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1Scientific RepoRts | 7:45064 | DOI: XXXXXXXXXX/srep45064
www.nature.com/scientificreports
Brain anatomy alterations
associated with Social Networking
Site (SNS) addiction
Qinghua He1,2,*, Ofir Turel2,3,* & Antoine Bechara2
This study relies on knowledge regarding the neuroplasticity of dual-system components that govern
addiction and excessive behavior and suggests that alterations in the grey matter volumes, i.e.,
ain
morphology, of specific regions of interest are associated with technology-related addictions. Using
voxel based morphometry (VBM) applied to structural Magnetic Resonance Imaging (MRI) scans of
twenty social network site (SNS) users with varying degrees of SNS addiction, we show that SNS
addiction is associated with a presumably more efficient impulsive
ain system, manifested through
educed grey matter volumes in the amygdala bilaterally (but not with structural differences in the
Nucleus Accumbens). In this regard, SNS addiction is similar in terms of
ain anatomy alterations
to other (substance, gambling etc.) addictions. We also show that in contrast to other addictions in
which the anterior-/ mid- cingulate cortex is impaired and fails to support the needed inhibition, which
manifests through reduced grey matter volumes, this region is presumed to be healthy in our sample
and its grey matter volume is positively co
elated with one’s level of SNS addiction. These findings
portray an anatomical morphology model of SNS addiction and point to
ain morphology similarities
and differences between technology addictions and substance and gambling addictions.
Notwithstanding the positive impacts of technologies on humans, technology-related addictions seem to be fairly
prevalent1,2; A recent meta-analysis suggests that globally the prevalence rate is about 6% and that it varies by
country, ranging from 2.6% to 10.9%3. While the negative outcomes of such addictions may not always be as
devastating as those generated by severe substance addictions, they attack the vulnerable population of ado-
lescents and young-adults4,5 and can have a myriad of negative effects on individuals’ work, school and social
functioning, wellbeing and psychological states2, as well as on their sleep hygiene and long-term cardio-metabolic
health5. Therefore, these addictions have been recognized as an important topic that merits further research6 and
the fifth edition of diagnostic and statistical manual for mental disorders has included the concept of “Internet
Gaming Disorder” in the appendix (section 3, potential disorders requiring further research)7. Conceptual
psychological-neurobiological models8 as well as functional
ain imaging studies9 suggest that such addictions
involve an interaction of sensitized reward processing and cue-reactivity with diminished prefrontal inhibitory con-
trol. Yet, more research is needed for understanding the structural neural underpinnings of this phenomenon10.
Specifically, even though addictions are recognized as “
ain diseases” by the American Medical Association, little
is known regarding potential
ain structural alterations associated with such addictions; this knowledge can help
esearchers and medical practitioners develop interventions for preventing or treating such addictions.
As such, this study seeks to examine potential
ain structural alterations associated with an important
instance of technology addictions, namely addiction to a social networking site. Social Networking Site (SNS)
addiction is a subcategory of the technology/Internet spectrum of addictions11 and is defined as a user’s mal-
adaptive psychological state of dependency on the use of an SNS, which is manifested through an obsessive
pattern of seeking and using this SNS such that these acts infringe normal functioning and produce a range of
typical behavioral addiction symptoms, including salience, withdrawal, relapse, growing tolerance, conflict and
mood modification12. While there is stronger consensus regarding the prevalence of maladaptive technology use
patterns which result in addiction-like symptoms1,2, it is not clear yet if the term “addiction” is best, and whether
other terms such as “use disorder” may be more appropriate. This study, however, uses the term “addiction” in
1Faculty of Psychology, Southwest University, Beibei, Chongqing, China. 2Brain and Creativity Institute, Department
of Psychology, University of Southern California, Los Angeles, California, USA. 3Information Systems and Decision
Sciences, California State University, Fullerton, Fullerton, California, USA. *These authors contributed equally to this
work. Co
espondence and requests for materials should be addressed to O.T. (email: XXXXXXXXXX)
eceived: 21 October 2016
Accepted: 20 Fe
uary 2017
Published: 23 March 2017
OPEN
mailto: XXXXXXXXXX
www.nature.com/scientificreports
2Scientific RepoRts | 7:45064 | DOI: XXXXXXXXXX/srep45064
line with prior research in this field, even though the medical community still debates if this term is appropri-
ate6. Furthermore, in line with this line of work13 we treat addiction as a continuous concept, i.e., we capture the
level of addiction-like symptoms all people have, rather than trying to medically classify people as addicts or
non-addicts using non-established criteria.
This study specifically focuses on
ain anatomy modulations in terms of the grey matter volumes (GMV; see
glossary of neuroscience terms in Appendix A) of
ain regions, which are arguably associated with SNS addic-
tion and are flexible or prone to anatomical modulations. These alterations are presumed to take place in central
and necessary regions of the dual-system which governs behavior14, the deficiency of which is associated with
addictions15. These regions are: (1) the Nucleus Accumbens (NAc), which has been implicated in playing a pri-
mary role in addictive behaviors through the processing of rewards that motivate behavior, including problematic
ehaviors; (2) the amygdala, which has been implicated in playing a key role in triggering impulsive behaviors
from conditioned cues; presumably by linking environmental cues to neural systems involved in negative rein-
forcement (e.g., the relief from an aversive condition such as withdrawal), as well as positive reward and reward
expectancy, such as those mediated by the NAc16; and (3) the midcingulate cortex (MCC), i.e., the dorsal region
of the anterior cingulate cortex (ACC), which is involved with self-control or inhibition processes in response to
impulsions generated through the impulsive system. The glossary in Appendix A provides details regarding these
neural substrates.
Addiction is often initiated by hyperactivity of the system that assesses rewards17 and drives impulsive behav-
iors15. This includes the NAc, the key substrate where mesolimbic dopamine is released, and reward seeking
ehavior is elicited, and it also includes the amygdala, which is thought to link environmental cues to reward
systems in the striatum, including the NAc. This system can become over-sensitized through repetitive enactment
of a rewarding behavior and recu
ing strong intrinsic rewards, which can lead to a constant state of “wanting”
to enact the addictive behavior18. The NAc is a central and necessary component of this reward system19, but
the amygdala has also been argued as a necessary component of a
oader neural system underlying automatic,
habit, and impulsive behaviors15,20,21. Hence, addictions are typically advanced by hyperactivity of the extended
amygdala circuit which includes the NAc and amygdala16. Many subcortical reward-system regions10, as opposed
to cortical regions, are morphologically flexible and can easily adjust to new environmental demands22. Hence,
it is reasonable to assume that addiction-associated morphology changes (see glossary of neuroscience terms in
Appendix A), if exist; can apply to the NAc and amygdala.
Oftentimes, the increased efficiency of the extended amygdala (reward) system is manifested through pruning
wasteful and redundant neurons, and specifically reducing the GMV of the amygdala such that lean, fast and com-
petent, bundles of neurons are retained. Achieving higher performance through pruning is very common23 and
is especially relevant in subcortical areas24. It should be noted that while grey matter volume reduction changes
to such regions are similar across addictions19,20, the processes that lead to such changes may differ between
addictions. In many cases, substances such as cocaine, which bind to dopamine receptors, create direct neurobi-
ological changes in the operation and GMV of such
ain regions25. In behavioral addictions, in contrast, such
as addiction to SNS or videogame use, the implicated systems are typically affected indirectly, by environmental
ehaviors26,27, through changing the work demands imposed on these
ain regions, e.g., through increasing the
need for reward or task-conflict processing and the resultant natural
ain adaptations28.
Regardless of the process, negative associations between the GMV of the (typically bilateral) amygdala and
other addictions have been observed in both substance and behavioral addictions, including for example in cases
of abuse of cannabis29, alcohol30, cocaine31, prescription opioids32, as well as in problematic behaviors such as
gambling33. Given possible neural and behavioral similarities between other addictions and technology-related
addictions34, and the shared neural basis of different addictions21 including behavioral ones27, it is reasonable to
expect that such negative associations also exist in the cases of SNS addiction. We hence hypothesize that (H1) the
grey matter volume of the amygdala will be negatively associated with one’s SNS addiction score; after controlling
for age, gender, number of contacts on the SNS, SNS use frequency, years of experience with the SNS, and the
whole
ain GMV. We suggest controlling for demographic and SNS use variables to ensure that the observed var-
iation in GMV is associated with addiction per-se. We also suggest cleaning any variance in GMV which may be
attributed to general
ain volume of grey matter, across regions, which may differ from one individual to another
and influence the GMV of the examined regions of interest (ROIs) regardless of addiction.
While the NAc is a central and active region in all addiction phases16, the existence and direction of possible
structural differences in the NAc in relation to addictions are not clear. Some studies, for example, show GMV
eduction in right NAc in alcoholism cases30 or left NAc in heroin-dependent patients35; whereas others show
increased GMV of left NAc in cannabis users29 and frequent video-gamers36. Some studies, albeit focusing on
connectivity, did not find co
elations of NAc connectivity with sharing of self-related information on social
media37. Given these mixed findings, and also the fact that the NAc is anatomically difficult to define with preci-
sion on scan images, we refrain from hypothesizing about the existence and direction of structural differences in
the NAc. Nevertheless, given the centrality of the NAc in reward processing, including in the case of social media
use38 we explore post-hoc whether structural differences in the NAc are associated with SNS addiction.
In addition to the abovementioned hyperactivity of the impulsive
eward assessment
ain system, addic-
tions typically also involve hypo-activity of the reflective or inhibition
ain system15. This hypo-activity is often
eflected in these areas of the
ain through reduced grey matter39–41. The ACC/MCC is of particular interest
since it is relevant for weak inhibition abilities and consequent addictions; and the grey matter morphology of the
ACC/MCC