Guiding behavior requires the brain to make predictions about future sensory
inputs. Here we show that efficient predictive computation starts at the
earliest stages of the visual system. We estimate how much information groups
of retinal ganglion cells carry about the future state of their visual inputs,
and show that every cell we can observe participates in a group of cells for
which this predictive information is close to the physical limit set by the
statistical structure of the inputs themselves. Groups of cells in the retina
also carry information about the future state of their own activity, and we
show that this information can be compressed further and encoded by downstream
predictor neurons, which then exhibit interesting feature selectivity.
Efficient representation of predictive information is a candidate principle
that can be applied at each stage of neural computation.

这项研究展示了高效预测计算从视觉系统的最早阶段开始，视网膜神经节细胞组可以有效地携带关于其视觉输入未来状态的信息，并且可以压缩到一定的极限，并被下游的预测神经元编码，并呈现有趣的特征选择性。