Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
The perception of multiple objects: a connectionist approach
The perception of multiple objects: a connectionist approach
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
SAIM: A Model of Visual Attention and Neglect
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
The end of the line for a brain-damaged model of unilateral neglect
Journal of Cognitive Neuroscience
Dynamic visual attention model in image sequences
Image and Vision Computing
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Recently, we have introduced a computational model, termed Selective Attention Identification Model [SAIM: Heinke, Humphreys, Attention spatial representation and visual neglect: simulating emergent attention and spatial memory in the Selective Attention for Identification Model (SAIM), Psychol. Rev. 110 (1) (2003) 29]. SAIM aims at translation-invariant object identification by selecting objects and mapping them into a focus of attention (FOA). With this architecture, SAIM can model a wide range of experimental evidence on normal attention and attentional disorders. Here, we demonstrate how SAIM can produce two specially striking forms of visual disorder, within- and between-object neglect. Patients with within-object neglect tend to ignore parts of objects and patients with between-object neglect might omit complete objects presented next to another object. Importantly, both deficits can occur irrespective of the objects' positions in tile visual field (translation invariant). To simulate neglect, the selection mechanism in SAIM was lesioned. Importantly, the selection mechanism selects objects and, at the same time, produces a translation-invariant representation of the objects in the FOA. Consequently, the lesion can have a translation-invariant effect, allowing SAIM to simulate within- and between-object neglect. This result gives additional credence to SAIM's integral approach to attention and translation-invariant object identification.