After more than 15 years of study, the 1/f noise or complex-systems approach to cognitive science has delivered promises of progress, colorful verbiage, and statistical analyses of phenomena whose relevance for cognition remains unclear. What the complex-systems approach has arguably failed to deliver are concrete insights about how people perceive, think, decide, and act. Without formal models that implement the proposed abstract concepts, the complex-systems approach to cognitive science runs the danger of becoming a philosophical exercise in futility. The complex-systems (...) approach can be informative and innovative, but only if it is implemented as a formal model that allows concrete prediction, falsification, and comparison against more traditional approaches. (shrink)

Four articles in this issue of topiCS (volume 4, issue 1) argue against a computational approach in cognitive science in favor of a dynamical approach. I concur that the computational approach faces some considerable explanatory challenges. Yet the dynamicists’ proposal that cognition is self-organized seems to only go so far in addressing these challenges. Take, for instance, the hypothesis that cognitive behavior emerges when brain and body (re-)configure to satisfy task and environmental constraints. It is known that for certain systems (...) of constraints, no procedure can exist (whether modular, local, centralized, or self-organized) that reliably finds the right configuration in a realistic amount of time. Hence, the dynamical approach still faces the challenge of explaining how self-organized constraint satisfaction can be achieved by human brains and bodies in real time. In this commentary, I propose a methodology that dynamicists can use to try to address this challenge. (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)

The complex systems approach to cognitive science invites a new understanding of extended cognitive systems. According to this understanding, extended cognitive systems are heterogenous, composed of brain, body, and niche, non-linearly coupled to one another. This view of cognitive systems, as non-linearly coupled brain–body–niche systems, promises conceptual and methodological advances. In this article we focus on two of these. First, the fundamental interdependence among brain, body, and niche makes it possible to explain extended cognition without invoking representations or computation. Second, (...) cognition and conscious experience can be understood as a single phenomenon, eliminating fruitless philosophical discussion of qualia and the so-called hard problem of consciousness. What we call “extended phenomenological-cognitive systems” are relational and dynamical entities, with interactions among heterogeneous parts at multiple spatial and temporal scales. (shrink)

Gestures and speech are clearly synchronized in many ways. However, previous studies have shown that the semantic similarity between gestures and speech breaks down as people approach transitions in understanding. Explanations for these gesture–speech mismatches, which focus on gestures and speech expressing different cognitive strategies, have been criticized for disregarding gestures’ and speech's integration and synchronization. In the current study, we applied three different perspectives to investigate gesture–speech synchronization in an easy and a difficult task: temporal alignment, semantic similarity, and (...) complexity matching. Participants engaged in a simple cognitive task and were assigned to either an easy or a difficult condition. We automatically measured pointing gestures, and we coded participant's speech, to determine the temporal alignment and semantic similarity between gestures and speech. Multifractal detrended fluctuation analysis was used to determine the extent of complexity matching between gestures and speech. We found that task difficulty indeed influenced gesture–speech synchronization in all three domains. We thereby extended the phenomenon of gesture–speech mismatches to difficult tasks in general. Furthermore, we investigated how temporal alignment, semantic similarity, and complexity matching were related in each condition, and how they predicted participants’ task performance. Our study illustrates how combining multiple perspectives, originating from different research areas (i.e., coordination dynamics, complexity science, cognitive psychology), provides novel understanding about cognitive concepts in general and about gesture–speech synchronization and task difficulty in particular. (shrink)