6. Discussion
The primary aim of this review was to present a summary of how internet addiction impacts on the functional connectivity of adolescent brain. Subsequently, the influence of Internet Addiction on the adolescent brain was compartmentalised into three sections: alterations of functional connectivity at various brain regions, specific functional connectivity relationships, and behavioural/developmental changes.
Overall, the specific effects of Internet Addiction on the adolescent brain were not completely clear, given the variety of functional connectivity changes. However, there were overarching behavioural, network and developmental trends that were supported that provided insight on adolescent development.
The first hypothesis that was held about this question was that Internet Addiction was widespread and would be regionally similar to substance-use and gambling addiction. After conducting a review of the information in the chosen articles, the hypothesis was predictably supported. The regions of the brain affected by Internet Addiction are widespread and influence multiple networks, mainly default mode network, executive control network, salience network and reward pathway.
In the default mode network, there was a complex mix of increases and decreases within the network. However, in the executive control network, the alterations of functional connectivity were more unilaterally decreased, but the findings of salience network and reward pathway were not quite clear. Overall, the functional connectivity changes within adolescents with Internet Addiction are very much network specific and lay a solid foundation from which to understand the subsequent behaviour changes that arise from the disorder.
The second hypothesis placed emphasis on the importance of between network interactions and within network interactions in the continuation of Internet Addiction and the development of its behavioural symptoms. The results from the findings involving the networks, default mode network, salience network, executive control network and reward system, support this hypothesis (see Fig 5). Studies confirm the influence of all these neural networks on reward valuation, impulsivity, salience to stimuli, cue reactivity and other changes that alter behaviour towards the internet use. Many of these changes are connected to the inherent nature of the adolescent brain.
There are multiple explanations that underlie the vulnerability of the adolescent brain towards Internet Addiction related urges. Several of them have to do with the inherent nature and underlying mechanisms of the adolescent brain. Children’s emotional, social, and cognitive capacities grow exponentially during childhood and adolescence [57]. Early teenagers go through a process called “social reorientation” that is characterised by heightened sensitivity to social cues and peer connections [58]. Adolescents’ improvements in their social skills coincide with changes in their brains’ anatomical and functional organisation [59]. Functional hubs exhibit growing connectivity strength [60], suggesting increased functional integration during development. During this time, the brain’s functional networks change from an anatomically dominant structure to a scattered architecture [60].
The adolescent brain is very responsive to synaptic reorganisation and experience cues [61]. As a result, one of the distinguishing traits of the maturation of adolescent brains is the variation in neural network trajectory [62]. Important weaknesses of the adolescent brain that may explain the neurobiological change brought on by external stimuli are illustrated by features like the functional gaps between networks and the inadequate segregation of networks [62].
The implications of these findings towards adolescent behaviour are significant. Although the exact changes and mechanisms are not fully clear, the observed changes in functional connectivity have the capacity of influencing several aspects of adolescent development. For example, functional connectivity has been utilised to investigate attachment styles in adolescents [63].
It was observed that adolescent attachment styles were negatively associated with caudate-prefrontal connectivity, but positively with the putamen-visual area connectivity [63]. Both named areas were also influenced by the onset of internet addiction, possibly providing a connection between the two. Another study associated neighbourhood / socioeconomic disadvantage with functional connectivity alterations in the default mode network and dorsal attention network [64]. The study also found multivariate brain behaviour relationships between the altered/disadvantaged functional connectivity and mental health and cognition [64].
This conclusion supports the notion that the functional connectivity alterations observed in Internet Addiction are associated with specific adolescent behaviours as well as the fact that functional connectivity can be utilised as a platform onto which to compare various neurologic conditions.
Limitations / strengths
There were several limitations that were related to the conduction of the review as well as the data extracted from the articles. Firstly, the study followed a systematic literature review design when analysing the fMRI studies.
The data pulled from these imaging studies were namely qualitative and were subject to bias contrasting the quantitative nature of statistical analysis. Components of the study, such as sample sizes, effect sizes, and demographics were not weighted or controlled. The second limitation brought up by a similar review was the lack of a universal consensus of terminology given Internet Addiction [47].
Globally, authors writing about this topic use an array of terminology including online gaming addiction, internet addiction, internet gaming disorder, and problematic internet use. Often, authors use multiple terms interchangeably which makes it difficult to depict the subtle similarities and differences between the terms.
Reviewing the explicit limitations in each of the included studies, two major limitations were brought up in many of the articles. One was relating to the cross-sectional nature of the included studies. Due to the inherent qualities of a cross-sectional study, the studies did not provide clear evidence that Internet Addiction played a causal role towards the development of the adolescent brain. While several biopsychosocial factors mediate these interactions, task-based measures that combine executive functions with imaging results reinforce the assumed connection between the two that is utilised by the papers studying Internet Addiction.
Another limitation regarded the small sample size of the included studies, which averaged to around 20 participants. The small sample size can influence the generalisation of the results as well as the effectiveness of statistical analyses. Ultimately, both included study specific limitations illustrate the need for future studies to clarify the causal relationship between the alterations of functional connectivity and the development of Internet Addiction.
Another vital limitation was the limited number of studies applying imaging techniques for investigations on Internet Addiction in adolescents were a uniformly Far East collection of studies. The reason for this was because the studies included in this review were the only fMRI studies that were found that adhered to the strict adolescent age restriction. The adolescent age range given by the WHO (10–19 years old) [65] was strictly followed. It is important to note that a multitude of studies found in the initial search utilised an older adolescent demographic that was slightly higher than the WHO age range and had a mean age that was outside of the limitations. As a result, the results of this review are biased and based on the 12 studies that met the inclusion and exclusion criteria.
Regarding the global nature of the research, although the journals that the studies were published in were all established western journals, the collection of studies were found to all originate from Asian countries, namely China and Korea. Subsequently, it pulls into question if the results and measures from these studies are generalisable towards a western population. As stated previously, Asian countries have a higher prevalence of Internet Addiction, which may be the reasoning to why the majority of studies are from there [8]. However, in an additional search including other age groups, it was found that a high majority of all functional connectivity studies on Internet Addiction were done in Asian countries.
Interestingly, western papers studying fMRI functional connectivity were primarily focused on gambling and substance-use addiction disorders. The western papers on Internet Addiction were less focused on fMRI functional connectivity but more on other components of Internet Addiction such as sleep, game-genre, and other non-imaging related factors. This demonstrated an overall lack of western fMRI studies on Internet Addiction. It is important to note that both western and eastern fMRI studies on Internet Addiction presented an overall lack on children and adolescents in general.
Despite the several limitations, this review provided a clear reflection on the state of the data. The strengths of the review include the strict inclusion/exclusion criteria that filtered through studies and only included ones that contained a purely adolescent sample. As a result, the information presented in this review was specific to the review’s aims. Given the sparse nature of adolescent specific fMRI studies on the functional connectivity changes in Internet Addiction, this review successfully provided a much-needed niche representation of adolescent specific results. Furthermore, the review provided a thorough functional explanation of the default mode network, executive control network, salience network and reward pathway making it accessible to readers new to the topic.
Future directions and implications
Through the search process of the review, there were more imaging studies focused on older adolescence and adulthood. Furthermore, finding a review that covered a strictly adolescent population, focused on functional connectivity changes, and was specifically depicting Internet Addiction, was proven difficult.
Many related reviews, such as Tereshchenko and Kasparov (2019), looked at risk factors related to the biopsychosocial model, but did not tackle specific alterations in specific structural or functional changes in the brain [66]. Weinstein (2017) found similar structural and functional results as well as the role Internet Addiction has in altering response inhibition and reward valuation in adolescents with Internet Addiction [47]. Overall, the accumulated findings only paint an emerging pattern which aligns with similar substance-use and gambling disorders. Future studies require more specificity in depicting the interactions between neural networks, as well as more literature on adolescent and comorbid populations.
One future field of interest is the incorporation of more task-based fMRI data. Advances in resting-state fMRI methods have yet to be reflected or confirmed in task-based fMRI methods [62]. Due to the fact that network connectivity is shaped by different tasks, it is critical to confirm that the findings of the resting state fMRI studies also apply to the task based ones [62]. Subsequently, work in this area will confirm if intrinsic connectivity networks function in resting state will function similarly during goal directed behaviour [62]. An elevated focus on adolescent populations as well as task-based fMRI methodology will help uncover to what extent adolescent network connectivity maturation facilitates behavioural and cognitive development [62].
A treatment implication is the potential usage of bupropion for the treatment of Internet Addiction. Bupropion has been previously used to treat patients with gambling disorder and has been effective in decreasing overall gambling behaviour as well as money spent while gambling [67]. Bae et al. (2018) found a decrease in clinical symptoms of Internet Addiction in line with a 12-week bupropion treatment [31]. The study found that bupropion altered the functional connectivity of both the default mode network and executive control network which in turn decreased impulsivity and attentional deficits for the individuals with Internet Addiction [31]. Interventions like bupropion illustrate the importance of understanding the fundamental mechanisms that underlie disorders like Internet Addiction.