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)

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)

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

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)

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)

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)

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)

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)

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)

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

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 term ‘module’ has – to my ear – too many associations with Fodor’s (1983) seminal book, and I will concentrate here on the more general notion of a cognitive system. The latter, as I will understand the term, is – roughly – a computational mechanism which can operate independently of all other computational mechanisms (for a much fuller and more precise treatment, see Lyons, 2001). To say that there is a face recognition system, for example, is to say, at (...) least in part, that there is a mechanism which by itself is capable of effecting a transformation from some set of inputs to face identification outputs. If there is one such system, there are likely to be several. Since systems may contain various subsystems, it is generally impossible to specify a system uniquely without specifying a set of inputs. The largest system that would count as a face recognition system would be the one that takes retinal irradiation arrays as inputs and delivers face identifications as outputs, but the last subsystem in this system would map high level representations to face identifications. For any task (where a task is construed as an input/output mapping), take away all cortical regions whose absence does not affect the ability of what is left to perform the task, and you are left with the system that performs that task. (shrink)

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)

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.

As much as assumptions about mechanisms and mechanistic explanation have deeply affected psychology, they have received disproportionately little analysis in philosophy. After a historical survey of the influences of mechanistic approaches to explanation of psychological phenomena, we specify the nature of mechanisms and mechanistic explanation. Contrary to some treatments of mechanistic explanation, we maintain that explanation is an epistemic activity that involves representing and reasoning about mechanisms. We discuss the manner in which mechanistic approaches serve to bridge levels rather than (...) reduce them, as well as the different ways in which mechanisms are discovered. Finally, we offer a more detailed example of an important psychological phenomenon for which mechanistic explanation has provided the main source of scientific understanding. (shrink)