Top-down selective visual attention: A neurodynamical approach

We propose a system of interconnected modules consisting of populations of neurons for modelling the underlying mechanisms involved in selective visual attention. We demonstrate that it is plausible to build a neural system for visual search, which works across the visual field in parallel, but, due to the intrinsic dynamics of the system, resembles apparent modes of visual attention, namely the serial focal and the parallel spread over the space mode. Thus, neither explicit serial focal search nor saliency maps need to be assumed. A focal attentional spotlight is not included in the system but rather focal attention emerges due to the convergence of the dynamic behaviour of the neural networks. The dynamics of the system can be interpreted as a mechanism for routing information from the sensory input.

[1]  William H. Press,et al.  Numerical recipes in C , 2002 .

[2]  J. Duncan,et al.  Competitive brain activity in visual attention , 1997, Current Opinion in Neurobiology.

[3]  E. Niebur,et al.  Modeling the Temporal Dynamics of IT Neurons in Visual Search: A Mechanism for Top-Down Selective Attention , 1996, Journal of Cognitive Neuroscience.

[4]  J. Riddoch,et al.  13. Competitive mechanisms of selection by space and object: a neuropsychological approach , 1996 .

[5]  Michael C. Mozer,et al.  Computational modeling of spatial attention , 1996 .

[6]  J. Wolfe,et al.  Guided Search 2.0 A revised model of visual search , 1994, Psychonomic bulletin & review.

[7]  B. C. Motter,et al.  Neural correlates of feature selective memory and pop-out in extrastriate area V4 , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[8]  B. Motter.  Neural correlates of attentive selection for color or luminance in extrastriate area V4 , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[9]  D. V. van Essen,et al.  A neurobiological model of visual attention and invariant pattern recognition based on dynamic routing of information , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[10]  John Duncan,et al.  A neural basis for visual search in inferior temporal cortex , 1993, Nature.

[11]  H. J. Muller,et al.  SEarch via Recursive Rejection (SERR): A Connectionist Model of Visual Search , 1993, Cognitive Psychology.

[12]  Michael C. Mozer,et al.  Perception of multiple objects - a connectionist approach , 1991, Neural network modeling and connectionism.

[13]  Daniel J. Amit,et al.  Quantitative Study of Attractor Neural Network Retrieving at Low Spike Rates: I , 1991 .

[14]  F. AbbottPhysics.  FIRING-RATE MODELS FOR NEURAL POPULATIONSL , 1991 .

[15]  John K. Tsotsos.  Analyzing vision at the complexity level , 1990, Behavioral and Brain Sciences.

[16]  R. H. Phaf,et al.  SLAM: A connectionist model for attention in visual selection tasks , 1990, Cognitive Psychology.

[17]  A. Treisman,et al.  Conjunction search revisited. , 1990, Journal of experimental psychology. Human perception and performance.

[18]  Susan L. Franzel,et al.  Guided search: an alternative to the feature integration model for visual search. , 1989, Journal of experimental psychology. Human perception and performance.

[19]  J. Duncan,et al.  Visual search and stimulus similarity. , 1989, Psychological review.

[20]  A. Treisman.  Features and Objects: The Fourteenth Bartlett Memorial Lecture , 1988, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[21]  Henry C. Tuckwell,et al.  Introduction to theoretical neurobiology , 1988 .

[22]  G W Humphreys,et al.  Visual search for targets defined by combinations of color, shape, and size: An examination of the task constraints on feature and conjunction searches , 1987, Perception & psychophysics.

[23]  F. Crick.  Function of the thalamic reticular complex: the searchlight hypothesis. , 1984, Proceedings of the National Academy of Sciences of the United States of America.

[24]  A. Treisman.  Perceptual grouping and attention in visual search for features and for objects. , 1982, Journal of experimental psychology. Human perception and performance.

[25]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

[26]  J. Duncan.  The locus of interference in the perception of simultaneous stimuli. , 1980, Psychological review.

[27]  Alan S. Brown,et al.  Information Processing and Cognition: The Loyola Symposium , 1976 .

[28]  M. Posner,et al.  Attention and cognitive control. , 1975 .

[29]  Charles Curtis Eriksen,et al.  The extent of processing of noise elements during selective encoding from visual displays , 1973 .

[30]  J. Deutsch.  Perception and Communication , 1958, Nature.

[31]  C. L. M..  The Psychology of Attention , 1890, Nature.