Journal of cognitive neuroscience
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Stimuli of high emotional significance such as social threat cues are preferentially processed in the human brain. However, there is an ongoing debate whether or not these stimuli capture attention automatically and weaken the processing of concurrent stimuli in the visual field. This study examined continuous fluctuations of electrocortical facilitation during competition of two spatially separated facial expressions in high and low socially anxious individuals. ⋯ Heightened electrocortical engagement in socially anxious participants was present in the first second of stimulus viewing and was sustained for the entire presentation period. These results, based on a continuous measure of attentional resource allocation, support the view that stimuli of high personal significance are associated with early and sustained prioritized sensory processing. These cues, however, do not interfere with the electrocortical processing of a spatially separated concurrent face, suggesting that they are effective at capturing attention, but are weak competitors for resources.
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In contrast to visual object processing, relatively little is known about how the human brain processes everyday real-world sounds, transforming highly complex acoustic signals into representations of meaningful events or auditory objects. We recently reported a fourfold cortical dissociation for representing action (nonvocalization) sounds correctly categorized as having been produced by human, animal, mechanical, or environmental sources. However, it was unclear how consistent those network representations were across individuals, given potential differences between each participant's degree of familiarity with the studied sounds. ⋯ Despite some variation of networks for environmental sounds, our results verified the stability of a fourfold dissociation of category-specific networks for real-world action sounds both before and after familiarity training. Additionally, we identified cortical regions parametrically modulated by each of the three high-level perceptual sound attributes. We propose that these attributes contribute to the network-level encoding of category-specific acoustic knowledge representations.