Prefrontal Control and Internet Addiction: A Theoretical Model and Review of Neuropsychological and Neuroimaging Findings (2014)

General introduction and search methods

Most people use the Internet as a functional tool in everyday-life and many individuals cannot imagine living without the Internet in business or private life. The Internet provides multifariousness of possibilities for communication, entertainment, and dealing with everyday-life requirements (e.g., making restaurant reservations, searching for information, keeping updated with respect to political and society issues, etc.). With the growth of the Internet over the last two decades, the number of subjects experiencing massive negative consequences in their lives has also grown extensively. These persons experience a loss of control over their Internet use and report social problems as well as school and/or work difficulties (Young, 1998a; Beard and Wolf, 2001).

This contribution is a narrative review on Internet addiction and prefrontal control processes. It reflects the ideas and opinions of the authors based on their literature search and experiences. Nevertheless, we would like to briefly comment on the procedure we used to select the articles referred to in this review. We used two databases searching for suitable articles: PubMed and PsycInfo. The search was conducted using the terms: “Internet addiction,” “Compulsive Internet use,” and “Internet use disorder.” After a general overview over the found articles, each of the terms was combined with each of the terms “prefrontal cortex” or “executive functions” or “neuropsychology” or “control processes” or “decision making” or “neuroimaging” or “functional brain imaging” using the conjunction “AND.” Each term was required to be present in the “Title/Abstract” of the paper. Both searches were further limited by “English” as the publication language. We selected original research papers as well as review articles. We also used the function “related articles.” Given the limited space, we had to exclude several articles. We aimed at including both classical articles and very current studies. On the other hand, we also included some articles of other research areas (e.g., pathological gambling, substance dependency), whenever it seemed appropriate. In summary, following a systematic search for relevant articles, we selected the studies and reviews cited on the basis of a subjective impression. We thereby aimed at summarizing the most important views and findings on Internet addiction with a focus on the link between control processes and symptoms of Internet addiction. We also aimed at summarizing some very recent findings and ideas, which may be helpful for inspiring both future scientific studies and new therapeutic approaches.

History of Internet addiction research, terminology, and symptoms

The first scientific description of a young man who developed severe psychosocial problems due to his excessive Internet use was done by Young (1996). It was followed by a growing number of other single- and multiple-case studies (e.g., Griffiths, 2000). Today, a relatively large literature exists on the phenomenology, the epidemiology for different countries, and co-morbidity of a problematic or pathological Internet use (see recent review by Spada, 2014). The prevalence rates reported in the last years have a wide variety from 0.8 in Italy to 26.7% in Hong Kong (see the excellent review by Kuss et al., 2013). Reasons for this extreme variance are most likely some cultural effects, but also the fact that until now, no standard assessment tool, no clearly defined cut-off scores, and even no fully accepted diagnostic criteria have been established (see exception for Internet Gaming disorder described below).

Although the clinical relevance is obvious and many clinicians see patients suffering from severe negative consequences due to an overuse of the Internet in general or certain Internet applications, the terminology used for this phenomenon and its classification are still under debate (Young, 1998b, 1999; Charlton and Danforth, 2007; Starcevic, 2013). Young (2004) argues that the criteria, which have been defined for pathological gambling and substance dependency should also be applied to Internet addiction. This is also in accordance with some other researchers, for example with the component model on addictive behaviors by Griffiths (2005). Nevertheless, there is a sum of different terms used in the scientific literature when referring to an overuse of the Internet, such as Internet addiction (Young, 1998b, 2004; Hansen, 2002; Chou et al., 2005; Widyanto and Griffiths, 2006; Young et al., 2011), compulsive Internet use (Meerkerk et al., 2006, 2009, 2010), Internet-related addictive behavior (Brenner, 1997), Internet-related problems (Widyanto et al., 2008), problematic Internet use (Caplan, 2002), and pathological Internet use (Davis, 2001). We prefer the term Internet addiction, since we see some important parallels between Internet addiction and other so-called behavioral addictions (e.g., Grant et al., 2013) and substance dependency (see also Griffiths, 2005; Meerkerk et al., 2009), which we will summarize in Sections “Neuropsychological Correlates of Internet Addiction” and “Neuroimaging Correlates of Internet Addiction.”

The APA has now focused on Internet gaming. We argue, however, that also other applications can be used addictively (Young et al., 1999; Meerkerk et al., 2006). Therefore, we summarize results of previous studies on Internet addiction in a broader way, although a great proportion of studies published so far concentrated on Internet gaming. Although not all criteria must be fulfilled, we would like to highlight one specific criterion, which seems very important and is most frequently fulfilled in patients suffering from Internet addiction. This criterion is: “Unsuccessful attempts to control the behavior” or to say it shorter: “Loss of control.” This criterion is also a factor frequently found when analyzing the factorial structure of questionnaires used to assess Internet addiction (Chang and Law, 2008; Korkeila et al., 2010; Widyanto et al., 2011; Lortie and Guitton, 2013; Pawlikowski et al., 2013). Consequently, the ability to control one’s own Internet use is an important factor preventing people from developing an Internet addiction. In turn, if an individual suffers from Internet addiction, one therapy goal must be to give the patient back the control over his/her Internet use. But why is it so difficult for some individuals to control the Internet use? One reason may be that Internet-related cues interfere with control processes mediated by the prefrontal cortex. We will summarize some recent findings from neuropsychological research emphasizing that in fact Internet-related stimuli interfere with decision making and other prefrontal functions, such as working memory and further executive functions. We will argue that reductions of prefrontal control processes play a major role in developing and maintaining an addictive use of the Internet.

Before we describe the role of control processes, we summarize recent models on Internet addiction, in order to make clear why specific cognitive processes may interact with other people’s characteristics, such as personality and psychopathological symptoms in the development and maintenance of Internet addiction in general or specific types of Internet addiction.

General comments on neuropsychological research in addiction

Cognitive control refers to the ability to control one’s own actions, behavior, and even thoughts and is a multifarious construct (Cools and D’Esposito, 2011). Although reductions in cognitive control are sometimes regarded as the main component of impulsivity, in neuropsychological research control mechanisms are ascribed to executive functions. Executive functions are control systems allowing us to regulate our behavior that is planned, goal oriented, flexible, and effective (Shallice and Burgess, 1996; Jurado and Rosselli, 2007; Anderson et al., 2008). These functions are strongly linked to parts of the prefrontal cortex, in particular the dorsolateral prefrontal cortex (e.g., Alvarez and Emory, 2006; Bari and Robbins, 2013; Yuan and Raz, 2014). The prefrontal cortex is connected to parts of the basal ganglia (e.g., Hoshi, 2013). For these connections, the term fronto-striatal loops is frequently used. Fronto-striatal loops include a more cognitive loop, which mainly connects the nucleus caudatus and putamen with the dorsolateral section of the prefrontal cortex (via the thalamus) and the limbic loop connecting limbic structures, such as the amygdala, and structures that are linked to motivational aspects of behavior, such as the nucleus accumbens, with the orbitofrontal and ventromedial part of the prefrontal brain area (Alexander and Crutcher, 1990). These parts of the brain are crucially involved in executive functions and other higher-order cognitions, but they are also main neural correlates of addictive behavior. Figure ​Figure22 summarizes these brain structures.

 

Figure 2

The prefrontal cortex regions and associated brain structures most likely involved in development and maintenance of an addictive use of the Internet. (A) Shows the lateral view of the brain including medial parts such as anterior cingulate gyrus and …

Before we focus on this issue in Section “Neuroimaging Correlates of Internet Addiction,” neuropsychological correlates of an addictive use of the Internet are summarized. In addiction research with a neuropsychological focus, executive functions, decision making, and attentional processes have been investigated extensively using traditional neuropsychological tasks, such as gambling tasks. These approaches have already been transferred to behavioral addictions, such as pathological gambling (e.g., Goudriaan et al., 2004; Brand et al., 2005b; Goudriaan et al., 2005, 2006; van Holst et al., 2010; Conversano et al., 2012) and compulsive buying (e.g., Black et al., 2012).

Neuropsychological functions in subjects with Internet addiction

Over the last years, a sum of studies has also been published, which assessed general neuropsychological functions in individuals with either GIA or a certain SIA. Most of the studies, however, were done with excessive Internet gamers. One example is the study by Sun et al. (2009). They used the Iowa Gambling Task (Bechara et al., 2000), which had been used in many studies with different patient populations with neurological and psychiatric diseases including substance dependency and behavioral addictions before (cf. Dunn et al., 2006). This task assesses decision making under ambiguous conditions. Performing well on the task requires particularly learning from feedback. The excessive Internet users in the study by Sun et al. (2009) had problems in performing the Iowa Gambling Task, indicating decision-making deficits, which had frequently been linked to addictive behaviors (Bechara, 2005). In another study by Pawlikowski and Brand (2011), it was shown that excessive Internet gamers make more risky and disadvantageous choices, even when the rules for positive and negative consequences are explicitly explained, measured by the Game of Dice Task (Brand et al., 2005a). This result is consistent with findings in other samples with addiction, such as opiate dependency (Brand et al., 2008b), and pathological gambling (Brand et al., 2005b). Furthermore, performing the Dice Task well is linked to prefrontal integrity (Labudda et al., 2008) and executive functions (e.g., Brand et al., 2006; Brand et al., 2008a, 2009). Consequently, the results suggest that patients with Internet addiction may have reductions in prefrontal control and other executive functioning.

With respect to the ability to inhibit responses to certain stimuli, the individuals investigated by Sun et al. (2009) performed normally on a Go/No-Go Task, which measures response inhibition functions. This result on intact response inhibition is consistent with the findings by Dong et al. (2010) and also consistent with normal performance on the classical Stroop paradigm (see behavioral data in Dong et al., 2013b). However, in another study, Dong et al. (2011b) reported higher response errors in the incongruent condition of the Stroop paradigm in male Internet addicted individuals. In all these studies on inhibitory control, however, neutral versions of the Go/No-Go task or the Stroop paradigm have been used, meaning that all stimuli were unrelated to the Internet. One may hypothesize that individuals with Internet addiction react differently on stimuli, which explicitly show Internet-related content and have difficulty in inhibiting responses only to those stimuli, as it has been shown in substance-dependent individuals (e.g., Pike et al., 2013). This was reported by Zhou et al. (2012) using a shifting-task with Internet game-related cues. The authors argue that reductions in response inhibition and lower mental flexibility may be responsible for the maintenance of Internet gaming addiction.

Concentrating on other forms of Internet addiction, namely the excessive use of Internet pornography, which is also one of the main types of SIA (Meerkerk et al., 2006), beyond Internet gaming, first studies have used classical paradigms assessing cognitive functions and modified them in terms of including Internet pornographic pictures as stimuli. For example, Laier et al. (2014) used the Iowa Gambling Task, but included pornographic and neutral pictures on the card decks. One group of participants performed the task with pornographic pictures on the disadvantageous decks (A and B) and neutral pictures on the advantageous decks (C and D) and the other group performed the task with reversed picture-deck association (pornographic pictures on the advantageous decks C and D). The results demonstrated that the group performing the task with pornographic pictures on the disadvantageous decks had lower scores than the other group. This means that they continued selecting the cards from the decks with pornographic pictures, even though they received high losses. This effect was particularly observed in subjects who responded with a subjective craving reaction on the presentation of pornographic stimuli (in another paradigm, also included in the study). This finding is consistent with the results of another study by the same group of authors (Laier et al., 2013b), in which they reported lower working memory performance for pornographic stimuli than for positive, negative, and neutral pictures. The authors conclude that sexual arousal as reaction to Internet pornographic pictures interferes with cognitive functions.

We now argue that particularly cognitive control processes are affected when Internet addicted individuals are confronted with the addiction-related stimuli. However, this hypothesized mechanism needs further investigations for certain types SIA. Most importantly, this mechanism can be investigated best by using cognitive tasks, which include addiction-related stimuli and not with simple standard cognitive tasks.

General comments on neuroimaging research in the context of addiction

Most studies investigating neural correlates of Internet addiction with functional imaging techniques have been conducted with Internet gamers. These studies have revealed great similarities with brain circuits involved in the problematic behavior in substance-related addictions and pathological gambling, which will be discussed in the following sections. Two different approaches can be distinguished: functional activation studies as well as structural investigations and resting-state imaging including diffusion tensor imaging. The goal of both approaches is the same: a better understanding of the brain mechanisms involved in the excessive and addictive use of the Internet or certain Internet applications. The overall research questions are: does the brain change over time insofar that it learns to react on Internet cues specifically, and do these brain reactions determine the loss of control over the Internet use? From substance-dependency research, it is well-known that different brain areas are involved in the controlled and deliberative substance intake (e.g., with respect to alcohol) as compared to an uncontrolled and habitual use. In the first stages of drug-dependency development, frontal brain areas are particularly involved in the decision to consume a certain drug, motivated by its reinforcing effects (Goldstein and Volkow, 2002). As a result of classical and instrumental conditioning processes (Everitt and Robbins, 2006), the nucleus accumbens and parts of the dorsal striatum together with limbic and para-limbic regions (e.g., the orbitofrontal cortex) learn to habitually react on drug cues with craving and the dorsolateral prefrontal cortex, which is linked to higher-order cognitive functions, loses its regulatory influences (Bechara, 2005; Goldstein et al., 2009). This is most likely the consequence of changes in the dopaminergic reward system by frontal-guided changes of glutaminergic innervation of the nucleus accumbens and related brain areas (Kalivas and Volkow, 2005). In individuals with substance-dependency environmental factors, such as the presence of drug-related cues, lead to activations of the ventral striatum, the anterior cingulate cortex, and also mediofrontal cortex areas (Kühn and Gallinat, 2011; Schacht et al., 2013). These areas, but also the amygdala and the orbitofrontal cortex, are related to craving (Chase et al., 2011). In the next section, we will summarize previous neuroimaging findings on neural correlates of Internet addiction and will argue that the processes underlying substance dependency are also valid for Internet addiction.

Functional neuroimaging in Internet addiction

Current studies on Internet addiction and in particular on Internet gaming addiction have applied neuroimaging methods to identify brain circuits involved in cue-reactivity and craving in those individuals who experience a loss of control over their Internet (games) use. A systematic review of those studies published in 2012 and earlier has been provided by Kuss and Griffiths (2012). They identified 18 studies, which used either functional magnetic resonance imaging (fMRI), positron emission tomography (PET), structural MRI or electroencephalography (EEG). When excluding the EEG studies (six studies summarized by Kuss and Griffith) and the two structural MRI studies, the systematic review concentrated on 10 studies with classical functional brain methods. We now applied the same search and inclusion criteria as documented in the review by Kuss and Griffiths (2012) and identified 13 studies (excluding EEG studies) published in peer-reviewed journals from January 2013 to end of January 2014. We here concentrate exemplarily on those earlier and current studies, which notably contribute to a better understanding of the link between prefrontal control processes and loss of control of the Internet use in individuals with Internet addiction.

One of the earliest studies on potential brain correlates of craving in subjects with Internet (gaming) addiction was reported by Ko et al. (2009). They studied excessive World-of-Warcraft (WoW) players (all participants played at least 30 h a week) with fMRI using a picture paradigm, which is comparable with those previously used in alcohol addiction research (e.g., Braus et al., 2001; Grüsser et al., 2004). The results were very similar to those reported in substance-dependent individuals (Schacht et al., 2013). The WoW players had, compared to the control group, stronger activations within the nucleus accumbens, the orbitofrontal cortex, and the caudate while watching WoW pictures. These activities were also correlated positively with subjective gaming urge. A comparable finding was reported by Sun et al. (2012), who also investigated excessive WoW players with a picture paradigm to induce craving. Here, activities in bilateral sections of the prefrontal cortex, in particular the dorsolateral prefrontal cortex, and the anterior cingulate cortex were positively correlated with subjective craving when watching WoW pictures. The results emphasize the view that the brain of Internet addicted individuals reacts with craving to the confrontation with Internet-related cues in the same way as the brain of substance-dependent individuals reacts on substance-related stimuli. Consistent with this, Han et al. (2011) found that the desire to play was positively related to activity in the right mediofrontal lobe and right parahippocampal gyrus even in healthy subjects, who were trained to play a certain video game for 10 days. Changes in prefrontal brain areas related to cue-reactivity and gaming urges in excessive players have also been reported in other previous studies (e.g., Han et al., 2010b; Ko et al., 2013a; Lorenz et al., 2013) and comparisons between cue-reactivity on gaming stimuli and substance dependency (e.g., tobacco) have been discussed (Ko et al., 2013b). Results illustrate similarities between Internet addiction and other addiction conditions with respect to underlying mechanisms of development, in particular conditioning processes (Robinson and Berridge, 2001, 2003; Thalemann et al., 2007). There is also some evidence for early functional brain adaptations in adolescent Internet users in frontal, temporal, and temporo-parietal–occipital junction area, as revealed by a ball-throwing paradigm (Kim et al., 2012). One first study linked cue-reactivity and craving with therapy success in subjects addicted to Internet games (Han et al., 2010a): at the first investigation with a picture paradigm and fMRI, the group of excessive StarCraft players (StarCraft is a real-time strategy video game), compared to volunteers with low StarCraft experiences, showed stronger activations in the dorsolateral prefrontal cortex, occipital areas, and left parahippocampal gyrus. Following a 6-week therapy with bupropion, which is frequently used in substance-dependence therapy, the craving reactions and playing time were reduced in the Internet gamers and the activity in the dorsolateral prefrontal cortex while watching StarCraft pictures were also decreased compared to the first fMRI investigation. Summarized, subjects with Internet addiction show craving reactions toward certain Internet-related cues on both subjective and neural level. Craving reactions are correlated with prefrontal brain changes, which are comparable to those reported for substance-dependent patients.

Also using fMRI, Dong et al. (2013b) investigated decision-making competence in individuals with Internet addiction (without specifying the type of Internet addiction). They used a card game with two options and manipulated the sequence of wins and losses, resulting in three conditions: continuous wins, continuous losses, and discontinuous wins and losses as control condition. Behaviorally, the individuals with Internet addiction needed longer for their decisions, in particular in the loss condition. Compared to the control subjects, the patients with Internet addiction had stronger brain activity in the inferior frontal gyrus, the anterior cingulate gyrus, and the insula in the win condition and stronger activity in the inferior frontal gyrus also in the loss condition. The posterior cingulate region and the caudate were less activated in patients with Internet addiction compared to the control group. The authors conclude that patients with Internet addiction have reductions in decision-making performance, because they need more endeavor to executive functions. In another publication with the same groups and tasks, the authors also reported a higher sensitivity for wins in comparison to losses in Internet addicted subjects (Dong et al., 2013a), which was accompanied by stronger activations in the inferior frontal gyrus and decreased activity in the posterior cingulate cortex in subjects with Internet addiction compared to the control group. These results fit with earlier investigations with the same guessing task (Dong et al., 2011a). Problems in making good decisions, meaning that individuals with Internet addiction continue playing games even though they are confronted with negative consequences, might be related to their problems in everyday-life (see also discussion in Pawlikowski and Brand, 2011). The argument of more endeavor in executive functions when being confronted with complex situations of decision making or when cognitive flexibility is required is confirmed by another fMRI study on cognitive flexibility of Internet addicted subjects (Dong et al., 2014). There is also first evidence for decreased error monitoring in subjects with Internet addiction, which is related to stronger activity in the anterior cingulate gyrus (Dong et al., 2013c), a region also known to be involved in cognitive control and conflict management (e.g., Botvinick et al., 2004). The results are consistent with another study on Internet addiction by Dong et al. (2012b), in which greater activity in the anterior (and also posterior) cingulate cortex was revealed for the interference condition of the Stroop paradigm.

Again, most studies used neutral stimuli when examining the neural correlates of cognitive functions in Internet addiction. Although these studies converge to the view that cognitive control processes are reduced in Internet addicted subjects, it would be important to investigate what happens in the brain of Internet addicts when being confronted with Internet-related stimuli. Given that individuals react with craving toward Internet-related cues (see literature review above), and that they obviously have some certain problems in executive control even in neutral situations, these executive and decision-making functions should be even worse when being in a situation, which offers Internet-related stimuli. This should be investigated in the future, because in daily life, the individuals are frequently confronted with the Internet and it would be clinically relevant to understand how the brain reacts toward those stimuli in interaction with reduced executive control functions.

Structural and resting-state neuroimaging in Internet addiction

A study on both structural and functional neural correlates of Internet/computer gaming with a large sample (N  = 154) adolescents reported higher gray matter volume in left ventral striatal region in frequent/excessive compared to infrequent players (Kühn et al., 2011). In the functional part of the study, activity in the region of the ventral striatum was higher in frequent compared to infrequent players in the loss condition of a monetary incentive delay task. The authors conclude that the volume changes in the left ventral striatal region may reflect changes in reward sensitivity linked to frequent playing of computer games. Gray matter density was also examined by Yuan et al. (2011). In a smaller sample (N  = 18) of adolescents with Internet addiction, decreased gray matter volume was found in several prefrontal regions: the dorsolateral prefrontal cortex (bilaterally), the orbitofrontal cortex, and the supplementary motor area, as well as in posterior parts of the brain (cerebellum and the left rostral anterior cingulate cortex). The changes in the prefrontal areas were correlated with reported duration of the disorder. The authors conclude that these brain changes may be responsible for an impairment of cognitive control in subjects with Internet addiction and that these changes have some important similarities with those observed in substance dependency. Reductions in gray matter density were also found in the left anterior and posterior cingulate cortex, as well as in the insula (Zhou et al., 2011) and in the orbitofrontal cortex (Hong et al., 2013a; Yuan et al., 2013). The changes in the orbitofrontal region were correlated with performance in the Stroop paradigm (Yuan et al., 2013), indicating functional reductions in prefrontal control processes. Gray matter reductions in the (right) orbitofrontal cortex in individuals with SIA for games, in addition also in the insula (bilaterally), and the right supplementary motor area were reported by Weng et al. (2013). Interestingly, the volume of the orbitofrontal cortex was correlated with the scores in the Internet Addiction Test (Young, 1998a), measuring symptom severity.

In addition to gray matter, abnormalities in patients with Internet addiction, functional connectivity shows some changes. These connectivity alterations fit well, at least partially, with the structural changes. For example, Lin et al. (2012) found lower fractional anisotropy in large parts of the brain of individuals with Internet addiction including the orbitofrontal cortex. Further changes in fractional anisotropy were found in the white matter of the parahippocampal gyrus (Yuan et al., 2011), bilateral frontal lobe white matter (Weng et al., 2013), and both internal (Yuan et al., 2011) and external capsule (Weng et al., 2013). Also, reductions in functional connectivity (using resting-state fMRI) were found in the right inferior temporal gyrus, bilateral parietal cortex and posterior cingulate cortex, and connectivity between the posterior cingulate gyrus and right precuneus, parts of the thalamus, caudate, ventral striatum, supplementary motor area, and lingual gyrus was correlated with severity of the problematic behavior in Internet gamers (Ding et al., 2013). However, in another study by Dong et al. (2012a), using diffusion tensor imaging, increased connectivity between several brain areas in patients with Internet addiction for games were reported, including thalamus and posterior cingulate cortex. The fractional anisotropy in the internal capsule was also correlated with the duration of the addictive behavior (Yuan et al., 2011). Reduced connectivity was also found between prefrontal and subcortical as well as parietal and subcortical structures, in particular with the putamen (Hong et al., 2013b). There are some references for changes in regional homogeneity with both increased homogeneity in middle frontal and parietal gyri (and further regions of brainstem and cerebellum) and decreased homogeneity in certain temporal, parietal, and occipital areas in individuals with Internet gaming addiction (Dong et al., 2012c).

Another line of arguments for the involvement of cue-reactivity and craving, which might interfere with cognitive control over the Internet use, comes from studies investigating the dopamine system in patients with Internet addiction. Although these studies are preliminary given, for example, very small samples sizes and their results have to be treated with caution: there are some first hints that the dopamine system is altered in Internet addicted individuals. One example is a SPECT study (Hou et al., 2012) showing that the level of dopamine transporter expression in the striatum is decreased in individuals with Internet addiction. This finding is consistent with the results of a study with raclopride PET (Kim et al., 2011), in which a reduced availability of dopamine 2 receptors in the striatum was found in Internet addicts (see also the review by Jovic and Ðinđić, 2011).

Although this is speculative so far, changes in dopaminergic functioning may – at least partly – explain the loss of control over the Internet use in individuals with Internet addiction. This assumption fits well with recent models on the development of addictive behavior in general, as suggested by Robinson and Berridge (2008), as already mentioned. Given that the parts of the prefrontal cortex involved in cognitive control, in particular the dorsolateral prefrontal cortex (see Figure ​Figure2)2) receives dopaminergic projections from the basal ganglia and the nucleus accumbens, functional changes in these structures can also reduce the integrity of executive control (Cools and D’Esposito, 2011). Given that the basal ganglia are inter-connected with each other and the thalamus by projections that include other neurotransmitter systems, in particular glutamate and GABA, changes in the dopaminergic system may also cause more global dysfunctions of the fronto-striatal loops, including both the cognitive and the limbic loop (Alexander and Crutcher, 1990). We have commented on the link between fronto-striatal loops and executive control functions in Section “Neuropsychological Correlates of Internet Addiction.” Considering the preliminary results on dopaminergic alterations in Internet addicted individuals, we argue that changes in this and other basal ganglia neurotransmitter systems are related to the loss of control over the Internet use by functional changes of prefrontal integrity.

Beyond the investigations of the dopamine system, further studies have addressed resting-state brain functionality in patients with Internet addiction. Using 18-FDG-PET, measuring glucose metabolism in the brain, Park et al. (2010) demonstrated that excessive Internet gamers had increased glucose metabolism in the region of the (right) orbitofrontal cortex, and also in parts of the basal ganglia (left caudate, insula), while posterior regions (e.g., parietal and occipital areas) showed decreased metabolism.

In summary, there are some first evidences for structural and resting-state brain changes in individuals with Internet addiction. These include both gray and white matter changes in the prefrontal brain areas and additional brain regions. There are also first evidences for changes in the dopaminergic system, which might be related to reinforcement processing and craving. Given that most studies were done with rather small samples, with one exception only (Kühn et al., 2011), and no consistent or systematic differentiation between different types of Internet addiction and between adolescent versus adult patients, the results must be treated with caution.

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