Dual-functional Network Regulation Underlies the Central Executive System in Working Memory

工作记忆 任务(项目管理) 编码(内存) 巴德利工作记忆模型 发音抑制 计算机科学 神经科学 心理学 认知心理学 认知 短时记忆 经济 管理
作者
Renshu Yu,Bukui Han,Xia Wu,Guodong Wei,J.T. Zhang,Mingzhou Ding,Xiaotong Wen
出处
期刊:Neuroscience [Elsevier BV]
卷期号:524: 158-180 被引量:1
标识
DOI:10.1016/j.neuroscience.2023.05.025
摘要

The frontoparietal network (FPN) and cingulo-opercular network (CON) may exert top-down regulation corresponding to the central executive system (CES) in working memory (WM); however, contributions and regulatory mechanisms remain unclear. We examined network interaction mechanisms underpinning the CES by depicting CON- and FPN-mediated whole-brain information flow in WM. We used datasets from participants performing verbal and spatial working memory tasks, divided into encoding, maintenance, and probe stages. We used general linear models to obtain task-activated CON and FPN nodes to define regions of interest (ROI); an online meta-analysis defined alternative ROIs for validation. We calculated whole-brain functional connectivity (FC) maps seeded by CON and FPN nodes at each stage using beta sequence analysis. We used Granger causality analysis to obtain the connectivity maps and assess task-level information flow patterns. For verbal working memory, the CON functionally connected positively and negatively to task-dependent and task-independent networks, respectively, at all stages. FPN FC patterns were similar only in the encoding and maintenance stages. The CON elicited stronger task-level outputs. Main effects were: stable CON → FPN, CON → DMN, CON → visual areas, FPN → visual areas, and phonological areas → FPN. The CON and FPN both up-regulated task-dependent and down-regulated task-independent networks during encoding and probing. Task-level output was slightly stronger for the CON. CON → FPN, CON → DMN, visual areas → CON, and visual areas → FPN showed consistent effects. The CON and FPN might together underlie the CES's neural basis and achieve top-down regulation through information interaction with other large-scale functional networks, and the CON may be a higher-level regulatory core in WM.

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
Sylvia完成签到 ,获得积分10
2秒前
SmileyZhang完成签到 ,获得积分10
2秒前
bgt完成签到 ,获得积分10
2秒前
shinn发布了新的文献求助10
3秒前
犹豫代曼完成签到,获得积分10
5秒前
hanm发布了新的文献求助10
6秒前
8秒前
10秒前
科研通AI6.3应助sl采纳,获得10
10秒前
爆米花应助阿坤采纳,获得10
11秒前
11秒前
腼腆的煎饼完成签到,获得积分10
12秒前
12秒前
茯苓完成签到,获得积分10
12秒前
贪玩的秋柔应助haki采纳,获得10
13秒前
王子睿发布了新的文献求助10
15秒前
ZRZR发布了新的文献求助10
15秒前
小汤完成签到 ,获得积分10
15秒前
张睿发布了新的文献求助10
16秒前
茯苓发布了新的文献求助10
17秒前
long完成签到,获得积分10
18秒前
shinn完成签到,获得积分10
18秒前
铁甲小宝完成签到,获得积分10
18秒前
想人陪的飞薇完成签到 ,获得积分10
20秒前
呆萌斩完成签到,获得积分20
21秒前
许诺完成签到,获得积分20
23秒前
去你丫的随机昵称完成签到 ,获得积分10
24秒前
科研通AI6.1应助阿坤采纳,获得10
25秒前
www完成签到,获得积分10
28秒前
英俊的铭应助wjq采纳,获得10
30秒前
李健的小迷弟应助王子睿采纳,获得30
31秒前
32秒前
zhuboujs完成签到,获得积分10
34秒前
科研通AI6.3应助阿坤采纳,获得10
36秒前
隐形曼青应助ccxr采纳,获得10
36秒前
yangya完成签到,获得积分10
37秒前
WZH发布了新的文献求助10
39秒前
39秒前
39秒前
熙原完成签到,获得积分10
40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
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 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 6353802
求助须知:如何正确求助?哪些是违规求助? 8168918
关于积分的说明 17194868
捐赠科研通 5410005
什么是DOI,文献DOI怎么找? 2863885
邀请新用户注册赠送积分活动 1841285
关于科研通互助平台的介绍 1689925