Department of Biomedical Engineering, University of Rochester, NY 14642, USA.
J Acoust Soc Am. 2009 Nov;126(5):2390-412. doi: 10.1121/1.3238250.
There is growing evidence that the dynamics of biological systems that appear to be exponential over short time courses are in some cases better described over the long-term by power-law dynamics. A model of rate adaptation at the synapse between inner hair cells and auditory-nerve (AN) fibers that includes both exponential and power-law dynamics is presented here. Exponentially adapting components with rapid and short-term time constants, which are mainly responsible for shaping onset responses, are followed by two parallel paths with power-law adaptation that provide slowly and rapidly adapting responses. The slowly adapting power-law component significantly improves predictions of the recovery of the AN response after stimulus offset. The faster power-law adaptation is necessary to account for the "additivity" of rate in response to stimuli with amplitude increments. The proposed model is capable of accurately predicting several sets of AN data, including amplitude-modulation transfer functions, long-term adaptation, forward masking, and adaptation to increments and decrements in the amplitude of an ongoing stimulus.
越来越多的证据表明,在短时间内呈现指数动态的生物系统,在某些情况下,从长期来看,用幂律动态来描述更为合适。本文提出了一种内毛细胞和听觉神经(AN)纤维之间突触的速率适应模型,该模型同时包含指数和幂律动态。具有快速和短期时间常数的指数适应成分主要负责形成起始反应,其后是两条具有幂律适应的平行路径,提供缓慢和快速适应反应。缓慢适应的幂律成分显著提高了刺激后 AN 反应恢复的预测。更快的幂律适应对于解释对幅度递增刺激的反应的“可加性”是必要的。所提出的模型能够准确地预测多组 AN 数据,包括调幅传递函数、长期适应、前掩蔽和对持续刺激幅度的递增和递减的适应。