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Indeed, the original formal proposal for IA to be included in the DSM-5 incorporated the subtypes of instant messaging, pornography use, and video games [ 17 ], expanded later to include social networking [ 18 ]. This would have aligned the DSM-5 with what has, in fact, occurred in the field since its publication, namely, the continued scientific investigation into the broad range of potentially problematic behaviors involving Internet use.

This inclusive approach has been proposed multiple times, both historically [ 17 ] and recently [ 1920 ]. Conceptualizing IA as a generalized problem with more specific subtypes is ripe for formal reconsideration.

There is a key element found throughout all internet-related experiences: The ability to maintain or heighten arousal with the click of a mouse or swipe of a finger. Thus, the act of seeking which would include surfing triggers the reward system [ 22 ]. Some internet activities, because of their power to deliver unending stimulation and activation of the reward systemare thought to constitute supernormal stimuli [ 24 ], which helps to explain why users whose brains manifest addiction-related changes get caught in their pathological pursuit.

To illustrate this phenomenon, Tinbergen created artificial bird eggs that were larger and more colorful than actual bird eggs. Surprisingly, the mother birds chose to sit on the more vibrant artificial eggs and abandon their own naturally laid eggs. Similarly, Tinbergen created artificial butterflies with larger and more colorful wings, and male butterflies repeatedly tried to mate with these artificial butterflies in lieu of actual female butterflies.

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Evolutionary Psychologist Dierdre Barrett took up this concept in her recent book Supernormal Stimuli: We humans can produce our own. In short, generalized internet chronic overuse is highly stimulating.

It recruits our natural reward system, but potentially activates it at higher levels than the levels of activation our ancestors typically encountered as our brains evolved, making it liable to switch into an addictive mode [ 27 ].

In the review that follows we will first provide an overview of the major theoretical understanding or models of addiction involving substances and of the neuroscientific basis on which the addictive processes work, whether there is involvement with substances or behaviors. We will then review the existing neuroscientific studies relating to the behavioral aspects of addiction generally, then the more specific problem of Gambling Disorder, and then progress to the flood of recent studies on IA, and its subtypes of gaming and pornography.

The majority of studies discussed examined key aspects of addiction involving behaviors through laboratory investigation, including functional neuroimaging studies and structural and resting-state neuroimaging studies. These bear on the established science relating to addiction generally. Where relevant, we have also discussed neuropsychological studies, which suggest laboratory behavioral parallels with brain studies such as those on structural brain abnormalities thought to be the result of addiction.

We have chosen to narrow our focus primarily to the neuroscientific research findings relating to addiction involving behaviors, despite the fact that there is also a large and growing body of research relating to their clinical presentation, epidemiology, health effects, public health ramifications, etc.

While that line of research overwhelmingly supports the prevalence and risks associated with Internet and Internet related addiction, it is outside the scope of this neuroscience focused review. Thus we believe that it makes sense to limit this review primarily to the studies that meet the most rigorous requirements, studies that address the neurobiochemical and neurophysiological processes known to underlie addiction generally. We hope that the articles reviewed here will make it clear that the dozens of studies supporting IA and each of its subtypes as being neuroscientifically similar to substance addiction and will demonstrate that all of the possible Internet behaviors must be considered as potentially addictive in the same way, as variations on a theme rather than separate disorders, just as diverse forms of gambling e.

In fact it is the case that most IA studies around the world have considered the various Internet behaviors in this light. Method To conduct the research, an extensive literature search and review was performed utilizing a variety of sources: A universal inclusion criterion was publication in a peer-reviewed journal. Continuous rechecks of the more rapidly emerging subject areas e. As such, an exact number of results reviewed was impossible to calculate as the rechecks often returned results already reviewed.

Some manual screen of ambiguously titled papers was required performed by first author. The reference management tool Zotero was used to build a database of all articles considered. Neurobiology of Addiction The scope of this topic was limited to the previous ten years, with primary focus given to articles published in the past five years. Older publications considered key developments within the scientific advancement of this field were also included for example, Blum et al.

Neurobiology of Addictive Behaviors This scope was not time-delimited, as it is an emerging topic whose entire historical context is relevant. Analytical priority, however, was given to literature reviews, and articles published via a newest to oldest methodology. The following search terms and their derivatives were used in multiple combinations: Multiple combinations of the following search terms and their derivatives were used in conducting the research: Internet Addiction As this is another emerging topic, there was no time-scope set for this topic, although priority was given to studies and reviews published in the previous five years.

Special attention to nomenclature was required here, as the disorder is studied under different headings. As such, the following search terms and their derivatives were used in multiple combinations: Internet Gaming Disorder No time-limitation was placed on this topic, and the following search terms and their derivatives were used in multiple combinations: A less-than-exhaustive final selection approach was taken based on the fact that the APA has already approved IGD as a research-worthy diagnosis, and thus the full volume of articles in this subject area was not needed to support our premise.

Internet Pornography Addiction Research into the area of addictive sexual behaviors on the Internet began with an inquiry into the various constructs surrounding compulsive sexual behavior. There was no specific time-delimitation for this search, however, as with behavioral addiction, analytical priority was placed upon literature reviews and articles published via a newest to oldest methodology.

Additional screening was required to differentiate articles about IP included and non-IP not included. Multiple combinations of the following search terms and their derivatives were used: Neurobiology of Addiction All drugs of abuse affect the mesolimbic dopamine DA pathway, which originates from the ventral tegmental area VTA and projects into the nucleus accumbens NAcc.

Commonly called the reward center, the NAcc is heavily connected with pleasure, reinforcement learning, reward seeking, and impulsivity. The mesolimbic dopamine pathway connects with three other key regions to form a collection of integrated circuits commonly called the reward system: The amygdala positive and negative emotions, emotional memoryhippocampus processing and retrieval of long term memoriesand the frontal cortex coordinates and determines behavior.

Taken together, the reward system and its connecting regions modulate, among other things, pleasure, reward, memory, attention, and motivation [ 43 ].

Naturally occurring behaviors such as eating and sex, have evolved such that they activate the reward system due to the fact that they reinforce behaviors necessary for survival [ 20 ]. The past decade has yielded multiple theories of addiction, all of which involve the reward system and related brain regions and substrates [ 44 ]. Three-Stage Model of Addiction Nora Volkow describes addiction as a neurobiochemically based shift from impulsive action learned through positive reinforcement to compulsive actions learned through negative reinforcement [ 43 ].

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This in turn is seen as leading to an addictive cycle that progressively worsens over time. Different classes of drugs activate the reward system through different means, however, the universal result is a flood of dopamine in the NAcc reward center. This results in acute positive reinforcement of the behavior that initiated the flood.

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In this impulsive stage, this positive reinforcement results in addictive related learning associations [ 45 ]. Neuroplastic changes begin to occur, however, as the continued release of dopamine in the NAcc leads to an increase in dynorphin levels. Dynorphin, in turn, decreases the dopaminergic function of the reward system, resulting in a decrease of the reward threshold and an increase in tolerance [ 4345 ].

The resulting negative emotional state leads to activation of brain stress systems and dysregulation of anti-stress systems. This leads to a decreased sensitivity to rewards and an increase in the reward threshold, which is called tolerance. This further progresses to negative reinforcement as the individual continues to engage in the addictive behaviors to avoid the negative affect associated with withdrawal. A key point of this stage is that withdrawal is not about the physiological effects from a specific substance.

Rather, this model measures withdrawal via a negative affect resulting from the above process. Aversive emotions such as anxiety, depression, dysphoria, and irritability are indicators of withdrawal in this model of addiction [ 4345 ]. Researchers opposed to the idea of behaviors being addictive often overlook or misunderstand this critical distinction, confusing withdrawal with detoxification [ 4647 ].

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A second component of the reward system comes into play here; the mesocortical dopamine pathway. Specific affected areas within the prefrontal cortex include the dorsolateral prefrontal cortex DLPFCresponsible for key components of cognition and executive function, and the ventromedial prefrontal cortex VMPFC responsible for components of inhibition and emotional response. Taken together, the mesocortical dopamine pathway affects the cognitive component of reward processing [ 4345 ].

The I-RISA model integrates the increased salience of learned drug-related cues resulting from the aforementioned positive and negative reinforcement of the addictive behavior with newly developed deficiencies in top-down inhibitory control. This leaves the individual vulnerable to reinstatement of the behavior, and two primary mechanisms have been identified; cue-induced reinstatement and stress-induced reinstatement [ 4345 ]. Anti-Reward George Koob proposed an expansion of the second stage of addiction.

In the opponent-process model of motivation, a-processes reflect positive hedonic effects and b-processes reflect negative hedonic effects. The application in addiction is that a-processes occur first and reflect tolerance. In contrast, the b-processes arise after the a-process have concluded and reflect withdrawal.

Solomon and Corbit [ 52 ] used skydivers as an example of the opposite, wherein the novice skydivers experience great fear when they jump b-process and some relief when they land a-process. As they repeat the behavior, the balance shifts such that experienced skydivers experience some fear when they jump but great relief when they land. Koob [ 51 ] overlays a detailed biologic model onto the psychological opponent-process theory. The aforementioned elevated levels of dynorphin further elevate CRF, and the engagement of these systems brings about many of the negative affects linked to the withdrawal stage.

Compounding the problem, the brains anti-stress system also becomes dysregulated, as evidenced by decreases in neuropeptide Y a natural anxiolytic in the brain.

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The reward system subsequently develops an altered set-point, leaving the individual vulnerable to relapse and dependence. Neurobiology of Learning, Habit, and Motivation While both the Anti-Reward and I-RISA models include learning components, other theories of addiction focus primarily on the learning aspects of addiction, and the biological underpinnings thereof.

Use a USB flash drive or an external drive to put your porn on.

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Hide it somewhere you can remember, and if someone sees it. You can create a password-protected, encrypted archive by using software such as 7-zip, which offer AES standard encryption.

However, you'll have to remember to delete the extracted files every time, once your finished viewing. You should always use a shredder program you should find it somewhere in your antivirus suiteor a secure wipe program such as C-cleanerto "overwrite" your deleted data, in order to make it difficult for someone to "recover" your deleted data, and catch you.

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This especially applies to deleting things like browser history. Laptops are the best because you can move your laptop so only you can see it and you can close the lid so nobody else can see it. For even more privacy, you can find and store porn on your mobile phone, tablet or other portable devices with an Internet browser incorporated into it. If you have an iPhone, make sure to use the "Privacy" mode on safari. This mode does not remember anything you search and there will be no history saved.

Position yourself so that you can see approaching people before they can see your computer, giving you a chance to act. Do not use speakers when viewing porn, for obvious reasons.

Do not use noise-canceling headphones or in-ear headphones with rubber seals. These headphones will block out external sounds, so you won't hear others coming.

For best results, use iPod-style earbuds. Also, take out one earbud so you can listen to the film with one ear and listen to your surroundings with the other. Hearing is more important than you may think.

This mainly applies to mobile or portable devices, which can be kept in places that would raise suspicion. Put the device in a sensible place such as on a table or next to a charger when you have finished using it. The more porn you look at, and the more often you look at it, the more likely you are to get caught. Reduce the time you spend looking at porn if you really want to reduce the likelihood of getting caught.

Your imagination is your greatest tool.

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This is a bit of an obvious point, but don't leave the window minimised when you're away in case someone else wants to use the computer. Part 2 Browsing Securely 1 Use incognito mode. This will remove everything from your browser history and will not affect the Google autocomplete. If you're not browsing incognito, make sure that you frequently clear your browsing history.