University of Nevada, Las Vegas, Interdisciplinary Program in Neuroscience, Las Vegas, NV 89154-1003, USA.
University of Nevada, Las Vegas, College of Medical Sciences, Las Vegas, NV 89154-1003, USA.
Curr Biol. 2024 Jul 8;34(13):2921-2931.e3. doi: 10.1016/j.cub.2024.05.045. Epub 2024 Jun 21.
Anterior cingulate cortex (ACC) activity is important for operations that require the ability to integrate multiple experiences over time, such as rule learning, cognitive flexibility, working memory, and long-term memory recall. To shed light on this, we analyzed neuronal activity while rats repeated the same behaviors during hour-long sessions to investigate how activity changed over time. We recorded neuronal ensembles as rats performed a decision-free operant task with varying reward likelihoods at three different response ports (n = 5). Neuronal state space analysis revealed that each repetition of a behavior was distinct, with more recent behaviors more similar than those further apart in time. ACC activity was dominated by a slow, gradual change in low-dimensional representations of neural state space aligning with the pace of behavior. Temporal progression, or drift, was apparent on the top principal component for every session and was driven by the accumulation of experiences and not an internal clock. Notably, these signals were consistent across subjects, allowing us to accurately predict trial numbers based on a model trained on data from a different animal. We observed that non-continuous ramping firing rates over extended durations (tens of minutes) drove the low-dimensional ensemble representations. 40% of ACC neurons' firing ramped over a range of trial lengths and combinations of shorter duration ramping neurons created ensembles that tracked longer durations. These findings provide valuable insights into how the ACC, at an ensemble level, conveys temporal information by reflecting the accumulation of experiences over extended periods.
前扣带皮层(ACC)的活动对于需要整合随时间推移的多种经验的操作很重要,例如规则学习、认知灵活性、工作记忆和长期记忆召回。为了阐明这一点,我们在大鼠在长达一小时的会议期间重复相同行为时分析了神经元活动,以研究活动随时间如何变化。当大鼠在三个不同的响应端口执行具有不同奖励可能性的无决策操作性任务时,我们记录了神经元集合(n=5)。神经元状态空间分析表明,每次行为的重复都是不同的,最近的行为比时间相隔较远的行为更相似。ACC 活动主要由神经状态空间的低维表示的缓慢、渐进变化主导,与行为的节奏保持一致。每个会议的顶级主成分都明显存在时间进展或漂移,这是由经验的积累驱动的,而不是内部时钟。值得注意的是,这些信号在不同的主题之间是一致的,这使我们能够根据从另一个动物的数据训练的模型准确地预测试验次数。我们观察到,在较长时间(数十分钟)内非连续的斜坡发射率驱动了低维集合表示。40%的 ACC 神经元的发射率在一系列试验长度范围内呈斜坡状,而较短持续时间的斜坡神经元的组合创建了可以跟踪较长时间的集合。这些发现提供了宝贵的见解,说明 ACC 如何在集合层面通过反映经验的积累来传递时间信息。