Guest Daniel R, Carney Laurel H
Department of Biomedical Engineering, University of Rochester, Rochester, New York 14627, USA.
Department of Neuroscience, University of Rochester, Rochester, New York 14627, USA.
J Acoust Soc Am. 2024 Dec 1;156(6):3954-3957. doi: 10.1121/10.0034457.
Power-law adaptation is a form of neural adaptation that has been recently implemented in a popular model of the mammalian auditory nerve to explain responses to modulated sound and adaptation over long time scales. However, the high computational cost of power-law adaptation, especially for longer simulations, means it must be approximated to be practically usable. Here, a straightforward scheme to approximate power-law adaptation is presented, demonstrating that the approximation improves on an existing approximation provided in the literature. Code that implements the new approximation is provided.
幂律适应是一种神经适应形式，最近已在哺乳动物听觉神经的一种流行模型中得以实现，用于解释对调制声音的响应以及长时间尺度上的适应情况。然而，幂律适应的高计算成本，尤其是对于较长时间的模拟，意味着必须对其进行近似处理才能实际应用。在此，提出了一种近似幂律适应的直接方案，证明该近似方法改进了文献中现有的一种近似方法。同时提供了实现新近似方法的代码。
