SAIM : A Model of Visual Attention and

This paper examines the reason for a particular impairment of cognitive functioning in brain-damaged patients called visual neglect. To achieve this goal a Selective Attention Identiication Model (SAIM) was developed which performs translation-invariant object recognition. SAIM uses a constraint satisfaction routine based on a continuous Hop-eld network to map an object into a focus of attention. The simulation results show that SAIM is a successful model of visual attention and visual neglect. 1 Introduction There is a growing impact of neuropsychological ndings on the understanding of the cognitive functioning of the brain. (e.g 1]). Neuropsychology is mainly concerned with cognitive deecits of brain-damaged patients. In this article we focus on examine the reason for a particular impairment called "visual neglect". The term "visual neglect" is used to refer to brain-damaged patients who fail to respond appropriately to stimuli presented on the side of space contralateral to their brain lesion. They fail to eat food on one side of an object, to cancel lines on one side of a sheet, to draw one half of an object or to read words on one side of a text. Classically, neglect is related to lesions of the right parietal lobe 4]. In order to examine how visual neglect might emerge following damage to an object recognition system, we developed a model called SAIM (Selective Attention Identiication Model, Fig. 1), which aims at a translation-invariant object recognition 2] 5]. It does this by mapping from locations on a retina through to a smaller "attentional" window, the Focus of Attention (FOA), with activation within the FOA providing the input to an object recognition system. This approach is similar to the model of 7], which focused on anatomical issues, whereas our work concentrates on psychological and neuropyschological modelling.