Attention, spatial representation and visual neglect: Simulating emergent attention and spatial memory in the Selective Attention for Identification Model (SAIM)
Dietmar Heinke, Glyn W. Humphreys
We present a computational model of human visual attention, termed SAIM (Selective Attention for Identification Model), based on the idea that there is competition between objects for recognition. SAIM uses a spatial window to select visual information for object recognition, ensuring both that parts are bound correctly within objects and that translation invariant object recognition can be achieved. We show how such a competitive model can provide a qualitative account of a range of psychological phenomena on both normal and disordered attention. Simulations of normal attention demonstrate two-object costs on selection, effects of familiarity on selection, global precedence, spatial cueing both within and between objects, and inhibition of return. When simulated lesions were conducted, SAIM demonstrated both unilateral neglect and spatial extinction, depending on the type and extent of the lesion. Different lesions also produced view-centred and object-centred neglect, enabling both forms of neglect to be simulated within a single patient. We discuss the relations between SAIM and others models in the literature, and we highlight how emergent properties of compeition with the model can unify (i) object- and space-based theories of normal selection, (ii) dissociations within the syndrome of visual neglect, (iii) 'attentional' and 'representational' accounts of neglect.