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A neuronal model of attentional spotlight: parietal guiding the temporal

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Abstract

Recent studies have reported an attentional feedback that highlights neural responses as early along the visual pathway as the primary visual cortex. Such filtering would help in reducing informational overload and in performing serial visual search by directing attention to individual locations in the visual field. The magnocellular (M) and parvocellular (P) subdivisions are two of the major parallel pathways in primate vision that originate in the retina and carry distinctly different types of information. The M pathway, characterized by its high sensitivity to movement and to low contrast stimuli, forms the predominant visual input into the dorsal, parietal stream in the neocortex. The P inputs, characterized by their colour selectivity and higher spatial resolution, are channeled mainly into the ventral, temporal stream. It is proposed that the attentional spotlight originates in the dorsal stream and helps in serially searching the field for conjunction of the relevant target features in the temporal stream, effectively performing a gating function on all visual inputs. This model predicts that a defect limited to the magnocellular or the dorsal pathway can lead to widespread deficits in cognitive abilities, including those functions that are largely based on parvocellular information. For example, the model provides a neural mechanism linking a peripheral defect in the magnocellular pathway to the reading disabilities in dyslexia. Even though there has been strong evidence for a magnocellular deficit in dyslexia, the paradox has been that the cognitive disability seems to be related to P pathway function. The scheme proposed here shows how M input may be vital for controlling sequential attention during reading.

Introduction

Over the last 40 years, we have made considerable progress in our knowledge of the visual pathways, in particular through electrophysiological investigations regarding the trigger features of cells at various levels of the visual system and also from psychophysical studies in humans and other primates. However, the natural world differs substantially from the visual stimuli used in these studies in many ways. One important respect in which it differs is that stimuli in real life rarely occur in isolation and the visual system is often confronted with a multitude of stimuli of different shapes, sizes, colours, depths and speeds of movement. Nevertheless, we are able to focus attention on one object and process just the relevant information, sometimes even doing this covertly while foveating elsewhere. We are also able to employ visual search over a large scene and find, for example, a known face in a crowd fairly rapidly. While doing all this, we can also quite effortlessly bind different features of an object together, so that we can attribute correctly say, the yellow colour to the banana and the red to the apple. One puzzling aspect of this capability is a large body of evidence (see later) which suggests that different stimulus attributes like colour, form and motion may be processed in different areas of the brain. Given this, how is the binding of features made possible? A neuronal model that provides a framework for visual attention should be able to address these questions satisfactorily.

This paper will briefly review some of the psychophysical and neurophysiological studies that are relevant to this problem and propose a neuronal scheme that can explain these data and make testable predictions.

Section snippets

A model of attention that incorporates a novel view of convergence of parallel pathways in vision

In proposing a neurophysiological basis for attention, this paper builds upon concepts that have been derived largely from psychophysical experiments over the last 20 years. These ideas and the relevant literature on parallel pathways in vision will be reviewed first.

Psychophysical consequences

This neural account of selective attention explains a number of psychophysical observations that have been difficult to reconcile fully with Treisman's original Feature Integration Theory and seem to fit better with its modified version, namely the guided search model [100]. Treisman's early examples [83]of conjunctions that required serial search were features that would be largely processed by the parvocellular pathways and the ventral stream. They in fact showed the typical dependence on

Relation to other models

The scheme outlined here stresses the importance of spatial selection in visual attention as have some others 19, 83, 86. It seems to contradict the alternative idea that attentional selection could be the result of competition between objects for dominance over neural resources rather than due to an early spatial filter 27, 28, 29. This latter model has gained considerable currency in recent years with the finding of within-modality competition in attentional tasks and single unit studies

Conclusions

In the present scheme, the following factors determine the time taken for visual search.

(1) Which of the features defining the target can be processed by the magnocellular dominated dorsal stream. To the extent that one or more defining features can be processed by the dorsal stream, the search would be parallel and therefore faster.

(2) The sizes and spatial separation of the targets that need to be processed by the ventral stream. When objects are crowded together in the visual world, the

Acknowledgements

I wish to thank M.B. Calford, M. Cook, B. Dreher and G.H. Henry for helpful criticism and J. Cappello for technical assistance. The work is supported by a grant from the National Health and Medical Research Council of Australia.

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