Wilson Hugh R, Diaconescu Andreea
Department of Biology and Centre for Vision Research, York University, Toronto, Ont., Canada M3J 1P3.
Vision Res. 2006 Nov;46(24):4143-51. doi: 10.1016/j.visres.2006.08.001. Epub 2006 Sep 27.
The effects of learning on the geometry of face space were investigated by measuring thresholds for discrimination and recognition of synthetic faces. This was based on a novel experimental technique that permitted measurement of psychometric functions for face recognition. Two major results were obtained. First, thresholds for face recognition were significantly better than thresholds for discrimination among novel faces. Second, rapid discrimination in the neighborhood of learned faces was better than discrimination near novel faces. Control experiments showed that this discrimination improvement occurred only with learned faces, and it could not be explained by generalized discrimination learning. Thus, face learning selectively alters or distorts face space in the vicinity of learned faces. This alteration may be due to an improvement in the signal/noise ratio as a result of face learning.
通过测量合成面孔识别和辨别阈值，研究了学习对面孔空间几何结构的影响。这基于一种新颖的实验技术，该技术允许测量人脸识别的心理测量函数。获得了两个主要结果。第一，人脸识别的阈值明显优于新面孔辨别阈值。第二，在熟悉面孔附近的快速辨别能力优于新面孔附近的辨别能力。对照实验表明，这种辨别能力的提高仅发生在熟悉面孔上，且不能用广义辨别学习来解释。因此，面孔学习会选择性地改变或扭曲熟悉面孔附近的面孔空间。这种改变可能是由于面孔学习导致信号/噪声比提高所致。
