The visual playground environment.

<p>A single frame (a) captured during the course of a trial is shown and visible inside it are the pen, the gray center, and blue and green dots for the target and pointer objects, respectively. Representative pointer and target object trajectories on the screen from three-second excerpts with a normally behaving (b) and impaired (c) mouse are portrayed.</p

Means of the main measures used in the two experiments.

<p>Counting rates are averaged across consecutive 6-second-long blocks. Error bars are standard errors.</p

A schematic of two distinct model agent IDSs.

<p>The IDSs (delineated by the surrounding curves) are fluidly or softly assembled by virtue of rich interactions on multiple scales (double-sided arrows) among the components (black dots and hammer) are portrayed. They either span across (A) or do not (B) the tool (hammer). It is assumed that the black dots stand for bodily structures. Notice that interaction between the tool and the agent is present in both cases but in (B) it is impoverished, i.e. constrained to a single scale. Customarily, one studies such systems by collecting a time series locally from the behavior of a single point of observation (C), that is, from a single element. Next, if possible one establishes their character as an IDS by searching for power-law scaling of certain statistical quantities (D) as it was done, for example, in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009433#pone.0009433-vanOrden1" target="_blank">[21]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009433#pone.0009433-Holden1" target="_blank">[25]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009433#pone.0009433-vanOrden2" target="_blank">[26]</a>. The two fluctuation function plots representative of our data exemplify analysis of the behavior of the tool in (A) and (B) and were obtained using DFA which we applied instead of power spectrum analysis. The scaling coefficient reveals long-range correlations characteristic of noise in the hand-tool in normal mode (A) and approaches the uncorrelated white-noise level in (B).</p

DFA results per block for a representative trial.

<p>The x-component of the lines stands for the time coordinates of the analyzed block and the y-component is the scaling coefficient obtained for that particular block. The red lines in the middle are the ones that cover the perturbation section of the trial.</p

<b>Musical creativity and the embodied mind: Exploring the possibilities of 4E cognition and dynamical systems theory</b>

The phenomenon of creativity has received a growing amount of attention from scholars working across a range of disciplines. While this research has produced many important insights, it has also traditionally tended to explore creativity in terms of the reception of products or outcomes, conceiving of it as a cognitive process that is limited to the individual domain of the creative agent. More recently, however, researchers have begun to develop perspectives on creativity that highlight the patterns of adaptive embodied interaction that occur between multiple agents, as well as the broader socio- material milieu they are situated in. This has promoted new understandings of creativity, which is now often considered as a distributed phenomenon. Because music involves such a wide range of socio-cultural, bodily, technological, and temporal dimensions it is increasingly taken as a paradigmatic example for researchers who wish to explore creativity from this more relational perspective. In this article, we aim to contribute to this project by discussing musical creativity in light of recent developments in embodied cognitive science. More specifically, we will attempt to frame an approach to musical creativity based in an 4E (embodied, embedded, enactive, and extended) understanding of cognition. We suggest that this approach may help us better understand creativity in terms of how interacting individuals and social groups bring forth worlds of meaning through shared, embodied processes of dynamic interactivity. We also explore how dynamical systems theory (DST) may offer useful tools for research and theory that align closely with the 4E perspective. To conclude, we summarize our discussion and suggest possibilities for future research.</p