Neural networks predict response biases of female túngara frogs.
Neural networks predict response biases of female túngara frogs.
复制标题
神经网络预测雌性通加拉青蛙的反应偏差。
DOI：
10.1098/rspb.1998.0293
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发表时间：
1998
期刊：
影响因子：
--
通讯作者：
Ryan,MJ
中科院分区：
文献类型：
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作者：
Phelps,SM;Ryan,MJ
人工神经网络已经成为有用的工具，用于探测感知偏差的起源，在没有明确的信息的基础神经基板。先前的研究已经表明，被选择用来识别或区分简单模式的神经网络可能对模式的大小或大小有着紧急的偏好，这种偏好通常由真实的女性表现出来，并且已经研究了这些偏好是如何塑造信号进化的。我们想知道简单的神经网络是否可以进化到对一个真正的配偶识别信号做出反应，这个信号就是汤加拉青蛙（Physalaemus pustulosus）的叫声。我们发现，网络不仅能够识别túngara青蛙的叫声，而且能够非常准确地定量预测雌性对许多新叫声的概括程度，并且这些预测在几种架构上都是稳定的。数据表明，P.脓疱雌性动物对叫声的反应可能常常是一种感觉系统的偶然副产品，这种感觉系统仅仅是为了识别物种而选择的。
Artificial neural networks have become useful tools for probing the origins of perceptual biases in the absence of explicit information on underlying neuronal substrates. Preceding studies have shown that neural networks selected to recognize or discriminate simple patterns may possess emergent biases toward pattern size or symmetry—preferences often exhibited by real females—and have investigated how these biases shape signal evolution. We asked whether simple neural networks could evolve to respond to an actual mate recognition signal, the call of the túngara frog,Physalaemus pustulosus. We found that not only were networks capable of recognizing the call of the túngara frog, but that they made remarkably accurate quantitative predictions about how well females generalized to many novel calls, and that these predictions were stable over several architectures. The data suggest that the degree to whichP. pustulosusfemales respond to a call may often be an incidental by–product of a sensory system selected simply for species recognition.