Editor's Note: This article is the first in a two-part series on Neurofeedback in the Treatment of Substance Abuse. This article presents evidence of the neurological basis, specifically EEG dysfunction, underlying addiction that makes it such a complicated condition to treat, and explains how neurofeedback addresses cognitive, emotional and physical symptoms. The second part of this article will include a discussion of the efficacy models of neurofeedback and a review of the research applying neurofeedback to substance abuse treatment, as well as address the possible mechanisms of its effectiveness in addiction.
Over the last two decades a new research and clinical approach--neurofeedback--has shown promise in the treatment of substance abuse. This article addresses how it works, what makes it so effective, why it is a potentially important tool in addiction, the neurophysiological issues it might address, the existing promising research and, most importantly, that neurofeedback can be a significant adjunct to the therapeutic and counseling process with addicts.
The category of disorders associated with substance abuse is the most common psychiatric set of conditions affecting an estimated 22 million people in this country (SAMHSA, 2004). Furthermore, the disorder is accompanied by serious impairments of cognitive, emotional and behavioral functioning. These conditions and symptoms so significantly alter a person's brain and its functioning, that we often refer to the drug as hijacking the brain, making it very difficult to think logically and appropriately weigh the consequences of the drug related behavior.
Detoxified addicts have been shown to have significant alterations in brain electroencephalographic (EEG) patterns and children of addicts also exhibit EEG patterns that are significantly different than normal (Sokhadze et al., 2008, for review). This indicates that, not only are we dealing with the neurological consequences of drug-related behavior, but there appears to be a genetic pattern as well, that places certain people at greater risk for addictive behaviors. The complexity of these factors makes the treatment of addiction one of the most difficult areas of mental, emotional and physical rehabilitation.
Multiple factors in
Treating addiction is compounded by the many factors contributing to its onset and maintenance. Furthermore, the addiction itself masks many other clinical conditions that become more evident once the drug user becomes abstinent. In fact, it is frequently other psychiatric problems that lead to drug abuse as the addict attempts self-medication. It has also been shown that people with cognitive disabilities are more vulnerable, and more likely to have a substance abuse disorder (Moore, 1998). These impairments appear to include attentional issues as well as the hypo-functioning of the frontal cortex, sometimes referred to as the executive brain, where decision making takes place (Fowler, et al., 2007).
As a result, we are learning that no one approach has all the answers. Multiple mechanisms require multiple considerations and approaches. In addition, addicts are a diverse group, resulting in the need for many tools and approaches. It appears that programs offering the most diversified array of treatment modalities are the most effective (Vaccaro & Sideroff, 2008). That is also why, for example, most programs urge the inclusion of a 12-step program for ongoing support.
But how do you address the biological and genetic aspects while also addressing the traumatic and emotional factors, the social cognitive and attentional factors? How do you deal with the apparent "procedural memory" and conditioned factors that cause an abstinent addict, on his or her way home from work, to all of a sudden take an inappropriate turn and end up at the drug dealer? Neurofeedback appears to be a tool, a training that has the facility to address many of these factors associated with addiction.
History of promising treatments
Over the years, there have been a number of developments that have been promising in the treatment of addiction. Each time a new approach is identified, it is immediately seen as being the long sought after "silver bullet" that will solve the addiction problem. This occurred with the development of methadone, and later Levo-Alpha Acetyl Methadol (LAAM). When I entered the field in 1976, as a post-doctoral fellow of the National Institute of Drug Abuse, Naltrexone was gaining popularity. Naltrexone is a long-acting opiate antagonist that blocks the effects of opiates, such as morphine, heroin and codeine.
It was around this time that the importance of addiction-related stimuli was becoming widely recognized (Wikler, 1984). In research examining the conditioned aspects of addiction, it was found that stimuli associated with the drug using behavior could serve as conditioned stimuli that would trigger an unconditioned psychophysiological response that had similarities to withdrawal and included anxiety, fear and physiological arousal (e.g. Sideroff & Jarvik, 1980). This conditioned patterning of response lead to the proposal that relapse liability might be determined by exposing addicts to these conditioned stimuli and monitoring their responses (Sideroff, 1980).
Following this conditioning model, one potential mechanism of Naltrexone treatment would be the behavioral extinction of some of the conditioned associations of addiction. In other words, if the addict attempted to get high while on Naltrexone, the lack of reinforcing effect might lessen the conditioned effects of drug related stimuli. This, in turn, might reduce readdiction liability. All that needed to happen was for the addict to use, without experiencing any effect; a perfectly reasonable theoretical assumption. So, not only was Naltrexone expected to be successful in keeping addicts from using, but it also could address conditioned aspects of addiction.
When I arrived at UCLA and the Veterans Administration at Brentwood in 1976, I was surprised to discover that the treatment program to which I had been awarded a fellowship, was already eliminated--almost before it began. With the help of the director of the methadone clinic, I started a new experimental Naltrexone treatment program, drawing recruits from the VA's methadone maintenance population.
Naltrexone did not meet its high expectations. While many methadone
patients expressed interest in using Naltrexone, the long process of
withdrawing from methadone--necessary in order to begin taking the opiate
antagonist--eliminated more than 80 percent of volunteers. Also, as we
enrolled volunteers, we found that 90 percent of the addicts who began
using Naltrexone never used opiates while on the antagonist; and the 10
percent who did use, only used once. It was as if the addict immediately
experienced this "no reward" condition and thus didn't bother to waste
his money. This, in itself, was an interesting finding, as it showed
this population to be able to demonstrate impulse control under certain
circumstances (Sideroff et al., 1978). As a result, we never had the
opportunity to test our theory of extinction.
The use of Naltrexone for opiate addiction has subsequently been viewed as an unworkable model. Yet, for the small fraction of individuals who were able to detox and begin taking Naltrexone, it did change their lives.
Typically, the "Silver Bullet" has been thought of in terms of a drug; something that could either eliminate craving or eliminate the high of the drug of abuse. What have become most useful, have been drugs of substitution, such as buprenorphine, (Johnson, et al., 2000), as we continue to search for an effective treatment combination that includes psychotherapy.
The EEG is one objective representation of how the brain is functioning. The EEG is recorded from scalp electrodes, and is a representation of electrical activity produced by the collective firing of populations of neurons in the brain, in the vicinity of the electrode. Figure 1 presents a chart of brain wave frequencies and the primary functions associated with their production. It should be pointed out that this is a gross representation and that more precise differences--beyong the scope of this article - can be found when you look at specific single frequencies within each range. While all frequencies and frequency ranges are important and necessary, problems arise when there is too much or too little of a particular type of brain wave; there is difficulty shifting in response to changing needs; or the EEG is to reactive.
For example, in a healthy functioning brain, if we look at the amount of theta being produced and we compared it (using 4-8 Hz) with beta frequencies between 13 and 21 Hz (cycles per second), there is approximately a 2 to 1 ratio. When we assess the EEGs of people with Attention Deficit Disorder (ADD), we see ratios that are 3 to 1 and much higher (Lubar, 2003).
These higher ratios indicate that the brain is producing too much of the slow waves relative to the beta waves, where the beta waves represent a more focused and engaged brain. In other words, these brains are under-activated. On the other hand, if we look at the EEG patterns of people with anxiety, worry and tension, there is typically too much activity occurring in the higher frequencies, usually between 24 and 35 Hz. The EEGs of people with substance abuse problems can show both of these patterns.
It has been demonstrated that the EEGs of
addicts show specific abnormalities when compared to normative data.
Studies of detoxified alcoholics indicate an increase in absolute and
relative power in the higher beta range, along with a decrease in alpha
and delta/theta power (Saletu, et al., 2002). Low voltage fast
desynchronized patterns (high beta) may be interpreted as demonstrating a
hyper arousal of the central nervous system (Saletu-Z et al., 2004);
and Bauer, showed a worse prognosis for the patient group with a more
pronounced frontal hyper-arousal (Bauer, 2001).
The fact that these EEG patterns as well as alcohol dependence itself are highly inheritable further supports the biological nature of this disease (Gabrielli et al., 1982; Schuckit & Smith, 1996; Van Beijsterveldt & Van Baal, 2002).
These specific abnormalities show both a worse prognosis and a predisposition to development of alcoholism. Individuals with a family history of alcoholism were found to have reduced relative and absolute alpha power in occipital and frontal regions and increased relative beta in both regions compared with those with a negative family history of alcoholism. In another study, these abnormalities also were associated with risk for alcoholism (Finn & Justus, 1999).
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