Visual periodicity reveals distinct attentional signatures for face and non-face categories

被引:0
|
作者
Quek, Genevieve L. [1 ]
de Heering, Adelaide [2 ]
机构
[1] Western Sydney Univ, MARCS Inst Brain, Westmead Innovat Quarter, 160 Hawkesbury Rd, Westmead, NSW 2145, Australia
[2] Univ libre Bruxelles ULB, Ctr Res Cognit & Neurosci CRCN, Unite Rech Neurosci Cognit UNESCOG, ULB Neurosci Inst UNI, Ave Franklin Roosevelt,50-CP191, B-1050 Brussels, Belgium
关键词
face perception; selective attention; EEG; frequency tagging; object recognition; TOP-DOWN SUPPRESSION; SELECTIVE ATTENTION; SPATIAL ATTENTION; HUMAN BRAIN; DISCRIMINATION; PERCEPTION; IDENTIFICATION; INFORMATION; MECHANISMS; RESPONSES;
D O I
10.1093/cercor/bhae228
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Observers can selectively deploy attention to regions of space, moments in time, specific visual features, individual objects, and even specific high-level categories-for example, when keeping an eye out for dogs while jogging. Here, we exploited visual periodicity to examine how category-based attention differentially modulates selective neural processing of face and non-face categories. We combined electroencephalography with a novel frequency-tagging paradigm capable of capturing selective neural responses for multiple visual categories contained within the same rapid image stream (faces/birds in Exp 1; houses/birds in Exp 2). We found that the pattern of attentional enhancement and suppression for face-selective processing is unique compared to other object categories: Where attending to non-face objects strongly enhances their selective neural signals during a later stage of processing (300-500 ms), attentional enhancement of face-selective processing is both earlier and comparatively more modest. Moreover, only the selective neural response for faces appears to be actively suppressed by attending towards an alternate visual category. These results underscore the special status that faces hold within the human visual system, and highlight the utility of visual periodicity as a powerful tool for indexing selective neural processing of multiple visual categories contained within the same image sequence.
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页数:16
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