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。如果没有适应，视神经元的动态范围(1-2个数量级)不能在自然刺激的动态范围(10-11个数量级)上支持功能视觉。因此，视觉神经元不仅适应平均光照水平，而且适应最近视觉刺激的平均对比度。对比度适应的生理基础在哺乳动物的视觉系统中得到了广泛的研究，但其功能后果尚不清楚。对功能后果的直接测试将需要信息论方法。本研究将检验关于对比度适应在LGN中的作用的两个截然不同但并不相互排斥的假说：(1)LGN中的对比度适应在不同的对比度条件下用于维持敏感性，从而提高编码效率。(2)LGN中的对比度适应用于计算视觉信息的对比度不变表征。为了验证这些假说，我们将在体内使用LGN中的细胞外电极记录神经对闪烁的视觉刺激的反应。这些反应编码的视觉信息将使用包括信息论在内的几种计算方法进行评估。首先，我们将确定LGN中的增益变化是否符合理论预测，并测试增益变化是否与保持不同对比度的编码效率相关。其次，我们将确定当相同的刺激模式以不同的对比度呈现时，LGN的反应在哪些方面相同(S)，并测量LGN中有多少视觉信息是对比度不变的。最后，我们将构建一个模型来测试我们对LGN中对比适应的理解。通过比较自适应和不自适应模型的输出，我们将从对比度不变性和高效编码两个方面测试功能结果。这项研究将有助于我们描述感觉信息是如何通过丘脑传递到皮质以及为什么。这对对比度适应障碍的诊断或治疗，以及修复视力损失的神经假体的发展具有重要意义。

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.