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Earlier neurobiological models of substance addictions proposed that addiction is the product of an imbalance between two separate, but interacting, neural systems: (1) an impulsive and amygdala-striatum dependent system that promotes automatic and habitual behaviors, and (2) a “reflective” prefrontal cortex dependent system for decision-making, forecasting the future consequences of a behavior, and inhibitory control. These impulsive and reflective systems are analogous to Daniel Kahneman’s model of System I and System II thinking, or the Behavioral Activation System (BAS) and the Behavioral Inhibition System (BIS). Here, the reflective system controls the impulsive system through several distinct mechanisms that regulate impulses. However, this control is not absolute – hyperactivity within the impulsive system can override the reflective system. Most prior research has focused either on the impulsive system (especially the ventral striatum and its mesolimbic dopamine projections) as a mechanism promoting the motivation and drive to seek drugs, or on the reflective system (prefrontal cortex) as a mechanism for decision-making and impulse control. More recent evidence suggests that a largely overlooked structure, the insula, also plays a key role in maintaining addiction (craving). Hence, a triadic model of addiction incorporates these three systems that are associated with archetypal behaviors in addiction: craving, motivation to procure the drug, poor decision-making, lack of impulse control, and deficits in self-regulation.
The present research explored the cortical correlates of rewarding mechanisms and cortical ‘unbalance’ effect in internet addiction (IA) vulnerability.
Methods
Internet Addiction Inventory (IAT) and personality trait (Behavioural Inhibition System, BIS; Behavioural Activation System, BAS) were applied to 28 subjects. Electroencephalographic (EEG, alpha frequency band) and response times (RTs) were registered during a Go-NoGo task execution in response to different online stimuli: gambling videos, videogames or neutral stimuli. Higher-IAT (more than 50 score, with moderate or severe internet addiction) and lower-IAT (<50 score, with no internet addiction).
Results
Alpha band and RTs were affected by IAT, with significant bias (reduced RTs) for high-IAT in response to gambling videos and videogames; and by BAS, BAS-Reward subscale (BAS-R), since not only higher-IAT, but also BAS and BAS-R values determined an increasing of left prefrontal cortex (PFC) activity (alpha reduction) in response to videogames and gambling stimuli for both Go and NoGo conditions, in addition to decreased RTs for these stimuli categories.
Conclusion
The increased PFC responsiveness and the lateralisation (left PFC hemisphere) effect in NoGo condition was explained on the basis of a ‘rewarding bias’ towards more rewarding cues and a deficit in inhibitory control in higher-IAT and higher-BAS subjects. In contrast lower-IAT and lower-BAS predicted a decreased PFC response and increased RTs for NoGo (inhibitory mechanism). These results may support the significance of personality (BAS) and IAT measures for explaining future internet addiction behaviour based on this observed ‘vulnerability’.
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