from cellular biology to phenomenology. However, the exact content of the view, and how it might achieve its ambitions, is not clear. This series of articles examines predictive coding and attempts to identify its key commitments and justification. The present article begins by focusing on possible confounds with predictive coding: claims that are often identified with predictive coding, but which are not predictive coding. These include the idea that the brain employs an efficient scheme for encoding its incoming sensory signals; that perceptual experience is shaped by prior beliefs; that cognition involves minimisation of prediction error; that the brain is a probabilistic inference engine; and that the brain learns and employs a generative model of the world. These ideas have garnered widespread support in modern cognitive neuroscience, but it is important not to conflate them with predictive coding.

Some proponents of structural representations (henceforth, structuralists) claim that no other theory of representation can legitimatize the explanatory appeals that cognitive science makes to mental content. Because other naturalistic approaches to representation purportedly posit an arbitrary relation between representing vehicles and representational content, these approaches must appeal to the role played by a representation, i.e., how it is used by the system in which it is embedded, to ground its content. This is in supposed contrast to structural representations, in which the relation of resemblance results in a non-arbitrary relationship between vehicles and content. Structuralists argue that, as a result, approaches that posit structural representations can, and alternative approaches cannot, explain how representational content can be causally relevant in the production of behavior. In this paper, I will argue that structural representations are susceptible to the very same critiques that proponents level against what they sometimes refer to as “use” theories. This, I contend, is not surprising given that a theory of structural representations is, in fact, just as much a use-theory as alternative approaches.

This paper develops a theory of analog representation. We first argue that the mark of the analog is to be found in the nature of a representational system’s interpretation function, rather than in its vehicles or contents alone. We then develop the rulebound structure theory of analog representation, according to which analog systems are those that use interpretive rules to map syntactic structural features onto semantic structural features. The theory involves three degree-theoretic measures that capture three independent ways in which a system can be more or less analog. We explain how our theory improves upon prior accounts of analog representation, provides plausible diagnoses for novel challenge cases, extends to hybrid systems that are partially analog and partially symbolic, and accounts for some of the advantages and disadvantages of representing analogically versus symbolically.

Computational physical systems may exhibit indeterminacy of computation (IC). Their identified physical dynamics may not suffice to select a unique computational profile. We consider this phenomenon from the point of view of cognitive science and examine how computational profiles of cognitive systems are identified and justified in practice, in the light of IC. To that end, we look at the literature on the underdetermination of theory by evidence and argue that the same devices that can be successfully employed to confirm physical hypotheses can also be used to rationally single out computational profiles, notwithstanding IC.

Extended cognition brings with it a particular phenomenology. It has been argued that when an artifact is integrated into an agent’s cognitive system, it becomes transparent in use to the cognizing subject. In this paper, I challenge some of the assumptions underlying how the transparency of artifacts is described in extended cognition theory. To this end, I offer two arguments. First, I make room for some forms of conscious thought and attention within extended cognitive routines, and I question the close association drawn between attention and effort. Second, I vindicate the importance of paying careful attention to individual differences and the diverse ways in which bodies and technologies can be experienced. I end by offering some hints toward an alternative, and more accurate, account of the phenomenology of extended cognition.

_Abstract_: Fueled by the rapid development of neuroscientific tools and techniques, some scholars consider the shift from traditional cognitive psychology toward cognitive neuroscience to be a _revolution_ (most notably Boone and Piccinini). However, the term “revolution” in philosophy of science can easily be construed as involving a paradigm shift in the sense of Kuhn’s _The Structure of Scientific Revolutions_. Is a Kuhnian account sound in the case at hand? To answer this question, we consider heuristic indicators of two features of paradigm shifts: the incommensurability of ontologies; and a gap between scientific communities. Based on our evidence, we argue that no revolution has occurred (at least, not yet). _Keywords_: Cognitive Neuroscience; Cognitive Psychology; Philosophy of Science; Thomas Kuhn; Scientometrics _La “rivoluzione delle neuroscienze cognitive” non è una rivoluzione (in senso kuhniano). Evidenze scientometriche _ _Riassunto_:_ _Complice il rapido sviluppo di strumenti e tecniche in neuroscienze, alcuni studiosi (in particolare Boone e Piccinini) intendono il passaggio dalla psicologia cognitiva classica alla neuroscienza cognitiva nei termini di una _rivoluzione_. Tuttavia, il termine ‘rivoluzione’ in filosofia della scienza è strettamente associato alla nozione di successione di paradigmi esposta da Kuhn ne _La struttura delle rivoluzioni scientifiche_. Obiettivo di questo lavoro è capire se effettivamente la concezione kuhniana offra una corretta descrizione di questa dinamica storica. In particolare, prenderemo in esame due indicatori euristici delle rivoluzioni kuhniane: l’incommensurabilità ontologica trai due paradigmi e la diversa composizione demografica delle comunità scientifiche. Sulla base delle evidenze scientometriche che prenderemo in esame, affermeremo che non è avvenuta nessuna rivoluzione (almeno per ora). _Parole chiave_: Neuroscienze cognitive; Psicologia cognitiva; Filosofia della scienza; Thomas Kuhn; Scientometria.

Daniel Dennett's distinction between personal and subpersonal explanations was fundamental in establishing the philosophical foundations of cognitive science. Since it was first introduced in 1969, the personal/subpersonal distinction has been adapted to fit different approaches to the mind. In one example of this, the ‘Pittsburgh school’ of philosophers attempted to map Dennett's distinction onto their own distinction between the ‘space of reasons’ and the ‘space of causes’. A second example can be found in much contemporary philosophy of psychology, where Dennett's distinction has been presumed to be equivalent to Stephen Stich's distinction between doxastic and subdoxastic states. Both these interpretations of the personal/subpersonal distinction, and also Dennett's own philosophical views of the mind, go beyond the personal/subpersonal distinction itself. They each involve supplementing the distinction between personal and subpersonal explanations with metaphysical claims about the relationship between the two kinds of explanation and the entities they posit

Whilst the topic of representations is one of the key topics in philosophy of mind, it has only occasionally been noted that representations and representational features may be gradual. Apart from vague allusions, little has been said on what representational gradation amounts to and why it could be explanatorily useful. The aim of this paper is to provide a novel take on gradation of representational features within the neuroscientific framework of predictive processing. More specifically, we provide a gradual account of two features of structural representations: structural similarity and decoupling. We argue that structural similarity can be analysed in terms of two dimensions: number of preserved relations and state space granularity. Both dimensions can take on different values and hence render structural similarity gradual. We further argue that decoupling is gradual in two ways. First, we show that different brain areas are involved in decoupled cognitive processes to a greater or lesser degree depending on the cause (internal or external) of their activity. Second, and more importantly, we show that the degree of decoupling can be further regulated in some brain areas through precision weighting of prediction error. We lastly argue that gradation of decoupling (via precision weighting) and gradation of structural similarity (via state space granularity) are conducive to behavioural success.

Pain is often used as the paradigmatic example of a phenomenal kind with a phenomenal quality common and unique to its instantiations. Philosophers have intensely discussed the relation between the subjective feeling, which unites pains and distinguishes them from other experiences, and the phenomenal properties of sensory, affective, and evaluative character along which pains typically vary. At the center of this discussion is the question whether the phenomenal properties prove necessary and/or sufficient for pain. In the empirical literature, sensory, affective, and evaluative properties have played a decisive role in the investigation of psychophysical correspondence and clinical diagnostics. This paper addresses the outlined philosophical and empirical issues from a new perspective by constructing a multidimensional phenomenal space for pain. First, the paper will construe the phenomenal properties of pains in terms of a property space whose structure reflects phenomenal similarities and dissimilarities by means of spatial distance. Second, philosophical debates on necessary and sufficient properties are reconsidered in terms of whether there is a phenomenal space formed of dimensions along which all and only pains vary. It is concluded that there is no space of this kind and, thus, that pain constitutes a primitive phenomenal kind that cannot be analyzed entirely in terms of its varying phenomenal properties. Third, the paper addresses the utility of continued reference to pain and its phenomenal properties in philosophical and scientific discourses. It is argued that numerous insights into the phenomenal structure of pain can be gained that have thus far received insufficient attention.

In their attempt to connect the workings of the human mind with their neural realizers, cognitive neuroscientists often bracket out individual differences to build a single, abstract model that purportedly represents (almost) every human being’s brain. In this paper I first examine the rationale behind this model, which I call ‘Platonic Brain Model’. Then I argue that it is to be surpassed in favor of multiple models allowing for patterned inter-individual differences. I introduce the debate on legitimate (and illegitimate) ways of mapping neural structures and cognitive functions, endorsing a view according to which function-structure mapping is context-sensitive. Building on the discussion of the ongoing debate on the function(s) of the so-called Fusiform “Face” Area, I show the necessity of indexing function-structure mappings to some populations of subjects, clustered on the basis of factors such as their expertise in a given domain.