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)

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

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)

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

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

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)

_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 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)

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)

The aim of this paper is to examine the usefulness of the Machamer, Darden, and Craver (2000) mechanism approach to gaining an understanding of explanation in cognitive neuroscience. We argue that although the mechanism approach can capture many aspects of explanation in cognitive neuroscience, it cannot capture everything. In particular, it cannot completely capture all aspects of the content and significance of mental representations or the evaluative features constitutive of psychopathology.

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)

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

History of Cognitive Neuroscience documents the major neuroscientific experiments and theories over the last century and a half in the domain of cognitive neuroscience, and evaluates the cogency of the conclusions that have been drawn from them. Provides a companion work to the highly acclaimed Philosophical Foundations of Neuroscience – combining scientific detail with philosophical insights Views the evolution of brain science through the lens of its principal figures and experiments Addresses philosophical criticism of Bennett (...) and Hacker?s previous book Accompanied by more than 100 illustrations. (shrink)

Myin, Erik (2000) Direct Self-Consciousness (2)Bermúdez, José Luis (2000) Concepts and the Priority Principle (10)Bermúdez, José Luis (2000) Circularity, "I"-Thoughts and the Linguistic Requirement for Concept Possession (11)Meeks, Roblin R. (2000) Withholding Immunity: Misidentification, Misrepresentation, and Autonomous Nonconceptual Proprioceptive First-Person Content (12)Newen, Albert (2001) Kinds of Self-Consciousness (13)Bermudez, Jose Luis (2000) Direct Self-Consciousness (4)Bermudez, Jose Luis (2000) Prelinguistic Self-Consciousness (5)Gallese, Vittorio (2000) The Brain and the Self: Reviewing the Neuroscientific Evidence (6)Bermudez, Jose Luis (2000) The Cognitive Neuroscience of (...) Primitive Self-Consciousness (7) [Currently Displayed]Robbins, Philip (2000) Paradox Twice Lost (8)Fuller, Gary and Slater, Carol W. (2000) "I"-Thoughts: Criteria, Constitution, and Concept Possession (9)Evans, Cedric Oliver (2000) Prelinguistic Self-Consciousness (3)Bermudez, Jose Luis and Polytechnique, CREA Ecole (1999) The Paradox of Self-Consciousness (representation and Mind) (1). (shrink)

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)

It is becoming ever more accepted that investigations of mind span the brain, body, and environment. To broaden the scope of what is relevant in such investigations is to increase the amount of data scientists must reckon with. Thus, a major challenge facing scientists who study the mind is how to make big data intelligible both within and between fields. One way to face this challenge is to structure the data within a framework and to make it intelligible by means (...) of a common theory. Radical embodied cognitive neuroscience can function as such a framework, with dynamical systems theory as its methodology, and self-organized criticality as its theory. (shrink)

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...

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)

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)

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)

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.

Krueger & Funder (K&F) describe social cognitive research as being flawed by its emphasis on performance errors and biases. They argue that a perspective shift is necessary to give balance to the field. However, such a shift may already be occurring with the emergence of social cognitive neuroscience leading to new theories and research that focus on normal social cognition.

When the cognitive neuroscience of consciousness is finally written, it will likely have many of the elements documented in this fine book. My review is relatively detailed because, out of fourteen authors of the eight articles in this book, only four have previously appeared in the Journal of Consciousness Studies. Stanislas Dehaene , The Cognitive Neuroscience of Consciousness Cambridge, MA: MIT Press, 2001, pp. 243 price $40.00 ISBN 0-262-54131-9.

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)

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)

Reliability in Cognitive Neuroscience: A Meta-Meta Analysis. . ???aop.label???. doi: 10.1080/09515089.2013.838818.

Pseudo‐mechanistic explanations in psychology and cognitive neuroscienceThis paper focuses on the level of systems/cognitive neuroscience. It argues that the great majority of explanations in psychology and cognitive neuroscience is “pseudo‐mechanistic.” On the basis of various case studies, Hommel argues that cognitive neuroscience should move beyond what he calls an “Aristotelian phase” to become a mature “Galilean” science seeking to discover actual mechanisms of cognitive phenomena.

We situate the debate on intentionality within the rise of cognitive neuroscience and argue that cognitive neuroscience can explain intentionality. We discuss the explanatory significance of ascribing intentionality to representations. At first, we focus on views that attempt to render such ascriptions naturalistic by construing them in a deflationary or merely pragmatic way. We then contrast these views with staunchly realist views that attempt to naturalize intentionality by developing theories of content for representations in terms of (...) information and biological function. We echo several other philosophers by arguing that these theories over-generalize unless they are constrained by a theory of the functional role of representational vehicles. This leads to a discussion of the functional roles of representations, and how representations might be realized in the brain. We argue that there’s work to be done to identify a distinctively mental kind of representation. We close by sketching a way forward for the project of naturalizing intentionality. This will not be achieved simply by ascribing the content of mental states to generic neural representations, but by identifying specific neural representations that explain the puzzling intentional properties of mental states. (shrink)

In this article, I compare the epistemic standing of the function-to-structure inferences found in cognitive neuroscience and of the inferences based on dissociations in neuropsychology. I argue that the former have a poorer epistemic standing than the latter.

This chapter contains sections titled: Is Simulation a Natural Category? Simulation and Respects of Similarity Simulation and Motor Cognition Simulation and Face‐based Emotion Attribution Simulation is a Robust and Theoretically Interesting Category References.

Might we have an instinctive tendency to perform helpful actions? This paper explores a model under development in cognitive neuroscience that enables us to understand what instinctive, helpful actions might look like. The account that emerges puts some pressure on key concepts in the philosophical understanding of folk psychology. In developing the contrast, a notion of embodied beliefs is introduced; it arguably fits folk conceptions better than philosophical ones. One upshot is that Humean insights into the role of (...) empathy and instinct in the production of helpful actions are affirmed. (shrink)

Understanding purpose and intent requires attention to our experience of time. Cognitive neuroscientific research into the functional and neural substrates of higher cognitive functions have direct bearing on the experience of temporal ordering. Consciousness, located within the short span of working memory, is made cognitively possible and evolutionarily valuable by biological constraints in time. These constraints, including our longevity, make thought about more extended events both possible and useful. Such cognitive processes, rooted in the neurophysiology of cortical (...) function, are a sine qua non for the construction of meaning, relationship, morality, and purposes that may extend beyond our mortality. Research in the cognitive neurosciences is overviewed, and implications are discussed for questions of mortality, design and intention, the reconstruction of meaning, and the experience of eternity. (shrink)

The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprised of networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons and the (...) neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena. (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.

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)

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.

Up to the 1960s, psychology was deeply under the influence of behaviourism, which focused on stimuli and responses, and regarded consideration of what may happen in the mind as unapproachable scientifically. This began to change with the devising of methods to try to tap into what was going on in the 'black box' of the mind, and the development of 'cognitive psychology'. With the study of patients who had suffered brain damage or injury to limited parts of the brain, (...) outlines of brain components and processes began to take shape, and by the end of the 1970s, a new science, cognitive neuroscience, was born. But it was with the development of ways of accessing activation of the working brain using imaging techniques such as PET and fMRI that cognitive neuroscience came into its own, as a science cutting across psychology and neuroscience, with strong connections to philosophy of mind. Experiments involving subjects in scanners while doing various tasks, thinking, problem solving, and remembering are shedding light on the brain processes involved. The research is exciting and new, and often makes media headlines. But there is much misunderstanding about what brain imaging tells us, and the interpretation of studies on cognition. In this Very Short Introduction Richard Passingham, a distinguished cognitive neuroscientist, gives a provocative and exciting account of the nature and scope of this relatively new field, and the techniques available to us, focusing on investigation of the human brain. He explains what brain imaging shows, pointing out common misconceptions, and gives a brief overview of the different aspects of human cognition: perceiving, attending, remembering, reasoning, deciding, and acting. Passingham concludes with a discussion of the exciting advances that may lie ahead.ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable. (shrink)