Accelerating Motion Perception Model Mimics the Visual Neuronal Ensemble of Crab

Hao Luan, Mu Hua, Jigen Peng, Shigang Yue, Shengyong Chen, Qinbing Fu
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引用次数: 1

Abstract

In nature, crabs have a panoramic vision for the localization and perception of accelerating motion from local segments to global view in order to guide reactive behaviours including escape. The visual neuronal ensemble in crab plays crucial roles in such capability, however, has never been investigated and modelled as an artificial vision system. To bridge this gap, we propose an accelerating motion perception model (AMPM) mimicking the visual neuronal ensemble in crab. The AMPM includes two main parts, wherein the pre-synaptic network from the previous modelling work simulates 16 MLGI neurons covering the entire view to localize moving objects. The emphasis herein is laid on the original modelling of MLGIs' post-synaptic network to perceive accelerating motions from a global view, which employs a novel spatial-temporal difference encoder (STDE), and an adaptive spiking threshold temporal difference encoder (AT-TDE). Specifically, the STDE transforms “time-to-travel” between activations of two successive segments of MLG1 into excitatory post-synaptic current (EPSC), which decays with the elapse of time. The AT-TDE in two directional, i.e., counter-clockwise and clockwise accelerating detectors guarantees “non-firing” to constant movements. Accordingly, the accelerating motion can be effectively localized and perceived by the whole network. The systematic experiments verified the feasibility and robustness of the proposed method. The model responses to translational accelerating motion also fit many of the explored physiological features of direction selective neurons in the lobula complex of crab (i.e. lobula complex direction cells, LCDCs). This modelling study not only provides a reasonable hypothesis for such biological neural pathways, but is also critical for developing a new neuromorphic sensor strategy.
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加速运动感知模型模拟螃蟹的视觉神经元集合
在自然界中,螃蟹具有从局部到全局加速运动的定位和感知全景视野,以指导包括逃跑在内的反应性行为。然而,螃蟹的视觉神经元集合在这种能力中起着至关重要的作用,但从未作为人工视觉系统进行过研究和建模。为了弥补这一差距,我们提出了一种模拟螃蟹视觉神经元集合的加速运动感知模型(AMPM)。AMPM包括两个主要部分,其中来自先前建模工作的突触前网络模拟了覆盖整个视图的16个MLGI神经元来定位运动物体。本文重点介绍了mlgi突触后网络的原始建模,从全局角度感知加速运动,该模型采用了一种新的时空差分编码器(STDE)和自适应尖峰阈值时间差分编码器(AT-TDE)。具体来说,STDE将MLG1两个连续片段激活之间的“旅行时间”转化为兴奋性突触后电流(EPSC), EPSC随着时间的流逝而衰减。AT-TDE的两个方向,即逆时针和顺时针加速探测器,保证了恒定运动的“不着火”。因此,加速运动可以被整个网络有效地定位和感知。系统实验验证了该方法的可行性和鲁棒性。该模型对平移加速运动的响应也符合螃蟹小叶复合体(即小叶复合体方向细胞,lobula complex direction cells, LCDCs)中方向选择神经元的许多生理特征。该模型研究不仅为这种生物神经通路提供了合理的假设,而且对于开发新的神经形态传感器策略也至关重要。
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