已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Using EEG microstates to examine post-encoding quiet rest and subsequent word-pair memory

地方政府 心理学 记忆巩固 脑电图 编码(内存) 认知心理学 神经科学 海马体
作者
Craig Poskanzer,Dan Denis,Ashley Herrick,Robert Stickgold
出处
期刊:Neurobiology of Learning and Memory [Elsevier BV]
卷期号:181: 107424-107424 被引量:17
标识
DOI:10.1016/j.nlm.2021.107424
摘要

Evidence suggests that the brain preferentially consolidates memories during “offline” periods, in which an individual is not performing a task and their attention is otherwise undirected, including spans of quiet, resting wakefulness. Moreover, research has demonstrated that factors such as the initial encoding strength of information influence which memories receive the greatest benefit. Recent studies have begun to investigate these periods of post-learning quiet rest using EEG microstate analysis to observe the electrical dynamics of the brain during these stretches of memory consolidation, specifically finding an increase in the amount of the canonical microstate D during a post-encoding rest period. Here, we implement an exploratory analysis to probe the activity of EEG microstates during a post-encoding session of quiet rest in order to scrutinize the impact of learning on microstate dynamics and to further understand the role these microstates play in the consolidation of memories. We examined 54 subjects (41 female) as they completed a word-pair memory task designed to use repetition to vary the initial encoding strength of the word-pair memories. In this study, we were able to replicate previous research in which there was a significant increase (p < .05) in the amount of microstate D (often associated with the dorsal attention network) during post-encoding rest. This change was accompanied by a significant decrease (p < .05) in the amount of microstate C (often associated with the default mode network). We also found preliminary evidence indicating a positive relationship between the amount of microstate D and improved memory for weakly encoded memories, which merits further exploration.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刘奕发布了新的文献求助10
1秒前
zhabgyucheng发布了新的文献求助30
2秒前
3秒前
4秒前
6秒前
7秒前
橙浮之年完成签到,获得积分10
10秒前
昏睡的冰枫完成签到 ,获得积分10
10秒前
11秒前
英俊的铭应助科研小白采纳,获得10
12秒前
科研通AI6.1应助清子采纳,获得10
13秒前
zhe完成签到,获得积分10
13秒前
jundongfan发布了新的文献求助30
16秒前
chenchen发布了新的文献求助10
16秒前
乐乐应助椰子水采纳,获得10
22秒前
23秒前
23秒前
25秒前
28秒前
科研小白发布了新的文献求助10
31秒前
34秒前
35秒前
jundongfan完成签到,获得积分20
36秒前
36秒前
Satal完成签到,获得积分10
38秒前
韩老麽完成签到 ,获得积分10
39秒前
39秒前
是多少应助li1_李采纳,获得10
41秒前
三D发布了新的文献求助10
42秒前
烟花应助chenchen采纳,获得10
42秒前
CodeCraft应助kitten采纳,获得10
42秒前
43秒前
Hello应助科研通管家采纳,获得10
43秒前
43秒前
43秒前
酷波er应助科研通管家采纳,获得10
43秒前
科研通AI2S应助科研通管家采纳,获得10
43秒前
43秒前
Copyright应助科研通管家采纳,获得10
43秒前
无花果应助科研通管家采纳,获得10
44秒前
高分求助中
GL 2 A method for assessing the in-place cleanability of food processing equipment, Fourth Edition, December 2023 3000
Annie Ernaux: De la perte au corps glorieux 600
Writing Systems 500
Understanding Modeling and Simulation of Polymerization Reactions 400
Invited Discussant 63O and 64O 400
A revision of Limenitis helmanni and its related species (Nymphalidae) from Central and South China 400
Direct and Iterative Linear System Solvers 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6823291
求助须知:如何正确求助?哪些是违规求助? 8536055
关于积分的说明 18168807
捐赠科研通 6158479
什么是DOI,文献DOI怎么找? 3034118
关于科研通互助平台的介绍 2014382
邀请新用户注册赠送积分活动 2011081