Sam Harris (2010) argues that, given our neurology, we can experience well-being, and that seeking to maximize this state lets us distinguish the good from the bad. He takes our ability to compare degrees of well-being as his starting point, but I think that the analysis can be pushed further, since there is a (non-religious) reason why well-being is desirable, namely the finite life of an individual organism. It is because death is a constant possibility that things can be assessed (...) as “for” or “against” one (Champagne 2011a; Smith 2000). Such an account lets us objectively adjudicate moral questions, as Harris desires. However, by anchoring itself in the mortal body as a whole and not just the brain, such an account dampens the claim that neuroscience would have all the answers. Moreover, it pivots on an affirmation of one’s life that can seem mysterious by regular scientific standards. This chapter thus explains why the trade-off is worthwhile. (shrink)

Many activities in Cognitive Science involve complex computer models and simulations of both theoretical and real entities. Artificial Intelligence and the study of artificial neural nets in particular, are seen as major contributors in the quest for understanding the human mind. Computational models serve as objects of experimentation, and results from these virtual experiments are tacitly included in the framework of empirical science. Cognitive functions, like learning to speak, or discovering syntactical structures in language, have been modeled and these models (...) are the basis for many claims about human cognitive capacities. Artificial neural nets (ANNs) have had some successes in the field of Artificial Intelligence, but the results from experiments with simple ANNs may have little value in explaining cognitive functions. The problem seems to be in relating cognitive concepts that belong in the `top-down' approach to models grounded in the `bottom-up' connectionist methodology. Merging the two fundamentally different paradigms within a single model can obfuscate what is really modeled. When the tools (simple artificial neural networks) to solve the problems (explaining aspects of higher cognitive functions) are mismatched, models with little value in terms of explaining functions of the human mind are produced. The ability to learn functions from data-points makes ANNs very attractive analytical tools. These tools can be developed into valuable models, if the data is adequate and a meaningful interpretation of the data is possible. The problem is, that with appropriate data and labels that fit the desired level of description, almost any function can be modeled. It is my argument that small networks offer a universal framework for modeling any conceivable cognitive theory, so that neurological possibility can be demonstrated easily with relatively simple models. However, a model demonstrating the possibility of implementation of a cognitive function using a distributed methodology, does not necessarily add support to any claims or assumptions that the cognitive function in question, is neurologically plausible. (shrink)

Esencjalistycznie zorientowani teoretycy emocji uważają, że emocje mają swoją istotę. Nie istnieje jednak zgoda co do tego, czym ona jest. Dla jednych substancją emocji jest poznanie lub oceny, dla innych zmiany fizjologiczno-cielesne, a jeszcze dla innych zdarzenia w mózgu. W artykule prezentuję najważniejsze argumenty przeciwko tym teoriom, a następnie prezentuję wieloskładnikową i wielofunkcyjną koncepcję emocji.

Science requires postformal capabilities to compare competing explanations and conceptualize how to coordinate or integrate them. With conflicts thus reconciled, science advances. The Model of Hierarchical Complexity facilitates the coordination of current arguments about intelligence. A cross-species measurement theory of comparative cognition is proposed. It has potential to overcome the lack of a general measurement theory for the science of comparative cognition, and the lack of domain-general mechanisms for evolutionary psychologists. The hierarchical complexity of concepts and debates as well as (...) the new theory are scored, and demonstrate the postformal hierarchical complexity of the proposed theory. (shrink)

© 2006 Konrad Lorenz Institute for Evolution and Cognition Research.

Cognitive neuroscience has come to be viewed as the flagship of the cognitive sciences and is transforming our understanding of the nature of mind. In this paper we survey several research fields in cognitive neuroscience (lateralization, neuroeconomics, and cognitive control) and note that they are making rapid progress on fundamental issues. Lateralization research is developing a comparative framework for evolutionary analysis, and is identifying individual- and population-level factors that favor brain asymmetries. Neuroeconomics is creating a research framework for studying valuation (...) mechanisms in the brain that allows investigation of more complex phenomena than traditional reward paradigms. And cognitive control research has cast light on the mechanisms of task learning and top-down control that enable fluid goal-directed behavior in complex situations. Reasons for the success of cognitive neuroscience are varied: technical advances (e.g., in molecular genetics and imaging) are part of the story, but the more important factors have to do with the power of integrating a bottom-up mechanistic approach with larger functional and evolutionary perspectives. The incorporation of a bottom-up component differentiates cognitive neuroscience from the multidisciplinary ambitions of classical cognitive science, which suffered from having limited access to mechanisms. (shrink)

Animal models are used in experiments in the behavioural neurosciences that aim to contribute to the prevention and treatment of cognitive and affective disorders in human beings, such as anxiety and depression. Ironically, those animals that are likely to be the best models for psychopathology are also likely to be considered the ones that are most morally problematic to use, if it seems probable that (and if indeed they are initially selected as models because) they have experiences that are similar (...) to human experiences that we have strong reasons to avoid causing, and indeed aim to alleviate (such as pain, anxiety or sadness). In this paper, against the background of contemporary discussions in animal ethics and the philosophy of animal minds, we discuss the views that it is morally permissible to use animals in these kinds of experiments, and that it is better to use less cognitively complex animals (such as zebrafish) than more complex animals (such as dogs). First, we criticise some justifications for the claim that human beings and more complex animals have higher moral status. We argue that contemporary approaches that attribute equal moral status to all beings that are capable of conscious strivings (e.g. avoiding pain and anxiety; aiming to eat and play) are based on more plausible assumptions. Second, we argue that it is problematic to assume that less cognitively complex animals have a lesser sensory and emotional experience than more complex beings across the board. In specific cases, there might be good reasons to assume that more complex beings would be harmed more by a specific physical or environmental intervention, but it might also be that they sometimes are harmed less because of a better ability to cope. Determining whether a specific experiment is justified is therefore a complex issue. Our aim in this chapter is to stimulate further reflection on these common assumptions behind the use of animal models for psychopathologies. In order to be able to draw more definite conclusions, more research will have to be done on the influence of cognitive complexity on the experience of (human and non-human) animals. (shrink)

The neurosciences seem to thrive on the constantly postponed promise to herald a definitive understanding of the human mind. What are the dynamics of this promise and its postponement? The long and fascinating history of the neurosciences offers ample material for looking into the articulation of neuroscientific research and contemporary culture. New tools and research methods, often announced as breakthroughs, brought along new representations of brain activity. In addition, they shaped the way of conceptualizing the brain’s mode of operation even (...) where they failed to meet the high expectations initially kindled. Rather than arriving at a definitive and final understanding of human nature by solving the riddle of the human brain, the neurosciences appear to operate as active interfaces mobilizing human societies to ever new research endeavors. (shrink)

Neuroscience research examining sex/gender differences aims to explain behavioral differences between men and women in terms of differences in their brains. Historically, this research has used ad hoc methods and has been conducted explicitly in order to show that prevailing gender roles were dictated by biology. I examine contemporary fMRI research on sex/gender differences in emotion processing and argue that it, too, both uses problematic methods and, in doing so, reinforces gender stereotypes.

Much of cognitive science is committed to the modular approach to the study of cognition. The core of this approach consists of a pair of assumptions - the anatomical and the functional modularity assumptions - which motivate two kinds of inference: the anatomical and the functional modularity inferences. The legitimacy of both of these inferences has been strongly challenged, a situation that has had surprisingly little impact on most theorizing in the field. Following the introduction of an important, yet rarely (...) made, distinction between two functional concepts - the distinction between cognitive working and cognitive role - this paper analyses these kinds of inference, and refocuses the attention on new aspects of their main limitations. It is argued that both the anatomical and functional modularity inferences can, and do, operate in three distinct modes in contemporary cognitive science, and that seeing this is essential to understanding both the power and the limitations of these methodological tools. (shrink)

This essay introduces the massive redeployment hypothesis, an account of the functional organization of the brain that centrally features the fact that brain areas are typically employed to support numerous functions. The central contribution of the essay is to outline a middle course between strict localization on the one hand, and holism on the other, in such a way as to account for the supporting data on both sides of the argument. The massive redeployment hypothesis is supported by case studies (...) of redeployment, and compared and contrasted with other theories of the localization of function. (shrink)

Abstract: The massive redeployment hypothesis (MRH) is a theory about the functional topography of the human brain, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components-originally developed to serve some specific purpose-were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs. If the (...) evolution of cognition was indeed driven by such exaptation, then we should be able to make some specific empirical predictions regarding the resulting functional topography of the brain. This essay discusses three such predictions, and some of the evidence supporting them. Then, using this account as a background, the essay considers the implications of these findings for an account of the functional integration of cognitive operations. For instance, MRH suggests that in order to determine the functional role of a given brain area it is necessary to consider its participation across multiple task categories, and not just focus on one, as has been the typical practice in cognitive neuroscience. This change of methodology will motivate (even perhaps necessitate) the development of a new, domain-neutral vocabulary for characterizing the contribution of individual brain areas to larger functional complexes, and direct particular attention to the question of how these various area roles are integrated and coordinated to result in the observed cognitive effect. Finally, the details of the mix of cognitive functions a given area supports should tell us something interesting not just about the likely computational role of that area, but about the nature of and relations between the cognitive functions themselves. For instance, growing evidence of the role of “motor” areas like M1, SMA and PMC in language processing, and of “language” areas like Broca’s area in motor control, offers the possibility for significantly reconceptualizing the nature both of language and of motor control. (shrink)

To accept that cognition is embodied is to question many of the beliefs traditionally held by cognitive scientists. One key question regards the localization of cognitive faculties. Here we argue that for cognition to be embodied and sometimes embedded, means that the cognitive faculty cannot be localized in a brain area alone. We review recent research on neural reuse, the 1/f structure of human activity, tool use, group cognition, and social coordination dynamics that we believe demonstrates how the boundary between (...) the different areas of the brain, the brain and body, and the body and environment is not only blurred but indeterminate. In turn, we propose that cognition is supported by a nested structure of task-specific synergies, which are softly assembled from a variety of neural, bodily, and environmental components (including other individuals), and exhibit interaction dominant dynamics. (shrink)

The social and cognitive science replication crisis is partly due to the limitations of commonly used statistical tools. Inferential statistics require that unsystematic measurement variation is independent of system history, and weak relative to systematic or causal sources of variation. However, contemporary systems research underscores the dynamic, adaptive nature of social, cognitive, and behavioral systems. Variation in human activity includes the influences of intrinsic dynamics intertwined with changing contextual circumstances. Conventional inferential techniques presume milder forms of variability, such as unsystematic (...) measurement error, as in a Gaussian distribution. Inferential statistics indicate an elementary Newtonian cause-effect metaphor for change that is inconsistent with known principles of change in complex systems. Pattern formation in self-organizing systems and quantum probability are used to illustrate theoretical metaphors that instantiate alternative notions of change in complex systems. Inferential statistics and related techniques are crucial scientific resources. However, in the social and behavioral sciences, they must be practiced in conjunction with an appropriate general systems framework that accommodates intrinsic fluctuations and contextual adaptation. (shrink)

Considerable methodological difficulties abound in neuroimaging, and several philosophers of science have recently called into question the potential of neuroimaging studies to contribute to our knowledge of human cognition. These skeptical accounts suggest that functional hypotheses are underdetermined by neuroimaging data. I apply Mayo’s error-statistical account to clarify the evidential import of neuroimaging data and the kinds of inferences it can reliably support. Thus, we can answer the question “What can we reliably learn from neuroimaging?” and make sense of how (...) this knowledge can contribute to novel construals of cognition. (shrink)

Several developments for diverse scientific goals, mostly in physics and physiology, had to take place, which eventually gave us fMRI as one of the central research paradigms of contemporary cognitive neuroscience. This technique stands on solid foundations established by the physics of magnetic resonance and the physiology of hemodynamics and is complimented by computational and statistical techniques. I argue, and support using concrete examples, that these foundations give rise to a productive theory-ladenness in fMRI, which enables researchers to identify and (...) control for the types of methodological and inferential errors. Consequently, this makes it possible for researchers to represent and investigate cognitive phenomena in terms of hemodynamic data and for experimental knowledge to grow independently of large scale theories of cognition. (shrink)

In our response, we clarify important theoretical differences between basic emotion and psychological construction approaches. We evaluate the empirical status of the basic emotion approach, addressing whether it requires brain localization, whether localization can be observed with better analytic tools, and whether evidence for basic emotions exists in other types of measures. We then revisit the issue of whether the key hypotheses of psychological construction are supported by our meta-analytic findings. We close by elaborating on commentator suggestions for future research.

I reject Lindquist et al.'s implicit claim that all emotion theories other than constructionist ones subscribe to a “brain locationist” approach. The neural mechanisms underlying relevance detection, reward, attention, conceptualization, or language use are consistent with many theories of emotion, in particular componential appraisal theories. I also question the authors' claim that the meta-analysis they report provides support for thespecificassumptions of constructionist theories.

Lindquist et al. convincingly argue that the brain implements psychological operations that are constitutive of emotion rather than modules subserving discrete emotions. However, thenatureof such psychological operations is open to debate. I argue that considering appraisal theories may provide alternative interpretations of the neuroimaging data with respect to the psychological operations involved.

The third issue of the Journal for the Philosophy of Language, Mind and the Arts is centered on a series of questions related to the nature of images. What properties characterize them? Do they exist also in our minds? What relationship do they have with phenomena such as perception, memory, language and interpretation? The authors participating in this issue have been asked to answer these and other questions starting from and in dialogue with the two philosophical perspectives that have most (...) enriched the study of our object of research since the second half of the twentieth century: analytical philosophy and visual culture studies. The first four essays address problems related to ontology (Didi-Huberman, Prinz, Bantinaki, Manzotti). In their pages the question will be asked not only about the nature of images but also about what it means for an image to represent an object or an action realistically. The second part contains discussions related to the topics of perception, appreciation and creation of pictures (Ferretti; Gavaler, Goldberg; Pigoni, Coraci, Carlenzi). The third section goes through the problems related to the very concept of representing by images (Biggs; Weichert; Derby). The last section of the issue is devoted to two cases in which images are used not so much and not only to represent something, but also to convey ethical-political values (Fasnacht; Olesiejuk). (shrink)

The posterior cortex, hippocampus, and prefrontal cortex in the Leabra architecture are specialized in terms of various neural parameters, and thus are predilections for learning and processing, but domain-general in terms of cognitive functions such as face recognition. Also, these areas are not encapsulated and violate Fodorian criteria for modularity. Anderson's terminology obscures these important points, but we applaud his overall message.

Neuroscience is a laboratory-based science that spans multiple levels of analysis from molecular genetics to behavior. At every level of analysis experiments are designed in order to answer empirical questions about phenomena of interest. Understanding the nature and structure of experimentation in neuroscience is fundamental for assessing the quality of the evidence produced by such experiments and the kinds of claims that are warranted by the data. This article provides a general conceptual framework for thinking about evidence and experimentation in (...) neuroscience with a particular focus on two research areas: cognitive neuroscience and cognitive neurobiology. (shrink)

In this chapter I investigate the kinds of changes that psychiatric kinds undergo when they become explanatory targets of areas of sciences that are not “mature” and are in the early stages of discovering mechanisms. The two areas of science that are the targets of my analysis are cognitive neuroscience and cognitive neurobiology.

When Fodor titled his (1983) book the _Modularity of Mind_, he overstated his position. His actual view is that the mind divides into systems some of which are modular and others of which are not. The book would have been more aptly, if less provocatively, called _The Modularity of Low-Level Peripheral Systems_. High-level perception and cognitive systems are non-modular on Fodor’s theory. In recent years, modularity has found more zealous defenders, who claim that the entire mind divides into highly specialized (...) modules. This view has been especially popular among Evolutionary Psychologists. They claim that the mind is massively modular (Cosmides and Tooby, 1994; Sperber, 1994; Pinker, 1997; see also Samuels, 1998). Like a Swiss Army Knife, the mind is an assembly of specialized tools, each of which has been designed for some particular purpose. My goal here is to raise doubts about both peripheral modularity and massive modularity. To do that, I will rely on the criteria for modularity laid out by Fodor (1983). I will argue that neither input systems, nor central systems are modular on any of these criteria. (shrink)

According to a widespread view, a complete explanatory reduction of all aspects of the human mind to the electro-chemical functioning of the brain is at hand and will certainly produce vast and positive cultural, political and social consequences. However, notwithstanding the astonishing advances generated by the neurosciences in recent years for our understanding of the mechanisms and functions of the brain, the application of these findings to the specific but crucial issue of human agency can be considered a “pre-paradigmatic science” (...) (in Thomas Kuhn’s sense). This implies that the situation is, at the same time, intellectually stimulating and methodologically confused. More specifically—because of the lack of a solid, unitary and coherent methodological framework as to how to connect neurophysiology and agency—it frequently happens that tentative approaches, bold but very preliminary claims and even clearly flawed interpretations of experimental data are taken for granted. In this article some examples of such conceptual confusions and intellectual hubris will be presented, which derive from the most recent literature at the intersection between neurosciences, on the one hand, and philosophy, politics and social sciences, on the other hand. It will also be argued that, in some of these cases, hasty and over-ambitious conclusions may produce negative social and political consequences. The general upshot will be that very much has still to be clarified as to what and how neurosciences can tell us about human agency and that, in the meantime, intellectual and methodological caution is to be recommended. (shrink)

Language research is currently in a state of flux. The phenomenon of language is not merely the topic of investigation in linguistics, it is examined by a multitude of scholars with different scientific backgrounds. In order to examine how these various disciplines approach language, a think-tank was founded in 2002, called DITO, Dynamisch Inter(-en trans)disciplinair onderzoek, or Dynamic Inter- (and trans)disciplinary Research. The think-tank is located at the Belgian Vrije Universiteit Brussel (Free University of Brussels). This book provides short introductory (...) articles to the language research conducted by some of the think-tank’s most important members, from within the point of view of the following 5 disciplines: philosophy of evolutionary biology, cognitive science, neuroscience, sign language research and artificial intelligence. (shrink)

Tracing the leading role of emotions in the evolution of the mind, a philosopher and a psychologist pair up to reveal how thought and culture owe less to our faculty for reason than to our capacity to feel. Many accounts of the human mind concentrate on the brain’s computational power. Yet, in evolutionary terms, rational cognition emerged only the day before yesterday. For nearly 200 million years before humans developed a capacity to reason, the emotional centers of the brain were (...) hard at work. If we want to properly understand the evolution of the mind, we must explore this more primal capability that we share with other animals: the power to feel. Emotions saturate every thought and perception with the weight of feelings. The Emotional Mind reveals that many of the distinctive behaviors and social structures of our species are best discerned through the lens of emotions. Even the roots of so much that makes us uniquely human—art, mythology, religion—can be traced to feelings of caring, longing, fear, loneliness, awe, rage, lust, playfulness, and more. From prehistoric cave art to the songs of Hank Williams, Stephen T. Asma and Rami Gabriel explore how the evolution of the emotional mind stimulated our species’ cultural expression in all its rich variety. Bringing together insights and data from philosophy, biology, anthropology, neuroscience, and psychology, The Emotional Mind offers a new paradigm for understanding what it is that makes us so unique. (shrink)

Given that visualisations via medical imaging have tremendously increased over the last decades, the overall presence of colour-coded brain slices generated on the basis of functional imaging, i.e. neuroimaging techniques, have led to the assumption of so-called kinds of brains or cognitive profiles that might be especially related to non-healthy humans affected by neurological, neuropsychological or psychiatric syndromes or disorders. In clinical contexts especially, one must consider that visualisations through medical imaging are suggestive in a twofold way. Imaging data not (...) only visually render pathological entities, but also tend to represent objective and concrete evidence for these psychophysical states in question. This article aims to identify key issues in visually rendering psychiatric disorders via functional approaches of imaging within the neurosciences from an epistemological point of view. (shrink)

The neurosciences are generating new findings regarding genetic and neurobiological aspects of the pathophysiology of mental disorders. Especially, certain genetic risk factors like neuregulin-1 seem to predispose individuals to a psychotic phenotype beyond the limits of traditional classificatory boundaries between organic psychoses in Alzheimer’s disease, bipolar affective disorder and schizophrenia. Little, however, is known about how such genetic risk factors actually confer an increased risk for psychosis in an individual patient. A gap between neuroscientific findings and psychopathological phenomena exists. The (...) main hypothesis how this gap may be bridged is that mental disorders arise as a consequence of dysfunctions of normal mental functions. Modularity may provide a useful conceptual framework in that temporally and/or spatially stable neural circuits subserve certain physiological functions of the human brain, which become the target of pathophysiological effectors. The idea of a modular construction of the human brain is based on neurobiological evidence regarding the columnar architecture of the cerebral cortex, which provides certain elementary analytical functions. Modular dysfunctions may be assessed with methods of experimental psychopathology, in which subsystems of brain functions are tested with standardized experimental psychological techniques (functional psychopathology). The main questions here are how to define a module, and whether the classical neuroscientific definitions can be used to characterize higher integrative functions of the human brain. (shrink)

The sceptical positions philosophers have adopted with respect to neuroimaging data are based on detailed evaluations of subtraction, which is one of many data analysis techniques used with neuroimaging data. These positions are undermined when the epistemic implications of the use of a diversity of data analysis techniques are taken into account. I argue that different data analysis techniques reveal different patterns in the data. Through the use of multiple data analysis techniques, researchers can produce results that are locally robust. (...) Thus, the epistemology of neuroimaging must take into consideration the details of the different data analysis techniques that are used to evaluate neuroimaging data, and the specific theoretical aims those techniques are deployed towards. _1_ Introduction _2_ Scepticism about Neuroimaging _3_ Data Analysis and Evidence _4_ Deconvolution and Pattern Classification Analysis _4.1_ Deconvolution analysis _4.2_ Region of interest selection _4.3_ Pattern classification analysis _5_ The Strength of Multiple Analyses _6_ Conclusion. (shrink)

Fodor's thinking on modularity has been influential throughout a range of the areas studying cognition, chiefly as a prod for positive work on modularity and domain-specificity. In _The Mind Doesn't Work That Way_, Fodor has developed the dark message of _The Modularity of Mind_ regarding the limits to modularity and computational analyses. This paper offers a critical assessment of Fodor's scepticism with an eye to highlighting some broader issues in play, including the nature of computation and the role of recent (...) empirical developments in the cognitive sciences in assessing Fodor's position. (shrink)

This paper surveys some recent work on realization in the philosophy of mind and the philosophy of science.

If personhood is the quality or condition of being an individual person, brainhood could name the quality or condition of being a brain. This ontological quality would define the `cerebral subject' that has, at least in industrialized and highly medicalized societies, gained numerous social inscriptions since the mid-20th century. This article explores the historical development of brainhood. It suggests that the brain is necessarily the location of the `modern self', and that, consequently, the cerebral subject is the anthropological figure inherent (...) to modernity (at least insofar as modernity gives supreme value to the individual as autonomous agent of choice and initiative). It further argues that the ideology of brainhood impelled neuroscientific investigation much more than it resulted from it, and sketches how an expanding constellation of neurocultural discourses and practices embodies and sustains that ideology. (shrink)

La resonancia magnética funcional es una de las técnicas de neuroimagen más difundidas en las neurociencias cognitivas. Su influencia tuvo un rol central en la configuración del aspecto experimental de este campo. Frente a esto, consideramos que su estatus como evidencia no ha sido suficientemente discutido en la literatura filosófica. En este trabajo nos centramos sobre este punto abordando el problema clásico de definir el alcance que puede tener la estrategia localizacionista en neurociencias. Atendemos al modo en que este problema (...) se manifiesta hoy, tomando algunos ejemplos recientes de abordajes neurocientíficos caracterizados por estudiar el carácter dinámico de la actividad a gran escala en el cerebro. Tomamos en cuenta un número de limitaciones que presenta la resonancia magnética funcional, distinguiendo aquellas cuyo tratamiento pone en juego problemáticas de una índole no meramente técnica. A partir del análisis de algunas maneras en que los investigadores les hacen frente, sostenemos que existe una medida importante en que este tipo de estudios de neuroimagen pueden ser orientados sobre la base de supuestos y consideraciones teóricas generales. Concluimos que esta particular permeabilidad teórica de la resonancia magnética funcional es un factor central que incide sobre su estatus como evidencia neurocientífica. (shrink)

The field of cognitive imaging is explodingboth in terms of the amount of our scientificresources dedicated to it and the associatedpublication rate. However, all of this effortis based on a critical question – Do cognitivemodules exist? Both of the reviewers of my book(Uttal, 2001) and I agree that this questionhas not yet been satisfactorily answered and,depending on the ultimate answer, the cognitiveimaging approach as well as some other parts ofthe quest for mechanistic models of mind mightnot be successful. Our views (...) of how our scienceshould respond to this serious problem,however, are quite different. Both ProfessorBechtel and Lloyd argue for an optimisticattack on the problem of the localization ofcognitive processes in the brain based on thehistory of other sciences. I argue that arealistic appreciation of the limits of thisapproach should temper the enthusiasm for whatultimately will go the way of other attempts tounravel the mind-brain problem. (shrink)

In distinguishing itself from other distributed approaches to cognition, Anderson's theory of neural reuse is susceptible to some of the same criticisms that have been leveled at modular approaches. Specifically, neural reuse theories state that: (1) the of a given brain circuit is fixed, rather than shaped by its input, and (2) that high-level cognitive behaviors can be cleanly mapped onto a specific set of brain circuits in a non-contextualized manner.

The past decade has witnessed a growing awareness of conceptual and methodological hurdles within psychology and neuroscience that must be addressed for taxonomic and explanatory progress in understanding psychological functions to be possible. In this paper, I evaluate several recent knowledge-building initiatives aimed at overcoming these obstacles. I argue that while each initiative offers important insights about how to facilitate taxonomic and explanatory progress in psychology and neuroscience, only a “coordinated pluralism” that incorporates positive aspects of each initiative will have (...) the potential for success. (shrink)

The commentators expressed concerns regarding the relevance and value of non-computational non-symbolic explanations of cognitive performance. But what counts as an “explanation” depends on the pre-theoretical assumptions behind the scenes of empirical science regarding the kinds of variables and relationships that are sought out in the first place, and some of the present disagreements stem from incommensurate assumptions. Traditional cognitive science presumes cognition to be a decomposable system of components interacting according to computational rules to generate cognitive performances (i.e., component-dominant (...) dynamics). We assign primacy to interaction-dominant dynamics among components. Though either choice can be a good guess before the fact, the primacy of interactions is now supported by much recent empirical work in cognitive science. Consequently, in the main, the commentators have failed so far to address the growing evidence corroborating the theory-driven predictions of complexity science. (shrink)

Oversimplified conceptions of cognitive neuroscience regard the goal of this discipline as the localization of previously discovered and validated cognitive processes. Research however is showing how brain data goes far beyond this translation role, as it can be used to help in explaining human cognition. Knowing about the brain is useful in building and redefining taxonomies of the mind and also in describing the mechanisms by which cognitive phenomena proceed. The present paper takes the cognitive system of attention as a (...) model research field to exemplify how biological knowledge can be used to advance the psychological theories explaining mental phenomena. (shrink)