The sexing of day-old chicks has been regarded as an extraordinarily difficult perceptual task requiring years of extensive practice for its mastery. Experts can sex chicks at over 98% accuracy at a rate of 1,000 chicks per hour spending less than a half second viewing the cloacal region. Naive subjects were shown 18 pictures of cloacal regions of male and female chicks (in random appearing arrangement) and asked to judge the sex of each chick. The pictures included a number of rare and difficult configurations. The subjects were then instructed as to the location of a critical cloacal structure for which a simple contrast in shape (convex vs. concave or flat) could serve as an indicant of sex. When the subjects judged the pictures again (in a different order), accuracy increased from slightly above chance to a level comparable to that achieved by a sample of experts. The correlation (over items) between the naive subjects and the experts before instruction was .21; after instruction, .82. The instructions were based on an interview and observation of an expert who had spent 50 years sexing 55 million chicks. Much of the reported difficulty in developing perceptual expertise in this task may stem from the need to classify extremely rare configurations in which the convexity of the structure is not apparent. The rate of learning of these instances could be greatly increased through the use of simple instructions that specified the location of diagnostic contour contrasts. A parallel is drawn between learning to sex chicks and learning to classify tanks as friend or foe.

Observers judged whether 2 successive computer-displayed rotations of a cube were the same or different. With respect to the observers, each rotation was about a vertical axis (Y), a horizontal (line-of-sight) axis (Z), an axis tilted just 10 ° from vertical or horizontal, or a maximally oblique axis. Independently, with respect to the cube, each rotation was about a symmetry axis through opposite faces (F) or through opposite corners (C), an axis tilted 10 ° from one of these symmetry axes, or an axis of extreme nonsymmetry. Speed and accuracy of comparison decreased as the axes of the successive rotations departed from the canonical axes of the environment (Z, or especially, Y), or even more sharply, from the symmetry axes of the cube (C, or especially, F). The internalized principles that guide the perceptual representation of rigid motions evidently are ones of kinematic geometry more than of physics.Evidence from many sources has indicated that space is not psychologically isotropic. We and other animals are quickest and most accurate in detecting objects (e.g., Ogilvie & Taylor, 1958) and in discriminating objects or their orientations (e.g.,

No abstract

Cognitive Neuroscience in Europe PS reviews three strands of European cognitive/behavioral neuroscience.Here are reviews ofthree recent volumes from Europe representing three major traditions or fields that have led to the currently emerging field of "cognitive neuroscience": brain and behm'ior, neural networks and neuropsychology.In Brain and Behavior, Bures and his co-authors remind us that in spite ofits current glamour, molecular neurobiological approaches call ne~'er lead to an understanding of the brain substrates of behm'ior. Bures and Bure.sol'lj are pioneering and leading scientists ill the sllldy of brainbases of learning and memory. They are now approaching the end of their careers and possess great wisdom-this book must be read by anyone professing an interest ill brain and behm'ior.. Neural Computers is edited by two members of the new generation of workers in the field of neural networks. Rolf Eckmiller and Christoph~'on der Malsburg. This volumesurveys the current state of the field. primarily In Europe, but also in the US and Japan. Europe is launching a major IIell' multinational initiath'e in neural networks (ESPRIT). To date, the US. and to a somewhat lesser extent Japan, hm'e dominated the field. Judging by this~'olume, hown'er, the Europeans are not far behind. It remains true that the major thrust of this field is computational rather than biological, but sewral pieces in NeuralComputers represent attempts to bridge to more realistic biological neural networks. To me this is the fundamental problem yet to be soil'ed in the field of neural networks.In From Neuropsychology to Mental Structure, Tim Shallice oven'iell's progress in the past two decades in the field that can claim to be the cornerstone of cognith'e neuroscience. namely the characterization and analysis of the structures of the human mind from the sllldy of humans with brain damage. A major issue in the book is the current controversy al'er use ofilldh'idual case studies vs group studies. Bill the conceplllaifocus is on the modularity ofmental struclllre, a notion~'eT}' comfortable to those who work at a more analyticalle~'e1 on brain systems and functions in animal models.

No abstract