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Our ability to select relevant information from the environment is limited by the resolution of attention – i.e., the minimum size of the region that can be selected. Neural mechanisms that underlie this limit and its development are not yet understood. Functional magnetic resonance imaging (fMRI) was performed during an object tracking task in 7- and 11-year-old children, and in young adults. Object tracking activated canonical fronto-parietal attention systems and motion-sensitive area MT in children as young as 7 years. Object tracking performance improved with age, together with stronger recruitment of parietal attention areas and a shift from low-level to higher-level visual areas. Increasing the required resolution of spatial attention – which was implemented by varying the distance between target and distractors in the object tracking task – led to activation increases in fronto-insular cortex, medial frontal cortex including anterior cingulate cortex (ACC) and supplementary motor area, superior colliculi, and thalamus. This core circuitry for attentional precision was recruited by all age groups, but ACC showed an age-related activation reduction. Our results suggest that age-related improvements in selective visual attention and in the resolution of attention are characterized by an increased use of more functionally specialized brain regions during the course of development.
Reaction times to previously ignored information are often delayed, a phenomenon referred to as negative priming (NP). Rothermund et al. (2005) proposed that NP is caused by the retrieval of incidental stimulus-response associations when consecutive displays share visual features but require different responses. In two experiments we examined whether the features (color, shape) that reappear in consecutive displays, or their level of processing (early-perceptual, late-semantic) moderate the likelihood that stimulus-response associations are retrieved. Using a perceptual matching task (Experiment 1), NP occurred independently of whether responses were repeated or switched. Only when implementing a semantic-matching task (Experiment 2), negative priming was determined by response-repetition as predicted by response-retrieval theory. The results can be explained in terms of a task-dependent temporal discrimination process (Milliken et al., 1998): Response-relevant features are encoded more strongly and/or are more likely to be retrieved than irrelevant features.
We introduce a computational model of the negative priming (NP) effect that includes perception, memory, attention, decision making, and action. The model is designed to provide a coherent picture across competing theories of NP. The model is formulated in terms of abstract dynamics for the activations of features, their binding into object entities, their semantic categorization as well as related memories and appropriate reactions. The dynamic variables interact in a connectionist network which is shown to be adaptable to a variety of experimental paradigms. We find that selective attention can be modeled by means of inhibitory processes and by a threshold dynamics. From the necessity of quantifying the experimental paradigms, we conclude that the specificity of the experimental paradigm must be taken into account when predicting the nature of the NP effect.