Multiplexing working memory and timing: Encoding retrospective and prospective information in transient neural trajectories.

联系PD/PI：博诺马诺，Dean V 摘要 大脑功能的一般原理是存储有关过去的信息以更好地预测和准备 未来。工作记忆和计时是两种计算功能，它们的进化使大脑能够使用最近的 关于过去的信息，以实现短期目标。工作记忆指的是瞬间储存的能力 信息以灵活的方式提供，而定时是指能够产生适时的马达响应，调制 及时注意，并预测外部事件何时发生。到目前为止，工作记忆和时间安排主要是 被视为独立的进程。我们在这里提出，因为大脑寻求使用关于过去的信息来 预测未来，工作记忆和时间往往是多重的。具体地说，活动的神经模式 在许多工作记忆任务的延迟期内记录的信息编码了关于 过去，以及对未来的预期预测。为了验证这一假设，我们开发了新的变种 延迟不匹配到样本任务，在该任务中，第一个提示预测延迟的持续时间，即项目有多长时间 必须保存在工作记忆中。这项任务将允许我们确定网络级别的群体响应是否对两者进行编码 关于延迟持续时间的过去和预期信息的回顾信息。初步结果来自一项 有监督的递归神经网络模型预测了神经活动模式的时间结构 从这两个方面来看，情况都会有所不同。这一预测将通过大规模的钙离子成像进行验证，以表征 与工作记忆和时间相关的脑区活动的时空模式。此外，光遗传 扰动实验和纵向表征神经活动的出现模式将是 已执行。这些实验反过来将被用来为旨在理解 神经元和电路层的学习规则是编码工作记忆和时间的模式出现的基础。 项目摘要/摘要第6页

Contact PD/PI: BUONOMANO, DEAN V Abstract A general principle of brain function is the ability to store information about the past to better predict and prepare for the future. Working memory and timing are two computational features that evolved to allow the brain to use recent information about the past to accomplish short-term goals. Working memory refers to the ability to transiently store information in a flexible manner, while timing refers to the ability to generate well timed motor responses, modulate attention in time, and predict when external events will occur. To date working memory and timing have primarily been treated as independent processes. Here we propose that because the brain seeks to use information about the past to predict the future, that working memory and timing are often multiplexed. Specifically, that the neural patterns of activity recorded during the delay period of many working memory tasks encodes both retrospective information about the past, as well as prospective predictions about the future. To test this hypothesis, we have developed novel variant of the delayed- nonmatch-to-sample task, in which the first cue predicts the duration of the delay, that is, how long an item must be held in working memory. This task will allow us to determine if network level population responses encode both retrospective information about the past and prospective information about delay duration. Preliminary results from a supervised recurrent neural network model predict that the temporal structure of the neural patterns of activity elicited by both cues will be different. This prediction will be tested using large scale Ca2+-imaging to characterize the spatiotemporal patterns of activity in brain areas associated with working memory and timing. Additionally, optogenetic perturbation experiments and longitudinal characterization of the emergence of neural patterns of activity will be performed. These experiments, will in turn, be used to ground computational studies aimed at understanding the neuronal and circuit level learning rules that underlie the emergence of patterns that encode working memory and time. Project Summary/Abstract Page 6