Tkačik Gašper, Ghosh Anandamohan, Schneidman Elad, Segev Ronen
Institute of Science and Technology Austria, Klosterneuburg, Austria.
Indian Institute of Science Education and Research-Kolkata, Mohanpur (Nadia), India.
PLoS One. 2014 Jan 21;9(1):e85841. doi: 10.1371/journal.pone.0085841. eCollection 2014.
Adaptation in the retina is thought to optimize the encoding of natural light signals into sequences of spikes sent to the brain. While adaptive changes in retinal processing to the variations of the mean luminance level and second-order stimulus statistics have been documented before, no such measurements have been performed when higher-order moments of the light distribution change. We therefore measured the ganglion cell responses in the tiger salamander retina to controlled changes in the second (contrast), third (skew) and fourth (kurtosis) moments of the light intensity distribution of spatially uniform temporally independent stimuli. The skew and kurtosis of the stimuli were chosen to cover the range observed in natural scenes. We quantified adaptation in ganglion cells by studying linear-nonlinear models that capture well the retinal encoding properties across all stimuli. We found that the encoding properties of retinal ganglion cells change only marginally when higher-order statistics change, compared to the changes observed in response to the variation in contrast. By analyzing optimal coding in LN-type models, we showed that neurons can maintain a high information rate without large dynamic adaptation to changes in skew or kurtosis. This is because, for uncorrelated stimuli, spatio-temporal summation within the receptive field averages away non-gaussian aspects of the light intensity distribution.
视网膜中的适应性变化被认为可以优化自然光信号编码为发送至大脑的一系列脉冲。虽然之前已经记录了视网膜处理过程中对平均亮度水平变化和二阶刺激统计量的适应性变化，但当光分布的高阶矩发生变化时，尚未进行过此类测量。因此，我们测量了虎螈视网膜中神经节细胞对空间均匀、时间独立刺激的光强度分布的二阶（对比度）、三阶（偏度）和四阶（峰度）矩的受控变化的反应。刺激的偏度和峰度被选择为覆盖自然场景中观察到的范围。我们通过研究能够很好地捕捉所有刺激下视网膜编码特性的线性 - 非线性模型来量化神经节细胞中的适应性。我们发现，与对比度变化所观察到的变化相比，当高阶统计量变化时，视网膜神经节细胞的编码特性仅发生微小变化。通过分析LN型模型中的最优编码，我们表明神经元可以在不对偏度或峰度变化进行大的动态适应的情况下维持高信息率。这是因为，对于不相关的刺激，感受野内的时空总和会平均掉光强度分布的非高斯方面。
