Another recent model draws together the concepts of alliesthe-sia and interoception to account for addiction (Paulus et al., 2009). Alliesthesia refers to the notion that whether or not a stimulus is rewarding or punishing depends on the internal (bodily) state of the individual (Cabanac, 1971). Negative alliesthesia is where repeated administration of a stimulus reduces its rewarding nature, for example the hedonic effects of drugs wearing off as the brain and body homeostatically adjust over time. Positive alliesthesia is where repeated administration (or omission) of a stimulus changes the internal mieliu in such a way as to increase its rewarding effects; this is the case of the subjective effects of smoking progressively turning positive in tobacco users. Alliesthesia is believed to have an important influence on the regulation of pleasure. We experience reward based on an evaluation of the stimulus relative to current internal state, and then engage regulatory mechanisms that maxi-mize the hedonic aspects of internal state (Cabanac, 2001). Key to this regulation is the comparison of the homeostatic state emerging from the body proper and some kind of central representation of desired internal state. Again, the insula is seen as the central hub of this interoceptive comparator mechanism. Via reciprocal connec-tions with the striatum, a ‘body prediction error’ can be calculated, which indicates to what extent the current state is meeting the desired state and hence is rewarding. Repeated drug use can be seen as resulting in ongoing disrup-tion of actual current body state (via peripheral effects) and central representations of ideal body state (via central neurotransmitter effects). Over time, individuals will become less sensitive to the positive hedonic hit of the drug (negative allesthesia) but more sensitive to the predicted pleasurable aspects of drug when under withdrawal or stress (positive allesthesia), changing the nature of the bodily signal. It is further proposed that this allostatic dysreg-ulation leads to an increase in body prediction error (coded in the insula), and an increased rate of decay of the body prediction error over time. This can elegantly model the shift from impulsive drug use in the early stages of addiction (linked to positive reinforce-ment mechanisms) to compulsive drug in later stages of addiction (linked to negative reinforcement mechanisms). However, exactly how and why long-term drug use would impact on prediction error is relatively under-specified. Goldstein et al. (2009) propose that in addiction dysfunction of the interoceptive system not only impacts the processing of drug cues but also involves broader alterations of emotional awareness. This account builds on the notion that the insula plays a major role on (i) subjective emotional experience, and (ii) body predic-tion error, both of which are needed to “sense” the actual state of the body and to change behaviour accordingly. Drug-induced dam-age to the insula would interrupt the interoceptive input signaling the actual state of the body. This interoceptive input conveys the internal signals that indicate a problem, such that its interruption may lead to impaired awareness and denial of the disorder. Intero-ceptive dysfunction would also maximize the mismatch between actual bodily input (either related to incentive motivation towards drug cues or to error signals that index prediction failures) and goal-directed behaviour. For example, addicts show a pronounced discrepancy between their low subjective emotional response to drug-related pictures and their high preference for these pictures during a probabilistic learning choice task (Moeller et al., 2010). Therefore, this account posits that the link between interoception and awareness contributes to explain some of the phenomenolog-ical and cognitive–affective phenomena typical of addiction: poor insight, denial, or dissociation between intention and action.
References
Verdejo-Garcia, Antonio, Luke Clark, and Barnaby D. Dunn. 2012. “The role of interoception in addiction: a critical review.” Neuroscience and biobehavioral reviews 36 (8): 1857–69. doi:10.1016/j.neubiorev.2012.05.007.