Janelia Research Campus, Ashburn, Virginia 20147, USA; email:
Annu Rev Neurosci. 2020 Jul 8;43:465-484. doi: 10.1146/annurev-neuro-080317-0621333. Epub 2020 Apr 13.
The brain contains a relatively simple circuit for forming Pavlovian associations, yet it achieves many operations common across memory systems. Recent advances have established a clear framework for learning and revealed the following key operations: ) pattern separation, whereby dense combinatorial representations of odors are preprocessed to generate highly specific, nonoverlapping odor patterns used for learning; ) convergence, in which sensory information is funneled to a small set of output neurons that guide behavioral actions; ) plasticity, where changing the mapping of sensory input to behavioral output requires a strong reinforcement signal, which is also modulated by internal state and environmental context; and ) modularization, in which a memory consists of multiple parallel traces, which are distinct in stability and flexibility and exist in anatomically well-defined modules within the network. Cross-module interactions allow for higher-order effects where past experience influences future learning. Many of these operations have parallels with processes of memory formation and action selection in more complex brains.
大脑中形成巴甫洛夫式联想的回路相对简单，但它完成了许多常见于记忆系统的操作。最近的研究进展为学习建立了一个清晰的框架，并揭示了以下关键操作：)模式分离，即对气味的密集组合表示进行预处理，以生成用于学习的高度特定且不重叠的气味模式；)汇聚，即将感官信息引导到一小部分输出神经元，这些神经元指导行为动作；)可塑性，其中改变感官输入到行为输出的映射需要一个强强化信号，该信号还受到内部状态和环境背景的调节；和)模块化，其中记忆由多个并行轨迹组成，这些轨迹在稳定性和灵活性方面存在差异，并且在网络中的解剖结构上定义明确的模块中存在。跨模块交互允许进行更高阶的影响，其中过去的经验会影响未来的学习。这些操作中的许多都与更复杂大脑中的记忆形成和动作选择过程类似。
