Robert Richardson

Multiple realization was once taken to be a challenge to reductionist visions, especially within cognitive science, and a foundation of the “antireductionist consensus.” More recently, multiple realization has come to be challenged on naturalistic grounds, as well as on more “metaphysical” grounds. Within cognitive science, one focal issue concerns the role of neural plasticity for addressing these issues. If reorganization maintains the same cognitive functions, that supports claims for multiple realization. I take up the reorganization involved in language dysfunctions to deal with questions concerned with multiple realization and neural plasticity. Beginning with Broca’s case for localization and the nineteenth century discussion of “reorganization,” and returning to more recent evidence for neural plasticity, I argue that, in the end, there is substantial support for multiple realization in cognitive systems; I further argue that this is wholly consistent with a recognition of methodological pluralism in cognitive science.

John Bickle's Psychoneural reduction: the new wave (Cambridge, MA: MIT Press, 1998) aims to resurrect reductionism within philosophy of mind. He develops a new model of scientific reduction, geared to enhancing our understanding of how theories in neuroscience and cognitive science are interrelated. I put this discussion in context, and assess the prospects for new wave reductionism, both as a general model of scientific reduction and as an attempt to defend reductionism in the philosophy of mind.

The formal framework of Kauffman (1991) depicts the constraints of self-organization on the evolution of complex systems and the relation of self-organization to selection. We discuss his treatment of 'generic constraints' as sources of order (section 2) and the relation between adaptation and organization (section 3). We then raise a number of issues, including the role of adaptation in explaining order (section 4) and the limitations of formal approaches in explaining the distinctively biological (section 5). The principal question we pose is the relation of generic constraints on evolution to more specific local constraints, imposed, for example, by the characteristic materials out of which organisms are constructed, the accidental features characteristic of the Bauplan of a lineage, and the local vicissitudes of adaptation. We offer no answer to this large question.

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

Mechanistic models in molecular systems biology are generally mathematical models of the action of networks of biochemical reactions, involving metabolism, signal transduction, and/or gene expression. They can be either simulated numerically or analyzed analytically. Systems biology integrates quantitative molecular data acquisition with mathematical models to design new experiments, discriminate between alternative mechanisms and explain the molecular basis of cellular properties. At the heart of this approach are mechanistic models of molecular networks. We focus on the articulation and development of mechanistic models, identifying five constraints which guide the articulation of models in molecular systems biology. These constraints are not independent of one another, with the result that modeling becomes an iterative process. We illustrate the use of these constraints in the modeling of the mechanism for bistability in the lac operon.

Optimization models treat natural selection as a process tending to produce maximal adaptedness to the environment, measured on some "criterion scale" defining the optimal phenotype. These models are descriptively adequate if they describe the outcomes of evolutionary processes. They are dynamically adequate if the variables which describe the outcomes also are responsible for those evolutionary outcomes. Optimality models can be descriptively adequate, but dynamically unrealistic. Relying on cases from evolutionary ecology, I provide reasons to question the dynamic adequacy of optimality models, and offer reasons for distinguishing, at least at a theoretical level, between satisficing and optimizing.

Recent work on self organization promises an explanation of complex order which is independent of adaptation. Self-organizing systems are complex systems of simple units, projecting order as a consequence of localized and generally nonlinear interactions between these units. Stuart Kauffman offers one variation on the theme of self-organization, offering what he calls a ``statistical mechanics'' for complex systems. This paper explores the explanatory strategies deployed in this ``statistical mechanics,'' initially focusing on the autonomy of statistical explanation as it applies in evolutionary settings and then turning to Kauffman's analysis. Two primary morals emerge as a consequence of this examination: first, the view that adaptation and self-organization should be seen as competing theories or models is misleading and simplistic; and second, while we need a synthesis treating self-organization and adaptation as geared toward different problems, at different levels of organization, and deploying different methods, we do not yet have such a synthesis.

Developmental biology has resurfaced in recent years, often without a clearly central role for the organism. The organism is pulled in divergent directions: on the one hand, there is an important body of work that emphasizes the role of the gene in development, as executing and controlling embryological change; on the other hand, there are more theoretical approaches under which the organism disappears as little more than an instance for testing biological generalizations. I press here for the ineliminability of the organism in developmental biology on explanatory grounds. I examine classical work concerned with growth and development, particularly in Drosophila and C. elegans. Some of this work is suggestive of modular development, and accordingly suggests a level below that of the organism as being explanatory. These are not the only type of case. There are other equally well-established results, which indicate greater integration in the developing organism. Though with a modular organization the organism can be thought of as made up of its constituent traits, and though the explanations of these traits may lie in terms of cells or genes, even with modular development the explanations of "genetic" differences require an appeal to the organism. With non-modular organization the organism has an even more central role. This does not mean that these genetic or cellular contributions are unreal in any way, or that development requires some sort of vitalistic contribution; but the genetic contributions make sense only as constituents of the organism, embedded in a larger organic context

Evolutionary models can explain the dynamics of populations, how genetic, genotypic, or phenotypic frequencies change with time. Models incorporating chance, or drift, predict specific patterns of change. These are illustrated using classic work on blood types by Cavalli-Sforza and his collaborators in the Parma Valley of Italy, in which the theoretically predicted patterns are exhibited in human populations. These data and the models display properties of ensembles of populations. The explanatory problem needs to be understood in terms of how likely an observed change, in either a population or an ensemble, would be under drift alone; this is fundamentally a matter of chance. Understood in this way, issues of drift and chance undercut most recent philosophical, but not biological, discussions of the role of "genetic drift.".

  Evolutionary psychology purports to explain human capacities as adaptations to an ancestral environment. A complete explanation of human language or human reasoning as adaptations depends on assessing an historical claim, that these capacities evolved under the pressure of natural selection and are prevalent because they provided systematic advantages to our ancestors. An outline of the character of the information needed in order to offer complete adaptation explanations is drawn from Robert Brandon (1990), and explanations offered for the evolution of language and reasoning within evolutionary psychology are evaluated. Pinker and Bloom's (1992) defense of human language as an adaptation for verbal communication, Robert Nozick's (1993) account of the evolutionary origin of rationality, and Cosmides and Tooby's (1992) explanation of human reasoning as an adaptation for social exchange, are discussed in light of what is known, and what is not known, about the history of human evolution. In each case, though a plausible case is made that these capacities are adaptations, there is not enough known to offer even a semblance of an explanation of the origin of these capacities. These explanations of the origin of human thought and language are simply speculations lacking the kind of detailed historical information required for an evolutionary explanation of an adaptation