Functional magnetic resonance imaging of internet addiction in young adults

Abstract

AIM: To report the results of functional magnetic resonance imaging (fMRI) studies pertaining internet addiction disorder (IAD) in young adults.

METHODS: We conducted a systematic review on PubMed, focusing our attention on fMRI studies involving adult IAD patients, free from any comorbid psychiatric condition. The following search words were used, both alone and in combination: fMRI, internet addiction, internet dependence, functional neuroimaging. The search was conducted on April 20^th, 2015 and yielded 58 records. Inclusion criteria were the following: Articles written in English, patients’ age ≥ 18 years, patients affected by IAD, studies providing fMRI results during resting state or cognitive/emotional paradigms. Structural MRI studies, functional imaging techniques other than fMRI, studies involving adolescents, patients with comorbid psychiatric, neurological or medical conditions were excluded. By reading titles and abstracts, we excluded 30 records. By reading the full texts of the 28 remaining articles, we identified 18 papers meeting our inclusion criteria and therefore included in the qualitative synthesis.

RESULTS: We found 18 studies fulfilling our inclusion criteria, 17 of them conducted in Asia, and including a total number of 666 tested subjects. The included studies reported data acquired during resting state or different paradigms, such as cue-reactivity, guessing or cognitive control tasks. The enrolled patients were usually males (95.4%) and very young (21-25 years). The most represented IAD subtype, reported in more than 85% of patients, was the internet gaming disorder, or videogame addiction. In the resting state studies, the more relevant abnormalities were localized in the superior temporal gyrus, limbic, medial frontal and parietal regions. When analyzing the task related fmri studies, we found that less than half of the papers reported behavioral differences between patients and normal controls, but all of them found significant differences in cortical and subcortical brain regions involved in cognitive control and reward processing: Orbitofrontal cortex, insula, anterior and posterior cingulate cortex, temporal and parietal regions, brain stem and caudate nucleus.

CONCLUSION: IAD may seriously affect young adults’ brain functions. It needs to be studied more in depth to provide a clear diagnosis and an adequate treatment.

Key Words: Internet addiction; Pathologic internet use; Functional magnetic resonance imaging; Internet gaming disorder; Functional neuroimaging

Core tip: We systematically reviewed the functional magnetic resonance imaging studies on adults affected by internet addiction disorder (IAD), without any other psychiatric condition. We found 18 studies, mostly conducted in East Asia and enrolling young males with internet gaming disorder. Internet addicts showed functional alterations in regions involved in cognitive control and reward/punishment sensitivity (orbitofrontal cortex, anterior and posterior cingulate, insula, dorsolateral prefrontal cortex, temporoparietal regions, brain stem and caudate nucleus) that are similar to those observed in substance use disorder. IAD is a disabling condition needing careful consideration due to its severe impact on young people’s brain functioning.

INTRODUCTION

Internet addiction disorder (IAD), also called pathologic/problematic internet use (PIU), may be defined as an impulse control disorder characterized by an uncontrolled Internet use, associated with a significant functional impairment or clinical distress[1]. IAD is not classified as a mental disorder in the Diagnostic and Statistical Manual of Mental Disorders-fifth edition, but a subtype of IAD, the internet gaming disorder (IGD) (also called videogame addiction), is included in the section 3 as a topic deserving future studies[2]. A recent meta-analysis on IAD[3] involving more than 89000 participants from 31 nations reported a global prevalence estimate of 6%, with the higher prevalence in the Middle East (10.9%) and the lowest prevalence in Northern and Western Europe (2.6%). A higher prevalence of IAD was significantly associated with lower subjective and environmental conditions. A recent study conducted on Indian college students[4] reported 8% of moderate IAD and identified the following variables as risk factors: Male gender, continuous availability online, using the internet more for making new friendships/relationships and less for coursework/assignment. Due to their high computer skill and easy Internet access, young adults are at augmented risk for IAD[5].

Some of the clinical characteristics of IAD are similar to those observed in behavioral or substance misuse disorders (loss of control, craving, withdrawal symptoms), Obsessive Compulsive Disorder, or Bipolar Disorder so the nature of IAD (primary psychiatric disorder or “online variant” of other psychiatric conditions) is still debated[6-9].

Functional imaging techniques increase the possibility to investigate the neural basis of IAD, enhancing the sensitivity and the statistical power of clinical data. Functional magnetic resonance imaging (fMRI), in particular, is a worldwide used non-invasive technique to study the neural underpinnings of psychiatric disorders[10-12]. By means of fMRI, brain signal changes may be analyzed in terms of functional fluctuations with respect to a given “baseline” (activations/deactivations analysis) or in terms of functional connectivity among different brain regions (network analysis). Metabolic activity changes in the brain can be monitored during the execution of paradigms (task related fMRI) or during the spontaneous cerebral activity (resting state fMRI)[13-16].

Aim of the present study was to systematically review the resting state and task related fMRI studies conducted on adult subjects with IAD, looking for reliable biomarkers of this challenging mental condition.

MATERIALS AND METHODS

We searched PubMed to identify fMRI studies investigating IAD in adult subjects. The following search words were used, both alone and in combination: fMRI, Internet addiction, Internet dependence, functional neuroimaging. The search was conducted on April 20^th, 2015 and yielded 58 records.

Inclusion criteria were the following: Articles written in English, patients’ age ≥ 18 years, patients affected by IAD, studies providing fMRI results during resting state or cognitive/emotional paradigms. Structural MRI studies, functional imaging techniques other than fMRI, studies involving adolescents, patients with comorbid psychiatric, neurological or medical conditions were excluded.

By reading titles and abstracts, we excluded 30 records. By reading the full texts of the 28 remaining articles, we identified 18 papers meeting our inclusion criteria and therefore included in the qualitative synthesis (Figure 1).

Figure 1 Flow diagram of the systematic review.

Biostatistics

Statistics were performed by Dr. Gianna Sepede, who has a certificated experience in Biomedical Statistics, Systematic Reviews and Meta-analysis. In the present paper, PRISMA 2009 checklist (http://www.prisma-statement.org/) was used to describe eligibility criteria, conduct the search, select the studies and report the qualitative synthesis results. Statistical methods were therefore adequately described, correct and conducted on homogeneous data. Number of subjects and dropouts were given. When appropriate, confidence limits and significant P values were calculated and reported.

RESULTS

We found 18 papers fulfilling our inclusion criteria, all published from 2009 to 2015[17-35]. The studies were all conducted in the Asian Continent (China, South Korea, Taiwan), with the only exception of the paper published by Lorenz et al[23], which was conducted in Germany.

In total, 666 subjects were tested by the 18 studies included in the qualitative synthesis: 347 patients with IAD (IADp), 304 normal comparisons (NC) and 15 subjects with Alcohol Use Disorder (AUDp) The large majority of IADp were male (n = 331, 95.4%) and very young (mean age ranged from 21 to 25 year). The number of patients involved in each study ranged from 8 to 74. For what regards the subtypes of IAD, 15 out of 18 studies focused on IGD[19-24,26-34], so more than 85% of all the IADp (n = 297) were IGD patients (IGDp). Different diagnostic criteria were used to assess IAD, such as Beard’s Diagnostic criteria for Internet addiction[35], Ko’s diagnostic criteria of Internet addiction for college students[36], Chinese Internet addiction test (C-IAT)[37] and Grüsser and Thalemann’s computer game addiction criteria[38].

The most used questionnaire to assess the severity of IAD was the Young’s IAT[1], with different cut-off (usually > 80, in a few studies > 50). To diagnose IGD, online gaming was also required to be the principal Internet activity (more than 80% of the time spent online or more than 30 h/wk).

In order to exclude subjects with comorbid psychiatric conditions or substance use disorders, structured interviews and psychometric scales to address depression, anxiety, impulsivity, substance addiction were usually provided.

MRI data were acquired with a 3 T scanner in 17 studies, and with a 1.5 T scanner in one study[19]. In 4 articles, only resting state fMRI was recorded, whereas 13 articles reported task related fMRI data, and one paper acquired both resting state and task related functional activations[31]. Seventeen studies were transversal observational reports, whereas the paper by Han et al[19] was a 6-wk longitudinal study.

The participants in the 18 selected studies were all free of any psychopharmacological treatment at the moment of the scanning (and at study enter for the above mentioned longitudinal study).

Resting state fMRI studies on IAD

A total number of five studies were selected[18,21,31,32,34]. The characteristic of the groups and the results of the studies are reported in Table 1. Right-handedness was an inclusion criterion in 4 studies[18,21,31,34], as well as male gender[21,31,32,34]. A total number of 298 subjects (Males n = 280, 94%), all medication free, were involved: 159 IADp (140 IGDp), 124 NC and 15 AUDp. Patients were usually very young (mean age ranging from 21 to 24 years).

Table 1 Resting state functional magnetic resonance imaging studies in internet addiction disorder.

Ref.	Design and aims	Participants	Diagnostic criteria and evaluation scales	fMRI methods	fMRI results
Liu et al[18]	Resting state fMRI study	n = 38, age range 18-25 yr	IAD: Beard's DQIA "5 +	Scanner: 3 T	Between group significant effects:
	Aim: To analyze encephalic	Medication free 100%	1 criteria" plus any one	FMRI Scan duration:	ReHo
	functional characteristic of	Right-handed 100%	of: ≥ 6 h/d for 3 mo	9 min	IAD > NC in: Cerebellum,
	IAD under resting state	Normal neurological examination 100%	Decline in academic performance	Software used: SPM2	brainstem, R CG, bilateral PH, R FL, L SFG, L precuneus, R PoCG,
		No comorbid psychiatric disorders	Unable to maintain normal school learning	ReHo measured by means of KCC	R MOG, R ITG, L STG, MTG
		Groups: IGA n = 19		Signal analyzed:
		Mean age: 21.0 ± 1.3 yr		BOLD
		Males n = 11 (57.9%)		Both whole brain and
		NC n = 19 (50%)		ROI based analysis
		Mean age: 20.0 ± 1.8 yr
		Males n = 11 (57.9%)
Dong et al[21]	Resting state fMRI study	n = 29, age 24.2 ± 3.8 yr	IGD: YIAT ≥ 80	Scanner: 3 T	Between group significant effects:
	Aim: To investigate the	Males 100%	> 80% of the online time	FMRI Scan duration:	ReHo
	effects of long-time online	Medication free 100%	was spent playing	9 min	IGA > NC in: Bilateral brainstem,
	game playing on visual and	Right-handed 100%	videogames	Software used:	bilateral IPL, L posterior
	auditory brain regions	No nicotine, cocaine or marijuana use	BDI < 5; MINI: No Axis I	DPARSF; ReHo measured by	cerebellum, L MiFG; IGA < NC in: L STG, L ITG, L OL,
		Groups: IGD n = 15; Age 24.2 ± 3.5 yr	psychiatric disorders	means of KCC; Signal analyzed:	L PL
		NC n = 14; Age 24.6 ± 3.8 yr		BOLD; Both whole brain and
				ROI based analysis
				Seed based connectivity analysis
1Dong et al[31]	Resting-state and task	n = 71	IGD: Young's IAT ≥ 50	Scanner: 3 T	Between group significant effects:
	related fMRI	Age 22.35	> 80% of the online time	Rs fMRI Scan	RsFc
	Aim: To examine the Fc of	Males 100%	was spent playing	duration: 7 min	IGD < NC in: Total ECN and L
	ECN during both resting	Medication free 100%	videogames	Software used: REST,	ECN
	state and Stroop task	Right-handed 100%	BDI < 5	DPARSF, SPM8, FSL
	performing	No DSM 5 psychiatric disorders	MINI: No Axis I psychiatric disorders	Signal analyzed: BOLD
		Groups: IGD n = 35		Whole brain analysis
		Age 22.2 ± 3.8 yr
		NC n = 36
		Age 22.8 ± 2.4 yr
Kim et al[32]	Resting state fMRI study	n = 45	For all participants:	Scanner: 3 T	Between group significant effects:
	Aim: To compare the brain	Males 100%	WAIS III ≥ 80	Rs fMRI Scan	ReHo
	functioning of IGD, AUD,	Medication free 100%	For IGD: YIAT ≥ 70	duration: 8 min	(1) IGD vs NC
	and NC during resting state	Groups: IGD n = 16	> 4.5 h/d were spent	Software used:	IGD > NC in L PCC
		Age 21.6 ± 5.9 yr	playing online	DPARSF, SPM8,	IGD < NC in R STG
		AUD n = 14	For AUD: SCID criteria	REST	(2) IGD vs AUD
		Age 28.6 ± 5.9 yr	AUDIT-K	ReHo measured by	IGD < NC in R STG
		NC n = 15	< 2 h/d were spent	means of KCC	(3) AUD vs NC
		Age 25.4 ± 5.9 yr	online	Signal analyzed:	AUD > NC in R PCC, R insula, L
		IGD were significantly	Other scales	BOLD	MTG
		younger than AUD	administered to all	Whole brain analysis	AUD < NC in R ACC
		(P < 0.01)	subjects:
			BDI: IGD and AUD > NC (P < 0.01)
			BAI: AUD > NC (P < 0.01)
			BIS-11: IGD and AUD > NC (P < 0.01)
Zhang et al[34]	Resting state fMRI study	n = 115	IGD: CIAS ≥ 67	Scanner: 3 T	Between group significant effects:
	fMRI in young adults with Internet gaming disorder	Males 100%; Medication free 100%	Internet gaming > 14 h/wk for 1 yr	Rs fMRI Scan duration: 7 min	RsFC; L anterior insula
	using rsFC	Right-handed 100%; Groups: IGD n = 74	Playing as the principal online activity	Software used: DPABI, REST, SPM8	IGD > NC in R putamen, R angular gyrus, IFG
	Aim: To study resting-state	age 22.3 ± 2 yr; n = 57 alcohol drinkers	NC: CIAS < 60	Signal analyzed: BOLD	R anterior insula; IGD > NC in ACC, middle CG,
	functional connectivity of	n = 8 cigarette smokers	internet gaming <	Seed based	L angular gyrus, L precuneus,
	the insula in IGD	NC n = 41;	2 h/wk	connectivity analysis	Bilateral SFG and STG
		age 23.0 ± 2.1 yr	Other scales: FTND		L posterior insula
		n = 29 alcohol drinkers	BDI: IGD > NC		IGD > NC in bilateral PoCG, L
		Cigarette use and frequency of alcohol use were higher in IGD with respect to NC (P < 0.05 and P < 0.01)	(P < 0.001); BAI: IGD > NC (P < 0.01)		precentral gyrus, R SMA, STG; R posterior insula; IGD > NC in bilateral STG
		No comorbid psychiatric disorders

¹Only resting state results are showed. AUD: Alcohol use disorder; IAD: Internet addiction disorder; IGD: Internet gaming disorder; NC: Normal controls; AUDIT-K: Korean version of alcohol use disorder identification test; BAI: Beck anxiety inventory; BDI: Beck depression inventory; BIS-11: Barratt impulsiveness scale-version 11; CIAS: Chen internet addiction scale; DQIA: Beard’s diagnostic questionnaire for internet addiction; FTND: Fagerstrom test for nicotine dependence; MINI: Mini international neuropsychiatric interview; SCID: Structured clinical interview for DSM-IV; YIAT: Young’s internet addiction test; WAIS: Wechsler adult intelligence scale; DPARSF: Data processing assistant for resting-state fMRI; KCC: Kendall’s coefficient of concordance; ReHo: Regional homogeneity; RsFC: Resting state functional connectivity; SPM: Statistical parametric mapping; R: Right; L: Left; ACC: Anterior cingulate cortex; CG: Cingulate gyrus; ECN: Executive control network; FL: Frontal lobe; IFG: Inferior frontal gyrus; IPL: Inferior parietal lobule; ITG: Inferior temporal gyrus; MiFG: Middle frontal gyrus; MOG: Middle occipital gyrus; MTG: Middle temporal gyrus; OL: Occipital lobe; PCC: Posterior cingulate cortex; PH: Parahippocampus; PL: Parietal lobe; PoCG: Postcentral gyrus; SFG: Superior frontal gyrus; SMA: Supplementary motor area; STG: Superior temporal gyrus.

In all the five selected studies, fMRI images were acquired using a 3 T scanner and scan duration ranged from 7 to 9 min. Resting state functional connectivity (RsFc) and/or Regional Homogeneity (ReHo) were calculated to assess between group differences. As a result, all the selected studies identified significant differences between patients and controls.

Liu et al[18], in their research on 19 IAD patients, reported an increased synchronization among frontal areas, cingulate gyrus, temporal and occipital regions, cerebellum and brain stem, with respect to matched normal comparisons. So the authors suggested an altered functional connectivity in regions belonging to the reward system of the brain. All the four papers focused on IGD patients[21,31,32,34] reported significant between group effects. Dong et al[21] observed that, when compared to controls, IGD patients showed an enhanced ReHo in sensorimotor coordination areas (brainstem, cerebellum, bilateral inferior parietal lobule, and left middle frontal gyrus), and a reduced ReHO in left-sided visual and auditory cortex. In a larger sample of IGD patients, Dong and colleagues[31] observed a reduced functional connectivity in areas belonging to the Executive Control Network, especially in the left hemisphere: Ventromedial prefrontal cortex, dorsolateral prefrontal cortex and parietal cortex.

In a recent study, Kim et al[32] compared the resting state brain functioning of IGD patients not only with healthy subjects, but also with a group of AUD patients, looking for similarities and differences between these two “addictive conditions”. As a result, they found that both IGD and AUD shared an augmented ReHo in posterior cingulate cortex with respect to healthy controls, whereas a reduced ReHo in the right superior temporal gyrus was observed in the IGD patients only. The authors also reported a negative correlation between the left inferior temporal cortex and the level of impulsivity.

To assess the role of the insular cortex in IGD, Zhang et al[34] conducted a seed-based resting state connectivity study in 74 patients with IGD and compared them with 41 normal controls. IGD patients exhibited enhanced rsFC between the anterior insula and anterior cingulate cortex, precuneus, angular gyrus and basal ganglia (all areas involved in cognitive control, salience, attention and craving). When analyzing the posterior part of the insula, they found an augmented rsFC in areas playing a key role in sensory-motor integration, such as post central and precentral gyrus, supplementary motor area and superior temporal gyrus. Moreover, they observed a positive correlation between the insula-superior temporal gyrus connectivity and the level of IGD severity.

Summarizing the rsfMRI studies, the more relevant abnormalities observed in IGD were localized in the superior temporal gyrus. Other important alterations were detected in limbic areas, medial frontal regions (anterior cingulate cortex, supplementary motor area) and parietal regions. Results in not gaming IAD were limited due to the small number of patients involved (n = 19) and reported altered functioning in reward-related brain regions (frontal, parietal, temporal regions, cingulated gyrus, brain stem and cerebellum).

Task-related fMRI studies on IAD

We found 14 studies reporting task-related neural correlates of IAD[17,19,20,22-31,33]. The characteristic of the groups and the results of the studies are reported in Table 2. Right-handedness was an inclusion criterion in all but two studies[19,23]. Only male participants were included in 13 studies, whereas a mixed gender sample was enrolled by Liu et al[33] (2015).

Table 2 Task related functional magnetic resonance imaging studies on internet addiction disorder.

Ref.	Design and aims	Participants	Diagnostic criteria and evaluation scales	Task and behavioral results	fMRI methods	fMRI results
Ko et al[17]	Task related fMRI study	n = 20; Males 100%	DCIA-C	Task used: Cue-reactivity paradigm.	Scanner: 3 T	Between group significant effects: IGD > NC in: R OFC, R basal ganglia (caudatum and accumbens), bilateral ACC, bilateral MFG, R DLPFC
	Aim: To identify the neural substrates of IGD by means of a cue-reactivity paradigm	Medication free 100%	MINI	Task design: Videogame viewing	fMRI scan duration: 4.8 min
		Right-handed 100%	CIAS	Behavioral results: Gaming craving: IGD > NC	Acquisition method: Block design
		Normal neurological examination 100%			Software used: SPM2
		No comorbid psychiatric disorders or substance use	AUDIT		Signal analyzed: BOLD
		Groups:	FTND		Whole brain and ROI based analysis
		IGD n = 10	Gaming craving scale
		Mean age: 22 ± 1.5 yr	For IGD: Addiction to World of Warcraft
		NC n = 10	Playing > 30 h/wk
		Mean age: 22.7 ± 1.3 yr
Han et al[19]	Six-week open label pharmacological study with task related fMRI acquisition	n = 19; Males 100%	SCID	Task used: Cue-reactivity paradigm.	Scanner: 1.5 T	Between group significant effects:
	Aim: To evaluate the efficacy of bupropion SR in reducing game craving and influencing brain activity in IGD	Medication free (at study enter) 100%	BDI < 17	Task design: Videogame viewing	fMRI scan duration: 7.5 min	At baseline:
		Normal neurological examination 100%	7 point Gaming Craving VAS	Behavioral results: Gaming craving: IGD > NC	Acquisition method: Block design	(1) IGD > NC in: L occipital lobe, cuneus, L DLPFC, L PH
		No comorbid psychiatric disorders or substance use disorders	For IGD: YIAT > 50	Bupropion effects in the IGD group: Significant decreases of: Craving (23.6%, P = 0.04)	Software used: Brain voyager	After 6 wk of Bupropion treatment on IGD:
		Groups: IGD n = 11	Playing > 4 h/d and 30 h/wk	Playing game time (35.4%, P = 0.01)	Signal analyzed: BOLD	(2) Significant decreased activation in L DLPFC
		Mean age: 21.5 ± 5.6 yr	Addiction to star craft	YIAT scores (15.4%, P = 0.01)	Acquisition time:
		Study treatment: Bupropion SR for 6 wk			(1) At study enter (baseline);
		NC n = 8			(2) After 6 wk of Bupropion treatment
		Mean age: 20.3 ± 4.1 yr			Whole brain analysis
Dong et al[20]	Task related fMRI study	n = 27; Males 100%	MINI	Task used: Guessing task	Scanner: 3 T	Between group significant effects:
	Aim: To investigate reward and punishment processing in IGD during a guessing task	Medication free 100%	For IGD: YIAT > 80	Task design: Two-choices gain or loss guessing task	fMRI scan duration: 16.3 min	In WIN condition: IGD > NC in L OFC (BA 11)
		Right-handed 100%	C-IAT criteria	Behavioral results: No between group significant differences in accuracy and reaction times	Acquisition method: Block design	In LOSS condition: NC > IGD in ACC
		Normal neurological examination 100%	Spending most of their time playing online Internet games		Software used: SPM5
		No comorbid psychiatric disorders or substance use disorders	For NC: YIAT < 20		Signal analyzed: BOLD
		Groups: IGD n = 14			Whole brain analysis
		Mean age: 23.4 ± 3.3 yr
		NC n = 13
		Mean age: 24.1 ± 3.2 yr
Dong et al[22]	Task related fMRI study	n = 24; Males 100%	For all participants: BDI < 13	Task used: Cognitive control task	Scanner: 3 T	Between group significant effects:
	Aim: To identify the neural correlates of response inhibition in individuals with and without IGD	Medication free 100%	For IGD: YIAT > 80	Task design: Three-choices color-word Stroop task	fMRI scan duration: 12 min	During Stroop effect: IGD > HC in: ACC, PCC, L insula, MiFG, MFG, L thalamus, R IFG, R SFG
		Right-handed 100%	C-IAT criteria	Behavioral results: No between group significant differences	Acquisition method: Event-related design
		No comorbid psychiatric disorders or substance use disorders	Spending most of their time playing online Internet games		Software used: SPM5
		Non smokers 100%	YIAT < 20		Signal analyzed: BOLD
		Groups: IGD n = 12			Whole brain analysis
		Mean age: 23.6 ± 3.5 yr
		NC n = 12
		Mean age: 24.2 ± 3.1 yr
Lorenz et al[23]	Task related fMRI study	n = 17; Males 100%	World of warcraft addiction inventory	Task used: Attentional bias/cue reactivity task	Scanner: 3 T	Between group significant effects
	Aim: To assess neural correlates of attentional bias and cue reactivity in IGD	Groups: IGD n = 8	CSVK	Task design: Two-choice dot probe paradigm during SP and LP trials	fMRI scan duration: 30 min	During SP trials
		Mean age: 25 ± 7.4 yr	Vocabulary test (WST-IQ)	Stimulus class:	Acquisition method: Block design	IGD > NC in bilateral ACC, R MPFC, L OFC, L PH, MTG, precuneus, cerebellum, R amygdala
		NC n = 9	Test of attention	(1) IAPS based emotional images (neutral and positive valences)	Software used: SPM8b	During LP trials IGD > NC in: R IFG, R Hippocampus, bilateral lingual gyrus and R calcarine gyrus
		Mean age: 24.8 ± 6.9 yr	Social interaction anxiety scale	(2) Computer generated stimuli (neutral images and World of Warcraft based images)	Signal analyzed: BOLD	PPI results: IGD > NC in connectivity between R IFG and:
			STAI	Behavioral results:	Whole brain analysis	IFG, orbital gyrus, MFG, MTG, MOG, STG, ITG, Angular gyrus, precuneus, basal ganglia
			BDI	In SP trials: IGD: RT congruent < RT incongruent	Connectivity analysis: Post hoc PPI, using R IFG as seed region
			BIS 11
			Iowa Gambling test
			For IGD: ≥ 3 Grüsser and Thalemann’s criteria for computer game addiction
Dong et al[24]	Task related fMRI study	n = 30; Males 100%	MINI	Task used: Cognitive control task	Scanner: 3 T	Between group significant effects
	Aim: To investigate error-monitoring ability in IGD	Medication free 100%	For IGD	Task design: Three-choices color-word Stroop task	fMRI scan duration: 12 min	During correct responses:
		Right-handed 100%	YIAT > 80	Focus: Error monitoring	Acquisition method: Event-related design	IGD < NC in OFC and ACC
		Non smokers 100%	Spending > 80% of their time online playing games	Behavioral results: No significant between	Software used: SPM8	During incorrect responses: IGD > NC in ACC
		No comorbid psychiatric disorders or substance use disorders	For NC: YIAT < 30	group effects	Signal analyzed: BOLD
		Groups: IGD n = 15			Whole brain analysis
		Mean age: 23.8 ± 3.7 yr
		NC n = 15
		Mean age: 24.1 ± 3.3 yr
Dong et al[25]	Task related fMRI study	n = 31; Males 100%	MINI	Task used: Guessing task	Scanner: 3 T	Between group significant effects
	Aim: To investigate brain correlates of decision-making in IAD	Medication free 100%	BDI < 5	Task design: Two-choices gain or loss guessing task	fMRI scan duration: 21 min	In WIN condition: IAD > NC in: ACC, insula and IFG
		Right-handed 100%	For IAD: YIAT > 80	Behavioral results:	Acquisition method: Block design	IAD < NC in: PCC and caudatum
		No comorbid psychiatric disorders or substance use disorders	For NC: YIAT < 30	In LOSS condition: RT	Software used: SPM5	In LOSS condition: IAD > NC in: Inferior CG
		Groups: IAD n = 16		IAD > NC	Signal analyzed: BOLD	IAD < NC in: PCC
		Mean age 21.4 ± 3.1 yr			Whole brain analysis
		NC n = 15
		Mean age: 22.1 ± 3.6 yr
Dong et al[26]	Task related fMRI study	n = 31; Males 100%	MINI	Task used: Guessing task	Scanner: 3 T	Between group significant effects
	Aim: To investigate reward/punishment sensitivities in IGD during a guessing task	Medication free 100%	BDI < 5	Task design: Two-choices gain or loss guessing task	fMRI scan duration: 21 min	In WIN condition: IGD > NC in L SFG
		Right-handed 100%	For IGD: YIAT > 80	No behavioral response was required	Acquisition method: Block design	In LOSS condition: IGD > NC in L SFG
		No comorbid psychiatric disorders or substance use disorders	Spending > 80% of their time online playing games	Post scanning self-report questionnaire	Software used: SPM5	IGD < NC in bilateral PCC
		Groups: IGD n = 16	For NC: YIAT < 30	(1) On subjective experiences	Signal analyzed: BOLD	In WIN-LOSS contrast condition
		Mean age 21.4 ± 3.1 yr		During LOSS condition:	Whole brain analysis	IGD > NC in L SFG
		NC n = 15		IGD < NC in reporting negative emotions
		Mean age: 22.1 ± 3.6 yr		(2) On craving for win:
				IGD > NC in both WIN and LOSS conditions
Dong et al[27]	Task related fMRI study	n = 30; Males 100%	MINI	Task used: Cognitive control task	Scanner: 3 T	Between group significant effects
	Aim: To explore cognitive flexibility in IGD during a color-word Stroop task	Medication free 100%	BDI < 5	Task design: Three-choices color-word Stroop task	fMRI scan duration: 16 min	Task switching
		Right-handed 100%	For IGD: YIAT > 80	Focus: Cognitive flexibility during task switching (from easy to difficult condition and viceversa)	Acquisition method: Event-related design	(1) From difficult to easy condition
		No comorbid psychiatric disorders or substance use disorders	Spending > 80% of their time online playing games	Behavioral results: No significant between group differences	Software used: SPM5	IGD > NC in: Bilateral insula, R STG
		Groups: IGD n = 15	For NC: YIAT < 30		Signal analyzed: BOLD	(2) From easy to difficult condition: IGD > NC in: Bilateral precuneus, L STG, L angular gyrus
		Mean age 21.2 ± 3.2 yr			Whole brain analysis
		NC n = 15
		Mean age: 22.1 ± 3.6 yr
Ko et al[28]	Task related fMRI study	n = 49; Males 100%	MINI	Task used: Cognitive control task	Scanner: 3 T	Between group significant effects
	Aim: To evaluate impulsivity and brain correlates of response inhibition and error processing in IGD	Medication free 100%	CIAS	Task design: Go/No-go Task	fMRI scan duration: 15.5 min	During response inhibition
		Right-handed 100%	BIS-11	Behavioral results: No significant between group differences	Acquisition method: event-related design	IGD > NC in bilateral caudate and L OFG (BA 47)
		No comorbid psychiatric disorders or substance use disorders	Dickman’s impulsivity scale		Software used: SPM5	During error processing
		Groups: IGD n = 26	For IGD: Fulfilling DCIA criteria		Signal analyzed: BOLD	IGD < NC in R insula
		Mean age 24.6 ± 3.2	Addiction to online gaming		Whole brain and ROI based analysis
		NC n = 23
		Mean age: 24.4 ± 2.1 yr
Liu et al[29]	Task related fMRI study	n = 22; Males 100%	DCIA-C	Task used: Cognitive control task	Scanner: 3 T	Between group significant effects
	Aim: To investigate brain correlates of response inhibition under gaming cue distraction in IGD	Medication free 100%	MINI	Task design: Modified Go/no-go Task with gaming cue distracters	fMRI scan duration: 8.5 min	During no gaming distracting condition
		Right-handed 100%	CIAS	Behavioral results: During gaming distracting condition	Acquisition method: Block design	IGD > NC in R SPL
		No comorbid psychiatric disorders or substance use disorders	FTND < 5	Commission errors IGD > NC	Software used: SPM5	During gaming distracting condition
		Groups: IGD n = 11			Signal analyzed: BOLD	NC > IGD in R DLPFC, R SPL and cerebellum
		Mean age 23.4 ± 2.3 yr			Whole brain and ROI based analysis	ROI based analysis results
		NC n = 11				In IGD
		Mean age: 22.4 ± 1.7 yr				R DLPFC and R SPL activations were positively associated to commission errors during gaming distracting condition
Chen et al[30]	Task related fMRI study	n = 30; Males 100%	MINI	Task used: Cognitive control task	Scanner: 3 T	Between group significant effects
	Aim: To evaluate neural correlates of response inhibition among subjects with IGD	Medication free 100%	CIAS	Task design: Go/no-go Task	fMRI scan duration: 6 min	During response inhibition
		Right-handed 100%		Behavioral results: No significant between group differences	Acquisition method: Block design	NC > IGD in R SMA/pre-SMA
		No comorbid psychiatric disorders or substance use disorders	BIS-11		Software used: SPM5
		Groups: IGD n = 15	For IGD: Fulfilling DCIA criteria		Signal analyzed: BOLD
		Mean age 24.7 ± 3.1 yr	Addiction to World of Warcraft		ROI based analysis
		NC n = 15
		Mean age: 24.5 ± 2.8 yr
1Dong et al[31]	Resting-state and task related fMRI	All participants: n = 71 age 22.35	IGD: YIAT ≥ 50	Task used: Cognitive control task	Scanner: 3 T	Between group significant effects
	Aim: To examine the Fc of ECN during both resting state and Stroop task performing	Participants who performed the fMRI Stroop task: n = 35	> 80% of the online time was spent playing videogames	Task design: Three-choices color-word Stroop task	fMRI scan duration: 15 min	During incongruent trials: IGD > NC in bilateral SFG
		Males 100%	BDI < 5	Behavioral results: No significant between group differences	Acquisition method: Event-related design	IGD < NC in L
		Medication free 100%	MINI: No Axis I psychiatric disorders		Software used: SPM8	DLPFC, ACC and left OFC
		Right-handed 100%	IAD		Signal analyzed: BOLD
		No DSM 5 psychiatric disorders			Whole brain and ROI based analysis
		Groups performing fMRI Stroop task:
		IGD n = 16
		NC n = 15
Liu et al[33]	Task related fMRI study	n = 38; Males 58%	HAM-A	Task used: Cue-reactivity paradigm.	Scanner: 3 T	Between group significant effects
	Aim: To investigate brain function in IGD individuals during a cue-reactivity paradigm	Medication free 100%	BDI	Task design: Videogame viewing	fMRI scan duration: 7.5 min	IGD > NC in: R SPL, R precuneus, R insula, R CG, R STG, L brain stem
		Right-handed 100%	For IGD: Beard's DQIA "5 + 1 criteria" plus any one of: ≥ 6 h/d for 3 mo; Decline in academic performance; Unable to maintain normal school learning	No behavioral response was required	Acquisition method: Block design
		No comorbid psychiatric disorders or substance use disorders			Software used: Brain Voyager
		Groups: IGD n = 19			Signal analyzed: BOLD
		Males n = 11 (58%)			Whole brain analysis
		Mean age 21.4 ± 1.0 yr
		NC n = 19
		Mean age: 20.1 ± 1.1 yr
		Males n = 11 (58%)

¹Only task related fMRI results are showed. IAD: Internet addiction disorder; IGD: Internet gaming disorder; NC: Normal controls; AUDIT: Alcohol use disorder identification test; BDI: Beck depression inventory; BIS-11: Barratt impulsiveness scale-version 11; CIAS: Chen internet addiction scale; C-IAT: Chinese internet addiction test; CSVK: Pathological computer gaming scale; DCIA-C: Diagnostic criteria of Internet addiction for college students; FTND: Fagerstrom test for nicotine dependence; HAM-A: Hamilton anxiety scale; IAPS: International affective picture system; MINI: Mini international neuropsychiatric interview; RT: reaction times; SCID: Structured clinical interview for DSM-IV; VAS: Visual analogue scale; YIAT: Young’s internet addiction test; R: Right; L: Left; ACC: Anterior cingulate cortex; CG: Cingulate gyrus; DLPFC: Dorsolateral prefrontal cortex; IFG: Inferior frontal gyrus; IPL: Inferior parietal lobule; ITG: Inferior temporal gyrus; MFG: Medial frontal gyrus; MPFC: Medial prefrontal cortex; MiFG: Middle frontal gyrus; MOG: Middle occipital gyrus; MTG: Middle temporal gyrus; OFC: Orbitofrontal cortex; PCC: Posterior cingulate cortex; PH: Parahippocampus; SMA: Supplementary motor area; SFG: Superior frontal gyrus; SPM: Statistical parametric mapping; SPL: Superior parietal lobe; STG: Superior temporal gyrus; SP: Short presentation; LP: Long presentation.

A total number of 368 subjects (males n = 352, 95.6%: Mean age ranging from 21 to 25 years) were involved: 188 IADs (IGDs n = 157) and 180 NC. Participants were all medication free at the moment of the scanning and at study enter for the longitudinal study by Han et al[19]. FMRI images were acquired using a 3 T scanner and scan duration ranged from 5 to 30 min.

The paradigms administered to the participants were: cue-reactivity tasks (three studies)[17,19,33], guessing tasks (three studies)[20,25,26] or cognitive control tasks of different kinds (eight studies)[22-24,27-31]. In more than half of the studies[20,22,24,27,28,30,31,33] no behavioral differences were found between cases and controls, but all of them reported significant group effects in functional activation of several brain regions, especially orbitofrontal gyrus, anterior cingulate cortex, insula, dorsolateral prefrontal cortex, precuneus, posterior cingulate cortex and superior temporal gyrus.

In cue-reactivity paradigms, addicted subjects are exposed to stimuli designed to elicit a craving for substance or behavior: In case of IAD, i.e., viewing images or videos related to videogames or Internet scenarios[17,39,40].

In probabilistic guessing tasks, participants are required to bet on different outcomes (i.e., on cards, dices, colors) and their brain response to win or loss conditions can be analyzed, to evaluate reward and punishment neural systems[41].

In cognitive control tasks, participants have to choice between different conflicting responses. Stimuli can be manipulated to increase difficulty and to measure particular cognitive abilities, such as sustained attention, response inhibition, impulsivity, task switching ability and error processing. Frequently used cognitive control tasks are the Stroop tasks: Participants are required to detect only a salient characteristic of the stimuli, ignoring the others (i.e., color words printed in different colored ink and participants have to ignore the word and name its color)[42]. When the different features of the stimuli are incongruent, the task difficulty increases and affects the performance (Stroop effect)[43]. Another important category of control tasks is the “go no-go paradigm”: Stimuli (i.e., digits, letters, shapes) are presented in a continuous stream and participants perform a binary decision on each stimulus. One of the outcomes requires participants to make a motor response (go), whereas the other requires participants to withhold a response (no-go)[44].

When the study is focused on the influence of emotion or salience on selective attention, dot prob paradigms are frequently used: Participants view neutral or salient stimuli appearing randomly on either side of the screen, then a dot is presented in the location of one former stimulus and participants have to indicate the correct location of the dot, so an attentional bias toward salient stimuli can be detected[45,46].

Cue-reactivity task fMRI studies in IAD

In their study on 10 IGDp addicted to the videogame World of Warcraft (WOW) Ko et al[17] found that IGDp reported a higher gaming urge when passive viewing WOW images with respect to NC. Moreover, a significant higher activation was observed in right orbitofrontal cortex, right basal ganglia (caudatum and accumbens), bilateral anterior cingulate cortex, bilateral medial prefrontal cortex, right dorsolateral prefrontal cortex.

Han et al[19] conducted a six-week open label pharmacological study aiming to evaluate bupropion efficacy in reducing game craving and modulate brain activation in 11 IGDp addicted to the videogame Starcraft. At baseline, all participants were medication free and the authors observed an higher game urging and an augmented activation of left dorsolateral prefrontal cortex, L parahippocampus, left occipital lobe and cuneus in IGDp, with respect to NC during Starcraft cue presentation. After bupropion treatment, a significant decreased activation of left dorsolateral prefrontal cortex was observed in IGDp. Bupropion, being an antidepressant agent modulating dopamine and norepinephrine reuptake, was reported to be efficacious in patients with substance use disorder, with or without comorbid mood disorders[47,48] and in pathological gambling[49]. So the authors hypothesized that bupropion reduced craving in IGD by modulating dorsolateral prefrontal cortex functional activity.

In a recent study using videogame stimuli, Liu et al[33] (2015) enrolled a mixed-gender sample of 19 IGDp (males 58%) and reported a significant dysfunction of the frontal cortex, with increased activation in right-sided temporo-parietal and limbic regions: Superior parietal lobe, insula, cingulate gyrus and superior temporal gyrus.

Guessing task fMRI studies in IAD

To evaluate reward and punishment sensitivity in IGDp, Dong et al[20] simulated a gain/loss situation: Participants had to choice between two covered playing cards and at the end of the fMRI scan session they received a money sum based on their wins and losses. fMRI data analysis revealed that during win condition IGDs showed an higher activation of left orbitofrontal cortex (BA11) with respect to NC, whereas in loss condition the opposite was true for anterior cingulate cortex activation. So the authors concluded that a reduced sensitivity to negative experiences (monetary loss) and an augmented sensitivity to positive events (monetary gain) throughout an altered functioning of orbitofrontal cortex and anterior cingulate cortex could explain why IADp persisted in their habit despite the negative consequences on their everyday life.

Using a similar guessing task, Dong et al[25] found that IGDp were significantly slower than NC when exposed to continuous losses, whereas no behavioral group effects were observed after continuous wins. In terms of brain activations, IGDs showed a reduced activation of posterior cingulate cortex and an increased activation of inferior frontal gyrus during both win and loss conditions, whereas an augmented activation of anterior cingulate cortex and insula was observed during win condition only. These results suggested that decision-making ability was impaired in IGDp, due to a functional inefficiency in the inferior frontal gyrus (higher activation but lower behavioral performance) and a reduced involvement of posterior cingulate cortex and caudate. In the same study sample, with a modified guessing paradigm (a different control condition was added to wins and losses) Dong et al[26] asked the participants to describe their subjective experience after the scan section: IGDp reported higher craving for win in both continuous win and loss conditions and reduced negative emotions during loss conditions. In terms of functional activations, the results were similar, but not identical to those previously reported[25] (probably due to the different control condition): IGDp hyperactivated the left superior frontal gyrus in both wins and losses (but the level of activation was higher during wins) and hypoactivated the posterior cingulate cortex during losses. The authors concluded that superior frontal gyrus in IGDp was insensitive to negative situations and posterior cingulate cortex failed to exert its cognitive control on environmental changes.

Cognitive control task fMRI studies in IAD

In the eight cognitive controls fMRI studies we selected, Stroop tasks were used in four studies[22,24,27,31], go/no-go paradigms in three studies[28-30] and a dot/prob paradigm in one study[23].

Dong et al[22] enrolled 12 male, drug free and no-smokers IGDp and compared them with healthy peers during a three-choices color-word Stroop task. The groups did not differ in terms of behavioral performance, but during Stroop effect (incongruent - congruent stimuli contrast) IGDp showed a significant hyperactivation in anterior cingulate cortex, posterior cingulate cortex, left insula, middle frontal gyrus, medial frontal gyrus, left thalamus, right inferior frontal gyrus, right superior frontal gyrus.

The authors speculated that a greater activation of posterior cingulate cortex in IGD group could indicate a failure to optimize task related attentional resources due to an incomplete disengagement of Default Mode Network. Furthermore, the hyperactivation of the anterior cingulate cortex, insula and prefrontal regions might reflect a cognitive inefficiency of fronto-limbic regions playing a key role in conflict monitoring and “top down” inhibitory control.

In a larger sample, Dong et al[24] administered the same Stroop paradigm with an event-related design and separately analyzed the functional correlates of correct and error responses to stimuli. IGDp and NC performed similarly, but differences emerged in activation patterns: during correct responses IGDp failed to activate anterior cingulate cortex and orbitofrontal cortex, whereas an abnormal activation of anterior cingulate cortex was observed during errors, thus suggesting an impaired error monitoring ability.

More recently, Dong et al[27] analyzed the cognitive flexibility of a group of IGD during a modified version of the Stroop task, adding a monetary reward for correct responses and creating easy and difficult task conditions. The two group did not significantly differ behaviorally. On the other hand, when the task switched from difficult to easy condition IGDp activated the bilateral insula and right superior temporal gyrus more than NC; when the task switched from easy to difficult condition, they hyperactivated the bilateral precuneus, left superior temporal gyrus and left angular gyrus. The authors hypothesized that an higher (and therefore less efficient) activation of limbic and temporoparietal regions playing a key role in inhibitory control and cognitive flexibility was a biomarker of IGD.

The same inhibitory control impairment was found in another study by Dong et al[31]. As a part of a larger resting state connectivity study, a subsample of IGDs performed a Stroop task during an event related fMRI scanning. The authors observed that during incongruent trials, IGDs showed an augmented activation of bilateral superior frontal gyrus and a reduced activation of left dorsolateral prefrontal cortex, left orbitofrontal cortex and anterior cingulate cortex, all regions implicated in executive control.

Ko et al[28] used a go/no-go paradigm with digit stimuli to assess response inhibition and error processing in 26 male IGDp. The authors did not found significant behavioral deficits in IGDp, with respect to NC. On the contrary, when analyzing fMRI data, they reported significant group effects: During successful response inhibition, IGDp activated the bilateral caudate and left orbitofrontal gyrus more than NC; during error committion they failed to activate the right insula. Orbitofrontal gyrus and insula are key regions in modulating inhibitory control and error processing, so the authors suggested that IGDp needed to hyperactivate the orbitofrontal gyrus to successfully perform the task and compensate for the insular hypofunction.

In a recent article, Chen et al[30] used a block design to analyze the functional correlates of cognitive control in IGDp by means of a short go/no-go task. Even though behaviorally intact, IGDp showed a reduced activation of supplementary motor area/pre supplementary motor area, a key region in selecting the appropriate behavior, withholding wrong responses.

Liu et al[29] enrolled a mixed gender sample of IGDp and used a modified go/no-go paradigm, entering gaming picture as background distracters. They observed similar group performance in the original paradigm, but more commission errors during the cue distraction condition in the IGD group. Moreover, during the original task, IGDp hyperactivated the right superior parietal lobe, whereas during the gaming distracting condition they hypoactivated right dorsolateral prefrontal cortex, right superior parietal lobe and cerebellum. A Region of Interest based analysis revealed that in IGDp the rate of commission errors was positively associated with the right dorsolateral prefrontal cortex and right superior parietal lobe activation. The authors therefore suggested that gaming cues significantly affected inhibitory control in IGDp, throughout a failure of dorsolateral prefrontal cortex and superior parietal lobe function.

A cognitive task with emotional and cue distracters was also used by Lorenz et al[23] in a small group of IGDp: They administered a two-choice dot probe paradigm during short (SP) and long presentation (LP) trials in order to elicit attentional bias and cue reactivity, respectively. Stimuli were International Affective Picture System based emotional images (with neutral or positive valence) and computer generated images (neutral pictures or images based on World of Warcraft videogame). IGDp showed a significant attentional bias vs both game related and affective pictures with positive valence. Compared to NC, IGDp showed an abnormal activation of medial prefrontal cortex, anterior cingulate cortex, left orbitofrontal cortex and amygdala during SP trials and of occipital regions, right inferior frontal gyrus and right hippocampus during LP trials. In authors’ opinion, IGDp patients showed a behavioral and neural response similar to that observed in patients with substance use disorder, giving more attention to positive stimuli.

DISCUSSION

In this paper we systematically reviewed the resting state and task related fMRI studies on adult patients with IAD. All but one of the papers included in our qualitative synthesis were conducted in the Asian continent, confirming the great attention given to this potential harmful condition by Eastern governments[50].

The majority of the studies were conducted on young male IGDp (mean age ≤ 25 years), with only a few females and subjects with non-gaming Internet addiction. To avoid any confounding effects of other conditions, we included only studies conducted in subjects free of any comorbid psychiatric or substance use disorder.

Summarizing the literature findings, we highlighted that IGDp differed from healthy comparisons in the functioning of several brain regions involved in reward and executive control/attention processing, even when they were behaviorally intact.

In particular, the most reported cortical dysfunctions were located in orbitofrontal gyrus, anterior cingulate cortex, insula, dorsolateral prefrontal cortex, superior temporal gyrus, inferior frontal gyrus, precuneus and posterior cingulate cortex, whereas for subcortical regions, functional alterations were often found in brainstem and caudate.

Orbitofrontal cortex is involved in decision-making, value-guided behaviors and reward/punishment sensitivity[51,52]: Through its multiple connections with prefrontal, limbic and sensorial regions, it estimates the potential reward of a given stimulus and the appropriate behavior in order to achieve a positive outcome. In patients with substance addiction, an altered functioning of orbitofrontal cortex has been linked to craving and impaired decision-making[53]. Anterior cingulate cortex and insular cortex are both relevant in sustained attention, conflict monitoring, error signaling[54] and processing of unpleasant stimuli[55]. They provide a hub between different cerebral systems, binding emotion to cognition[56,57]. Altered functioning of anterior cingulate cortex and insula have been found in alcohol and drug addiction[58,59].

Dorsolateral prefrontal cortex is a region involved in different cognitive tasks, such as working memory[60] and motor skill learning[61]. An abnormal activation of dorsolateral prefrontal cortex was found in heavy alcohol drinkers with respect to light drinkers during a go/no go task[62] and in pathological gamblers during a cue-reactivity task[63].

Superior temporal gyrus was found activated in the processing of audiovisual stimuli with an emotional content[64] and during task shifting[65]. A reduced activation of superior temporal gyrus was reported in cocaine addicts during a Stroop task[66].

Inferior frontal gyrus has a role in cognitive inhibition[67], target detection[68], decision making[69] and emotional processing[70]. In response to decision-making involving uncertainty and during aversive interoceptive processing, young adults with problematic use of cocaine and amphetamine exhibited a reduced inferior frontal gyrus activation with respect to both former stimulant users and healthy controls[71]. The precuneus has a pivotal role in self-consciousness, visuo-spatial imagery, episodic memory retrieval[72] and target detection during high difficulty tasks[73]. In their work on internet addicts with comorbid nicotine dependence, Ko et al[74] reported an increased activation of precuneus during game cue exposure in acutely ill IGDp, but not in remitted IGD.

Posterior cingulate cortex is considered part of the default mode of the brain[75] and its deactivation during high demanding cognitive tasks is seen as an expression of a reallocation of processing resources[76]. An altered function of posterior cingulate cortex and other components of Default Mode Network was reported in cocaine addicts, especially in those with chronic use[77].

The importance of brainstem in providing ascending and descending pathways between brain and body is well documented[78]. In particular, prefrontal regions and anterior cingulate cortex are deeply connected to the brainstem, so a dysfunction of this subcortical structure leads to attentional and executive impairment[79].

Caudate nucleus is involved in posture, motor control and modulation of approach/attachment behavior[80]. In response to alcohol cues, heavy alcohol users showed higher caudate activation with respect to moderate users[81].

Radiological imaging is a useful research strategy in psychiatric and neurological fields, and may be considered as a form of “molecular pathological epidemiology”[82,83], an interdisciplinary research area aiming to investigate the complex relationships among genes, environment, molecular alterations and long term outcome of clinical disorders[84].

Taken together, the results of our systematic review suggest that young adult with IGD, without any other psychiatric disorder, showed a pattern of functional brain alterations similar to those observed in substance addiction.

Altered functioning of anterior and posterior cingulate cortex, prefrontal and parietal regions, limbic areas and subcortical structures results in impaired response inhibition and abnormal sensitivity to reward and punishment. As observed in substance use disorders, patients with IAD show a reduced cognitive flexibility, more stereotyped responses and inappropriate behavior, with negative consequences on social and working life[85-87].

Limits of the study

The majority of patients enrolled in the reviewed studies were males IGDp, so the conclusions can’t be extended to other subtypes of IAD or to female patients. Focusing our review on adult subjects, we excluded fMRI studies conducted on pediatric and adolescent populations.

COMMENTS

Background

Internet addiction disorder (IAD) is an impulse control disorder characterized by an uncontrolled Internet use, associated with a significant functional impairment or clinical distress. Even if it is not classified as a mental disorder in the current edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), it is a highly debated condition, due to its relevant prevalence among adolescents and young adults.

Research frontiers

Some of the clinical characteristics of IAD, such as loss of control, craving and withdrawal symptoms when patients are not allowed to use the Internet are similar to those observed in behavioral or substance use disorders. Therefore, in the last years several neuroimaging studies have been conducted aiming to investigate the relation between the clinical presentation of IAD and the functioning of cortical and subcortical regions involved in reward processing and cognitive control.

Innovations and breakthroughs

Neuroimaging research is nowadays a promising approach to fill the gap between the molecular basis of psychiatric disorders and their clinical manifestations. The scientific literature on debated diagnosis such as IAD is rapidly growing, so providing an updated review of the last published data may be of interest for the readers. Focusing the authors’ systematic review on homogeneous study samples (only adult patients, no psychiatric comorbid conditions allowed) results of different researches can be easily compared to find similarities and discordances.

Applications

In clinical settings, patients with the same psychiatric condition often differ from one another in terms of clinical symptoms, response to pharmacological treatments and long-term outcome. Studying their brains and behaviors in details could help to provide more accurate diagnosis and treatments.

Terminology

IAD: An impulse control disorder characterized by an uncontrolled Internet use, associated with a significant functional impairment or clinical distress; IGD: A subtype of IAD, also called videogame addiction, characterized by excessive online gaming as the principal Internet activity.

Peer-review

This is a very interesting article.