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，记住，评估和决定的能力对于我们是谁以及我们如何构建生活至关重要。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 人们认为新的体验可以推动海马的独特大脑活动模式，这是为日常生活中存储记忆至关重要的大脑区域。人们认为，随后的这种经验重新激活这种经验是可以推动巩固过程，该过程植入了海马和皮质回路中的模式。同样，随后的检索被认为依赖于与原始体验中存在的模式相似的恢复原状。当前的证据表明，在锋利波纹波事件（SWR）中，海马神经元序列的重播是记忆巩固和记忆检索的候选机制。为了确定记忆重播是否可以为相关的内存表示形式进行整合和检索，我们将执行指示操作，这些操纵不仅仅是中断所有SWR来通过其内容进行目标重播事件。我们的工作将基于我们在实时反馈和无集群解码方面的最新发展方面的专业知识，这使我们能够开发出海马重播事件的实时，基于内容的中断所需的所有技术元素。这将使我们能够评估特定内存重播事件在内存过程中的作用。我们的具体目的是：1）开发一个最佳的自适应统计框架，用于实时解码和内存重播中断，2）测试以下假设：海马重放事件为重播记忆提供了记忆巩固，以及3）测试海马重播事件的假设，该假设支持了对未来探索的内部探索和内部探索的特定探索。我们的实时方法有可能在重播特定活动模式与合并记忆的能力和利用过去的经验指导未来决策之间建立新的因果关系。