Real-time analysis of memories and decisions

实时分析记忆和决策

• 批准号: 8787330
• 负责人: Uri Tzvi Eden
• 金额: $ 67.43万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8787330
• 关键词: Accounting; Algorithms; Alzheimer' s Disease; Animals; Behavioral; Brain; Brain region; Cells; Cognitive; Communities; Complex; Data; Decision Making; Development; Disease; Elements; Environment; Epilepsy; Event; Feedback; Future; Goals; Health; Hippocampus (Brain); Individual; Interruption; Laboratories; Learning; Left; Life; Link; Memory; Mental Depression; Neurons; Neurosciences; Pattern; Prefrontal Cortex; Process; Retrieval; Role; Schizophrenia; Site; Structure; Technology; Testing; Time; Work; awake; base; cognitive function; experience; information processing; insight; memory process; memory retrieval; neural circuit; new technology; novel strategies; open source; relating to nervous system; research study

DESCRIPTION (provided by applicant): The abilities to learn, remember, evaluate and decide are central to who we are and how we structure our lives. These abilities, and indeed the vast majority of cognitive functions, are thought to depend on specific patterns of brain activity. Each new experience is thought to drive a unique pattern of brain activity in the hippocampus, a brain region critical for storing memories for the events of daily life. Subsequent reactivation of this experience after learning is thought to drive a consolidation process that engrains the patterns in hippocampal and cortical circuits. Similarly, subsequent retrieval is thought to rely on the reinstatement of patterns similar to those present during the original experience. Current evidence points to the replay of sequences of hippocampal neurons during sharp-wave ripple events (SWRs) as a candidate mechanism for both memory consolidation and memory retrieval. To determine whether memory replay drives consolidation and retrieval for the associated memory representations, we will carry out directed manipulations that go beyond interrupting all SWRs to target replay events by their content. Our work will build on our expertise in real-time feedback and recent developments in cluster-less decoding that have allowed us to develop all of the technological elements required for real-time, content-based interruption of hippocampal replay events. This will allow us to assess the role of specific memory replay events in memory processes. Our Specific Aims are: 1) to develop an optimal adaptive statistical framework for real-time decoding and interruption of memory replay, 2) to test the hypothesis that hippocampal replay events drive memory consolidation for the replayed memories, and 3) to test the hypothesis that hippocampal replay events support rule learning and the internal exploration of specific future possibilities. Our real-time approach has the potential to create new causal links between the replay of specific patterns of activity and the ability to consolidation memories and to use past experience to guide future decisions.

描述(由申请人提供)：学习、记忆、评估和决定的能力对我们是谁以及我们如何构建我们的生活至关重要。这些能力，甚至绝大多数认知功能，都被认为取决于大脑活动的特定模式。每个人 新的体验被认为推动了海马体中一种独特的大脑活动模式，海马体是存储日常生活事件记忆的关键大脑区域。学习后这种经验的随后重新激活被认为驱动了一个巩固过程，该过程在海马区和大脑皮层回路中植入了模式。同样，随后的提取被认为依赖于与原始体验中出现的模式相似的模式的恢复。目前的证据表明，在尖波涟漪事件(SWRs)期间，海马神经元序列的重播是记忆巩固和记忆提取的候选机制。为了确定内存重放是否会驱动相关内存表示的整合和检索，我们将执行定向操作，这些操作不仅仅是中断所有SWR，而是通过内容来确定重放事件的目标。我们的工作将建立在我们在实时反馈方面的专业知识和无簇解码方面的最新进展的基础上，这些进展使我们能够开发基于内容的实时中断海马体重放事件所需的所有技术元素。这将使我们能够评估特定的记忆重放事件在记忆过程中的作用。我们的具体目标是：1)为记忆重放的实时解码和中断建立一个最优的自适应统计框架；2)检验海马重放事件驱动重放记忆巩固的假设；3)检验海马重放事件支持规则学习和对未来特定可能性的内部探索的假设。我们的实时方法有可能在特定活动模式的重播与巩固记忆和使用过去经验指导未来决策的能力之间建立新的因果联系。