The Contribution of Dentate-Neural Networks to Memory Encoding

齿状神经网络对记忆编码的贡献

• 批准号: 8532687
• 负责人: Laura Ewell
• 金额: $ 5.22万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8532687
• 关键词: Animals; Binding; Biological Neural Networks; Cells; Cues; Disease; Electrophysiology (science); Environment; Episodic memory; Event; Hilar; Hippocampus (Brain); Human; Impairment; Individual; Interneurons; Knowledge; Lead; Memory; Neurons; Pathology; Pattern; Population; Prevention; Process; Psyche structure; Role; Sensory; Short-Term Memory; Symptoms; System; Technology; Testing; Time; awake; cell type; density; dentate gyrus; experience; extracellular; in vivo; memory encoding; neuropsychiatry; optogenetics; research study; theories; therapeutic target; tool

DESCRIPTION (provided by applicant): Several neuropsychiatric disorders show extensive pathology in the input layer to the hippocampus, the dentate gyrus. One set of symptoms common to these diseases is impairments in memory that are consistent with proposed dentate gyrus function, such as deficits in episodic memory and working memory. Little is known, however, about the neural network mechanisms that underlie dentate gyrus memory encoding. In Aim 1 we will elucidate the dentate gyrus network mechanisms that support memory encoding by recording from dentate neuronal populations in awake behaving animals while they perform a dentate gyrus dependent working-memory task. In Aim 2 we will look at the contribution of individual classes of dentate neurons to the neural network computations essential for memory encoding, as several diseases differentially target individual classes of neurons. Completion of these aims will provide the framework to compare healthy network processes that underlie memory formation to disease processes, and may lead to therapeutic targets.

描述(申请人提供)：几种神经精神障碍显示海马齿状回的输入层有广泛的病理改变。这些疾病的一组常见症状是记忆障碍，这与拟议的齿状回功能一致，例如情景记忆和工作记忆缺陷。然而，对齿状回记忆编码背后的神经网络机制知之甚少。在目标1中，我们将通过记录清醒行为动物执行齿状回依赖工作记忆任务时的齿状回神经元群来阐明支持记忆编码的齿状回网络机制。在目标2中，我们将研究个别类别的齿状神经元对记忆编码所必需的神经网络计算的贡献，因为几种疾病不同地针对个别类别的神经元。这些目标的完成将提供一个框架，将构成记忆形成的健康网络过程与疾病过程进行比较，并可能导致治疗目标。