Faber Justin, Bozovic Dolores
Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, CA, United States.
California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, United States.
Front Neurol. 2024 Jul 10;15:1444617. doi: 10.3389/fneur.2024.1444617. eCollection 2024.
The remarkable signal-detection capabilities of the auditory and vestibular systems have been studied for decades. Much of the conceptual framework that arose from this research has suggested that these sensory systems rest on the verge of instability, near a Hopf bifurcation, in order to explain the detection specifications. However, this paradigm contains several unresolved issues. Critical systems are not robust to stochastic fluctuations or imprecise tuning of the system parameters. Further, a system poised at criticality exhibits a phenomenon known in dynamical systems theory as , where the response time diverges as the system approaches the critical point. An alternative description of these sensory systems is based on the notion of chaotic dynamics, where the instabilities inherent to the dynamics produce high temporal acuity and sensitivity to weak signals, even in the presence of noise. This alternative description resolves the issues that arise in the criticality picture. We review the conceptual framework and experimental evidence that supports the use of chaos for signal detection by these systems, and propose future validation experiments.
听觉和前庭系统卓越的信号检测能力已被研究了数十年。这项研究产生的许多概念框架表明，这些感觉系统处于不稳定的边缘，接近霍普夫分岔，以便解释检测规格。然而，这种范式包含几个未解决的问题。关键系统对随机波动或系统参数的不精确调整并不稳健。此外，处于临界状态的系统表现出动力系统理论中已知的一种现象，即当系统接近临界点时响应时间会发散。对这些感觉系统的另一种描述基于混沌动力学的概念，即动力学固有的不稳定性产生了高时间敏锐度和对微弱信号的敏感性，即使在存在噪声的情况下也是如此。这种替代描述解决了临界状态图景中出现的问题。我们回顾了支持这些系统利用混沌进行信号检测的概念框架和实验证据，并提出了未来的验证实验。
