Hippocampal-cortical networks underlying memory retrieval of linguistic knowledge

海马皮质网络是语言知识记忆检索的基础

• 批准号: 9906282
• 负责人: Jonathan Kleen
• 金额: $ 20.02万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9906282
• 关键词: Address; Alzheimer' s Disease; Animal Experimentation; Animals; Auditory; Award; Behavior; Behavioral; Brain; Brain region; Clinical; Cognition; Communication; Comprehension; Computational Linguistics; Custom; Data; Data Analyses; Dementia; Development; Disease; Electric Stimulation; Electrocorticogram; Electrodes; Epilepsy; Etiology; Event; Foundations; Functional disorder; Future; Goals; Grant; Hippocampus (Brain); Human; Impaired cognition; Impairment; Individual; Inferior frontal gyrus; Intractable Epilepsy; Investigation; Knowledge; Laboratories; Language; Light; Linguistics; Literature; Machine Learning; Memory; Mentorship; Methods; Monitor; Names; Neurologic; Neurons; Neurosciences; Paper; Participant; Patients; Pattern; Performance; Physiological; Population; Resources; Retrieval; Role; Sampling; Semantic memory; Semantics; Site; Stereotyping; Stimulus; Structure; Structure of middle temporal gyrus; Temporal Lobe; Temporal Lobe Epilepsy; Testing; Therapeutic; Therapeutic Intervention; Time; Training; Work; awake; base; behavior measurement; brain circuitry; career; cognitive function; density; effective therapy; improved; innovation; insight; language processing; memory retrieval; multidisciplinary; natural language; nervous system disorder; neural circuit; neuroethics; neurophysiology; neurotransmission; relating to nervous system; semantic processing; signal processing; syntax; theories; tool

ABSTRACT Language and memory overlap heavily in brain circuitry and in our day-to-day lives. Both are also frequently disrupted in neurological conditions such as temporal lobe epilepsy and Alzheimer’s disease. We have a limited understanding of the mechanisms by which cortical language centers integrate with memory circuits; for example, to support the retrieval of linguistic knowledge. This limits our insight into disease pathophysiology and slows the development of more effective therapies for cognitive impairments. This K23 will support an investigation of how language and memory integrate in the human brain, by harnessing unique innovations and resources. First, we will use special high-density grid and depth electrodes to record from many hundreds of local neuronal populations distributed throughout memory and language centers, among patients undergoing intracranial monitoring for refractory epilepsy. Second, to target distinct moments of linguistic-mnemonic integration, we have customized an auditory naming behavioral task that combines controlled yet natural language stimuli with memory retrieval of linguistic knowledge. Third, I will apply state-of-the-art analyses with pattern classifiers and computational linguistics, an approach that could improve the framework of how we understand neural representations of deep language processing. I will first evaluate whether the activity patterns in cortical language centers and the hippocampus reveal neural signatures of dynamic integration during knowledge retrieval, and whether their activity patterns reflect mutual information sufficient to predict the linguistic content of task trials (Aim 1). I will then use electrical stimulation to selectively disrupt neural processing in these regions, to determine if and how they contribute to distinct stages of language and memory integration (Aim 2). This approach will also allow us to probe whether the hippocampus is required for semantic memory, a long-debated question arising from classic literature. My mentorship team has a constellation of expertise aligning with my training plan and the goals of this investigation, including cortical language neurophysiology, hippocampal memory neurophysiology, and investigative neurostimulation. This proposal builds upon my prior expertise in translational intracranial recordings and neural signal processing, and my long-term career goal of understanding and improving treatments for cognitive impairments in epilepsy. I will receive training, coursework, and direct mentorship in skillsets that I will continue to use throughout my scientific career, including language and memory neurophysiology, human neurostimulation, neuroethics, machine learning, computational linguistics, scientific communication, and independent laboratory management. The knowledge and training acquired during this award period will allow me to establish an independent laboratory and emerge as a leader in human intracranial neurophysiology, applying my expertise to unmet needs in epilepsy.

摘要 语言和记忆在大脑回路和我们的日常生活中有很大的重叠。两者也经常 在神经系统疾病如颞叶癫痫和阿尔茨海默病中被破坏。我们有一个 对皮层语言中心与记忆回路整合的机制的理解有限; 例如，支持语言知识的检索。这限制了我们对疾病病理生理学的了解 并减缓了更有效的认知障碍疗法的发展。这款K23将支持 研究语言和记忆如何整合在人类大脑中，通过利用独特的创新， 资源首先，我们将使用特殊的高密度网格和深度电极记录数百个 局部神经元群体分布在整个记忆和语言中心，在患者接受 难治性癫痫的颅内监测第二，针对语言记忆的不同时刻， 整合，我们定制了一项结合受控与自然的听觉命名行为任务 语言刺激与语言知识的记忆提取。第三，我将应用最先进的分析， 模式分类器和计算语言学，一种可以改善我们如何 理解深层语言处理的神经表征。首先，我将评估该活动是否 皮层语言中心和海马的模式揭示了动态整合的神经特征 在知识检索过程中，以及它们的活动模式是否反映了足以预测 任务试验的语言内容（目标1）。然后我会用电刺激有选择地干扰 在这些区域进行处理，以确定它们是否以及如何对语言和记忆的不同阶段做出贡献 整合（目标2）。这种方法也将使我们能够探测海马体是否是语义所必需的。 记忆，一个长期争论的问题，从经典文学。我的导师团队有一群 专业知识与我的培训计划和本次调查的目标相一致，包括皮层语言 神经生理学、海马记忆神经生理学和研究性神经刺激。这项建议 建立在我之前在翻译颅内记录和神经信号处理方面的专业知识基础上， 了解和改善癫痫认知障碍治疗的长期职业目标。我会 接受培训，课程，和技能的直接指导，我将继续在我的整个使用 科学生涯，包括语言和记忆神经生理学，人类神经刺激，神经伦理学， 机器学习、计算语言学、科学传播和独立实验室 管理在此期间获得的知识和培训将使我能够建立一个 我是一个独立的实验室，运用我的专业知识， 癫痫患者未满足的需求。