Neural Evidence for Attentional Capture by Salient Distractors
51 Pages Posted: 6 Jun 2023 Publication Status: Review Complete
More...Abstract
Salient objects often capture our attention, serving as distractors and hindering our current goals. It remains unclear when and how salient distractors interact with our goals and our knowledge on the neural mechanisms responsible for attentional capture is limited to a few brain regions recorded from non-human primates. Here we conducted a multivariate analysis on human intracranial signals covering most brain regions, and successfully dissociated distractor-specific representations from target-arousal signals in the high-frequency (60-100 Hz) activity. We found that salient distractors were processed rapidly around 220 ms, while target-tuning attention was attenuated simultaneously, supporting initial capture by distractors. Notably, neuronal activity specific to the distractor representation was strongest in superior and middle temporal gyrus, amygdala, and anterior cingulate cortex, while there were smaller contributions from parietal and frontal cortices. These results provide neural evidence for attentional capture by salient distractors engaging a much larger network than previously appreciated.
Note:
Funding Information: This research was supported by the National Science and Technology Innovation 2030 Major Program (2022ZD0204802), and the National Natural Science Foundation of China grant (32000738) to BW, the Sanming Project of Medicine in Shenzhen (SZSM202003006) to XM.
Declaration of Interests: All authors approved the final version of the manuscript for submission and declared no competing financial interests.
Ethical Approval Statement: The present study was conducted according to the latest version of the Declaration of Helsinki and approved by the Medical Ethics Committee of Shenzhen University General Hospital. All participants gave verbal or written informed consent to participate in research.
Keywords: Attentional capture, salient distractor, intracranial EEG, IEM decoding Introduction
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