Online research in philosophy

Good research requires, among other virtues,(i) methods that yield stable experimentalobservations without arbitrary (post hoc)assumptions, (ii) logical interpretations ofthe sources of observations, and (iii) soundinferences to general causal mechanismsexplaining experimental results by placing themin larger explanatory contexts. In TheNew Phrenology , William Uttal examines theresearch tradition of localization, and findsit deficient in all three virtues, whetherbased on lesion studies or on new technologiesfor functional brain imaging. In this paper Iconsider just the arguments concerning brainimaging, especially functional MagneticResonance Imaging. I think that Uttal is tooharsh in his methodological critique, butcorrect in his assessment of the conceptuallimitations of localist evidence. I proposeinstead a data-driven test for assessingrelative modularity in brain images, and showits use in a secondary analysis of fMRI datafrom the National fMRI Data Center(www.fmridc.org). Although the analysis is alimited pilot study, it offers additionalempirical challenge to localism.

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.

Some theorists who emphasize the complexity of biological and cognitive systems and who advocate the employment of the tools of dynamical systems theory in explaining them construe complexity and reduction as exclusive alternatives. This paper argues that reduction, an approach to explanation that decomposes complex activities and localizes the components within the complex system, is not only compatible with an emphasis on complexity, but provides the foundation for dynamical analysis. Explanation via decomposition and localization is nonetheless extremely challenging, and an analysis of recent cognitive neuroscience research on memory is used to illustrate what is involved. Memory researchers split between advocating memory systems and advocating memory processes, and I argue that it is the latter approach that provides the critical sort of decomposition and localization for explaining memory. The challenges of linking distinguishable functions with brain processes is illustrated by two examples: competing hypotheses about the contribution of the hippocampus and competing attempts to link areas in frontal cortex with memory processing.

The project of referring to localized cognitive operations in the brain has a long history and many impressive successes. It is a core element in the practice of giving mechanistic explanations of mental abilities. But it has also been challenged by prominent critics. One of the critics’ claims is that brain regions are not specialized for specific cognitive operations and any science that refers to them is misguided. Most recently this claim has been advanced by theorists promoting a dynamical-systems perspective on cognition. There are, however, two ways to view the dynamical-systems perspective. The first is as a competitor to the mechanist perspective, rejecting altogether the conception of the brain as a mechanism or set of mechanisms underlying mental phenomena and thereby rejecting any reference to localized cognitive operations. The second is as a corrective to an overly simplistic conception of a mechanism and as complementary to a more adequate understanding of how mechanisms function. In this chapter I defend the later perspective. On this perspective, the traditional project of referring to localized mental operations in the brain is still important, but both the cognitive operations and brain regions in which they are localized must be conceived in the context of a dynamically active system.

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.

Much of cognitive neuroscience as well as traditional cognitive science is engaged in a quest for mechanisms through a project of decomposition and localization of cognitive functions. Some advocates of the emerging dynamical systems approach to cognition construe it as in opposition to the attempt to decompose and localize functions. I argue that this case is not established and rather explore how dynamical systems tools can be used to analyze and model cognitive functions without abandoning the use of decomposition and localization to understand mechanisms of cognition.

William Uttal's The new phrenology is a broad attack on localization in cognitive neuroscience. He argues that even though the brain is a highly differentiated organ, "high level cognitive functions" should not be localized in specific brain regions. First, he argues that psychological processes are not well-defined. Second, he criticizes the methods used to localize psychological processes, including imaging technology: he argues that variation among individuals compromises localization, and that the statistical methods used to construct activation maps are flawed. Neither criticism is compelling. First, as we illustrate, there are behavioral measures which offer at least weak constraints on psychological attribution. Second, though imaging does face methodological difficulties associated with variation among individuals, these are broadly acknowledged; moreover, his specific criticisms of the imaging work, and in particular of fMRI, misrepresent the methodology. In concluding, we suggest a way of framing the issues that might allow us to resolve differences between localizationist models and more distributed models empirically.