In this volume, three aspects are examined: a) normal subjects, where new findings on spatial behavior are described. b) brain-lesioned subjects, where the ...

The traditional verbal/nonverbal dichotomy is inadequate for completely describing cerebral lateralization. Musical functions are not necessarily mediated by the right hemisphere; evidence for a specialist left-hemisphere mechanism dedicated to the encoded speech signal is weakening, and the right hemisphere possesses considerable comprehensional powers. Right-hemisphere processing is often said to be characterized by holistic or gestalt apprehension, and face recognition may be mediated by this hemisphere partly because of these powers, partly because of the right hemisphere's involvement in emotional affect, and (...) possibly through the hypothesized existence of a specialist face processor or processors in the right. The latter hypothesis may, however, suffer the same fate as the one relating to a specialist encodedness processor for speech in the left. Verbal processing is largely the province of the left because of this hemisphere's possession of sequential, analytic, time-dependent mechanisms. Other distinctions are special cases of an analytic/holistic dichotomy. More fundamentally, however, the left hemisphere is characterized by its mediation of discriminations involving duration, temporal order, sequencing, and rhythm, at thesensory level, and especially at themotorlevel. Spatial aspects characterize the right, the mapping of exteroceptive body space, and the positions of fingers, limbs, and perhaps articulators, with respect to actual and target positions. Thus there is a continuum of function between the hemispheres, rather than a rigid dichotomy, the differences being quantitative rather than qualitative, of degree rather than of kind. (shrink)

The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The (...) evidence speaks strongly against bottom-up approaches to vision. In particular, the constraints suggest an attentional mechanism that exploits knowledge of the specific problem being solved. This analysis of visual search performance in terms of attentional influences on visual information processing and complexity satisfaction allows a large body of neurophysiological and psychological evidence to be tied together. (shrink)

Purely parallel neural networks can model object recognition in brief displays – the same conditions under which illusory conjunctions have been demonstrated empirically. Correcting errors of illusory conjunction is the “tag-assignment” problem for a purely parallel processor: the problem of assigning a spatial tag to nonspatial features, feature combinations, and objects. This problem must be solved to model human object recognition over a longer time scale. Our model simulates both the parallel processes that may underlie illusory conjunctions and the serial (...) processes that may solve the tag-assignment problem in normal perception. One component of the model extracts pooled features and another provides attentional tags that correct illusory conjunctions. Our approach addresses two questions: How can objects be identified from simultaneously attended features in a parallel, distributed representation? How can the spatial selectional requirements of such an attentional process be met by a separation of pathways for spatial and nonspatial processing? Our analysis of these questions yields a neurally plausible simulation of tag assignment based on synchronizing feature processing activity in a spatial focus of attention. (shrink)