Files/.DS_Store __MACOSX/Files/._.DS_Store Files/Brain anatomy alterations associated with Social Networking Site (SNS) addiction.pdf 1Scientific RepoRts | 7:45064 | DOI: XXXXXXXXXX/srep45064...

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Files/.DS_Store __MACOSX/Files/._.DS_Store Files/Brain anatomy alterations associated with Social Networking Site (SNS) addiction.pdf 1Scientific RepoRts | 7:45064 | DOI: 10.1038/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., brain 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 brain system, manifested through reduced 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 brain 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 correlated with one’s level of SNS addiction. These findings portray an anatomical morphology model of SNS addiction and point to brain 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 brain 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 “brain diseases” by the American Medical Association, little is known regarding potential brain structural alterations associated with such addictions; this knowledge can help researchers and medical practitioners develop interventions for preventing or treating such addictions. As such, this study seeks to examine potential brain 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. Correspondence and requests for materials should be addressed to O.T. (email: [email protected]) received: 21 October 2016 Accepted: 20 February 2017 Published: 23 March 2017 OPEN mailto:[email protected] www.nature.com/scientificreports/ 2Scientific RepoRts | 7:45064 | DOI: 10.1038/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 brain anatomy modulations in terms of the grey matter volumes (GMV; see glossary of neuroscience terms in Appendix A) of brain 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 behaviors; (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 behavior 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 recurring 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 broader 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 brain regions25. In behavioral addictions, in contrast, such as addiction to SNS or videogame use, the implicated systems are typically affected indirectly, by environmental behaviors26,27, through changing the work demands imposed on these brain regions, e.g., through increasing the need for reward or task-conflict processing and the resultant natural brain 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 brain 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 brain 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 reduction 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 correlations 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/reward assessment brain system, addic- tions typically also involve hypo-activity of the reflective or inhibition brain system15. This hypo-activity is often reflected in these areas of the brain 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
Answered 3 days AfterSep 25, 2021

Answer To: Files/.DS_Store __MACOSX/Files/._.DS_Store Files/Brain anatomy alterations associated with Social...

Abirami answered on Sep 28 2021
134 Votes
NEUR3004 Mini-Research Project #2
I went through the experimental research paper that was briefly discussed on the radio as suggest
ed by you. It indeed is a breakthrough study analyzing the technological side effects and impact on the human physiological well-being and brain structure. Importantly, the study is well designed and documented, as it compares the addictive behavior of social media with the addiction caused by substance abuse.
For the research, the scientists selected over 20 people of age ranging from 18-23 years, who were the users of Facebook. The degree of using Facebook ranged from person to person. Various factors such as age, brain size, and screen activity were recorded before the analysis. After analyzing their physique, they were checked for the changes in their brain structure and anatomy computationally using an MRI scan. Further to validate their conclusions they utilized voxel-based morphometry, where they compared and scored the brain structure of these people based on the level of addiction with the brain structure of people who were addicted to substance abuse.
The scientists majorly focused on the three main structures of the brain. They are (i) nucleus accumbens (NAc) which are involved with the stress, motivation, and reward system of humans, (ii) the amygdala that is...
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