Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Germany.
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Psychiatry Res Neuroimaging. 2023 Mar;329:111593. doi: 10.1016/j.pscychresns.2023.111593. Epub 2023 Jan 14.
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.
过度使用智能手机（ESU）可能符合成瘾行为的标准。与其他相关的行为成瘾不同，特别是网络成瘾障碍，人们对 ESU 背后的神经相关性知之甚少。在这项研究中，我们使用功能磁共振成像（fMRI）从三个不同的行为范式（即线索反应性、抑制性和工作记忆）获取个体的任务数据，这些个体是根据心理计量学定义的 ESU（n=19）与对照组（n-ESU；n=20）进行比较的。智能手机成瘾量表（SPAI）用于根据新的五因素模型（SPAI-I）量化 ESU 的严重程度。采用多元数据融合方法，即联合独立成分分析（jICA），分析来自三个独立实验条件的 fMRI 数据，但联合分析以检测不同个体之间存在的趋同和与域无关的神经特征，这些特征在有和没有 ESU 的个体之间存在差异。在三个功能任务中，jICA 确定了一个主要的额顶叶系统，与 n-ESU 相比，ESU 个体的网络强度较低（p < 0.05 FDR 校正）。此外，还发现额顶叶网络强度与 SPAI-I 的“时间花费”和“渴望”维度之间存在显著关联。数据表明，额顶叶认知控制网络是过度使用智能手机且可能具有成瘾性的认知域无关的神经特征。
