Susilo Tirta, McKone Elinor, Edwards Mark
Department of Psychology, Australian National University, Canberra, ACT 0200, Australia.
Vision Res. 2010 Feb 8;50(3):300-14. doi: 10.1016/j.visres.2009.11.016. Epub 2009 Nov 26.
Recent evidence has shown that face space represents facial identity information using two-pool opponent coding. Here we ask whether the shape of the monotonic neural response functions underlying such coding is linear (i.e. face space codes all equal-sized physical changes with equal sensitivity) or nonlinear (e.g. face space shows greater coding sensitivity around the average face). Using adaptation aftereffects and pairwise discrimination tasks, our results for face attributes of eye height and mouth height demonstrate linear shape; including for bizarre faces far outside the normal range. We discuss how linear coding explains some results in the previous literature, including failures to find that adaptation enhances face discrimination, and suggest possible reasons why face space can maintain detailed coding of values far outside the normal range. We also discuss specific nonlinear coding models needed to explain other findings, and conclude face space appears to use a mixture of linear and nonlinear representations.
最近的证据表明，面部空间使用双池对立编码来表示面部身份信息。在这里，我们探讨这种编码背后的单调神经反应函数的形状是线性的（即面部空间以相等的敏感性编码所有大小相等的物理变化）还是非线性的（例如面部空间在平均脸周围表现出更大的编码敏感性）。使用适应后效和成对辨别任务，我们关于眼睛高度和嘴巴高度等面部属性的结果表明是线性形状；包括对于远超出正常范围的怪异面孔。我们讨论线性编码如何解释先前文献中的一些结果，包括未能发现适应增强面部辨别能力，并提出面部空间能够维持对远超出正常范围的值进行详细编码的可能原因。我们还讨论了解释其他发现所需的特定非线性编码模型，并得出结论，面部空间似乎使用了线性和非线性表示的混合方式。
