Part of Advances in Neural Information Processing Systems 18 (NIPS 2005)
Gregory Zelinsky, Wei Zhang, Bing Yu, Xin Chen, Dimitris Samaras
To investigate how top-down (TD) and bottom-up (BU) information is weighted in the guidance of human search behavior, we manipulated the proportions of BU and TD components in a saliency-based model. The model is biologically plausible and implements an artificial retina and a neuronal population code. The BU component is based on feature- contrast. The TD component is defined by a feature-template match to a stored target representation. We compared the model’s behavior at differ- ent mixtures of TD and BU components to the eye movement behavior of human observers performing the identical search task. We found that a purely TD model provides a much closer match to human behavior than any mixture model using BU information. Only when biological con- straints are removed (e.g., eliminating the retina) did a BU/TD mixture model begin to approximate human behavior.