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Selection for Object Identification: Modelling Emergent Attentional Processes in Normality and Pathology

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Book cover 4th Neural Computation and Psychology Workshop, London, 9–11 April 1997

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

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Abstract

We report a model of translation-invariant object recognition: SAIM (for Selective Attention for Identification Model). In SAIM, objects compete in a “selection network” to achieve a mapping from their location on the retina to a translation-invariant “focus of attention”. We investigated spatially selective lesions affecting either the mapping from one side of the retina into the selection network, or the mapping from the selection network to one side of the attentional window. Lesions into the selection network produced a pattern of retinotopic neglect, with processing biased against stimuli on the affected side of the retina. Lesions out of the selection network produced a form of neglect that was tied to one side of an object irrespective of where the object fell on the retina. These different forms of neglect match patterns reported in brain lesioned human patients.We propose that forms of selection in vision emerge as a consequence of procedures for achieving viewpoint-independent object recognition.

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© 1998 Springer-Verlag London Limited

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Humphreys, G.W., Heinke, D. (1998). Selection for Object Identification: Modelling Emergent Attentional Processes in Normality and Pathology. In: Bullinaria, J.A., Glasspool, D.W., Houghton, G. (eds) 4th Neural Computation and Psychology Workshop, London, 9–11 April 1997. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-1546-5_9

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  • DOI: https://doi.org/10.1007/978-1-4471-1546-5_9

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-76208-9

  • Online ISBN: 978-1-4471-1546-5

  • eBook Packages: Springer Book Archive

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