We outline a framework of multilevel neurocognitive mechanisms that incorporates representation and computation. We argue that paradigmatic explanations in cognitive neuroscience fit this framework and thus that cognitive neuroscience constitutes a revolutionary break from traditional cognitive science. Whereas traditional cognitive scientific explanations were supposed to be distinct and autonomous from mechanistic explanations, neurocognitive explanations aim to be mechanistic through and through. Neurocognitive explanations aim to integrate computational and representational functions and structures across multiple levels of organization (...) in order to explain cognition. To a large extent, practicing cognitive neuroscientists have already accepted this shift, but philosophical theory has not fully acknowledged and appreciated its significance. As a result, the explanatory framework underlying cognitive neuroscience has remained largely implicit. We explicate this framework and demonstrate its contrast with previous approaches. (shrink)

The third edition of a work that defines the field of cognitive neuroscience, with extensive new material including new chapters and new contributors.

This book investigates the philosophical, empirical, and theoretical bases on which a cognitive neuroscience of consciousness can be founded.

This volume is an unprecedented compilation of research papers from esteemed Russian psychophysiologists, cognitive scientists, and neuroscientists. It also provides a detailed exposition of Russian advances in neuropsychology and cognitive science from the late nineteenth century to the present.

We discuss the development of cognitive neuroscience in terms of the tension between the greater sophistication in cognitive concepts and methods of the cognitive sciences and the increasing power of more standard biological approaches to understanding brain structure and function. There have been major technological developments in brain imaging and advances in simulation, but there have also been shifts in emphasis, with topics such as thinking, consciousness, and social cognition becoming fashionable within the brain sciences. The discipline (...) has great promise in terms of applications to mental health and education, provided it does not abandon the cognitive perspective and succumb to reductionism. (shrink)

Working memory has been one of the most intensively studied systems in cognitive psychology. The Cognitive Neuroscience of Working Memory brings together world class researchers from around the world to summarise our current knowledge of this field, and directions for future research.

The Cognitive Neuroscience of Vision begins by introducing the reader to the anatomy of the eye and visual cortex and then proceeds to discuss image and...

This introductory chapter attempts to clarify the philosophical, empirical, and theoretical bases on which a cognitive neuroscience approach to consciousness can be founded. We isolate three major empirical observations that any theory of consciousness should incorporate, namely (1) a considerable amount of processing is possible without consciousness, (2) attention is a prerequisite of consciousness, and (3) consciousness is required for some specific cognitive tasks, including those that require durable information maintenance, novel combinations of operations, or the spontaneous generation (...) of intentional behavior. We then propose a theoretical framework that synthesizes those facts: the hypothesis of a global neuronal workspace. This framework postulates that, at any given time, many modular cerebral networks are active in parallel and process information in an unconscious manner. An information becomes conscious, however, if the neural population that represents it is mobilized by top-down attentional amplification into a brain-scale state of coherent activity that involves many neurons distributed throughout the brain. The long-distance connectivity of these `workspace neurons' can, when they are active for a minimal duration, make the information available to a variety of processes including perceptual categorization, long-term memorization, evaluation, and intentional action. We postulate that this global availability of information through the workspace is what we subjectively experience as a conscious state. A complete theory of consciousness should explain why some cognitive and cerebral representations can be permanently or temporarily inaccessible to consciousness, what is the range of possible conscious contents, how they map onto specific cerebral circuits, and whether a generic neuronal mechanism underlies all of them. We confront the workspace model with those issues and identify novel experimental predictions. Neurophysiological, anatomical, and brain-imaging data strongly argue for a major role of prefrontal cortex, anterior cingulate, and the areas that connect to them, in creating the postulated brain-scale workspace. (shrink)

"The Cognitive Neurosciences III is a magnificent accomplishment. It covers topics trom ions to consciousness, from reflexes to social psychology. ...

This paper argues that the fundamental problem of cognitive neuroscience arises from the neuronal description of the brain and the phenomenal description of the conscious mind. In general philosophers agree that no functional approach can explain phenomenal consciousness; some even think that science is forever unable to explain the qualitative character of our experiences. In order to overcome these challenges, I propose a distinction between intrinsic and extrinsic properties of the brain according to which brain states are characterized by (...) intrinsic properties, whereas the brain under the causal influence of an organism’s environment acquires extrinsic properties. These extrinsic properties may account for both phenomenal experiences as well as our thoughts about these experiences. At the end I discuss this proposal viability in relation to higher-order theories. (shrink)

This is a work in the epistemology of functional neuroimaging (fNI) and it applies the error-statistical (ES) philosophy to inferential problems in fNI to formulate and address these problems. This gives us a clear, accurate, and more complete understanding of what we can learn from fNI and how we can learn it. I review the works in the epistemology of fNI which I group into two categories; the first category consists of discussions of the theoretical significance of fNI findings and (...) the second category discusses methodological difficulties of fNI. Both types of works have shortcomings; the first category has been too theory-centered in its approach and the second category has implicitly or explicitly adopted the assumption that methodological difficulties of fNI cannot be satisfactorily addressed. In this dissertation, I address these shortcomings and show how and what kind of experimental knowledge fNI can reliably produce which would be theoretically significant. I take fMRI as a representative fNI procedure and discuss the history of its development. Two independent trajectories of research in physics and physiology eventually converge to give rise to fMRI. Thus, fMRI findings are laden in the theories of physics and physiology and I propose how this creates a kind of useful theory-ladenness which allows for the representation of and intervention in the constructs of cognitive neuroscience. Duhemian challenges and problems of underdetermination are often raised to argue that fNI is of little, if any, epistemic value for psychology. I show how the ES notions of severe tests and error probabilities can be applied in epistemological analyses of fMRI. The result is that hemodynamic hypotheses can be severely tested in fMRI experiments and I demonstrate how these hypotheses are theoretically significant and fuel the growth of experimental knowledge in cognitive neuroscience. Throughout this dissertation, I put the emphasis on the experimental knowledge we obtain from fNI and argue that this is the fruitful approach that enables us to see how fNI can contribute to psychology. In doing so, I offer an error-statistical epistemology of fNI, which hopefully will be a significant contribution to the philosophy of psychology. (shrink)

This book, a member of the Series in Affective Science, is a unique interdisciplinary sequence of articles on the cognitive neuroscience of emotion by some of ...

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

The “top-down” and “bottom-up” approaches have been thought to exhaust the possibilities for doing cognitive neuroscience. We argue that neither approach is likely to succeed in providing a theory that enables us to understand how cognition is achieved in biological creatures like ourselves. We consider a promising third way of doing cognitive neuroscience, what might be called the “neural dynamic systems” approach, that construes cognitive neuroscience as an autonomous explanatory endeavor, aiming to characterize in its own terms (...) the states and processes responsible for brain-based cognition. We sketch the basic motivation for the approach, describe a particular version of the approach, so-called ‘Dynamic Causal Modeling’ (DCM), and consider a concrete example of DCM. This third way, we argue, has the potential to avoid the problems that afflict the other two approaches. (shrink)

The problem of animal consciousness has profound implications on our concept of nature and of our place in the natural world. In philosophy of mind and cognitive neuroscience the problem of animal consciousness raises two main questions (Velmans, 2007): the distribution question (“are there conscious animals beside humans?”) and the phenomenological question (“what is it like to be a non-human animal?”). In order to answer these questions, many approaches take into account similarities and dissimilarities in animal and human behavior, (...) e.g. the use of language or tools and mirror self-recognition (Allen and Bekoff, 2007), however behavioral arguments don’t seem to be conclusive (Baars, 2005). Cognitive neuroscience is providing comparative data on structural and functional similarities, respectively called “homologies” and “analogies”. Many experimental results suggest that the thalamocortical system is essential for consciousness (Edelman and Tononi, 2000; Tononi, 2008). The argument from homology states that the general structure of thalamocortical system remained the same in the last 100-200 million years, for it is neuroanatomically similar in all the present and past mammals and it didn’t change much during phylogeny (Allen and Bekoff, 2007). The argument from analogy states that the key functional processes correlated with consciousness in humans are still present in all other mammals and many other animals (Baars, 2005). These processes are information integration through effective cortical connectivity (Massimini et al., 2005; Rosanova et al., 2012) and elaboration of information at a global level (Dehaene and Changeux, 2011). On this basis, the Cambridge Declaration on Consciousness states that all mammals, birds, and many other animals (such as octopuses) possess the neurological substrates of consciousness (Low et al., 2012). Conscious experience is private (Chalmers, 1995; Nagel, 1974) therefore the answer to the phenomenological question may be impossible. Nevertheless, cognitive neuroscience may provide an answer to the distribution question, showing that conscious experience is not limited to humans since it is a major biological adaptation going back millions of years. (shrink)

Consciousness seems to be an enigmatic phenomenon: it is difficult to imagine how our perceptions of the world and our inner thoughts, sensations and feelings could be related to the immensely complicated biological organ we call the brain. This volume presents the thoughts of some of the leading philosophers and cognitive scientists who have recently participated in the discussion of the status of consciousness in science. The focus of inquiry is the question: "Is it possible to incorporate consciousness into (...) science?" Philosophers have suggested different alternatives -- some think that consciousness should be altogether eliminated from science because it is not a real phenomenon, others that consciousness is a real, higher-level physical or neurobiological phenomenon, and still others that consciousness is fundamentally mysterious and beyond the reach of science. At the same time, however, several models or theories of the role of conscious processing in the brain have been developed in the more empirical cognitive sciences. It has been suggested that non-conscious processes must be sharply separated from conscious ones, and that the necessity of this distinction is manifested in the curious behavior of certain brain-damaged patients. This book demonstrates the dialogue between philosophical and empirical points of view. The writers present alternative solutions to the brain-consciousness problem and they discuss how the unification of biological and psychological sciences could thus become feasible. Covering a large ground, this book shows how the philosophical and empirical problems are closely interconnected. From this interdisciplinary exploration emerges the conviction that consciousness can and should be a natural part of our scientific world view. (shrink)

In recent years there have been growing calls for forging greater connections between education and cognitive neuroscience. As a consequence great hopes for the application of empirical research on the human brain to educational problems have been raised. In this article we contend that the expectation that results from cognitive neuroscience research will have a direct and immediate impact on educational practice are shortsighted and unrealistic. Instead, we argue that an infrastructure needs to be created, principally through interdisciplinary (...) training, funding and research programs that allow for bidirectional collaborations between cognitive neuroscientists, educators and educational researchers to grow. We outline several pathways for scaffolding such a basis for the emerging field of ‘Mind, Brain and Education’ to flourish as well as the obstacles that are likely to be encountered along the path. (shrink)

This article reviews concepts of, as well as neurocognitive and genetic studies on, empathy. Whereas cognitive empathy can be equated with affective theory of mind, that is, with mentalizing the emotions of others, affective empathy is about sharing emotions with others. The neural circuits underlying different forms of empathy do overlap but also involve rather specific brain areas for cognitive (ventromedial prefrontal cortex) and affective (anterior insula, midcingulate cortex, and possibly inferior frontal gyrus) empathy. Furthermore, behavioral and imaging (...) genetic studies provide evidence for a genetic basis for empathy, indicating a possible role for oxytocin and dopamine as well as for a genetic risk variant for schizophrenia near the gene ZNF804A. (shrink)

Music offers a unique opportunity to better understand the organization of the human brain. Like language, music exists in all human societies. Like language, music is a complex, rule-governed activity that seems specific to humans, and associated with a specific brain architecture. Yet unlike most other high-level functions of the human brain - and unlike language - music is a skill at which only a minority of people become proficient. The study of music as a major brain function has for (...) some time been relatively neglected. Just recently, however, we have witnessed an explosion in research activities on music perception and performance and their correlates in the human brain. This volume brings together an outstanding collection of international authorities - from the fields of music, neuroscience, psychology, and neurology - to describe the amazing advances being made in understanding the complex relationship between music and the brain. Aimed at psychologists and neuroscientists, this is a book that will lay the foundations for a cognitive neuroscience of music. (shrink)

This chapter provides an overview of the basic research strategies and analytic techniques deployed in computational cognitive neuroscience. On the one hand, “top-down” strategies are used to infer, from formal characterizations of behavior and cognition, the computational properties of underlying neural mechanisms. On the other hand, “bottom-up” research strategies are used to identify neural mechanisms and to reconstruct their computational capacities. Both of these strategies rely on experimental techniques familiar from other branches of neuroscience, including functional magnetic resonance imaging, (...) single-cell recording, and electroencephalography. What sets computational cognitive neuroscience apart, however, is the explanatory role of analytic techniques from disciplines as varied as computer science, statistics, machine learning, and mathematical physics. These techniques serve to describe neural mechanisms computationally, but also to drive the process of scientific discovery by influencing which kinds of mechanisms are most likely to be identified. For this reason, understanding the nature and unique appeal of computational cognitive neuroscience requires not just an understanding of the basic research strategies that are involved, but also of the formal methods and tools that are being deployed, including those of probability theory, dynamical systems theory, and graph theory. (shrink)

How do cognitive neuroscientists explain phenomena like memory or language processing? This book examines the different kinds of experiments and manipulative research strategies involved in understanding and eventually explaining such phenomena. Against this background, it evaluates contemporary accounts of scientific explanation, specifically the mechanistic and interventionist accounts, and finds them to be crucially incomplete. Besides, mechanisms and interventions cannot actually be combined in the way usually done in the literature. This book offers solutions to both these problems based on (...) insights from experimental practice. It defends a new reading of the interventionist account, highlights the importance of non-interventionist studies for scientific inquiry, and supplies a taxonomy of experiments that makes it easy to see how the gaps in contemporary accounts of scientific explanation can be filled. The book concludes that a truly empirically adequate philosophy of science must take into account a much wider range of experimental research than has been done to date. With the taxonomy provided, this book serves a stepping-stone leading into a new era of philosophy of science—for cognitive neuroscience and beyond. (shrink)

The greatest contemporary challenge in the arena of cognitive neuroscience concerns the relation between consciousness and the brain. Over recent years the focus of work in this area has switched from the analysis of diverse spatial regions of the brain to that of the timing of neural events. It appears that two conditions are necessary in order for neural events to become correlated with conscious experience. First, the firing of assemblies of neurones must achieve a degree of coherence, and, (...) second, reflexive (i.e. top-down, or reentrant) neural pathways must be activated. It does not, of course, follow that such neural activity causes consciousness; it may be, for example, that the neural activity formats the brain to interact with consciousness. The latter possibility is suggested by analysis of mystical texts suggesting that coherence and reflexivity constitute the conditions for the influx of “spirit.” Kabbalistic sources, for example, describe a hierarchy of “brains” in the human and divine realms through which the principles of coherence and reflexivity operate. Whilst the ontological assumptions of such a scheme place it beyond the realm of psychology, parallels with the picture deriving from the contemporary cognitive neuroscience of consciousness are striking. (shrink)

Recent years have seen the emergence of a new interdisciplinary field called embodied or enactive cognitive science. Whereas traditional representationalism rests on a fixed inside–outside distinction, the embodied cognition perspective views mind and brain as a biological system that is rooted in body experience and interaction with other individuals. Embodiment refers to both the embedding of cognitive processes in brain circuitry and to the origin of these processes in an organism’s sensory–motor experience. Thus, action and perception are no (...) longer interpreted in terms of the classic physical–mental dichotomy, but rather as closely interlinked. This paper describes the cycles of brain–organism interaction, of sensory–motor interaction with the environment and of embodied interaction with others. The brain is then interpreted as an organ of modulation and transformation that mediates the cycles of organism–environment interaction. Finally, consequences of the embodied and enactive approach for psychiatry are pointed out, in particular for a circular concept of mental illness. (shrink)

The combination of ethnographic and cognitive neuroscience research provides considerable insight into the origin and symbolism of Native Californian rock art. Although made by different social groups for different purposes in various parts of the state, the ethnographic record demonstrates that the art depicts the mental imagery and somatic hallucinations of trance, taken to represent supernatural experiences. When this art is viewed from a cognitive neuroscience perspective, it suggests that the shamanistic state of consciousness was far from primarily (...) "ecstatic," instead often involving the generation of unpleasant emotions; and that biochemical changes during trance necessitated the making of rock art if the memory of these supernatural experiences was to be preserved. (shrink)

Generalized anxiety disorder (GAD) and social phobia (SP) are major anxiety disorders identified by the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV). They are comorbid, overlap in symptoms, yet present with distinct features (worry in GAD and fear of embarrassment in SP). Both have also been explained in terms of conditioning-based models. However, there is little reasoning currently to believe that GAD in adulthood reflects heightened conditionability or heightened threat processing—though patients with SP may show heightened processing (...) of social threat stimuli. Moreover, the computational architectures that maintain these disorders in adulthood are different. For GAD this may reflect the development of an inefficient “worrying” strategy of emotional regulation. For SP this appears to reflect the atypical processing of self-referential information. (shrink)

In this article, I review recent findings in cognitive neuroscience in learning, particularly in the learning of mathematics and of reading. I argue that while cognitive neuroscience is in its infancy as a field, theories of learning will need to incorporate and account for this growing body of empirical data.

The perception and cognition of art, a venture done effortlessly by all members of our species, is a complicated affair in which visual perception, brain structures, sensory reasoning, and aesthetic evaluation are made in less time that it takes to read this sentence. Only recently, through perceptual/brain studies, have we begun to understand the many neurological sub-routines involved in visual perception. The discoveries made in cognitive neuroscience laboratories have helped us better understand the perception of everyday visual phenomena, including (...) the perception of art. In addition, cognitive neuroscientists have provided techniques and instruments which are valuable in the study of the psychology of art. In this paper I give an overview of the past research which has advanced our understanding of how people process visual art. In addition the results of a preliminary study of an accomplished artist as he drew a portrait while in an MRI machine are presented. (shrink)

Cognitive neuroscience increasingly relies on complex data analysis methods. Researchers in this field come from highly diverse scientific backgrounds, such as psychology, engineering, and medicine. This poses challenges with respect to acquisition of appropriate scientific computing and data analysis skills, as well as communication among researchers with different knowledge and skills sets. Are researchers in cognitive neuroscience adequately equipped to address these challenges? Here, we present evidence from an online survey of methods skills. Respondents (n= 307) mainly comprised (...) students and post-doctoral researchers working in the cognitive neurosciences. Multiple choice questions addressed a variety of basic and fundamental aspects of neuroimaging data analysis, such as signal analysis, linear algebra, and statistics. We analyzed performance with respect to the following factors: undergraduate degree (grouped into Psychology, Methods, and Biology), current researcher status (undergraduate student, PhD student, and post-doctoral researcher), gender, and self-rated expertise levels. Overall accuracy was 72%. Not surprisingly, the Methods group performed best (87%), followed by Biology (73%) and Psychology (66%). Accuracy increased from undergraduate (59%) to PhD (74%) level, but not from PhD to post-doctoral (74%) level. The difference in performance for the Methods vs. non-methods (Psychology/Biology) groups was especially striking for questions related to signal analysis and linear algebra, two areas particularly relevant to neuroimaging research. Self-rated methods expertise was not strongly predictive of performance. The majority of respondents (93%) indicated they would like to receive at least some additional training on the topics covered in this survey. In conclusion, methods skills among junior researchers in cognitive neuroscience can be improved, researchers are aware of this, and there is strong demand for more skills-oriented training opportunities. We hope that this survey will provide an empirical basis for the development of bespoke skills-oriented training programs in cognitive neuroscience institutions. We will provide practical suggestions on how to achieve this. (shrink)

This chapter discusses neurocognitive work relevant to moral psychology and the proposition that innate factors make important contributions to moral judgment. It reviews various sources of evidence for an innate moral faculty, before presenting brain-imaging data in support of the same conclusion. It is argued that our moral thought is the product of an interaction between some ‘gut-reaction’ moral emotions and our capacity for abstract reflection.

It is by now a well-supported hypothesis in cognitive neuroscience that there exists a functional network for the moral appraisal of situations. However, there is a surprising disagreement amongst researchers about the significance of this network for moral actions, decisions, and behavior. Some researchers suggest that we should uncover those ethics [that are built into our brains ], identify them, and live more fully by them, while others claim that we should often do the opposite, viewing the cognitive (...) neuroscience of morality more like a science of pathology. To analyze and evaluate the disagreement, this paper will investigate some of its possible sources. These may include theoretical confusions about levels of explanation in cognitive science, or different senses of ‘morality’ that researchers are looking to explain. Other causes of the debate may come from empirical assumptions about how possible or preferable it is to separate intuitive moral appraisal from moral decisions. Although we will tentatively favor the ‘Set Aside’ approach, the questions outlined here are open areas of ongoing research, and this paper will be confined to outlining the position space of the debate rather than definitively resolving it. (shrink)

The nine chapters of this book, written by leading authorities in their fields, cover major topics in cognitive neuroscience, including noninvasive measurement ...

Could "cognitive neuroscience" be an oxymoron? "Cognitive" and "neuroscience" cohere only to the extent that the entities identified as "cognitive" can be coordinated with entities identified as neural. This coordination is typically construed as intertheoretic reduction between "levels" of scientific description. On the cognitive side, folk psychological concepts crystallize into behavioral taxonomies, which are further analyzed into purported cognitive capacities. These capacities are expressed or operationalized in paradigmatic experimental tasks. These cogs comprise a stable ontology, (...) sustaining more than a century of psychology. On the neural side, the biological hierarchy from cells to brains also affords a . (shrink)

In this article, I develop an account of the use of intentional predicates in cognitive neuroscience explanations. As pointed out by Maxwell Bennett and Peter Hacker, intentional language abounds in neuroscience theories. According to Bennett and Hacker, the subpersonal use of intentional predicates results in conceptual confusion. I argue against this overly strong conclusion by evaluating the contested language use in light of its explanatory function. By employing conceptual resources from the contemporary philosophy of science, I show that although (...) the use of intentional predicates in mechanistic explanations sometimes leads to explanatorily inert claims, intentional predicates can also successfully feature in mechanistic explanations as tools for the functional analysis of the explanandum phenomenon. Despite the similarities between my account and Daniel Dennett's intentional-stance approach, I argue that intentional stance should not be understood as a theory of subpersonal causal explanation, and therefore cannot be used to assess the explanatory role of intentional predicates in neuroscience. Finally, I outline a general strategy for answering the question of what kind of language can be employed in mechanistic explanations. (shrink)

In this article, I review recent findings in cognitive neuroscience in learning, particularly in the learning of mathematics and of reading. I argue that while cognitive neuroscience is in its infancy as a field, theories of learning will need to incorporate and account for this growing body of empirical data.

Study of “theory of mind” in nonhuman primates is hampered both by the lack of rigorous methodology that Heyes stresses and by our lack of knowledge of the cognitive neuroscience of nonhuman primate conceptual structure. Recent advances in this field indicate that progress can be made by first asking simpler research questions.