Statistical models and sensory attention

Physiological investigations into the neural basis of sensory attention have led to puzzling and contradictory results. Attention can seemingly lead to increased, decreased and unchanged neural activities, according to features of attentional experiments that are not well understood. We take one particular case in which activities increase as a result of attention, model its possible statistical underpinning, and relate our model to other attentional suggestions. Increased activities in population codes are associated with increased certainty about the encoded quantities. This increased certainty has to come from somewhere; in our model it emerges from particular changes in the model's processing strategy.

[1]  N. Mackintosh.  A Theory of Attention: Variations in the Associability of Stimuli with Reinforcement , 1975 .

[2]  J. Pearce,et al.  A model for Pavlovian learning: Variations in the effectiveness of conditioned but not of unconditioned stimuli. , 1980 .

[3]  A. Dickinson.  Contemporary Animal Learning Theory , 1981 .

[4]  D G Pelli,et al.  Uncertainty explains many aspects of visual contrast detection and discrimination. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[5]  R. Desimone,et al.  Selective attention gates visual processing in the extrastriate cortex. , 1985, Science.

[6]  H. Spitzer,et al.  Increased attention enhances both behavioral and neuronal performance. , 1988, Science.

[7]  C. J. Downing.  Expectancy and visual-spatial attention: effects on perceptual quality. , 1988, Journal of experimental psychology. Human perception and performance.

[8]  S. Grossberg.  Neural Networks and Natural Intelligence , 1988 .

[9]  N. Graham.  Visual Pattern Analyzers , 1989 .

[10]  Allen Allport,et al.  Visual attention , 1989 .

[11]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

[12]  Richard S. Sutton,et al.  Adapting Bias by Gradient Descent: An Incremental Version of Delta-Bar-Delta , 1992, AAAI.

[13]  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.

[14]  B. C. Motter.  Focal attention produces spatially selective processing in visual cortical areas V1, V2, and V4 in the presence of competing stimuli. , 1993, Journal of neurophysiology.

[15]  H Sompolinsky,et al.  Simple models for reading neuronal population codes. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Charles H. Anderson,et al.  BASIC ELEMENTS OF BIOLOGICAL COMPUTATIONAL SYSTEMS , 1994 .

[17]  J. Palmer.  Set-size effects in visual search: The effect of attention is independent of the stimulus for simple tasks , 1994, Vision Research.

[18]  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.

[19]  Terence D. Sanger,et al.  Theoretical Considerations for the Analysis of Population Coding in Motor Cortex , 1994, Neural Computation.

[20]  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.

[21]  R. Desimone,et al.  Neural mechanisms of selective visual attention. , 1995, Annual review of neuroscience.

[22]  D. V. van Essen,et al.  Responses in area V4 depend on the spatial relationship between stimulus and attention. , 1996, Journal of neurophysiology.

[23]  A. H. C. van der Heijden.  17. Selective attention as a computational function , 1996 .

[24]  Peter Dayan,et al.  Neural Models for Part-Whole Hierarchies , 1996, NIPS.

[25]  L. Abbott,et al.  Invariant visual responses from attentional gain fields. , 1997, Journal of neurophysiology.

[26]  Peter Dayan,et al.  Statistical Models of Conditioning , 1997, NIPS.

[27]  D. V. van Essen,et al.  Spatial Attention Effects in Macaque Area V4 , 1997, The Journal of Neuroscience.

[28]  T. Sejnowski,et al.  Spatial Transformations in the Parietal Cortex Using Basis Functions , 1997, Journal of Cognitive Neuroscience.

[29]  B. C. Motter.  Neurophysiology of visual attention. , 1998 .

[30]  Alexandre Pouget,et al.  Probabilistic Interpretation of Population Codes , 1996, Neural Computation.

[31]  Carrie J. McAdams,et al.  Effects of Attention on Orientation-Tuning Functions of Single Neurons in Macaque Cortical Area V4 , 1999, The Journal of Neuroscience.

[32]  C W Tyler,et al.  Distraction of attention and the slope of the psychometric function. , 1999, Journal of the Optical Society of America. A, Optics, image science, and vision.