N. Lobato-Dauzier, A. Baccouche, G. Gines, T. Levi, Y. Rondelez, T. Fujii, S. H. Kim, N. Aubert-Kato, A. J. Genot
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引用次数: 0
摘要
复杂的生物体通过感觉神经元感知周围环境,这些神经元将物理刺激编码为尖峰电活动。过去几十年来,从神经元中汲取灵感的计算方法层出不穷,其中包括利用化学反应模拟人工神经网络的 DNA 化学神经元。然而,它们缺乏生物感知神经元的物理传感和时间编码。在这里,我们报告了一种基于DNA和酶的热感化学神经元,当暴露在寒冷环境中时,它的化学活性会出现尖峰。令人惊讶的是,这种化学神经元与冷痛觉神经元的玩具模型在数学上有很深的相似之处:它们在静止和振荡之间遵循相似的分岔路线,并避免了与典型分岔相关的伪现象(如不可逆、阻尼或不适时尖峰)。我们通过将数字和模拟热信息编码成化学波形,在实验中证明了这种鲁棒性。这种化学神经元可为在 DNA 中实现第三代神经网络模型(尖峰网络)铺平道路,并为联想学习打开大门。复杂生物通过感觉神经元感知周围环境,这些神经元将物理刺激编码为尖峰电活动。这里报告的是一种基于 DNA 和酶的热感化学神经元,当暴露在寒冷环境中时,这种神经元会产生尖峰化学反应。
Neural coding of temperature with a DNA-based spiking chemical neuron
Complex organisms perceive their surroundings with sensory neurons that encode physical stimuli into spikes of electrical activities. The past decades have seen a throve of computing approaches taking inspiration from neurons, including reports of DNA-based chemical neurons that mimic artificial neural networks with chemical reactions. Yet, they lack the physical sensing and temporal coding of sensory biological neurons. Here we report a thermosensory chemical neuron based on DNA and enzymes that spikes with chemical activity when exposed to cold. Surprisingly, this chemical neuron shares deep mathematical similarities with a toy model of a cold nociceptive neuron: they follow a similar bifurcation route between rest and oscillations and avoid artefacts associated with canonical bifurcations (such as irreversibility, damping or untimely spiking). We experimentally demonstrate this robustness by encoding—digitally and analogically—thermal messages into chemical waveforms. This chemical neuron could pave the way for implementing the third generation of neural network models (spiking networks) in DNA and opens the door for associative learning. Complex organisms perceive their surroundings with sensory neurons that encode physical stimuli into spikes of electrical activities. Here a thermosensory chemical neuron based on DNA and enzymes has been reported, which spikes with chemical activity when exposed to cold.