International Centre for Neuromorphic Systems, MARCS Institute, Western Sydney University, Sydney, NSW 2747, Australia
International Centre for Neuromorphic Systems, MARCS Institute, Western Sydney University, Sydney, NSW 2747, Australia.
Neural Comput. 2024 Sep 17;36(10):1939-2029. doi: 10.1162/neco_a_01696.
Neural action potentials (APs) are difficult to interpret as signal encoders and/or computational primitives. Their relationships with stimuli and behaviors are obscured by the staggering complexity of nervous systems themselves. We can reduce this complexity by observing that "simpler" neuron-less organisms also transduce stimuli into transient electrical pulses that affect their behaviors. Without a complicated nervous system, APs are often easier to understand as signal/response mechanisms. We review examples of nonneural stimulus transductions in domains of life largely neglected by theoretical neuroscience: bacteria, protozoans, plants, fungi, and neuron-less animals. We report properties of those electrical signals-for example, amplitudes, durations, ionic bases, refractory periods, and particularly their ecological purposes. We compare those properties with those of neurons to infer the tasks and selection pressures that neurons satisfy. Throughout the tree of life, nonneural stimulus transductions time behavioral responses to environmental changes. Nonneural organisms represent the presence or absence of a stimulus with the presence or absence of an electrical signal. Their transductions usually exhibit high sensitivity and specificity to a stimulus, but are often slow compared to neurons. Neurons appear to be sacrificing the specificity of their stimulus transductions for sensitivity and speed. We interpret cellular stimulus transductions as a cell's assertion that it detected something important at that moment in time. In particular, we consider neural APs as fast but noisy detection assertions. We infer that a principal goal of nervous systems is to detect extremely weak signals from noisy sensory spikes under enormous time pressure. We discuss neural computation proposals that address this goal by casting neurons as devices that implement online, analog, probabilistic computations with their membrane potentials. Those proposals imply a measurable relationship between afferent neural spiking statistics and efferent neural membrane electrophysiology.
神经动作电位(APs)作为信号编码器和/或计算原语很难解释。由于神经系统本身的惊人复杂性,它们与刺激和行为的关系变得模糊不清。我们可以通过观察到“更简单”的无神经元生物也将刺激转化为影响其行为的短暂电脉冲来降低这种复杂性。没有复杂的神经系统,APs 通常更容易作为信号/响应机制来理解。我们回顾了理论神经科学在很大程度上忽略的生命领域中非神经刺激转换的例子:细菌、原生动物、植物、真菌和无神经元动物。我们报告了这些电信号的特性,例如幅度、持续时间、离子基础、不应期,特别是它们的生态目的。我们将这些特性与神经元进行比较,以推断神经元满足的任务和选择压力。在生命之树中,非神经刺激转换将行为反应与环境变化联系起来。无神经元生物用电信号的存在或不存在来表示刺激的存在或不存在。它们的转换通常对刺激具有高度的敏感性和特异性,但与神经元相比通常较慢。神经元似乎为了敏感性和速度而牺牲了其刺激转换的特异性。我们将细胞刺激转换解释为细胞在那一刻检测到重要东西的断言。特别是,我们将细胞的动作电位视为快速但嘈杂的检测断言。我们推断,神经系统的主要目标是在巨大的时间压力下,从嘈杂的感觉尖峰中检测到极其微弱的信号。我们讨论了神经计算的提案,这些提案通过将神经元作为其膜电位实现在线、模拟、概率计算的设备来解决这个目标。这些提案意味着传入神经尖峰统计数据和传出神经膜电生理学之间存在可测量的关系。