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面部特征形成轨迹:学习自然特征鲜明和漫画化面部的神经生理学关联。

Faces forming traces: neurophysiological correlates of learning naturally distinctive and caricatured faces.

机构信息

Department of Psychology, Friedrich Schiller University of Jena, Am Steiger 3, Haus 1, 07743 Jena, Germany.

出版信息

Neuroimage. 2012 Oct 15;63(1):491-500. doi: 10.1016/j.neuroimage.2012.06.080. Epub 2012 Jul 14.

Abstract

Distinctive faces are easier to learn and recognise than typical faces. We investigated effects of natural vs. artificial distinctiveness on performance and neural correlates of face learning. Spatial caricatures of initially non-distinctive faces were created such that their rated distinctiveness matched a set of naturally distinctive faces. During learning, we presented naturally distinctive, caricatured, and non-distinctive faces for later recognition among novel faces, using different images of the same identities at learning and test. For learned faces, an advantage in performance was observed for naturally distinctive and caricatured over non-distinctive faces, with larger benefits for naturally distinctive faces. Distinctive and caricatured faces elicited more negative occipitotemporal ERPs (P200, N250) and larger centroparietal positivity (LPC) during learning. At test, earliest distinctiveness effects were again seen in the P200. In line with recent research, N250 and LPC were larger for learned than for novel faces overall. Importantly, whereas left hemispheric N250 was increased for learned naturally distinctive faces, right hemispheric N250 responded particularly to caricatured novel faces. We conclude that natural distinctiveness induces benefits to face recognition beyond those induced by exaggeration of a face's idiosyncratic shape, and that the left hemisphere in particular may mediate recognition across different images.

摘要

独特的面孔比典型的面孔更容易学习和识别。我们研究了自然独特性与人为独特性对面孔学习表现和神经相关性的影响。最初非独特的面孔的空间变形被创建,使得它们的评定独特性与一组自然独特的面孔相匹配。在学习过程中,我们呈现了自然独特的、变形的和非独特的面孔,以便在新面孔中进行后续识别,学习和测试使用的是相同身份的不同图像。对于学习过的面孔,与非独特的面孔相比,自然独特的和变形的面孔在表现上具有优势,自然独特的面孔的优势更大。在学习过程中,独特的和变形的面孔会引起更负的枕颞 ERP(P200、N250)和更大的中央顶正性(LPC)。在测试时,最早的独特性效应再次出现在 P200 中。与最近的研究一致,与新面孔相比,学习过的面孔的 N250 和 LPC 总体上更大。重要的是,虽然学习过的自然独特面孔的左侧半球 N250 增加了,但右侧半球 N250 对变形的新面孔反应特别强烈。我们得出结论,自然独特性对面孔识别的促进作用超出了对面孔独特形状的夸张所带来的促进作用,特别是左侧半球可能介导了不同图像之间的识别。

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