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Published on: July 5, 2015
The neural correlates of perceptual load induced attentional selection: an fMRI study
P Wei1, A J Szameitat, H J Müller
1Beijing Key Laboratory of Learning and Cognition and Department of Psychology, Capital Normal University, Beijing 100048, China; Department of Psychology, LMU München, D-80802 München, Germany; Center for Brain and Cognition Sciences and Department of Psychology, Peking University, Beijing 100871, China.
Abstract:
The neural correlates of perceptual load induced attentional selection were investigated in an functional magnetic resonance imaging (fMRI) experiment in which attentional selection was manipulated through the variation of perceptual load in target search. Participants searched for a vertically or horizontally oriented bar among heterogeneously (the high load condition) or homogeneously (the low load condition) oriented distractor bars in the central display, which was flanked by a vertical or horizontal bar presented at the left or the right periphery. The search reaction times were longer when the central display was of high load than of low load, and were longer when the flanker was incongruent than congruent with the target. Importantly, the flanker congruency effect was manifested only in the low load condition, not in the high load condition, indicating that the perceptual load in target search determined whether the task-irrelevant flanker was processed. Imaging analyses revealed a set of fronto-parietal regions having higher activations in the high than in the low load condition. Anterior cingulate cortex (ACC) was more activated for the incongruent than for the congruent trials. Moreover, ACC and bilateral anterior insula were sensitive to the interaction between perceptual load and flanker congruency such that the activation differences between the incongruent and congruent conditions were significant in the low, but not in the high load condition. These results are consistent with the claim that ACC and bilateral anterior insula may exert executive control by selectively biasing processing in favor of task-relevant information and this biasing depends on the resources currently available to the control system.
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