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

This long-awaited work by prominent Harvard psychologist Stephen Kosslyn integrates a twenty-year research program on the nature of high-level vision and mental ...

As we move around in our environment, and interact with it, many of the most important problems we face involve the processing of spatial information. We have to be able to navigate by perceiving and remembering the locations and orientations of the objects around us relative to ourself; we have to sense and act upon these objects; and we need to move through space to position ourselves in favourable locations or to avoid dangerous ones. While this appears so simple that (...) we don't even think about it, the difficulty of solving these problems has been shown in the repeated failure of artificial systems to perform these kinds of tasks efficiently. In contrast, humans and other animals routinely overcome these problems every single day. This book examines some of the neural substrates and mechanisms that support these remarkable abilities. The hippocampus and the parietal cortex have been implicated in various core spatial behaviours, such as the ability to localise an object and navigate to it. Damage to these areas in humans and animals leads to impairment of these spatial functions. This collection of papers, written by internationally recognized experts in the field, reviews the evidence that each area is involved in spatial cognition, examines the mechanisms underlying the generation of spatial behaviours, and considers the relative roles of the parietal and hippocampal areas, including how each interacts with the other. The papers integrate a wide range of theoretical and experimental approaches, and touch on broader issues relating to memory and imagery. As such, this book represents the state of the art of current research into the neural basis of spatial cognition. It should be of interest to anyone - researchers or graduate students - working in the areas of cognitive neuroscience, neuroanatomy, neuropsychology, and cognition generally. (shrink)

The term conceptual simulation refers to a type of everyday reasoning strategy commonly called “what if” reasoning. It has been suggested in a number of contexts that this type of reasoning plays an important role in scientific discovery; however, little direct evidence exists to support this claim. This article proposes that conceptual simulation is likely to be used in situations of informational uncertainty, and may be used to help scientists resolve that uncertainty. We conducted two studies to investigate the relationship (...) between conceptual simulation and informational uncertainty. Study 1 was an in vivo study of expert scientists; the results suggest that scientists do use conceptual simulation in situations of informational uncertainty, and that they use conceptual simulation to make inferences from their data using the analogical reasoning process of alignment by similarity detection. Study 2 experimentally manipulated experts' level of uncertainty and provides further support for the hypothesis that conceptual simulation is more likely to be used in situations of informational uncertainty. Finally, we discuss the relationship between conceptual simulation and other types of reasoning using qualitative mental models. (shrink)

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find‐on‐map) or within an egocentric view of a space (find‐in‐scene). A (...) general strategy instantiated in a computational cognitive model of the find‐on‐map task, based on the results from, was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps. (shrink)