Recent literature on the role of pictorial representation in the life sciences has focused on the relationship between detailed representations of empirical data and more abstract, formal representations of theory. The standard argument is that in both a historical and epistemic sense, this relationship is a directional one: beginning with raw, unmediated images and moving towards diagrams that are more interpreted and more theoretically rich. Using the neural network diagrams of Warren McCulloch and Walter Pitts as a case study, I (...) argue that while in the empirical sciences, pictorial representation tends to move from data to theory, in areas of the life sciences that are predominantly theoretical, when abstraction occurs at the outset, the relationship between detail and abstraction in pictorial representations can be of a different character. (shrink)

Primatologists generally agree that monkeys lack higher-order intentional capacities related to theory of mind. Yet the discovery of the so-called “mirror neurons” in monkeys suggests to many neuroscientists that they have the rudiments of intentional understanding. Given a standard philosophical view about intentional understanding, which requires higher-order intentionality, a paradox arises. Different ways of resolving the paradox are assessed, using evidence from neural, cognitive, and behavioral studies of humans and monkeys. A decisive resolution to the paradox requires substantial additional empirical (...) work and perhaps a rejection of the standard philosophical view. (shrink)

We praise Arbib et al.'s Neural organization for its support of the integration of different levels of analysis, while noting that it does not always achieve what it advocates. We extend this approach into an area of neuropsychological activity in need of the structure offered by Organization at the intersection of the conflated fields of executive function and frontal lobe function.

The dynamics of neuronal systems, briefly neurodynamics, has developed into an attractive and influential research branch within neuroscience. In this paper, we discuss a number of conceptual issues in neurodynamics that are important for an appropriate interpretation and evaluation of its results. We demonstrate their relevance for selected topics of theoretical and empirical work. In particular, we refer to the notions of determinacy and stochasticity in neurodynamics across levels of microscopic, mesoscopic and macroscopic descriptions. The issue of correlations between neural, (...) mental and behavioral states is also addressed in some detail. We propose an informed discussion of conceptual foundations with respect to neurobiological results as a viable step to a fruitful future philosophy of neuroscience. (shrink)

I want to raise three questions for discussion: 1. How are a philosopher’s concerns about the human mind related to a neuroscientist’s concerns? 2. Can neuroscience explain everything that we want to understand about the human mind? 3. Does neuroscience threaten our dignity or humanity (or anything else that we cherish about ourselves)? Let’s take these questions one at a time.

Neuroscience and cognitive science seek to explain behavioral regularities in terms of underlying mechanisms. An important element of a mechanistic explanation is a characterization of the operations of the parts of the mechanism. The challenge in characterizing such operations is illustrated by an example from the history of physiological chemistry in which some investigators tried to characterize the internal operations in the same terms as the overall physiological system while others appealed to elemental chemistry. In order for biochemistry to become (...) successful, researchers had to identify a new level of operations involving operations over molecular groups. Existing attempts at mechanistic explanation of behavior are in a situation comparable to earlier approaches to physiological chemistry, drawing their inspiration either from overall psychology activities or from low-level neural processes. Successful mechanistic explanations of behavior require the discovery of the appropriate component operations. Such discovery is a daunting challenge but one on which success will be beneficial to both behavioral scientists and cognitive and neuroscientists. (shrink)

trying to explain these reactions in terms of changes in ele- began trying to characterize physiological processes in.

The need to align multiple experimental procedures and produce converging results so as to demonstrate that the phenomenon under investigation is real and not an artifact is a commonplace both in scientific practice and discussions of scientific methodology (Campbell and Stanley 1963; Wimsatt 1981). Although sometimes this is the purpose of aligning techniques, often there is a different purpose—multiple techniques are sought to supply different perspectives on the phenomena under investigation that need to be integrated to answer the questions scientists (...) are asking. After introducing this function, I will illustrate it by considering three of the major techniques in cognitive neuroscience for linking cognitive function with neural structure. (shrink)

The idea of integrating evolutionary biology and psychology has great promise, but one that will be compromised if psychological functions are conceived too abstractly and neuroscience is not allowed to play a contructive role. We argue that the proper integration of neuroscience, psyychology, and evolutionary biology requires a telelogical as opposed to a merely componential analysis of function. A teleological analysis is required in neuroscience itself; we point to traditional and curent research methods in neuroscience, which make critical use of (...) distinctly teleological functional considerations in brain cartography. Only by invoking teleological criteria can researchers distinguish the fruitful ways of identifying brain components from the myriad of possible ways. One likely reason for reluctance to turn to neuroscience is fear of reduction, but we argue that, in the context of a teleological perspective on function, this concern is misplaced. Adducing such theoretical considerations as top-down and bottom-up constraints on neuroscientific and psychological models, as well as existing cases of productive, multidisciplinary cooperation, we argue that integration of neuroscience into psychology and evolutionary biology is likely to be mutually beneficial. We also show how it can be accommodated methodologically within the framework of an interfield theory. (shrink)

Traditionally, identity and supervenience have been proposed in philosophy of mind as metaphysical accounts of how mental activities (fully understood, as they might be at the end of science) relate to brain processes. Kievet et al. suggest that to be relevant to cognitive neuroscience, these philosophical positions must make empirically testable claims and be evaluated accordingly – they cannot sit on the sidelines, awaiting the hypothetical completion of cognitive neuroscience. We agree with the authors on the importance of rendering these (...) positions relevant to ongoing science. We disagree, however, with their proposal that a metaphysical relationship (identity or supervenience) should “serve as a means to conceptually organize and guide the analysis of neurological and behavioral data” (p. 7). Instead, we advance a different view of the goals of cognitive neuroscience and of the proper means of relating metaphysics and explanation. Our central objection to the psychometric approach deployed by Kievet et al. is that the formal models only account for correlations between variables (measurements) and do not aid in explaining phenomena. Cognitive neuroscience is concerned with the latter. We develop this point in section 2 in which we present what we find to be problematic in their proposed models. In section 3 we advance an account of what is required to explain phenomena: (a) providing an adequate description of a phenomenon; and (b) characterizing the mechanism responsible for it. In doing so we will characterize a version of the identity theory, heuristic identity theory (HIT) which figures centrally in developing such explanations and illustrate its role in what we take to.. (shrink)

This article examines the neurobiological basis of the healing power attributed to shamanic practices in the Andes and Brazil in light of the pharmacology of neurotransmitters and the new technological explorations of brain functioning. The psychotropic plants used in shamanic psychiatric cures interfere selectively with the intrinsic neuromediators of the brain. Mainly they may alter: (1) the neuroendocrine functioning through the adrenergic system by controlling stressful conditions, (2) the dopaminergic system in incentive learning and emotions incorporation, (3) the serotoninergic system (...) in modulating behaviors, and mood, and (4) basic functions implied in anxiety or depression. PET scans and functional magnetic resonance imaging studies of hypnotic trance and altered states of consciousness may provide a useful model for the neurophysiological phenomena of shamanic drum-and-dance trance. The reorganization of cortical areas and the direct interconnections between the prefrontal cortex and the dopaminergic reward centers in the limbic system are of particular significance for human social judgment and symbolic processing. Those centers—including the hypothalamus and the amygdala (associated with psychosomatic equilibrium, memory, and emotion) are enhanced. This arousal may be amplified in order to induce a cathartic crisis—the shamanic trance. It is suggested that through this holistic approach the shaman empirically interferes in neurobiological dysfunctions. (shrink)

A biological neuroscientific theory must acknowledge that the function of a neurological system is to produce behaviors that promote survival. Thus, unlike what Gold & Stoljar claim, function and behavior are the province of neurobiology and cannot be relegated to the field of psychological phenomena, which would then trivialize the radical doctrine if accepted. One possible advantage of adopting such a (correctly revised) radical doctrine is that it might ultimately produce a successful, evolutionarily based, theory of mind.

Analytic and continental philosophies of mind are too long divided. In both traditions there is extensive discussion of consciousness, the mind-body problem, intentionality, subjectivity, perception (especially visual) and so on. Between these two discussions there are substantive disagreements, overlapping points of insight, meaningful differences in emphasis, and points of comparison which seems to offer nothing but confusion. In other words, there are the ideal circumstances for doing philosophy. Yet, there has been little discourse. This paper invites expanding discourse between these (...) two philosophical traditions. The first part briefly describes the existing literature which works across the analytic- phenomenology divide, situating my work within it as a focus on analytic physicalism and phenomenal explanation. In the longer second part, I sketch a model for explanation embedded simultaneously in both traditions. Hopefully, a theoretical framework emerges that the unlikely combination of Maurice Merleau- Ponty and Patricia Churchland could accept. In the third part, I apply the three-tiered model to a discussion of plasticity and suggest that the model both reflects existing research across three levels of analysis and can be a fruitful way to approach future research. My suggestion for a three-tiered model is quite tentative. Much less tentative is my claim that constructive dialogue between phenomeno- logical and physicalist study of consciousness is long-overdue, illuminating, and practical. (shrink)

Skinner has made significant contributions to the science of the behavior of organisms, including human ones, especially through his emphasis on observable behavior. He has correctly placed psychology among the biological sciences. My disagreement with his position stems from his apparent belief that a knowledge of the pertinent neurophysiology is not necessary (though perhaps desirable) to an explanation of the behavior of an organism. I believe this is a significant conceptual shortcoming, and that correcting it will bring psychology into a (...) more consistent position with the biological sciences in general. CiteULike Connotea Del.icio.us What's this? (shrink)

Logical problems inherent in claims that biological neuroscience can ultimately explain mind are not anomalous: They result from underlying social interests. Neuroscientists are currently making a successful bid to fill a vacuum of authority created by the demise of Freudian theory in popular culture. The conflations described in the Gold & Stoljar target article are the result of alliances between certain apologist-philosophers, neuroscientists, and institutions, for the purpose of commanding authority and resources. Social analysis has a role to play in (...) addressing logical issues in the philosophy of neuroscience. (shrink)

Various authors insist that some body of natural phenomena are legitimately describable or explainable only on one level of description, and would disqualify any description not confined to that level. None offers an acceptable definition explicitly. I extract such a definition I find implicit in the work of two such authors, J.J. Gibson and Hubert Dreyfus, and modify the result to render it more defensible philosophically. I also criticize the definition Shaw and Turvey offer, demonstrate some applications of my definition, (...) and try to forestall certain misunderstandings of those presuppositions and that definition. (shrink)

The question posed by Dunn and Kirsner (D&K) is an instance of a more general one: What can we infer from data? One answer, if we are talking about logically valid deductive inference, is that we cannot infer theories from data. A theory is supposed to explain the data and so cannot be a mere summary of the data to be explained. The truth of an explanatory theory goes beyond the data and so is never logically guaranteed by the data. (...) This is not just a point about cognitive neuropsychology, or even about psychology in general. It is a familiar point about all science. (shrink)

This paper will examine the nature of mechanisms and the distinction between the relevant and irrelevant parts involved in a mechanism’s operation. I first consider Craver’s account of this distinction in his book on the nature of mechanisms, and explain some problems. I then offer a novel account of the distinction that appeals to some resources from Mackie’s theory of causation. I end by explaining how this account enables us to better understand what mechanisms are and their various features.

Hodgkin and Huxley’s 1952 model of the action potential is an apparent dream case of covering-law explanation. The model appeals to general laws of physics and chemistry (specifically, Ohm’s law and the Nernst equation), and the laws, coupled with details about antecedent and background conditions, entail many of the significant properties of the action potential. However, Hodgkin and Huxley insist that their model falls short of an explanation. This historical fact suggests either that there is more to explaining the action (...) potential than subsuming it under a general laws or that Hodgkin and Huxley were wrong about the explanatory import of their model. In this paper, I defend Hodgkin and Huxley’s view that their model alone does not explain the action potential (contra Weber 2005). I argue further that neuroscientists lacked crucial explanatory details about the action potential until they could describe the molecular and ionic mechanisms by virtue of which their model holds (see Bogen 2005). Mathematical generalizations are important epistemic tools for assessing mechanistic explanations, but they are neither necessary nor sufficient for adequate explanations, even at the lowest levels of organization where biological phenomena are integrated with physics and chemistry. (shrink)

Hodgkin and Huxley’s model of the action potential is an apparent dream case of covering‐law explanation in biology. The model includes laws of physics and chemistry that, coupled with details about antecedent and background conditions, can be used to derive features of the action potential. Hodgkin and Huxley insist that their model is not an explanation. This suggests either that subsuming a phenomenon under physical laws is insufficient to explain it or that Hodgkin and Huxley were wrong. I defend Hodgkin (...) and Huxley against Weber’s heteronomy thesis and argue that explanations are descriptions of mechanisms. †To contact the author, please write to: Department of Philosophy, Philosophy‐Neuroscience‐Psychology Program, Washington University in St. Louis, One Brookings Drive, Wilson Hall, St. Louis, MO 63130; e‐mail: ccraver@artsci.wustl.edu. (shrink)

Carl Craver investigates what we are doing when we sue neuroscience to explain what's going on in the brain.

Long-Term Potentiation (LTP) is a kind of synaptic plasticity that many contemporary neuroscientists believe is a component in mechanisms of memory. This essay describes the discovery of LTP and the development of the LTP research program. The story begins in the 1950's with the discovery of synaptic plasticity in the hippocampus (a medial temporal lobe structure now associated with memory), and it ends in 1973 with the publication of three papers sketching the future course of the LTP research program. The (...) making of LTP was a protracted affair. Hippocampal synaptic plasticity was initially encountered as an experimental tool, then reported as a curiosity, and finally included in the ontic store of the neurosciences. Early researchers were not investigating the hippocampus in search of a memory mechanism; rather, they saw the hippocampus as a useful experimental model or as a structure implicated in the etiology of epilepsy. The link between hippocampal synaptic plasticity and learning or memory was a separate conceptual achievement. That link was formulated in at least three different ways at different times: reductively (claiming that plasticity is identical to learning), analogically (claiming that plasticity is an example or model of learning), and mechanistically (claiming that plasticity is a component in learning or memory mechanisms). The hypothesized link with learning or memory, coupled with developments in experimental techniques and preparations, shaped how researchers understood LTP itself. By 1973, the mechanistic formulation of the link between LTP and memory provided an abstract framework around which findings from multiple perspectives could be integrated into a multifield research program. (shrink)

Many areas of science develop by discovering mechanisms and role functions. Cummins' (1975) analysis of role functions-according to which an item's role function is a capacity of that item that appears in an analytic explanation of the capacity of some containing system-captures one important sense of "function" in the biological sciences and elsewhere. Here I synthesize Cummins' account with recent work on mechanisms and causal/mechanical explanation. The synthesis produces an analysis of specifically mechanistic role functions, one that uses the characteristic (...) active, spatial, temporal, and hierarchical organization of mechanisms to add precision and content to Cummins' original suggestion. This synthesis also shows why the discovery of role functions is a scientific achievement. Discovering a role function (i) contributes to the interlevel integration of multilevel mechanisms, and (ii) provides a unique, contextual variety of causal/mechanical explanation. (shrink)

We argue that intelligible appeals to interlevel causes (top-down and bottom-up) can be understood, without remainder, as appeals to mechanistically mediated effects. Mechanistically mediated effects are hybrids of causal and constitutive relations, where the causal relations are exclusively intralevel. The idea of causation would have to stretch to the breaking point to accommodate interlevel causes. The notion of a mechanistically mediated effect is preferable because it can do all of the required work without appealing to mysterious interlevel causes. When interlevel (...) causes can be translated into mechanistically mediated effects, the posited relationship is intelligible and should raise no special philosophical objections. When they cannot, they are suspect. (shrink)

The idea that biorobots can be used as a testbed for the evaluation of hypotheses about how an animal functions is supported. Generation of realistic feedback is a major advantage of biorobotic models. Nevertheless, skeptics can only be convinced that this approach is valid if significant biological insights are generated from its application.

This paper explores structuralism as a way to model theories from scientific practice. As a case study I analyzed a theory about the dynamics of the basal ganglia, a part of the brain that is involved in Parkinson's disease. After introducing the case study I explore how to structurally represent qualitative assumptions about disease, intervention and dynamical systems in general. I further explicate the structure of the basal ganglia theory in detail, how it explains Parkinson's disease and how it implies (...) treatments. I close with a consideration of how a structuralist representation could be useful in practice to explore and develop theories with the aid of a computer. (shrink)

Quartz & Sejnowski (Q&S) disregard evidence that suggests that their view of dendrites is inadequate and they ignore recent results concerning the role of neurotrophic factors in synaptic remodelling. They misrepresent neuronal selectionism and thus erect a straw-man argument. Finally, the results discussed in section 4.2 require neuronal proliferation, but this does not occur during the period of neuronal development of relevance here. Footnotes1 Address correspondence to TE at te@proteus.psyc.nott.ac.uk.

The concept of representation has been a key element in the scientific study of mental processes, ever since such studies commenced. However, usage of the term has been all but too liberal—if one were to adhere to common use it remains unclear if there are examples of physical systems which cannot be construed in terms of representation. The problem is considered afresh, taking as the starting point the notion of activity spaces—spaces of spatiotemporal events produced by dynamical systems. It is (...) argued that representation can be analyzed in terms of the geometrical and topological properties of such spaces. Several attributes and processes associated with conceptual domains, such as logical structure, generalization and learning are considered, and given analogues in structural facets of activity spaces, as are misrepresentation and states of arousal. Based on this analysis, representational systems are defined, as is a key concept associated with such systems, the notion of representational capacity. According to the proposed theory, rather than being an all or none phenomenon, representation is in fact a matter of degree—that is can be associated with measurable quantities, as is behooving of a putative naturalistic construct. (shrink)

A standing challenge for the science of mind is to account for the datum that every mind faces in the most immediate – that is, unmediated – fashion: its phenomenal experience. The complementary tasks of explaining what it means for a system to give rise to experience and what constitutes the content of experience (qualia) in computational terms are particularly challenging, given the multiple realizability of computation. In this paper, we identify a set of conditions that a computational theory must (...) satisfy for it to constitute not just a sufficient but a necessary, and therefore naturalistic and intrinsic, explanation of qualia. We show that a common assumption behind many neurocomputational theories of the mind, according to which mind states can be formalized solely in terms of instantaneous vectors of activities of representational units such as neurons, does not meet the requisite conditions, in part because it relies on inactive units to shape presently experienced qualia and implies a homogeneous representation space, which is devoid of intrinsic structure. We then sketch a naturalistic computational theory of qualia, which posits that experience is realized by dynamical activity-space trajectories (rather than points) and that its richness is measured by the representational capacity of the trajectory space in which it unfolds. (shrink)

The target paper of Dr. Feinberg is a testimony to an admirable scholarship and deep thoughtfulness. This paper develops a general theoretical framework of nested hierarchy in the brain that allows production of mind with consciousness. The difference between non-nested and nested hierarchies is the following. In a non-nested hierarchy the entities at higher levels of the hierarchy are physically independent from the entities at lower levels and there is strong constraint of higher upon lower levels. In a nested hierarchy, (...) higher levels are physically composed of lower levels, and there is no central control of the system resulting in weak constraint of higher upon lower levels. (shrink)

Despite the voluminous literature on biological functions produced over the last 40 years, few philosophers have studied the concept of function as it is used in neuroscience. Recently, Craver (forthcoming; also see Craver 2001) defended the causal role theory against the selected effects theory as the most appropriate theory of function for neuroscience. The following argues that though neuroscientists do study causal role functions, the scope of that theory is not as universal as claimed. Despite the strong prima facie superiority (...) of the causal role theory, the selected effects theory (when properly developed) can handle many cases from neuroscience with equal facility. It argues this by presenting a new theory of function that generalizes the notion of a ‘selection process’ to include processes such as neural selection, antibody selection, and some forms of learning—that is, to include structures that have been differentially retained as well as those that have been differentially reproduced. This view, called the generalized selected effects theory of function, will be defended from criticism and distinguished from similar views in the literature. (shrink)

We address three issues that might be important in evaluating the validity of the planning–control model: (1) It could be artificial to distinguish between control and planning when control involves the re-planning of a new corrective submovement that overlaps with the initial response; (2) experiments involving illusions are not totally compelling; (3) selectively implicating the superior parietal lobe in movement control and the basal ganglia in movement planning, appears questionable.

Our commentary focuses, first, on Glover's proposal that only motor planning is sensitive to cognitive aspects of the target object, whereas the on-line control is completely immune to them. We present behavioural data showing that movement phases traditionally (and by Glover) thought to be under on-line control, are also modulated by object cognitive aspects. Next, we present data showing that some aspects of cognition can be coded by means of movement planning. We propose a reformulation of Glover's theory to include (...) both an influence of cognition on on-line movement control, and a mutual influence between motor planning and some aspects of cognition. (shrink)

Recent work in cognitive neuroscience on the child's Theory of Mind (ToM) has pursued the idea that the ability to metarepresent mental states depends on a domain-specific cognitive subystem implemented in specific neural circuitry: a Theory of Mind Module. We argue that the interaction of several domain-general mechanisms and lower-level domain-specific mechanisms accounts for the flexibility and sophistication of behavior, which has been taken to be evidence for a domain-specific ToM module. This finding is of more general interest since it (...) suggests a parsimonious cognitive architecture can account for apparent domain specificity. We argue for such an architecture in two stages. First, on conceptual grounds, contrasting the case of language with ToM, and second, by showing that recent evidence in the form of fMRI and lesion studies supports the more parsimonious hypothesis. Theory of Mind, Metarepresentation, and Modularity Developmental Components of ToM The Analogy with Modularity of Language Dissociations without Modules The Evidence from Neuroscience Conclusion CiteULike Connotea Del.icio.us What's this? (shrink)

Nativists about syntactic processing have argued that linguisticprocessing, understood as the implementation of a rule-basedcomputational architecture, is spared in Williams syndrome, (WMS)subjects – and hence that it provides evidence for a geneticallyspecified language module. This argument is bolstered by treatingSpecific Language Impairments (SLI) and WMS as a developmental doubledissociation which identifies a syntax module. Neuroconstructivists haveargued that the cognitive deficits of a developmental disorder cannot beadequately distinguished using the standard gross behavioural tests ofneuropsychology and that the linguistic abilities of the (...) WMS subject canbe equally well explained by a constructivist strategy of neurallearning in the individual, with linguisitic functions implemented in anassociationist architecture. The neuroconstructivist interpretation ofWMS undermines the hypothesis of a double dissociation between SLI andWMS, leaving unresolved the question of nativism about syntax. Theapparent linguistic virtuosity of WMS subjects is an artefact ofenhanced phonological processing, a fact which is easier to demonstratevia the associationist computational model embraced byneuroconstructivism. (shrink)

Either genetically specified modular cognitive architecture for syntactic processing does not exist (neuroconstructivism), or there is a module but its development is so abnormal in Williams syndrome (WS) that no conclusion can be drawn about its normal architecture (moderate nativism). Radical nativism, which holds that WS is a case of intact syntax, is untenable. Specific Language Impairment and WS create a dilemma that radical nativism cannot accommodate.

Although a wide variety of questions were raised about different aspects of the target article, most of them fall into one of five categories each of which deals with a general question. These questions are (1) Is the radical neuron doctrine really radical? (2) Is the trivial neuron doctrine really trivial? (3) Were we sufficiently critical of the radical neuron doctrine? (4) Is there a distinction to be drawn at all between the two doctrines? and (5) How does our (...) argument bear on related issues in the ontology of mind? Our replies to the objections and observations presented are organized around these five questions. (shrink)

Let me first state that I like Antti Revonsuo’s discussion of the various methodological and interpretational problems in neuroscience. It shows how careful and methodologically reflected scientists have to proceed in this fascinating field of research. I have nothing to add here. Furthermore, I am very sympathetic towards Revonsuo’s general proposal to call for a Philosophy of Neuroscience that stresses foundational issues, but also focuses on methodological and explanatory strategies. In a footnote of his paper, Revonsuo complains – as many (...) others do today – about what is sometimes called “physics imperialism”. This is the view that physics dominates the philosophy of science. I am not sure if this is still the case nowadays, but it is certainly historically correct that almost all work in the field of methodology centered around cases from physics. Although this has been changing, there are still plenty of special sciences philosophers did not worry about much. Admittedly, I am myself a trained physicist and not a neuroscientist and will therefore probably be biased negatively. As it is, I will discuss some examples from physics in order to illustrate my points. (shrink)

Let me first state that I like Antti Revonsuo’s discussion of the various methodological and interpretational problems in neuroscience. It shows how careful and methodologically reflected scientists have to proceed in this fascinating field of research. I have nothing to add here. Furthermore, I am very sympathetic towards Revonsuo’s general proposal to call for a Philosophy of Neuroscience that stresses foundational issues, but also focuses on methodological and explanatory strategies.2 In a footnote of his paper, Revonsuo complains – as many (...) others do today – about what is sometimes called “physics imperialism”. This is the view that physics dominates the philosophy of science. I am not sure if this is still the case nowadays, but it is certainly historically correct that almost all work in the field of methodology centered around cases from physics. Although this has been changing, there are still plenty of special sciences philosophers did not worry about much. Admittedly, I am myself a trained physicist and not a neuroscientist and will therefore probably be biased negatively. As it is, I will discuss some examples from physics in order to illustrate my points. (shrink)

Neural organization contains a wealth of facts from all areas of brain research and provides a useful overview of physiological data for those working outside the immediate field. Furthermore, it gives a good example that the approach of dynamical system theory together with the concepts of cooperative and competitive interaction can be fruitful for an interdisciplinary approach to cognition.

& Explanations of psychological phenomena seem to genervs. with neuroscience) design. Crucially, the neuroscience inate more public interest when they contain neuroscientific..

The papers collected in this volume explore some of the powers and limitations of the concept of mechanism for the scientific understanding of cognitive systems, and aim at bringing together some of the most recent developments in the philosophical understanding of the relation of cognition to neuroscience. Earlier versions of most papers have been presented at a workshop held in Paris on June 19th, 2006, which was organized by Institut Jean Nicod and supported by RESCIF (R seau des sciences cognitives (...) en Ile-de-France). (shrink)

Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.

Carl Craver’s recent book offers an account of the explanatory and theoretical structure of neuroscience. It depicts it as centered around the idea of achieving mechanistic understanding, i.e., obtaining knowledge of how a set of underlying components interacts to produce a given function of the brain. Its core account of mechanistic explanation and relevance is causal-manipulationist in spirit, and offers substantial insight into casual explanation in brain science and the associated notion of levels of explanation. However, the focus on mechanistic (...) explanation leaves some open questions regarding the role of computation and cognition. (shrink)

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

Surveys theories in contemporary neuroscience, exploring many of its methodological techniques and problems.

A formal neuron has been studied mathematically. The spiking behaviour of a single neuron has been considered and the influence of the other neurons has been replaced by an average activity level. Four different kinds of spiking behaviour are predicted by the model: B (bursts), C (continuous), P (periodic) and S (silent) neurons and several real neurons can be classified within these four categories. Some properties of the spiking neuron are calculated: 1) the time between spikes, 2) the spike train (...) length and 3) the silent time. Because these magnitudes can be measured in the laboratory, an experimental validation of the model is proposed. (shrink)

The idea of integrating evolutionary biology and psychology has great promise, but one that will be compromised if psychological functions are conceived too abstractly and neuroscience is not allowed to play a contructive role. We argue that the proper integration of neuroscience, psychology, and evolutionary biology requires a telelogical as opposed to a merely componential analysis of function. A teleological analysis is required in neuroscience itself; we point to traditional and curent research methods in neuroscience, which make critical use of (...) distinctly teleological functional considerations in brain cartography. Only by invoking teleological criteria can researchers distinguish the fruitful ways of identifying brain components from the myriad of possible ways. One likely reason for reluctance to turn to neuroscience is fear of reduction, but we argue that, in the context of a teleological perspective on function, this concern is misplaced. Adducing such theoretical considerations as top-down and bottom-up constraints on neuroscientific and psychological models, as well as existing cases of productive, multidisciplinary cooperation, we argue that integration of neuroscience into psychology and evolutionary biology is likely to be mutually beneficial. We also show how it can be accommodated methodologically within the framework of an interfield theory. (shrink)

Gold & Stoljar pose a dilemma for linguistics should neurobiology win out as the science of mind. The dilemma can be avoided by reestablishing linguistics as an autonomous discipline, rather than a branch of the science of mind. Independent considerations for doing this are presented.

In this paper, I examine metaphysical aspects in the neuroeconomics debate. I propose that part of the debate can be better understood by supposing two metaphysical stances, mechanistic and functional. I characterize the two stances, and discuss their relations. I consider two models of framing, in order to illustrate how the features of mechanistic and functional stances figure in the practice of the sciences of individual decision making.

The cerebral distinctness of the linguistic and mathematical faculties does not entail their functional independence. Approaches to language that posit a common foundation for the two make claims about design features, not location, and are thus not affected by the finding that one ability can be spared by a neurological accident that compromises the other.

Gold & Stoljar's argument rejecting the “explanatory sufficiency” of the radical neuron doctrine depends on distinguishing it from the trivial neuron doctrine. This distinction depends on the thesis of “supervenience,” which depends on Hume's regularity theory of causation. In contrast, the radical neuron doctrine depends on a physical theory of causation, which denies the supervenience thesis. Insofar as the target article argues by drawing implications from the premise of Humean causation, whereas the radical doctrine depends on the competing premise of (...) physical causation, the resulting critique of the neuron doctrine amounts largely to begging the question of causation. (shrink)

In this study I propose an epistemological discussion of multiple spatio-temporal scales in neuroscience. Are such scales merely convenient levels of description of structure and function, or do they correspond to irreducible levels of brain organization? What criteria should we employ in order to reduce one level to another, or to identify levels that are not reducible to others? Should we think of these criteria as based on empirical and/or theoretical reasons? Beginning with an empirical criterion – the necessity of (...) different experimental methodologies for the measurement of different phenomena in the same system – I summarize spatial and temporal scales currently used in neuroscience and discuss the possibility of a more general theoretical criterion. I conclude that multiscaling should be recognized as a central concept in the epistemology of neuroscience. (shrink)

In this study I propose an epistemological discussion of multiple spatio-temporal scales in neuroscience. Are such scales merely convenient levels of description of structure and function, or do they correspond to irreducible levels of brain organization? What criteria should we employ in order to reduce one level to another, or to identify levels that are not reducible to others? Should we think of these criteria as based on empirical and/or theoretical reasons? Beginning with an empirical criterion – the necessity of (...) different experimental methodologies for the measurement of different phenomena in the same system – I summarize spatial and temporal scales currently used in neuroscience and discuss the possibility of a more general theoretical criterion. I conclude that multiscaling should be recognized as a central concept in the epistemology of neuroscience. (shrink)

Gold & Stoljar's target article is important because it shows the limitations of neurobiological theories of the mind more powerfully than previous philosophical criticisms, especially those that focus on the subjective nature of experience and those that use considerations from philosophy of language to argue for the holism of the mental. They use less controversial assumptions and clearer arguments, the conclusions of which are applicable to the whole of neuroscience. Their conclusions can be applied to psychiatry to argue that, contrary (...) to many researchers' assumptions, the approaches to both understanding and treating mental disorders must be interdisciplinary. (shrink)

This research was carried out to explore some of the cognitive processes involved in scientific anomalies resolution. 40 subjects with a good neuropsychology expertise were asked to explain two (invented) anomalous neuropsychological cases. The subjects' efforts to give a meaningful structure to the data were recorded, and the resulting reasoning blocks were analysed to extract and compute the inferential (deductive, inductive and abductive) and analogical processes used. The processes were intercorrelated to experimentally verify the co-occurrence of different forms of logical (...) thinking. Statistical analysis point out the relevance of abductive inferences, the possible presence of an inferential-style switching process , the high number of external analogies used, the cognitive closeness manifested by expert reasoners. (shrink)

According to the computational theory of mind (CTM), mental capacities are explained by inner computations, which in biological organisms are realized in the brain. Computational explanation is so popular and entrenched that it’s common for scientists and philosophers to assume CTM without argument.

According to some philosophers, computational explanation is proprietary
to psychology—it does not belong in neuroscience. But neuroscientists routinely offer computational explanations of cognitive phenomena. In fact, computational explanation was initially imported from computability theory into the science of mind by neuroscientists, who justified this move on neurophysiological grounds. Establishing the legitimacy and importance of computational explanation in neuroscience is one thing; shedding light on it is another. I raise some philosophical questions pertaining to computational explanation and outline some promising answers that (...) are being developed by a number of authors. (shrink)

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (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.

ERP studies have shown modulation of activation in left frontal and posterior cortical language areas, as well as recruitment of right hemisphere homologues, based on task demands. Furthermore, blood-flow studies have demonstrated changes in the neural circuitry of word processing based on experience. The neural areas and time course of language processing are plastic depending on task demands and experience.

Explanatory problems in the philosophy of neuroscience are not well captured by the division between the radical and the trivial neuron doctrines. The actual problem is, instead, whether mechanistic biological explanations across different levels of description can be extended to account for psychological phenomena. According to cognitive neuroscience, some neural levels of description at least are essential for the explanation of psychological phenomena, whereas, in traditional cognitive science, psychological explanations are completely independent of the neural levels of description. The challenge (...) for cognitive neuroscience is to discover the levels of description appropriate for the neural explanation of psychological phenomena. (shrink)

1. From developmental molecular biology to neurogenomics 2. More than you wanted to know about short term and long term implicit memory 3. How are explicit memories stored? 4. How the brain recalls memories 5. Each explicit memory is just a lot of implicit memories 6. Is ‘knowledge how’ computable? 7. Computationalism and neuroscience..

This article considers claims that biology should seek general theories similar to those found in physics but argues for an alternative framework for biological theories as collections of prototypical interlevel models that can be extrapolated by analogy to different organisms. This position is exemplified in the development of the Hodgkin‐Huxley giant squid model for action potentials, which uses equations in specialized ways. This model is viewed as an “emergent unifier.” Such unifiers, which require various simplifications, involve the types of heuristics (...) discussed in Wimsatt’s writings on reduction, but with a twist. Here, the heuristics are used to generate emergent rather than reductive explanations. †To contact the author, please write to: Department of History and Philosophy of Science, University of Pittsburgh, 1017 Cathedral of Learning, Pittsburgh, PA 15260; e‐mail: kfs@pitt.edu. (shrink)

We suggest that neither selectionism nor constructivism alone are responsible for learning-based changes in the brain. On the basis of quantitative structural studies of human brain tissue it has been possible to find evidence of both increase and decrease in tissue mass at synaptic and dendritic levels. It would appear that both processes are involved in the course of learning-dependent changes.

There is a lack of connection between the cognitive neuroscience and evolutionary approaches to the study of the mind, in philosophy as well as the sciences. For instance, although Millikan may display a thorough understanding of evolutionary theory in her arguments for the adaptive value of substance concepts, she gives scant attention to what could be the neural substrates of these concepts. Neuroscience research calls into question her assumption that substance concepts play a role in practical skills and suggests that (...) conceptual knowledge in the brain may be organized by perceptual features rather than by individuals and natural kinds. (shrink)

Lewis describes the developmental core of dynamic systems theory. I offer recent data from developmental neuroscience on the sequential experience-dependent maturation of components of the limbic system over the stages of infancy. Increasing interconnectivity within the vertically integrated limbic system allows for more complex appraisals of emotional value. The earliest organization of limbic structures has an enduring impact on all later emotional processing.

Computer simulations show that an unstructured neural-network model [Shultz, T. R., & Bale, A. C. (2001). Infancy, 2, 501–536] covers the essential features␣of infant learning of simple grammars in an artificial language [Marcus, G. F., Vijayan, S., Bandi Rao, S., & Vishton, P. M. (1999). Science, 283, 77–80], and generalizes to examples both outside and inside of the range of training sentences. Knowledge-representation analyses confirm that these networks discover that duplicate words in the sentences are nearly identical and that they (...) use this near-identity relation to distinguish sentences that are consistent or inconsistent with a familiar grammar. Recent simulations that were claimed to show that this model did not really learn these grammars [Vilcu, M., & Hadley, R. F. (2005). Minds and Machines, 15, 359–382] confounded syntactic types with speech sounds and did not perform standard statistical tests of results. (shrink)

What is needed today is a biologically grounded explanation of behavior, one that moves beyond the so?called mind?body problem. Yet no solution will be found by philosophers who refuse to learn about how brains and bodies work, or by neuroscientists pursuing experimental research based on outmoded or blatantly anti?biological theories. Churchland's book proposes a solution: to come by a unified theory of the mind?brain philosophers have to work together with neuroscientists. Yet Churchland's vision of a unified theory is based on (...) an assumption that, while widely held, may not adequately reflect brain functioning in the production of behavior, namely, the assumption that brain processes represent. The present paper proposes an alternative view, suggesting that patterns of neural activity do not ?represent? anything, that brains do not ?read? or ?transform? representations, and that brains do not require representations to produce goal?directed behavior. Representations are replaced by self?organizing neural processes that achieve a certain end?state of interaction between the organism and its environment in a flexible and adaptive manner. Some of the implications of this view for neuroscientific research and the philosophy of mind are outlined. (shrink)

Cognition and behavior are the result of neural processes occurring at multiple levels of organization. Synthetic computational approaches are capable of bridging the gaps between multiple organizational levels and contribute to our understanding of how neural structures give rise to specific dynamical states. Such approaches are indispensable for formulating the theoretical foundations of cognitive neuroscience.

The problem at issue here is the nature of connection between the features of the experiments described in psychological/mentalistic terms and the features described in spacio-temporally-based physical terms. This question is an aspect of the long-standing problem of the relationship between mind and matter, which has a history dating back to the time of the ancient Greeks. The issue was rekindled by the rise of Newtonian physics during the seventeenth century, and it generated a huge body of speculation and argumentation (...) during the second half of the twentieth century. It is neither appropriate nor feasible try to review or explain here the complexities of contemporary philosophical opinions on this question, except to say that the reigning view is “materialism,” and that: (1), there is no agreement among its proponents as to how to make rational good sense of this doctrine (Horgan, 1994); and (2), the doctrine, and its supporters, seem, nevertheless, to have strongly influenced the thinking of many neuroscientists. The central thesis of materialism is that: “The human body is a causally complete physico-chemical system: although the body is highly susceptible to external causal influences, all physical events in the body, and all bodily movements are fully explainable in physico-chemical terms.” (Horgan, 1994:472). (shrink)

_Two notions of autonomy are distinguished. The respective_ _denials that psychology is autonomous from neurobiology are neuron_ _doctrines, moderate and radical. According to the moderate neuron_ _doctrine, inter-disciplinary interaction need not aim at reduction. It is_ _proposed that it is more plausible that there is slippage from the_ _moderate to the radical neuron doctrine than that there is confusion_ _between the radical neuron doctrine and the trivial version._.

Descriptive accounts of the nature of explanation in neuroscience and the global goals of such explanation have recently proliferated in the philosophy of neuroscience (e.g., Bechtel, Mental mechanisms: Philosophical perspectives on cognitive neuroscience. New York: Lawrence Erlbaum, 2007; Bickle, Philosophy and neuroscience: A ruthlessly reductive account. Dordrecht: Kluwer Academic Publishing, 2003; Bickle, Synthese, 151, 411–434, 2006; Craver, Explaining the brain: Mechanisms and the mosaic unity of neuroscience. Oxford: Oxford University Press, 2007) and with them new understandings of the <span class='Hi'>experimental</span> (...) practices of neuroscientists have emerged. In this paper, I consider two models of such practices; one that takes them to be reductive; another that takes them to be integrative. I investigate those areas of the neuroscience of learning and memory from which the examples used to substantiate these models are culled, and argue that the multiplicity of <span class='Hi'>experimental</span> protocols used in these research areas presents specific challenges for both models. In my view, these challenges have been overlooked largely because philosophers have hitherto failed to pay sufficient attention to fundamental features of <span class='Hi'>experimental</span> practice. I demonstrate that when we do pay attention to such features, evidence for reduction and integrative unity in neuroscience is simply not borne out. I end by suggesting some new directions for the philosophy of neuroscience that pertain to taking a closer look at the nature of neuroscientific experiments. (shrink)