The American Society of Addiction defines addiction as a chronic and relapsing disease of brain reward, motivation, memory, and related circuitry (Satel & Lilienfeld, 2013), a definition that has both positive and negative implications for those suffering from conditions such as alcoholism. Although labeling Dr. Smith’s uncontrollable craving for alcohol as a medical condition can greatly benefit how he is perceived by society and his treatment options, doing so trivializes the social and emotional aspects of the disease, which can greatly impact addicts’ recovery. The deleterious effects of recognizing addiction as a purely neurological disorder outweigh any benefits that addicts may gain in the long run.
Addicts are often viewed as “bad people” who are “morally weak” and lack self-control; providing a biological basis for this condition removes some of the blame from patients, who rarely choose to be addicts and are to a degree victims of their neurochemistry, and legitimizes their symptoms. It opens up the possibility for the development of pharmaceutical drugs that target disruptions in neural circuitry to restore the brain and maximize recovery. Calling addiction a neurological disorder places it amongst more traditional brain disorders, such as Parkinson’s disease, which can greatly improve the public’s impression of these individuals. On a broader level, it can encourage health insurance companies to expand their coverage for treatments for addiction and the government to provide more funding for treatment and research on it (Satel & Lilienfeld, 2013). On a more personal level, this classification removes a tremendous amount of emotional burden that can have a strong impact on patients’ mental health and motivation for recovery. A stigma as heavy as this one has intimations that can affect one’s reputation and career, such as the loss of clients and or one’s license to practice medicine. Individuals, such as Dr. Smith, are pressured to live with their disorder in shame until a catastrophic event, such as a lawsuit, reveals it after it has already been established and in a dangerous light that only perpetuates the stigma. Debunking the belief that addiction is a consequence of character flaws prompts people to more readily seek and accept treatment earlier without fear of attack on their abilities and morals, actions that could prevent tragedies such as the amputation of Dr. Smith’s patient.
The power of neurochemistry is demonstrated in a study conducted by Falk et al. (2012), which found neural responses that were recorded while viewing anti-smoking campaigns to be more indicative of action than conscious thought. This finding lends support to the idea that even if we desire one thing, to quit smoking or drinking, our mind may not allow us to because it is under the control of processes that operate outside of conscious awareness. If we do not always have autonomous power over actions, actions that are consequences of biological abnormalities should not be held against us. Understanding brain circuitry is a crucial step in developing treatments that change the brain into a less “addictive” state that promotes self-control and willpower to stop an action.
However, identifying alcoholism as a “brain disease” overemphasizes the contribution of biology and the value of brain-level resolutions and understates relevant psychological and social causes and interventions. Many addicts, including Dr. Smith, pose that their craving and actions are uncontrollable, but in actuality, their addiction is not entirely inborn; they made the original explicit and voluntary decision to try alcohol and ultimately chose to continue drinking, knowing it may transform into an uncontrollable, involuntary habit. Neurochemistry is only one of many factors that contribute to the development of addiction. Patients may initially be drawn to a drug for a number of reasons that are not specifically associated with brain regions, such as the need to assuage pain caused by “persistent self-loathing, anxiety, alienation, intolerance of stress or boredom, and loneliness” (Satel & Lilienfeld, 2013). The “brain disease” label masks the psychological elements that interact with neurological factors and appears to exempt addicts from social norms, furthering the notion that addiction can be fixed with solely a medical cure. Ending addiction requires incredible personal agency and a serious effort to change one’s patterns of thought and behavior (Satel & Lilienfeld, 2013), but in order to be able to do that, an addict must accept a certain level of personal responsibility. An individual must have the motivation to act and the mindset to cope with the difficulty of achieving sobriety otherwise addiction will prevail. The present definition of addiction as a brain disease does not account for these important non-biological components that can either perpetuate or eliminate addiction.
The importance of these psychosocial aspects is highlighted in rehabilitation programs that use non-medicated methods. For example, Project HOPE utilized the power of punishment, specifically brief incarceration, to reduce the temptation of further drug use and the likelihood of relapse (Satel & Lilienfled, 2013). This treatment program underscores the fact that the brain circuitry and neurology of addiction do not need to be understood in order to effectively treat addiction. Drug addiction and symptoms can manifest differently across patients as a result of differences in personal motivation, sensitivity to drugs, and social context; these differences could be used to customize treatments that target specific elements of addiction. Additionally, the definition can have a dangerous effect on the emotional health of addicts; calling addiction a “chronic and relapsing” condition implies a long-term battle that is futile and that relapse that is inevitable. Stating addicts’ desires and actions are uncontrollable insinuates that this condition cannot be changed, which can prompt addicts to question why they should even attempt to beat addiction if they are destined to return to their addictive actions. As Satel and Lilienfeld (2013) argue, addiction is unlike many other illnesses, such as pneumonia, where success is almost guaranteed with the appropriate drug; without the ambition to act against one’s own body and mind, one will not be motivated to even take the medication that could correct the disrupted neurochemistry.
Although there is much society and individuals can gain from recognizing addiction as a brain disease, the consequences of doing so may be harmful enough to nullify any progress that is made. Thus, the current definition of addiction must be modified to incorporate both biological and psychosocial components that influence the development and recovery from addiction so that effective, comprehensive treatments can be developed.
Understanding Addiction as a Brain Disease
Evaluating the Effectiveness of Neuromarketing
More and more companies areusing neuromarketing to increase the power of their brand, however, the true success of their methods still remain unclear. Neuromarketers are beginning to use brain scans that are recorded while participatants view their promotions to predict purchases of their product; although their findings are intriguing and appear promising, there is no definitive evidence that their strategies are effective.
The public information we currently have on neuromarketing strategies are based on research conducted by consumer neuroscientists and neuromarketers; depending on their research goals, data may be interpreted in ways that lead to biased conclusions and support a specific theory. While consumer neuroscientists are interested in how the brain functions during choice making, neuromarketers are more interested in what the individual actually chooses (Satel & Lilienfeld, 2013). Because neuromarketers’ motives are more concerned with profit, they may have more reason to need and look for corroboration. Not only do neuromarketers not provide clear and detailed documentation of their methods and research protocols, but companies often also use different formulas for analysis, so it is difficult to compare findings and to determine the validity of each (Satel & Lilienfeld, 2013). Context can also have an enormous influence on how the results of imaging studies are interpreted and even the minutest differences in an experimental design can create enormous differences in findings. Without given specific information to test repeatability and generalizability of private companies’ results, it is extremely unclear whether their research can be trusted and used by other companies to predict purchasing decisions.
Neuroscientists currently have some understanding of distinct brain areas that are related to the anticipation of gain and loss, information that companies are taking advantage of. (Satel & Lilienfeld, 2013). It is well understood that the medial orbitofrontal cortex and ventral striatum are involved in the regulation of emotions and in the “encoding of the ‘value’ of experiences,” (Berns & Moore, 2013; Satel & Lilienfeld, 2013). When Berns and Moore (2011) tried using function magnetic resonance imaging (fMRI) to predict the popularity, or sales, of music artists, they found that activity in the ventral striatum, which was strongly correlated with the number of sales, was more predictive than subjective reports provided by participants. They proposed that brain responses are more accurate reflections of likeability as reward-related regions reflect sub-conscious processes while subjective reports may be subject to framing effects of the conditions in which participants are asked how much they like something, which can affect processing of stimuli, one’s comparison of the current item to similar items that the participant already has experience with, and one’s prediction of usefulness (Berns & Moore, 2011). Scientific studies support the opinion that uncontrollable physiological responses to a stimulus are more accurate than thoughts resulting from cognitive processes that can manipulate and alter experiences.
However, these studies neglected many factors that could invalidate their conclusions and require reinterpretation of their data. Even if companies are able to correlate a stimulus with a specific brain region, there remains the question of whether the stimulus will cause similar brain activation patterns across all consumers. Individual differences in desires and preferences may enhance or reduce activity in variant regions throughout the brain, thus reverse inference is not necessarily accurate and brain activation patterns obtained from participants cannot be assumed to predict the responses of the larger population. Additionally, when consumers’ neural responses are evoked and recorded, their readings may not reflect responses that would occur when the advertisements are viewed in real time. The activation measured in a laboratory may reflect a participant’s anticipation of viewing something rather than their response to what they are viewing at that moment (Satel & Lilienfeld, 2013). Brain patterns may also vary depending on the mode it is looking at (video, text, images, or different combinations of them). Different brain regions are required to process still images vs. moving stimuli; to listen vs. to read words; and to process black and white vs. color. Our brain and emotions respond differently to the same information based on how it is framed, so different methods of presentation may lead to different brain patterns. Because neuromarketers aim to maximize consumers’ positive responses, they use as many features as possible to maximize the effect of their marketing, which is easy to do in an age where there is a plethora of technology that allows us to integrate different modes. When these campaigns and advertisements are put to the test in studies, it is difficult to separate out the effect of each feature from the rest (Satel & Lilienfeld, 2013). It is hard to determine whether a combination of features produces a synergistic or additive effect in the context of brain networks that are as complex as ours. If these possible confounds are not controlled for before analysis or comparing studies, data will be misinterpreted and erroneous conclusions about the impressive power of neuromarketing will be declared.
While some studies, such as Berns and Moore’s (2011), suggest activation of reward-related and emotion-related regions can be used to predict one’s desire for a product, even if we are able to achieve success in persuading clients to want a product, this desire does not necessarily translate into real purchases. Purchases are influenced by many external factors and cognitive processes, which are at work after we view an advertisement, such as self-control, reason, practicality, price, mood, and social effects. With so many influences working at once, it is hard to understand how they interact and how their interactions translate into real action; current studies only address some of the factors that are present at the time of viewing. The present lack of substantial evidence for effective neuromarketing calls for further studies with better, more controlled and specific experimental designs.
Considering the Validity of Lie Detection Tests
A lie and the act of telling a lie are both extremely complicated concepts to identify in real-life, let alone a brain scan. The practice of detecting a lie through brain activity is gaining more attention and neuroscientists are currently attempting to use activation patterns to distinguish truth from non-truth, however, the applicability of the findings made within a laboratory to lying in real-world situations is still doubtful.
The use of lie detection tests has long been controversial due to its debated reliability, so the validity and acceptable usage of lie detection results depend on the circumstances and the people the results affect. Results would be valid in unserious situations that do not endanger the lives of other individuals or cause people unnecessary stress, such as withholding test results until the doctor is certain of his interpretation rather than informing and worrying a patient before verification. If prior to the test researchers were able to confirm that deception and truth telling engage different neural mechanisms that manifest as different activation patterns, it would be valid to also use the results in more serious circumstances. In theory, deception requires more memory and executive functions than truth telling as when you lie, specific brain regions work harder to inhibit honesty and create a falsehood (Farah et al., 2014), but since this concept is still under investigation, use of lie detection results should be limited to circumstances that do not require absolute certainty or honesty, such as telling white lies to avoid hurting someone’s feelings or in trivial situations. If the results were to be used in consequential situations, they could be used as a pre-screen, signaling the need for further investigation, rather than as absolute evidence.
Because Dr. Smith’s actions directly affected the health of his patient, his lie detection results must be taken more seriously. If lie detection tests are accurate and reliable, his results could still be considered invalid for a number of external factors, such individual traits. If Dr. Smith was a habitual liar or generally not very excitable, he would show little or no activity in areas that are normally activated during conflict. On the other hand, he could also produce a false positive if his brain was more easily excitable than the average individual, however, determining individual hyper- and hypo-sensitivity is difficult and impractical to determine. As the reliability of lie detection tests is being studied in more depth, methods of beating the test are becoming public knowledge; if Dr. Smith were aware of these tricks, his test results would be highly inaccurate and should be removed as evidence.
Lie-detection tests are considered unreliable for a number of reasons. Although brain fingerprinting aims to detect whether specific information is present in the brain, there remains the problem that not everything we experience is remembered and what is remembered can often be modified, which makes it difficult to identify fake memories from memories of real events. It is possible to create a lie that one truly believes in so much that it becomes a “real” memory. Through constant rehearsal, individuals can trick their brains into believing a lie through familiarity and changed brain connections (Satel & Lilienfeld, 2013). Brain variability between individuals also contributes to the inconclusive nature of lie detection results. As Satel & Lilienfeld (2013) state, “there are many ways to lie, but only one way to tell the truth,” which allows individuals to utilize different methods for constructing lies. Depending on which cognitive processes are needed to construct a type of lie, different brain activation patterns would be observed. So far in comparing patterns, no region or set of regions have been identified as always being activated in all people when they are telling a lie and always silent when they are not telling a lie. Not all lies are psychologically similar, and thus, can manifest differently physiologically (Satel & Lilienfeld, 2013). Each type of lie demands different circuitry depending on the degree of rehearsal and emotional investment the lie has. It is possible that processes other than deception that are unknowingly being activated may contribute to brain activity patterns (Farah et al., 2014), which can compromise the results. These tests measure non-specific brain signals of effort or inhibition and emotion can change the circuitries of lying and truth-telling, including memory, inhibition, and cognitive control (Farah et al., 2014); a highly emotional event, such as an interrogation, may hypersensitize the circuitries involved in deception, which can cause a false positive result. Although fMRI-based lie detection tests may appear more reliable due to the “physical” evidence it seems to provide, in actuality they may be just as unreliable as traditional polygraph tests, as the brain is an extremely complex system that is made up of intricately connected networks that are difficult to analyze separately.
Many of the studies that have attempted to determine the effectiveness of fMRI-based lie detection contain numerous experimental design confounds. The largest concern is that these studies are not representative of the lying that occurs outside of the laboratory setting. These studies typically use healthy, educated undergraduate students who are cooperative and have little personal relevance with the lies they are telling. They do not suffer any consequence from lying, so there is no emotional stake in these controlled settings. Instructed lies may produce an activity pattern that does not reflect deception or may reflect other neural processes that are also activated as a result of the experimental task (Farah et al., 2014). In contrast, no one instructs suspects to lie in a specific way and they have a lot more at stake; an interrogation is highly emotional and personally relevant event that may prompt suspects to act a particular way. Guilty suspects may try to beat the test, such as by wiggling a finger or a toe to reduce accuracy (Farah et al., 2014), while participants have no inclination to attempt such an act. Habitual liars and criminals may naturally show lower activity in some regions, such as the ACC and amygdala, during lying, while innocent suspects may exhibit more activation while truthfully answering questions about highly emotional and relevant events, which might require more effort and control (Farah et al., 2014). These situation-specific variables make it difficult to assess the applicability of what researchers discover in their laboratories.
Despite the sophistication of fMRI-based lie detection tests and our understanding of various brain regions’ roles in truth and lie telling, the large number of situational and individual factors that must be considered every time brain scans are evaluated make our current version and interpretation of lie detection tests to be indeterminately useful in real-life circumstances.
Examining the Connection Between Brain Activity and Action
The emergence and increasing prominence of Neurolaw in the past decade have important implications for the fate of criminals on trial and on parole. Brain scans have frequently been used to indicate abnormal neural activity that presumably prompt action or lack thereof. After two years in prison, Dr. Smith was given a functional MRI scan as part of his neuropsychological assessment that would determine his parole status. The ACC is known to be associated with error processing, conflict monitoring, and avoidance learning (Aharoni et al., 2013) and the amygdala is known to be a mediator of impulses and emotions; Dr. Smith revealed reduced activity in both of these regions in his brain scan, leading to the conclusion that he may be unfit for release as he may be incapable of regulating his behavior and emotions. Although atypical brain scans may indicate some cognitive deficiencies, it should not be used to determine the fate of individuals, as there are many alternate explanations for such scans.
It is often hard to deny or argue against physical evidence provided by an organ that is responsible for our thoughts and actions. Damage to the ACC is observed to cause “changes in disinhibition, apathy, and aggressiveness” and lower activity is correlated with a higher probability of rearrest in criminals (Aharoni et al., 2013). Reduced activity in the amygdala suggests less control over primitive impulses such as anger and fear (Satel & Lilienfeld, 2013). Characteristics that are associated with reduced activity in these two areas are common amongst criminals and often drive their criminal activity. Should Dr. Smith decide to continue practicing as a doctor, it is a true concern that he may be a public threat if he has an innate inclination for violence and for low behavior regulation. His brain scan predicts he is likely to re-commit behaviors that led to his incarceration, such as arriving to work drunk and making dangerous mistakes that harm his patients, so it may be wise to deny Dr. Smith parole if his behaviors have not and will not change.
However, this conclusion is not absolute; fMRI scans can be interpreted a number of other ways that would lead to a drastically different fate for Dr. Smith. The apparent abnormality observed, reduced activity in the ACC and amygdala, may not reflect a true abnormality in the function of these regions. The “normal” brain used as a standard brain for comparison is a composite of averaged brains; people can naturally fall above or below this average while still being considered within normal range, thus reduced activity does not conclusively indicate a problem. Individual differences in the exact localization of functions, activation patterns, and cognitive processes are neither rigid across time or individuals, so declaring that an activity or lack of activity in an area causes one specific behavior is not convincing. His reduced activity may be a result of his experience as a doctor. The amygdala manages more than just fear; it also mediates our responses in “unexpected, novel, unfamiliar, or exciting” situations (Satel & Lilienfeld, 2013). Working in a hospital very likely exposed him to the aforementioned circumstances often; the brain becomes more efficient at a task if it performs it repeatedly, so Dr. Smith may simply be extremely efficient at handling unfamiliarity, which would lead to less brain activity. Amygdala activity may also be suppressed to prevent emotional attachment to patients, which could cloud judgment. Similarly, the ACC may exhibit lower activity because Dr. Smith is experienced with handling conflict. His experience as a physician may have affected his brain rather than his brain affecting the actions that he was convicted for.
The brain is an organ with incredible plasticity; it is constantly reorganizing itself as a result of injury and experience. The fMRI scan considered for his parole review was taken after two years of being prison, an experience that could have greatly affected his brain circuitry. This brain scan may not reflect what his brain looked like prior to prison and his brain may reorganize again after being released from prison and living in a different environment. To say this present “abnormality” is relevant to his past criminal behavior or is indicative of future actions stretches the validity of conclusions that can be drawn, as not all people with “bad” brains (lesions or abnormal activation patterns) break the law (Satel & Lilienfeld, 2013).
Conclusions drawn from brain scans are not as objective as they appear; many different stimuli and processes can illuminate the same brain region as brain areas are often responsible for more than one function, so it is difficult to say with certainty which process is being called upon during a scan. Researchers can only speculate based on context or on previous knowledge of functions and emotions that are correlated with increased activity in a given brain region (Satel & Lilienfeld, 2013). It is also possible that we are still unaware of other functions that use these regions and that could have been active as the scan was taken.
The conditions and processing of the fMRI can also influence the amount of activation observed in the regions of interest. Firstly, an important question to consider is what was Dr. Smith doing during the scan? Did he perform a task or was he lying idly within the machine? If he did perform a task, was it relevant in content? For example, Aharoni et al. (2013) used a go/no-go task that tested criminals on impulse control, a process that is commonly disrupted in rule-breakers. Did the task Dr. Smith performed during his scan similarly reflect the recruitment or inhibition of processes that are relevant to his situation and responsibilities as a physician? Secondly, what kind of design was Dr. Smith’s task? Whether it was a blocked design or an event-related fMRI design could have influenced the results and the conclusions that were drawn from them. If a jittered event-related design, where fixation periods are interspersed with the conditions, was used, activity associated with a condition of the task can be compared to baseline for comparison. For example, individuals with lower ACC activity made more errors in a go/no-go task, indicating difficulty inhibiting a reaction when required to do so. Thirdly, was his scan preprocessed? If smoothing was performed on his scan, his lawyer could argue that this prepreocessing step significantly altered amygdala activity more than those of other areas, as the amygdala is an extremely small brain region. Smoothing would average the brain regions surrounding the amygdala with the amygdala and if the surrounding areas were particularly active, the smoothed scan would show lower responses from amygdala. This preprocessing step could have diminished any activity that was present in the amygdala, possibly indicating an abnormality that is not truly there.
Studies in the past show strong correlations between reduced activity in a specific brain region and particular abnormal behaviors, but the lack of activity observed in Dr. Smith’s ACC and amygdala should not be used against him in his case for parole because there are many realistic explanations for the observed abnormalities that do not necessarily make him a threat to society. The judge should review both Dr. Smith’s background and the possible manipulations and misinterpretations of his brain scan before making a decision based on solely the brain scan itself.