Partendo dalle definizioni che Ricoeur e Merleau-Ponty assegnano al concetto di filosofi a, è mia intenzione mostrare come non una metafisica tradizionalmente intesa, quanto un ideale metafisico insito in una teoria filosofica della conoscenza appaia e sia necessario ai fini dell’investigazione dell’esperienza. Ritengo che la dialettica tra trascendenza ed immanenza della verità nella storia, nonostante le diverse declinazioni dovute agli interessi dei due pensatori, possa contribuire a rendere un’immagine unitaria e, a più riprese, interdipendente di Ricoeur da Merleau-Ponty e di (...) quest’ultimo alla luce della revisione ermeneutica operata all’interno della fenomenologia dal filosofo di Valence.En partant des définitions que Ricoeur et Merleau-Ponty donnent du concept de philosophie, c’est mon intention de montrer comment non pas une métaphysique au sens traditionnel, mais un idéal métaphysique logé dans une théorie philosophique de la connaissance apparaît et est nécessaire dans la perspective d’une investigation de l’expérience. Je soutiens que la dialectique entre transcendance et immanence de la vérité dans l’histoire, quelles que soient les différentes déclinaisons qu’elle connaît dans les intérêts des deux penseurs, peut contribuer à donner une image unitaire et, à plusieurs reprises, à montrer une interdépendance de Ricoeur à l’égard de Merleau-Ponty et de ce dernier à l’égard de la révision herméneutique opérée à l’intérieur de la phénoménologie par le philosophe de Valence.By starting from the definitions that Ricoeur and Merleau-Ponty give to the concept of philosophy, I intend to show how a metaphysical ideal lodged in a philosophical theory of knowledge, and not a metaphysics in the traditional sense, appears and is necessary when viewed from the perspective of experience. I hold that the dialectic between transcendence and immanence of the truth in history, despite the difference of interest in how it is developed by the two thinkers, can contribute to the formation of an unified image and, in several ways, to showing an interdependence of Ricoeur in relation to Merleau-Ponty and of Merleau-Ponty in relation to the hermeneutical revision effected within phenomenology by the philosopher from Valence. (shrink)

Literature on consumers’ ethical decision making is rooted in a rationalist perspective that emphasizes the role of moral reasoning. However, the view of ethical consumption as a thorough rational and conscious process fails to capture important elements of human cognition, such as emotions and intuitions. Based on moral psychology and microsociology, this paper proposes a holistic and integrated framework showing how emotive and intuitive information processing may foster ethical consumption at individual and social levels. The model builds on social intuitionism (...) to show how consumers’ a priori affect-laden intuitive moral judgments impact their post hoc reflective moral reasoning. Symbolic interactionism is used to interpret consumers as interdependent and socially embedded agents that self-construct their social identity through interactions with other consumers. The proposed social intuitionist framework of consumers’ ethical decision making shows that other-oriented moral emotions—such as elevation, gratitude, and empathy—interact with persuasion and social influence in ethical consumption. Consequently, moral emotions and intuition drive interpersonal persuasion among ethical consumers. Theoretical propositions and implications for consumer ethics theory and practice are discussed. (shrink)

Bayesian cognitive science is a research programme that relies on modelling resources from Bayesian statistics for studying and understanding mind, brain, and behaviour. Conceiving of mental capacities as computing solutions to inductive problems, Bayesian cognitive scientists develop probabilistic models of mental capacities and evaluate their adequacy based on behavioural and neural data generated by humans (or other cognitive agents) performing a pertinent task. The overarching goal is to identify the mathematical principles, algorithmic procedures, and causal mechanisms that enable cognitive agents (...) to take uncertainty into account and weigh it appropriately in producing adaptive behaviour. -/- The appeal of Bayesian cognitive science derives from its transparency, normativity, and unifying power. Resources from Bayesian statistics allow cognitive scientists to characterise transparently, in terms of random variables and probabilistic dependencies between them, the inductive problems that many mental capacities are presumed to solve. Given this characterisation, researchers can define an upper bound on one’s performance on that problem and use it as a benchmark for interpreting experimental results, formulating hypotheses about why and when deviations from optimal performance should be expected, and seeking explanations of mental capacities within one encompassing theoretical framework. -/- Although critics question the testability, explanatory power, and plausibility of Bayesian models of mental capacities, Bayesian cognitive science has proved itself to be an incredibly fruitful research programme. Fuelled by empirical and theoretical results from psychology, neuroscience, philosophy, computer science, artificial intelligence, and evolution, Bayesian cognitive science has: advanced our understanding of why cognitive systems should keep track of uncertainty and use it to facilitate adaptive behaviour; clarified how the brain might encode information about the uncertainty of its stimuli and perform computations with probability distributions; and crystallised the insight that cognitive agents’ management of uncertainty might be grounded in predictive processes aimed at avoiding surprising exchanges with the environment. (shrink)

Recent theories on cognitive science have stressed the significance of moral intuition as a counter to and complementary part of moral reasoning in decision making. Thus, the aim of this paper is to create an integrated framework that can account for both intuitive and reflective cognitive processes, in order to explore the antecedents of ethical decision making. To do that, we build on Scholasticism, an important medieval school of thought from which descends the main pillars of the modern Catholic social (...) doctrine. Particularly, the focus will be on the scholastic concept of synderesis, which is an innate human faculty that constantly inclines decision makers toward universal moral principles. Managerial implications are discussed, stressing how a rediscovery of decision makers’ intuitive moral judgments could be relevant in the reflective thinking practice of managers’ ethical reasoning, thus saving them from rational insensitivity to ethical dilemmas. (shrink)

According to the free energy principle, life is an “inevitable and emergent property of any random dynamical system at non-equilibrium steady state that possesses a Markov blanket” :20130475, 2013). Formulating a principle for the life sciences in terms of concepts from statistical physics, such as random dynamical system, non-equilibrium steady state and ergodicity, places substantial constraints on the theoretical and empirical study of biological systems. Thus far, however, the physics foundations of the free energy principle have received hardly any attention. (...) Here, we start to fill this gap and analyse some of the challenges raised by applications of statistical physics for modelling biological targets. Based on our analysis, we conclude that model-building grounded in the free energy principle exacerbates a trade-off between generality and realism, because of a fundamental mismatch between its physics assumptions and the properties of actual biological targets. (shrink)

According to a growing trend in theoretical neuroscience, the human perceptual system is akin to a Bayesian machine. The aim of this article is to clearly articulate the claims that perception can be considered Bayesian inference and that the brain can be considered a Bayesian machine, some of the epistemological challenges to these claims; and some of the implications of these claims. We address two questions: (i) How are Bayesian models used in theoretical neuroscience? (ii) From the use of Bayesian (...) models in theoretical neuroscience, have we learned or can we hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine? From actual practice in theoretical neuroscience, we argue for three claims. First, currently Bayesian models do not provide mechanistic explanations; instead they are useful devices for predicting and systematizing observational statements about people's performances in a variety of perceptual tasks. That is, currently we should have an instrumentalist attitude towards Bayesian models in neuroscience. Second, the inference typically drawn from Bayesian behavioural performance in a variety of perceptual tasks to underlying Bayesian mechanisms should be understood within the three-level framework laid out by David Marr ( [1982] ). Third, we can hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine to the extent that Bayesian models will prove successful in yielding secure and informative predictions of both subjects' perceptual performance and features of the underlying neural mechanisms. (shrink)

Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this paper, we argue that this realist attitude is unwarranted. The Bayesian research program in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach (...) is overall better supported by the empirical evidence. So, to develop philosophical theories of mind on the basis of a realist interpretation of results from Bayesian cognitive science is unwarranted. Naturalistic philosophers of mind should instead adopt an anti-realist attitude towards these results and remain agnostic as to whether Bayesian models are true. For continuing on with an exclusive focus and praise of Bayes within debates about the predictive processing theory will impede progress in philosophical understanding of scientific practice in computational cognitive science as well as of the architecture of the mind. (shrink)

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

Courtesy of its free energy formulation, the hierarchical predictive processing theory of the brain (PTB) is often claimed to be a grand unifying theory. To test this claim, we examine a central case: activity of mesocorticolimbic dopaminergic (DA) systems. After reviewing the three most prominent hypotheses of DA activity—the anhedonia, incentive salience, and reward prediction error hypotheses—we conclude that the evidence currently vindicates explanatory pluralism. This vindication implies that the grand unifying claims of advocates of PTB are unwarranted. More generally, (...) we suggest that the form of scientific progress in the cognitive sciences is unlikely to be a single overarching grand unifying theory. (shrink)

Diese Studie der Deskription bei Franz Brentano lässt dessen Philosophie als ein «Programm der Deskription» erscheinen, das einen spezifischen Beitrag zur Gottesfrage leistet. Im Gegensatz zur scholastischen Tradition stellt er diese Frage auf sprachlicher Ebene und sucht dadurch erkenntnistheoretisch-metaphysische Engführungen zu überwinden. Er betont die deskriptive (nicht physikalische oder metaphysische) Bedeutung der Kausalität in ihrer Zeitgebundenheit und zeigt, dass die Existenz Gottes zeitlich bestimmt werden muss: Nur so ist eine sinnvolle Rede von Gott möglich. Brentanos Denken wurde in der Theologie (...) kaum wahrgenommen, aber die deskriptive Lösung des Problems von «esse et essentia», die Arten der Zeitlichkeit, die Betrachtung von Analogielehre und Univozität sind richtungsweisend. (shrink)

Can rational agents coordinate in simultaneous interactions? According to standard game theory they cannot, even if there is a uniquely best way of doing so. To solve this problem we propose an argument in favor of ‘belief-less reasoning’, a mode of inference that leads to converge on the optimal solution ignoring the beliefs of the other players. We argue that belief-less reasoning is supported by a commonsensical Principle of Relevant Information that every theory of rational decision must satisfy. We show (...) that this principle can be used to justify (some versions of) team reasoning, as well as other schemes of practical reasoning that do not involve sophisticated meta-representation. (shrink)

This paper brings together results from the philosophy and the psychology of explanation to argue that there are multiple concepts of explanation in human psychology. Specifically, it is shown that pluralism about explanation coheres with the multiplicity of models of explanation available in the philosophy of science, and it is supported by evidence from the psychology of explanatory judgment. Focusing on the case of a norm of explanatory power, the paper concludes by responding to the worry that if there is (...) a plurality of concepts of explanation, one will not be able to normatively evaluate what counts as good explanation. (shrink)

Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates (...) this claim and argues that the main challenge this era is facing is not the lack of biological realism. The challenge lies in identifying general neurocomputational principles for the design of artificial systems, which could display the robust flexibility characteristic of biological intelligence. (shrink)

In this volume, a range of high-profile researchers in philosophy of mind, philosophy of cognitive science, and empirical cognitive science, critically engage with Clark's work across the themes of: Extended, Embodied, Embedded, Enactive, and Affective Minds; Natural Born Cyborgs; and Perception, Action, and Prediction. Daniel Dennett provides a foreword on the significance of Clark's work, and Clark replies to each section of the book, thus advancing current literature with original contributions that will form the basis for new discussions, debates and (...) directions in the discipline. (shrink)

Aboitiz et al. suggest that the mammalian isocortex is derived from the dorsal cortex of reptiles and birds, and that there has been a major divergence in the connectivity patterns (and hence function) of the mammalian and reptilian/avian hippocampus. There is considerable evidence to suggest, however, that the avian hippocampus serves the exact same function as the mammalian hippocampus.

According to the reward-prediction error hypothesis of dopamine, the phasic activity of dopaminergic neurons in the midbrain signals a discrepancy between the predicted and currently experienced reward of a particular event. It can be claimed that this hypothesis is deep, elegant and beautiful, representing one of the largest successes of computational neuroscience. This paper examines this claim, making two contributions to existing literature. First, it draws a comprehensive historical account of the main steps that led to the formulation and subsequent (...) success of the RPEH. Second, in light of this historical account, it explains in which sense the RPEH is explanatory and under which conditions it can be justifiably deemed deeper than the incentive salience hypothesis of dopamine, which is arguably the most prominent contemporary alternative to the RPEH. (shrink)

In this paper, I examine Reinforcement Learning modelling practice in psychiatry, in the context of alcohol use disorders. I argue that the epistemic roles RL currently plays in the development of psychiatric classification and search for explanations of clinically relevant phenomena are best appreciated in terms of Chang’s account of epistemic iteration, and by distinguishing mechanistic and aetiological modes of computational explanation.

Medical decision-making on behalf of intellectually and developmentally disabled (IDD) patients amounts to a critical challenge, one which has been widely discussed by bioethicists, medical, and le...

Veissière and collaborators ground their account of culture and social norms in the free-energy principle, which postulates that the utility of an outcome is equivalent to its probability. This equivalence would mean that their account entails that complying with social norms has always adaptive value. But, this is false, because many social norms are obviously maladaptive.

Bazzocchi disposes the text of the Tractatus in a user-friendly manner, exactly as Wittgenstein's decimals advise. This discloses the logical form of the book by distinct reading units, linked into a fashioned hierarchical tree. The text becomes much clearer and every reader can enjoy, finally, its formal and literary qualities.

Bruineberg and collaborators distinguish three philosophical positions about the status of Markov blankets in the context of active inference modelling, namely: literalism, realism, and instrumentalism. They criticize the first two positions and suggest that instrumentalism is “less problematic but also less interesting” (sect. 6.1.2, para. 5) Here, I sketch how literalists and realists might reply to Bruineberg et al.'s criticisms, and I explain why instrumentalism is more interesting and contentious than what Bruineberg and collaborators suggest.

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature in the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by the prior credibility of a potential explanation, the causal framing used to describe the explanation, the generalizability of the explanation, and its statistical relevance for the evidence. Collectively, (...) the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations were not susceptible to causal framing effects. Instead, highly credible hypotheses were sensitive to the effects of factors which are usually considered relevant from a normative point of view: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they illuminate the close relationship between prior beliefs and explanatory power. Third, they clarify the relationship between abductive and probabilistic reasoning. (shrink)

The present work refers to the doctorship research that implemented the Free-Expression Painting Studio technique to assist university students who had suicidal ideations or attempts. This technique was developed in France by the psychologist Michel Ternoy, based on Minkowski’s structural-phenomenon analysis method. A group session will be presented and discussed from Michel Henry’s phenomenology of life. Psychology and phenomenology can create spaces for belonging and support, which allow the transformation of suffering from experiences in the community. The Painting Studio makes (...) it possible to experience the affection of the other as a potential of one’s own possibilities, mobilizing the affective dialectical relationship, through which one can go from unbearable suffering to original fruition. We seek to show that art can be part of the therapeutic process as an alternative to the passage to the act of suicide before it becomes unbearable. (shrink)

Where does a probabilistic language-of-thought (PLoT) come from? How can we learn new concepts based on probabilistic inferences operating on a PLoT? Here, I explore these questions, sketching a traditional circularity objection to LoT and canvassing various approaches to addressing it. I conclude that PLoT-based cognitive architectures can support genuine concept learning; but, currently, it is unclear that they enjoy more explanatory breadth in relation to concept learning than alternative architectures that do not posit any LoT.

In this paper we aim to find a definition of virtual which fits the latest developments of digital technology, but also applies to the analog world. We consider the virtual as related to immanence, taking inspiration from Deleuze’s reading of Bergson and Merleau-Ponty’s last work. We first analyze Deleuze’s idea of immanence, from which virtuality emerges, then we focus on Merleau-Ponty’s concept of flesh and its virtual center. We argue that both philosophers see immanence as a dynamic medium of virtuality, (...) overcoming the traditional concept of substance and theorizing a deep intertwining of bodies and technology. Our analysis shows that the virtual is defined by the following features: it implies an epistemological and ontological monism, relationality, and entanglement with reality. The virtual clearly emerges in digital technologies, but also belongs to analog reality, as a general condition for our knowing and being in the world as such. (shrink)

Letheby’s "Philosophy of Psychedelics" relies on Predictive Processing to try and find unifying explanations relevant to understanding how serotonergic psychedelics work in psychiatric therapy, what subjective experiences are associated with their use and whether such experiences are epistemically defective. But if Predictive Processing lacks genuinely explanatory unifying power, Letheby’s account of psychedelic therapy risks being unwarranted. In this commentary, I motivate this worry and sketch an alternative interpretation of psychedelic therapy within the Reinforcement Learning framework.

What is the relationship between the concepts of the predictive processing theory of brain functioning and the everyday concepts with which people conduct and explain their mental lives? To answer this question, we focus on predictive processing explanations of mental disorder that appeal to false inference. After distinguishing two concepts of false inference, we survey four ways of understanding the relationship between explanations of mental phenomena at the personal and sub-personal level. We then argue that if predictive processing accurately accounts (...) for psychological and socio-cultural dynamics, then personal and sub-personal concepts must display a looping relationship that can impact the nature of at least some mental phenomena. In particular, explaining the phenomenon of delusion in terms of the sub-personal concept of false inference should change the nature of delusional experiences themselves. (shrink)

It is often claimed that the greatest value of the Bayesian framework in cognitive science consists in its unifying power. Several Bayesian cognitive scientists assume that unification is obviously linked to explanatory power. But this link is not obvious, as unification in science is a heterogeneous notion, which may have little to do with explanation. While a crucial feature of most adequate explanations in cognitive science is that they reveal aspects of the causal mechanism that produces the phenomenon to be (...) explained, the kind of unification afforded by the Bayesian framework to cognitive science does not necessarily reveal aspects of a mechanism. Bayesian unification, nonetheless, can place fruitful constraints on causal–mechanical explanation. 1 Introduction2 What a Great Many Phenomena Bayesian Decision Theory Can Model3 The Case of Information Integration4 How Do Bayesian Models Unify?5 Bayesian Unification: What Constraints Are There on Mechanistic Explanation?5.1 Unification constrains mechanism discovery5.2 Unification constrains the identification of relevant mechanistic factors5.3 Unification constrains confirmation of competitive mechanistic models6 ConclusionAppendix. (shrink)

The Cognitive Reserve (CR) hypothesis suggests that the brain actively attempts to cope with neural damages by using pre-existing cognitive processing approaches or by enlisting compensatory approaches. This would allow an individual with high CR to better cope with aging than an individual with lower CR. Many of the proxies used to assess CR indirectly refer to the flexibility of thought. The present paper aims at directly exploring the relationships between CR and creativity, a skill that includes flexible thinking. We (...) tested a sample of 72 adults (aged between 45 and 78) assessing both their level of CR and their creativity. To evaluate CR we used the proxies commonly used in literature, namely, three subtests from the WAIS (vocabulary, similarities, and digit span) and the years of education. We also used an ad-hoc test asking people to report how frequently they tend to perform activities that are believed to increase CR. We used verbal creativity tasks (alternative uses and generation of acronyms) to assess individual levels of creativity. We asked participants to describe their main occupation (present or past) and coded each occupation as creative or not creative. Results (controlling for age-related differences) showed that scores from the WAIS correlated positively with creativity performance, even though correlations varied across the subtests. Focusing on the frequency and type of activities that people perform, and comparing individuals who have or had a creative job to those with a routine job, a clear relationship between creativity and CR emerged. This effect was more relevant than the level of job complexity. Implications for the study of CR and aging are discussed. (shrink)

A widely shared view in the cognitive sciences is that discovering and assessing explanations of cognitive phenomena whose production involves uncertainty should be done in a Bayesian framework. One assumption supporting this modelling choice is that Bayes provides the best approach for representing uncertainty. However, it is unclear that Bayes possesses special epistemic virtues over alternative modelling frameworks, since a systematic comparison has yet to be attempted. Currently, it is then premature to assert that cognitive phenomena involving uncertainty are best (...) explained within the Bayesian framework. As a forewarning, progress in cognitive science may be hindered if too many scientists continue to focus their efforts on Bayesian modelling, which risks to monopolize scientific resources that may be better allocated to alternative approaches. (shrink)

Can facts about subpersonal states and events be constitutively relevant to personal-level phenomena? And can knowledge of these facts inform explanations of personal-level phenomena? Some philosophers, like Jennifer Hornsby and John McDowell, argue for two negative answers whereby questions about persons and their behavior cannot be answered by using information from subpersonal psychology. Knowledge of subpersonal states and events cannot inform personal-level explanation such that they cast light on what constitutes persons’ behaviors. In this paper I argue against this position. (...) After having distinguished between enabling and constitutive relevance, I defend the claim that at least some facts about subpersonal states and events are constitutively relevant to some personal-level phenomenon, and therefore can, and sometimes should, inform personal-level explanations. I draw some of the possible consequences of my claim for our understanding of personal-level behavior by focusing on the phenomenon of addiction. (shrink)

Abductive reasoning assigns special status to the explanatory power of a hypothesis. But how do people make explanatory judgments? Our study clarifies this issue by asking: How does the explanatory power of a hypothesis cohere with other cognitive factors? How does probabilistic information affect explanatory judgments? In order to answer these questions, we conducted an experiment with 671 participants. Their task was to make judgments about a potentially explanatory hypothesis and its cognitive virtues. In the responses, we isolated three constructs: (...) Explanatory Value, Rational Acceptability, and Entailment. Explanatory judgments strongly cohered with judgments of causal relevance and with a sense of understanding. Furthermore, we found that Explanatory Value was sensitive to manipulations of statistical relevance relations between hypothesis and evidence, but not to explicit information about the prior probability of the hypothesis. These results indicate that probabilistic information about statistical relevance is a strong determinant of Explanatory Value. More generally, our study suggests that abductive and probabilistic reasoning are two distinct modes of inference. (shrink)