In this book, Newell makes the case for unified theories by setting forth a candidate.

The relation between mind and brain is one of the big scientific questions that has attracted scientists’ attention for centuries but also eluded their understanding. In this book, William Uttal provides a critical review of cognitive neuroscience, focusing on a specific question: What do the brain-imaging techniques developed in the last two decades or so—mostly functional magnetic resonance imaging and positron emission tomography —tell us about the brain-mind problem? His unambiguous and abrasive answer is: nothing.The book is organized in nine (...) chapters. The introductory chapter provides historical, methodological, and philosophical background. Importantly, it highlights a shift in the way neuroscientists think about modularity and localization. Traditionally, researchers using brain imaging have tended to subscribe to a strong view of modularity and localization, where distinct cognitive modules are assumed to be localized in well-defined regions of the brain. In the l .. (shrink)

For many years, the game of chess has provided an invaluable task environment for research on cognition, in particular on the differences between novices and experts and the learning that removes these differences, and upon the structure of human memory and its paramaters. The template theory presented by Gobet and Simon based on the EPAM theory offers precise predictions on cognitive processes during the presentation and recall of chess positions. This article describes the behavior of CHREST, a computer implementation of (...) the template theory, in a memory task when the presentation time is varied from one second to sixty, on the recall of game and random positions, and compares the model to human data. Strong players are better than weak players in both types of positions, especially with long presentation times, but even after brief presentations. CHREST predicts the data, both qualitatively and quantitatively. Strong players' superiority with random positions is explained by the large number of chunks they hold in LTM. Their excellent recall with short presentation times is explained by templates, a special class of chunks. CHREST is compared to other theories of chess skill, which either cannot account for the superiority of Masters in random positions or predict too strong a performance of Masters in such positions. (shrink)

This paper presents a computational model of the way humans inductively identify and aggregate concepts from the low-level stimuli they are exposed to. Based on the idea that humans tend to select the simplest structures, it implements a dynamic hierarchical chunking mechanism in which the decision whether to create a new chunk is based on an information-theoretic criterion, the Minimum Description Length (MDL) principle. We present theoretical justifications for this approach together with results of an experiment in which participants, exposed (...) to meaningless symbols, have been implicitly encouraged to create high-level concepts by grouping them. Results show that the designed model, called hereafter MDLChunker, makes precise quantitative predictions both on the kind of chunks created by the participants and also on the moment at which these creations occur. They suggest that the simplicity principle used to design MDLChunker is particularly efficient to model chunking mechanisms. The main interest of this model over existing ones is that it does not require any adjustable parameter. (shrink)