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

项目摘要 这项研究计划的最终目标是确定序列监测的神经机制。这 知识可以直接有助于理解顺序行为的疾病的新治疗方法， 强迫症（Obsessive-Compulsive Disorder，OCD）每天，我们监控着一系列的视觉信息 例如在寻找正确的出口时的一系列公共汽车或火车站。序列监测是主动的 跟踪后续“状态”或步骤的顺序的过程。监测不同于其他研究充分的 序列过程，如明确的记忆，或潜在的更自动的行为，如一系列的 电动机输出（例如，弹钢琴）或统计序列学习。然而，监测方面 序列处理在很大程度上仍是未知的。 跨序列的高阶相似性的知识（例如，AAAB，&@），抽象，可以帮助排序 监测.例如，理解游戏中每个回合所需的步骤，或游戏中的重复模式， 诗歌或歌曲，可以提高我们的意识和处理。摘要序列监测包括查看 具有抽象结构的序列，对这种结构的主动监测和响应。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征。 我们假设序列结构的一个关键元素，位置，是在外侧前额叶皮层中编码的 （LPFC）与相位爆发，在一起创建人口斜坡。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， 我们发现，增加（斜升）血氧水平依赖（BOLD）活动在吻侧LPFC的， 人对于序列执行是必需的并且是序列监控的基础（Desrochers等人，2015年a， 2019年）。在清醒状态下的fMRI中，我们观察到在执行结构化动作的猴子的LPFC中平行的BOLD斜坡， 序列查看任务。我们将使用这些数据专门针对电生理记录（Desrochers 例如，2015 b; Feingold*，Desrochers* 等人，2012）。该查看任务还提供了对以下内容的稳健的粗体响应： 观察序列偏差，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，并且可以以子区域特异性定位数据采集。 我们将系统地检验序列位置的特征是连续相位的假设， LPFC中的神经尖峰增加（目的1），并且与序列位置相关的神经活动受到调制 时间的流逝和奖励的期望（目标2）。序列监测是许多自然 行为。这些数据是唯一的指导下，并直接相关，功能磁共振成像映射。假设- 在这种驱动下，来自fMRI识别的大脑区域的这些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.