It is a common belief that at least part of the cause of addiction is an attempt at feeling better--self-medicating. When someone with reduced or an absence of synchronous alpha rhythm takes a drink of alcohol, it results in the generation of an alpha rhythm or what is referred to as alpha synchrony, which a normal functioning brain has much greater capacity to produce (Pollock et al., 1983). Thus, it appears that the alcohol is helping the addicted person compensate for their brain's inability to produce an alpha rhythm which is associated with a state of calmness. This mechanism helps to explain the use of alcohol by this group of addicts.
In related research on abstinent heroin-dependent subjects, it is interesting to note similar abnormalities of deficits in alpha frequencies, along with excessive high beta EEG activity (Franken et al. 2004; Polunina & Davydov, 2004). Although it appears that in some studies, these changes found in early abstinence normalize after several months of abstinence (Shufman et al., 1966; Polunina & Davydov, 2004). Cocaine-dependent subjects may show similar increases in beta activity, but in addition show increases in frontal alpha (Herning, et al., 1994). These changes, specifically the elevation of fast beta activity, appear to be correlated with relapse in cocaine abuse (Bauer, 2001). In contrast, methamphetamine abusers have been shown to have significant increases in delta and theta frequency bands (Newton et al, 2003).
There are many questions that this research does not answer with regard to the relationship between abnormal EEG patterns and addiction. For example, it is not known if these dysfunctional elements are coincidental or causal. In addition, these EEG patterns are found in many mental disorders, some that are typically coincident with substance abuse. These questions do not minimize the probable conclusions that the EEG dysfunction creates specific vulnerabilities of these subjects. For example, frontal alpha, which is also found with some types of ADD, results in impairment of executive functions, such as decision making; and excessive fast beta activity can result in excess emotional and physical tension as well, as obsessive qualities.
Other substances of abuse have also been shown to correlate with abnormal EEG patterns. For example, studies have demonstrated that subjects with a chronic history of marijuana use demonstrate EEG patterns of frontal elevations of alpha frequencies. (Struve, Manno, Kemp, Patrick, & Manno 2003). This is referred to as "alpha hyper-frontality." Another common feature of the EEG of chronic users is a reduction of alpha mean frequency, which may indicate some deficits in intellectual functioning.
Neurofeedback, as a subset of biofeedback, monitors a subject's brain waves and feeds back selective information about these brain waves, in order to gain control over these patterns. Neurofeedback programs typically allow for the setting of thresholds within specific frequency bands or ranges so that when the EEG either rises above the threshold or drops below the threshold, some form of signal or reinforcement is presented to the subject. This feedback lets the brain know when it has been successful, thus, in an operant conditioning model, encourages this rewarded brain wave response. When the goal is to have the signal go above a threshold, we refer to this as "up training" or rewarding. When the goal is to reinforce signals that drop below a threshold, we refer to this as "down training," or inhibiting this component of the EEG.
Joe Kamiya, a researcher at the University of Chicago, was the first researcher to discover that when a subject was informed that he was producing alpha brain wave frequencies, he would then be able to learn to detect, on his own, when he was in alpha (Kamiya, 1968). As a result of this finding, he designed a study in which he similarly gave feedback to the subjects as to their production of alpha, with the instruction to produce alpha. He found that when given this feedback, subjects were able to increase their production of synchronous alpha waves (Nowlis & Kamiya, 1970). Interestingly, his success led to the popularity of alpha training in mass culture, which coincided with its loss of credibility in the academic community.
Neurofeedback research and its acceptance took on a new impetus when Sterman, working with cats, was able to train these animals using a similar operant conditioning model, to increase the amount of synchronous spindle activity in the 14 Hz frequency range (Sterman, 2000). Since these spindles occurred over the sensorimotor cortex, he labeled them sensorimotor rhythm (SMR). These studies confirmed that the production of these brain waves--associated with motoric stillness--resulted in animals that were more resistant to the triggering of seizures. Sterman, then adapted this EEG biofeedback procedure with epileptic patients and demonstrated its effectiveness in reducing the frequency and intensity of seizures.
When a subject produces SMR activity, he is mentally alert with relaxed muscles (lower muscle tone). Lubar, working in Sterman's laboratory, recognized the potential of this discovery, and in a series of research studies, he and his colleagues were able to train children with hyperactive disorder to increase their production of SMR activity with feedback, resulting in reduced hyperactivity (Lubar, 1985).
The training procedures have evolved so that in addition to reinforcing SMR frequencies, the training of ADD also typically reinforces slightly higher frequencies of either 15 to 18, or 15 to 20 Hz activity, and at the same time, down trains the slower (theta) frequencies. The protocols address the ratio between the slower (theta) brain waves, with the faster brain waves, with a goal of training greater activation of the brain, which translates into improved attention. In one follow up study, Lubar and associates were able to demonstrate that gains made in variables of attention were maintained in subjects 10 years following training (Lubar, 1995; 2003).
At the same time that neurofeedback was being used to address attentional and cognitive deficits, primarily by training the activation of the brain, it also was being used to help people relax and establish autonomic and neuromuscular balance. With populations demonstrating aspects of anxiety, obsessive compulsive disorder and tension, the procedure has been to train increases in alpha frequencies (8-12 Hz) or a combination of alpha and theta (Moore, 2000). In these cases, the process is one of training a lowering of activation of the brain. A wide range of neurofeedback protocols have now been applied to cognitive, emotional and physical symptoms and conditions with a growing range of positive results. A bibliography covering these studies is available (Hammond 2008).
Acknowledgement: The author wishes to express his appreciation to Eleanor Criswell, Jay Gunkelman, David Kaiser and Hugh Baras for their helpful comments.
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