Pavel Tikhonov1, Alexander Efimtcev2, Dmitriy Iskhakov2, and Mikhail Zubkov1
1Department of Physics and Engineering, ITMO University, Saint-Petersberg, Russian Federation, 2Department of Radiology, Federal Almazov North‐West Medical Research Center, Saint-Petersberg, Russian Federation
Synopsis
Task-related fMRI studies are
providing increasing amount of information on the neurobiological aspects of
the Gaming Disorder. This study aims to further explore the functional
connectivities present in the gaming disorder subject brain via task-based fMRI
study using individualized visual stimuli. 22 participants undergo fMRI
scanning with gaming-related and neutral visual stimuli. Data analysis shows
altered medial prefrontal cortex connectivity resembling that in cases of
substance addiction.
Introduction
Gaming Disorder (as defined in the ICD-11) or Internet
Gaming Disorder (as defined in the DSM-5) has attracted a lot of attention in
recent years. With the ongoing debate on the origins and personal and social
implications of compulsive gaming behavior1–4 studies have
been undertaken to explore the neurobiological aspects of the disorder. A
number of works investigate the brain functional networks via functional MRI (fMRI),
particularly with task-related fMRI5,6 and functional
connectivity estimation using generalized Psychophysiological Interactions (gPPI)
analysis. The findings in these include altered functional connectivity
patterns similar to the ones observed in substance addiction, particularly
related to the mechanisms of craving and reward3.
The latter were primarily detected in the cue-response task-related fMRI
experiments.
This study aims to further explore the functional
connectivities present in the gaming (or internet gaming) disorder subject
brain via task-based fMRI study using visual associative stimuli.Methods
The participants for the study were recruited via
social media by announcing a volunteer survey
in the local academic and gaming social groups. Among the 22 volunteers
participating in the study, 15 were gamers (mean age
23.6 ± 3.9 years) and 7 volunteers formed the control group (mean age 21.8 ±
2.3 years). There were 2 female, and 13 male participants in the gaming group, 3 female and 4 male
in the control group. The selection
criterion for the gamers group was 20 to 30 hours of
video game time per week. The declared game time was verified via an analysis
of gaming platform accounts provided in the survey. All surveyed gamers
displayed a preference for different game genres and titles. The selection
criterion for the control group was game time less than 10 hours per week. All the
participants were provided a written informational guide in accordance with
local ethics committee.
The experiment used a paradigm of 12 consecutive
alternating blocks: "Neutral" and "Game". The
"Neutral" block consisted of 10 random non-game images. The
"Game" block consisted of 10 random individual game images. Individual
stimuli were selected for each gamer in accordance with the preferred games
listed in the survey. The control group stimuli in the “Game” block were
randomly selected from the gamer group image pool. The “Neutral” stimuli were
the same for all participants and consisted of 40 images unrelated to video
games. The duration of one image presentation was 3 seconds, the duration of
the block was 30 seconds, the duration of the entire paradigm was 360 seconds
(Fig. 1). The demonstration was controlled via the PsychoPy3 program. The
images were projected onto a screen visible to the subject via a mirror system.
MRI data were obtained on a 1.5T scanner using a 16-channel
head coil. First, structural MPRAGE images of the brain were obtained. The structural
3D scans were obtained in the sagittal plane with
the following parameters: matrix 192×192×160, 240×240×192 mm
FoV, TE/TR = 3.7/2400 ms. Then, functional axial scans with visual stimuli were
obtained with an EPI-FID pulse sequence (BOLD technique). The protocol
parameters for functional scans were: matrix 64×64,
230×230 mm
FoV, TE/TR = 50/3000 ms, slice thickness = 5 mm, slice gap = 1.3 mm. The fMRI analysis
was performed using the CONN 18b toolbox (MATLAB R2020b). The
first two scans were discarded to avoid the
effects of triggering a scan. All scans were normalized to MNI-space and
converted to an isotropic 2 mm voxel space, local averaging with Gaussian 8 mm
FWHM window was applied. We performed ROI-to-ROI
analysis with task modulation effects (gPPI),
taking medial prefrontal cortex as the most significant hub, which participates
in regulation of brain function on of different levels.Results
Gaming group participants, compared to controls group
participants, exhibited significantly increased functional connectivity (Fig
2., Fig. 3) between: medial prefrontal cortex (MPFC) and frontal cortex (right
hemisphere), insular cortex, including its posterior part and planum polare
(right hemisphere), 7b and 8 areas in right cerebellar hemisphere. On the other
side, functional connectivity between MPFC and anterior division of cingulate
cortex was decreased. Besides, there was found an increase of functional
connectivity between MPFC and putamen and pallidum in both hemispheres, both
temporal lobes (inferior and middle temporal gyri), superior frontal gyrus
(right). Discussion and conclusion
The results confirm findings of a number of previous
studies, stating, there is evidence, that neural mechanisms underlying Internet
gaming disorder resemble those of substance addiction. Alterations of
functional connectivity of mesolimbic system in gaming disorder subjects allow
to linking it to the dopamine release similar to that of abuse-inducing drugs. Lower
employment of the dopamine transporter and dopamine receptor D2 indicates a
sub-sensitivity of dopamine reward mechanisms. The results also correlate with
studies, showing a decline in gray matter volume7,
particularly, in the anterior cingulate, supplementary motor areas, cerebellum,
insula, and the inferior temporal gyrus in internet gaming disorder subjects.
Further investigation, employing combined task-related and resting-state fMRI,
as well as morphometry applied to an increased number of participants is still
required. Acknowledgements
This work was supported by the Russian Science Foundation (Grant No. 18-79-10167)References
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