A computational model of stereoscopic prey capture in praying mantises.
A computational model of stereoscopic prey capture in praying mantises.
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DOI：
10.1371/journal.pcbi.1009666
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发表时间：
2022-05
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
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我们提出了一个简单的模型，可以解释螳螂捕食打击的立体敏感性。该模型由一个单一的“视差传感器”组成：一个对立体视差敏感的双目神经元，从而对与动物的距离敏感。该模型是密切基于已知的行为和神经生理特性的螳螂立体视觉。神经元的单眼输入反映时间变化，并且对对比度符号不敏感，使得传感器对眼间相关性不敏感。单眼感受野有一个兴奋中心和抑制周围，使它们根据大小进行调整。视差传感器线性组合来自两只眼睛的输入，应用阈值，然后应用指数输出非线性。传感器的活动代表了模型螳螂的瞬时攻击概率。我们整合这在刺激持续时间，以获得预期的罢工次数，以响应不同的立体视差，大小和垂直视差的移动目标。我们优化了模型的参数，使其预测与我们的经验数据一致的平均罢工率作为刺激规模和差距的函数。该模型证明能够再现相对广泛的调谐到大小和狭窄的调谐到立体视差看到螳螂罢工的行为。虽然该模型只有一个单一的中心周围的每只眼睛的感受野，它显示定性相同的大小和差距之间的相互作用，我们观察到在真实的螳螂：首选的大小增加模拟猎物的距离增加超过首选的距离。我们表明，这是因为一个立体的“假匹配”的刺激在一只眼睛的前沿和其在其他后缘之间的，将需要进一步的工作，以找到这种假匹配是否发生在真实的螳螂。重要的是，该模型还显示了现实的反应，刺激与垂直视差和对相同的刺激提供了一个“鬼匹配”，尽管没有被拟合到这些数据。这是昆虫立体视觉的第一个图像可计算模型，并再现了神经生理学和引人注目的行为的关键特征。螳螂是迄今为止已知的唯一一种使用立体（3D）视觉计算深度的昆虫。螳螂立体视觉似乎比人类立体视觉和大多数机器立体视觉算法更简单。因此，螳螂立体视觉的计算模型可能有益于机器人领域，特别是在计算能力有限的情况下。结合行为观察和神经生理学数据，我们提出了一个非常简单的模型结构来描述螳螂的猎物捕获反应。我们使用有关螳螂对其猎物的尺寸和距离偏好的有限可用数据来训练我们的模型参数。我们的简单模型能够定性地再现我们训练数据中先前无法解释的特征，并预测模型训练中未包含的其他经验数据中的关键观察结果。虽然我们相信我们的模型是一个部分和严重简化帐户螳螂立体视觉，我们的研究结果是支持我们的模型结构作为一个近似的大小和视差传感器时，螳螂捕捉猎物。
We present a simple model which can account for the stereoscopic sensitivity of praying mantis predatory strikes. The model consists of a single “disparity sensor”: a binocular neuron sensitive to stereoscopic disparity and thus to distance from the animal. The model is based closely on the known behavioural and neurophysiological properties of mantis stereopsis. The monocular inputs to the neuron reflect temporal change and are insensitive to contrast sign, making the sensor insensitive to interocular correlation. The monocular receptive fields have a excitatory centre and inhibitory surround, making them tuned to size. The disparity sensor combines inputs from the two eyes linearly, applies a threshold and then an exponent output nonlinearity. The activity of the sensor represents the model mantis’s instantaneous probability of striking. We integrate this over the stimulus duration to obtain the expected number of strikes in response to moving targets with different stereoscopic disparity, size and vertical disparity. We optimised the parameters of the model so as to bring its predictions into agreement with our empirical data on mean strike rate as a function of stimulus size and disparity. The model proves capable of reproducing the relatively broad tuning to size and narrow tuning to stereoscopic disparity seen in mantis striking behaviour. Although the model has only a single centre-surround receptive field in each eye, it displays qualitatively the same interaction between size and disparity as we observed in real mantids: the preferred size increases as simulated prey distance increases beyond the preferred distance. We show that this occurs because of a stereoscopic “false match” between the leading edge of the stimulus in one eye and its trailing edge in the other; further work will be required to find whether such false matches occur in real mantises. Importantly, the model also displays realistic responses to stimuli with vertical disparity and to pairs of identical stimuli offering a “ghost match”, despite not being fitted to these data. This is the first image-computable model of insect stereopsis, and reproduces key features of both neurophysiology and striking behaviour. The praying mantis is the only insect so far known to compute depth using stereoscopic (3D) vision. Mantis stereopsis appears to be simpler than human stereopsis and most machine sterovision algorithms. A computational model of mantis stereopsis may therefore be beneficial to the field of robotics, particularly where computational power is limited. Using a combination of behavioural observations and neurophysiological data, we propose a very simple model structure to describe the prey capture response in the praying mantis. We used the limited available data on the mantis’ size and distance preferences for its prey to train our model parameters. Our simple model is able to qualitatively reproduce previously unexplained characteristics of our training data, and predicts key observations in additional empirical data that was not included in the model training. Whilst we believe our model to be only a partial and heavily simplified account of mantis stereopsis, our results are supportive of our model structure as an approximation of the size and disparity sensors used by the mantis when catching its prey.
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影响因子：
4.5
作者：
Humenberger, Martin;Zinner, Christian;Vincze, Markus
通讯作者：
Vincze, Markus
影响因子：
16.2
作者：
Bahl, Armin;Serbe, Etienne;Borst, Alexander
通讯作者：
Borst, Alexander
DOI：
10.1242/jeb.143883
发表时间：
2017-07-15
期刊：
The Journal of experimental biology
影响因子：
--
作者：
Nityananda V;Read JCA
通讯作者：
Read JCA
影响因子：
4.3
作者：
Allenmark, Fredrik;Read, Jenny C. A.
通讯作者：
Read, Jenny C. A.
影响因子：
4.5
作者：
Ambrosch, Karina;Kubinger, Wilfried
通讯作者：
Kubinger, Wilfried