We address the problem of musical variation (identification of different musical sequences as variations) and its implications for mental representations of music. According to reductionist theories, listeners judge the structural importance of musical events while forming mental representations. These judgments may result from the production of reduced memory representations that retain only the musical gist. In a study of improvised music performance, pianists produced variations on melodies. Analyses of the musical events retained across variations provided support for the reductionist account (...) of structural importance. A neural network trained to produce reduced memory representations for the same melodies represented structurally important events more efficiently than others. Agreement among the musicians' improvisations, the network model, and music‐theoretic predictions suggest that perceived constancy across musical variation is a natural result of a reductionist mechanism for producing memory representations. (shrink)

What is the relationship between complexity in the world and complexity in the mind? Intuitively, increasingly complex objects and events should give rise to increasingly complex mental representations (or perhaps a plateau in complexity after a certain point). However, a counterintuitive possibility with roots in information theory is an inverted U-shaped relationship between the “objective” complexity of some stimulus and the complexity of its mental representation, because excessively complex patterns might be characterized by surprisingly short computational descriptions (e.g., if they (...) are represented as having been generated “randomly”). Here, we demonstrate that this is the case, using a novel approach that takes the notion of “description” literally. Subjects saw static and dynamic visual stimuli whose objective complexity could be carefully manipulated, and they described these stimuli in their own words by giving freeform spoken descriptions of them. Across three experiments totaling over 10,000 speech clips, spoken descriptions of shapes (Experiment 1), dot-arrays (Experiment 2), and dynamic motion-paths (Experiment 3) revealed a striking quadratic relationship between the raw complexity of these stimuli and the length of their spoken descriptions. In other words, the simplest and most complex stimuli received the shortest descriptions, while those stimuli with a “medium” degree of complexity received the longest descriptions. Follow-up analyses explored the particular words used by subjects, allowing us to further explore how such stimuli were represented. We suggest that the mind engages in a kind of lossy compression for overly complex stimuli, and we discuss the utility of such freeform responses for exploring foundational questions about mental representation. (shrink)

The ultimate tool, it could be said, is the brain and body. Therefore, a way to understand tool use is to study the brain's control of the body. A more manageable aim is to use the tools of cognitive science to explore the planning of physical actions. Here, I focus on two kinds of physical acts which directly or indirectly involve tool use: producing finger‐press sequences, and walking and reaching for objects. The main question is how people make choices between (...) finger‐press sequences, and how people make choices between walk‐and‐reach sequences. Are the choices made with reference to motor imagery, in which case the longer the sequences are the longer it takes to choose between them, or are shortcuts taken which rely on distinctive features of the alternatives? The reviewed experiments favor the latter alternative. The general view of action planning emerging from this work is one in which action features are highlighted and held in memory, not just to choose between potential actions but also to control the unfolding of long actions over time. Speculations are offered about tool use. (shrink)

The arts are one of the most complex of human endeavours, and so it is fitting that a special issue on Complex Systems in Aesthetics and Arts is being published. As the editors of this special issue, we would like to thank the reviewers of the submitted papers for their hard work in making this issue possible, as well as the authors who submitted their work and were very responsive to the comments of the reviewers and editors.

Contemporary theories of learning postulate one or at most a small number of different learning mechanisms. However, people are capable of mastering a given task through qualitatively different learning paths such as learning by instruction and learning by doing. We hypothesize that the knowledge acquired through such alternative paths differs with respect to the level of abstraction and the balance between declarative and procedural knowledge. In a laboratory experiment we investigated what was learned about patterned letter sequences via either direct (...) instruction in the relevant patterns or practice in solving letter‐sequence extrapolation problems. Results showed that both types of learning led to mastery of the target task as measured by accuracy performance. However, behavioral differences emerged in how participants applied their knowledge. Participants given instruction showed more variability in the types of strategies they used to articulate their knowledge as well as longer solution times for generating the action implications of that knowledge as compared to the participants given practice. Results are discussed regarding the implications for transfer, generalization, and procedural application. Learning theories that claim generality should be tested against cross‐scenario phenomena, not just parametric variations of a single learning scenario. (shrink)

A central goal of cognitive science is to develop a general theory of transfer to explain how people use and apply their prior knowledge to solve new problems. Previous work has identified multiple mechanisms of transfer including (but not limited to) analogy, knowledge compilation, and constraint violation. The central hypothesis investigated in the current work is that the particular profile of transfer processes activated for a given situation depends on both (a) the type of knowledge to be transferred and how (...) it is represented, and (b) the processing demands of the transfer task. This hypothesis was investigated in two laboratory training studies. The results from Experiment 1 show that each mechanism predicts specific behavioural patterns of performance across a common set of transfer tasks. The results from Experiment 2 show that people can adaptively shift between transfer mechanisms depending on their prior knowledge and the characteristics of the task environment. A framework for the development of a general theory of transfer based on multiple mechanisms is proposed and implications of the theory are discussed for measuring and understanding knowledge transfer. (shrink)