Linking sensory input and its consequences is a fundamental brain operation. During behavior, the neural activity of neocortical and limbic systems often reflects dynamic combinations of sensory and task-dependent variables, and these "mixed representations" are suggested to be important for perception, learning, and plasticity. However, the extent to which such integrative computations might occur outside of the forebrain is less clear. Here, we conduct cellular-resolution two-photon Ca²⁺ imaging in the superficial "shell" layers of the inferior colliculus (IC), as head-fixed mice of either sex perform a reward-based psychometric auditory task. We find that the activity of individual shell IC neurons jointly reflects auditory cues, mice's actions, and behavioral trial outcomes, such that trajectories of neural population activity diverge depending on mice's behavioral choice. Consequently, simple classifier models trained on shell IC neuron activity can predict trial-by-trial outcomes, even when training data are restricted to neural activity occurring prior to mice's instrumental actions. Thus, in behaving mice, auditory midbrain neurons transmit a population code that reflects a joint representation of sound, actions, and task-dependent variables.

将感觉输入与其后果联系起来是一项基本的大脑操作。在行为过程中，新皮质和边缘系统的神经活动通常反映感觉和任务相关变量的动态组合，这些“混合表征”被认为对于感知、学习和可塑性很重要。然而，这种综合计算在多大程度上可能发生在前脑之外还不清楚。在这里，我们在下丘（IC）的表面“壳”层中进行细胞分辨率的双光子 Ca ²⁺成像，无论性别的头部固定小鼠执行基于奖励的心理测量听觉任务。我们发现，单个壳 IC 神经元的活动共同反映了听觉线索、小鼠的行为和行为试验结果，因此神经群体活动的轨迹根据小鼠的行为选择而有所不同。因此，即使训练数据仅限于小鼠工具动作之前发生的神经活动，针对 shell IC 神经元活动训练的简单分类器模型也可以预测逐次试验的结果。因此，在行为小鼠中，听觉中脑神经元传输反映声音、动作和任务相关变量的联合表示的群体代码。