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基于离散情绪类别对Nencki情感图片系统的特征描述(NAPS BE)。

Characterization of the Nencki Affective Picture System by discrete emotional categories (NAPS BE).

作者信息

Riegel Monika, Żurawski Łukasz, Wierzba Małgorzata, Moslehi Abnoss, Klocek Łukasz, Horvat Marko, Grabowska Anna, Michałowski Jarosław, Jednoróg Katarzyna, Marchewka Artur

机构信息

Laboratory of Brain Imaging, Neurobiology Centre, Nencki Institute of Experimental Biology, 3, Pasteur Street, 02-093, Warsaw, Poland.

Laboratory of Psychophysiology, Department of Neurophysiology, Nencki Institute of Experimental Biology, Warsaw, Poland.

出版信息

Behav Res Methods. 2016 Jun;48(2):600-12. doi: 10.3758/s13428-015-0620-1.

Abstract

The Nencki Affective Picture System (NAPS; Marchewka, Żurawski, Jednoróg, & Grabowska, Behavior Research Methods, 2014) is a standardized set of 1,356 realistic, high-quality photographs divided into five categories (people, faces, animals, objects, and landscapes). NAPS has been primarily standardized along the affective dimensions of valence, arousal, and approach-avoidance, yet the characteristics of discrete emotions expressed by the images have not been investigated thus far. The aim of the present study was to collect normative ratings according to categorical models of emotions. A subset of 510 images from the original NAPS set was selected in order to proportionally cover the whole dimensional affective space. Among these, using three available classification methods, we identified images eliciting distinguishable discrete emotions. We introduce the basic-emotion normative ratings for the Nencki Affective Picture System (NAPS BE), which will allow researchers to control and manipulate stimulus properties specifically for their experimental questions of interest. The NAPS BE system is freely accessible to the scientific community for noncommercial use as supplementary materials to this article.

摘要

恩茨基情感图片系统(NAPS;马尔切夫卡、祖拉夫斯基、耶德诺罗格和格拉博夫斯卡,《行为研究方法》,2014年)是一套标准化的1356张逼真、高质量的照片,分为五类(人物、面孔、动物、物体和风景)。NAPS主要是沿着效价、唤醒和趋近-回避等情感维度进行标准化的,但迄今为止,这些图像所表达的离散情绪的特征尚未得到研究。本研究的目的是根据情感分类模型收集规范评分。从原始NAPS集中选取了510张图像的一个子集,以便按比例覆盖整个维度情感空间。在这些图像中,我们使用三种可用的分类方法,识别出引发可区分离散情绪的图像。我们引入了恩茨基情感图片系统的基本情绪规范评分(NAPS BE),这将使研究人员能够针对他们感兴趣的实验问题专门控制和操纵刺激属性。NAPS BE系统可供科学界免费用于非商业用途,作为本文的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/78cd/4891391/8d30e2d5fcbc/13428_2015_620_Fig1_HTML.jpg

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