The popularization of neuroscientific ideas about learning—sometimes legitimate, sometimes merely commercial—poses a real challenge for classroom teachers who want to understand how children learn. Until teacher preparation programs are reconceived to incorporate relevant research from the neuro- and cognitive sciences, teachers need translation and guidance to effectively use information about the brain and cognition. Absent such guidance, teachers, schools, and school districts may waste time and money pursuing so called brain-based interventions that lack a firm basis in research. Meanwhile, the (...) success of our schools will continue to be narrowly defined by achievement standards that ignore knowledge of the neural and cognitive processes of learning. To achieve the goals of neuroeducation, its proponents must address unique ethical issues that neuroeducation raises for five different groups of individuals: a) practicing teachers, b) neuroscience researchers whose work could inform education, c) publishers and the popular media, d) educational policy-makers, and e) university-level teacher educators. We suggest ways in which these ethical challenges can be met and provide a model for teacher preparation that will enable teachers themselves to translate findings from the neuro-and cognitive sciences and use legitimate research to inform how they design and deliver effective instruction. (shrink)

Nobody in this debate questions the point that neuroeconomics remains full of potential, and little else as yet. If so, that really is progress of sorts. I was getting afraid that we would have to open nominations for the Captain Ahab Award for obsessive work on the promotion of neuroeconomics.

Nobody in this debate questions the point that neuroeconomics remains full of potential, and little else as yet. If so, that really is progress of sorts. I was getting afraid that we would have to open nominations for the Captain Ahab Award for obsessive work on the promotion of neuroeconomics.

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)

Milner and Goodale's Two Visual Systems Hypothesis is regarded as common ground in recent discussions of visual consciousness. A central part of TVSH is a functional model of vision and action. In this paper, I provide a brief overview of these current discussions and argue that there is ambiguity between a strong and a weak version of PAM. I argue that, given a standard way of individuating computational mechanisms, the available evidence cannot be used to distinguish between these versions. This (...) not only has consequences for philosophical theories of the role of visual consciousness but also for the role of experimental evidence in model testing in cognitive neuroscience. (shrink)

While there is much evidence for the influence of automatic emotional responses on moral judgment, the roles of reflection and reasoning remain uncertain. In Experiment 1, we induced subjects to be more reflective by completing the Cognitive Reflection Test prior to responding to moral dilemmas. This manipulation increased utilitarian responding, as individuals who reflected more on the CRT made more utilitarian judgments. A follow-up study suggested that trait reflectiveness is also associated with increased utilitarian judgment. In Experiment 2, subjects considered (...) a scenario involving incest between consenting adult siblings, a scenario known for eliciting emotionally driven condemnation that resists reasoned persuasion. Here, we manipulated two factors related to moral reasoning: argument strength and deliberation time. These factors interacted in a manner consistent with moral reasoning: A strong argument defending the incestuous behavior was more persuasive than a weak argument, but only when increased deliberation time encouraged subjects to reflect. (shrink)

Reverse inference in cognitive neuropsychology has been characterized as inference to ‘psychological processes’ from ‘patterns of activation’ revealed by functional magnetic resonance or other scanning techniques. Several arguments have been provided against the possibility. Focusing on Machery’s presentation, we attempt to clarify the issues, rebut the impossibility arguments, and propose and illustrate a strategy for reverse inference. 1 The Problem of Reverse Inference in Cognitive Neuropsychology2 The Arguments2.1 The anti-Bayesian argument3 Patterns of Activation4 Reverse Inference Practiced5 Seek and Ye Shall (...) Find, Maybe6 Conclusion. (shrink)

The central task of cognitive neuroscience to map cognitive capacities to neural mechanisms faces three interlocking conceptual problems that together frame the problem of cognitive ontology. First, they must establish which tasks elicit which cognitive capacities, and specifically when different tasks elicit the same capacity. To address this operationalization problem, scientists often assess whether the tasks engage the same neural mechanisms. But to determine whether mechanisms are of the same or different kinds, we need to solve the abstraction problem by (...) determining which mechanistic differences are and are not relevant, and also the boundary problem by distinguishing the mechanism from its background conditions. Solving these problems, in turn, requires understanding how cognitive capacities are elicited in tasks. These three problems, which have been noted and discussed elsewhere in the literature, together form a ‘cycle of kinds’ that frames the central problem-space of cognitive ontology. We describe this cycle to clarify the intellectual challenges facing the cognitive ontologist and to reveal the kind of iterative process by which ontological revision in cognitive neuroscience is likely to unfold. (shrink)

Recent studies indicate that patients who are diagnosed with vegetative states may retain more awareness than their clinical assessments suggest. Disorders of consciousness traditionally have been diagnosed on the basis of outwardly observable behaviors alone, but new functional imaging studies have shown surprising levels of brain activity in some patients, indicating that even higher-level cognitive functions like language processing and visual imagery may be preserved. For example, one recently developed method purports to detect voluntary mental imagery solely on the basis (...) of neural response patterns observed with functional magnetic resonance imaging. This line of research has already led to some widely reported cases of patients who were discovered to have more brain activity than expected. In November 2009, Rom Houben, a Belgian man who was thought to be in a coma for 23 years, was diagnosed with locked-in syndrome through the use of neuroimaging; however, that assessment was later overturned by further testing. (shrink)

The neuroscientific investigation of sex differences has an unsavoury past, in which scientific claims reinforced and legitimated gender roles in ways that were not scientifically justified. Feminist critics have recently argued that the current use of functional neuroimaging technology in sex differences research largely follows that tradition. These charges of ‘neurosexism’ have been countered with arguments that the research being done is informative and valuable and that an over-emphasis on the perils, rather than the promise, of such research threatens to (...) hinder scientific progress. To investigate the validity of these contrasting concerns, recent functional magnetic resonance imaging (fMRI) investigations of sex differences and citation practices were systematically examined. In line with the notion of neurosexism, the research was found to support the influence of false-positive claims of sex differences in the brain, to enable the proliferation of untested, stereotype-consistent functional interpretations, and to pay insufficient attention to the potential plasticity of sex differences in both brain and mind. This, it is argued, creates a literature biased toward the presentation of sex differences in the brain as extensive, functionally significant, and fixed—and therefore implicitly supportive of a gender essentialist perspective. It is suggested that taking feminist criticisms into account would bring about substantial improvement in the quality of the science, as well as a reduction in socially harmful consequences. (shrink)

A leading theoretical framework for naturalistic explanation of mind holds that we explain the mind by positing progressively "stupider" capacities ("homunculi") until the mind is "discharged" by means of capacities that are not intelligent at all. The so-called homuncular fallacy involves violating this procedure by positing the same capacities at subpersonal levels. I argue that the homuncular fallacy is not a fallacy, and that modern-day homunculi are idle posits. I propose an alternative view of what naturalism requires that reflects how (...) the cognitive sciences are actually integrating mind and matter. (shrink)

This article clarifies three principles that should guide the development of any cognitive ontology. First, that an adequate cognitive ontology depends essentially on an adequate task ontology; second, that the goal of developing a cognitive ontology is independent of the goal of finding neural implementations of the processes referred to in the ontology; and third, that cognitive ontologies are neutral regarding the metaphysical relationship between cognitive and neural processes.

The intriguing issue of pain and suffering in patients with disorders of consciousness (DOCs), particularly in Unresponsive Wakefulness Syndrome/Vegetative State (UWS/VS) and Minimally Conscious State (MCS), is assessed from a theoretical point of view, through an overview of recent neuroscientific literature, in order to sketch an ethical analysis. In conclusion, from a legal and ethical point of view, formal guidelines and a situationist ethics are proposed in order to best manage the critical scientific uncertainty about pain and suffering in DOCs (...) and ensure the best possible care for the patient. (shrink)

Since the mid‐1980s, psychologists and neuroscientists have used brain imaging to test hypotheses about human thought processes and their neural instantiation. In just three decades, functional neuroimaging has been transformed from a crude clinical tool to a widely used research method for understanding the human brain and mind. Such rapidly achieved success is bound to evoke skepticism. A degree of skepticism toward new methods and ideas is both inevitable and useful in any field. It is especially valuable in a science (...) as young as cognitive neuroscience and its even younger siblings, social and affective neuroscience. Healthy skepticism encourages us to check our assumptions, recognize the limitations of our methods, and proceed thoughtfully. Skepticism itself, however, also must be examined.In this article, I review the most commonly voiced criticisms of functional neuroimaging. In the spirit of healthy skepticism, I will critically examine these criticisms themselves. Each contains at least a kernel of truth, although I will argue that in some cases the kernel has been overextended in ways that are inaccurate or misleading. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

The current view of the relationship between areas of the mind-brain sciences is one where cross-disciplinary collaboration is required to advance claims about the mind-brain that stand on firm epistemic footing. My goal in this dissertation is to analyze what it means for information from different areas of science to fit together to produce strong epistemic claims by addressing how and to what extent claims about the mind-brain are corroborated in scientific practice. Philosophers of science have advanced various concepts of (...) the notion of fitting together information from different areas of science and its relation to scientific progress (e.g., Bickle, 1998, 2003, 2006; Darden and Maull, 1977; Mitchell, 2002, 2003; Mitchell and Dietrich, 2006; Nagel 1949, 1970, 1979; Piccinini and Craver, 2011; and Roskies, 2010). However, each concept of fitting together is vague and subject to multiple clarificatory questions. To get a handle on the notion of fitting together, I introduce the term ‘interdisciplinary corroboration’ as a placeholder for the various accounts of fitting together to facilitate my investigation of how claims about the mind-brain are corroborated in scientific practice. I argue review papers are a good place to begin analyzing interdisciplinary corroboration; accordingly, I conduct a two-part analysis of a review paper by Eichenbaum (2013) entitled ‘Memory on Time’. I use the lessons from my analysis to develop and advance a methodology for philosophers of science interested in knowledge production for evaluating review papers for corroboration in the mind-brain sciences. (shrink)

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

This PhD thesis focuses on the philosophical foundations of Neuroeconomics, an innovative research program which combines findings and modelling tools from economics, psychology and neuroscience to account for human choice behaviour. The proponents of Neuroeconomics often manifest the ambition to foster radical modifications in the accounts of choice behaviour developed by its parent disciplines. This enquiry provides a philosophically informed appraisal of the potential for success and the relevance of neuroeconomic research for economics. My central claim is that neuroeconomists can (...) help other economists to build more predictive and explanatory models, yet are unlikely to foster revolutionary modifications in the economic theory of choice. The contents are organized as follows. In chapters 1-2, I present neuroeconomists’ investigative tools, distinguish the most influential approaches to neuroeconomic research and reconstruct the case in favour of a neural enrichment of economic theory. In chapters 3-7, I combine insights from neuro-psychology, economic methodology and philosophy of science to develop a systematic critique of Neuroeconomics. In particular, I articulate four lines of argument to demonstrate that economists are provisionally justified in retaining a methodologically distinctive approach to the modelling of decision making. My first argument points to several evidential and epistemological concerns which complicate the interpretation of neural data and cast doubt on the inferences neuroeconomists often make in their studies. My second argument aims to show that the trade-offs between the modelling desiderata that neuroeconomists and other economists respectively value severely constrain the incorporation of neural insights into economic models. My third argument questions neuroeconomists’ attempts to develop a unified theory of choice behaviour by identifying some central issues on which they hold contrasting positions. My fourth argument differentiates various senses of the term ‘revolution’ and illustrates that neuroeconomists are unlikely to provide revolutionary contributions to economic theory in any of these senses. (shrink)

Does a diagnosis of brain dysfunction matter for ascriptions of moral responsibility? This chapter argues that, while knowledge of brain pathology can inform judgments of moral responsibility, its evidential value is currently limited for a number of practical and theoretical reasons. These include the problem of establishing causation from correlational data, drawing inferences about individuals from group data, and the reliance of the interpretation of brain findings on well-established psychological findings. Brain disorders sometimes matter for moral responsibility, however, because they (...) change an individual’s moral psychology in a way that is beyond their control. While control over psychological changes is not an excusing factor, brain disorders can mitigate moral responsibility because they confront individuals with new psychological deficits or urges for which their previous moral education and existing external and internal moral resources have not prepared them. (shrink)

The aim of this article is to discuss the conditions under which functional neuroimaging can contribute to the study of higher cognition. We begin by presenting two case studies—on moral and economic decision making—which will help us identify and examine one of the main ways in which neuroimaging can help advance the study of higher cognition. We agree with critics that functional magnetic resonance imaging (fMRI) studies seldom “refine” or “confirm” particular psychological hypotheses, or even provide details of the neural (...) implementation of cognitive functions. However, we suggest that neuroimaging can support psychology in a different way—namely, by selecting among competing hypotheses of the cognitive mechanisms underlying some mental function. One of the main ways in which neuroimaging can be used for hypothesis selection is via reverse inferences, which we here examine in detail. Despite frequent claims to the contrary, we argue that successful reverse inferences do not assume any strong or objectionable form of reductionism or functional locationism. Moreover, our discussion illustrates that reverse inferences can be successful at early stages of psychological theorizing, when models of the cognitive mechanisms are only partially developed. (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)

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

Recent advancements in the brain sciences have enabled researchers to determine, with increasing accuracy, patterns and locations of neural activation associated with various psychological functions. These techniques have revived a longstanding debate regarding the relation between the mind and the brain: while many authors now claim that neuroscientific data can be used to advance our theories of higher cognition, others defend the so-called `autonomy' of psychology. Settling this significant question requires understanding the nature of the bridge laws used at the (...) psycho-neural interface. While these laws have been the topic of extensive discussion, such debates have mostly focused on a particular type of link: reductive laws. Reductive laws are problematic: they face notorious philosophical objections and they are too scarce to substantiate current research at the interface of psychology and neuroscience. The aim of this article is to provide a systematic analysis of a different kind of bridge laws--associative laws--which play a central, albeit often overlooked, role in scientific practice. (shrink)

Neuroimaging technology is the most widely used tool to study human cognition. While originally a promising tool for mapping the content of cognitive theories onto the structures of the brain, recently developed tools for the analysis, handling and sharing of data have changed the theoretical landscape of cognitive neuroscience. Even with these advancements philosophical analyses of evidence in neuroimaging remain skeptical of the promise of neuroimaging technology. These views often treat the analysis techniques used to make sense of data produced (...) in a neuroimaging experiment as one, attributing the inferential limitations of analysis pipelines to the technology as a whole. Situated against the neuroscientists own critical assessment of their methods and the limitations of those methods, this skepticism appears based on a misunderstanding of the role data analysis techniques play in neuroimaging research. My project picks up here, examining how data analysis techniques, such as pattern classification analysis, are used to assess the evidential value of neuroimaging data. The project takes the form of three papers. In the first I identify the use of multiple data analysis techniques as an important aspect of the data interpretation process that is overlooked by critics. In the second I develop an account of inferences in neuroimaging research that is sensitive to this use of data analysis techniques, arguing that interpreting neuroimaging data is a process of isolating and explaining a variety of data patterns. In the third I argue that the development and uptake of new techniques for analyzing data must be accompanied by changes in research practices and standards of evidence if they are to promote knowledge generation. My approach to this work is both traditionally philosophical, insofar as it involves reading and analyzing the work of philosophers and neuroscientists, and embedded insofar as most of the research was conducted while engaged in attending lab meetings and participating in the work of those scientists whose work is the object of my research. (shrink)

Neuroscience is a fascinating discipline – its dynamic progress has led to the emergence of new interdisciplinary research programmes with great potential. One of these research areas is neuroeconomics. As will be shown in this article, this discipline, which is difficult to clearly characterize and define, is faced with many problems. This paper argues that social scientists should be interested in the problems and tendencies in social neuroscience for several reasons. Neuroeconomics, and other disciplines inspired by neuroscience, will compete with (...) their parent disciplines in many fields of interest. On one hand it will be necessary for scientists to define and defend the irreplaceable roles of their disciplines, but also critically evaluate the potential of new approaches on the other. In the context of this discussion, which reopens questions about the scientific status of economics and its roles, this paper introduces the main problems related to neuroeconomics. This paper concludes that these problems represent a wide domain for social scientists and methodologists of science. (shrink)

This paper considers the practical question of why people do not behave in the way they ought to behave. This question is a practical one, reaching both into the normative and descriptive domains of morality. That is, it concerns moral norms as well as empirical facts. We argue that two main problems usually keep us form acting and judging in a morally decent way: firstly, we make mistakes in moral reasoning. Secondly, even when we know how to act and judge, (...) we still fail to meet the requirements due to personal weaknesses. This discussion naturally leads us to another question: can we narrow the gap between what people are morally required to do and what they actually do? We discuss findings from neuroscience, economics, and psychology, considering how we might bring our moral behavior better in line with moral theory. Potentially fruitful means include nudging, training, pharmacological enhancement, and brain stimulation. We conclude by raising the question of whether such methods could and should be implemented. (shrink)

Research has consistently shown that people consider harmful side effects of an action more intentional than helpful side effects. This phenomenon is known as the side- effect effect (SEE), which refers to the influence of moral considerations in judgments of intentionality and other non-moral concepts. There is an ongoing debate about how to explain this asymmetric pattern of judgment and the psychological factors involved in it. It has been posited that affective reactions to agents that bring about harmful side- effects (...) could bias intentionality attributions in these cases, explaining the asymmetric pattern of intentionality judgments that we observe in the SEE. We call this the affective bias hypothesis (ABH). Evidence for the ABH is mixed, with some findings suggesting a role for affective processes, while others suggesting that affective processes play no role in the SEE. A possible explanation for these apparently contradictory results points to affective processes involved in the SEE being confined to anger. In a series of empirical studies, we systematically measured and manipulated participants’ anger in order to test this possibility. Our findings suggest that anger play no role in intentionality judgments in SEE cases, while providing support for a non-emotional motivation to blame as a factor underlying the SEE. (shrink)

The study of psychological mechanisms is an interdisciplinary endeavour, requiring insights from many different domains. In this article, I argue that philosophy plays an essential role in this interdisciplinary project, and that effective scientific study of psychological mechanisms requires that working scientists be responsible metaphysicians. This means adopting deliberate metaphysical positions when studying mechanisms that go beyond what is empirically justified regarding the nature of the phenomenon being studied, the conditions of its occurrence, and its boundaries. Such metaphysical commitments are (...) necessary in order to set up experimental protocols, determine which variables to manipulate under experimental conditions, and which conclusions to draw from different scientific models and theories. It is important for scientists to be aware of the metaphysical commitments they adopt, since they can easily be led astray if invoked carelessly. (shrink)

La eclosión de las neurodisciplinas está conectada con el amplio y creciente uso de neuroimágenes en neurociencia cognitiva, en particular de las obtenidas mediante resonancia magnética funcional. Sin embargo, la aplicación de estudios sobre el cerebro basados en esta técnica a la filosofía, la ética o el derecho, entre otros campos, no es tan clara como a veces se supone y encuentra importantes limitaciones.