Event-Related Potentials Dissociate Effects of Salience and Space in Biased Competition for Visual Representation

BACKGROUND: Selective visual attention is the process by which the visual system enhances behaviorally relevant stimuli and filters out others. Visual attention is thought to operate through a cortical mechanism known as biased competition. Representations of stimuli within cortical visual areas compete such that they mutually suppress each others' neural response. Competition increases with stimulus proximity and can be biased in favor of one stimulus (over another) as a function of stimulus significance, salience, or expectancy. Though there is considerable evidence of biased competition within the human visual system, the dynamics of the process remain unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here, we used scalp-recorded electroencephalography (EEG) to examine neural correlates of biased competition in the human visual system. In two experiments, subjects performed a task requiring them to either simultaneously identify two targets (Experiment 1) or discriminate one target while ignoring a decoy (Experiment 2). Competition was manipulated by altering the spatial separation between target(s) and/or decoy. Both experimental tasks should induce competition between stimuli. However, only the task of Experiment 2 should invoke a strong bias in favor of the target (over the decoy). The amplitude of two lateralized components of the event-related potential, the N2pc and Ptc, mirrored these predictions. N2pc amplitude increased with increasing stimulus separation in Experiments 1 and 2. However, Ptc amplitude varied only in Experiment 2, becoming more positive with decreased spatial separation. CONCLUSIONS/SIGNIFICANCE: These results suggest that N2pc and Ptc components may index distinct processes of biased competition--N2pc reflecting visual competitive interactions and Ptc reflecting a bias in processing necessary to individuate task-relevant stimuli

Modelling Visual Search with the Selective Attention for Identification Model (VS-SAIM): A Novel Explanation for Visual Search Asymmetries

In earlier work, we developed the Selective Attention for Identification Model (SAIM [16]). SAIM models the human ability to perform translation-invariant object identification in multiple object scenes. SAIM suggests that central for this ability is an interaction between parallel competitive processes in a selection stage and a object identification stage. In this paper, we applied the model to visual search experiments involving simple lines and letters. We presented successful simulation results for asymmetric and symmetric searches and for the influence of background line orientations. Search asymmetry refers to changes in search performance when the roles of target item and non-target item (distractor) are swapped. In line with other models of visual search, the results suggest that a large part of the empirical evidence can be explained by competitive processes in the brain, which are modulated by the similarity between target and distractor. The simulations also suggest that another important factor is the feature properties of distractors. Finally, the simulations indicate that search asymmetries can be the outcome of interactions between top-down (knowledge about search items) and bottom-up (feature of search items) processing. This interaction in VS-SAIM is dominated by a novel mechanism, the knowledge-based on-centre-off-surround receptive field. This receptive field is reminiscent of the classical receptive fields but the exact shape is modulated by both, top-down and bottom-up processes. The paper discusses supporting evidence for the existence of this novel concept