Some visual properties are consistent across a wide range of environments, while other properties are more labile. The efficient coding hypothesis states that many of these regularities in the environment can be discarded from neural representations, thus allocating more of the brain's dynamic range to properties that are likely to vary. This paradigm is less clear about how the visual system prioritizes different pieces of information that vary across visual environments. One solution is to prioritize information that can be used to predict future events, particularly those that guide behavior. The relationship between the efficient coding and future prediction paradigms is an area of active investigation. In this review, we argue that these paradigms are complementary and often act on distinct components of the visual input. We also discuss how normative approaches to efficient coding and future prediction can be integrated.

中文翻译：

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同一枚硬币的两面：高效且预测性的神经编码

一些视觉属性在各种环境中都是一致的，而其他属性则更加不稳定。有效编码假说指出，环境中的许多规律可以从神经表征中丢弃，从而将更多的大脑动态范围分配给可能变化的属性。该范式不太清楚视觉系统如何优先考虑因视觉环境而异的不同信息。一种解决方案是优先考虑可用于预测未来事件的信息，特别是那些指导行为的信息。高效编码和未来预测范式之间的关系是一个积极研究的领域。在这篇评论中，我们认为这些范式是互补的，并且通常作用于视觉输入的不同组成部分。我们还讨论了如何整合高效编码和未来预测的规范方法。