Real-time control of memory encoding - Revision 1

内存编码的实时控制 - 修订版 1

• 批准号: 10373859
• 负责人: Megan Teresa deBettencourt
• 金额: $ 3.03万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10373859
• 关键词: Acquaintances; Automobile Driving; Behavior; Brain; Clinical; Contralateral; Coupling; Cues; Data; Data Collection; Detection; Electroencephalography; Event; Event-Related Potentials; Failure; Feedback; Frequencies; Functional Magnetic Resonance Imaging; Goals; Intervention; Laboratories; Link; Location; Maintenance; Measures; Memory; Mental disorders; Modeling; Monitor; Names; Occupational; Participant; Performance; Reaction Time; Reporting; Research; Rewards; Role; Shapes; Short-Term Memory; Signal Transduction; Stimulus; Sum; System; Testing; Time; Visual; Volition; base; brain computer interface; experimental study; improved; lens; long term memory; memory encoding; memory retention; nervous system disorder; neurofeedback; neurotransmission; relating to nervous system; stimulus interval; success; temporal measurement; time use; visual information

Project Summary Fluctuations of neural activity impact memory. Subsequent memory analyses have demonstrated that particular neural states predict better working memory and long-term memory behavior. These analyses are typically conducted after data collection, but monitoring neural fluctuations in real time would enable more direct and timely interventions. We will use real-time electroencephalography (EEG) to track moment-to- moment fluctuations of neural activity in order to more directly link brain signals with behavior, and to enhance memory performance. In this proposal, we focus on two key moments for memories: pre-stimulus (Aim 1) and active maintenance during a retention interval (Aim 2). In Aim 1, we will test the hypothesis that pre-stimulus neural signals (oscillatory alpha and theta) predict memory encoding success. In Experiment 1, we will vary the point of time when the stimuli appear based on real-time calculations of alpha and theta power. We will use neural activity as the independent variable to “trigger” stimulus presentation when the brain is in either advantageous states (low alpha, high theta) or disadvantageous states (high alpha, low theta). We predict that better brain states will predict better working memory and long-term memory precision in a sensitive continuous report task. In Experiment 2, we will provide neurofeedback to reward advantageous pre-stimulus brain states (low alpha, high theta). We predict that up-regulating these advantageous states will lead to enhanced memory performance (more precise memories). In Aim 2, we will test the hypothesis that sustained activity tracks active maintenance of information. Sustained activity is a key signature of working memory, but recent evidence has questioned its role through the demonstration of activity-silent working memory. In Experiment 3, we will use real-time measures of sustained activity (contralateral delay activity, multivariate alpha topography) to adjust the duration of a retention interval and the identity of working memory probes. We predict that performance will be better (quicker reaction times, more precise memories) when memory probes are triggered based on higher sustained activity. In Experiment 4, we will provide neurofeedback during the retention interval to reward greater sustained activity. We predict that up-regulating these advantageous states will lead to greater memory precision. Across these experiments, we will explore memory encoding via the lens of real-time EEG to trigger information (Experiments 1 & 3) and provide feedback (Experiments 2 & 4). The proposed research will characterize the fate of mnemonic representations by tracking and driving neural activity both pre-encoding (Aim 1) and post-encoding (Aim 2), in order to understand how neural fluctuations give rise to what we remember.

项目总结

项目成果

Decoding the content of working memory in school-aged children.

解码学龄儿童工作记忆的内容。

• DOI: 10.1101/2023.02.10.527990
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Turoman,Nora;Fiave,ProsperAgbesi;Zahnd,Clélia;deBettencourt,MeganT;Vergauwe,Evie
• 通讯作者: Vergauwe,Evie

Sustained Attention and Spatial Attention Distinctly Influence Long-term Memory Encoding.

• DOI: 10.1162/jocn_a_01748
• 发表时间: 2021-09-01
• 期刊: JOURNAL OF COGNITIVE NEUROSCIENCE
• 影响因子: 3.2
• 作者: DeBettencourt, Megan T.;Williams, Stephanie D.;Vogel, Edward K.;Awh, Edward
• 通讯作者: Awh, Edward

Attention fluctuations impact ongoing maintenance of information in working memory.

• DOI: 10.3758/s13423-020-01790-z
• 发表时间: 2020-12
• 期刊: Psychonomic bulletin & review
• 影响因子: 3.5
• 作者: Hakim N;deBettencourt MT;Awh E;Vogel EK
• 通讯作者: Vogel EK

Pupillometry signatures of sustained attention and working memory.

持续关注和工作记忆的瞳孔测定签名。

• DOI: 10.3758/s13414-022-02557-5
• 发表时间: 2022-11
• 期刊: Attention, perception & psychophysics
• 作者: Keene PA;deBettencourt MT;Awh E;Vogel EK
• 通讯作者: Vogel EK

Predicting visual memory across images and within individuals

预测跨图像和个体内部的视觉记忆

• DOI: 10.1016/j.cognition.2022.105201
• 发表时间: 2022
• 期刊: Cognition
• 影响因子: 3.4
• 作者: Wakeland-Hart, Cheyenne D.;Cao, Steven A.;deBettencourt, Megan T.;Bainbridge, Wilma A.;Rosenberg, Monica D.
• 通讯作者: Rosenberg, Monica D.