亲爱的研友该休息了!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!身体可是革命的本钱,早点休息,好梦!

Neural Network Dynamics Supporting Adaptive Attentional Control in the Context of Nicotine Withdrawal: a Review with Empirical Example

背景(考古学) 尼古丁 控制(管理) 认知心理学 心理学 干预(咨询) 注意力控制 感知控制 注意力网络 经验证据 实证研究 认知 人工神经网络 动力学(音乐) 计算机科学 自我控制 神经科学 注意眨眼 尼古丁依赖 注意偏差 线索反应性
作者
Yan Xu,Alexander Weigard,Stephen Jeffrey Wilson,Zvi R. Shapiro,Hilary Galloway-Long,Tyler Warner,Alexandra L. Roule,Christina O. Hlutkowsky,Cynthia Huang-Pollock
出处
期刊:Nicotine & Tobacco Research [Oxford University Press]
卷期号:28 (7): 1082-1093
标识
DOI:10.1093/ntr/ntaf269
摘要

INTRODUCTION: Tobacco use is a leading preventable cause of disability and death, with nicotine withdrawal-related affective and cognitive sequelae posing a key barrier to cessation. Understanding how the dynamics between salience (SN), default mode (DMN), and frontoparietal networks (FPN) support or lead to failures of adaptive attentional control - and how these network interactions may be altered by the cognitive and affective challenges of withdrawal - may help illuminate mechanisms that contribute to smoking relapse. CURRENT REVIEW: The goal of the current review is to synthesize existing literature on resting-state and task-based network connectivity studies of SN, DMN and FPN under nicotine withdrawal, while situating the interpretations of this literature in the broader cognitive neuroscientific understanding of the three-network dynamics. In particular, there is a need to clarify context-dependent network connectivity under nicotine withdrawal, particularly when cognitive and affective demands co-occur. EMPIRICAL EXAMPLE: In addition to the review, we provide a proof-of-concept empirical example examining SN, DMN, and FPN dynamics in daily smokers following nicotine satiation and 12-hour abstinence when cognitive and affective demands were being manipulated. Although prior studies link nicotine withdrawal with increased salience signaling, our data provides initial evidence that SN's modulatory capacity may be reduced - impairing the SN's ability to toggle between the DMN and FPN under high demand. CONCLUSION: Together, results from the literature and our empirical example underscore the importance of context-dependent connectivity analyses for understanding how affective and environmental demands shape attentional control and for informing precise risk prediction and intervention strategies. IMPLICATIONS: This review and empirical example highlight the importance of examining context-dependent brain network dynamics in nicotine withdrawal. Preliminary findings suggest that under cognitive and affective load, the SN not only signals detection of salience or increased demand, but also modulates engagement of the DMN and FPN. Nicotine withdrawal may impair this modulatory capacity, thereby disrupting attentional control. These insights emphasize the utility of task-based connectivity paradigms for identifying mechanisms of relapse vulnerability.

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
zsj完成签到,获得积分10
7秒前
神勇凡英完成签到,获得积分10
15秒前
16秒前
无聊的谷雪完成签到,获得积分10
17秒前
年轻的幼菱完成签到,获得积分10
55秒前
59秒前
ddd发布了新的文献求助10
1分钟前
1分钟前
yy发布了新的文献求助10
1分钟前
科研通AI6.2的应助被唐晓秦采纳,获得10
1分钟前
落后斌完成签到,获得积分10
1分钟前
1分钟前
1分钟前
甜美尔烟完成签到,获得积分10
1分钟前
null的应助被科研通管家采纳,获得10
1分钟前
1分钟前
研友_LX62KZ发布了新的文献求助20
1分钟前
唐晓秦发布了新的文献求助10
1分钟前
2分钟前
一只抱枕发布了新的文献求助10
2分钟前
欠虐宝宝完成签到 ,获得积分10
2分钟前
ddd完成签到,获得积分10
2分钟前
斯文败类的应助被研友_LX62KZ采纳,获得10
2分钟前
英姑的应助被曾经蛟凤采纳,获得10
2分钟前
2分钟前
研友_LX62KZ发布了新的文献求助10
2分钟前
复杂以旋完成签到,获得积分10
2分钟前
fabius0351完成签到 ,获得积分0
2分钟前
温婉的安彤完成签到,获得积分10
2分钟前
高贵的晓啸完成签到,获得积分10
2分钟前
我是老大的应助被pivot_literature采纳,获得10
2分钟前
CipherSage的应助被唐晓秦采纳,获得10
2分钟前
和谐归尘发布了新的文献求助10
2分钟前
2分钟前
2分钟前
难过洙完成签到,获得积分10
3分钟前
3分钟前
Owen的应助被Paddi采纳,获得10
3分钟前
难过云朵完成签到 ,获得积分10
3分钟前
现代的如容完成签到,获得积分10
3分钟前
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
Research Methodology: Best Practices for Rigorous, Credible, and Impactful Research 1000
自動車の空力技術 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7782641
求助须知:如何正确求助?哪些是违规求助? 9322148
关于积分的说明 20387292
捐赠科研通 7371022
什么是DOI,文献DOI怎么找? 3320428
关于科研通互助平台的介绍 2468323
邀请新用户注册赠送积分活动 2336505