School of Biomedical Sciences, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK.
Sussex Neuroscience, School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK.
Neuron. 2019 Jun 19;102(6):1211-1222.e3. doi: 10.1016/j.neuron.2019.04.002. Epub 2019 May 1.
Sensory systems must reduce the transmission of redundant information to function efficiently. One strategy is to continuously adjust the sensitivity of neurons to suppress responses to common features of the input while enhancing responses to new ones. Here we image the excitatory synaptic inputs and outputs of retinal ganglion cells to understand how such dynamic predictive coding is implemented in the analysis of spatial patterns. Synapses of bipolar cells become tuned to orientation through presynaptic inhibition, generating lateral antagonism in the orientation domain. Individual ganglion cells receive excitatory synapses tuned to different orientations, but feedforward inhibition generates a high-pass filter that only transmits the initial activation of these inputs, removing redundancy. These results demonstrate how a dynamic predictive code can be implemented by circuit motifs common to many parts of the brain.
感觉系统必须减少冗余信息的传递，才能有效地发挥作用。一种策略是不断调整神经元的敏感性，抑制对输入常见特征的反应，同时增强对新特征的反应。在这里，我们对视网膜神经节细胞的兴奋性突触输入和输出进行成像，以了解这种动态预测编码是如何在空间模式分析中实现的。双极细胞的突触通过突触前抑制变得对方向敏感，从而在方向域中产生侧向拮抗作用。单个神经节细胞接收对不同方向敏感的兴奋性突触，但前馈抑制产生高通滤波器，仅传递这些输入的初始激活，从而去除冗余。这些结果表明，动态预测代码如何通过大脑许多部分共有的电路模式来实现。
