Neocortical-Hippocampal Circuits Underlying Pattern Separation in Humans

项目摘要 记忆对我们的生活至关重要。有了它们，我们创造了一段独特的历史，与我们周围的世界联系起来， 做出明智的决定随着年龄的增长，记忆力的变化越来越普遍， 功能可能是阿尔茨海默病的最早迹象之一，这是一项重大的公共卫生挑战， 超过560万美国人。过去的研究表明，区分相似记忆的能力 经验（即模式分离）是老年人记忆障碍的早期迹象，有患阿尔茨海默氏症的风险 疾病这种记忆的中断被认为是随后认知能力下降的早期预兆， 在疾病的最早阶段是一个合适的治疗目标。然而，这样的瞄准是不可能的 而不完全理解支持人类模式分离的电路级动态。而 计算理论长期以来一直认为海马体和大脑皮层之间的相互作用是必要的。 新皮层，该领域一直在努力克服识别人类中这种网络级动态的挑战， 使用fMRI的有限时间分辨率和使用EEG的有限空间分辨率。我建议填补这一空白， 知识使用一个罕见的和独特的机会，记录从新皮层和海马体与 植入颅内电极用于临床监测的人体的上级空间和时间分辨率 同时他们进行模式分离记忆任务。我会收集至少一个人的神经记录数据 15名患者接受临床监测，在海马中手术植入深度电极， UCI综合癫痫科的新皮质。我提出了三个具体目标：（1）检验假设 海马体和新皮层中θ波能量的增加将预测成功的辨别能力， （2）验证了在编码过程中，大脑皮层-新皮层的相互作用 将有方向性的偏见，使海马体领导皮层，反映新学到的整合， 信息进入新皮层的网站;和（3）测试的假设，在检索，大脑皮层-新皮层 相互作用将是有方向性的，这样皮质会引导海马，反映了大脑的访问。 新皮层的记忆内容建议的研究是可行的， 加州大学欧文分校的培训环境以及临床基础设施和癫痫监测部门的可用性， 研究专用记录设备。利用这些资源，我已经收集了初步数据， 支持三种假设。在Michael Yassa博士和Jack Lin博士的共同指导下，我将获得 临床和认知神经科学的高级培训。在Lee Swindlehurst博士的指导下， 电气工程，我采用技术来分析高维数据和方向性措施 网络分析。在这群导师的帮助下，我的目标是填补知识上的一个关键空白， 人类大脑中的记忆机制，其总体目标是将这些知识应用于逆转 老年性记忆丧失和阿尔茨海默病。

Project Summary Memories are crucial to our lives. With them, we generate a unique history, connect with the world around us, and make informed decisions. Memory loss occurs as we get older, and more pervasive changes in memory function can be among the earliest signs of Alzheimer’s disease, a major public health challenge affecting more than 5.6 million Americans. Past studies have shown that the ability to discriminate among similar mnemonic experiences (i.e. pattern separation) is an early sign of memory impairment in older adults at risk for Alzheimer’s disease. This disruption in memory is thought to be an early harbinger of subsequent cognitive decline and may be a suitable therapeutic target in the earliest stages of the disease. However, such targeting is impossible without a complete understanding of the circuit-level dynamics that support pattern separation in humans. While computational theories have long suggested a necessary role for interactions between the hippocampus and the neocortex, the field has struggled with challenges in identifying such network level dynamics in humans due to limited temporal resolution using fMRI and limited spatial resolution using EEG. I propose to fill this gap in knowledge using a rare and unique opportunity to record from both the neocortex and the hippocampus with superior spatial and temporal resolution in humans implanted with intracranial electrodes for clinical monitoring while they engage in a pattern separation memory task. I will collect neural recording data from a minimum of 15 patients undergoing clinical monitoring with surgically implanted depth electrodes in the hippocampus and the neocortex at the UCI Comprehensive Epilepsy Unit. I propose three specific aims: (1) Test the hypothesis that increased theta power in the hippocampus and neocortex will predict successful discrimination performance on pattern separation task; (2) Test the hypothesis that during encoding, hippocampal-neocortical interactions will be directionally biased such that the hippocampus leads the cortex, reflecting the integration of newly learned information into neocortical sites; and (3) Test the hypothesis that during retrieval, hippocampal-neocortical interactions will be directionally biased such that the cortex leads the hippocampus, reflecting the access of memory content from neocortical sites. The proposed studies are feasible with the excellent research and training environment at UC Irvine and the availability of clinical infrastructure and an epilepsy monitoring unit with research-dedicated recording equipment. Using these resources, I have already collected preliminary data in support of all three hypotheses. With the joint mentorship of Dr. Michael Yassa and Dr. Jack Lin, I will receive advanced training in clinical and cognitive neuroscience. With additional mentorship of Dr. Lee Swindlehurst in electrical engineering, I am employing techniques to analyze high dimensional data and directionality measures for network analysis. With the help of this constellation of mentors, I aim to fill a critical gap in knowledge about memory mechanisms in the human brain, with the overarching goal of applying this knowledge to reversing memory loss in aging and Alzheimer’s disease.