Contrast Adaptation in the LGN

描述（由申请人提供）：视觉系统必须在广泛的照明条件下工作。没有适应，视觉神经元的动态范围（1-2个数量级）不能支持自然刺激的动态范围（10-11个数量级）的功能性视觉。因此，视觉神经元不仅适应平均光水平，而且适应最近视觉刺激的平均对比度。在哺乳动物视觉系统中，对比度适应的生理基础已被广泛研究，但其功能后果尚不清楚。功能后果的直接测试将需要一个信息理论的方法。所提出的研究将测试关于LGN中的对比度自适应功能的两个不同但不相互排斥的假设：（1）LGN中的对比度自适应用于在不同对比度条件下保持灵敏度并因此保持编码效率。(2)LGN中的对比度自适应用于计算视觉信息的对比度不变表示。为了验证这些假设，我们将记录神经反应闪烁的视觉刺激使用细胞外电极在LGN在体内。这些反应编码的视觉信息将使用几种计算方法进行评估，包括信息论。首先，我们将确定LGN中增益的变化是否符合理论预测，并测试增益变化是否与在对比度上保持编码效率相关。其次，我们将确定在什么方面（S）的LGN反应是相同的，当相同的刺激模式在不同的对比度，并测量多少视觉信息的LGN是对比度不变的。最后，我们将构建一个模型来测试我们对LGN中对比度适应的理解。通过比较有和没有适应的模型的输出，我们将测试对比度不变性和有效编码方面的功能后果。这项研究将有助于我们描述感觉信息如何通过丘脑传递到皮层以及为什么。这对于对比度适应障碍的诊断或治疗以及恢复视力丧失的神经修复术的发展可能是有价值的。

DESCRIPTION (provided by applicant): The visual system must function under a broad range of illumination conditions. Without adaptation, the dynamic range of visual neurons (1-2 orders of magnitude) could not support functional vision over the dynamic range of natural stimuli (10-11 orders of magnitude). Therefore visual neurons adapt, not only to the mean light level, but also to the average contrast of recent visual stimuli. The physiological basis of contrast adaptation has been studied extensively in the mammalian visual system, but its functional consequences are not known. A direct test of functional consequences will require an information theoretic approach. The proposed study would test two distinct but not mutually exclusive hypotheses about the function of contrast adaptation in the LGN: (1) Contrast adaptation in the LGN serves to maintain sensitivity and therefore coding efficiency under different contrast conditions. (2) Contrast adaptation in the LGN serves to compute a contrast-invariant representation of visual information. To test these hypotheses, we will record neural responses to flickering visual stimuli using extracellular electrodes in the LGN in vivo. The visual information encoded by these responses will be assessed using several computational approaches, including information theory. First we will determine whether the changes in gain in the LGN fit theoretical predictions and test whether gain changes are correlated with the maintenance of coding efficiency across contrasts. Second, we will determine in what respect(s) the LGN response is the same when the same stimulus patterns are presented at different contrasts, and measure how much of the visual information in the LGN is contrast invariant. Finally we will construct a model to test our understanding of contrast adaptation in the LGN. By comparing the output of the model with and without adaptation, we will test the functional consequences in terms of both contrast invariance and efficient coding. This study will contribute an important component to our description of how sensory information is relayed to cortex through the thalamus and why. This could be valuable for the diagnosis or treatment of disorders of contrast adaptation, and for the development of neural prosthetics to restore vision loss.