Introduction
Drug addiction can be defined as a loss of executive control over maladaptive incentive habits (Belin, Belin-Rauscent, Murray, & Everitt, 2013). In 2018, there were 2,917 registered deaths in England and Wales related to poisoning by drug misuse, which was a 17% increase from 2017 and a 46% increase from 2008 (Statistics on Drug Misuse, England, 2019). According to this study, the number of deaths related to drug misuse are at their highest since 1993. Furthermore, the National Treatment Agency estimated the cost of drug misuse to the NHS to be approximately £500 million in 2014 (Williams, 2018). However, only a small proportion of those who initially use drugs develop addiction (Lopez-Quintero et al., 2011). Despite extensive research, the neuroscientific mechanisms underlying this devastating brain disorder remain poorly understood. It is imperative that we understand the risk factors of drug addiction, thus allowing clinicians to identify vulnerable individuals who are of higher risk and provide them with the support they need before it is too late.
Drug addiction involves elements of both impulsivity and compulsivity. Impulsivity is the tendency to act prematurely without foresight (Dalley, Everitt, & Robbins, 2011). It can be an individual endophenotype which may predispose some individuals to addiction and can be a key component in the early stages of the addiction process. Another theory is that drug consumption may result in structural changes in the brain, which further enhances impulsive behaviour and intensifies the addiction cycle (Koob & Le Moal, 2001). Compulsivity can be defined as persistent maladaptive behaviour, which has no obvious relationship to the overall goal and often results in negative consequences (Dalley, Everitt, & Robbins, 2011). Although sometimes confused, the two behaviours can be distinguished by their involvement in different aspects of response control during decision making processes, which is largely mediated by distinct (although still related) neural circuitry. Impulsivity is thought to facilitate the development of compulsivity and drug addiction is likely to involve a transition from impulsive to compulsive behaviour (Belin et al., 2008).
Experimentally, behaviours underlying addiction can be investigated by reversal learning, which measures behavioural flexibility. This is the ability of the individual to rapidly change between different tasks, mentally, in order to produce appropriate behavioural responses to the environment (Zhukovsky et al., 2019). The individual must actively suppress responses to previously rewarded behaviour, which is biologically and psychologically related to impulsivity and compulsivity. Thus, reversal learning can be used to indicate vulnerability for disorders characterised by impulsivity, such as drug addiction (Izquierdo & Jentsch, 2012). Rats are often used to model reversal learning and drug addiction because they provide excellent face validity and predictive validity (Spanagel, 2017). Furthermore, there is considerable overlap between rats and humans in the neuroanatomical substrates involved in drug addiction. This means that findings from experiments in rats can, with caution, be translated to humans.
During the initial stages of the discrimination reversal learning, an action is repeatedly paired with an outcome, allowing the individual to associate the two together (Hauser et al., 2015; Izquierdo & Jentsch, 2012). Throughout the training period, the subject begins to consistently perform the action that it has learned to be associated with the reward. The reversal learning rules can be deterministic, which is where every correct action always leads to a reward, or probabilistic. In the latter, the probabilities of obtaining a reward change unpredictably and the subjects have to learn these changes based on previous trials (Hauser et al., 2015). The reversal phase is then implemented once the subjects have reached a certain threshold for accuracy on the discrimination behaviour. At the reversal stage, the trained behaviour is no longer rewarded, although it still dominates initially due to the training history (Izquierdo & Jentsch, 2012). Thus, reversal learning tests the ability of the subject to suppress the initially trained response and instead display the behaviour which it previously learned to be unrewarded.
An inability to disengage from trained behaviour after a contingency shift reflects a compulsive or habitual response tendency (Izquierdo & Jentsch, 2012). Rats exposed to cocaine show impaired reversal learning, which reflects their inability to respond to external feedback in order to guide their behaviour and instead they continue to seek cocaine despite its devaluation (Miles et al., 2003) or the risk of punishment (Pelloux et al., 2007). Furthermore, research has shown that highly impulsive rats exhibit greater compulsive cocaine-seeking behaviour by tolerating mild foot-shock punishment readily in a cocaine seeking paradigm (Belin et al., 2008). Thus, impulsivity is an endophenotype which contributes to the persistence phase of cocaine self-administration, which may be predictive of addiction in rats.
There are key neural circuits and networks preserved across many species which are responsible for discrimination reversal learning, such as the frontal cortex (Izquierdo & Jentsch, 2012). In particular, the orbitofrontal cortex (OFC) has an important role in behavioural flexibility. Normal acquisition of the initial discrimination but impaired reversal learning is often observed in rats with OFC lesions (McAlonan & Brown, 2003). These rats also showed perseverative responding to the previously rewarded behaviour. In addition, OFC damage leads to inflexible associative encoding in the basolateral amygdala (BLA) (Stalnaker et al., 2007). Rats with bilateral neurotoxic OFC lesions took longer to learn the reversal rules in a reversal learning task. However, if the rats also had BLA lesions, then this impairment was non-existent. This demonstrated the potential involvement of the OFC in updating associative encoding in the BLA, thereby allowing the OFC to facilitate cognitive flexibility.
It is clear from the above findings that there are structural changes which are involved in the behavioural phenotypes associated with cocaine self-administration. However, it is still unclear whether these structural changes in the brain are present prior to cocaine addiction, thus acting as an endophenotype which may predispose to addiction, or whether these changes are caused by the consumption of the drug itself. To investigate this, 52 rats were given baseline MRI scans on postnatal days 21, 35 and 63, after which they underwent behavioural phenotyping with reversal learning being one of the behaviours assessed. Following this, the rats had another adult pre-cocaine MRI scan before being trained to self-administer cocaine. To analyse this data, a combined computational and behavioural approach was taken to investigate any underlying behavioural and neuroanatomical biomarkers which may predispose to cocaine addiction.
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Executive Control Loss in Drug Addiction.
(2022, July 14). Edubirdie. Retrieved December 25, 2024, from https://edubirdie.com/examples/analysis-of-drug-addiction-as-a-loss-of-executive-control-over-maladaptive-incentive-habits/
“Executive Control Loss in Drug Addiction.” Edubirdie, 14 Jul. 2022, edubirdie.com/examples/analysis-of-drug-addiction-as-a-loss-of-executive-control-over-maladaptive-incentive-habits/
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Executive Control Loss in Drug Addiction [Internet]. Edubirdie.
2022 Jul 14 [cited 2024 Dec 25].
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