Neural and computational mechanisms of loss aversion in smartphone addiction.

IF 2.9 2区 医学 Q2 NEUROSCIENCES
Jinlian Wang, Chang Liu, Xiang Li, Yuanyuan Gao, Weipeng Jin, Pinchun Wang, Xuyi Chen, Qiang Wang
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Abstract

Smartphones have become integral to daily life, and their overuse can lead to various maladaptive behaviors and decision-making patterns. This study investigated the neural and computational mechanisms underlying smartphone addiction, focusing on its impact on loss-aversion decision-making. We combined computational models, such as the Drift Diffusion Model, with a novel analytic approach, intersubject representational similarity analysis (IS-RSA). Behavioral results showed that higher smartphone addiction symptom (SAS) scores were correlated with reduced loss-aversion (lnλ), while the drift rate was positively associated with SAS. Furthermore, the drift rate mediated the relationship between SAS and lnλ. Neuroimaging analyses revealed that SAS was associated with increased gain-related activity in the occipital pole (OP) but decreased activity in the precuneus and middle frontal gyrus. Additionally, reduced activity was observed in the angular gyrus and superior temporal gyrus during loss processing. IS-RSA further identified brain activation patterns in the default mode network, frontoparietal network, visual network, and sensorimotor network, which corresponded to intersubject variations in SAS, particularly during gain processing but not during loss processing. These patterns were also observed when gains and losses were processed simultaneously. Mediation analyses indicated that brain activation strengths in the OP, precuneus, and MFG during gain processing mediated the relationship between SAS and lnλ and drift rate. Similar mediation effects were observed for intersubject variations in SAS and computational process patterns (eg decision threshold, drift rate, and nondecision time) within these networks. These findings provide novel insights into the neural and computational mechanisms of loss aversion in smartphone addiction, with implications for understanding cognitive biases and informing interventions for addictive behaviors.

智能手机成瘾中损失厌恶的神经和计算机制。
智能手机已经成为日常生活中不可或缺的一部分,过度使用智能手机会导致各种适应不良行为和决策模式。本研究探讨了智能手机成瘾的神经和计算机制,重点关注其对损失规避决策的影响。我们将计算模型,如漂移扩散模型,与一种新的分析方法,学科间代表性相似性分析(IS-RSA)相结合。行为学结果显示,智能手机成瘾症状(SAS)得分越高,损失厌恶情绪(lnλ)越低,而漂移率与SAS呈正相关。此外,漂移速率介导了SAS和lnλ之间的关系。神经影像学分析显示,SAS与枕极(OP)的增益相关活动增加有关,但楔前叶和额中回的活动减少有关。此外,在损失处理过程中,观察到角回和颞上回的活动减少。IS-RSA进一步确定了默认模式网络、额顶叶网络、视觉网络和感觉运动网络的大脑激活模式,这些模式对应于SAS的主体间变化,特别是在增益处理过程中,而不是在损失处理过程中。当收益和损失同时处理时,也观察到这些模式。中介分析表明,增益加工过程中上脑、楔前叶和后脑区的脑激活强度介导了SAS、lnλ和漂移率之间的关系。在这些网络中,SAS和计算过程模式(如决策阈值、漂移率和非决策时间)的主体间差异也观察到类似的中介效应。这些发现为智能手机成瘾中损失厌恶的神经和计算机制提供了新的见解,对理解认知偏见和干预成瘾行为具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cerebral cortex
Cerebral cortex 医学-神经科学
CiteScore
6.30
自引率
8.10%
发文量
510
审稿时长
2 months
期刊介绍: Cerebral Cortex publishes papers on the development, organization, plasticity, and function of the cerebral cortex, including the hippocampus. Studies with clear relevance to the cerebral cortex, such as the thalamocortical relationship or cortico-subcortical interactions, are also included. The journal is multidisciplinary and covers the large variety of modern neurobiological and neuropsychological techniques, including anatomy, biochemistry, molecular neurobiology, electrophysiology, behavior, artificial intelligence, and theoretical modeling. In addition to research articles, special features such as brief reviews, book reviews, and commentaries are included.
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