Suppr超能文献

快速序列视觉呈现中人脸识别的实时测量。

Real-time measurement of face recognition in rapid serial visual presentation.

作者信息

Touryan Jon, Gibson Laurie, Horne James H, Weber Paul

机构信息

Boulder Center for Neurotechnology, Science Applications International Corporation Louisville, CO, USA.

出版信息

Front Psychol. 2011 Mar 11;2:42. doi: 10.3389/fpsyg.2011.00042. eCollection 2011.

Abstract

Event-related potentials (ERPs) have been used extensively to study the processes involved in recognition memory. In particular, the early familiarity component of recognition has been linked to the FN400 (mid-frontal negative deflection between 300 and 500 ms), whereas the recollection component has been linked to a later positive deflection over the parietal cortex (500-800 ms). In this study, we measured the ERPs elicited by faces with varying degrees of familiarity. Participants viewed a continuous sequence of faces with either low (novel faces), medium (celebrity faces), or high (faces of friends and family) familiarity while performing a separate face-identification task. We found that the level of familiarity was significantly correlated with the magnitude of both the early and late recognition components. Additionally, by using a single-trial classification technique, applied to the entire evoked response, we were able to distinguish between familiar and unfamiliar faces with a high degree of accuracy. The classification of high versus low familiarly resulted in areas under the curve of up to 0.99 for some participants. Interestingly, our classifier model (a linear discriminant function) was developed using a completely separate object categorization task on a different population of participants.

摘要

事件相关电位(ERPs)已被广泛用于研究识别记忆所涉及的过程。特别是,识别的早期熟悉成分与FN400(300至500毫秒之间的额中负向偏转)有关,而回忆成分与顶叶皮质上稍后出现的正向偏转(500至800毫秒)有关。在本研究中,我们测量了由不同熟悉程度的面孔引发的ERPs。参与者在执行单独的面孔识别任务时,观看了一系列具有低(新面孔)、中(名人面孔)或高(朋友和家人面孔)熟悉度的连续面孔。我们发现熟悉程度与早期和晚期识别成分的幅度显著相关。此外,通过使用应用于整个诱发反应的单试次分类技术,我们能够以高度的准确性区分熟悉和不熟悉的面孔。对于一些参与者,高熟悉度与低熟悉度的分类在曲线下面积高达0.99。有趣的是,我们的分类器模型(线性判别函数)是使用针对不同参与者群体的完全独立的物体分类任务开发的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb54/3110906/aa8f57383fac/fpsyg-02-00042-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验