Neuroscience of Addiction Lab

Let’s introduce the team!

In our ‘Meet the team’ posts you will learn more about the NOFA lab members. Always wanted to know more about our projects, research interests, background, or hobbies? Keep reading!

What is your name? Lauren Kuhns

Can you tell something about yourself? I am originally from the UnitedStates, and I received my bachelor’s degree in Psychology at YaleUniversity in 2014. I moved to the Netherlands 5 years ago to do myMasters in psychology at the University of Amsterdam, and havecontinued on because it is a great environment for doing research.

What is your role at the NOFA lab? I am a second year PhD Candidate inthe lab. I spend about half of my time working on the Joint Study which isan ongoing cross-cultural neuroimaging study of Cannabis Use Disorder. Inaddition, I supervise bachelor and master’s student internships and thesisprojects and help teach a psychobiology course on addiction.

What is your main research interest/topic? I am mostly interested in therole of individual differences on the underlying neuromechanisms ofaddiction. In other words, does an addicted brain always look the same?And if not, what does that mean for our theoretical models of addiction?Most of my research centers around how factors such as age(adolescents vs. adults), culture (NL vs US) and co-use of other drugs(e.g. cigarettes/tobacco products) may influence motivational circuits inthe brain in the context of problematic cannabis and alcohol use.

Is there anything else we should know about you? I have a miniaturepoodle named Ralph Ravioli Cucumber.

As the neuroscience of addiction lab is also highly involved in teaching at the University of Amsterdam, we would like to share some of the great output from our recent bachelor course on addiction. In our ‘Food for thought: Student Edition’ series we will share some excellent essays on a variety of addiction related topics. This time you will have the opportunity to read Roos van Oeveren’s essay on ‘Competing models of addiction: two sides of the same coin?’.

About the author: I am a third year Psychobiology bachelor student at the University of Amsterdam. Whilst still deciding on my future specialization, I took the course “addiction” as an elective. I was deeply fascinated by the topic, and I found the neurobiology of addiction especially intriguing.

---

Competing models of addiction: two sides of the same coin?

Addiction has become a widespread problem. In the United States, 8-10% of people aged 12 years or older are estimated to be addicted to drugs such as alcohol, tobacco and also illicit drugs (Volkow, Koob & McLellan, 2016). With the goal of finding effective treatment, research into the underlying neurobiological mechanisms of addiction increased over the span of the last few decades. A long-accepted theory, that most scientists still admire, is the Brain Disease Model of Addiction (BDMA). This model is suggested by Leshner (1997) and recognizes addiction as a chronic, relapsing disorder characterized by structural brain changes. This model provides structure to the creation of social and health policies, behavioral treatments, and novel medications for addiction. However, some researchers have started questioning the brain disease model recently.

For example, Hall, Carter & Forlini (2015) state that the brain disease model of addiction is only accepted for social implications. Nonetheless, the model has not led to novel effective treatments and it lacks evidence based on animal and neuroimaging studies (Hall et al., 2015). In addition, brain alterations as found in addiction are thought to be an expression of natural brain plasticity, such as learning and development, instead of a disease (Lewis, 2017; Lewis 2018). Finding a comprehensive model to describe addiction is necessary for the development of effective treatments. However, scientists pleading contradicting models drive us only farther from this goal. According to Lewis (2017), the brain disease model of addiction and his proposed ‘developmental-learning model of addiction’ cannot be combined. However, I believe that these two models can be joined together into a novel, comprehensive model explaining addiction.

Firstly, a closer look into the brain disease model of addiction. Addiction has been described in three stages that are associated with different brain areas that indicate that addiction relies on mesolimbic reward systems. These stages are 1) binge/intoxication, mediated by the ventral tegmental area and ventral striatum, 2) withdrawal/negative effect, mediated by the amygdala, and 3) preoccupation/anticipation (craving), mediated by a broad network consisting of areas involving in craving and disturbed inhibitory control (Koob & Volkow, 2010). Throughout these stages, dopamine is an important transmitter that enhances structural changes in synaptic networks, such as in the striatum which mediates the pursuing of rewards (Koob & Volkow, 2010). These brain alterations are in line with the behavioral sensitization towards drugs seen in addiction.

The developmental-learning model of addiction recognizes the neurobiology of the brain disease model. However, it is viewed as a result of natural brain plasticity in the context of learning and development. The idea is that brain alterations should be expected in the presence of an addiction since our brain is supposed to change as a result of new experiences (Lewis, 2017). Addiction is seen as another experience that is strengthened by emotions and social influences. Desire shapes synaptic configuration thereby increasing sensitivity to cues associated with what is desired, resulting in a vicious circle of behavior or drug-taking (Lewis, 2017). The origination of addiction is not different from any other habit; however, it emerges more rapidly and more radical brain changes are observed due to the high motivational value of drugs.

Despite being based on the same neurobiological information, Lewis (2017) claims that the brain disease model and the developmental model of addiction cannot get along. The main statement is that the point of view on the neuroscientific research is very different for both models. Whereas the BDMA draws on the principle of ‘neuronormativity’, the developmental-learning model is based on neuroplasticity. In other words, according to Lewis (2017), the BDMA recognizes only two stages, either ‘normal’ or ‘pathological’, whilst the developmental-learning model acknowledges exclusively ‘normal’ states scattered in the spectrum of radical habit development.

Nonetheless, science nearly never succeeds to draw a harsh line between ‘pathological‘ and ‘normal’, as disorders and diseases go through development and therefore exist gradually in a spectrum. Rather the arbitrary concepts of the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) suggest a harsh lines between ‘pathological’ and ‘normal’ whilst it is acknowledged that disorders develop gradually. For example, in Alzheimer’s disease the distinction between ‘normal’ and ‘pathological’ forgetting is vague. Yet, it is accepted worldwide that Alzheimer’s disease is, in fact, a disease. Regarding this point of view, I propose that the mechanism through which addiction develops is indeed part of the natural, healthy neuroplasticity in habit formation. However, the rapid and radical development that Lewis (2017) states as characteristics of addiction are capable of shifting the addiction into the characteristics of a disease. Additionally, “developmental psychopathology” is an acknowledged term for other disorders that develop in a vague zone between pathology and learning, such as depression and anxiety disorders (Lewis, 2017). Lewis (2017) believes that explaining the etiology of addiction through natural plasticity excludes a disease. However, addiction is the only habit in which we observe such strong and radical habit formation, making the association with normal brain development unfair. We should, contrary to the BDMA, recognize the etiology of addiction through natural brain development mediated by strong motivation. Nonetheless, it is not excluded that this disease can develop through a natural mechanism.

In addition, Lewis (2017) does not distinguish between different types of addiction. However, difference in brain activity for different substance addictions (nicotine, alcohol and cocaine) in the amygdala and anterior cingulate cortex (ACC) have been found (Kühn & Gallinat, 2011). Analyzing brain changes in addiction as a pure expression of normal, standardized brain development fails to explain different effects of different substances. This suggests an effect on the brain activity by the substance itself, alongside the brain alterations due to habit formation. This could be in line with the idea that addiction develops through natural brain mechanisms. I propose that the substance has an extra effect on the neuroplasticity itself, leading to radical, pathological brain development and is in line with what is stated above. An important difference to the BDMA is that the BDMA assumes substance use to be the cause of all observed brain alterations. I believe the substance radicalizes normal habit formation into a pathological habit formation.

Furthermore, addiction is known to be related to genetic vulnerability (Ouzir & Errami, 2016). Yet, Lewis (2017) did not recognize any genetic factors underlying addiction vulnerability. A genetic predisposition for developing an addiction indicates a relationship to a disease. However, the presence of individual differences, such as sensitivity, do not exclude the collaboration between genetic influences and natural mechanisms. Individual differences are the rule and not the exception. Throughout the whole structural and functional development of the brain, individuals differ. The genetic vulnerability could result in a sensitivity for developing radical habit formation, which is in harmony with the aggregation of the BDMA and the developmental-learning model.

Moreover, this genetic predisposition in combination with natural neuroplasticity is in line with research into the social plasticity hypothesis. Briefly, this hypothesis states that vulnerability to social influences (such as peer pressure) increase the chance of excessive substance use when this is used in one’s social environment (Cousijn, Luijten & Feldstein Ewing, 2017). This hypothesis is mainly based on risk and resilience to addiction in adolescence, however, it is also in line with the broad idea that vulnerability to addiction shows high individual differences due to genetic predispositions and that the habit itself (for example excessive drinking use), can also differ between individuals (which is also strictly stated in the developmental-learning model (Lewis, 2017)).

Regarding current scientific knowledge as stated above, the brain disease model of addiction and the developmental-learning model can be combined into a novel, comprehensive model. Harsh distinction lines between pathological and normal habit formation should not be the goal and zones of change should be accepted. It should be highly recognized that I was not able to fully elaborate on all aspects of both models, and further, that more research is needed to expand this novel model. Moreover, combining the BDMA and the developmental-learning model can fulfill the need of a basis for novel treatment. Treatments of addiction based on the BDMA fail to be effective (Hall et al., 2015). Whilst the developmental-learning model fails to explain all symptoms of addiction (as elaborated above), the combination of both models could provide a basis for effective, novel treatments of addiction and new social and psychological policies. Future research should focus on individual treatment as proposed by Lewis (2017) regarding individual development, perspectives, goals and capacities in combination with research into genetic predispositions and the effects of specific substances.

References

Cousijn, J., Luijten, M. & Feldstein Ewing, S.W. (2018). Adolescent resilience to addiction: a social plasticity hypothesis. The Lancet Child & Adolescent Health, 2(1), 69-78. doi:10.1016/S2352-4642(17)30148-7.

Hall, W., Carter, A. & Forlini, C. (2015). The brain disease model of addiction: is it supported by the evidence and has it delivered on its promises? The Lancet Psychiatry, 2(1), 105-110. doi:10.1016/S2215-0366(14)00126-6.

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596

Leshner, A.I. (1197). Addiction Is a Brain Disease, and It Matters. Science, 278(45). doi:10.1126/science.278.5335.45

Koob, G., Volkow, N. Neurocircuitry of Addiction. Neuropsychopharmacol, 35, 217–238. doi:10.1038/npp.2009.110

Kühn, S., & Gallinat, J. (2011). Common biology of craving across legal and illegal drugs—A quantitative meta‐analysis of cue‐reactivity brain response. European Journal of Neuroscience, 33(7), 1318–1326. https://doi.org/10.1111/j.1460-9568.2010.07590.x

Lewis, M. (2017). Addiction and the Brain: Development, Not Disease. Neuroethics, 10(1), 7–18. doi:10.1007/s12152-016-9293-4

Lewis, M. (2018). Brain Change in Addiction as Learning, Not Disease. New English Journal of Medicine, 379(16), 1551-1560. doi: 10.1056/NEJMra1602872.

Ouzir, M. & Errami, M. (2016) Etiological theories of addiction: A comprehensive update on neurobiological, genetic and behavioural vulnerability. Pharmacology Biochemistry and Behavior, 148, 59-68. doi:https://doi.org/10.1016/j.pbb.2016.06.005.

Volkow, N. D., Koob, G. F., & McLellan, A. T. (2016). Neurobiologic Advances from the Brain Disease Model of Addiction. The New England journal of medicine, 374(4), 363–371. doi:10.1056/NEJMra1511480

As the neuroscience of addiction lab is also highly involved in teaching at the University of Amsterdam, we would like to share some of the great output from our recent bachelor course on addiction. In our ‘Food for thought: Student Edition’ series we will share some excellent essays on a variety of addiction related topics. This time you will have the opportunity to read Maura Fraikin’s essay on the potential of MDMA as a treatment for post traumatic stress disorder.

About the author: I am currently in my third year of the psychobiology bachelor at the University of Amsterdam. I am very intrigued by the intertwining of biology and psychology and how biological processes influence neurological phenomena. Cognition, psychopharmacology and the neurobiological mechanisms underlying psychiatric disorders are some of my main interests.

---

Is MDMA a safe and effective way to improve treatment for PTSD?

Post-traumatic stress disorder (PTSD) is a devastating mental disorder that is triggered by a traumatic event (American Psychiatric Association, 2013). Approximately 7.4% of the Dutch population develops PTSD at some point in their lives, with women being more likely than men to develop PTSD (De Vries & Olff, 2009). The symptoms of PTSD can be divided into four categories: repeated memories, avoidance, negative alterations in mood and thinking, and changes in arousal and reactivity (American Psychiatric Association, 2013). PTSD quite often co-occurs with other mental illnesses and PTSD has a large impact on quality of life (Brady et al., 2000). PTSD is even associated with an increased risk of attempting suicide (Tull, 2019), emphasising the relevance to expand research on treating the symptoms patients suffer from.

Currently available treatments include Cognitive Behaviour Therapy, Cognitive Processing Therapy, Eye Movement Desensitisation and Reprocessing and/or pharmacotherapy (American Psychiatric Association, 2013; Thal & Lommen, 2019). However, the rate of treatment resistance is high, often causing impairments for life (Rodriguez, Holowka & Marx, 2012). Another problem in PTSD treatment is that psychotherapy methods are trauma-focused, which can be quite overwhelming leading to many patients to drop out of treatment (Zepinic, 2015; Burge, 2018). Moreover, all currently used pharmacotherapies in PTSD are symptomatic treatments that do not get to the heart of the problems (Katzman, 2014; Burge, 2018; Bahji et al., 2020). Therefore, an effective treatment is needed that is capable of reducing the considerable rates of treatment failure related to current PTSD treatments.

MDMA, or 3,4-methylenedioxymethamphetamine, emerges as a promising therapeutic candidate for this. MDMA was invented in 1912 as a potential medicine and used in psychotherapy in the 1960s. At the same time, it ended up in the party scene, after which it ended up on list one of the Dutch Opium Act (Kuypers, 2019). This means that possession, trade, production, import and export of MDMA is illegal (art. 2 & art. 10 Opiumwet, 2019), making it hard to study MDMA in clinical settings. However, the beneficial effects of MDMA are unique and might be useful in PTSD treatment. It temporarily decreases fear while increasing relational trust and could therefore be effective to enhance the effects of psychotherapy (Mithoefer et al., 2011).

This leads to the question: does MDMA treatment in combination with psychotherapy successfully alleviate PTSD symptoms? I will argue why, in my opinion, MDMA has therapeutic potential for treatment of PTSD due to its unique characteristics, unlike other pharmacotherapies, to make psychotherapy effective and explain why people should be less reluctant to use this abused drug for medical purposes.

The effect of MDMA-assisted psychotherapy in treatment-resistant PTSD patients

The first completed clinical trial to indicate that MDMA might serve as a therapeutic adjunct in PTSD was performed by Mithoefer et al. (2011). In their study, 20 treatment resistant PTSD patients were tested in a randomized double-blind placebo controlled design. In the first stage of the study, patients were divided into an inactive placebo or MDMA group, in which participants received a dose of 125 mg MDMA, followed by an optional supplemental dose of 62.5 mg MDMA 2.5 hours later during two psychotherapy sessions. In the second stage, participants in the placebo group were given the option to participate in an open-label crossover part of the study in which they received 125 mg MDMA as well. MDMA significantly reduced the scores on the Clinician-Administered PTSD Scale (CAPS), which is a standard symptom scale used to quantify PTSD symptoms and assess the severity. The clinical response rate, defined as more than 30% reduction in CAPS score from baseline, was 83% in the MDMA group compared to 25% in the placebo group. Interestingly, the clinical response rate of the initial placebo group who transitioned to MDMA-assisted psychotherapy increased to 100% in stage two. Furthermore, no serious adverse effects related to MDMA were found.  However, the double blinded design in their study did not work. The majority of the participants and researchers correctly guessed the condition of the subjects. This is probably because MDMA is a psychoactive substance and it produces some noticeable physical and psychological effects, which might have influenced the results.

To evaluate the durability of the outcomes, the same research group assessed CAPS scores again in a follow-up study 3.5 years later. The statistically and clinically significant reduction in PTSD symptoms was maintained. This is indicative of a persistent effect of MDMA-assisted psychotherapy. None of the subjects reported they felt harmed from participating. Importantly, none of the participants used MDMA recreationally afterwards (Mithoefer et al., 2013).

Oehen et al. (2013), however, did not find a significant reduction of MDMA-assisted psychotherapy in clinical PTSD symptoms, although they did find a positive effect on self-reported PTSD symptoms. They examined the efficacy and safety of MDMA-assisted psychotherapy in 12 treatment-resistant PTSD patients in a randomized double-blind trial. Participants were randomly assigned into either full dose MDMA or placebo groups in stage one. As previously mentioned, MDMA has a psychoactive effect, making it hard to maintain the double blind status in clinical studies. To overcome this methodological challenge, an active placebo control of 25 mg followed by 12.5 mg MDMA 2.5 hours later was used, instead of the inactive placebo used by Mithoefer et al. (2011). The full-dose group received 125 mg MDMA, with a supplemental dose of 62.5 mg 2.5 hours later. This also differs from the study of Mithoefer et al. (2011) in which the supplemental dose of MDMA was optional.

In stage two, subjects in the active placebo condition were given the opportunity to continue in an open-label part of the study, receiving the full active dose of MDMA in conjunction with psychotherapy, similar to the method of Mithoefer et al. (2011). A 23.5% decrease in CAPS scores was found in the full-dose group, although this was not statistically significant. Furthermore, scores on the Posttraumatic Diagnostic Scale (PDS), which serves as a self-reporting measure to assess the presence of PTSD symptoms, significantly improved. Similar to results found in the earlier study (Mithoefer et al., 2011), patients in the active placebo group did not respond to treatment at first, but after receiving the full-dose MDMA in stage 2 they all responded to treatment, with half of the subjects no longer fulfilling PTSD criteria. At the one year follow-up, there was a further reduction in CAPS scores of 35% in the full-dose and 52% in the crossover group, thus indicating clinical response. Regarding the safety, no drug-related serious adverse events occurred, indicating that MDMA can be administered safely in a clinical setting in PTSD patients. Moreover, participants did not report any recreational use of MDMA at 12-month follow-up.

Discussion

These findings indicate that MDMA-assisted psychotherapy can successfully alleviate PTSD symptoms. There is empirical evidence that MDMA has therapeutic potential to be a successful, long-lasting and overall safe intervention for treatment-resistant PTSD patients. However, there are some limitations to the studies that need to be considered. All studies had small sample sizes and the majority of participants were female and Caucasian. It is possible that both gender and ethnic differences exist in response to psychotherapy in combination with MDMA. Furthermore, both durations of treatments and the extent of treatment before entering the study differed across studies, which makes the results difficult to compare. Moreover, the double-blinding was not effective in one study (Mithoefer et al., 2011), which could have influenced the results due to a bias of participants. These limitations emphasise that the conclusions must be drawn with caution.

Critics argue that the risk of abuse increases when MDMA gets legalised for medical use, since patients might use the drug afterwards to get the same feeling (Parrot, 2014) and as a non-patient it might be easier to gain access to MDMA. However, MDMA will be used in conjunction with psychotherapy in PTSD patients, meaning it will only be available under therapeutic supervision in certified clinics (Burge, 2018). Thus, PTSD patients will not be able to resell MDMA, as is done with Ritalin for example. Moreover, the fact that all studies showed that MDMA was not used for recreational purposes after treatment suggests that MDMA given in the context of psychotherapy has low abuse liability. Although we do need to be very wary about misuse, under appropriate supervision the risk seems small.

Another argument against the use of MDMA in PTSD treatment is that in studies of recreational ecstasy use severe adverse effects did occur. However, we should be careful to compare the morbidity and mortality statistics that are related to recreational ecstasy use with medical MDMA use in a controlled setting (Sessa, 2017). Both dose and content play an important role. Recreational dosages of MDMA in ecstasy vary and have increased over the past years. The mean dosage of MDMA in ecstasy in the Netherlands is 160 mg with outliers above 200 mg of MDMA (Drugs info team, 2018). Considering that recreational users quite often use more than one pill, the dosages of recreational MDMA are often higher than those in medical setting. Also, ecstasy does not always consist of pure MDMA—it may contain other substances. Furthermore, patients will have to be thoroughly screened in advance to minimize risks (Burge, 2018).

Research into the effectiveness of MDMA in alleviation of PTSD symptoms is scarce. The described studies that investigated the effectiveness were more or less the only ones. Thus, more research is needed to confirm the findings and to study long term outcomes. Also, gender and ethnic differences should be taken into consideration in future studies. Furthermore, research into the effective dosage and sessions of MDMA-assisted psychotherapy is useful. If the positive results of MDMA-assisted psychotherapy are replicated in phase three trials, MDMA might be approved by the FDA. Next to the fact that MDMA is on list 1 of the Dutch Opium Act, it will then also be included in the medicines law. If MDMA-assisted psychotherapy can indeed effectively be used in patients with treatment-resistant PTSD, the percentage of patients who commit suicide could decrease, as a result of increased quality of life. Altogether, MDMA is a potential medicine for PTSD and people should be less reluctant to use it for medical purposes, but more research is needed to get to conclusive results.

References

American Psychiatric Association. (2013) Diagnostic and statistical manual of mental disorders, (5th ed.). Washington, DC: Author

Bahji, A., Forsyth, A., Groll, D., & Hawken, E. R. (2019). Efficacy of 3, 4-methylenedioxymethamphetamine (MDMA)-assisted psychotherapy for posttraumatic stress disorder: A systematic review and meta-analysis. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 109735. DOI:10.1016/j.pnpbp.2019.109735

Burge, B. (2018). MDMA, Psychotherapy, and the Future of PTSD Treatment. Retrieved from: https://www.ted.com/talks/brad_burge_mdma_psychotherapy_and_the_future_of_ptsd_treatment

Brady, K. T., Killeen, T. K., Brewerton, T., & Lucerini, S. (2000). Comorbidity of psychiatric disorders and posttraumatic stress disorder. The Journal of clinical psychiatry

de Vries, G. J., & Olff, M. (2009). The lifetime prevalence of traumatic events and posttraumatic stress disorder in the Netherlands. Journal of Traumatic Stress: Official Publication of The International Society for Traumatic Stress Studies, 22(4), 259-267. DOI: 10.1002/jts.20429.

Drugs info team. (2018). Xtc feiten. Retrieved from: https://www.drugsinfoteam.nl/drugsinfo/xtc/xtc-feiten

Katzman, M. A., Bleau, P., Blier, P., Chokka, P., Kjernisted, K., & Van Ameringen, M. (2014). Canadian clinical practice guidelines for the management of anxiety, posttraumatic stress and obsessive-compulsive disorders. BMC psychiatry, 14(S1), S1. DOI:10.1186/1471-244X-14-S1-S1

Kearney, D., Martinez, M., & Simpson, T. (2018). Posttraumatic Stress Disorder (PTSD). In Integrative Medicine (pp. 86–93.e3). DOI:10.1016/B978-0-323-35868-2.00010-4

Kuypers, K. (2019, 17 oktober). Waarom zeggen alle psychiaters ‘ja’ tegen mdma? AD. Retrieved from: https://www.ad.nl/wetenschap/waarom-zeggen-alle-psychiaters-ja-tegen-mdma~a8b97feb/

Mithoefer, M. C., Wagner, M. T., Mithoefer, A. T., Jerome, L., & Doblin, R. (2011). The safety and efficacy of±3, 4-methylenedioxymethamphetamine-assisted psychotherapy in subjects with chronic, treatment-resistant posttraumatic stress disorder: the first randomized controlled pilot study. Journal of Psychopharmacology, 25(4), 439-452. DOI: 10.1177/0269881110378371

Mithoefer, M. C., Wagner, M. T., Mithoefer, A. T., Jerome, L., Martin, S. F., Yazar-Klosinski, B., … Doblin, R. (2013). Durability of improvement in post-traumatic stress disorder symptoms and absence of harmful effects or drug dependency after 3,4-methylenedioxymethamphetamine-assisted psychotherapy: a prospective long-term follow-up study. Journal of psychopharmacology (Oxford, England), 27(1), 28–39. DOI:10.1177/0269881112456611

Oehen, P., Traber, R., Widmer, V., & Schnyder, U. (2013). A randomized, controlled pilot study of MDMA (±3,4-Methylenedioxymethamphetamine)-assisted psychotherapy for treatment of resistant, chronic Post-Traumatic Stress Disorder (PTSD). Journal of Psychopharmacology, 27(1), 40–52. DOI:10.1177/0269881112464827

Opiumwet (2019). Retrieved from: https://wetten.overheid.nl/BWBR0001941/2019-07-19#BijlageI

Parrott, A. (2014). The Potential Dangers of Using MDMA in Psychotherapy. Journal of Psychoactive Drugs. 46 (1): 37–43. DOI:10.1080/02791072.2014.873690

Rodriguez, P., Holowka, D. W., & Marx, B. P. (2012). Assessment of posttraumatic stress disorder-related functional impairment: A review. J Rehabil Res Dev, 49(5), 649-65 DOI: 10.1682/JRRD.2011.09.0162

Sessa, B. (2017). MDMA and PTSD treatment:“PTSD: from novel pathophysiology to innovative therapeutics”. Neuroscience letters, 649, 176-180. DOI: 10.1016/j.neulet.2016.07.004

Thal, S. B., & Lommen, M. J. (2018). Current perspective on MDMA-assisted psychotherapy for posttraumatic stress disorder. Journal of contemporary psychotherapy, 48(2), 99-108. DOI: 10.1007/s10879-017-9379-2

Tull, M. (2019, 23 november). The Connection Between PTSD and Suicide. Retrieved from: https://www.verywellmind.com/ptsd-and-suicide-2797540

Zepinic, V. (2015). Treatment Resistant Symptoms of Complex PTSD Caused by Torture During War. Canadian Social Science, 11(9), 26-32. DOI:10.3968/7551

As the neuroscience of addiction lab is also highly involved in teaching at the University of Amsterdam, we would like to share some of the great output from our recent bachelor course on addiction. In our ‘Food for thought: Student Edition’ series we will share some excellent essays on a variety of addiction related topics. This time you will have the opportunity to read Marisse Koolstra’s essay on a highly interesting and relevent question: “Excessive social media use: A modern addiction or coping mechanism?”

About the author: Marisse Koolstra is a 21 year-old from a city close to Utrecht and because she wanted to understand the biological background of human behavior and brain diseases, she decided to study Psychobiology at the University of Amsterdam. After she has finished her bachelor thesis, on which she is currently working, she hopes to combine a research master with a more clinical oriented one, because she would like to bring together both fields in her future working life.

---

Excessive social media use: A modern addiction or coping mechanism?

Could one have imagined at the time of the invention of one of the very first social media sites, GeoCities, which was founded in 1994, that nowadays one can be called ‘addicted to social media’? Studies on internet addiction reveal prevalence rates ranging from 2.6% to 10.9% differing per country (Cheng & Li, 2014), and studies specifically focusing on the prevalence of Social Network Site (SNS) addiction report rates varying from 1.6% to 8.6% in the case of Facebook, and 34% to Xiaonei, a Chinese social media site (Andreassen, 2015). Keeping in mind the fact that these prevalence rates are often based on small and non-representative samples, it does show that there are people who use SNSs excessively, and – not unimportantly – experience negative consequences of it, just like other addicts. Besides the problems, the other addiction stages (salience, tolerance, mood modification, withdrawal, relapse and conflict) are applicable to SNS addicts as well (Andreassen, 2015).

It can be debated, however, whether addiction is a proper term for the behavior observed. Since the introduction of gambling disorder in the DSM-5, it has been a topic of discussion for several possibly addictive behaviors whether these should be considered addictions as well (Kardefelt-Winther, 2017). This raises the question of whether excessive SNS use can be considered an addiction. In my opinion, it is too soon to draw conclusions yet because of sparse and inconclusive neuroscientific evidence and the suggestion of other underlying problems to be the core of the behavior observed, when taking into account the model proposed by Kardefelt-Winther et al. (2017). Therefore, I will from now on use ‘problematic SNS use’ instead of ‘SNS addiction’.  

Neurobiological substrates

First of all, research focusing on the neurobiological substrates of the excessive use of and dependence on SNSs is limited. He et al. (2017) studied the grey matter volume (GMV) of several brain areas associated with the presence of an addiction of people with varying degrees of problematic SNS use and conclude that SNS addicts have reduced GMV in the amygdala and increased GMV in the anterior cingulate cortex (ACC) and midcingulate cortex (MCC). No structural changes were found in the nucleus accumbens (NA). In my opinion, this conclusion should be nuanced, since there was no group of controls who did not experience problematic SNS use included in the experimental design, so they compared problematic-users of varying degrees with each other. The way the conclusion is formulated now suggests that they compared problematic users with non-problematic users. When the same research group did include a control group, however, the same structural changes in excessive SNS users regarding the amygdala were found, but excessive SNS users did not show significantly different grey matter volumes in the prefrontal regions including the ACC compared to the control group (He et al., 2017).

He et al. (2017) compared their findings with structural brain changes found in substance use disorder or food addiction, namely that the changes found in the amygdala are the same for people with a substance use disorder or other behavioral addictions such as gambling. The changes found in the ACC and MCC and the absence of structural changes in the NA are not consistent with changes seen in substance and food addiction. However, there are a lot of inconsistencies in the findings on brain changes in other addictions and it is still controversial whether food addiction should be considered an addiction as well (Fletcher & Kenny, 2018), so they might be jumping to conclusions a little too quickly.

Besides findings suggesting structural differences between controls and problematic SNS users, a study conducted by Turel et al., (2014) found abnormal functioning of the inhibitory-control brain system in problematic Facebook users when performing a go/no-go task. The activation of the impulsive (amygdala-striatal) brain system in this task was positively associated with the degree of addiction, which is also seen in other addictions. However, there was no hypoactive inhibitory system (prefrontal system), which is also seen in gambling and substance addictions (Turel et al., 2014).

Underlying problems as the core

Considering neurobiological substrates, it cannot be concluded that excessive social media use is comparable with substance use addictions based upon the existing literature. However, it has been suggested that behavioral addictions should not necessarily be compared to the diagnostic criteria of substance addictions since this possibly holds a risk for pathologizing common behaviors. To avoid this, Kardefelt-Winther et al. (2017) proposed a definition of behavioral addictions, which includes the following four exclusion criteria:  “1.) the behaviour is better explained by an underlying disorder (e.g. a depressive disorder of impulsive-control disorder); 2.) the functional impairment results from an activity that, although potentially harmful, is the consequence of a willful choice (e.g. high‐level sports); 3) The behaviour can be characterized as a period of prolonged intensive involvement that detracts time and focus from other aspects of life, but does not lead to significant functional impairment or distress for the individual; 4.) The behaviour is the result of a coping strategy.” (Kardefelt-Winther et al., 2017).

Of particular interest in the case of problematic SNS use is the last criterion, since several studies are pointing towards the interpretation of problematic SNS use as a coping strategy rather than an addiction (Kardefelt-Winther, 2016). For example, a study investigating internet addiction suggested that heavier internet users are using the internet as an escape and another one suggested that excessive online gaming may be a way to avoid real-life problems. These both fit better with a perspective of problematic internet use as coping strategy than addiction, although both studies approached it from an addiction perspective (Armstrong et al., 2000; Lemmens et al., 2011 resp., cited by Kardefelt-Winther, 2016).

Problematic SNS use may also be a coping strategy rather than an addiction. In her review on SNS addiction, Andreassen (2005) indicates that problematic use of SNS is associated with the need for belonging (Pelling & White, 2009), social contact (Lee et al., 2012), and reduction of loneliness (Teppers et al., 2014). Besides these needs, Facebook use for mood regulation explained people’s inadequate self-regulation of their use (Lee et al., 2012). In addition, it is also related to low self-esteem (Hong et al., 2014) and fear of missing out (Buglas et al., 2017).

It could be questioned on the other hand, whether these coping strategies also play a role in substance use disorder. Indeed, Kronenberg et al. (2015) found that patients with a substance use disorder made more use of palliative reaction (seeking distraction; trying to feel better by drinking or smoking), avoidance (waiting, avoiding the situation) and passive reaction (rumination, drawing back) coping styles than healthy controls when confronted with problems or unpleasant incidents, as measured with the Utrecht Coping List. This would then maybe advocate for problematic SNS use being an addiction, since substance use disorders are called addictions despite the presence of palliative coping strategies.

Conclusion

To summarize, from a neurobiological point of view, there are indications that some differences between problematic SNS users and controls possibly exist, but drawing comparisons with patients with SUD remains difficult and premature. On the other hand, there are also studies suggesting that problematic SNS use is the result of a coping strategy. Therefore, I would not recommend to draw conclusions about problematic SNS use yet, since the label assigned to it will determine how we view and treat problem users: as individuals who need medication and professional intervention? Or as individuals who have underlying problems and should be taught more effective coping strategies? Too hastily drawing conclusions about these questions without a proper evidence base can cause pathologizing and stigmatizing of normal behaviors. On the other hand, people with problematic SNS use may also feel as if their problem is not taken seriously and will not receive adequate treatments if it actually appears to be addiction but is not viewed accordingly. 

To obtain more clarity about problematic SNS use, future studies should in my opinion determine to what extent problematic SNS use is related to a coping strategy. It could be argued namely, that problematic SNS use is the coping strategy, whereas coping could be just one contributive factor in substance use disorder. Another question which follows from this is whether everyone who experiences problems with excessive SNS use, uses SNSs as a coping strategy, or whether subgroups of people with problematic SNS use are distinguishable. Besides that, more studies that investigate the relation between problematic SNS use and brain structure and function are needed, but they should not necessarily be aimed at comparing problematic SNS use with other addictions a priori, since this does not leave enough room for an objective look for other explanations of problematic SNS besides being an addiction.

References

Andreassen, C.S. (2015). Online Social Network Site Addiction: A Comprehensive Review. Current Addiction Reports, 2, 175–184.

Buglas, S.L., Binder, J.F., Betts, L.R. & Underwood, J.D.M. (2017). Motivators of online vulnerability: The impact of social network site use and FOMO. Computers in Human Behavior, 66, 248-255. doi:10.1016/j.chb.2016.09.055

Cheng, C. & Li, A. Y. L. (2014). Internet Addiction Prevalence and Quality of (Real) Life: A Meta-Analysis of 31 Nations Across Seven World Regions. Cyberpsychology Behavior and Social Networking, 17, 755–760. doi:10.1089/cyber.2014.0317.

Fletcher, P.C. & Kenny, P.J. (2018). Food addiction: a valid concept?. Neuropsychopharmacol, 43, 2506–2513. doi:10.1038/s41386-018-0203-9

He, Q., Turel, O., Bechara, A. (March 2017). Brain anatomy alterations associated with Social Network Site (SNS) addiction. Scientific reports, 7. doi: 10.1038/srep45064

He, Q., Turel, O., Brevers, D. & Bechara, A. (November 2017). Excess social media use in normal populations is associated with amygdala-striatal but not with prefrontal morphology. Psychiatry Research: Neuroimaging, 269, 31-35.

Hong, F., Huang., D. Lin, H. & Chiu, S. (2014). Analysis of the psychological traits, Facebook usage, and Facebook addiction model of Taiwanese university students. Telematics and Informatics, 31, 597-606. doi:10.1016/j.tele.2014.01.001

Kardefelt-Winther, D., Heeren, A., Schimmenti, A., van Rooij, A., Maurage, P., Carras., M., Edman., J., Blaszcynski, A., Khazaal, Y. & Billieux, J. (2017). How can we conceptualize behavioural addiction without pathologizing common behaviors? Addiction, 112(10), 1709-1715. doi:10.1111/add.13763

Kardefelt-Winther, D. (2017). Conceptualizing internet use disorders: Addiction or coping process? Psychiatry and Clinical Neurosciences, 71, 459-466. doi:10.1111/pcn.12413

Kronenberg, L.M., Goossens, P.J.J., van Busschbach, J., van Achterberg, T. & van den Brink, W. (2015). Coping styles in substance use disorder (SUD) patients with and without co-occurring attention deficit/hyperactivity disorder (ADHD) or autism spectrum disorder (ASD). BMC Psychiatry, 15. doi:10.1186/s12888-015-0530-x

Lee, Z.W.Y., Cheung, C.M.K. & Thadani, D.R. (2012). An investigation into the problematic use of Facebook. Proceedings of the 45th Hawaii International conference on System Sciences., 1768–1776. doi:10.1109/HICSS.2012.106.

van Oeveren, R. (2019) Should we acknowledge behavioral addictions? Mini-essay for subject Addiction.

Pelling E.L. & White K.M. (2009). The theory of planned behavior applied to young people’s use of social networking web sites. CyberPsychology & Behavior, 12, 755–759. doi: 10.1089=cpb.2009.0109

Teppers, E., Luyckx, K., Klimstra, T.A. & Goossens, L. (2014). Loneliness and Facebook motives in adolescence: A longitudinal inquiry into directionality of effect. Journal of Adolescence, 37(5), 691-699. doi:10.1016/j.adolescence.2013.11.003

Turel, O., He, Q., Xue, G., Xiao, L. & Bechara, A. (2014). Examination of neural systems sub-serving Facebook ‘addiction’. Psychological Reports: Disability & Trauma, 115(3), 675-695. doi:10.2466/18.PR0.115c31z8

Let’s introduce the team!

In our ‘Meet the team’ posts you will learn more about the NOFA lab members. Always wanted to know more about our projects, research interests, background, or hobbies? Keep reading!

What is your name? Bibian Borst

Can you tell something about yourself? I am a third year psychobiology student who has always had a love for football and music. I played football in the United States for two years where I studies Biology and Psychology. After two years I came back to the Netherlands and started my psychobiology bachelor at the University of Amsterdam.  In Amsterdam I joined multiple student organisations. I am a member of the OC of psychobiology, I was the president of the CareerCie of the studentorganisation Congo that organised a career day, and I work at Ajax (again love for football and music fits perfectly here, cause my job is attending football games and music concerts).

What is your role at the NOFA lab? I am a bachelor intern and we are fully emerged in the research group at the NOFA lab. This means that we take part in the testing of the participants, we go on recruiting to gather those participants, and have a calling session each week to contact and screen the possible participants.  My personal goal is just to learn as much as I can in this half year and be a reliable person in the research group.

What is your main research interest/topic? I am interested in the difference between sensation seeking behaviour traits in comparison to impulsivity. These two traits are often put together in substance use research but can have different effect on the motives of why people use a substance as well on the amount of use and problems relating the use. These kinds of models have been primarily tested with alcohol and I am interested to see what the relationship is with cannabis.

Is there anything else we should know about you? I have a small obsession with avocado’s!

Let’s introduce the team!

In our ‘Meet the team’ posts you will learn more about the NOFA lab members. Always wanted to know more about our projects, research interests, background, or hobbies? Keep reading!

What is your name? Emese Kroon

Can you tell something about yourself? I was born in the Netherlands and grew up in a relatively small village close to Amsterdam. I completed a bachelors degree in psychobiology and afterwards completed the research master psychology, both at the University of Amsterdam. During my bachelor and master I studied a variety of topics from cell biology to evolutionary psychology, but got more and more interested in addiction research. Although the research I did for the past years mostly centers around this one topic, I still prefer combining different types of research methods. That is also why I’m really glad the NOFA lab gives me the opportunity to combine neuroimaging techniques with classic measures of human behaviour and cognition.

What is your role at the NOFA lab? I’m a second year PhD student working on the Joint Study. A super interesting and extensive study in which we, in collaboration with the University of Texas Dallas (UTD), look into the effects of Cannabis Use Disorder (CUD) on the brain and how cultural difference shape the effects of cannabis on our brain and behaviour.

What is your main research interest/topic? In my PhD project I focus on the effects of heavy cannabis use and CUD on the brain and behaviour. What makes that some heavy users cannabis users develop an addiction while others do not? I’m particularly interested in the role of cognitive control and the importance of context in the effects of cognitive control. Cognitive control is often found to be impaired in individuals suffering from substance use disorders, but the context specificity of this impairment is unclear.

Is there anything else we should know about you? Where to start! A little summary: my favourite colour is blue, I like penguins, I’m not a fan of biking in Dutch weather, I play korfbal (a very very Dutch sport), and live in Amsterdam.

Have you heard of the Amsterdam Underground tour? Before it was a tourist hot spot, the city center of Amsterdam was embroiled in drugs and crime. To broaden your horizons and learn first-hand about this fairly recent history, you can take a tour of the city center guided by former addicts who survived on the streets. Each walk is different, and you will hear a personal story about addiction and survival. You can find more info here: https://www.amsterdamunderground.org/

In the NOFA lab, one of the topics we investigate is the role of social processes in addiction. In this ted talk, Johann Hari argues for the role of putting the social disconnection and isolation often seen in addiction at the forefront in order to offer a more compassionate and effective response to the people suffering with addictions.

What really causes addiction — to everything from cocaine to smart-phones? And how can we overcome it? Johann Hari has seen our current methods fail firsthand, as he has watched loved ones struggle to manage their addictions. He started to wonder why we treat addicts the way we do — and if there might be a better way. As he shares in this deeply personal talk, his questions took him around the world, and unearthed some surprising and hopeful ways of thinking about an age-old problem.