Drieu Céline, Zhu Ziyi, Wang Ziyun, Fuller Kylie, Wang Aaron, Elnozahy Sarah, Kuchibhotla Kishore
Department of Psychological and Brain Sciences, Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD, USA.
Johns Hopkins Kavli Neuroscience Discovery Institute, Baltimore, MD, USA.
Nature. 2025 Mar 19. doi: 10.1038/s41586-025-08730-8.
Rapid learning confers significant advantages on animals in ecological environments. Despite the need for speed, animals appear to only slowly learn to associate rewarded actions with predictive cues. This slow learning is thought to be supported by gradual changes to cue representation in the sensory cortex. However, evidence is growing that animals learn more rapidly than classical performance measures suggest, challenging the prevailing model of sensory cortical plasticity. Here we investigated the relationship between learning and sensory cortical representations. We trained mice on an auditory go/no-go task that dissociated the rapid acquisition of task contingencies (learning) from its slower expression (performance). Optogenetic silencing demonstrated that the auditory cortex drives both rapid learning and slower performance gains but becomes dispensable once mice achieve 'expert' performance. Instead of enhanced cue representations, two-photon calcium imaging of auditory cortical neurons throughout learning revealed two higher-order signals that were causal to learning and performance. A reward-prediction signal emerged rapidly within tens of trials, was present after action-related errors early in training, and faded in expert mice. Silencing at the time of this signal impaired rapid learning, suggesting that it serves an associative role. A distinct cell ensemble encoded and controlled licking suppression that drove slower performance improvements. These ensembles were spatially clustered but uncoupled from sensory representations, indicating higher-order functional segregation within auditory cortex. Our results reveal that the sensory cortex manifests higher-order computations that separably drive rapid learning and slower performance improvements, reshaping our understanding of the fundamental role of the sensory cortex.
快速学习赋予动物在生态环境中的显著优势。尽管需要速度,但动物似乎只能缓慢地学会将获得奖励的行为与预测线索联系起来。这种缓慢学习被认为是由感觉皮层中线索表征的逐渐变化所支持的。然而,越来越多的证据表明,动物学习的速度比传统性能指标所显示的要快,这对感觉皮层可塑性的主流模型提出了挑战。在这里,我们研究了学习与感觉皮层表征之间的关系。我们训练小鼠进行听觉Go/No-Go任务,该任务将任务偶然性(学习)的快速获取与其较慢的表现(性能)区分开来。光遗传学沉默表明,听觉皮层驱动快速学习和较慢的性能提升,但一旦小鼠达到“专家”水平,听觉皮层就变得不再必要。在整个学习过程中对听觉皮层神经元进行双光子钙成像,结果显示,并没有增强的线索表征,而是出现了两个对学习和性能有因果关系的高阶信号。一个奖励预测信号在几十次试验内迅速出现,在训练早期与动作相关的错误后仍然存在,并在专家小鼠中逐渐消失。在这个信号出现时进行沉默会损害快速学习,这表明它起到了关联作用。一个不同的细胞群编码并控制舔舐抑制,从而推动较慢的性能提升。这些细胞群在空间上聚集,但与感觉表征解耦,表明听觉皮层内存在高阶功能分离。我们的结果表明,感觉皮层表现出高阶计算,可分别驱动快速学习和较慢的性能提升,重塑了我们对感觉皮层基本作用的理解。