Multivariate Decoding of the Retrieval Brain State Across Cognition

跨认知检索大脑状态的多元解码

• 批准号: 10710764
• 负责人: Nicole Marie Long
• 金额: $ 39.75万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710764
• 关键词: Accounting; Attention; Behavior; Brain; Clinical; Cognition; Cognitive; Cognitive deficits; Cues; Data; Disease; Electroencephalography; Episodic memory; Event; Failure; Familiarity; Foundations; Future; Goals; Impaired cognition; Individual; Instruction; Knowledge; Learning; Link; Longevity; Maintenance; Measures; Memory; Memory impairment; Modeling; Outcome; Patients; Pattern; Performance; Process; Property; Research; Retrieval; Scalp structure; Semantics; Short-Term Memory; Stimulus; Stroke; Testing; Time; Work; attentional modulation; behavior influence; behavioral outcome; cognitive function; directed attention; flexibility; healthy aging; indexing; memory encoding; memory process; memory retrieval; millisecond; neural; novel strategies; operation; programs; sensory stimulus; stimulus processing; theories

Brain states – stable patterns of whole-brain activity and connectivity – dictate neural processing and behav- ioral outcomes, yet understanding of specific brain states remains limited. In particular, there has been limited consideration of how the retrieval state may drive the processes and representations that support memory and cognition. The long-term goal of this research program is to link cognitive brain states and behavior. The overall objective of the current application is to define the properties of the retrieval state. The central hypothesis of this proposal is that the retrieval state reflects a control-independent internal attention brain state. The specific aims of this proposal are to establish retrieval state temporal dynamics, link retrieval and internally directed attention, and identify the factors that induce retrieval. This proposal will use multivariate decoding of scalp EEG data to index trial-level retrieval over time and across tasks. The findings of the current proposal are expected to provide a significant conceptual advance that will be broadly relevant to understanding memory and cognition.

大脑状态--全脑活动和连接的稳定模式--决定了神经处理和神经网络， 虽然这是一个口头的结果，但对特定大脑状态的理解仍然有限。特别是， 考虑检索状态如何驱动支持记忆的过程和表示， 认知.这项研究计划的长期目标是将认知大脑状态和行为联系起来。整体 本申请的目的是定义检索状态的属性。这个问题的核心假设是 这一假设的前提是，提取状态反映的是一种独立于控制的内部注意脑状态。具体目标 该建议的主要内容是建立检索状态时间动态，链接检索和内部定向注意， 并找出诱发检索的因素。该建议将使用头皮EEG数据的多变量解码， 随着时间的推移和跨任务的索引试验级检索。目前提案的结果预计将提供 这是一个重大的概念进步，将与理解记忆和认知广泛相关。

项目成果

Response-locked theta dissociations reveal potential feedback signal following successful retrieval.

响应锁定 theta 解离揭示了成功检索后的潜在反馈信号。

• DOI: 10.1101/2024.01.11.575166
• 发表时间: 2024
• 期刊: bioRxiv : the preprint server for biology
• 作者: Smith,DevynE;Wheelock,JustinR;Long,NicoleM
• 通讯作者: Long,NicoleM