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
耍酷的世平完成签到,获得积分10
1秒前
闵闵发布了新的文献求助30
2秒前
彩色煎蛋发布了新的文献求助10
4秒前
可温完成签到,获得积分10
6秒前
7秒前
心灵美的大山完成签到,获得积分10
9秒前
10秒前
troublemaker发布了新的文献求助10
10秒前
11秒前
12秒前
yexu845发布了新的文献求助10
13秒前
17秒前
17秒前
nidejun发布了新的文献求助10
18秒前
18秒前
JamesPei应助花卷儿采纳,获得10
18秒前
ChenChen发布了新的文献求助20
19秒前
深情安青应助troublemaker采纳,获得10
20秒前
梦华老师发布了新的文献求助10
21秒前
念之完成签到 ,获得积分10
21秒前
21秒前
21秒前
22秒前
23秒前
斯文败类应助白色桔梗采纳,获得10
25秒前
lin发布了新的文献求助10
25秒前
小可发布了新的文献求助10
26秒前
26秒前
ycd发布了新的文献求助10
26秒前
27秒前
tong发布了新的文献求助10
27秒前
hahasun完成签到,获得积分10
28秒前
iiiicecream发布了新的文献求助10
29秒前
科研通AI6.1应助哭泣之槐采纳,获得10
29秒前
ljz发布了新的文献求助30
29秒前
29秒前
30秒前
zhao完成签到 ,获得积分10
30秒前
31秒前
自由的冥幽完成签到,获得积分20
34秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Research Handbook on the Law of the Paris Agreement 1000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Superabsorbent Polymers: Synthesis, Properties and Applications 500
Photodetectors: From Ultraviolet to Infrared 500
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 6352281
求助须知:如何正确求助?哪些是违规求助? 8166946
关于积分的说明 17188455
捐赠科研通 5408524
什么是DOI,文献DOI怎么找? 2863264
邀请新用户注册赠送积分活动 1840703
关于科研通互助平台的介绍 1689652