论文标题
感觉系统适应的非平衡动力学
Non-equilibrium dynamics of adaptation in sensory systems
论文作者
论文摘要
生物感觉系统使用适应性来响应广泛的环境信号，通过将其响应特性调整为刺激的统计数据，以最大程度地提高信息传输。我们得出了根据贝叶斯过滤器的连续刺激的均值和方差变化的最佳适应规则，并将它们映射到随机方程式上，将环境状态与控制响应函数的内部变量相结合。我们计算适应速度和准确性及其对信息传输的影响的数值和精确结果。我们发现，在有效适应的状态下，适应速度随环境的变化速度而定。最后，我们利用适应性和随机热力学之间的数学等效性来定量适应与熵产生速率定义的适应时间过程的不可逆性。我们的结果提出了一种以无模型和非参数方式对凭经验量化适应的方法。
Adaptation is used by biological sensory systems to respond to a wide range of environmental signals, by adapting their response properties to the statistics of the stimulus in order to maximize information transmission. We derive rules of optimal adaptation to changes in the mean and variance of a continuous stimulus in terms of Bayesian filters, and map them onto stochastic equations that couple the state of the environment to an internal variable controling the response function. We calculate numerical and exact results for the speed and accuracy of adaptation, and its impact on information transmission. We find that, in the regime of efficient adaptation, the speed of adaptation scales sublinearly with the rate of change of the environment. Finally, we exploit the mathematical equivalence between adaptation and stochastic thermodynamics to quantitatively relate adaptation to the irreversibility of the adaptation time course, defined by the rate of entropy production. Our results suggest a means to empirically quantify adaptation in a model-free and non-parametric way.
