Abnormal Functional Connectivity in Cognitive Control Network, Default Mode Network, and Visual Attention Network in Internet Addiction: A Resting-State fMRI Study

Abstract

Internet addiction (IA) has become a global mental and social problem, which may lead to a series of psychiatric symptoms including uncontrolled use of internet, and lack of concentration. However, the exact pathophysiology of IA remains unclear. Most of functional connectivity studies were based on pre-selected regions of interest (ROI), which could not provide a comprehensive picture of the communication abnormalities in IA, and might lead to limited or bias observations. Using local functional connectivity density (lFCD), this study aimed to explore the whole-brain abnormalities of functional connectivity in IA. We evaluated the whole-brain lFCD resulting from resting-state fMRI data in 28 IA individuals and 30 demographically matched healthy control subjects (HCs). The correlations between clinical characteristics and aberrant lFCD were also assessed. Compared with HCs, subjects with IA exhibited heightened lFCD values in the right dorsolateral prefrontal cortex (DLPFC), left parahippocampal gyrus (PHG), and cerebellum, and the bilateral middle cingulate cortex (MCC) and superior temporal pole (STP), as well as decreased lFCD values in the right inferior parietal lobe (IPL), and bilateral calcarine and lingual gyrus. Voxel-based correlation analysis revealed the significant correlations between the Young's Internet Addiction Test (IAT) score and altered lFCD values in the left PHG and bilateral STP. These findings revealed the hyper-connectivity in cognitive control network and default mode network as well as the hypo-connectivity in visual attention network, verifying the common mechanism in IA and substance addiction, and the underlying association between IA, and attention deficit/hyperactivity disorder in terms of neurobiology.

The Modulation of Reward and Habit Systems by Acupuncture in Adolescents with Internet Addiction

“…Thus, all analyses in our study were based on these 57 subjects (27 IA subjects and 30 HCs). Thirteen of the 27 IA subjects were included in our prior article investigating the abnormal functional connectivity density in IA [28] and further consented to participate in the present study to explore the modulation effect of acupuncture on IA. Table 1, no significant intergroup difference was observed in age, gender, or years of education at baseline (p > 0:05).…”

The Spontaneous Activity Pattern of the Middle Occipital Gyrus Predicts the Clinical Efficacy of Acupuncture Treatment for Migraine Without Aura

“…To evaluate the associations between the classifying features and the severity of symptoms, voxel-based correlation analyses (48) were conducted between the meaningful classifying features and the duration/baseline MMDs/baseline VAS scores in patients with MWoA. The statistical significance threshold of the correlation was set to p < 0.05 (uncorrected) and the threshold of cluster size was set to 20 contiguous voxels.…”

Identifying Internet Addiction and Evaluating the Efficacy of Treatment Based on Functional Connectivity Density: A Machine Learning Study

“…In a longitudinal fMRI study, the FC of the putamen in individuals with IA was also found to be significantly correlated with the online time per day, suggesting that the habitual use of the internet was related to hyperactive impulsive habit system in the brain (Lee et al, 2021). Using functional connectivity density (FCD) analysis, a novel method that overcomes the bias of FC produced by the preselection of ROIs, to analyze whole-brain functional communication, we further found altered dorsolateral prefrontal cortex (DLPFC) function in our prior study (Wang et al, 2019), representing the defective reflecting system in IA. These fMRI studies have provided us with the potential neuropathologic mechanism underlying IA; however, the average differences between groups are insufficient in guiding individual clinical practice directly.…”

“…Thus, the final dataset included data obtained from 27 individuals with IA and 30 HCs. Fifteen of 27 individuals with IA had participated in our former fMRI study detecting functional abnormalities in IA (Wang et al, 2019) and further consented to take part in the present CBT study. Each individual with IA met the diagnostic criteria for IA (assessed by the Internet Addiction Questionnaire), while all the demographically matched HCs did not meet the criteria for IA.…”

“…In the last two decades, with the development of digital information technology, the internet has brought great convenience and benefit to people's lives, but the popularity of the internet has also brought new public health issues, such as internet addiction (IA). IA, characterized by excessive internet craving and habitual and uncontrolled use of the internet (Hormes et al, 2014;Wang et al, 2019), has widely prevailed all over the world, with a prevalence ranging from 0.2 to 57.5% (Darvesh et al, 2020). Even in medical students, the pooled incidence rate of IA is as high as 30.1% (Zhang et al, 2018).…”