Explanation in Neuroscience

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)

Neuroscience hasn’t shown how quite similar sensory circuits encode quite different colors and other qualia, nor how the unified pictorial form of images is encoded, nor how these codes yield conscious images. Neuroscience’s fixation here on cortical codes may be the culprit. Treating conscious images partly as retinal substances may avoid these problems. The evidence for conscious retinal images is that (a) the cortical codes for images are quite problematic, (b) injecting retinas with certain genes turns dichromats into trichromats without (...) cortical help, (c) retinas can discern colors by themselves without cortex, (d) retinal distortions appear in images but cortical distortions don’t, (e) retinal detectors support finely detailed colors, but V4 detectors don’t, due to their big receptive fields, (f) retinal activity has pictorial form, but viable cortical codes for pictorial form don’t exist. So, the colors and unified pictorial form of images arguably arise mainly across arrays of retinal detectors—not from abstract cortical codes. Images may be hidden in retinal activity beyond what EEGs show of it (cf. Strawson’s monism). Also, cortex refines these retinal images but cortical impairment (anesthesia, lesions, etc.) blocks awareness of them, for they’re no longer accessible to the mind’s subject-centered consciousness, resident in cortex. This proposal is largely testable and based in recent evidence. It avoids neuroscience’s elusive, problematic coded images and enigmatic explanations of how they become conscious. (shrink)

Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship between that (...) structure and function fails to be manipulable independent of other causal relationships within the system. Contrary to this line of reasoning, I argue that functional robustness often attends feedback control, rather than failures of modularity. Feedback control poses its own challenges to causal explanation and inference, but those challenges do not undermine modularity—and indeed, modularity is crucial to grappling with them. (shrink)

The traditional approach to explanation in cognitive neuroscience is realist about psychological constructs, and treats them as explanatory. On the “standard framework,” cognitive neuroscientists explain behavior as the result of the instantiation of psychological functions in brain activity. This strategy is questioned by results suggesting the distribution of function in the brain, the multifunctionality of individual parts of the brain, and the overlap in neural realization of purportedly distinct psychological constructs. One response to this in the field has been to (...) employ the tools of databasing and machine learning to attempt to find and quantify specific correlations between psychological kinds such as ‘memory’ or ‘attention’ (or sub-kinds thereof) and patterns of activity in the brain. I assess the status and prospects of these projects. I argue that current proponents of the project are vague about their aims, vis-à-vis the standard framework, sometimes suggesting substantiation of the framework, sometimes suggesting retaining the framework but revising the ontology of mental constructs, and sometimes suggesting abandonment of the framework. I argue that extant results from within the projects fail to substantiate the standard framework, and propose an alternative. On my view, psychological constructs should not be viewed as explanantia, but instead as heuristic concepts that help us uncover ways that behaviors can vary and the ways that the brain implements those distinctions. I then discuss the normative upshot of these views for databasing and brain mapping projects. (shrink)

Alex Rosenberg’s latest book purports to establish that narrative history cannot have any epistemic value. Rosenberg argues not for the replacement of narrative history by something more science-like, but rather the end of histories understood as an account of human doings under a certain description. This review critiques three of his main arguments: 1) narrative history must root its explanations in folk psychology, 2) there are no beliefs nor desires guiding human action, and 3) historical narratives are morally and ethically (...) pernicious. Rosenberg’s book reprises themes about action explanation he first rehearsed 40 years ago, albeit with neuroscience rather than sociobiology now “preempting” explanations that trade on folk psychological notions. Although Rosenberg’s argument strategy has not altered, the review develops a number of reasons as to why his approach now lacks any plausibility as a strategy for explaining histories, much less a successful one. (shrink)

According to mainstream philosophical views causal explanation in biology and neuroscience is mechanistic. As the term ‘mechanism’ gets regular use in these fields it is unsurprising that philosophers consider it important to scientific explanation. What is surprising is that they consider it the only causal term of importance. This paper provides an analysis of a new causal concept—it examines the cascade concept in science and the causal structure it refers to. I argue that this concept is importantly different from the (...) notion of mechanism and that this difference matters for our understanding of causation and explanation in science. (shrink)

This paper defines and defends a notion of teleological function which is fit to figure in explanations concerning how organic systems, and the items which compose them, are able to perform certain activities, such as surviving and reproducing or pumping blood. According to this notion, a teleological function of an item (such as the heart) is a typical way in which items of that type contribute to some containing system's ability to do some activity. An account of what it is (...) for an item to contribute to a containing system's ability to perform an activity is provided. I argue that the view acquires its normative status in virtue of the fact that it obeys a function-accident distinction and obeys a function-dysfunction distinction; that the view is ahistorical; and, that its ahistoricity provides it with an advantage over one of its main competitors. (shrink)

Explanations in behavioural neuroscience are often said to be mechanistic in the sense that they explain an organism’s behaviour by describing the activities and organisation of the organism’s parts that are “constitutively relevant” to organism behaviour. Much has been said about the constitutive relevance of working parts (in debates about the so-called “mutual manipulability criterion”), but relatively little has been said about the constitutive relevance of the organising relations between working parts. Some New Mechanists seem to endorse a simple causal-linking (...) account: organising relations are constitutively relevant to organism behaviour if and only if (and because) they are causal relations that link the working parts that are constitutively relevant to organism behaviour. In this paper, I argue that the causal-linking account is inadequate because it neglects the constitutive relevance of anatomical relations that organise the working parts of a behaving organism. I demonstrate this by considering a case study where the anatomical organisation of the barn owl (Tyto alba) is constitutively relevant to their mechanism for sound localization. The anatomical organisation of this mechanism is best understood as the back-and-forth flow of task information across 7 “levels of anatomy” (a notion that I distinguish from levels of mechanism). A further implication, I conclude, is that at least some of the interlevel structure of neuroscientific explanation is accounted for by levels of anatomy, not levels of mechanism. (shrink)

This paper considers the question of whether the influential distinction between levels of explanation introduced by David Marr can be used as a general framework for contemplating levels of explanation in cognitive sciences. Marr introduced three levels at which we can explain cognitive processes: the computational, algorithmic, and implementational levels. Some argue that Marr’s levels of explanation can only be applied to modular cognitive systems. However, since many psychological processes are non-modular, it seems that Marr’s levels of explanation cannot explain (...) such psychological processes. To show that the latter claim is not convincing, the paper draws upon an influential paradigm from cognitive sciences that is based on the principle of free energy. Based on this paradigm, the paper argues that even non-modular psychological processes can be computationally analyzed and algorithmically implemented. The conclusion of the paper is that, at least under the assumption that the func- tion of the mind is to minimize free energy, Marr’s levels of explanation can be successfully used as a general framework for understanding psychological processes at different levels of description. (shrink)

Trauma and traumatization have arguably always been part of the human experience yet have in the last few decades come to occupy a prominent place in various popular and academic contexts. This chapter offers an interdisciplinary and comparative investigation of trauma and traumatization in different historical contexts. More specifically, my aim is to discuss whether the rich bodies of research in trauma and traumatization in Holocaust survivors and their descendants yield relevant insights for post-slavery contexts. It has been shown that (...) children of Holocaust survivors suffer from stress and other symptoms related to their parents’ traumatization which influence the interactions with their environments. Such results made me wonder whether the traumatic impact of chattel slavery—which has been abolished some 160 years ago—might have a similar impact, yet now across several generations. Issues of the transmission and current persistence of trauma are inherently linked to questions of social justice, recognition and reparations. This chapter is meant, however, as an exploration of interdisciplinary connections that should be studied in concert to account for the traumatic impact of historical and present day experiences. It starts by discussing the concepts of trauma and post-traumatic stress disorder. Continuing by exploring the phenomenon of the inter- and transgenerational transmission of trauma, it relies in part on the important body of research conducted on families of Holocaust survivors. I then turn to the much less researched ‘post-traumatic slave syndrome’ (DeGruy) and discuss two factors that might contribute to the transgenerational transmission of trauma in the families of former enslaved: epigenetics and the continuation of traumatization even after the abolition of slavery as articulated in Historical Trauma theory. Drawing upon these insights, I conclude that it is plausible that a continuing transgenerational transmission of trauma might occur in some families of slavery survivors, the knowledge of which might help to break the chains of such traumatization across generations. (shrink)

The philosophical literature on scientific explanation in neuroscience has been dominated by the idea of mechanisms. The mechanist philosophers often claim that neuroscience is in the business of finding mechanisms. This view has been challenged in numerous ways by showing that there are other successful and widespread explanatory strategies in neuroscience. However, the empirical evidence for all these claims was hitherto lacking. Empirical evidence about the pervasiveness and uses of various explanatory strategies in neuroscience is particularly needed because examples and (...) case studies that are used to illustrate philosophical claims so far tend to be hand-picked. The risk of confirmation bias is therefore considerable: when looking for white swans, all one finds is that swans are white. The more systematic quantitative and qualitative bibliometric study of a large body of relevant literature that we present in this paper can put such claims into perspective. Using bibliometric tools, we identify the typical linguistic patterns used in the alleged mechanistic, dynamical, and topological explanations in the literature, their preponderance and how they change over time. Our findings show abundant use of mechanistic language, but also the presence of a significant neuroscience literature using topological and dynamical explanatory language, which grows over time and increasingly differentiates from each other and from mechanistic explanations. (shrink)

We provide three innovations to recent debates about whether topological or “network” explanations are a species of mechanistic explanation. First, we more precisely characterize the requirement that all topological explanations are mechanistic explanations and show scientific practice to belie such a requirement. Second, we provide an account that unifies mechanistic and non-mechanistic topological explanations, thereby enriching both the mechanist and autonomist programs by highlighting when and where topological explanations are mechanistic. Third, we defend this view against some powerful mechanist objections. (...) We conclude from this that topological explanations are autonomous from their mechanistic counterparts. (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)

Millikan’s (1984. Language, Thought, and Other Biological Categories: New Foundations for Realism. MIT Press) selected effects theory of functions states that functions are effects for which the ancestors of a trait were selected for. As the function is an effect a thing’s ancestors produced, only things that are reproductions in some sense can have functions. Against this reproduction requirement, Garson (2019. What Biological Functions Are and Why They Matter. Cambridge University Press) argues that not only processes of differential reproduction but (...) also processes of differential persistence can lead to new functions. Since such “persistence functions” have the same explanatory power as traditional selected effects functions, selected effects theorists should include them in their theory. In this paper, I will defend Millikan’s theory against this argument. I will show that the proponents of the generalized theory have yet to provide a working notion of populations that avoids a liberality problem. Further, I will argue that persistence functions are at best a marginal case of functions due to their restricted explanatory power. (shrink)

Some New Mechanists have proposed that claims of compositional relations are justified by combining the results of top-down and bottom-up interlevel interventions. But what do scientists do when they can perform, say, a cellular intervention, but not a subcellular detection? In such cases, paired interlevel interventions are unavailable. We propose that scientists use abduction and we illustrate its use through a case study of the ionic theory of resting and action potentials.

In a recent paper, Gualtiero Piccinini and Carl Craver have argued that psychology is not distinct from neuroscience. Many have argued that Piccinini and Craver’s argument is unsuccessful. However, none of these authors have questioned the appropriateness of Piccinini and Craver’s argument for their key premise—that functional analyses are mechanism sketches. My first and main goal in this paper is to show that Piccinini and Craver offer normative considerations in support of what is a descriptive premise and to provide some (...) guidelines on how to argue for this premise. My second goal is to show that the distinctness question should be of great significance for philosophy of cognitive science. (shrink)

Despite the huge and constant progress in the molecular and cellular neuroscience fields, our capability to understand brain alterations and treat mental illness is still limited. Therefore, a paradigm shift able to overcome such limitation is warranted. Behavior and the associated mental states are the interface between the central nervous system and the living environment. Since, in any system, the interface is a key regulator of system organization, behavior is proposed here as a unique and privileged level of control and (...) orchestration of brain structure and activity. This view has relevant scientific and clinical implications. First, the study of behavior represents a singular starting point for the investigation of neural activity in an integrated and comprehensive fashion. Second, behavioral changes, accomplished through psychotherapy or environmental interventions, are expected to have the highest impact to specifically reorganize the complexity of the human mind and thus achieve a solid and long-lasting improvement in mental health. (shrink)

In this essay I propose that what design principles in systems biology and systems neuroscience do is to present abstract characterizations of mechanisms, and thereby facilitate mechanistic explanation. To show this, one design principle in systems neuroscience, i.e., the multilayer perceptron, is examined. However, Braillard (2010) contends that design principles provide a sort of non-mechanistic explanation due to two related reasons: they are very general and describe non-causal dependence relationships. In response to this, I argue that, on the one hand, (...) all mechanisms are more or less general (or abstract), and on the other, many (if not all) design principles are causal systems. (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)

We provide two programmatic frameworks for integrating philosophical research on understanding with complementary work in computer science, psychology, and neuroscience. First, philosophical theories of understanding have consequences about how agents should reason if they are to understand that can then be evaluated empirically by their concordance with findings in scientific studies of reasoning. Second, these studies use a multitude of explanations, and a philosophical theory of understanding is well suited to integrating these explanations in illuminating ways.

This chapter provides a systematic overview of topological explanations in the philosophy of science literature. It does so by presenting an account of topological explanation that I (Kostić and Khalifa 2021; Kostić 2020a; 2020b; 2018) have developed in other publications and then comparing this account to other accounts of topological explanation. Finally, this appraisal is opinionated because it highlights some problems in alternative accounts of topological explanations, and also it outlines responses to some of the main criticisms raised by the (...) so-called new mechanists. (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 authors argue that their target is orthogonal to the realism and instrumentalist debate. I argue that it is born directly from it. While the distinction is helpful in illuminating how some ontological commitments demand a theory of implementation, it's less clear whether different views cleanly map onto the epistemic and metaphysical uses defined in the paper.

William James wrote that the life of religion “consists of the belief that there is an unseen order, and that our supreme good lies in harmoniously adjusting ourselves thereto.” Naturalism organizes our experiences of the universe within a science-grounded philosophical and/or religious framework aligning it with what is supremely good for our lives. This article describes a science-grounded specific “Framework of Spirituality” identifying part of this unseen order that opens a “spiritual core” within persons as a source of healing and (...) happiness. A cognitive behavioral therapy (CBT) expanded process shows how experiences of human worth and dignity are keys to this new awareness and provides speculation for a brain function and evolutionary explanation. Details of this knowledge are related to various perspectives and authors of naturalism—scientific, religious, ecstatic, and ecological—to contribute to a future direction for the understanding, development, and further expression of naturalism. (shrink)

I propose a dynamic causal approach to characterizing the notion of a mechanism. Levy and Bechtel, among others, have pointed out several critical limitations of the new mechanical philosophy, and pointed in a new direction to extend this philosophy. Nevertheless, they have not fully fleshed out what that extended philosophy would look like. Based on a closer look at neuroscientific practice, I propose that a mechanism is a dynamic causal system that involves various components interacting, typically nonlinearly, with one another (...) to produce a phenomenon of interest. (shrink)

Proponents of ontic conceptions of explanation require all explanations to be backed by causal, constitutive, or similar relations. Among their justifications is that only ontic conceptions can do justice to the ‘directionality’ of explanation, i.e., the requirement that if X explains Y , then not-Y does not explain not-X . Using topological explanations as an illustration, we argue that non-ontic conceptions of explanation have ample resources for securing the directionality of explanations. The different ways in which neuroscientists rely on multiplexes (...) involving both functional and anatomical connectivity in their topological explanations vividly illustrate why ontic considerations are frequently (if not always) irrelevant to explanatory directionality. Therefore, directionality poses no problem to non-ontic conceptions of explanation. (shrink)

In this Handbook entry, I review how colour similarity spaces are constructed, first for physical sources of colour and secondly for colour as it is perceptually experienced. The unique hues are features of one of the latter constructions, due initially to Hering and formalized in the Swedish Natural Colour System. I review the evidence for a physiological basis for the unique hues. Finally, I argue that Tye's realist approach to the unique hues is a mistake.

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)

Researchers in the cognitive sciences often seek neural correlates of psychological constructs. In this paper, I argue that even when these correlates are discovered, they do not always lead to reductive outcomes. To this end, I examine the psychological construct of a critical period and briefly describe research identifying its neural correlates. Although the critical period is correlated with certain neural mechanisms, this does not imply that there is a reductionist relationship between this psychological construct and its neural correlates. Instead, (...) this case study suggests that there may be many-to-many psychological-neural mappings, not just one-to-one or even one-to-many relations between psychological kinds and types of neural mechanisms. (shrink)

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

ABSTRACT LeDoux's pioneering work on the neurobiology of fear has played a crucial role in informing debates in the philosophy of emotion. For example, it plays a key part in Griffiths’ argument for why emotions don’t form a natural kind. Likewise, it is employed by Faucher and Tappolet to defend pro-emotion views, which claim that emotions aid reasoning. LeDoux, however, now argues that his work has been misread. He argues that using emotion terms, like ‘fear’, to describe neurocognitive data adds (...) a ‘surplus meaning’: it attributes phenomenal properties to survival circuits which they don’t possess. This paper aims to explore LeDoux's new proposal, and examine the potentially devastating consequences that ensue for the aforementioned views. I end by addressing the worry that these lessons are conditional on LeDoux's own higher-order theory of emotional consciousness being true. (shrink)

Since our moral and legal judgments are focused on our decisions and actions, one would expect information about the neural underpinnings of human decision-making and action-production to have a significant bearing on those judgments. However, despite the wealth of empirical data, and the public attention it has attracted in the past few decades, the results of neuroscientific research have had relatively little influence on legal practice. It is here argued that this is due, at least partly, to the discussion on (...) the relationship of the neurosciences and law mixing up a number of separate issues that have different relevance on our moral and legal judgments. The approach here is hierarchical; more and less feasible ways in which neuroscientific data could inform such judgments are separated from each other. The neurosciences and other physical views on human behavior and decision-making do have the potential to have an impact on our legal reasoning. However, this happens in various different ways, and too often appeal to any neural data is assumed to be automatically relevant to shaping our moral and legal judgments. Our physicalist intuitions easily favor neural-level explanations to mental-level ones. But even if you were to subscribe to some reductionist variant of physicalism, it would not follow that all neural data should be automatically relevant to our moral and legal reasoning. However, the neurosciences can give us indirect evidence for reductive physicalism, which can then lead us to challenge the very idea of free will. Such a development can, ultimately, also have repercussions on law and legal practice. (shrink)

In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I argue that (...) MVPA does not inherently provide a new answer to classical worries about reverse inference, and that the method faces pervasive interpretive problems of its own. Further, the epistemic setting of MVPA and other decoding methods contributes to a potentially worrisome shift towards prediction and away from explanation in fundamental neuroscience. (shrink)

This paper examines the explanatory distinctness of wiring optimization models in neuroscience. Wiring optimization models aim to represent the organizational features of neural and brain systems as optimal (or near-optimal) solutions to wiring optimization problems. My claim is that that wiring optimization models provide design explanations. In particular, they support ideal interventions on the decision variables of the relevant design problem and assess the impact of such interventions on the viability of the target system.

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

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

In their target article, Lynch, Parke, and O’Malley argue against the quick application of causal, interventionist explanatory frameworks to microbiomes and their purported role in many disparate states, from obesity to anxiety. I think the authors have undersold the force of their argument. A careful consideration of the scope of their claims, made easier by a parallel drawn from the history of explanation in neuroscience, yields a productive pessimism: that causal explanations likely operate at the wrong level of analysis for (...) dynamic, distributed, Quineian entities like the microbiome. That is, we shouldn’t expect causal explanations for microbiomes at all—and this includes the authors’ own “microbiome success story” of C. difficile. Neuroscience, with its own computationally challenging, dynamic entity—the brain—may provide lessons for how to approach something like predictive control over the microbiome. (shrink)

In the last couple of years, a few seemingly independent debates on scientific explanation have emerged, with several key questions that take different forms in different areas. For example, the questions what makes an explanation distinctly mathematical and are there any non-causal explanations in sciences (i.e., explanations that don’t cite causes in the explanans) sometimes take a form of the question of what makes mathematical models explanatory, especially whether highly idealized models in science can be explanatory and in virtue of (...) what they are explanatory. These questions raise further issues about counterfactuals, modality, and explanatory asymmetries: i.e., do mathematical and non-causal explanations support counterfactuals, and how ought we to understand explanatory asymmetries in non-causal explanations? Even though these are very common issues in the philosophy of physics and mathematics, they can be found in different guises in the philosophy of biology where there is the statistical interpretation of the Modern Synthesis theory of evolution, according to which the post-Darwinian theory of natural selection explains evolutionary change by citing statistical properties of populations and not the causes of changes. These questions also arise in philosophy of ecology or neuroscience in regard to the nature of topological explanations. The question here is can the mathematical (or more precisely topological) properties in network models in biology, ecology, neuroscience, and computer science be explanatory of physical phenomena, or are they just different ways to represent causal structures. The aim of this special issue is to unify all these debates around several overlapping questions. These questions are: are there genuinely or distinctively mathematical and non-causal explanations?; are all distinctively mathematical explanations also non-causal; in virtue of what they are explanatory; does the instantiation, implementation, or in general, applicability of mathematical structures to a variety of phenomena and systems play any explanatory role? This special issue provides a platform for unifying the debates around several key issues and thus opens up avenues for better understanding of mathematical and non-causal explanations in general, but also, it will enable even better understanding of key issues within each of the debates. (shrink)

La hipótesis del marcador somático (SMH) ha sido una de las teorías más influyentes en las neurociencias desde principios de los años 90s en que fue formulada por Antonio Damasio en su libro El error de Descartes (1994). Desde entonces, diversos estudios, a favor y en contra se han escrito, sin un veredicto. En este trabajo se propone una explicación abarcadora de lo que es la hipótesis del marcador somático. En segundo lugar, se hace una valoración sucinta del peso que (...) la amígdala pueda tener en el proceso de toma de decisiones inconscientes. En contraste, se citan algunos resultados que apuntan que la corteza prefrontal ventromedial estaría comprometida con nuestras decisiones racionales. Finalmente, se recuperan algunas críticas de otros investigadores a la hipótesis del marcador somático a partir de resultados mixtos obtenidos en el juego de azar y apuestas de Iowa. Se concluye que la mayor valía de la SMH es haber terminado con la dualidad cerebro-cuerpo, pero que la hipótesis por sí misma, no es suficiente para sostener que el proceso de toma de decisiones se realice principalmente a partir de lo que sentimos. El proceso de toma de decisiones, si bien se vale de respuestas inconscientes somatosensoriales, es un proceso físico-emocional-racional más complejo, que carece aún de suficientes evidencias para ser situado. The somatic marker hypothesis (SMH) has been one of the most influential theories in the neurosciences since the early 1990s, when it was formulated by Antonio Damasio in his book Descartes’ Error (1994). Since then, various studies, for and against, have been written without a verdict. Firstly, this study provides a comprehensive explanation of the SMH. Secondly, it provides a detailed assessment of the relevance of the amygdala in the process of making unconscious decisions. In contrast, we cite some results that suggest that the ventromedial prefrontal cortex would be involved in our rational decisions. Finally, we review some of the criticism of the SMH that was based on the mixed results obtained in the Iowa Gambling Task. We suggest that the main value of the SMH is that it resolves the brain-body duality problem. However, the hypothesis by itself is insufficient to claim that the decision-making process is mainly based on our feelings. Although the decision-making process uses unconscious somatosensory responses, it is a more complex physical-emotional-rational process, which still lacks sufficient evidence to be located. (shrink)

Debate about cognitive science explanations has been formulated in terms of identifying the proper level(s) of explanation. Views range from reductionist, favoring only neuroscience explanations, to mechanist, favoring the integration of multiple levels, to pluralist, favoring the preservation of even the most general, high-level explanations, such as those provided by embodied or dynamical approaches. In this paper, we challenge this framing. We suggest that these are not different levels of explanation at all but, rather, different styles of explanation that capture (...) different, cross-cutting patterns in cognitive phenomena. Which pattern is explanatory depends on both the cognitive phenomenon under investigation and the research interests occasioning the explanation. This reframing changes how we should answer the basic questions of which cognitive science approaches explain and how these explanations relate to one another. On this view, we should expect different approaches to offer independent explanations in terms of their different focal patterns and the value of those explanations to partly derive from the broad patterns they feature. (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)

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

It is a common idea, and an element in many legal systems, that people can deserve punishment when they commit criminal (or immoral) actions. A standard philosophical objection to this retributivist idea about punishment is that if human choices and actions are determined by previous events and the laws of nature, then we are not free in the sense required to be morally responsible for our actions, and therefore cannot deserve blame or punishment. It has recently been suggested that this (...) argument can be backed up by neuroscience, since neuroscientific explanations of human behavior leave no room for non-determined free actions. In this thesis, an argument of this sort is discussed. According to this argument, that I call “the Revision Argument”, we should revise the legal system so that any retributivist justification of punishment is removed. I examine some objections to the Revision Argument according to which compatibilism about free will and responsibility is a morally acceptable basis of retributive punishment. I argue that these objections have difficulties in providing a plausible account of the relevant difference between people who deserve punishment for their actions and people who do not. Therefore, I argue that they fail to refute the conclusion of the Revision Argument. (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)

Santiago Ramón y Cajal, the primary architect of the neuron doctrine and the law of dynamic polarization, is considered to be the founder of modern neuroscience. At the same time, many philosophers, historians, and neuroscientists agree that modern neuroscience embodies a mechanistic perspective on the explanation of the nervous system. In this paper, I review the extant mechanistic interpretation of Cajal’s contribution to modern neuroscience. Then, I argue that the extant mechanistic interpretation fails to capture the explanatory import of Cajal’s (...) law of dynamic polarization. My claim is that the definitive formulation of Cajal’s law of dynamic polarization, despite its mechanistic inaccuracies, embodies a non-mechanistic pattern of reasoning (i.e., design explanation) that is an integral component of modern neuroscience. (shrink)

I will review the most widely held account of phantom sensations; the “re-mapping hypothesis.” According to the re-mapping hypothesis, amputation is followed by significant neural reorganization that, over time, restores the alignment between the brain’s representation of and the actual condition of the body. Implicit in the re-mapping hypothesis is the view that the brain’s primary function is to accurately represent the body. In response, I propose an alternative theory, the “preservation hypothesis.” The preservation hypothesis argues that the primary function (...) of the brain is to preserve the entirety of the brain’s structures and functional capacities. While these issues concern empirical matters, assessing our views on the subject discloses deeply held assumptions regarding the brain’s primary function; does the brain operate to provide an accurate representation of the body? Or, does the brain operate solely to preserve its structures and functional capacities in their entirety? (shrink)

In fMRI research, the goal of correcting for multiple comparisons is to identify areas of activity that reflect true effects, and thus would be expected to replicate in future studies. Finding an appropriate balance between trying to minimize false positives (Type I error) while not being too stringent and omitting true effects (Type II error) can be challenging. Furthermore, the advantages and disadvantages of these types of errors may differ for different areas of study. In many areas of social neuroscience (...) that involve complex processes and considerable individual differences, such as the study of moral judgment, effects are typically smaller and statistical power weaker, leading to the suggestion that less stringent corrections that allow for more sensitivity may be beneficial, but also result in more false positives. Using moral judgment fMRI data, we evaluated four commonly used methods for multiple comparison correction implemented in SPM12 by examining which method produced the most precise overlap with results from a meta-analysis of relevant studies and with results from nonparametric permutation analyses. We found that voxel-wise thresholding with family-wise error correction based on Random Field Theory provides a more precise overlap (i.e., without omitting too few regions or encompassing too many additional regions) than either clusterwise thresholding, Bonferroni correction, or false discovery rate correction methods. (shrink)

In this paper, I argue that looking at the concept of neural function through the lens of cognition alone risks cognitive myopia: it leads neuroscientists to focus only on mechanisms with cognitive functions that process behaviorally relevant information when conceptualizing “neural function”. Cognitive myopia tempts researchers to neglect neural mechanisms with noncognitive functions which do not process behaviorally relevant information but maintain and repair neural and other systems of the body. Cognitive myopia similarly affects philosophy of neuroscience because scholars overlook (...) noncognitive functions when analyzing issues surrounding e.g., functional decomposition or the multifunctionality of neural structures. I argue that we can overcome cognitive myopia by adopting a patchwork approach that articulates cognitive and noncognitive “patches” of the concept of neural function. Cognitive patches describe mechanisms with causally specific effects on cognition and behavior which are likely operative in transforming sensory or other inputs into motor outputs. Noncognitive patches describe mechanisms that lack such specific effects; these mechanisms are enabling conditions for cognitive functions to occur. I use these distinctions to characterize two noncognitive functions at the mesoscale of neural circuits: subsistence functions like breathing are implemented by central pattern generators and are necessary to maintain the life of the organism. Infrastructural functions like gain control are implemented by canonical microcircuits and prevent neural system damage while cognitive processing occurs. By adding conceptual patches that describe these functions, a patchwork approach can overcome cognitive myopia and help us explain how the brain’s capacities as an information processing device are constrained by its ability to maintain and repair itself as a physiological apparatus. (shrink)