Event networks and the neural representations that support real-world memory

支持现实世界记忆的事件网络和神经表征

• 批准号: 10717508
• 负责人: JANICE CHEN
• 金额: $ 54.36万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10717508
• 关键词: Attention; Behavior; Belief; Brain; Child; Collection; Complex; Corpus striatum structure; Crowding; Data; Decision Making; Development; Dimensions; Disease; Environment; Event; Fever; Functional Magnetic Resonance Imaging; Goals; Graph; Higher Order Chromatin Structure; Hippocampus; Home; Hour; Human; Internet; Judgment; Laboratory Finding; Learning; Life; Link; Location; Machine Learning; Measures; Memory; Mental Health; Modeling; Organism; Participant; Pattern; Persons; Prevalence; Property; Research; Research Personnel; Role; Schizophrenia; Semantics; Services; Shapes; Stimulus; Stream; Structure; System; Techniques; Telephone; Testing; Time; Visit; Volition; Work; behavior influence; brain behavior; experience; experimental study; improved; innovation; memory encoding; memory process; memory retrieval; movie; musician; neural; neural correlate; neuromechanism; novel; real world application; reconstruction; tool

Project Summary Memory systems evolved to inform the continual learning and decision making of organisms as they explore and engage with an enormously complicated world. Humans in particular have a remarkable ability to recount complex sequences of events: we can easily reconstruct a narrative about the past hour or day purely from memory. In such real-world remembering, semantic and causal associations become exceedingly important, defining a web of relational connections across time to guide recall. For example, your day might contain two "hub" events: a dinner party that requires visiting several shops to pick up supplies, and a morning phone call saying that your child has a fever and needs to go home; each spawns a multitude of events that make up your day. Rich associations among these moments form an “event network” whose local and global properties shape recall; your decisions guide how each event will unfold. While studies show that relations between simple items are important for memory organization and its accompanying neural computations, no existing models consider the higher-order structure of networks composed from inter-related naturalistic events. Even among naturalistic studies, most use passively-viewed movies or stories; participants have no choices to make or goals to pursue. This lack of attention to the higher-order network properties and volitional aspects of real- world experiences has hindered efforts to identify the cortical dynamics that underlie ecologically meaningful memory processes. We seek to understand how memory encoding and retrieval of realistic events is implemented, in terms of cortical representations and interactions between brain systems. Doing so requires paradigms with two critical attributes. First, the stimuli must be sufficiently complex. Memory researchers have long focused on reductive scenarios with isolated stimuli that intentionally destroy semantic and causal connections. In contrast, our experiments use realistic events that are richly associated with each other and will naturally generate a diversity of event network structures. Second, participants must take an active role in creating their memories. Organisms in the real world can volitionally interact with their input stream: at a crowded party, you can choose to explore the kitchen or the living room, talk to the biologist or the musician, leave early or stay until dawn. We will test how participants' volitional behaviors, as they interact with and actively seek information about their environment, shape event networks and neural representations of events. Altogether, these experiments will provide novel frameworks and tools to examine how emergent higher-order structure in natural experiences governs the neural mechanisms underlying encoding and recall. By advancing the level of ecological validity and stimulus complexity in human memory research, we expect to help uncover brain-behavior relationships not apparent in simpler paradigms, and increase the translatability of laboratory findings to real-world applications.

项目摘要 记忆系统的进化为生物体在探索过程中的持续学习和决策提供了信息 并与一个极其复杂的世界打交道。特别是人类具有非凡的重述能力。 复杂的事件序列：我们可以很容易地重建关于过去一小时或一天的叙事 记忆。在这样的现实世界记忆中，语义和因果联系变得极其重要， 定义一个跨越时间的关系联系网络，以指导回忆。例如，您的一天可能包含两个 “中心”活动：需要去几家商店取用品的晚宴，以及早上的电话。 说你的孩子发烧了，需要回家；每一次都会产生一系列事件，组成你的 天。这些时刻之间的丰富关联形成了一个具有局部和全球属性的事件网络 形状回忆；你的决定指导着每个事件将如何展开。虽然研究表明， 简单的项目对于记忆组织及其伴随的神经计算很重要，不存在 模型考虑了由相互关联的自然主义事件组成的网络的更高阶结构。连 在自然主义研究中，大多数人使用被动观看的电影或故事；参与者没有选择 或要追求的目标。这种对实数的高阶网络性质和意志方面的缺乏关注 世界经验阻碍了确定具有生态意义的大脑皮层动力学的努力 记忆过程。 我们试图了解现实事件的记忆编码和检索是如何实现的，就 大脑皮层的表征和大脑系统之间的相互作用。要做到这一点，需要有两个关键的范例 属性。首先，刺激必须足够复杂。记忆研究人员长期以来一直专注于还原 孤立刺激故意破坏语义和因果联系的情景。相比之下，我们的 实验使用彼此紧密关联的现实事件，自然会生成 活动网络结构的多样性。其次，参与者必须在创造他们的记忆方面发挥积极的作用。 现实世界中的有机体可以随意地与它们的输入流互动：在拥挤的派对上，你可以选择 要探索厨房或起居室，与生物学家或音乐家交谈，早点离开或呆到天亮。我们 将测试参与者的意志行为如何，因为他们与他们的互动并积极寻找关于他们的信息 环境、塑造事件网络和事件的神经表征。总而言之，这些实验将 提供新的框架和工具来研究自然体验中的新出现的高阶结构 支配着编码和回忆背后的神经机制。通过提升生态有效性水平 和人类记忆研究中的刺激复杂性，我们希望有助于揭示大脑与行为的关系 在更简单的范例中并不明显，并增加了实验室结果在现实世界中的可译性 申请。