Data from: Spatiotemporal spike coding of behavioral adaptation in the dorsal anterior cingulate cortex

The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70–200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys’ behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators.

前额叶皮层（frontal cortex）负责在受复杂规则支配的环境中调控行为适应。多项研究已证实，当出现提示是否更新及如何更新行为策略的信息性事件后，神经元放电率的调制与行为适应密切相关。然而，这些神经元活动的时空特征是否参与编码即将发生的行为更新，目前仍不明确。我们以猕猴为研究对象，在其基于过往选择的反馈记忆调整行为的过程中，对背侧前扣带回皮层（dorsal anterior cingulate cortex，简称dACC）开展了相关研究。我们采用一种模拟不同具有生物学合理性的解码环路的算法，分析了单神经元单位以及成对同时记录的神经元的锋电位序列（spike train）。该方法可用于评估对锋电位计数（spike-count）敏感和对锋电位时序（spike-timing）敏感的解码器的性能。在接收到反馈信号时，单神经元会产生典型化的锋电位序列，其时间结构对信息性事件的识别准确率高于单纯依赖锋电位计数的方式。最优解码时间窗处于70~200毫秒范围内，这一区间显著短于行为任务所需的记忆时间尺度。尤为重要的是，单神经元的锋电位时间模式可预测猕猴的行为反应时。此外，成对同时记录的神经元之间，其锋电位模式的部分特征通常存在差异。综上，我们的研究结果表明，背侧前扣带回皮层通过复杂的时空锋电位编码调控行为适应。同时，该结果也提示，解码背侧前扣带回皮层反馈信号的下游神经网络，并非仅能作为神经积分器（neural integrators）发挥作用。