Investigating the neural representation of structured sequence viewing in the lateral prefrontal cortex of nonhuman primates

项目总结 本研究计划的最终目的是确定序列监测的神经机制。这 知识可以直接帮助理解对顺序行为是 被扰乱，如强迫症(OCD)。每天，我们都会监控视觉信息序列 例如，在寻找正确的出口时，需要一系列的公共汽车或火车停靠站。序列监控是主动的 跟踪后续“状态”或步骤的顺序的过程。监测有别于其他经过充分研究的 顺序过程，如外显记忆，或潜在的更自动的行为，如一系列 运动输出(例如，弹钢琴)或统计序列学习。然而，在监测方面， 序列处理在很大程度上仍然是未知的。 跨序列的高阶相似性(例如，AAAB、&@)、抽象的知识可以帮助序列 监控。例如，了解游戏中每个回合所需的步骤，或了解游戏中的重复模式 诗歌或歌曲，可以提高我们的意识和处理能力。摘要序列监控包括查看 具有抽象结构、对该结构的主动监测和响应的序列。在这里，我们将 使用被动结构化序列观察来确定抽象序列结构的神经表示。 我们假设序列结构的一个关键元素位置在外侧前额叶皮质中编码 (LPFC)，具有阶段性突发，总体上造成人口增长。这些神经动力学可以独特地 “标记”序列中的每个序列位置，支持监控。这一预测是基于先前的文献，并且 根据我们的发现，增加(斜坡)血氧水平依赖(BOLD)的活动在嘴端LPFC 人类对于序列执行是必要的并且是序列监测的基础(Desrocher等人，2015a， 2019年)。在清醒的fMRI中，我们观察到猴子在LPFC中平行的大胆坡度，这些猴子进行了结构化的 序列查看任务。我们将使用这些数据来专门针对电生理记录(Desrocher 等人，2015b；Feingold*，Desrocher*等人。2012年)。此查看任务还提供了强大而大胆的响应 查看顺序偏差并避免运动和决策混乱，同时提供实验 灵活性。通过使用这些活动模式来指导神经记录，我们消除了基于解剖学的需求 关于跨物种同源性的假设，并可以本地化具有次区域特异性的数据获取。 我们将系统地检验序列位置以连续的阶段为特征的假设 LPFC中神经峰电位的增加(目标1)，与序列位置相关的神经活动受到调制 通过时间流逝和回报期望(目标2)。序列监测是许多自然现象的基础 行为。这些数据在指导功能磁共振成像方面是独一无二的，并且与功能磁共振成像直接相关。而假设- 在驱动下，这些来自fMRI识别的大脑区域的记录的任何结果都将促进我们对此的理解 关键的过程。

PROJECT SUMMARY The ultimate goal of this research program is to determine the neural mechanisms of sequence monitoring. This knowledge can directly contribute to understanding new treatments for disorders where sequential behaviors are disrupted, such as Obsessive-Compulsive Disorder (OCD). Daily, we monitor sequences of visual information such as the series of bus or train stops when looking for the correct exit. Sequence monitoring is the active process of tracking the order of subsequent “states” or steps. Monitoring is distinct from other well-studied sequence processes, such as explicit memorization, or potentially more automatic behaviors such as a series of motor outputs (e.g., playing the piano) or statistical sequence learning. However, the monitoring aspects of sequence processing remain largely unknown. Knowledge of higher-order similarities across sequences (e.g., AAAB, &&&@), abstractions, can aid sequence monitoring. For example, understanding the steps required in each turn in a game, or the repetitive pattern in a poem or song, can improve our awareness and processing. Abstract sequence monitoring includes viewing the sequences that possess abstract structure, active monitoring of this structure, and response. Here, we will determine the neural representation of abstract sequential structure using passive structured sequence viewing. We hypothesize that a key element of sequence structure, position, is encoded in the lateral prefrontal cortex (LPFC) with phasic bursts that in aggregate create population ramping. These neural dynamics can uniquely “tag” each serial position in the sequence, supporting monitoring. This prediction is based on prior literature, and on our discovery that increasing (ramping) blood oxygen level-dependent (BOLD) activity in the rostral LPFC of humans is necessary for sequence execution and underlies sequence monitoring (Desrochers et al., 2015a, 2019). During awake fMRI, we observed parallel BOLD ramping in the LPFC of monkeys performing a structured sequence viewing task. We will use these data to specifically target electrophysiological recordings (Desrochers et al., 2015b; Feingold*, Desrochers* et al. 2012). This viewing task also provides robust BOLD responses to viewed sequence deviants and avoids motor and decision-making confounds while providing experimental flexibility. By using these activity patterns to guide neural recordings, we remove the need for anatomy-based assumptions about cross-species homology and can localize data acquisition with sub-region specificity. We will systematically test the hypotheses that sequence position is characterized by successive phasic increases in neural spiking in LPFC (Aim 1), and that neural activity related to sequence position is modulated by the passage of time and reward expectation (Aim 2). Sequence monitoring is fundamental to many natural behaviors. These data are unique in being guided by, and directly relatable-to, fMRI mapping. While hypothesis- driven, any outcome of these recordings from fMRI-identified brain areas will advance our understanding of this crucial process.