In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue (...) that topological predictions can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone. (shrink)

Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function (e.g., Weiskopf, 2011). In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function (e.g., Piccinini & Craver, 2011; Povich, 2015). In this paper, I show how model-based cognitive neuroscience (MBCN) epitomizes the integrative mechanistic perspective (...) and concentrates the most revolutionary elements of the cognitive neuroscience revolution (Boone & Piccinini, 2016). I also show how the prominent subset account of functional realization supports the integrative mechanistic perspective I take on MBCN and use it to clarify the intralevel and interlevel components of integration. (shrink)

In this paper, findings from research in neuroscience of morality will be reviewed to consider the purposes of moral education. Particularly, I will focus on two main themes in neuroscience, novel neuroimaging and experimental investigations, and Bayesian learning mechanism. First, I will examine how neuroimaging and experimental studies contributed to our understanding of psychological mechanisms associated with moral functioning while addressing methodological concerns. Second, Bayesian learning mechanism will be introduced to acquire insights about how moral learning occurs in (...) human brains. Based on the reviewed neuroscientific research on morality, I will examine how evidence can support the model of moral education proposed by virtue ethics, Neo-Aristotelian moral philosophy in particular. Particularly, two main aims of virtue ethics-based moral education, the habituation of virtues and the cultivation of phronesis, will be discussed as the important purposes of moral education based on neuroscientific evidence. (shrink)

The central idea is that the cerebral cortex is a model building machine, where regularities in the world serve as templates for the models it builds. First it is shown how this idea can be naturalized, and how the representational contents of our internal models depend upon the evolutionarily endowed design principles of our model building machine. Current neuroscience suggests a powerful form that these design principles may take, allowing our brains to uncover deep structures of the world hidden (...) behind surface sensory stimulation, the individuals, kinds, and properties that form the objects of human perception and thought. It is then shown how this account solves various problems that arose for previous attempts at naturalizing intentionality, and also how it supports rather than undermines folk psychology. As in the parable of the blind men and the elephant, the seemingly unrelated pieces of earlier theories (information, causation, isomorphism, success, and teleology) emerge as different aspects of the evolved model-building mechanism that explains the intentional features of our kind of mind. (shrink)

Attempts to introduce Gestalt theory into the realm of visual neuroscience are discussed on both theoretical and experimental grounds. To define the framework in which these proposals can be defended, this paper outlines the characteristics of a standard model, which qualifies as a received view in the visual neurosciences, and of the research into natural images statistics. The objections to the standard model and the main questions of the natural images research are presented. On these grounds, this paper defends (...) the view that Gestalt psychology and experimental phenomenology provide a contribution to the research into perception by the construction of phenomenological models for an ecologically meaningful interpretation of the empirical evidence and the hypothetical constructs of the natural image research within the visual neuroscience. A formal framework for the phenomenological models is proposed, wherein Gestalt theoretical principles and empirical evidence are represented in terms of topological properties and relationships, which account for the order and structures that make the environment accessible to observers at a relevant behavioural level. It is finally argued that these models allow us to evaluate the principles and the empirical evidence of various natures which are integrated from different fields into the research into perception, and in particular into visual neurosciences. (shrink)

Neuroscientists have in recent years turned to building models that aim to generate predictions rather than explanations. This “predictive turn” has swept across domains including law, marketing, and neuropsychiatry. Yet the norms of prediction remain undertheorized relative to those of explanation. I examine two styles of predictive modeling and show how they exemplify the normative dynamics at work in prediction. I propose an account of how predictive models, conceived of as technological devices for aiding decision-making, can come to be adequate (...) for purposes that are defined by both their guiding research questions and their larger social context of application. (shrink)

The goals and tasks of neuroethics formulated by Farahany and Ramos (2020) link epistemological and methodological issues with ethical and social values. The authors refer simultaneously to the social significance and scientific reliability of the BRAIN Initiative. They openly argue that neuroethics should not only examine neuroscientific research in terms of “a rigorous, reproducible, and representative neuroscience research process” as well as “explore the unique nature of the study of the human brain through accurate and representative models of its (...) function and dysfunction”, but also its responsibilities or social consequences. In our commentary, we would like to concentrate on problem selection, which is shortly noticed by Farahany and Ramos, and by BRAIN Initiative’s Neuroethics Report itself. The document raises an important issue related to problem selection, which is strengthening or perpetuating existing prejudices and biases by choosing a research subject: “scientists are prompted to consider how the questions they choose to study in the laboratory might amplify existing biases.” This leads to several further problems: what constitutes bias?; how biases may be embedded in the selection of research programs?; is it possible to conduct completely unbiased research?; who should be a gatekeeper in the case of research that may amplify biases? We try to notice possible answers to these questions in the context of the research on differences (e.g., cognitive, medical, behavioral) between human populations. (shrink)

In this paper, I examined whether evidence from the neuroscience of morality supports the standard models of phronesis, i.e., Jubilee and Aretai Centre Models. The standard models explain phronesis as a multifaceted construct based on interaction and coordination among functional components. I reviewed recent neuroscience studies focusing on brain networks associated with morality and their connectivity to examine the validity of the models. Simultaneously, I discussed whether the evidence helps the models address challenges, particularly those from the phronesis (...) eliminativism. Neuroscientific evidence supported the importance of brain networks, i.e., the default mode, salience, and central executive functioning networks, in moral functioning in general. The findings favorably supported the multifaceted and integrative nature of phronesis proposed by the standard models. Finally, I considered how the two models could explain the mechanisms of phronesis more integratively based on neuroscientific findings. At the end of this paper, with the evidence, I proposed several practical ideas to promote the cultivation of phronesis, e.g., the consideration of coordination among components for moral functioning and the use of moral exemplars. (shrink)

As philosophical and scientific arguments for free will skepticism continue to gain traction, we are likely to see a fundamental shift in the way people think about free will and moral responsibility. Such shifts raise important practical and existential concerns: What if we came to disbelieve in free will? What would this mean for our interpersonal relationships, society, morality, meaning, and the law? What would it do to our standing as human beings? Would it cause nihilism and despair as some (...) maintain or would it rather have a humanizing effect on our practices and policies, freeing us from the negative effects of belief in free will? In this chapter we consider the practical implications of free will skepticism and argue that life without free will and basic desert moral responsibility would not be as destructive as many people believe. We argue that prospects of finding meaning in life or of sustaining good interpersonal relationships, for example, would not be threatened. On treatment of criminals, we argue that although retributivism and severe punishment, such as the death penalty, would be ruled out, preventive detention and rehabilitation programs would still be justified. While we will touch on all these issues below, our focus will be primarily on this last issue. -/- We begin in section I by considering two different routes to free will skepticism. The first denies the causal efficacy of the types of willing required for free will and receives its contemporary impetus from pioneering work in neuroscience by Benjamin Libet, Daniel Wegner, and John-Dylan Haynes. The second, which is more common in the philosophical literature, does not deny the causal efficacy of the will but instead claims that whether this causal efficacy is deterministic or indeterministic, it does not achieve the level of control to count as free will by the standards of the historical debate. We argue that while there are compelling objections to the first route—e.g., Al Mele (2009), Eddy Nahmias (2002, 2011), and Neil Levy (2005)—the second route to free will skepticism remains intact. In section II we argue that free will skepticism allows for a workable morality, and, rather than negatively impacting our personal relationships and meaning in life, may well improve our well-being and our relationships to others since it would tend to eradicate an often destructive form of moral anger. In section III we argue that free will skepticism allows for adequate ways of responding to criminal behavior—in particular, incapacitation, rehabilitation, and alternation of relevant social conditions—and that these methods are both morally justified and sufficient for good social policy. We present and defend our own preferred model for dealing with dangerous criminals, an incapacitation account built on the right to self-protection analogous to the justification for quarantine (see Pereboom 2001, 2013, 2014a; Caruso 2016a), and we respond to recent objections to it by Michael Corrado and John Lemos. (shrink)

Purpose – For half a century, neuroscientists have used Shannon Information Theory to calculate “information transmitted,” a hypothetical measure of how well neurons “discriminate” amongst stimuli. Neuroscientists’ computations, however, fail to meet even the technical requirements for credibility. Ultimately, the reasons must be conceptual. That conclusion is confirmed here, with crucial implications for neuroscience. The paper aims to discuss these issues. Design/methodology/approach – Shannon Information Theory depends upon a physical model, Shannon’s “general communication system.” Neuroscientists’ interpretation of that model (...) is scrutinized here. Findings – In Shannon’s system, a recipient receives a message composed of symbols. The symbols received, the symbols sent, and their hypothetical occurrence probabilities altogether allow calculation of “information transmitted.” Significantly, Shannon’s system’s “reception” (decoding) side physically mirrors its “transmission” (encoding) side. However, neurons lack the “reception” side; neuroscientists nonetheless insisted that decoding must happen. They turned to Homunculus, an internal humanoid who infers stimuli from neuronal firing. However, Homunculus must contain a Homunculus, and so on ad infinitum – unless it is super-human. But any need for Homunculi, as in “theories of consciousness,” is obviated if consciousness proves to be “emergent.” Research limitations/implications – Neuroscientists’ “information transmitted” indicates, at best, how well neuroscientists themselves can use neuronal firing to discriminate amongst the stimuli given to the research animal. Originality/value – A long-overdue examination unmasks a hidden element in neuroscientists’ use of Shannon Information Theory, namely, Homunculus. Almost 50 years’ worth of computations are recognized as irrelevant, mandating fresh approaches to understanding “discriminability.”. (shrink)

Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience and with them new understandings of the experimental practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to (...) substantiate these models are culled, and argue that the multiplicity of experimental protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of experimental practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)

Our philosophical understanding of mental illness is being shaped by neuroscience. However, it has the paradoxical effect of igniting two radically opposed groups of philosophical views. On one side, skepticism and denialism assume that, lacking clear biological mechanisms and etiologies for most mental illnesses, we should infer they are constructions best explained by means of social factors. This is strongly associated with medical nihilism: it considers psychiatry more harmful than benign. On the other side of the divide, naturalism and (...) reductionism are on the look for failures in the biological functioning of the organism whenever a genuine mental illness occurs. Psychiatry as currently practiced, accordingly, exhibits the gaps of an ongoing research programme; a yet to be completed neuroscience would link mental illnesses with identifiable biological mechanisms. Both sides of this divide claim to be fostered by scientific discoveries and advances in neuroscience, when taken at face value. Against this background, we argue instead for a modest view. To that end, we draw attention to some nuances in the scientific realism debate. While contending that neuroscientific theories and models aim to provide true representations of their target systems, and can justifiably claim to have attained some, we argue that our confidence should not be placed beforehand in specific features of these scientific representations. Hence, it would be unwarranted to extract morals for psychiatry from posits (or their absence) in neuroscientific explanations of mental illnesses. To illustrate our position, we examine some recent discoveries in neuroscience concerning bipolar disorder. We conclude by linking our topic to a broader issue in the philosophy of medicine: insofar as psychiatry is a biomedical specialty, its classifications of health and disease are guided by pragmatic concerns, as well as by scientific discoveries. (shrink)

For both Jung and Patañjali our human desire to understand “God” is as real as any other instinct. Jung’s and Patañjali’s models further align in their emphasis on the teleological directedness of the psyche, and their aim at reconciling science and religious experience. As an atheist, Freud was in disagreement, but all three scholars align in their emphasis on the study of affect as an empirical means of entering into the psyche. For Patañjali, the nadir of affect lays in transcending (...) sorrow and stabilizing the mind. Mental stability in turn produces the capacity to fully differentiate between the binding states of mind, which lead to human suffering, and the experience of pure consciousness resting in authentic nature. Contemporary brain research indicates that conscious states are inherently affective—further, the upper brainstem is intrinsically conscious whereas the cortex is not; it derives its consciousness from the brainstem. Understanding consciousness, then, may have less to do with reflective cognition than with instinct. This research spotlights the phenomena of affect, as it appears to not only draw us back to the highly significant rupture of the Freud Jung dialogue, but also forward into formulating a contemporary clinical picture of the drive towards (or away from) religious experience. (shrink)

"New wave" reductionism aims at advancing a kind of reduction that is stronger than unilateral dependency of the mental on the physical. It revolves around the idea that reduction between theoretical levels is a matter of degree, and can be laid out on a continuum between a "smooth" pole (theoretical identity) and a "bumpy" pole (extremely revisionary). It also entails that both higher and lower levels of the reductive relationship sustain some degree of explanatory autonomy. The new wave predicts that (...) reductions of folk psychology to neuroscience will be located in the middle of this continuum; as neuroscientific evidence about mental states checks in, theoretical folk psychology will therefore be moderately revised. However, the model has conceptual problems which preclude its success in reviving reductionism, and its commitment to a syntactic approach wrecks its attempt to rescue folk psychology. Moreover, the architecture of the continuum operates on a category mistake that sneaks in an eliminativist conclusion. I argue that new wave reductionism therefore tends to be eliminativism in disguise. (shrink)

We chart how neuroscience and philosophy have together advanced our understanding of moral judgment with implications for when it goes well or poorly. The field initially focused on brain areas associated with reason versus emotion in the moral evaluations of sacrificial dilemmas. But new threads of research have studied a wider range of moral evaluations and how they relate to models of brain development and learning. By weaving these threads together, we are developing a better understanding of the neurobiology (...) of moral judgment in adulthood and to some extent in childhood and adolescence. Combined with rigorous evidence from psychology and careful philosophical analysis, neuroscientific evidence can even help shed light on the extent of moral knowledge and on ways to promote healthy moral development. (shrink)

Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original (...) code, serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code. (shrink)

In this article, I argue that intentional psychology (i.e. the interpretation of human behaviour in terms of intentional states and propositional attitudes) plays an essential role in the sciences of the mind. However, this role is not one of identifying scientifically respectable states of the world. Rather, I argue that intentional psychology acts as a type of phenomenological model, as opposed to a mechanistic one. I demonstrate that, like other phenomenological models in science, intentional psychology is a methodological tool with (...) its own benefits and insights that complements our mechanistic understanding of systems. As a result, intentional psychology's distinctive scientific benefit is its ability to model systems in unique, non-mechanistic, ways. This allows us to generate predictions that we cannot otherwise generate using the mechanistic models of neuroscience and cognitive psychology necessary for various scientific tasks. (shrink)

The aim of this paper is to refer basic philosophical approaches to the problem of musical meaning and, on the other hand, to describe some examples of the research on musical meaning found in the field of cognitive neuroscience. By looking at those two approaches together it can be seen that there is still no agreement on how musical meaning should be understood, often due to several methodological problems of which the most important seem to be the possibility of (...) inter-theoretical reduction and application of an accurate theory of explanation. I am suggesting that the application of some form of the mechanistic model of explanation might be found useful for clarifying reductionism-antireductionism dispute concerning musical meaning, and more importantly, for providing some answers for the debate in music-as-language controversy. (shrink)

Given that teachers become primary fundamental exemplars and models for their students and the students are likely to emulate the presented teachers’ behaviors, it is necessary to consider how to promote teachers’ abilities as potential moral educators during the course of teacher education. To achieve this ultimate aim in teacher education, as argued by moral philosophers, psychologists, and educators, teachers should be able to well understand the mechanisms of moral functioning and how to effectively promote moral development based on evidence. (...) Recent findings in the fields of social sciences that have examined how morality is functioning among human beings, moral psychology in particular, provide us with the evidence through experiments and observations. Furthermore, thanks to the development of scientific research methods that enable researchers to investigate the neural-level nature of human behavior, the researchers now can examine neural correlates of moral functioning that constitutes the basis of moral behavior and development. To facilitate the understanding of the field of neuroscience of morality and its educational implications within the context of teacher education, first, the recent trend in the field will be reviewed, and second, how it can provide useful insights to teachers and teacher educations will be discussed. (shrink)

The aim of the Validation Theory (VT) as a meta-empirical construct is to introduce a new vista in the reorganization of the neuroscience, in its role of a science of the Mind-and-Brain unification. The present study focuses on existing discrepancies and contradictions between the methods of basic neurosciences and those prescribed by the psychological science. Our view is that these discrepancies are based on a high penetration of traditional neuroscience methods into the biological processes, coupled with low extrapolation (...) (experimenting with animal models) and vice versa for the psychological and psychopathological methods. A novel epistemological model for integrating psychological and neuroscientific knowledge is proposed. It is represented as a simultaneous investigation of the brain activity with penetrating high resolution functional Magnetic Resonance Imaging and in extenso application of set of psychological tests for exploring correspondence (cross-validation) between their compounds. The proposed approach leads to a revision of the neuroscientific and psychological terms, methods and data, followed by a revision of their relative interplay. This would make possible a practical exchange of expensive but objective fMRI with the lower costing psychological instruments (effect of "minimization"). The approaches proceeding from VT will infiltrate diagnostics and prevention in psychiatry. On a further stage the pharmaco-psychological monitoring will uncover new opportunities. This proofs' based research and practice represents an integral counterpart of the values-based mental health care. In conclusion VT is an evolutionary corner stone in order to traverse the stage of a Brain-Brain paradigm and to reach the point of development of the Mind-Brain paradigm. (shrink)

I discuss whether there are some lessons for philosophical inquiry over the nature of simulation to be learnt from the practical methodology of reengineering. I will argue that reengineering serves a similar purpose as simulations in theoretical science such as computational neuroscience or neurorobotics, and that the procedures and heuristics of reengineering help to develop solutions to outstanding problems of simulation.

According to [Bayesian] models” in cognitive neuroscience, says a recent textbook, “the human mind behaves like a capable data scientist”. Do they? That is to say, do such model show we are rational? I argue that Bayesian models of cognition, perhaps surprisingly, do not and indeed cannot, show that we are Bayesian-rational. The key reason is that such models appeal to approximations, a fact that carries significant implications. After outlining the argument, I critique two responses, seen in recent cognitive (...) neuroscience. One says that the mind can be seen as approximately Bayes-rational, while the other reconceives norms of rationality. (shrink)

In Measuring the Immeasurable Mind: Where Contemporary Neuroscience Meets the Aristotelian Tradition, Matthew Owen argues that despite its nonphysical character, it is possible to empirically detect and measure consciousness. -/- Toward the end of the previous century, the neuroscience of consciousness set its roots and sprouted within a materialist milieu that reduced the mind to matter. Several decades later, dualism is being dusted off and reconsidered. Although some may see this revival as a threat to consciousness science aimed (...) at measuring the conscious mind, Owen argues that measuring consciousness, along with the medical benefits of such measurements, is not ruled out by consciousness being nonphysical. Owen proposes the Mind-Body Powers model of neural correlates of consciousness, which is informed by Aristotelian causation and a substance dualist view of human nature inspired by Thomas Aquinas, who often followed Aristotle. In addition to explaining why there are neural correlates of consciousness, the model provides a philosophical foundation for empirically discerning and quantifying consciousness. En route to presenting and applying the Mind-Body Powers model to neurobiology, Owen rebuts longstanding objections to dualism related to the mind-body problem. With scholarly precision and readable clarity, Owen applies an oft forgotten yet richly developed historical vantage point to contemporary cognitive neuroscience. (shrink)

The present essay discusses the relationship between moral philosophy, psychology and education based on virtue ethics, contemporary neuroscience, and how neuroscientific methods can contribute to studies of moral virtue and character. First, the present essay considers whether the mechanism of moral motivation and developmental model of virtue and character are well supported by neuroscientific evidence. Particularly, it examines whether the evidence provided by neuroscientific studies can support the core argument of virtue ethics, that is, motivational externalism. Second, it discusses (...) how experimental methods of neuroscience can be applied to studies in human morality. Particularly, the present essay examines how functional and structural neuroimaging methods can contribute to the development of the fields by reviewing the findings of recent social and developmental neuroimaging experiments. Meanwhile, the present essay also considers some limitations embedded in such discussions regarding the relationship between the fields and suggests directions for future studies to address these limitations. (shrink)

A strange dialectical reversal characterizes the oppositions which psychoanalysis posits against philosophy and neuroscience: what psychoanalysis intervenes with as a unique and missing quality of these subjects, reveals itself upon enquiry as already having been a feature of said subjects. This article first discusses the failed intervention of psychoanalysis within the perceived totalities and absolutes of German idealism. Psychoanalysis, founded on an ontological division and internal inconsistency with a retroactive logic, finds this internal contradiction already reflected within the supposed (...) totalities of Schelling and Hegel. Schelling’s “blind act,” a decision with no prior foundation that grounds an abstract identity-in-itself, appears as the counterpart to what Badiou calls the strictly “analytic act.” Hegel’s Science of Logic, in which the inconclusive interpenetration of being and nothing presupposes its own conclusion in the transitions to essence, and in which an internal incompleteness and contradiction are retroactively constitutive of the concept, similarly nullifies the intervention of psychoanalysis. Finally, precisely such a reversal is presented in neuroscience, where the constitutive contradiction of contingently functional neuronal formations in the adaptive “multiple demand” model of executive functioning repeats the contingent and self-contradicting psychoanalytic subject as being its own deference within linguistic, discursive formations. (shrink)

In this paper I argue that neuroscience has been harmed by the widespread adoption of seriously inadequate methodologies or philosophies of science - most notably inductivism and falsificationism. I argue that neuroscience, in seeking to understand the human brain and mind, needs to follow in the footsteps of evolution.

Patient RB has a peculiar memory impairment wherein he experiences his memories in rich contextual detail, but claims to not own them. His memories do not feel as if they happened to him. In this paper, I provide an explanatory model of RB’s phenomenology, the self-attentional model. I draw upon recent work in neuroscience on self-attentional processing and global workspace models of conscious recollection to show that RB has a self-attentional deficit that inhibits self-bias processes in broadcasting the contents (...) of episodic memories to the global workspace. Typically, self-related contents enjoy a higher salience level than other-related contents. Elimination of bias toward self-related contents diminishes the salience of those contents to the level of other-related contents. Because the typical high salience of self-related content is necessary for the feeling of ownership, RB lacks the feeling of ownership. I also discuss potential applications of the self-attentional model to other psychopathological cases. (shrink)

Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for a physically (...) different kind of process. I discuss the advantages of this approach in the context of evolutionary biology. (shrink)

This paper addresses concerns raised recently by Datteri (Biol Philos 24:301–324, 2009) and Craver (Philos Sci 77(5):840–851, 2010) about the use of brain-extending prosthetics in experimental neuroscience. Since the operation of the implant induces plastic changes in neural circuits, it is reasonable to worry that operational knowledge of the hybrid system will not be an accurate basis for generalisation when modelling the unextended brain. I argue, however, that Datteri’s no-plasticity constraint unwittingly rules out numerous experimental paradigms in behavioural (...) and systems neuroscience which also elicit neural plasticity. Furthermore, I propose that Datteri and Craver’s arguments concerning the limitations of prosthetic modelling in basic neuroscience, as opposed to neuroengineering, rests on too narrow a view of the ways models in neuroscience should be evaluated, and that a more pluralist approach is needed. I distinguish organisational validity of models from mechanistic validity. I argue that while prosthetic models may be deficient in the latter of these explanatory virtues because of neuroplasticity, they excel in the former since organisational validity tracks the extent to which a model captures coding principles that are invariant with plasticity. Changing the brain, I conclude, is one viable route towards explaining the brain. (shrink)

People suffering from Obsessive-Compulsive Disorder (OCD) do things they do not want to do, and/or they think things they do not want to think. In about 10 percent of OCD patients, none of the available treatment options is effective. A small group of these patients is currently being treated with deep brain stimulation (DBS). Deep brain stimulation involves the implantation of electrodes in the brain. These electrodes give a continuous electrical pulse to the brain area in which they are implanted. (...) It turns out that patients may experience profound changes as a result of DBS treatment. It is not just the symptoms that change; patients rather seem to experience a different way of being in the world. These global effects are insufficiently captured by traditional psychiatric scales, which mainly consist of behavioural measures of the severity of the symptoms. In this article we aim to capture the changes in the patients’ phenomenology and make sense of the broad range of changes they report. For that we introduce an enactive, affordance-based model that fleshes out the dynamic interactions between person and world in four aspects. The first aspect is the patients’ experience of the world. We propose to specify the patients’ world in terms of a field of affordances, with the three dimensions of broadness of scope (‘width’ of the field), temporal horizon (‘depth’), and relevance of the perceived affordances (‘height’). The second aspect is the person-side of the interaction, that is, the patients’ self-experience, notably their moods and feelings. Thirdly, we point to the different characteristics of the way in which patients relate to the world. And lastly, the existential stance refers to the stance that patients take towards the changes they experience: the second-order evaluative relation to their interactions and themselves. With our model we intend to specify the notion of being in the world in order to do justice to the phenomenological effects of DBS treatment. (shrink)

Biomedical science has been remarkably successful in explaining illness by categorizing diseases and then by identifying localizable lesions such as a virus and neoplasm in the body that cause those diseases. Not surprisingly, researchers have aspired to apply this powerful paradigm to addiction. So, for example, in a review of the neuroscience of addiction literature, Hyman and Malenka (2001, p. 695) acknowledge a general consensus among addiction researchers that “[a]ddiction can appropriately be considered as a chronic medical illness.” Like (...) other diseases, “Once addiction has taken hold, it tends to follow a chronic course.” (Koob and La Moal 2006, p. ?). Working from this perspective, much effort has gone into characterizing the symptomology of addiction and the brain changes that underlie them. Evidence for involvement of dopamine transmission changes in the ventral tegmental area (VTA) and nucleus accumbens (NAc) have received the greatest attention. Kauer and Malenka (2007, p. 844) put it well: “drugs of abuse can co-opt synaptic plasticity mechanisms in brain circuits involved in reinforcement and reward processing”. Our goal in this chapter to provide an explicit description of the assumptions of medical models, the different forms they may take, and the challenges they face in providing explanations with solid evidence of addiction. <br>. (shrink)

One striking feature of the contemporary modeling practice is its interdisciplinarity: the same function forms and equations, and mathematical and computational methods are being transferred across disciplinary boundaries. Within philosophy of science this interdisciplinary dimension of modeling has been addressed by both analogy and template-based approaches that have proceeded separately from each other. We argue that a more fully-blown account of model transfer needs both perspectives. We examine analogical reasoning and template application through a detailed case study on the transfer (...) of the Ising model from physics into neuroscience. Our account combines the analogy and template-based approaches through the notion of a model template that highlights the conceptual side of model transfer. (shrink)

Drawing from empirical literature on ecological psychology, affective neuroscience, and philosophy of mind, this article describes a model of affect-as-motivation in the intentional bond between organism and environment. An epistemological justification for the motivating role of emotions is provided through articulating the perceptual context of emotions as embodied, situated, and functional, and positing perceptual salience as a biasing signal in an affordance competition model. The motivational role of affect is pragmatically integrated into discussions of action selection in the neurosciences.

The fate of optimality modeling is typically linked to that of adaptationism: the two are thought to stand or fall together (Gould and Lewontin, Proc Relig Soc Lond 205:581–598, 1979; Orzack and Sober, Am Nat 143(3):361–380, 1994). I argue here that this is mistaken. The debate over adaptationism has tended to focus on one particular use of optimality models, which I refer to here as their strong use. The strong use of an optimality model involves the claim that selection is (...) the only important influence on the evolutionary outcome in question and is thus linked to adaptationism. However, biologists seldom intend this strong use of optimality models. One common alternative that I term the weak use simply involves the claim that an optimality model accurately represents the role of selection in bringing about the outcome. This and other weaker uses of optimality models insulate the optimality approach from criticisms of adaptationism, and they account for the prominence of optimality modeling (broadly construed) in population biology. The centrality of these uses of optimality models ensures a continuing role for the optimality approach, regardless of the fate of adaptationism. (shrink)

This analysis summarizes conclusions on an evolutionary model for the origin of moral and religious capacities in the genus Homo. The authors’ published model (2020, Routledge) is now extended to the emergence of nascent theological thinking, augmenting the previous line of theory based on genomics, cognitive science, neuroscience, paleoneurology, cognitive archaeology, ethnography, and modern social science. This analysis concludes that findings support the earliest theological thinking in Homo sapiens, but not in an earlier species, Homo erectus, and clarifies why (...) and when it likely began. Types of anatomy, behavior, neurology, and cognition are presented that support tendencies to frame a structure of religious principles and a set of supernatural figures that early humans would consider right, just, exemplary, and even sacred. Stages of emergent physical, behavioral, and cognitive features are presented in tables. While based on published research results in the sciences, the model is presented here with anticipation of future testing. (shrink)

Today research on prosocial behaviour is very much shaped by the success of social neuroscience. However, some philosopher's criticise neuroscience as reductionist. The purpose of this paper is to analyse this critique. With a philosophical background in Charles Taylor's hermeneutic thesis "man as a self-interpreting animal", the paper shows that neuroscientists' attempt to describe prosocial behaviour in science through brain imaging technologies (MRI) constitute a neurochemical self that resonates a modern ‘paradigm of clarity and objectivity’ as presented by (...) Taylor. It is argued that this scientific explanation model challenges Taylor's hermeneutic self. Where human behaviour previous was mapped on a psychological level, prosocial behaviour is described in the body - the human brain - on a neurophysiological level. The author applies an autism analogy metaphor, which paradoxical shows that the neurochemical self’s emphasis on structures and observations epistemological facilitate an autistic understanding of prosocial behaviour alien to the situated and interpreted feelings of Taylor's self-understanding(s), and the logic of our everyday language. (shrink)

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. Moreover, we (...) argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. (shrink)

Philosophy can shed light on mathematical modeling and the juxtaposition of modeling and empirical data. This paper explores three philosophical traditions of the structure of scientific theory—Syntactic, Semantic, and Pragmatic—to show that each illuminates mathematical modeling. The Pragmatic View identifies four critical functions of mathematical modeling: (1) unification of both models and data, (2) model fitting to data, (3) mechanism identification accounting for observation, and (4) prediction of future observations. Such facets are explored using a recent exchange between two groups (...) of mathematical modelers in plant biology. Scientific debate can arise from different modeling philosophies. (shrink)

Conceptual modeling of a portion of the world is a necessary prerequisite to set the stage and define software system boundaries. In this context, one of the challenges is to provide a unified framework to create a comprehensive representation of the targeted domain. According to many researchers, conceptual model (CM) development is a hard task, and system requirements are difficult to collect, causing many miscommunication problems. Accordingly, CMs require more than modeling ability alone: they first require an understanding of the (...) targeted domain that the model attempts to represent. Accordingly, a preconceptual modeling (pre-CM) stage is intended to address ontological issues before typical CM development is initiated. It involves defining a portion of reality when entities and processes are differentiated and integrated as unified wholes. This pre-CM phase forms the focus of research in this paper. The purpose is not show how to model; rather, it is to demonstrate how to establish a metaphysical basis of the involved portion of reality. To demonstrate such a venture, we employ the so-called thinging machine (TM) modeling that has been proposed as a high-level CM. A TM model integrates staticity and dynamism grounded in a fundamental construct called a thimac (things/machine). It involves two modes of reality, existence (events) and subsistence (regions: roughly, specifications of things and processes). Currently, the dominant approach in CM has evolved to limit its scope of application to develop ontological categorization (types of things). In contrast, advocates of TM modeling have pursued a broader metaphysical study of the nature of the domain’s things and processes beyond categorization. In the TM approach, pre-CM metaphysics is viewed as a part and parcel of CM itself. The general research problem is how to map TM constructs to what is out there in the targeted domain. Discussions involve the nature of thimacs (things and processes) and subsistence and existence as they are superimposed over each other in reality. Specifically, we make two claims, (i) the perceptibility of regions as a phenomenon and (ii) the distinctiveness of existence as a construct for events. The results contribute to further the understanding of TM modeling in addition to introducing some metaphysical insights. (shrink)

Advances in neuroscience implicate reentrant signaling as the predominant form of communication between brain areas. This principle was used in a series of masking experiments that defy explanation by feed-forward theories. The masking occurs when a brief display of target plus mask is continued with the mask alone. Two masking processes were found: an early process affected by physical factors such as adapting luminance and a later process affected by attentional factors such as set size. This later process is (...) called masking by object substitution, because it occurs whenever there is a mismatch between the reentrant visual representation and the ongoing lower level activity. Iterative reentrant processing was formalized in a computational model that provides an excellent fit to the data. The model provides a more comprehensive account of all forms of visual masking than do the long-held feed-forward views based on inhibitory contour interactions. (shrink)

This paper is devoted to some generalizations of explanatory potential of connectionist approaches to theoretical problems of the philosophy of mind. Are considered both strong, and weaknesses of neural network models. Connectionism has close methodological ties with modern neurosciences and neurophilosophy. And this fact strengthens its positions, in terms of empirical naturalistic approaches. However, at the same time this direction inherits weaknesses of computational approach, and in this case all system of anticomputational critical arguments becomes applicable to the connectionst models (...) of mind. The last developments in the field of deep learning gave rich empirical material for cognitive sciences. Multilayered networks, mathematical models of associative dynamics of learning, self-organizing neuronets and all that allow to explain the principles of human conceptual organizing and after this to emulate these processes in computer systems. At all engineering achievements of this technology there is a traditional criticism from representatives of cognitive psychology who cannot accept a thesis about learning ability of a neuronet on the basis of redistribution of scales. Process of learning of natural intelligence, according to cognitive models, happens due to attraction of knowledge broadcast in a symbolical form (mental representations, concepts) at the expense of the systems of output knowledge expressed in the propositional contents. Some philosophical aspects of «neural metaphor» in modern cognitive sciences create the problem field which demands comprehensive understanding, the first step towards which is taken in this work. (shrink)

Starting from a philosophical perspective, which states that the living structures are actually a combination between matter and information, this article presents the results on an analysis of the bipolar information-matter structure of the human organism, distinguishing three fundamental circuits for its survival, which demonstrates and supports this statement, as a base for further development of the informational model of consciousness to a general informational model of the human organism. For this, it was examined the Informational System of the Human (...) Body and its components from the perspective of the physics/information/neurosciences concepts, showing specific functions of each of them, highlighting the correspondence of these centers with brain support areas and with their projections in consciousness, which are: Center of Acquisition and Storing of Information (CASI) reflected in consciousness as memory, Center of Decision and Command (CDC) (decision), Info-Emotional Center (IES) (emotions), Maintenance Informational System (MIS) (personal status), Genetic Transmission System (GTS) (associativity/genetic transmission) and Info Genetic Generator (IGG) related by the body development and inherited behaviors. The Info Connection (IC), detected in consciousness as trust and confidence can explain the Near-Death Experiences (NDEs) and associated phenomena. This connection is antientropic and informational, because from the multitude of uncertain possibilities is selected a certain one, helping/supporting the survival and life. The human body appears therefore as a bipolar structure, connected to two poles: information and matter. It is argued that the survival, which is the main objective of the organism, is complied in three main ways, by means of: (i) the reactive operation for adaptation by attitude; (ii) the info-genetic integration of information by epigenetic processes and genetic transmission of information for species survival, both circuits (i) and (ii) being associated to the information pole; (iii) maintenance of the material body (defined as informed matter) and its functions, associated to the matter pole of the organism. It results therefore that the informational system of the human body is supported by seven informational circuits formed by the neuro-connections between the specific zones of the brain corresponding to the informational subsystems, the cognitive centers, the sensors, transducers and execution (motor/mobile) elements. The fundamental informational circuits assuring the survival are the reactive circuit, expressible by attitude, the epigenetic/genetic circuit, absorbing and codifying information to be transmitted to the next generations, and the metabolic circuit, connected to matter (matter pole). The presented analysis allows to extend the informational modeling of consciousness to an Informational Model of Consciousness and Organism, fully describing the composition/functions of the organism in terms of information/matter and neurosciences concept. (shrink)

Enterprise Risk Management involves the process of identification, evaluation, treatment, and communication regarding risks throughout the enterprise. To support the tasks associated with this process, several frameworks and modeling languages have been proposed, such as the Risk and Security Overlay (RSO) of ArchiMate. An ontological investigation of this artifact would reveal its adequacy, capabilities, and limitations w.r.t. the domain of risk and security. Based on that, a language redesign can be proposed as a refinement. Such analysis and redesign have been (...) executed for the risk elements of the RSO grounded in the Common Ontology of Value and Risk. The next step along this line of research is to address the following research problems: What would be the outcome of an ontological analysis of security-related elements of the RSO? That is, can we identify other semantic deficiencies in the RSO through an ontological analysis? Once such an analysis is provided, can we redesign the security elements of the RSO accordingly, in order to produce an improved artifact? Here, with the aid of the Reference Ontology for Security Engineering (ROSE) and the ontological theory of prevention behind it, we address the remaining gap by proceeding with an ontological analysis of the security-related constructs of the RSO. The outcome of this assessment is an ontology-based redesign of the ArchiMate language regarding security modeling. In a nutshell, we report the following contributions: (1) an ontological analysis of the RSO that identifies six limitations concerning security modeling; (2) because of the key role of the notion of prevention in security modeling, the introduction of the ontological theory of prevention in ArchiMate; (3) a well-founded redesign of security elements of ArchiMate; and (4) ontology-based security modeling patterns that are logical consequences of our proposal of redesign due to its underlying ontology of security. As a form of evaluation, we show that our proposal can describe risk treatment options, according to ISO 31000. Finally, besides presenting multiple examples, we proceed with a real-world illustrative application taken from the cybersecurity domain. (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)

The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...) and less theoretical than physics. However, the key leverageable idea is that careful extension of the science of living systems can be more effectively applied to some of our most vexing modern problems than the prevailing scheme, derived from abstractions in physics. While these have some universal application and demonstrate computational advantages, they are not theoretically mandated for the living. A new set of mathematical abstractions derived from biology can now be similarly extended. This is made possible by leveraging new formal tools to understand abstraction and enable computability. [The latter has a much expanded meaning in our context from the one known and used in computer science and biology today, that is "by rote algorithmic means", since it is not known if a living system is computable in this sense (Mossio et al., 2009).] Two major challenges constitute the effort. The first challenge is to design an original general system of abstractions within the biological domain. The initial issue is descriptive leading to the explanatory. There has not yet been a serious formal examination of the abstractions of the biological domain. What is used today is an amalgam; much is inherited from physics (via the bridging abstractions of chemistry) and there are many new abstractions from advances in mathematics (incentivized by the need for more capable computational analyses). Interspersed are abstractions, concepts and underlying assumptions “native” to biology and distinct from the mechanical language of physics and computation as we know them. A pressing agenda should be to single out the most concrete and at the same time the most fundamental process-units in biology and to recruit them into the descriptive domain. Therefore, the first challenge is to build a coherent formal system of abstractions and operations that is truly native to living systems. Nothing will be thrown away, but many common methods will be philosophically recast, just as in physics relativity subsumed and reinterpreted Newtonian mechanics. -/- This step is required because we need a comprehensible, formal system to apply in many domains. Emphasis should be placed on the distinction between multi-perspective analysis and synthesis and on what could be the basic terms or tools needed. The second challenge is relatively simple: the actual application of this set of biology-centric ways and means to cross-disciplinary problems. In its early stages, this will seem to be a “new science”. This White Paper sets out the case of continuing support of Information and Communication Technology (ICT) for transformative research in biology and information processing centered on paradigm changes in the epistemological, ontological, mathematical and computational bases of the science of living systems. Today, curiously, living systems cannot be said to be anything more than dissipative structures organized internally by genetic information. There is not anything substantially different from abiotic systems other than the empirical nature of their robustness. We believe that there are other new and unique properties and patterns comprehensible at this bio-logical level. The report lays out a fundamental set of approaches to articulate these properties and patterns, and is composed as follows. -/- Sections 1 through 4 (preamble, introduction, motivation and major biomathematical problems) are incipient. Section 5 describes the issues affecting Integral Biomathics and Section 6 -- the aspects of the Grand Challenge we face with this project. Section 7 contemplates the effort to formalize a General Theory of Living Systems (GTLS) from what we have today. The goal is to have a formal system, equivalent to that which exists in the physics community. Here we define how to perceive the role of time in biology. Section 8 describes the initial efforts to apply this general theory of living systems in many domains, with special emphasis on crossdisciplinary problems and multiple domains spanning both “hard” and “soft” sciences. The expected result is a coherent collection of integrated mathematical techniques. Section 9 discusses the first two test cases, project proposals, of our approach. They are designed to demonstrate the ability of our approach to address “wicked problems” which span across physics, chemistry, biology, societies and societal dynamics. The solutions require integrated measurable results at multiple levels known as “grand challenges” to existing methods. Finally, Section 10 adheres to an appeal for action, advocating the necessity for further long-term support of the INBIOSA program. -/- The report is concluded with preliminary non-exclusive list of challenging research themes to address, as well as required administrative actions. The efforts described in the ten sections of this White Paper will proceed concurrently. Collectively, they describe a program that can be managed and measured as it progresses. (shrink)

This Research Topic aimed at deepening our understanding of the levels and explanations that are of interest for cognitive sci- entists, neuroscientists, psychologists, behavioral scientists, and philosophers of science. Indeed, contemporary developments in neuroscience and psy- chology suggest that scientists are likely to deal with a multiplicity of levels, where each of the different levels entails laws of behavior appropriate to that level (Berntson et al., 2012). Also, gathering and modeling data at the different levels of analysis is not (...) suffi- cient: the integration of information across levels of analysis is a crucial issue. Given such state of affairs, a number of interesting questions arise. How can the autonomy of explanatory levels be properly understood in behavioral explanation? Is reductionism a satis- factory strategy? How can high-level and low-level models be constrained in order to be actually explanatory of both behav- ioral and neurological or molecular evidence? What is the kind of relationship between those models? (shrink)

How much does stimulus input shape perception? The common-sense view is that our perceptions are representations of objects and their features and that the stimulus structures the perceptual object. The problem for this view concerns perceptual biases as responsible for distortions and the subjectivity of perceptual experience. These biases are increasingly studied as constitutive factors of brain processes in recent neuroscience. In neural network models the brain is said to cope with the plethora of sensory information by predicting stimulus (...) regularities on the basis of previous experiences. Drawing on this development, this chapter analyses perceptions as processes. Looking at olfaction as a model system, it argues for the need to abandon a stimulus-centred perspective, where smells are thought of as stable percepts, computationally linked to external objects such as odorous molecules. Perception here is presented as a measure of changing signal ratios in an environment informed by expectancy effects from top-down processes. (shrink)

The relationship between topological explanation and mechanistic explanation is unclear. Most philosophers agree that at least some topological explanations are mechanistic explanations. The crucial question is how to make sense of this claim. Zednik (Philos Psychol 32(1):23–51, 2019) argues that topological explanations are mechanistic if they (i) describe mechanism sketches that (ii) pick out organizational properties of mechanisms. While we agree with Zednik’s conclusion, we critically discuss Zednik’s account and show that it fails as a general account of how and (...) when topological explanations are mechanistic. First, if topological explanations were just mechanism sketches, this implies that they could be enriched by replacing topological terms with mechanistic detail. This, however, conflicts how topological explanations are used in scientific practice. Second, Zednik’s account fails to show how topological properties can be organizational properties of mechanisms that have a place in mechanistic explanation. The core issue is that Zednik’s account ignores that topological properties often are _global_ properties while mechanistic explanantia refer to _local_ properties. We demonstrate how these problems can be solved by a recent account of mechanistic completeness (Craver and Kaplan in Br J Philos Sci 71(1):287–319, 2020; Kohár and Krickel in Calzavarini and Viola (eds) Neural mechanisms—new challenges in the philosophy of neuroscience, Springer, New York, 2021) and use a multilayer network model of Alzheimer’s Disease to illustrate this. (shrink)

In this paper I discuss one of the key issuesin the philosophy of neuroscience:neurosemantics. The project of neurosemanticsinvolves explaining what it means for states ofneurons and neural systems to haverepresentational contents. Neurosemantics thusinvolves issues of common concern between thephilosophy of neuroscience and philosophy ofmind. I discuss a problem that arises foraccounts of representational content that Icall ``the economy problem'': the problem ofshowing that a candidate theory of mentalrepresentation can bear the work requiredwithin in the causal economy of a (...) mind and anorganism. My approach in the current paper isto explore this and other key themes inneurosemantics through the use of computermodels of neural networks embodied and evolvedin virtual organisms. The models allow for thelaying bare of the causal economies of entireyet simple artificial organisms so that therelations between the neural bases of, forinstance, representation in perception andmemory can be regarded in the context of anentire organism. On the basis of thesesimulations, I argue for an account ofneurosemantics adequate for the solution of theeconomy problem. (shrink)