Abstract
When searching for a target in a visual scene filled with distractors, the mechanism of inhibition of return prevents revisiting previously attended locations. We proposed a new computational model for the inhibition of return, which is able to examine priority or saliency map in a manner consistent with psychophysical findings. The basic elements of the model are two neural integrators connected with two inhibitory interneurons. The integrators keep the saliency value of the currently attended location in the working memory. The inhibitory inter-neurons modulate a feedforward flow of information between the saliency map and the output map which points to the location of interest. Computer simulations showed that the model is able to read-out the saliency map when the objects are moving or when eye movements are present. Also, it is able to simultaneously select more then one location, even when they are non-contiguous. The model can be considered as a neural implementation of the episodic theory of attention.
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Šetić, M., Domijan, D. (2008). A Computational Model of Saliency Map Read-Out during Visual Search. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_45
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DOI: https://doi.org/10.1007/978-3-540-87559-8_45
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