CRCNS US-Spain Research Proposal: Serial dependence in working memory

工作记忆是在一段时间内保留和处理信息的能力，是高级认知功能的核心组成部分，包括语言、解决问题、推理和抽象思维。工作记忆容量在学业成绩的个体差异中占很大比例，并且在精神分裂症、中风、创伤性脑损伤和多动症等临床疾病中受到损害。了解工作记忆的神经基础在过去几年一直是科学研究的前沿问题。这个项目依赖于工作记忆的“不完美”，即序列依赖：前一次记忆的内容经常影响下一次记忆的内容，尽管这已经不再有用了。序列依赖性可以提供对细胞机制和神经递质系统的深入了解。患有遗传性疾病如精神分裂症、自闭症和脑炎的患者表现出不同的系列依赖模式。本项目采用实验和理论相结合的方法来理解不同的神经递质系统和大脑区域在序列依赖中的作用，这将揭示介导工作记忆的回路的基本特性。除了实验的直接目标之外，理解工作记忆的神经基础和开发捕捉其特性的机制模型预计将对许多科学领域产生更广泛的影响，包括神经科学、心理学、认知科学、计算机科学和机器学习。结合实验建模的方法也直接相关的理解和治疗这些临床条件。该方法为神经精神疾病的模型指导研究开辟了新的途径，并增强了计算精神病学的影响范围。工作记忆与前额皮质有关，前额皮质是认知处理的中心区域，具有独特的解剖和细胞组织。NMDA受体大量存在于前额叶皮层，被认为对维持工作记忆中的信息起着至关重要的作用，因为它们能够使神经元长时间处于兴奋状态，并诱导突触连接的可塑性。然而，将它们的细胞作用与工作记忆行为联系起来的直接证据很少。本项目将探讨NMDA受体支持工作记忆功能的电路机制。我们将依靠一种新的方法，通过研究历史偏差的机制，作为工作记忆中持久的nmdar依赖机制的表现。系列依赖性在精神分裂症和抗nmdar脑炎患者中受到系统影响，提示潜在的nmdar依赖机制。实验将训练非人类灵长类动物执行空间工作记忆任务；获取背外侧前额叶和后顶叶皮层单个神经元的神经生理记录和局部场电位；系统使用NMDAR拮抗剂；并使用光遗传皮层刺激来测试一系列偏差计算模型的行为和生理预测。神经数据分析和计算建模将在额顶叶网络模型中整合实验结果。这将阐明前额叶NMDA受体在形成历史依赖偏见中的作用，以及局部回路（内在）连接和远程连接的重要性。明确亚单位特异性NMDAR机制，以及额顶叶网络的作用，将为后续实验提供具有生物物理细节和增强预测能力的新计算框架。该项目有望促进对认知过程和调节认知过程的神经网络的理解。西班牙卡洛斯三世国家卫生研究所（ISCIII）正在资助一个伙伴项目。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Working memory, the ability to retain and manipulate information over a period of seconds, represents a core component of higher cognitive functions, including language, problem solving, reasoning, and abstract thought. Working memory capacity accounts for a great proportion of individual variability in academic performance, and it is impaired in clinical conditions including schizophrenia, stroke, traumatic brain injury, and ADHD. Understanding the neural basis of working memory has been a question in the forefront of scientific research over the past few years. This project relies on an “imperfection” of working memory, serial dependence: the contents of memory in a previous trial often affect what is being recalled in a following one, even though this is no longer useful. Serial dependences can provide insight into cellular mechanisms and neurotransmitter systems. Patients with genetic conditions such as schizophrenia, autism, and encephalitis exhibit different patterns of serial dependence. This project forms a collaborative experimental and theoretical approach to understand the role of different neurotransmitter systems and brain areas in serial dependence, which will reveal fundamental properties of the circuits that mediate working memory. Beyond the immediate goals of the experiments, understanding the neural basis of working memory and developing mechanistic models that capture its properties is expected to have broader impacts on a number of scientific fields, including neuroscience, psychology, cognitive science, computer science, and machine learning. The combined experimental-modeling approach has also direct relevance to understanding and treating these clinical conditions. The approach opens new avenues of model-guided research in neuropsychiatric conditions and enhances the reach of computational psychiatry.Working memory has been linked to the prefrontal cortex, an area central to cognitive processing, with unique anatomical and cellular organization. NMDA receptors, which are abundant in the prefrontal cortex, are suspected to play a critical role for the maintenance of information in working memory, by virtue of their ability to maintain neurons at an excited state for an extended period of time, and to induce plasticity of synaptic connections. Direct evidence linking their cellular role to working memory behavior has been scant, however. This project will address the circuit mechanisms by which NMDA receptors support working memory function. We will rely on a novel approach, by investigating the mechanisms of history biases, as a manifestation of long-lasting NMDAR-dependent mechanisms in working memory. Serial dependencies are systematically affected in patients with schizophrenia and anti-NMDAR encephalitis, suggesting an underlying NMDAR-dependent mechanism. Experiments will train non-human primates to perform spatial working memory tasks; obtain single neuron neurophysiological recordings and local field potentials from dorsolateral prefrontal and posterior parietal cortex; administer NMDAR antagonists systemically; and use optogenetic cortical stimulation to test behavioral and physiological predictions of a computational model of serial biases. Analysis of neural data and computational modeling will integrate the results of the experiments in a fronto-parietal network model. This will shed light on the role of prefrontal NMDA receptors in shaping history-dependent biases, and the importance of local-circuit (intrinsic) connections and long-range connections. Specifying subunit-specific NMDAR mechanisms, and the role of the fronto-parietal network, will inform a new computational framework with biophysical detail and enhanced predictive power for subsequent experimentation. The project is expected to advance understanding of cognitive processes and the neural networks mediating them. A companion project is being funded by the National Institute of Health Carlos III, Spain (ISCIII).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.