Exploring common and distinct neural basis of procrastination and impulsivity through elastic net regression

冲动性 弹性网正则化 拖延 回归 基础(线性代数) 心理学 回归分析 认知心理学 人工智能 计算机科学 发展心理学 社会心理学 机器学习 数学 精神分析 几何学
作者
Yin Yao,Ti SU,Xueke Wang,Bowen Hu,Rong Zhang,Feng Zhou,Tingyong Feng
出处
期刊:Cerebral Cortex [Oxford University Press]
卷期号:35 (2) 被引量:4
标识
DOI:10.1093/cercor/bhae503
摘要

Abstract Prior work highlighted that procrastination and impulsivity shared a common neuroanatomical basis in the dorsolateral prefrontal cortex, implying a tight relationship between these traits. However, theorists hold that procrastination is motivated by avoiding aversiveness, while impulsivity is driven by approaching immediate pleasure. Hence, exploring the common and distinct neural basis underlying procrastination and impulsivity through functional neuroimaging becomes imperative. To address this, we employed elastic net regression to examine the links between whole-brain resting-state functional connectivity and these traits in 822 university students from China. Results showed that the functional connections between the default network and the visual network were positively associated with both traits, indicating that the dysfunction of higher-order cognition (eg self-control) may account for their tight relationship. A distinct neural basis was also identified: Procrastination was negatively associated with functional connections between the frontal-parietal network and the ventral-attention network and between the cingular-opercular network and the subcortical network. In contrast, connections between the default network and the somato-motor network were negatively associated with impulsivity. These findings suggest that procrastination may be rooted in emotion-regulation deficits, while impulsivity may be rooted in reward-processing deficits. This deeper understanding of their neural basis provides insights for developing targeted interventions.
最长约 10秒,即可获得该文献文件

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
修仙中应助科研通管家采纳,获得10
刚刚
linman发布了新的文献求助10
刚刚
科研通AI2S应助lanyuhan采纳,获得10
刚刚
SciGPT应助科研通管家采纳,获得10
刚刚
华仔应助科研通管家采纳,获得10
刚刚
orixero应助科研通管家采纳,获得10
刚刚
Ava应助科研通管家采纳,获得10
刚刚
mdwm发布了新的文献求助10
刚刚
科研笨蛋发布了新的文献求助10
刚刚
我是老大应助tang123采纳,获得10
刚刚
小白完成签到,获得积分10
刚刚
刚刚
科研通AI2S应助科研通管家采纳,获得10
刚刚
南冥完成签到,获得积分10
刚刚
风织花开应助科研通管家采纳,获得20
1秒前
1秒前
1秒前
1秒前
1秒前
1秒前
1秒前
1秒前
1秒前
凯七发布了新的文献求助10
2秒前
yang完成签到 ,获得积分10
2秒前
多肉丸子发布了新的文献求助10
2秒前
所所应助songyl采纳,获得10
2秒前
五虎完成签到,获得积分0
2秒前
jinsijia完成签到,获得积分10
3秒前
lengchitu完成签到,获得积分10
3秒前
3秒前
今后应助潇洒孤丹采纳,获得10
3秒前
JamesPei应助Rain采纳,获得10
4秒前
老迟到的可兰完成签到,获得积分10
4秒前
邓仕文完成签到,获得积分20
4秒前
XUHAO完成签到,获得积分10
4秒前
5秒前
沃铁发布了新的文献求助10
5秒前
包容剑鬼完成签到,获得积分10
5秒前
sdl发布了新的文献求助30
5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
The Multiple Self-States Drawing Technique 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 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 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 7768753
求助须知:如何正确求助?哪些是违规求助? 9311946
关于积分的说明 20326464
捐赠科研通 7353879
什么是DOI,文献DOI怎么找? 3315828
关于科研通互助平台的介绍 2464872
邀请新用户注册赠送积分活动 2330405