Addiction to Altering States: Observable Tendencies Attributed to Learning and Neurology

By Philip J. Spelman
2011, Vol. 3 No. 10 | pg. 2/2 |

Studies of self-control provide a plausible description of the process occurring when drug addicts act in favor of taking drugs achieving short-term reinforcement instead of abstinence for long-term benefits. “Self-control” is “a matter of choosing a large delayed reward over an immediate small reward” (Domjan, 2006, p. 184). One mathematical function used to describe self-control is the value discounting function, which describes the value of a positive reinforcer based on the amount of time that must be waited before receiving the reinforcement. Continued use in spite of punishment (negative consequences) suggests that the reinforcement values of the short-term effects of drugs are greater than the long-term value of avoiding negative consequences (Domjan, 2006). It is then quite logical that predictors of more immediate reinforcement will be more attractive than others.

Salience, in the form of sensitization to a stimulus, is observable in both behavioral and neurological studies. “Sensitization is extremely long-lasting, for example, lasting for up to a year in rats…persistence of sensitization may be comparable to persistence of drug craving in humans, a devastating feature of addiction that makes lasing recovery very difficult” (Kauer, 2004, p. 450). The idea of conditioned homeostatic responding is well supported in theory and by recent neurological and behavioral investigations.

It was shown that the homeostatic mechanism can account for the appearance of withdrawal symptoms. Domjan (2006) writes that “drugs often cause physiological challenges to homeostasis that trigger unconditioned compensatory reactions” (p. 102). Remember that, upon contact with stimuli that predict reinforcement, salience for those stimuli increases and they are more readily noticed and responded to than other stimuli. It is also true that, just as Pavlov’s bell could trigger salivation in his dogs, so can the repeated encounter with stimuli predicting the onset of a homeostatic imbalance trigger a compensatory response prior to the onset of the imbalance. Domjan (2006) writes, “The cues that become associated with the drug-induced physiological challenge can come to elicit these compensatory reactions as anticipatory or feed-forward conditioned responses” (p. 102). What has been established is that withdrawal symptoms can be classically conditioned, and thus their appearance can be predicted by the presentation of drug-related stimuli. It is said then that “craving in habitual drug users…is a manifestation of these drug anticipatory conditioned responses” (Domjan, 2006, p. 102).

Many approaches to understanding the phenomenon of craving resort to more recent neurological systems found to be engaged during activities involving actual reinforcement or presentation of reinforcement-related stimuli. For example, when Carlson (2004) describes increase in salience resulting from reinforcing experience, he says that “the stimuli associated with drug taking become exciting and motivating – a provocation to act” (p. 516). He follows this with the claim that when a person with a history of drug use sees or thinks about those stimuli, they experience craving, “an impulsion to take the drug” (Carlson, p. 516). Carlson (2004) is careful to note, however, that the impulsion to take the drug is not necessarily due to a drive to relieve an unpleasant feeling (i.e. withdrawal symptoms due to compensatory responses). To illustrate the associational impacts of the reinforcing experience, Carlson (2004) cites several studies that used PET technology to observe brain activity during exposure to drug-related stimuli.

Carlson (2004) mentions a report that says “most functional imaging studies show activation of the orbitofrontal cortex and the anterior cingulate cortex when taking or craving an addictive drug” (p. 516). In one study, neural activity was measured in abstinent cocaine users using PET scans to show neurological responding to drug- or non-drug-related stimuli. With respect to classical conditioning and what has been said about salience, theoretically attention should not be drawn to anything that does not signal a reinforcing stimulus. In a neutral-themed interview, participants described their genealogy. In the second interview, to induce a craving state, participants were asked to describe their own methods of cocaine preparation. The resulting PET images showed typical neural activity across the brain during the neutral interview. In the cocaine-themed interview, however, in addition to the activity present in the neutral condition, there was a marked increase in activity in the orbitofrontal cortex while the subjects were craving cocaine (Carlson, 2004, p. 516).

Motivation, in light of these theories, is the direct result of homeostatic imbalance. Compensatory responses conditioned to cocaine-related stimuli might create an imbalance – in the absence of cocaine – as the responses are counteracting a non-existent imbalance. In essence, conditioned withdrawal is believed to be non-drug induced withdrawal symptoms. As was previously mentioned, the quickest way to alleviate unpleasant withdrawal symptoms is to use the drug again (McKim, 2006).

Similar to the studies cited by Carlson (2004), in the introduction to their investigation, Due, Huettel, Hall, and Rubin (2002) mention two studies that examined neural activation by drug-related stimuli. One of the studies showed “significant activation in the amygdala, anterior cingulate, and temporal pole, while the other detected significant activation in the dorsolateral prefrontal, medial orbitofrontal, temporal, retrosplenial, visual, and temporal/parietal corticies” (p. 954). These areas are commonly mentioned with respect to motivation, reinforcement, and drug addiction.

Due et al. (2002) hypothesized that, although previous “addictive-cue” studies tended to focus on the limbic brain regions typically considered to be involved in reinforcement, two “distinctive neural circuits might be activated by smoking cues” (p. 954). The predicted circuits were a reward circuit and a visuospacial attention circuit. The reward circuit, which was previously identified in animal studies, consisted of the “mesocorticolimbic regions that include the ventral tegmental area, nucleus accumbens, amygdala, hippocampus, medial dorsal thalamus, ventral pallidum, and prefrontal cortex” (Due et al., p. 954). This circuit was already known to be activated by consumption of addictive substances, but the researchers predicted that it might be activated by predictors of the availability of the addictive substances (i.e. stimuli associated with the drug).

The researchers’ prediction is a neurologically-founded support for the idea of conditioned homeostatic responses, in that the homeostatic responses could result from classically conditioned cues. So neural activity was predicted to occur in areas known to be highly associated with learning (via reinforcement) as a result of exposure to stimuli relating to smoking; if participants should show activation and report craving, it would support the idea of a homeostatic mechanism as the source of drug craving. The findings of the study support the ideas of salience, conditioned responding, and conditioned homeostatic responding.

Due et al. (2002) found that in the nicotine-deprived smokers, exposure to cigarette-related stimuli elicited greater neural activation in smokers than in non-smokers in mesocorticolimbic areas associated with reinforcement; also there was increased neural activity in areas involved in visuospatial attention. They report that their findings are consistent with the relatively new theories about the role of the “mesolimbic dopamine substrates in drug reinforcement” (Due et al., 2002, p. 959), which is part of the motivational control system (Due et al., 2002; Hyman et al., 2006; McKim, 2006). One of the key findings of this study was that activation occurred in the reward circuit, which traditionally has been thought to happen only in response to the use of drugs (not drug cues). The participants in the study received no drug, but the reward circuitry still showed activity.

The visuospatial activation seen in this study may be representative of the type of mechanism that allows the general search mode of appetitive behavior to succeed. After a stimulus is conditioned to signal the availability of a reinforcer, and has gained salience, it is believed to be integrated into the learning and memory system in the motivational control system of the brain (McKim, 2006).

From all that has here been presented, there are many questions and considerations that should be addressed in future research. A comprehensive model of addiction will be complex and will include recent neurological discoveries (e.g. neurotransmitters, specific pathways, cerebral blood flow, etc), traditional theories and proposed mechanisms, and the general neural systems, such as the motivation control system proposed by McKim (2006). There appeared to be a lack of studies on normal drinking and drug behavior.

To close this preliminary attempt it may be interesting to note that in the motivation control system, the cortex does not receive information from the reinforcement system, but does send information to it (McKim, 2006); this supposition lends itself to a possible explanation of the “irrational” behavior displayed by drug addicts who use in spite of negative consequences. Assuming the motivation system begins at the VTA (reinforcement system), after the nucleus accumbens removes inhibition of the basal ganglia and movement begins, the cortex is made aware of some sort of imbalance. The imbalance will only be corrected, however, when the VTA ceases eliciting a compensatory response.

The cortex receives sensory information from the thalamus and communicates with the hippocampus and amygdala. It seems that the associations in the hippocampus and the amygdala would make the strongest contribution to the final response because they send memory and associative information (i.e. past response and following outcome) to the nucleus accumbens, which has ultimate control over the basal ganglia. If the taking of drugs is associated with alleviation of imbalance (withdrawal symptoms), then in a situation where there are several alternatives, the salience of drugs will make them the simplest, and most likely stimuli to engage.

However, it seems that in the case of the addict, even if the cortex decides against taking drugs, perhaps because of a negative experience, the association of drugs and relief may be so strong that any inhibition on the part of the cortex will be insufficient to change the direction of the behavior as it is the nucleus accumbens, and not the cortex, that activate the general search movement. It follows from this type of system that an imbalance and strong salience might allow suppression of the cortex itself, leading to inability to “decide” to use a drug.

This discussion has touched on theories and behaviors (from neurological and observational studies) involving classical conditioning in general, sequential organization and directed behavior, set point or homeostatic theories and mechanisms, withdrawal as homeostatic (compensatory) response, the motivational control system and its subsystems, stimulus salience, stimulus generalization, schema theory, habituation and sensitization, and several other theories and research. Although this approach attempted to integrate some theories and more recent discoveries, addiction and drug use in general are still very complex. There is much more that needs to be addressed and follow-up research on this investigation will attend to applications of new research to specific learning theories in more depth with the aim of relating them to the mechanisms of addiction.


References

American Psychological Association. (2000).Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Washington, DC: American Psychological Association.

Carlson, N. R. (2004). Foundations of psychological psychology (6th ed.). United States: Allyn & Bacon.

Domjan, M. P. (2006). The principles of learning and behavior: Active learning edition (5th ed.). Belmont, CA: Thomson Wadsworth.

Due, D. L., Huettel, S. A., Hall, W. G., & Rubin, D. C. (2002). Activation in mesolimbic and visuospatial neural circuits elicited by smoking cues: Evidence from functional magnetic resonance imaging. American Journal of Psychiatry, 159, 954-960.

Goldstein, R. Z., & Volkow, N. D. (2002). Drug addiction and its underlying neurobiological basis: Neuroimaging evidence for the involvement of the frontal cortex. American Journal of Psychiatry, 159, 1642-1652.

Hyman, S. E., Malenka, R. C., & Nestler, E. J. (2006). Neural mechanisms of addiction: The role of reward-related learning and memory, Annual Review of Neuroscience, 29, 565-598.

Kauer, J. A. (2004). Learning mechanisms in addiction: Synaptic plasticity in the ventral tegmental area as a result of exposure to drugs of abuse. Annual Review of Physiology, 68. 447-475.

McKim, W. A. (2006). Drugs and behavior: An introduction to behavioral pharmacology. Upper Saddle River, NJ: Prentice Hall.

McVee, M. B., Dunsmore, K., & Gavelek, J. R. (2005). Schema theory revisited. Review of Educational Research, 75(4), 531-566.

National Institute on Drug Abuse. (2007).Drugs, brains, and behavior: The science of addiction(NIH Publication No. 07-5605 ). United States.

Quickfall, J., & Crockford, D. (2006). Brain neuroimaging in cannabis use: A review. Journal of Neuropsychiatry and Clinical Neurosciences, 18(3), 318-332.

Siegel, S., & Ramos, B. M. C. (2002). Applying laboratory research: Drug anticipation and the treatment of drug addiction. Experimental and Clinical Psychopharmacology, 10(3), 162-183.

Wrase, J., Makris, N., Braus, D. F., Mann, K., Smolka, M. N., Kennedy, D. N., Caviness, V. S., Hodge, S. M., Tang, L., Albaugh, M., Ziegler, D. A., Davis, O. C., Kissling, C., Schumann, G., Breiter, H. C., & Heinz, A. (2008). Amygdala volume associated with alcohol abuse relapse and craving. American Journal of Psychiatry, 165, 1179-1184.

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