The complex-systems approach to cognitive science seeks to move beyond the formalism of information exchange and to situate cognition within the broader formalism of energy flow. Changes in cognitive performance exhibit a fractal (i.e., power-law) relationship between size and time scale. These fractal fluctuations reflect the flow of energy at all scales governing cognition. Information transfer, as traditionally understood in the cognitive sciences, may be a subset of this multiscale energy flow. The cognitive system exhibits not just a single power-law (...) relationship between fluctuation size and time scale but actually exhibits many power-law relationships, whether over time or space. This change in fractal scaling, that is, multifractality, provides new insights into changes in energy flow through the cognitive system. We survey recent findings demonstrating the role of multifractality in (a) understanding atypical developmental outcomes, and (b) predicting cognitive change. We propose that multifractality provides insights into energy flows driving the emergence of cognitive structure. (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)
Readers of TopiCS are invited to join a debate about the utility of ideas and methods of complexity science. The topics of debate include empirical instances of qualitative change in cognitive activity and whether this empirical work demonstrates sufficiently the empirical flags of complexity. In addition, new phenomena discovered by complexity scientists, and motivated by complexity theory, call into question some basic assumptions of conventional cognitive science such as stable equilibria and homogeneous variance. The articles and commentaries that appear in (...) this issue also illustrate a new debate style format for topiCS. (shrink)
Physicians have developed a number of implicit and explicit approaches to complex medical decisions. Decision analysis is an explicit, quantitative method of clinical decision making that involves the separation of the probabilities of events from their relative values, or utilities. Its use can help physicians make difficult choices in a manner that promotes true patient participation. Decision analysis also provides a framework for the incorporation of data from multiple sources and for the assessment of the impact of uncertain data on (...) the final decision. Although this approach is imperfect, it represents a significant advance in clinical decision making. (shrink)
Reviews : Zygmunt Bauman, Intimations of Postmodernity ; Steven Seidman and David G. Wagner , Postmodernism and Social Theory ; Stephen Crook, Jan Pakulski and Malcolm Wa ters, Postmodernization: Change in Advanced Society ; Gianni Vattimo, The End of Modernity—Nihilism and Hermeneutics in Post-modern Culture.