期刊
PSYCHIATRY RESEARCH-NEUROIMAGING
卷 329, 期 -, 页码 -出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.pscychresns.2023.111593
关键词
Addiction; Functional magnetic resonance imaging; Independent component analysis; Prefrontal cortex; Smartphone
This study used functional magnetic resonance imaging (fMRI) to compare the brain activity of excessive smartphone users and non-excessive users, and found that excessive smartphone users had lower connectivity strength in the frontoparietal system. This suggests that excessive smartphone use may be associated with the cognitive control network of the frontoparietal cortex.
Excessive smartphone use (ESU) may fulfill criteria for addictive behavior. In contrast to other related behavioral addictions, particularly Internet Gaming Disorder, little is known about the neural correlates underlying ESU. In this study, we used functional magnetic resonance imaging (fMRI) to acquire task data from three distinct behavioral paradigms, i.e. cue-reactivity, inhibition, and working memory, in individuals with psychometrically defined ESU (n = 19) compared to controls (n-ESU; n = 20). The Smartphone Addiction Inventory (SPAI) was used to quantify ESU-severity according to a novel five-factor model (SPAI-I). A multivariate data fusion approach, i.e. joint Independent Component Analysis (jICA) was employed to analyze fMRI-data derived from three separate experimental conditions, but analyzed jointly to detect converging and domain-independent neural signatures that differ between persons with vs. those without ESU. Across the three functional tasks, jICA identified a predominantly frontoparietal system that showed lower network strength in individuals with ESU compared to n-ESU (p < 0.05 FDR-corrected). Furthermore, significant associations between frontoparietal network strength and SPAI-I's dimensions time spent and craving were found. The data suggest a frontoparietal cognitive control network as cognitive domain-independent neural signature of excessive and potentially addictive smartphone use.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据