Wireless

New! The EmbeddedBlue Transceiver AppMod provides standard Bluetooth connectivity for BASIC Stamp applications without the need for detailed Bluetooth knowledge. Engineers, educators, hobbyists, and OEMs can take advantage of advanced wireless connectivity with this easy to use module. It is designed and manufactured by A7 Engineering based on specifications provided by Parallax, the exclusive distributor of the EmbeddedBlue Application Module.

The communication potential with Bluetooth is rather amazing when compared to proprietary RF, especially with the proliferation of Bluetooth enabled hardware devices. The documentation includes a detailed overview and sample source code for EmbeddedBlue projects with the BASIC Stamp 2 series, including interfacing to standard Bluetooth devices.

EEG and Subjective Correlates of Alpha-Frequency

Binaural-Beat Stimulation Combined with Alpha Biofeedback

by

Dale S. Foster

Memphis State University

May 1990

 

Acknowledgements

I would like to express my appreciation to Dr. Robert Crawford, Dr. Robert Davis, Dr. Todd Davis, Dr. Burl Gilliland and Dr. Kenneth Lichstein for their advice, encouragement and support throughout the completion of this work. I would also like to thank Dr. Jane Davis at Christian Brother's College for the opportunity to solicit participants from her introductory psychology classes. My appreciation also goes out to Dr. Michael Daley, Ryan Eason and Palitha Jayasinghe in the MSU Electrical Engineering Department for their technical assistance in creating the hardware and software necessary for the A/D conversions of the EEG data.

I also express my thanks to Libby Keenan, Coordinator of MSU's Computer Services Training Center, for her help with the software used to transform the raw data. I would also like to thank George Relyea, Manager of MSU's Statistical Services, for his assistance with the SPSSX statistical analysis.

 

Abstract

The purpose of this study was to determine the effects of alpha-frequency binaural-beat stimulation combined with alpha biofeedback on alpha-frequency brain-wave production and subjective experience of mental and physical relaxation. The study compared the alpha brain- wave production and subjective report of mental and physical relaxation of four groups, each of which received brief relaxation response training and one of four treatments: 1) alpha-frequency binaural-beat stimulation, 2) visual alpha- frequency brain-wave biofeedback, 3) alpha- frequency

binaural-beat stimulation combined with visual alpha biofeedback, or 4) artificially produced ocean surf sounds. Sixty volunteer undergraduate and graduate students were randomly assigned to the four groups and instructed to utilize their respective treatment as the "mental device" in Benson's relaxation response paradigm while they relaxed with eyes open for twenty minutes. Two 2 X 4 mixed ANOVAs revealed that all groups evidenced increased subjective report of relaxation and increased alpha production. An interaction effect was found in which the group with both alpha binaural beats and alpha biofeedback produced more treatment alpha than the group with alpha biofeedback alone. Additionally, nine of the fifteen subjects with both binaural beats and feedback reported being able to control alpha production via their focus on the alpha binaural beats. The data suggest the possibility that binaural beats can be used to evoke specific cortical potentials through a frequency-following response. Further investigation is warranted into the possibilities of using binaural beats alone and in conjunction with brain wave biofeedback to promote the self- regulation and management of consciousness.

 

Introduction

In recent years, the self-regulation of physiological processes has received an increasing amount of attention from the behavioral science community due to a number of factors, the most important of which is the increasing sophistication of techniques for measuring and feeding back meaningful information concerning these processes. Technological advances in the areas of electronics and computers have promoted the application of cybernetic principles to such biological events as heart rate, blood pressure, skin temperature, electrodermal responses, and spontaneous and evoked cortical potentials (Yates, 1980). The ability to empirically quantify these biological events and their operant control has also sparked renewed interest from behavioral scientists in the objective study of the self- regulation of consciousness (Schwartz & Shapiro, 1976). In fact, although at one time conscious and/or volitional processes were considered to be outside the proper domain of psychological investigation, the study of consciousness is now viewed as a central issue in cognitive psychology (Davidson, Schwartz & Shapiro, 1983). The empirical investigation of the operant control of spontaneous and evoked cortical potentials began with the invention of the electroencephalograph (EEG) by Richard Caton around 1875 (Empson, 1986). Since that time advances made in EEG technology have enabled feedback of specific cortical potentials in forms which have allowed individuals to achieve control over certain specific cortical potentials under certain conditions (Rockstroh, Birbaumer, Elbert, & Lutzenberber, 1984). EEG technology has promoted the conditioned self-regulation of electrical brain rhythms through biofeedback procedures and thus has enhanced operants' abilities to self-regulate the behaviors and states of consciousness with which those rhythms are associated.

The empirical investigation of the sensory stimulation of cortical potentials also dates from Caton's invention of the EEG. Various forms of rhythmic stimulation such as flashing lights or pulsing sound have been found to entrain the electrical activity of the brain through the frequency-following response (FFR). Another form of auditory stimulation which may invoke a FFR, although much more subtle than bursts of sound, is binaural beats.

The present study is viewed within the context of the empirical investigation of the self-regulation and management of consciousness. More specifically, the aspects of consciousness which are focused upon are those which relate to the self-regulation and management of alpha-frequency brain waves, a primary correlate of certain aspects of consciousness. A distinction is made between self-regulation and management of consciousness for two reasons. First, much of consciousness appears to be outside the realm of direct self- regulation. For example, regardless of the level of motivation for maintaining a waking state of consciousness, humans find themselves losing consciousness, or falling asleep, almost daily. Second, information concerning past and present events related to consciousness is useful for planning or managing present or future events related to consciousness. For example, if I am aware that I tend to move from a

waking state into a sleeping state after being awake for a certain number of hours, then I may use this information to plan to be in or near a bed when that event occurs. Thus those aspects of consciousness which are outside of my direct control are managed rather than regulated

In relation to this study, two techniques are considered, alpha brain-wave biofeedback and alpha-frequency binaural-beat stimulation. Alpha brain-wave biofeedback is considered a consciousness self-regulation technique while alpha-frequency binaural-beat stimulation is considered a consciousness management technique. The distinction adopted here between self- regulation and management, however, is seen as a conceptual convention for the promotion of clarity. Both techniques could be considered to contain components of both self-regulation and management of consciousness.

 

Brain wave biofeedback has already been demonstrated to be an effective technique for the self-regulation of consciousness (Brown, 1970; Green & Green, 1979; Kamiya, 1969). Through the presentation of auditory or visual stimuli which convey useful information concerning the amount of alpha or theta brain-wave production, subjects are able to voluntarily increase or decrease the production of those brain waves. Through the self- regulation of a specific cortical rhythm, one begins to control those aspects of consciousness associated with that rhythm. For example, if I am aware that alpha-frequency brain waves are associated with mental relaxation, I may learn to self-regulate my level of mental relaxation by learning to self-regulate my alpha-frequency brain waves. Brain wave biofeedback techniques are presently being used successfully in the operant conditioning of specific frequency bands as well as single neurons (Rockstroh, Birbaumer, Elbert, & Lutzenberger, 1984).

Although the existence of the phenomenon of binaural beats is well documented (Oster, 1973), the application of binaural-beat stimulation as a consciousness management technique has as yet received little attention except among a small population of researchers (Atwater, 1988; Hutchison, 1986; Monroe, 1982). However the principle of using sensory stimuli to entrain specific cortical rhythms through the frequency- following response is well documented (Gerken, Moushegian, Stillman, & Rupert, 1975; Neher, 1961; Sohmer, Pratt, & Kinarti, 1977; Stillman, Crow, & Moushegian, 1978; Yaguchi, & Iwahara, 1976).

Binaural beats are auditory brainstem responses which originate in the superior olivary nucleus of each hemisphere. They result from the interaction of two different auditory impulses, originating in opposite ears, below 1000 Hz and which differ in frequency between one and 30 Hz (Oster, 1973). For example, if a pure tone of 400 Hz is presented to the right ear and a pure tone of 410 Hz is presented simultaneously to the left ear, an amplitude modulated standing wave of 10 Hz, the difference between the two tones, is experienced as the two wave forms mesh in and out of phase within the superior olivary nuclei. This binaural beat is not heard in the ordinary sense of the word (the human range of hearing is from 20-20,000 Hz). It is perceived as an auditory beat and theoretically can be used to entrain specific neural rhythms through the frequency-following response (FFR)--the tendency for cortical potentials to entrain to or resonate at the frequency of an external stimulus. Thus, it is theoretically possible to utilize a specific binaural-beat frequency as a consciousness management technique to entrain a specific cortical rhythm.

The entrainment of the alpha rhythm is perceived as a justifiable starting point in this investigation. The alpha rhythm was discovered by Hans Berger around 1924 and has been the object of extensive investigation since. However, there is still disagreement concerning the nature and origins of alpha. The alpha frequency range is usually considered to be from eight to twelve cycles per second and is generally associated with a relaxed but awake state of consciousness. Kamiya (1969) was one of the first to demonstrate operant control of the alpha rhythm through an auditory feedback stimulus. Brown (1970) demonstrated operant conditioning of alpha activity through the use of a visual feedback stimulus. Both researchers reported that enhanced alpha

activity was usually accompanied by subjective experiences of pleasant affect. Cade and Coxhead (1979), on the basis of EEG data from "some four thousand" (p. vii) subjects, maintain that the maintenance of a prominent alpha rhythm in the EEG is a prerequisite to developing a state of consciousness which they have reportedly quantified and termed "the awakened mind." Elmer and Alyce Green in their book Beyond Biofeedback report that alpha and theta biofeedback training facilitated states of consciousness which were conducive to creative imagery and personal psychotherapeutic insights.

This study seeks to empirically examine some of the effects of alpha-frequency biofeedback combined with alpha-frequency binaural beats on EEG alpha production and subjective experience of mental and physical arousal. The rationale behind this approach includes the possibility that learning to enhance alpha-frequency brain waves by allowing the binaural beats to entrain the cortex through a FFR may provide the subject with a skill that is generalizable to other environments.

 

Purpose

The purpose of this study is to begin to examine some of the electroencephalographic (EEG) and subjective effects of alpha-frequency binaural beats stimulation alone and in combination with alpha-frequency brain-wave biofeedback. Conceivably, as the EEG and subjective effects of binaural beats become better understood, their use as a consciousness management technique will become more effective.

 

Need for the Study

The literature on alpha biofeedback training illuminates the fact that there is yet much research to be done on the nature of the alpha rhythm and the factors involved in its operant control. The already reported successful practical applications of alpha biofeedback training provide reasonable motivation to continue to explore the phenomenon. Additionally, the preliminary attempts to utilize binaural beats and the FFR to facilitate specific brain-wave frequencies provide adequate justification for further examination of binaural-beat stimulation in order to better understand its effects. A visual eyes-open biofeedback task may serve to compliment the binaural-beat technique by providing the subject a measure of degree of entrainment achieved. A computerized search of the Psychological Abstracts and Index Medicus revealed no examples of research combining alpha biofeedback with a binaural-beat technique. The importance of the alpha rhythm and the possible benefits of its operant control provide motivation to begin to examine alpha biofeedback paradigms in conjunction with binaural beats. This study will examine the effects of both eyes-open visual alpha biofeedback and a binaural-beat technique on the production of alpha-frequency brain waves and subjective report.

 

Research Question

This study addresses the broad research question concerning what the individual and interaction effects of alpha-frequency binaural-beat stimulation and alpha biofeedback are upon subjects' EEG alpha production and subjective experience of mental and physical relaxation.

 

Hypotheses

The following four hypotheses were tested:

H(1) Alpha frequency binaural-beat stimulation will increase alpha brain wave production above eyes- open baseline levels.

H(2) Visual eyes-open alpha-biofeedback training will increase alpha production above eyes-open baseline levels.

Ho(3) The combination of visual eyes-open alpha- biofeedback training with alpha-frequency binaural-beat stimulation will interact to increase alpha production more than either technique alone.

H(4) The combination of alpha binaural beats with alpha biofeedback will result in increased subjective report of relaxation.

 

Definitions of Terms

For the purposes of this research the following terms are operationally defined as follows:

1. Alpha production: Alpha production is defined as the ratio of the 10.5 Hz band of the Mind Mirror II EEG (Blundell, undated; Cade & Coxhead, 1979) to the entire measured EEG spectrum.

2. Eyes-open baselines: Eyes-open baselines are defined as the ratio of the 10.5 Hz band of the EEG to the entire measured EEG spectrum during the two minute period of time after orientation and before the procedure while the subject is mentally and physically relaxed in dim ambient light with eyes open and gaze fixed.

3. Alpha-frequency binaural-beat stimulation: The alpha frequency binaural beats were produced by a model 201B Hemi-Sync Synthesizer (Instruction manual, undated) and vibrated at 10.5 Hz.

4. Visual eyes-open alpha biofeedback: Alpha feedback was provided by the 10.5 Hz band of a Mind Mirror II EEG (Blundell, undated; Cade & Coxhead, 1979). In dim ambient light subjects observed two lights which indicated strength of alpha production by diverging laterally from a middle point. Orientation to the procedure included information concerning oculomotor strategies which have been found to affect alpha production. Subjects were instructed to maintain a fixed gaze throughout the procedure and not to use other oculomotor strategies to control alpha production.

5. Subjective report: Subjective report of mental and physical relaxation is defined as scores on a Self-Report Form.

 

Assumptions

The analysis of variance techniques used in this study rest upon a mathematical model which assumes that the error effects are distributed normally in the treatment population, the error

effects are independently determined and distributed in the treatment population, and the error effects vary homogeneously in the treatment population.

 

Limitations

This study is subject to the following limitations:

1) Inasmuch as no frequency of binaural beats is provided other than alpha frequency, the assumption is not made that any increase in alpha production is necessarily unique to alpha- frequency binaural-beat stimulation. 2) Due to the fact that subjects were not screened for susceptibility to the treatment stimuli, the variability of susceptibility between subjects may obscure the findings of treatment effects.

3) Although subjects were informed of oculomotor strategies which have been found to increase alpha production and instructed uniformly concerning their use, no objective control for use of oculomotor strategies was used.

4) Although dominant alpha frequencies vary between and among individuals, no effort was made to evaluate and feed back the dominant alpha frequency of subjects. It seems reasonable that a technique which provides a beat frequency which is more natural to the system would have greater impact on the system.

 

Review of the Literature

Since the discovery of the human electroencephalogram (EEG) numerous applications have been found for utilization of the developing knowledge of the electrical rhythms of the brain. Brain wave biofeedback research has contributed evidence of operant control of the EEG and continues to provide increasing illumination into the nature and functions of the brain's electrical rhythms. The interaction of these rhythms with the environment has also become better understood with the aid of EEG technology by allowing measurement of the effects of sensory stimuli on cortical potentials. The frequency-following response (FFR) is the tendency for the EEG to become entrained to the frequency of an environmental stimulus. The following study employs a combination of alpha brain-wave biofeedback and utilization of the frequency- following response through an alpha-frequency binaural-beat technique in an effort to determine the subjective and EEG correlates of this combination.

 

Electroencephalography

The history of electroencephalography, the measurement and study of the brain's electrical activity, dates back to the mid- to late nineteenth century when advances made in the science of electromagnetism began to be applied to human physiology. Richard Caton developed a technique for detecting the electrical activity from the exposed surfaces of the brains of living rabbits and monkeys. He demonstrated his findings at a meeting of the British Medical Association in 1875 and later published them in the British Medical Journal (Caton, 1875). He is credited with the discovery of the spontaneous EEG in animals and with demonstrating the ability to detect electrical brain responses to stimuli. In 1924 Hans Berger, a German psychiatrist,

developed and applied electroencephalographic techniques for use with humans and in 1929 published his first paper on the subject (Empson, 1986).

Since Berger's discovery, the human EEG has provided information which has promoted a wide variety of discoveries about the brain. Functional roles of different areas of the brain have been discovered (Giannitrapani, 1985), development of the brain has become better understood (Surwillo, 1971), and correlations have been found between EEGs and behavior, personality factors and mental disorders (Saul, David, & Davis, 1949; Glaser, 1963; Robinson, 1974).

The normal human EEG has a frequency range from 0.5 Hertz (Hz) to 30 Hz which is usually subdivided into four or five bands: delta (0.5-3.5 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (13-28 Hz), and gamma (28+ Hz). Each of these bands has been correlated with specific behavioral states. Delta frequency waves are generally associated with deep sleep, theta waves with light sleep or dreaming, alpha waves with relaxed consciousness, and beta and gamma waves with active consciousness. Modern computerized EEGs can provide immediate feedback of the brain's electrical activity according to location, frequency, and amplitude. This information can be utilized to identify and possibly modify specific functional states of individuals. Also, this information, when compared with normative data, can be used to indicate deficiencies or specialties of function of an individual.

 

The Alpha Rhythm

Hans Berger is credited with the discovery of the human alpha rhythm in 1924 (Empson, 1986). Berger's first recognizable pattern in the human EEG was a relatively dominant, stable, synchronous wave form of about ten cycles per second which occurred primarily when the eyes were closed and during states of relaxation. Berger also noted that alpha was replaced by beta waves when the eyes were opened or when the individual was engaged in mental activity such as arithmetic calculations. For Berger, alpha waves represented a form of automatic functioning, a state of electrical readiness which exists when the subject is awake and conscious but inattentive. By 1934 (Adrian & Matthews, 1934) a consensus had been reached that alpha activity was related to relief from both visual activity and attention (Klinger, Greqoire, & Barta, 1973). The relationship of alpha to both the visual/oculomotor system and mental activity has been an important factor in alpha biofeedback research.

In most individuals there is a fairly consistent alpha frequency of around 10 cycles/second (Wieneke, Deinema, Spoelstra, Storm Van Leeuwen, & Versteeg, 1980). Although the alpha range is usually defined to be from 8-12 Hz, within this range the actual dominant alpha frequency varies between individuals (Schwibbe, Bruell, & Becker, 1981), within individuals across time according to differing conditions (Banquet, 1972, 1973), and within some individuals' brains at the same time (Inouye, Shinosaki, Yagasaki, & Shimizu, 1986). This variation of the alpha rhythm within and between individuals illustrates the complex and idiosyncratic nature of the phenomenon. Additionally, numerous variables have been correlated with the alpha rhythm in various ways.

 

Alpha and Arousal

Some researchers have attempted to relate alpha activity to physiological arousal. The alpha rhythm is most evident when the subject is awake, has closed eyes and is relatively relaxed, and tends to disappear or decrease when the subject engages in mental concentration or physical movement, or becomes tense, apprehensive or anxious. It has thus been described as occupying

a mediating position on the continuum of nervous activation ranging from deep sleep to high emotional excitement as described by arousal theory (Malmo, 1959). Lindsley (1952) characterizes synchronized, optimal alpha rhythm as a state of relaxed wakefulness in which attention tends to wander, free association is enhanced, and behavioral efficiency of routine reactions and creative thought is good. Evans (1972) suggests that alpha is related to cognitive arousal and attention in a U-shaped manner in the sense that it disappears at either extreme of arousal and attention. Cade and Coxhead (1979) describe a two factor theory of arousal in which the alpha rhythm is indicative of relaxed cortical arousal. Other physiological measures such as skin resistance reflect peripheral or somatic arousal. In their model cortical and peripheral arousal interact but may vary independently.

 

Alpha and Hypnosis

A number of researchers have focused on the alpha rhythm as a possible physiological correlate of hypnosis. London, Hart, and Leibovitz (1968) found evidence that hypnotic susceptibility is positively correlated with higher levels of waking alpha production. However, other researchers attempting to replicate this finding have had both positive and negative results (Engstrom, London, & Hart, 1970; Evans, 1972; Galbraith, London, Leibobitz, Cooper, & Hart, 1970; Nowlis & Rhead, 1968; Ulett, Akpinar, & Itil, 1972).

 

Alpha and Meditation

In the late 1950's and early 1960's research into the EEG effects of meditation began to reveal that the alpha rhythm appears different during meditation and may undergo long-term changes in persistent meditators (Bagchi & Wenger, 1958; Kasamatsu & Hirai, 1969). Anand, Chhina, and Singh (1961) reported that the EEG of meditators showed a high amplitude slowed alpha rhythm which gradually spread from the occipital to the frontal areas. Banquet (1973) also found high amplitude alpha rhythms during meditation. Additionally, Banquet noted a second stage of meditation in which theta frequencies appeared and moved from frontal to posterior channels. A third stage, which Banquet observed in only the most experienced meditators, was characterized by high-frequency beta waves over the whole scalp. Banquet also noted that during meditation alpha blocking did not occur to low intensity light and sound stimulation. Empson (1986) summarizes the recent research on meditation and concludes that the experience of meditation "requires the constant maintenance of a fairly low level of arousal which allows the sort of dissociated, free-associative thinking that meditation entails" (p. 31). The low-frequency, high-amplitude alpha rhythms generally found during meditation thus seem to represent a voluntary lowering of arousal by the meditator.

 

These findings concerning the EEG activity of meditators sparked increased interest in the meanings of these rhythms and how to control them. Stewart (1974) observes that the interest in alpha brain wave biofeedback training appears to have originated from EEG monitoring of Zen and Yoga practitioners. The perceived link between meditation and alpha production influenced many to assume that increased alpha production would result in the ability to reap the benefits of meditation. This assumption has been a driving force behind the interest in alpha biofeedback training. However, over two decades of research into alpha biofeedback training indicates that this assumption is at best simplistic.

 

Alpha Biofeedback Training

Alpha biofeedback training was first introduced by Kamiya in 1962 (Kamiya, 1969) when he demonstrated that subjects who were required to guess whether or not alpha was present in their EEGs and were subsequently informed of their accuracy, could, within a few hours, correctly identify when they were producing alpha with high accuracy. He also found that those subjects who were successful in discrimination training could also produce or suppress alpha activity at will. He later successfully utilized auditory alpha-biofeedback devices which informed subjects of their alpha production through the presentation or absence of a tone generated by their alpha rhythms (Nowlis & Kamiya, 1970). The mental states which Kamiya's subjects associated with increased alpha production were reported to be feelings of relaxation, "letting go," and pleasant affect.

 

Brown (1970) studied alpha biofeedback in an eyes open condition and found that subjects were able to increase their alpha production with a visual feedback stimulus in the form of a small blue light which was activated by alpha production. She reported that successful alpha enhancement was correlated with subjective experiences of narrowing of awareness and pleasant feeling states. Other researchers have reported successful attempts to enhance alpha production with both visual and auditory feedback (Green, Green, and Walters, 1970; Honorton, Davidson, and Bindler, 1972; Inouye, Sumitsuji, & Matsumoto, 1980). Although Kamiya and Brown used the occipital regions to train alpha, successful alpha training has also occurred using central (Potolicchio, Zukerman, & Chernigovskaya, 1979), parietal and frontal regions (Nowlis & Wortz, 1973). There has also been success training interhemispheric synchronization of alpha (Mikuriya, 1979).

Since the advent of alpha biofeedback training, research in the area has revealed relationships between alpha production and such diverse topics as pain control (Pelletier & Peper, 1977) and extrasensory perception (Rao & Feola, 1979). Alpha production has also been correlated in various ways with creativity (Martindale & Hines, 1975), reaction time (Woodruff, 1975; Ancoli & Green, 1977), locus of control (Goesling, 1974; Johnson & Meyer, 1974), neuroticism (Travis, Kondo, & Knott, 1974b), and other personality variables (Degood & Valle, 1975).

 

Alpha Training and Contingent Feedback

One of the most fundamental principles of biofeedback is the necessity of accurate monitoring and feedback of the physiological process of interest in order for that process to be operantly controlled. It seems to be a comment on the complexity of the phenomenon of alpha biofeedback that after over twenty years of research there is still a lack of agreement among researchers that the increased alpha production observed in alpha biofeedback training paradigms is dependent upon the presence of accurate contingent feedback. While some researchers contend that alpha control is dependent upon true feedback (Kondo, Travis, Knott, & Bean, 1979; Pressner & Savitsky, 1977; Travis, Kondo, & Knott, 1974a), other researchers have found that alpha enhancement occurs under conditions of false feedback or no feedback and is thus less dependent upon accurate feedback than on other situational factors such as expectancy, instructions, or reinforcements other than the feedback (Brolund & Schallow, 1976; Holmes, Burish, & Frost, 1980; Lindholm & Lowry, 1978; Lynch, Paskewitz, & Orne, 1974; Prewett & Adams, 1976; Williams, 1977).

 

EEG Alpha and the "Alpha Experience"

According to the early research into alpha control, the successful enhancement of alpha was accompanied by "pleasant feeling states," "dissolving into the environment," altered perception of time, relaxation, "letting go," "letting mind wander," and visual inattentiveness (Brown, 1970; Nowlis & Kamiya, 1970). These observations led to the conclusion that enhanced alpha production resulted in an altered state of consciousness referred to as the "alpha state." However, further research into the subjective experiences which accompany alpha biofeedback training reveal that there are many other factors involved which influence these experiences. While some research indicates that the "alpha experience" requires both enhanced EEG alpha production and an "instructional set" (Walsh, 1974), other research indicates that the "alpha experience" does not necessarily accompany high or enhanced levels of EEG alpha (Plotkin, 1976, 1978; Plotkin & Cohen, 1976; Plotkin, Mazer, & Loewy, 1976), and may be relatively independent of alpha production (Plotkin, 1979). Enhanced alpha has been accompanied by elevated mood states as well as neutral or unpleasant mood changes (Bear, 1977; Cott, Pavloski, & Goldman, 1981; Travis, Kondo, & Knott, 1975). Marshall and Bentler (1976) contend that the level of physical relaxation is probably the determining factor in the experience of the "alpha state" rather than the amount of alpha production. This interpretation lends itself to a discrimination between cognitive and somatic relaxation. Although alpha production is related to both physical and mental arousal, it is neither a necessary consequence of nor a prerequisite to physical relaxation. Nor is it necessarily accompanied by pleasant affect. It is a multifaceted phenomenon which exists in a web of relationships with these and other variables.

 

Alpha and the Oculomotor System

As was mentioned earlier, Berger recognized that alpha production was somehow associated with both the visual system as well as mental effort. The further definition of these associations has been an ongoing theme since Berger's discovery. While Kamiya and Brown were further defining the links between alpha and subjective experiences of relaxation and pleasant affect, other researchers were further defining the links between alpha and the oculomotor system (Dewan, 1967; Mulholland & Evans, 1966).

The assumption that increased alpha control results in increased control over arousal breaks down when the link between alpha and the oculomotor system is not controlled for (Goodman, 1976). Brown (1974) relates an incident in which a colleague who had been practicing alpha biofeedback requested to have his EEG monitored in her lab to check his progress. They discovered that he had learned to control his alpha production by moving his eyes, not by producing it by itself. Even though he thought he had learned to control his alpha production by lowering his level of arousal, he had actually only learned to keep the alpha feedback tone on by unconsciously discovering and using another mechanism by which alpha may be controlled. The fact that the alpha rhythm is correlated with numerous cognitive and behavioral variables has spawned controversy over whether or not cognitive strategies are primary factors in alpha control or merely mediate oculomotor control of alpha (Hardt & Kamiya, 1976; Plotkin, 1976a; Plotkin, 1976b).

 

Alpha Control and Baseline Alpha

The intimate relationship between the oculomotor system and the alpha rhythm has revealed some design difficulties in alpha training procedures. It seems that success in increasing alpha density depends partially on whether or not eyes-open or eyes-closed baselines are used and

upon the amount of light available during the training procedure. Paskewitz and Orne (1973) compared two groups of subjects who were trained with alpha feedback tones. One group was trained in total darkness and the other was trained in dim ambient light. The group trained in darkness demonstrated no increases in alpha densities while the group trained in dim ambient light demonstrated increases in alpha densities compared to eyes- open baseline levels. Neither group demonstrated increases in alpha when compared to eyes-closed baselines. They concluded that alpha training can lead to changes in alpha densities only when conditions have lowered alpha densities below the levels spontaneously seen under optimal conditions. They concluded, "Subjects can acquire volitional control over alpha activity only under conditions which normally lead to decreased densities. . . Alpha feedback training may enable a subject to overcome suppressing effects when they are present" (p. 363). They further state that the pleasant subjective experiences reported to be associated with alpha feedback training are likely consequences of the acquisition of skill in disregarding stimuli in the external and internal environments which would ordinarily inhibit alpha activity. Seen within this context, they describe an increase in alpha density as not an end in itself but an index of the subject's ability to disregard or remain unaffected by alpha blocking stimuli.

Other studies have indicated that the individual subject's baseline alpha amplitude and density is an important factor in obtaining increases in alpha through feedback training (Kondo, Travis, & Knott, 1973).

 

Alpha and Attention

Alpha is usually associated with mental states of nonattention, disappearing when the individual focuses attention on something either in the external or internal environments. Brown, however, (1974) reports that during visual alpha feedback training sessions her subjects demonstrated alpha during the periods when they were attending to the visual stimulus and produced desynchronized beta frequencies during the rest periods when they were not attending to the feedback light. The link between alpha production and attention is thus more complex. She noted that "the subjects who lost awareness of all environmental factors except the light . . . were those subjects with the highest levels of alpha production. Conversely, the subjects who remained aware of the environment . . . produced the smallest amounts of alpha" (Brown, 1974, p. 333). One interpretation of this seeming paradox is that the subjects entered a state of selective attention which did not require an alert, no-alpha EEG. Possibly, the subjects were attending to being nonattentive during the feedback trials and became less attentive to being nonattentive during the rest periods.

 

Alpha and Anxiety

There are indications that alpha production is related to anxiety (Nowak & Marczynski, 1981). However, the use of alpha-biofeedback training to reduce anxiety has met with mixed success. Hardt and Kamiya (1978) reported that with high trait anxiety subjects alpha training resulted in anxiety reduction in proportion to alpha increases and anxiety increases in proportion to alpha suppression. Watson, Herder, and Passini (1978) report long-term improvement in both state and trait anxiety with alcoholics who participated successfully in alpha training. Plotkin and Rice (1981), however, found that anxiety reduction was related more to perceived success in the feedback task than to actual changes in alpha production. They thus attribute the reductions in anxiety that occur during alpha feedback training to placebo effects.

In a study by Orne and Paskewitz (1974) subjects were given alpha feedback training and were told that their alpha production would determine whether or not they would receive electrical shock during periods signaled by a tone. Although the subjects indicated increased physiological and psychological arousal during times of jeopardy, as measured by increased heart rate, skin conductance responses, and reported subjective apprehension and anxiety, their alpha production was not affected. These results indicate that a reduction in alpha production is not a necessary consequence of increased anxiety or physiological arousal. However, the results do not necessitate the conclusion that increased alpha production does not reduce anxiety.

 

Therapeutic Applications of Alpha Training

Although there have been reports of unsuccessful attempts to utilize alpha biofeedback training therapeutically (Hord, Lubin, Tracy, Jensma, & Johnson, 1976; Leib, Tryon, & Stroebel, 1976; Mandelzys, Lane, & Marceau, 1981; Watson & Herder, 1980), positive results have been reported with several therapeutic applications. Goldberg, Greenwood, and Taintor (1976) reported that a decrease in illicit drug use accompanied learned control of alpha in four chemically addicted subjects. Peniston and Kulkosky (1989) utilized alpha-theta brain-wave training with alcoholics and reported long-term improvement in depression scores and sustained prevention of relapse. Alpha training paradigms have been successful in reducing seizures and abnormal brain rhythms in epileptics (Johnson & Meyer, 1974a; Rouse, Peterson, & Shapiro, 1975; Sterman, 1973). Success has been noted in the treatment of migraine headaches (Andreychuk & Skriver, 1975; Cohen, McArthur, & Rickles, 1980), although alpha training was not found to be superior to other biofeedback strategies. The control of pain has been found to be related to alpha production in meditators (Pelletier & Peper, 1977) and alpha-biofeedback strategies have been found to facilitate control of chronic pain in conjunction with hypnotic suggestion (Melzack & Perry, 1975) and stress inoculation training (Hartman & Ainsworth, 1980). Mills and Solyom (1974) used alpha training successfully with five ruminating obsessives and found that virtually no ruminations occurred during alpha, indicating possibilities for further research and application of alpha training in this area. Alpha suppression training has been successful improving performance on an arithmetic task with mentally retarded subjects (Jackson & Eberly, 1982), and improving attention and reading skills (Ludlam, 1981).

 

Binaural Beats and the Frequency-Following Response

As has already been seen, the alpha rhythm is influenced by many factors, both internal and external. Environmental factors such as photic and auditory stimulation have been found to influence alpha production in various ways. Flickering lights can entrain the electrical rhythms of the brain through the frequency- following response. A more subtle example of the frequency-following response occurs through binaural beats, an auditory brainstem response.

 

Photic Stimulation

Research clearly indicates the possibility of entraining specific frequencies of brain waves by presenting subjects with frequency-specific flickering lights (Arinibar & Pfurtscheller, 1978; Nogawa, Katayama, Tabata, Ohshio, & Kawahara, 1976; Regan, 1966; Williams & West, 1975; Yaguchi & Iwahara, 1976). For example, alpha-frequency brain waves may be entrained by exposing subjects to a light stimulus flickering at a rate within the alpha frequency range. The tendency for the electrical rhythms of the brain to become entrained to frequencies of sensory

stimuli in the environment is called the frequency-following response (Moushegian, Rupert, & Stillman, 1978; Sohmer, Pratt, & Kinarti, 1977; Stillman, Crow, & Moushegian, 1978).

 

Auditory Stimulation

Research also indicates that auditory stimuli can be used to entrain the electrical rhythms of the brain (Neher, 1961; Picton, Woods, & Proulx, 1978a; Picton, Woods, & Proulx, 1978b). Auditory entrainment of cortical rhythms can occur through two different routes. One may achieve entrainment through bursts of sounds such as through drum beats, or one may achieve entrainment through the less direct and more subtle route of binaural beats.

The range of the electrical rhythms of the human cortex is 0 Hz to about 40 Hz. Since humans have an auditory range of 20 to 20,000 Hz, it is not possible to directly entrain cortical rhythms below 20 Hz with pure tones. However, the phenomenon of binaural beats, an auditory brainstem response, allows the entrainment of frequencies below 30 Hz through the interaction of pure tones within the superior olivary nuclei.

In 1839 H. W. Dove, a German experimenter, discovered the auditory effect of binaural beats (Oster, 1973). He found that when two different frequencies of sound were presented, one to each ear, a third frequency equal to the difference between the two frequencies was experienced. This third, binaural beat is actually the result of the interaction of the two primary tones within the auditory brainstem. For example, if a pure tone with a frequency of 400 Hz is presented to one ear and a second tone of 410 Hz is presented to the other ear, a third binaural beat with a frequency of 10 Hz will also be heard as a result of the interaction of the two frequencies. Binaural beats can be generated at frequencies below 40 Hz and may be used to entrain electrical rhythms of the brain to vibrate at the same frequency through the frequency-following response (Dobie & Norton, 1980; Gerken, Moushegian, Stillman, & Rupert, 1975; Moushegian, Rupert, & Stillman, 1978; Smith, Marsh, & Brown, 1975; Smith, Marsh, Greenberg, & Brown, 1978; Sohmer, Pratt, & Kinarti, 1977; Stillman, Crow, & Moushegian, 1978; Yamada, Yamane, & Kodera, 1977). Mediating processes through which the auditory brainstem binaural beat may entrain the cortex are likely to include attentional and motivational factors. Binaural-beat techniques are reportedly being used to successfully entrain specific brain-wave frequencies for specific purposes (Atwater, 1988). Preliminary reports indicate that the techniques may lend themselves to therapeutic applications. The combination of binaural beats and brain wave biofeedback may also prove therapeutically useful in the future.

 

 

Methodology

The Pilot Study

A pilot study was implemented January 1989, in order to further define the parameters necessary to test the utility of binaural beats in enhancing alpha production. The purposes of the study were to determine (a) the effectiveness of the binaural- beat technique in enhancing alpha production within a single session, (b) the effectiveness of the binaural-beat technique in enhancing alpha production across sessions, and (c) the number of sessions necessary in order for the binaural-beat technique to enhance the self-regulation of alpha in subjects.

 

Method

Subjects.

Four volunteer students, one undergraduate female, one graduate female, one undergraduate male, and one graduate male, were used ranging in age from 20-38. A total of eighteen sessions of usable data was compiled. One subject completed six sessions, two subjects completed five sessions, and one subject completed two sessions.

 

Procedure.

The initial session included a discussion of a handout describing the components of the "relaxation response" (Benson, 1975) and a brief introduction to the binaural-beat phenomenon. Subjects were told that the experiment was designed to provide a binaural beat to serve as the "mental device" (p. 27) in Benson's paradigm. Subjects were reminded of the importance of maintaining a passive attitude and focusing on the binaural beat before each session.

The procedure for each session was the same; (a) subjects completed a brief pre-test of subjective experience of relaxation and anxiety, (b) subjects were given instructions to relax and breathe slowly and deeply for three to five minutes, (c) EEG activity was recorded while subjects listened with eyes closed for seven minutes each to three conditions of sound--artificially produced surf sounds, surf sounds with audible alpha-frequency binaural beats, and surf sounds with subaudible alpha-frequency binaural beats, (d) subjects completed a brief post-test of subjective experience of the procedure and levels of relaxation and anxiety.

 

Instruments.

The binaural beats were produced by a Model 201B Hemi-Sync Synthesizer ("Instruction Manual," undated). EEGs were recorded bipolarly from occipital and temporal sites of both hemispheres (T3, T4, 01, & 02 sites as per Jasper, 1958) by a Mind Mirror II EEG (Blundell, undated; Cade & Coxhead, 1979).

 

Scoring.

Average alpha ratios were computed for each condition of each session. Each of the 28 channels was sampled three times per second. For each condition a ratio of alpha/all frequencies was computed. These ratios were utilized in the statistical analysis.

 

Results

Early in the study it became evident that methodological refinements were needed in order to demonstrate any effects of the binaural beats. The analysis of variance of the data revealed that

there were no significant differences in alpha production either within sessions across conditions or across sessions. Although alpha production was observed to increase in the binaural-beats condition early in some sessions, a tendency was observed for the subjects to move through alpha into desynchronized theta, indicating light sleep. Subjective reports of "dozing off" corroborated these observations. These periods of light sleep, almost devoid of alpha, affected the average alpha ratios.

Subjective reports indicated that the procedure was experienced as either pleasing and relaxing or neutral. Open interviews revealed that one subject who was certain he had found the key and was controlling his alpha was in actuality producing no more EEG alpha than before.

 

Discussion

Since the procedural conditions of the pilot study were insufficient to document that the alpha binaural beats could stimulate increased alpha, the strategy of adding the biofeedback task was conceived to provide subjects with an ongoing measure of success. It is conceivable that with feedback, subjects will be able to discover successful strategies for letting the binaural beats entrain their brain rhythms to the frequency of the stimulus.

 

The Study

 

Based on the results reported in the pilot study, the following study was conducted which incorporates a feedback condition into the binaural-beat procedure. The feedback will theoretically provide the subject a measure of the success with which he or she is allowing the binaural beat to entrain the EEG.

 

Subjects

Sixty volunteer undergraduate and graduate students from Memphis State University and Christian Brother's College participated in the study. The students from Christian Brother's College were volunteers from Jane Davis' introductory psychology classes. The Memphis State students were from Burl Gilliland's, Bob Davis', and Fleetis Hannah's counseling classes. Participants were screened for known neurological damage and abnormalities.

 

Instrumentation

The binaural beats were provided by a model 201B Hemi-Sync Synthesizer ("Instruction Manual," undated). The alpha-frequency binaural beats were created by presenting two pure tones, one to each ear, through a set of headphones, which differed in frequency by 10.5 Hz. The instrument was tested for validity and reliability on an oscilloscope and found to meet adequate standards for both.

EEGs were recorded bipolarly from occipital and temporal sites of both hemispheres (T3, T4, 01, 02 sites as per Jasper, 1958) by a Mind Mirror II EEG (Blundell, undated; Cade & Coxhead, 1979). After recording the EEGs on magnetic tape, the information was converted to digital form and computer analyzed.

 

Design and Procedure

Sixty subjects received brief relaxation response training based on a handout they were given, and randomly assigned to one of four groups: (a) alpha frequency binaural-beat stimulation, (b) visual, eyes-open alpha brain-wave biofeedback, (c) both alpha-frequency binaural beats and alpha biofeedback, or (d) artificially produced surf sounds. The ratio of males to females was kept constant for all groups.

The procedure for each subject consisted of the following steps: (a) the subject completed a pre- test of subjective mental and physical relaxation, (b) the subject was introduced to the four components of the "relaxation response" (Benson, 1975), (c) the subject was introduced to the stimulus which served as the mental device to theoretically elicit the relaxation response (either alpha binaural beats, alpha biofeedback, both, or phased white noise), (d) the subject was connected to the EEG, (e) the subject was instructed to become comfortable, relax, and breathe slowly and deeply for three to four minutes, (f) a two-minute eyes-open EEG baseline was recorded, (g) the subject was provided with the appropriate stimulus and allowed to become oriented to the situation, (h) the subject engaged in a ten minute eyes-open session of attempting to passively allow the stimulus to serve as the mental device to elicit the relaxation response, (i) the subject was briefly interviewed concerning strategies being used and subjective experience of the procedure and possibly reminded of previously mentioned strategies, (j) the subject engaged in a second ten minute session identical to the first, (k) the subject was disconnected from the EEG, (l) the subject completed the Self-Report Form and was interviewed concerning subjective experience of the procedure.

 

Data Analysis

Hypotheses H(1), H(2), and H(3) were tested by utilizing a 2 X 4 mixed analysis of variance and appropriate follow-up procedures. The between subjects independent variable was be the specific stimulus used by the subject as a mental device to elicit the relaxation response. The within- subjects variable was the time of the sampling of the alpha production; baseline or treatment sample. The dependent variable was the alpha production of the subject.

Hypothesis H(4) was tested by utilizing a 2 X 4 mixed analysis of variance with appropriate follow- up procedures. The between subjects independent variable was the stimulus used as the mental device and the within subjects independent variable was the time of testing; pre- or post- procedure. The dependent variable was the level of relaxation reported.

 

Summary

This study attempts to examine the effects of alpha-frequency binaural-beat stimulation combined with alpha-frequency brain-wave biofeedback on alpha production and subjective report of relaxation through the utilization of a 2 X 4 mixed ANOVA design. It seems plausible that the

combination of visual alpha feedback and alpha binaural beats will enhance the frequency- following response and assist the subjects voluntarily entrain their cortical rhythms to the stimulus.

 

Analysis of the Data

Demographics of Subject Sample

Sixty volunteer subjects, forty females and twenty males, from various Memphis State counseling classes and from two Christian Brother's College introductory psychology classes participated in the study. Volunteers from Christian Brother's College were offered extra credit for their participation. Subjects were solicited by the author to participate in a study of the relaxation response. Age of subjects ranged from eighteen to forty-five with a mean of 27.7, a mode of 19, and a standard deviation of 7.64. Data was gathered between October 6, 1989 and October 21, 1989.

 

Data Analysis Techniques

Subjects were randomly assigned to four treatment groups of fifteen, each with ten females and five males. Each of the four groups received brief relaxation training followed by one of four treatments, a) alpha frequency binaural beats stimulation, b) alpha frequency brain wave feedback, c) alpha frequency binaural beats with alpha frequency brain wave feedback, or d) artificially produced ocean surf sounds. Baseline and treatment alpha production ratios were obtained as well as pre- and posttreatment measures of subjective experience of mental and physical relaxation. The data was analyzed using the Statistical Package for the Social Sciences X (SPSSX) analysis of variance and followup procedures (Norusis, 1988). Since the form of the alpha production scores was proportional, arcsine transformations were performed on the alpha ratios prior to analysis in order to promote homogeneity of error variance and normality of error effects and to obtain additivity of effects (Kirk, 1982). For the experimental effects which achieved significance, the omega squared statistic was computed to indicate the strength of the associations (Kirk, 1982).

 

Assumptions

The mathematical model upon which the SPSSX analysis of variance procedures rest assumes that the error effects are distributed normally in the treatment population, independently determined and distributed in the treatment population, and vary homogeneously in the treatment population. The degree to which these assumptions were met affects the validity of the findings.

 

Homogeneity of variance.

Homogeneity of variance is a major assumption underlying the SPSSX analysis of variance procedures. The Bartlett-Box F test for univariate homogeneity of variance was used as a starting point for testing this assumption. The results of this procedure are reported in Table 1.

 

Table 1

Bartlett-Box F Test for Homogeneity of Variance

Measure F P

Alpha Production

Baseline 1.109 .344

Treatment 2.305 .075

Relaxation Scores

Pre-test 0.121 .948

Post-test 0.735 .531

The significance levels indicate that there is no reason to reject the hypothesis that the variances in the two groups are equal. However, an additional test which examines the variances and covariances simultaneously is necessary in order to sufficiently test for homogeneity of dispersion (Norusis, 1988).

 

Homogeneity of dispersion.

Homogeneity of dispersion matrices must be considered when using multivariate analysis of variance (Norusis, 1988). Box's M test is based on the determinants of the variance-covariance matrices in each cell as well as the pooled variance-covariance matrices, thus providing a multivariate test for the homogeneity of the matrices. The results of this procedure are presented in Table 2. As indicated, there appears to be no reason to reject the hypothesis that the variance-covariance matrices are equal across all levels of the between-subjects factors. We can conclude, therefore, that the assumption of homogeneity of variance of the error effects is not violated in this data set.

Table 2

Box's M Test for Homogeneity of Dispersion

Measure F P

Alpha Production 1.128 .338

Total Relaxation 0.317 .970

 

Hypothesis 1

It was hypothesized that alpha frequency binaural beats stimulation would increase alpha brain wave production above eyes-open baseline levels.

Table 3 shows the results of the 2 X 4 SPSSX repeated measures ANOVA of alpha production.

Table 3

ANOVA Summary for Alpha Production Ratios

Source SS df MS F

Between .01 3 .003 1.07

Error .20 56 .004

Within .04 1 .04 101.84*

Interaction .01 3 .003 4.16**

Error .02 56 .0004

*p < .01

**p < .05

 

Between effect showed no significant differences among the groups, indicating that all groups were essentially equal in their baseline alpha production. However, the within effect, the difference between baseline and treatment alpha ratios, was significant (F(1,56) = 101.84; p < .01). Table 4 displays the group means for baseline and treatment alpha production.

Table 4

Mean Alpha Production Ratios

| Baseline | Treatment | Marginal*

Group| Mean SD | Mean SD | Mean

| | |

A | .081 (.033) | .114 (.044) | .098

B | .073 (.028) | .092 (.033) | .083

C | .084 (.040) | .134 (.052) | .109

D | .075 (.045) | .127 (.068) | .101

-----+------------------+--------------------+------------

* | .078 (.036) | .117 (.052) | .098

-----+------------------+--------------------+------------

*row and/or column averages

Additionally, a significant interaction effect was found (F(3,56) = 4.16; p < .05), indicating that significant differences were present in cell group means.

 

Post-hoc analysis was accomplished by the SPSSX one-way analysis of variance follow-up procedure. As demonstrated by Table 5, the treatment alpha production ratio of Group A was found to be significantly higher than the baseline alpha production ratio (F(1,56) = 93.34; p < .01). Thus Hypothesis 1 was not rejected. Omega squared for the effect ( = .613) indicates that we can conclude that the treatment for group A accounts for about 61% of the variance in the alpha production scores.

 

Table 5

ANOVA Summary for Followup on Group A

Source SS df MS F

Between groups .0327 1 .0327 93.3429*

Error .0196 56 .0004

 

*p < .01

Hypothesis 2

It was hypothesized that visual eyes-open alpha biofeedback training will increase alpha production above eyes-open baseline levels.

As demonstrated by Table 6, post-hoc analysis reveals that the treatment alpha production ratio of Group B was found to be significantly higher than the baseline alpha production ratio of Group B (F(1,56) = 30.94; p < .01). Thus Hypothesis 2 was not rejected. Omega squared ( = .346) indicates that the treatment accounts for about 35% of the variance in the alpha production scores of Group B.

Table 6

ANOVA Summary for Followup on Group B

Source SS df MS F

Between Groups .0108 1 .0108 30.9429*

Error .0196 56 .0004

 

*p < .01

Hypothesis 3

It was hypothesized that the combination of visual eyes-open alpha biofeedback training with alpha frequency binaural beats stimulation will interact to increase alpha production more than either technique alone.

As demonstrated by Table 7, post-hoc analysis reveals that the treatment alpha production ratio of Group C is significantly higher than the baseline alpha production ratio (F(1,56) = 214.29; p < .01). Omega squared ( = .785) indicates that the treatment effects account for about 79% of the variance in the alpha production of Group C.

 

Table 7

ANOVA Summary for Followup on Group C

Source SS df MS F

Between Groups .0750 1 .0750 214.286*

Error .0196 56 .0004

 

*p < .01

Follow-up analysis of the interactions between groups is displayed in Table 8. As indicated, a significant interaction was found (F(3,112)=2.6914; p < .05).

Table 8

ANOVA Summary for Followup on Interaction

Source SS df MS F

Between Groups .0153 3 .0051 2.6914*

Error .2128 112 .0019

*p < .05

Tukey's HSD test revealed that the groups which were significantly different at the .05 level were Groups B and C. Omega squared ( = .0417) indicates that the differential treatment of groups B and C accounts for about 4% of the variance between the two groups' alpha production scores.

Group C did not differ significantly from Group A, thus Hypothesis 3 was rejected.

Hypothesis 4

It was hypothesized the combination of alpha binaural beats with alpha biofeedback would result in increased subjective report of relaxation.

Table 9 displays the results of the 2 X 4 SPSSX repeated measures ANOVA on subjective report of

Table 9

ANOVA Summary for Subjective Report of Total Relaxation

Source SS df MS F

Between 37.67 3 12.56 1.20

Error 585.20 56 10.45

Within 1116.30 1 1116.30 214.97*

Interaction 19.90 3 6.63 1.28

Error 290.80 56 5.19

*p < .01

total relaxation. Between effect showed no significant difference among the groups, indicating that the groups were essentially equal in their pretest scores on subjective report of mental and physical relaxation. However, results also indicated that the within effect, the difference between pre- and post-test scores of mental and physical relaxation, was significant (F(1,56) = 214.97; p <.01). No interaction effect was found. Table 10 provides the means and standard deviations of the pre- and post-treatment scores of relaxations.

 

Table 10

ANOVA Summary for Mean Subjective Report of Total

Relaxation

| Pre-test | Post-test | Margin*

Group| Mean SD | Mean SD | Mean

| | |

A | 11.1 (3.62) | 4.07 (1.67) | 7.59

B | 10.2 (3.26) | 4.53 (2.33) | 7.37

C | 11.3 (3.56) | 6.33 (1.76) | 8.82

D | 11.4 (3.16) | 4.73 (2.22) | 8.07

* | 11.0 (3.40) | 4.92 (2.00) | 7.96

*row and/or column averages

In relation to Hypothesis 4, the post-treatment relaxation scores of Group C were found to be significantly higher than the pre-treatment scores (F(1,56)=144.51; p<.01), resultantly Hypothesis 4 was not rejected. Table 11 displays the results of the follow-up ANOVA on pre- and post-test total relaxation scores. Omega squared ( = .712) indicates that the treatment effects account for about 71% of the variance in the total relaxation scores of Group C.

 

Table 11

ANOVA Summary for Follow-up on Group C Total

Relaxation

Source SS df MS F

Between Groups 750.0 1 750.0 144.5*

Error 290.6 56 5.19

*p < .01

 

Qualitative Data Gathered

In addition to the quantitative data gathered, anecdotal information was gathered during open interviews which supplements the quantitative data already reported. At the end of the procedure, each subject was uniformly asked, "How was your experience?" Subjects in groups A and C were also asked, "How was your experience of the beats?" Subjects in groups B and C were asked, "How was your experience of the feedback?" and "What strategies were successful in increasing alpha?" Subjects in group C were asked, "Were there any associations between your focus on the beats and your alpha production?" Group D subjects were asked, "How was your experience of the surf sounds?" Information concerning the responses to these questions is reported as it relates to common themes among the groups and differential themes between the groups.

 

All Groups

The characteristic response of subjects, regardless of the treatment group, was that the experience was enjoyable, pleasant and relaxing. Numerous subjects reported various visual,

auditory, tactile or kinesthetic sensations. These sensations are reported in relation to the group or treatment with which they were associated. A number of subjects in all groups reported drowsiness and a desire to close the eyes. Other common themes reported were feelings of peace, calm and tranquility, altered perception of time, feelings of numbness, and disassociation from the body. An additional theme noted in all groups was difficulty eliminating intrusive thoughts.

 

Associations With the Binaural Beats

Subjects in groups A and C received alpha frequency binaural beats stimulation. In response to the question, "How was your experience of the beats?" the following themes were noted: a) the beats were comfortable, pleasant and relaxing, b) felt more physically relaxed when focused on the beats, c) the beat was helpful in eliminating intrusive thoughts and relaxing mentally, d) perception of the beat tended to change in frequency and amplitude, depending on focus e) creative imagery or insights came to mind, f) physical sensations such as bodily warmth or tingling, and g) intracranial sensations, such as feelings of light pressure, especially in the temporal and frontal areas.

Three subjects reported difficulty focusing on the beat. Three subjects with previous meditation experience reported the beats to be more relaxing than other relaxation or meditation strategies. One subject reported that she could use the memory of the beat to recall the feelings she experienced with it.

One subject reported that the color of the visual stimulus seemed to fade when focusing on the tones. The same subject noted a visual perception of a clockwise rotation of the colors green and red at a rate of about two cycles per second.

Two subjects associated the beats with sensations in the sinuses; one reported that the beat caused a pressure build-up while another reported that the beat seemed to cause her sinus drainage to stop. The subject who reported that the beats caused her sinus drainage to stop reported that she "moved it around my body and it stopped my cough and relieved the tension in my neck."

 

Associations With Alpha Feedback

Subjects in groups B and C received alpha feedback and were asked how they experienced the feedback and what strategies were helpful in increasing alpha. Subjects generally reported that the feedback was pleasant and interesting. Several also reported that it was difficult not to let the movement of the lights interfere with their efforts to become mentally relaxed.

Themes which surfaced in regard to successful strategies discovered included a) confirmation of oculomotor strategies which affected alpha, b) deep breathing and or exhalation was associated with increased alpha, c) verbal strategies such as affirmations increased alpha, d) mental imagery such as pleasant memories or scenes increased alpha, e) mental effort or thinking decreased alpha, f) alpha increased when momentarily between thoughts, g) alpha increased when focused on the binaural beats, and h) it became easier to control alpha production as the session progressed.

Three subjects reported identifying no successful strategies for increasing alpha and two reported identifying no feelings which corresponded to increased alpha.

 

Associations With the Surf Sounds

In response to questions regarding experience of the surf sounds subjects unanimously reported positive feelings and associations. There seemed to be a higher level of enthusiasm for the surf sounds than for the binaural beats. One obvious explanation is that surf sounds often are associated with pleasant beach and ocean memories. Several subjects in Group D reported such associations.

Group C

Group C subjects were asked uniformly if they noticed any correlation between their focus on the binaural beat and the movement of the two lights indicating increased alpha. Nine of the fifteen subjects stated in various ways that focusing on the beat was a successful strategy in increasing alpha. The following statements are verbatim reports from four of these subjects:

Subject #53 was observed to have an unusually high alpha production near the end of the session. During the interview he reported to have gained complete control of the lights by his focus on the beats. He stated, "The beat increased slightly in frequency and volume right after alpha increased dramatically. Then I used that memory to make alpha increase again."

Subject #56 reported that he felt "a moving rolling pressure across the frontal area and then filling both sides as the beats filled my mind and the alpha increased."

Subject #27 reported "the tones became like a bar in the front of my head and when the bar formed the beat disappeared and the alpha increased."

Subject #34 reported that she "was able to focus on the lower tone in my right ear and bring it to the other until when they came together and I heard the beat, the alpha lights would go all the way out."

 

Summary, Conclusions and Recommendations

Summary

The data provides evidence that all groups demonstrated increases in alpha production and subjective experience of both mental and physical relaxation resulting from the treatment procedures. The only interaction found was that of groups B and C. Under the conditions of this study, the combination of alpha-frequency binaural beats and alpha brain-wave feedback resulted in significantly more alpha production than alpha brain-wave feedback alone.

 

Conclusions

The conclusions that can be drawn from this study are presented as they relate to each hypothesis.

Hypothesis 1

Hypothesis 1, that alpha-frequency binaural beats stimulation would increase alpha brain wave production, was not rejected. However, the increase in alpha production over baseline was due to numerous factors, one of which was the binaural- beat stimulation. The subjects also received brief relaxation response instructions and conditions conducive to relaxation were provided. It should be noted that group A, which received alpha- frequency binaural beats, did not differ significantly in treatment alpha production from Group D, which received artificially produced surf sounds. It cannot be concluded from this data that the increase in alpha for Group A was due to a frequency-following response.

Hypothesis 2

Hypothesis 2, that visual eyes-open alpha- frequency biofeedback training would increase alpha production above eyes-open baseline levels, was not rejected. However, the amount of alpha increase which is due to the biofeedback training as opposed to other treatment effects such as the relaxation-response training or naturally occurring biological rhythms is indeterminable from these results.

Hypothesis 3

Hypothesis 3, that the combination of alpha feedback and alpha binaural beats would interact to increase alpha production more than either technique alone, was rejected. The treatment alpha production of Group C (feedback and beats) was significantly greater than that of Group B (feedback only) but not that of Group A (beats only). Before concluding that the difference between Groups B and C was due to the alpha- frequency binaural beats, it must be noted that the most parsimonious explanation of this difference is that the addition of a pleasant, constant auditory stimulus made conditions more conducive to spontaneous alpha for subjects in Group C. These results do not necessarily lead to the conclusion that the increase in alpha-frequency brain-wave production is due specifically to the presentation of alpha-frequency binaural beats. It should be noted that Group C did not differ significantly in alpha production from Group D, which also received a pleasant, constant auditory stimulus.

A conceptual distinction between spontaneous and evoked cortical potentials is helpful when considering the effects of alpha-frequency binaural beats. Since the human alpha rhythm is a naturally occurring or spontaneous rhythm of the cortex, deciding how much if any of the alpha production was evoked by the alpha-frequency binaural beats is difficult. Due to methodological limitations of this study, it is impossible to state conclusively that any of the alpha production was evoked. It could be argue that the most parsimonious explanation of the difference in alpha production between groups B and C is that group C conditions were more optimal for spontaneous alpha due to the addition of a constant, pleasant auditory stimulus.

It is useful to note that subjects in groups B and C were presented with conditions which usually induce alpha blocking. The alpha feedback was both visual and moving, and subjects were given the tasks of identifying associations with increased alpha and strategies which caused alpha to increase. Given this information--the visual stimuli and complex tasks of these groups--it might be expected that these two groups would produce less treatment alpha than the other seemingly less active groups. Since these two groups produced as much treatment alpha as the other two groups, it could then be argued that these two groups were resultantly more active in their production of alpha than the other two groups. The additional information in the next section concerning the subjective reports of associations made between the beats and alpha production

may promote the argument that a significant part of that activity involved, for group C, an active focus on the binaural beats.

 

Associations Between Alpha Beats and Alpha

Production

The subjective reports of associations between alpha production and focus on the alpha frequency beats are not only worthy of note but perhaps the most significant findings of this study. Nine of the fifteen subjects in Group C reported that increased attention to the beats was associated with increased alpha production. One might argue that since this association was implied by the conditions of the treatment, subjects were simply responding to suggestion or expectation effects. However, the detail of the events involved in the association reported by several of the subjects warrants a consideration of the possibility that these subjects did in fact voluntarily self- regulate their own alpha production by their attentional focus on the beats. Another possibility that warrants consideration is that a portion of the alpha production of these subjects was evoked by the alpha frequency binaural beats.

 

Hypothesis 4

Hypothesis 4, that the combination of alpha binaural beats with alpha biofeedback would result in increased subjective report of relaxation, was not rejected. Evidently the procedure was experienced to be both mentally and physically relaxing. Since there was no interaction among the groups, the beats and feedback procedure was found to be no more relaxing than the other procedures.

 

Recommendations

The following recommendations are made in regard to the further investigation of the interactions of binaural beats and biofeedback for the purpose of facilitating self-regulation and management of consciousness:

1. The use of additional beat frequencies and feedback techniques and such methodological refinements necessary to enable more conclusive statements concerning the ability of binaural beats to entrain electrocortical rhythms.

2. Longitudinal quantification of the effects of binaural-beat techniques on states of consciousness.

3. The integration of EEG measurement, assessment and feedback wherein naturally occurring rhythms are detected and appropriate binaural beats are fed back which stabilize or enhance a desired indigenous state of consciousness or entrain an otherwise targeted state of consciousness.

 

 

References

 

Adrian, E. D. & Matthews, B. H. (1934). The Berger rhythm: Potential changes from the occipital lobes in man. Brain, 57, 355-385.

Anand, B. K., Chhina, G. S., & Singh, B. (1961). Some aspects of electroencephalographic studies in yogis. Electroencephalography and Clinical Neurophysiology, 13, 452-456.

Ancoli, S., & Green, K. F. (1977). Authoritarianism, introspection, and alpha wave biofeedback training. Psychophysiology, 14, 40-44.

Andreychuk, T., & Skriver, C. (1975). Hypnosis and biofeedback in the treatment of migraine headache. International Journal of Clinical and Experimental Hypnosis, 23, 172-183.

Aranibar, A., & Pfurtscheller, G. (1978). On and off effects in the background EEG activity during one- second photic stimulation. Electroencephalography and Clinical Neurophysiology, 44, 307-316.

Atwater, F. H. (1988). The Monroe Institute's Hemi- Sync process: A theoretical perspective. Faber, VA: Monroe Institute.

Bagchi, B. K., & Wenger, M. A. (1958). Simultaneous EEG and other recordings during some yogic practices. Electroencephalography and Clinical Neurophysiology, 10, 193.

Banquet, J. P. (1972). EEG and meditation. Electroencephalography and Clinical Neurophysiology, 33, 454.

Banquet, J. P. (1973). Spectral analysis of the EEG in meditation. Electroencephalography and Clinical Neurophysiology, 35, 143-151.

Bear. (1977). Efficacy of alpha biofeedback training in elevating mood. Journal of Consulting and Clinical Psychology, 45, 334.

Benson, H. (1975). The relaxation response. New York: Morrow.

Blundell, G. G. (undated). The meaning of EEG. London: Audio Ltd.

Brolund, J. W., & Schallow, J. R. (1976). The effects of reward on occipital alpha facilitation by biofeedback. Psychophysiology, 13, 236-241.

Brown, B. B. (1970). Recognition of aspects of consciousness through association with EEG alpha activity represented by a light signal. Psychophysiology, 6, 442-452.

Brown, B. B. (1974). New mind new body. New York: Harper and Row.

Cade, C. M., & Coxhead, N. (1979). The awakened mind. Longmead, Great Britain: Element Books. Caton, R. (1875). The electric currents of the brain. British Medical Journal, 2, 278.

Cohen, M. J., McArthur, D. L., & Rickles, W. H. (1980). Comparison of four biofeedback treatments for migraine headache: Psychological and headache variables. Psychosomatic Medicine, 42, 463-480.

Cott, A., Pavloski, R. P., & Goldman, J. A. (1981). Cortical alpha rhythm, biofeedback, and the determinants of subjective state. Journal of Experimental Psychology: General, 110, 381-397.

Davidson, R. J., Schwartz, G. E., & Shapiro, D. (1980). Consciousness and self-regulation: Advances in research. (Vol. 3). New York: Plenum Press.

Degood, D. E., & Valle, R. S. (1975). A state-trait analysis of alpha density and personality variables in a normal population. Journal of Clinical Psychology, 31, 624-631.

Dewan, E. M. (1967). Occipital alpha rhythm, eye position, and lens accommodation. Nature, 214, 975-977.

Dobie, R. A., & Norton, S. J. (1980). Binaural interaction in human auditory evoked potentials. Electroencephalography and Clinical Neurophysiology, 49, 303-313.

Empson, J. (1986). Human brainwaves: The psychological significance of the electroencephalogram. New York: Stockton Press.

Engstrom, D. R., London, P., & Hart, J. T. (1970). Hypnotic susceptibility increased by EEG alpha training. Nature, 227, 1261-1262.

Evans, F. J. (1972). Hypnosis and sleep: Techniques for exploring cognitive acitvity during sleep. In E. Fromm & R. E. Shor (Eds.), Hypnosis: Research developments and perspectives. Chicago: Aldine- Atherton.

Galbraith, G. C., London, P., Leibovitz, M. P., Cooper, L. M., & Hart, J. T. (1970). EEG and hypnotic susceptibility. Journal of Comparative and Physiological Psychology, 72, 125-131.

Gerken, G. M., Moushegian, G., Stillman, R. D., & Rupert, A. L. (1975). Human frequency-following responses to monaural and binaural stumuli. Electroencephalography and Clinical Neurophysiology, 38, 379-386.

Giannitrapani, D. (1985). The electrophysiology of intellectual functions. New York: Karger.

Glaser, G. H. (1963). EEG and behavior. New York: Basic Books.

Goesling, W. J. (1974). Relationship between internal and external locus of control and the operant conditioning of alpha through biofeedback training. Perceptual and Motor Skills, 39, 1339- 1343.

Goldberg, R. J., Greenwood, J. C., & Taintor, Z. (1976). Alpha conditioning as an adjunct treatment for drug dependence: I. International Journal of the Addictions, 11, 1085-1089.

Goodman, D. M. (1976). The effect of oculomotor activity on alpha-blocking in the absence of visual stimuli. Psychophysiology, 13, 462-465.

Green, E. E., Green, A. M., & Walters, E. D. (1970). Voluntary control of internal states: psychological and physiological. Journal of Transpersonal Psychology, 2, 1-25.

Hardt, J. V., & Kamiya, J. (1976). Some comments on Plotkin's self-regulation of electroencephalographic alpha. Journal of Experimental Psychology: General, 105, 100-108.

Hardt, J. V., & Kamiya, J. (1978). Anxiety change through electroencephalograph alpha feedback seen only in high anxiety subjects. Science, 201, 79-81.

Hartman, L. M., & Ainsworth, K. D. (1980). Self- regulation of chronic pain: Preliminary empirical findings. Canadian Journal of Psychiatry, 25, 38-

43.

Instruction manual for the hemi-sync synthesizer model 201B. (undated). Nellysford, VA: Interstate Industries.

Holmes, D. S., Burish, T. G., & Frost, R. O. (1980). Effects of instructions and biofeedback on EEG alpha production and the effects of EEG alpha biofeedback training for controlling arousal in a subsequent stressful situation. Journal of Research in Personality, 14, 212-223.

Honorton, C., Davidson, R., & Bindler, P. (1972). Shifts in subjective state associated with feed- back augmented EEG alpha. Psychophysiology, 9, 262.

Hord, D. J., Lubin, A., Tracy, M. L. Jensma, B. W., & Johnson, L. C. (1976). Feedback for high EEG alpha does not maintain performance or mood during sleep loss. Psychophysiology, 13, 58-62.

Hutchison, M. (1986). Megabrain: New tools and techniques for brain growth and mind expansion. New York: Beech Tree Books.

Inouye, T., Shinosaki, K., Yagasaki, A., & Shimizu, A. (1986). Spatial distribution of generators of alpha activity. Electroencephalography and Clinical Neurophysiology, 63, 353-360.

Inouye, T., Sumitsuji, N. & Matsumoto, K. (1980). EEG changes induced by light stimuli modulated with the subject's alpha rhythm. Electroencephalography and Clinical Neurophysiology, 49, 135-142.

Jackson, G. M., & Eberly, D. A. (1982). Facilitation of performance on an arithmetic task as a result of the application of a biofeedback procedure to suppress alpha wave activity. Biofeedback and Self-Regulation, 7, 211-221.

Jasper, H. H. (1958). Report of the committee of methods of clinical examination in electroencephalography. Electroencephalography and Clinical Neurophysiology, 10, 370.

Johnson, R. K., & Meyer, R. G. (1974a). Phased biofeedback approach for epileptic seizure control. Journal of Behavior Therapy and Experimental Psychiatry, 5, 185-187.

Johnson, R. K., & Meyer, R. G. (1974b). The locus of control construct in EEG alpha rhythm feedback. Journal of Consulting and Clinical Psychology, 42,

913.

Kamiya, J. (1969). Operant control of the EEG alpha rhythm and some of its reported effects on consciousness. In C. T. Tart (Ed.), Altered states of consciousness (pp. 519-529). Garden City, N. Y.: Anchor Books.

Kasamatsu, A., & Hirai, T. (1969). An electroencephalographic study on the zen meditation (Zazen). In C. T. Tart (Ed.), Altered states of consciousness (pp. 501-514). Garden City, N.Y.: Anchor Books.

Kirk, R. E. (1982). Experimental design: Procedures for the behavioral sciences. (2nd ed.). Monterey, CA: Brooks/Cole.

Klinger, E., Gregoire, K. C., & Barta, S. G. (1973). Physiological correlates of mental activity: Eye movements, alpha, and heart rate during imaging, suppression, concentration, search, and choice. Psychophysiology, 10, 471-477.

Kondo, C. Y., Travis, T. A., & Knott, J. R. (1973). Initial abundance and amplitude of alpha as determinants of performance in an enhancement paradigm. Electroencephalography and Clinical Neurophysiology, 35, 106.

Kondo, C. Y., Travis, T. A., Knott, J. R., & Bean, J. A. (1979). Effects of true and inverted feedback on integrated occipital alpha. Journal of Psychology, 102, 101-106.

Leib, W., Tryon, W. W., & Stroebel, C. S. (1976). Alpha biofeedback: Fact or artifact? Psychophysiology, 13, 541-545.

London, P., Hart, J. T., & Leibovitz, M. P. (1968). EEG alpha rhythms and susciptibility to hypnosis. Nature, 219, 71-72.

Lindholm, E., & Lowry, S. (1978). Alpha production in humans under conditions of false feedback. Bulletin of the Psychonomic Society, 11, 106-108.

Lindsley, D. B. (1952). Psychological phenomenon and the electroencephalogram. Electroencephalography and Clinical Neurophysiology, 4, 443.

Ludlam, W. H. (1981). Visual electrophysiology and reading/learning difficulties. Journal of Learning Disabilities, 14, 587-590.

Lynch, J. L., Paskewitz, D. A., & Orne, M. T. (1974). Inter-session stability of human alpha rhythm densities. Electroencephalography and Clinical Neurophysiology, 36, 538-540.

Malmo, R. B. (1959). Activation: A neuropsychological dimension. Psychology Review, 66, 367.

Mandelzys, N., Lane, E. B., & Marceau, R. (1981). The relationship of violence to alpha levels in a biofeedback training paradigm. Journal of Clinical Psychology, 37, 202-209.

Marshall, M. S., & Bentler, P. M. (1976). The effects of deep physical relaxation and low- frequency-alpha brainwaves on alpha subjective reports. Psychophysiology, 13, 505-516.

Martindale, C. (1978). Creativity, consciousness, and cortical arousal. Journal of Altered States of Consciousness, 3, 69-87.

Martindale, C., & Armstrong, J. (1974). The relationship of creativity to cortical activation and its operant control. Journal of Genetic Psychology, 124, 311-320.

Martindale, C., & Hines, D. (1975). Creativity and cortical activation during creative, intellectual and EEG feedback tasks. Biological Psychology, 3, 91-100. Melzack, R., & Perry, C. (1975). Self- regulation of pain: The use of alpha-feedback and hypnotic training for the control of chronic pain. Experimental Neurology, 46, 452-569.

Mikuriya, T. H. (1979). Interhemispheric alpha rhythm synchronization: A voluntary altered state of consciousness. American Journal of Clinical Biofeedback, 2, 22-25.

Mills, G. K., & Solyom, L. (1974). Biofeedback of EEG alpha in the treatment of obsessive ruminations: An exploration. Journal of Behavior Therapy and Experimental Psychiatry, 5, 37-41.

Monroe, R. (1982). The Hemi-Sync process. Monroe Institute Bulletin, #PR31380H. Nellysford, VA.

Monroe, R. (1985). The Hemi-Sync synthesizer. Breakthrough. Faber, VA: Monroe Institute.

Moushegian, G., Rupert, A. L., & Stillman, R. D. (1978). Evaluation of frequency-following potentials in man: Masking and clinical studies. Electroencephalography and Clinical Neurophysiology, 45, 711-718.

Mulholland, T., & Evans, C. R. (1966). Oculomotor function and the alpha activation cycle. Nature, 211, 1278-1279.

Neher, A. (1961). Auditory driving observed with electrodes in normal subjects. Electroencephalography and Clinical Neurophysiology, 13, 449-451.

Nogawa, T., Katayama, K., Tabata, Y., & Ohshio, T. (1976). Electroencephalography and Clinical Neurophysiology, 40, 78-88.

Norusis, M. J. (1988). SPSS-X advanced statistics guide. (2nd. ed.) Chicago: SPSS Inc.

Nowak, S. M., & Marczynski, T. J. (1981). Trait anxiety is reflected in EEG alpha response to stress. Electroencephalography and Clinical Neurophysiology, 52, 175-191.

Nowlis, D. P., & Kamiya, J. (1970). The control of electroencephalographic alpha rhythms through auditory feedback and the associated mental activity. Psychophysiology, 6, 476-484.

Nowlis, D. P., & Rhead, J. C. (1968). Relation of eyes-closed resting EEG alpha activity to hypnotic susceptibility. Perceptual and Motor Skills, 27, 1047-1050.

Nowlis, D. P., & Wortz, E. C. (1973). Control of the ratio of midline parietal to midline frontal EEG alpha rhythms through auditory feedback. Perceptual and Motor Skills, 37, 815-824.

Orne, M. T., & Paskewitz, D. A. (1974). Aversive situational effects on alpha feedback training. Science, 186, 458-460.

Oster, G. (1973). Auditory beats in the brain. Scientific American, 229, 94-102.

Paskewitz, D. A., & Orne, M. T. (1973). Visual effects on alpha feedback training. Science, 181, 360-363.

Pelletier, K. R., & Peper, E. (1977). Developing a biofeedback model: Alpha EEG feedback as a means for pain control. The International Journal of Clinical and Experimental Hypnosis, 25, 361-371.

Peniston, E. G., & Kulkosky, P. J. (1989). Alpha- theta brainwave training and beta-endorphin levels in alcoholics. Alcoholism: Clinical and Experimental Research, 13, 271-279.

Picton, T. W., Woods, D. L., & Proulx, G. B. (1978). Human auditory sustained potentials. I. The nature of the response. Electroencephalography and Clinical Neurophysiology, 45, 186-197.

Picton, T. W., Woods, D. L., & Proulx, G. G. (1978). Human auditory sustained potentials. II. Stimulus relations. Electroencephalography and Clinical Neurophysiology, 45, 198-210.

Plotkin, W. B. (1976a). Appraising the ephemeral alpha phenomenon: A reply to Hardt and Kamiya. Journal of Experimental Psychology: General, 105, 109-121.

Plotkin, W. B. (1976b). On the self-regulation of the occipital alpha rhythm: Control strategies, states of consciousness, and the role of physiological feedback. Journal of Experimental Psychology: General, 105, 66-99.

Plotken, W. B. (1978). Long-term eyes-closed alpha-enhancement training: Effects on alpha amplitudes and on experiential state. Psychophysiology, 15, 40-52.

Plotkin, W. B. (1979). The alpha experience revisited: Biofeedback in the transformation of psychological state. Psychological Bulletin, 86, 1132-1148.

Plotkin, W. B., & Cohen, R. (1976). Occipital alpha and the attributes of the "alpha experience." Psychophysiology, 13, 16-21.

Plotkin, W. B., Mazer, C., & Loewy, D. (1976). Alpha enhancement and the likelihood of an alpha experience. Psychophysiology, 13, 466-471.

Plotkin, W. B., & Rice, K. M. (1981). Biofeedback as a placebo: Anxiety reduction facilitated by training in either suppression or enhancement of alpha brainwaves. Journal of Consulting and Clinical Psychology, 49, 590-596.

Potolicchio, S. J., Zukerman, A. S., & Chernigovskaya, N. V. (1979). Feedback control of human alpharhythm from the central area. Biofeedback and Self-Regulation, 4, 211-219.

Pressner, J. A., & Savitsky, J. C. (1977). Effect of contingent and noncontingent feedback and subject expectancies on electroencephalographic biofeedback training. Journal of Consulting and Clinical Psychology, 45, 713-714.

Prewett, M. J., & Adams, H. E. (1976). Alpha activity suppression and enhancement as a function of feedback and instructions. Psychophysiology, 13, 307-310.

Rao, K. R., & Feola, J. (1979). Electrical activity of the brain and ESP: An exploratory study of alpha rhythm and ESP scoring. Journal of Indian Psychology, 2, 118-133.

Regan, D. (1966). Some characteristics of average steady-state and transient responses evoked by modulated light. Electroencephalography and Clinical Neurophysiology, 20, 238-248.

Robinson, S. (1974). Relationship between EEG and behavior. In T. M. Itil (Ed.), Psychotropic drugs and the human EEG. Modern problems in pharmacopsychiatry: Vol. 8. Clinical EEG correlations (pp. 286-300). New York: Turan M. Itil.

Rockstroh, B., Birbaumer, N., Elbert, T., & Lutzenberger, W. (1984). Operant control of EEG and event-related and slow brain potentials. Biofeedback and Self-Regulation, 9, 139-160.

Rouse, L., Peterson, J., & Shapiro, G. (1975). EEG alpha entrainment reaction within the biofeedback setting and some possible effects on epilepsy. Physiological Psychology, 3, 113-122.

Saul, J. J., David, H., & Davis, P. A. (1949). Psychologic correlations with the electroencephalogram. Psychosomatic Medicine, 11, 361.

Schwartz, G. E., & Shapiro, D. (Eds.). (1976). Consciousness and self-regulation: Advances in research. (Vol. 1). New York: Plenum Press.

Schwibbe, M., Bruell, A., & Becker, D. (1981). Peak centered power spectra: A successful attempt to calculate efficient parameters in the alpha range of EEG. Electroencephalography and Clinical Neurophysiology, 52, 497-500.

Smith, J. C., Marsh, J. T., & Brown, W. S. (1975). Far-field recorded FFR's: Evidence for the locus of brainstem sources. Electroencephalography and Clinical Neurophysiology, 39, 465-472.

Smith, J. C., Marsh, J. T., Greenberg, S., & Brown, W. S. (1978). Human auditory frequency-following responses to a missing fundamental. Science, 201, 639-641.

Sohmer, H., Pratt, H., & Kinarti, R. (1977). Sources of frequency following responses (FFR) in man. Electroencephalography and Clinical Neurophysiology, 42, 656-664.

Sterman, M. B. (1973). Neurophysiological and clinical studies of sensorimotor EEG biofeedback training: Some effects on epilepsy. Seminars in Psychiatry, 5, 507-525.

Stewart, R. A. (1974). Self-realization as the basis psychotherapy: A look at two Eastern-based practices, transcendental meditation and alpha brain wave biofeedback. Social Behavior and Personality, 2, 191-200.

Stillman, R. D., Crow, G., & Moushegian, G. (1978). Components of the frequency-following potential in man. Electroencephalography and Clinical Neurophysiology, 44, 438-446.

Surwillo, W. W. (1971). Human reaction time and period of the EEG in relation to development. Psychophysiology, 8, 468.

Travis, T. A., Konko, C. Y., & Knott, J. R. (1974a). Parameters of eyes-closed alpha enhancement. Psychophysiology, 11, 674-681.

Travis, T. A., Kondo, C. Y., & Knott, J. R. (1974b). Personality variables and alpha enhancement: A correlative study. British Journal of Psychiatry, 124, 542-544.

Travis, T. A., Kondo, C. Y., & Knott, J. R. (1975). Subjective aspects of alpha enhancement. British Journal of Psychiatry, 127, 122-126.

Ulett, G. A., Akpinar, S., & Itil, T. M. (1972). Hypnosis: Physiological, pharmacological reality. American Journal of Psychiatry, 128, 799-805.

Walsh, D. H. (9174). Interactive effects of alpha feedback and instructional set on subjective state. Psychophysiology, 11, 428-435.

Watson, C. G., & Herder, J. (1980). Effectiveness of alpha biofeedback therapy: Negative results. Journal of Clinical Psychology, 36, 508-513.

Watson, C. G., Herder, J., & Passini, F. T. (1978). Alpha biofeedback therapy in alcoholics: An 18- month follow-up. Journal of Clinical Psychology, 34, 765-769.

Wieneke, G. H., Deinema, C. H., Spoelstra, P., Storm Van Leeuwen, W., & Versteeg, H. (1980). Normative spectral data on alpha rhythm in male adults. Electroencephalography and Clinical Neurophysiology, 49, 636-645.

Williams, P. (1977). EEG alpha feedback: A comparison of two control groups. Psychosomatic Medicine, 39, 44-47.

Williams, P., & West, M. (1975). EEG responses to photic stimulation in persons experienced at meditation. Electroencephalography and Clinical Neurophysiology, 39, 519-522.

Woodruff, D. S. (1975). Relationships among EEG alpha frequency, reaction time, and age: A biofeedback study. Psychophysiology, 12, 673- 681.

Yaguchi, K., & Iwahara, S. (1976). Temporal sequence of frequency specific and nonspecific effects of flickering lights upon the occipital electrical activity in man. Brain Research, 107, 27-38.

Yamada, O., Yamane, H., & Kodera, K. (1977). Simultaneous recordings of the brain stem response and the frequency-following response to low-frequency tone. Electroencephalography and Clinical Neurophysiology, 43, 362-370.

Yates, A. J. (1980). Biofeedback and the modification of behavior. New York: Plenum Press.

 

Self-Report Form

 

Name: Date: Time:

Sex: F M Age: Group: A B C D

Level of Relaxation (pre-procedure):

Mental.

relaxed 1 2 3 4 5 6 7 8 9 10 tense

Physical.

relaxed 1 2 3 4 5 6 7 8 9 10 tense

Level of Relaxation (post-procedure):

Mental.

relaxed 1 2 3 4 5 6 7 8 9 10 tense

Physical.

relaxed 1 2 3 4 5 6 7 8 9 10 tense

Comments

 

 

 

 

Relaxation Response Handout

The relaxation response is an integrated mind/body reaction which has been found to have such benefits as increased mental and physical health and improved ability to deal with tension and stress. Some physiological components of the response are decreased oxygen consumption, decreased respiratiry rate, decreased heart rate, and increased alpha brain wave production. An individual's ability to voluntarily control the relaxation response thus enables a degree of control over these bodily processes. Also, gaining voluntary control of these physical processes results in greater control of the general relaxation response.

Herbert Benson in his book The Relaxation Response (1975), surveys some of the major techniques used for eliciting the relaxation response and describes the essential components of these techniques:

1. A Mental Device. A constant stimulus such as a sound, word, or phrase repeated silently or audibly, or fixed gazing at an object.

2. A Passive Attitude. If distracting thoughts occur they should be disregarded and one's attention should be redirectded to the technique. One should not worry about how well he or she is doing.

3. A Relaxed Body. A comfortable position free from muscular stress.

4. A Quiet Environment. A location free from distracting stimuli.

The research indicates that those individuals who have gained a degree of control over their relaxation response and the accompanying physiological processes through this technique have done so through regular practice. Just like any skill, practice tends to improve performance.

Benson recommends that one practice the technique for ten to twenty minutes once or twice per day.

An important component of the ability to voluntarily control the relaxation response is an identification of the subjective feelings associated with it. Once one knows where a place is, getting there becomes easier.

Thanks for volunteering to participate in this study of the relaxation response. I hope you enjoy it as much as I do.

http://brain.web-us.com/usage.htm]THE SCHUMANN'S RESONANCES AND

HUMAN PSYCHOBIOLOGYOur brain waves share and are attuned to certain frequencies of the Schumann's

resonances, the ELF signals that pulsate between the Earth's crust and ionosphere.

Extracted from Nexus Magazine, Volume 10, Number 3 (April-May 2003)PO Box 30, Mapleton Qld 4560 Australia. editor@nexusmagazine.comTelephone: +61 (0)7 5442 9280; Fax: +61 (0)7 5442 9381From our web page at: www.nexusmagazine.com

© 2002, 2003 by Richard Alan Miller and Iona Miller

PLANETARY RHYTHMS AND HUMAN HEALTH

Lewis B. Hainsworth of Western Australia seems to be the first researcher to recognise the relationship of brain-wave frequencies to the naturally circulating rhythmic signals, known as Schumann's resonances (SR), in the space between the surface of the Earth and the ionosphere. Hainsworth imparted this awareness to Dr Robert O. Becker, noted electromagnetics pollution expert, and to Harvard neurologists as early as 1975.

In 1977, this phenomenon--the relationship between brain-wave rhythms and the spectrum of the natural Earth ELF (extremely low frequency) signals--became the basis for Itzhak Bentov's Stalking the Wild Pendulum (Dutton, 1977). Later research confirmed a relationship to human health and well-being and even to ESP or psi phenomena.

Hainsworth sent up a clarion cry against hazardous EM (electromagnetic) pollution, whose dangers pale in comparison to the threat of technologies such as HAARP [High-frequency Active Auroral Research Program], which sends violent pulsations into the Earth's ionosphere, potentially disrupting the entire electromagnetic shield of the planet and certainly affecting the whole biosphere and thus human welfare in general.

Some research has suggested that the frequency of the basic Schumann's resonance has recently been rising in value, possibly threatening the whole biosphere, human welfare and our evolutionary future. All biological processes are a function of electromagnetic field interactions. EM fields are the connecting link between the world of form and resonant patterns. They store gestalts or patterns of information. The bridge connecting solar system resonances and brain frequencies resides in our human DNA helix, which co-evolved in the Earth's environment.

Electrical engineer Lewis B. Hainsworth, MA, was among the first to suggest that human health is linked with geophysical parameters by way of the naturally occurring Schumann's ELF. His hypothesis identified naturally occurring features which determine the frequency spectrum of human brain-wave rhythms:The frequencies of naturally occurring electromagnetic signals, circulating in the electrically resonant cavity bounded by the Earth and the ionosphere, have governed or determined the 'evolution' or development of the frequencies of operation of the principal human brain-wave signals. In particular, the alpha rhythm is so placed that it can in no circumstances suffer an extensive interference from naturally occurring signals.

Hainsworth concluded that the frequencies of human brain-waves evolved in response to these signals. If his hypothesis is correct, conditions for evolutionary changes in human brain-wave patterns have now been established. Furthermore, variations in these patterns can produce mild to disastrous health and behavioural changes.

The nature of the applied stimulus makes it difficult to identify the responses directly, as they are most likely to occur in the form of stress-related conditions. They will therefore show up as drastic increases in mental disturbance, antisocial behaviour, psychosomatic conditions and neurological disturbances. Some electrical field phenomena have already been linked with abnormal cell growth and a decrease in immunocompetency.

All these factors could be expected to lead to the appearance of "new" diseases, probably accompanied by a decline in resistance to many minor infections, an increase in conditions related to abnormal cell development, including cancer, birth defects and infertility, and an increase in psychological disturbance problems, e.g., drug addiction and suicide. These existing psychobiological problems could be expected to increase in scale, but could be studied for deviations from "normal" alpha cycles of 10.4 Hz, with detectable changes in psychological characteristics and mental abilities.

Hainsworth therefore strongly urged that research into widespread measurements of the natural SR signals' frequency variations and field strengths be carried out and compared with statistics for the incidence of heart attacks, suicide attempts, road accidents, social violence, domestic accidents, crimes, etc. Studies are often conducted in this inferential way (such as those by Krippner and Persinger), searching correlations between the phenomena of Earth lights and tectonic strain and reports of UFO sightings, abduction reports and other anomalous psychophysical experiences for an electromagnetic connection to temporal lobe seizures.

We strongly suggest that correlations of broad changes in the modulations of SR be studied in relationship to microwave radiation, ELF signals and HAARP for both immediate and long-term consequences. We have discussed elsewhere the obvious ramifications of such EM pollution and 10-50 Hz modulations on the human system (Miller & Miller, "Synthetic Telepathy", 2001).

We have also discussed the benefits for human well-being and relaxation from entraining with these natural rhythms (The Diamond Body, 1981). When a person is deeply relaxed, slow rhythmic sine-wave patterns can be detected in both the EEG and the heart/aorta resonating oscillator in the 7-8 Hz range. Resonance occurs when the natural vibration frequency of a body is greatly amplified by vibrations at the same frequency from another body.

Oscillators alter the environment in a periodic manner. Thus, standing waves in the body, whether during meditation/relaxation or not, can be driven by a larger signal. Progressively amplified wave-forms, created by resonance, result in large oscillations entraining other circuits in the body tuned to those frequencies. A hierarchy of frequencies thus couples our psychophysical selves to the harmonic frequency of the electrical charge of the Earth, which naturally pulses at the same frequencies. This is hardly a coincidence, as we are adaptive products of our environment.

Our planet is surrounded by a layer of electrically charged particles called the ionosphere. The lower layer of the ionosphere is roughly 60-80 kilometres (40-50 miles) from the crust, and this charged layer is known to reflect radio waves. Bombardment by HAARP signals "pushes" out this boundary layer, thus altering the natural, pulsating rhythm. Natural fluctuations in frequency occur daily, by the lunar month, and in response to solar flares.

Since the ionosphere is a highly charged layer, it forms a so-called capacitor with the Earth. This means that there is a difference in electrical potential between the two, the Earth being negatively charged and the ionosphere being positively charged. This potential varies somewhat, but is around 200 volts per metre. This is a fundamental type of electrical generator. The solar winds, interacting with the upper atmosphere rotation, act as the collector and brushes of a generator. The lower atmosphere can be seen as a storage battery for this gradient potential.

This electromagnetic field around the Earth can be viewed as a stiff jelly. When our bodies move and vibrate, these movements are transmitted to the environment, and vice versa. These fields not only impinge on our bodies, they also affect the charges inside our bodies. When we are standing on the ground, under normal conditions, we are grounded. Our body then acts as a sink for the electrostatic field and actually distorts the force-lines somewhat. The human body also has its own electrostatic field about itself.

These field lines are the result of the various biochemical reactions in the body. This resultant bio-field couples us to the iso-electric field of the planet (Miller & Miller, 1981).

In 1957, German physicist Dr W. O. Schumann calculated the Earth/ionosphere cavity resonance frequencies (which were named after him). He fixed the most predominant standing wave at about 7.83 Hz.

A "tuned system" consists of at least two oscillators of identical resonant frequencies. If one oscillator starts emitting, the other will be activated by the signal very shortly, in the process of resonance, entrainment or kindling (igniting the resonance phenomenon among the neurons). It becomes obvious that in deep meditation, when waves of alpha and theta rhythms cascade across the entire brain, a resonance is possible between the human being and the planet. Energy and information which are embedded in a field are transferred. Perhaps the planet communicates with us in this primal language of frequencies.

According to Hainsworth, the influence of naturally occurring Schumann's resonance signals on brain-wave pattern evolution is formally stated to show that low-power electrical fields could produce evolutionary change. The electrical fields produced by modern electro-technology are then possible sources of evolutionary change. The characteristics of some forms which might result should be considered. Some fields might inhibit survival of existing forms. Because of lack of available data, precise measurements are lacking and must therefore be quantitatively valueless. Technology not only will change, but is changing, human evolution. Only extensive investigation of the naturally occurring signals will give any lead in showing what results might occur.

The possibility exists that human health is linked with geophysical parameters by way of the naturally occurring Schumann's resonances. A number of attempts have been made to discover the correlation through geomagnetic and ionospheric storms. The correlation comes through the biological fact that the human system is apparently sensitive to such low-power ELF signals. We don't know what the range of such a correlation might be.

The frequency values of the SR signals are determined by the effective dimensions of the cavity between the Earth and ionosphere. Thus, any events which change these dimensions will change

the resonant frequencies. As Hainsworth warned, "such events could be ionospheric storms, and could even result from a man-made ionospheric disturbance" (emphasis added).

Geomagnetic storms are the magnetic changes produced by ionospheric storms, and are thus associated with conditions capable of changing the SR signals. However, although such storms can produce these changes, measurement of these parameters cannot give any indication of whether the resonance signals have changed to a value outside their normal range or not. Since the undisturbed state of the ionosphere corresponds to the normal SR patterns, then ionospheric disturbances are likely to produce abnormal patterns, but will not necessarily do so in all cases. If biological response is linked to Schumann's resonance signals, this will reduce any apparent link with geomagnetic or ionospheric data.

Trying to determine the relationships between geophysical and biological conditions can become extremely complex. The frequencies of the SR signals change with ionospheric conditions. These conditions change diurnally, seasonally and with variations in solar activity, which, in turn, varies with the 11-year sunspot cycle and also with the 27-29-day lunar cycle, mainly during sunspot minimum periods. Lunar tidal changes in the height and thickness of the layers could also sometimes affect the cavity dimensions and hence the Schumann's frequencies. So can powerful ELF signals from HAARP.

It should be borne in mind that if some signal conditions are harmful, then other conditions might be beneficial. This means that if, for example, seasonal and tidal conditions have resulted in the signals being in a biologically disturbing state, then the advent of a solar flare could result in changes in the signals, bringing them into a biologically beneficial state. The converse could also occur.

If we are sensitive to ELF signals, then when these factors are considered we would expect to get confusion if we try to link any effect with geophysical changes. For instance, there could be incidences of classic states of "lunacy" in some years if damaging signals coincided with full moons, then in other years the observations and analyses would show that the effects were not lunar.

An analysis of the correlation between the incidence of ionospheric disturbance and rate of admission to Heathcote Hospital (Perth, Western Australia) for about a three-year total indicated that when a disturbance occurred then the admission rate changed. The probability of the association being random was of the order of 2000:1 against. However, the fact that sometimes the rate went up and sometimes down showed that ionospheric storms changed the rate of incidence of mental disturbance in a way that is consistent with that change being dependent on the actual causes being linked to variations in the Schumann's resonance signals. At that point, Hainsworth decided to concentrate on trying to get some observational work going on measuring the SR signals.

Hainsworth's set-up used a 2,000-turn, 1-metre-square antenna, and another of 1/3-metre square, plus amplifiers to handle signals from 0 to 30 Hz. His amplified Schumann's signals were analysed in a laboratory. On one occasion the signal dropped to zero amplitude when a solar flare occurred, and did not start recovering for about an hour and a half afterwards. It was originally just under 7 Hz and came back at only just over 6 Hz. His next step would have been to develop a wave analyser to try to pick out individual signals. But the failing health of both himself and his wife prevented this.

The value of proceeding with his seminal work has now increased many-fold due to the threat from the proposed US Missile Defense Shield. This is the offspring of the United States' HAARP program in Alaska, whose raison d'être, or mission statement, allegedly dealing with national security, is vague if not purposefully misleading.

 

EM FREQUENCIES AND HUMAN RESPONSE

Hainsworth posed a series of questions, all of which are answered with a resounding "yes". This should lead us in the direction of extreme caution towards introducing new EM or ELF sources and ionospheric changes in our environment. He presented his data in two papers (referenced at the end of this article and posted on the website http://www.nwbotanicals.org). His questions are as follows:1. Does the human biological system contain, use or generate any forms of electrical signal?2. Does it respond to any of these signals?3. Does it respond to audible signals at these frequencies?4. Does it respond to optical signals at these frequencies?5. Do human signals change with psychological or mental states, such as stress or problem solving?6. Does the human system respond to any very, very low-power electromagnetic signals?

Brain waves have only been studied since about the mid-1920s, and the signal form that is apparently most widely known and identified is the alpha rhythm. The frequency of this signal varies from individual to individual, but it lies between about 7-8 Hz and 12 Hz, with an average value of 10.5 Hz. Theta and beta rhythm signals also occur, and are identifiable by EEG below the 8 Hz and above the 12 Hz frequencies. Since the discovery and measurement of these signals, a great deal of effort has been devoted to trying to work out how they originated in the first place and what determines their frequencies of operation.

In the early to mid-1950s, Schumann (a geophysicist almost certainly uninterested in neurology) suggested that electromagnetic signals might circulate at extremely low frequencies in the electrically resonant cavity between the Earth and the ionosphere. He was right. The signals came to be called "Schumann's resonances". One major component was originally predicated at a frequency of about 10 Hz. In 1959 it was measured to be slightly different. Meanwhile, the military co-opted the discovery for using ELF signals for submarine communications.

In fact, the first mode of these circulating signals has an average value of 7.8 Hz, with a typical diurnal range of from 7.2 to 8.8 Hz, and the second mode has an average value of 14.1 Hz and a range of from 13.2 to 15.8 Hz. These match the brain-wave theta rhythm and beta rhythm nicely. The blank range between the two modes is a very reasonable match with the normal frequency range of the human alpha rhythm, between 8 to 12 Hz or cycles.

Additionally, it was found that there is minimum (zero) power circulating in the Earth/ionosphere cavity at 10.4 Hz--which is virtually an exact match for the average value of the alpha rhythm. Hainsworth points out that the existence of these natural signals and the close relationship of their frequencies of oscillation were facts unknown to senior neurologists and mental health specialists as late as 1975.

Hainsworth argued that up to the end of 1979, no long-term systematic measurements of any great value were being made of the Schumann's resonance signals. Measurements were being made only intermittently for the purpose of obtaining research data for use by post-graduate geophysicists in constructing esoteric mathematical models of the ionosphere. It follows from this that, until long after the end of 1979, no figures on these signals were available. Consequently, no "expert" can produce numerical evidence to support an objection to Hainsworth's original hypothesis, since the only numerical values available are those favouring it.

However, Hainsworth left us with some open-ended questions:7. Has any evidence ever been obtained to indicate that the human system is totally unaffected

by externally applied electromagnetic fields?8. Have any measurement programs ever been attempted to show whether the human system is (a) totally unaffected, (b) always affected, or (c) sometimes affected by naturally [or artificially] occurring electromagnetic signals?9. Has the existence of such signals, having a close relationship with human biological signal frequencies, been known for many years?10. Have those relationships been studied with adequate protocols in any detail?

Schumann's resonances are actually observed, by experiment, occurring at several harmonic frequencies between 6 and 50 cycles per second (one cycle equals one hertz). Specifically they are found at 7.8, 14, 20, 26, 33, 39 and 45 Hz, with a daily variation of around ±0.5 Hz.

Only as long as the properties of Earth's electromagnetic cavity remain about the same do these frequencies remain the same. Cycles may vary somewhat due to ionospheric response to solar cycle activity and properties of the atmosphere and magnetosphere. Projects, such as HAARP, which heat up or blast out the ionosphere pose a potential threat of catastrophic proportions to this interactive system.

 

MEASURING BRAIN WAVES BY EEG

The resonant cavity formed between the ionosphere and the Earth produces rhythmic waves capable of entraining and phase-locking with brain waves.

Even at the turn of this millennium, Hainsworth (now deceased) seems to have been unfamiliar with extensive work in brain-wave research in neurology, hypnotherapy, biofeedback and neural feedback. This research includes extensive experiments in frequency-following response (FFR) and relating brain waves and brain-wave deficiencies to psychobiological states.

The brain is a massive source of ELF signals that get transmitted throughout the body through the nervous system, which is sensitive to magnetic fields. Brain waves and natural biorhythms can be entrained by strong external ELF signals, such as stationary waves at Schumann's resonances. Entrainment, synchronisation and amplification promote coherent large-scale activity rather than typical flurries of transient brain waves. Thus, resonant standing waves emerge from the brain, which under the right conditions facilitates internal and external bio-information transfer via ELF electromagnetic waves. These SR waves exhibit non-local character and nearly instant communication capability.

The EEG (electroencephalograph) measures brain waves of different frequencies within the brain. Rhythmicity in the EEG is a key variable in the coordination of cortical activity. Electrodes are placed on specific sites on the scalp to detect and record the electrical impulses within the brain. Frequency is the number of times a wave repeats itself within a second. It can be compared to the frequencies on a radio. Amplitude represents the power of electrical impulses generated by the brain. Volume or intensity of brain-wave activity is measured in microvolts.

Raw EEG frequency bands include gamma (25-60 Hz); beta (12-25 Hz); alpha (7-12 Hz); theta (4-7 Hz); and delta (less than 4 Hz). Their ranges overlap one another along the frequency spectrum by 0.5 Hz or more. These frequencies are linked to behaviours, subjective feeling states, physiological correlates, etc. Clinical improvement with EEG biofeedback is traceable to improved neuroregulation in basic functions by appeal to their underlying rhythmic mechanisms.

Schumann's resonance forms a natural feedback loop with the human mind/body. The human brain and body developed in the biosphere, the EM environment conditioned by this cyclic pulse.

Conversely, this pulse acts as a "driver" of our brains and can also potentially carry information. Functional processes may be altered and new patterns of behaviour facilitated through the brain's web of inhibitory and excitatory feedback networks. Functional processes may be altered and new patterns of behaviour facilitated through the brain's web of inhibitory and excitatory feedback networks.

The brain has its own set of vibrations it uses to communicate with itself and the rest of the body. EEG equipment distinguishes these waves by measuring the speed with which neurons fire in cycles per second. At their boundaries these waves can overlap somewhat, merging seamlessly into one another--so different researchers may give slightly different readings for the range of cycles per second (Hz). The rate of cycling determines the type of activity, kindling wave after wave over the whole surface of the brain by igniting more neurons.

The frequency bands and wave characteristics are described as follows:

¥ Gamma waves (25-60 Hz) appear to relate to simultaneous processing of information from different brain areas, e.g., involving memory, learning abilities, integrated thoughts or information-rich task processing. Gamma rhythms modulate perception and consciousness, which disappear with anaesthesia. Synchronous activity at about 40 Hz appears involved in binding sensory inputs into the single, unitary objects we perceive.

¥ Beta waves (12-25 Hz) dominate our normal waking state of consciousness when attention is directed towards cognitive tasks and the outside world. Beta is a "fast" activity, present when we are alert or even anxious, or when engaged in problem solving, judgement, decision making, information processing, mental activity and focus. Nobel Prize winner Sir Francis Crick and other scientists believe the 40 Hz beta frequency may be key to the act of cognition.

¥ Alpha waves (7-12 Hz) are present during dreaming and light meditation when the eyes are closed. As more and more neurons are recruited to this frequency, alpha waves cycle globally across the whole cortex. This induces deep relaxation, but not quite meditation. In alpha, we begin to access the wealth of creativity that lies just below our conscious awareness. It is the gateway, the entry point that leads into deeper states of consciousness. Alpha waves aid overall mental coordination, calmness, alertness, inner awareness, mind/body integration and learning.

Alpha is also the home of the window frequency known as the SR, which propagates with little attenuation around the planet. When we intentionally generate alpha waves and go into resonance with that Earth frequency, we naturally feel better, refreshed, in tune, in synch. It is, in fact, environmental synchronisation.

¥ Theta waves (4-7 Hz) occur most often in sleep but are also dominant in the deepest states of meditation (body asleep/mind awake) and thought (gateway to learning, memory). In theta, our senses are withdrawn from the external world and focused on the mindscape--internally originating signals. Theta waves are associated with mystery, an elusive and extraordinary realm we can explore. It is that twilight state which we normally only experience fleetingly as we rise from the depths of delta upon waking or drifting off to sleep. In theta, we are in a waking dream; vivid imagery flashes before the mind's eye and we are receptive to information beyond our normal conscious awareness. Theta meditation increases creativity, enhances learning, reduces stress and awakens intuition and other extrasensory perception skills.

¥ Delta waves (0-4 Hz) are the slowest but highest in amplitude. They are generated in deepest meditation and dreamless sleep. Delta waves confer a suspension of external existence and provide the most profound feelings of peace. In addition, certain frequencies within the delta range trigger the release of a growth hormone which is beneficial for healing and regeneration. This is why sleep, deep restorative sleep, is so essential to the healing process.

 

Rhythm & Harmonic Resonance

There is a harmonic relationship between the Earth and our mind/body. Earth's low-frequency iso-electric field, the magnetic field of the Earth and the electrostatic field which emerges from our body are closely interwoven. Our internal rhythms interact with external rhythms, affecting our balance, REM patterns, health, and mental focus. SR waves probably help regulate our bodies' internal clocks, affecting sleep/dream patterns, arousal patterns and hormonal secretion (such as melatonin).

The rhythms and pulsations of the human brain mirror those of the resonant properties of the terrestrial cavity, which functions as a waveguide. This natural frequency pulsation is not a fixed number, but an average of global readings, much like the EEG gives an average of brain-wave readings. SR actually fluctuates, like brain waves, due to geographical location, lightning, solar flares, atmospheric ionisation and daily cycles.

The most important slow rhythm is the daily rhythm sensed directly as the change in light. Rhythms connected with the daily rhythm are called circadian (an example is pineal gland melatonin secretion). Some experiments in the absence of natural light have shown that the basic human "clock" is actually slightly longer than one day (24 hours), and closer to one lunar day (24 hours 50 minutes).

On a slower scale, a strong influence on the Earth is its geomagnetic field, which is influenced by the following periods: the Moon's rotation (29.5 days); the Earth's rotation (365.25 days); sunspot cycles (11 or 22 years); the nutation cycle (18.6 years); the rotation of the planets (88 days to 247.7 years); and the galaxy's rotation cycle (250 million years). Very important rhythms, like hormone secretion and dominant nostril exchange, are in the order of 1-2 hours. In the range of human EEG, we have the Sun's electromagnetic oscillation of 10 Hz, while the Earth/ionosphere system is resonant at frequencies in the theta, alpha, beta-1 (low or slow) and beta-2 (high or fast) bands.

Different species often have internal generators of environmental rhythms, which can be extremely precise, up to 10-4. The frequency of these oscillators is then phase-locked-loop (PLL) synchronised with the natural rhythms. Environmental synchronisation sources are often called zeitgebers. The mechanism of optical synchronisation can be shown. The presented rhythms should inspire a better understanding of the interaction of internal and external rhythms during specific states of consciousness.

The bioelectrical domain is geared to thalamocortical generation of rhythmic activity. In neurofeedback, what is being trained is the degree of rhythmicity of the thalamocortical regulatory circuitry. Rhythmicity manages the entire range of activation and arousal in the bio-electrical domain. One role advocated for rhythmic activity is that of time binding: the need for harnessing brain electrical activity, which is spatially distributed, while maintaining it as a single entity.

Brain waves indicate the arousal dimension, and arousal mediates a number of conditions. Changes in sympathetic and parasympathetic arousal "tune" the nervous system. Underarousal leads towards unipolar or reactive depression, attention deficit disorder, chronic pain and insomnia. Overarousal is linked with anxiety disorders, sleep onset problems, nightmares, hypervigilance, impulsive behaviour, anger/aggression, agitated depression, chronic nerve pain and spasticity. A combination of underarousal and overarousal causes anxiety and depression as well as ADHD.

Instabilities in certain rhythms can be correlated with tics, obsessive-compulsive disorder, aggressive behaviour, rage, bruxism, panic attacks, bipolar disorder, migraines, narcolepsy, epilepsy, sleep apnoea, vertigo, tinnitus, norexia/bulimia, suicidal ideation and behaviour, PMS, multiple chemical sensitivities, diabetes, hypoglycaemia and explosive behaviour.

The brain responds to inputs at a certain frequency or frequencies. The computer can create wave-form patterns or certain frequencies that compare with the mind's neural signals in terms of mind patterns. If people can control their mind patterns, they can enter different states of being (mental relaxation, study, etc.).

So what happens when the mind is entrained with a sound or vibration that reflects the thought patterns? When the mind responds to certain frequencies and behaves as a resonator, is there a harmonic frequency that the mind vibrates to or can attune to? What does the study of harmonic resonance, sound or vibration have to do with the brain's frequency waves?

Sound waves are examples of periodicity, of rhythm. Sound is measured in cycles per second (hertz or Hz). Each cycle of a wave is, in reality, a single pulse of sound. The average range of hearing for the human ear is somewhere between 16 Hz and 20,000 Hz. We cannot hear extremely low frequencies, but we can perceive them as rhythmic.

Entrainment is the process of synchronisation, where vibrations of one object will cause the vibrations of another object to oscillate at the same rate. External rhythms can have a direct effect on the psychology and physiology of the listener. Slower tempos from 48 to 70 BPMs have been proven to decrease heart and respiratory rates, thereby altering the predominant brain-wave patterns.

Binaural beats are continuous tones of subtly different frequencies, delivered to each ear independently in stereo via headphones. If the left channel's pitch is 100 cycles per second and the right channel's pitch is 108 cycles per second, the difference between the two equals 8 cycles per second. When these sounds are combined, they produce a pulsing tone that waxes and wanes in a "wah wah" rhythm.

Binaural beats are not an external sound; rather, they are subsonic frequencies heard within the brain itself. These frequencies are created as both hemispheres work simultaneously to hear sounds that are pitch-differed by key mathematical intervals (window frequencies). The brain waves respond to these oscillating tones by following them (entrainment), and both hemispheres begin to work together. Communication between the two sides of the brain is associated with flashes of creativity, insight and wisdom.

Alpha-wave biofeedback is considered a consciousness self-regulation technique, while alpha-frequency binaural beat stimulation (frequency-following response) is a passive management technique where cortical potentials entrain to or resonate at the frequency of an external stimulus. Through the self-regulation of specific cortical rhythms, we begin to control those aspects of consciousness associated with that rhythm. When the goal is alpha, either in meditation or in biofeedback, it means entraining with the primary SR.

 

MEASURING CHANGES IN SCHUMANN'S RESONANCES

Earth's background base frequency, or "heartbeat" (Schumann's resonances), fluctuates and may be rising dramatically. Though it varies between geographical regions, for decades the overall measurement was 7.8 cycles per second. This was once thought to be a constant. Global military communications were developed using this frequency. However, recent reports set the rate at

over 11 cycles and climbing. Science doesn't know why, what to make of it or even if these reports are credible.

Gregg Braden claims to have found data collected by Norwegian and Russian researchers, and says it's not been widely reported in the USA. The authors have been unable to substantiate this. Braden suggests the only reference to SR to be found in the Seattle Library reference section is tied to the weather. Science acknowledges SR as a sensitive indicator of temperature variations and worldwide weather conditions. Braden believes the fluctuating SR may be a factor in the severe weather conditions of recent years.

As previously stated, the Earth behaves like an enormous electrical circuit. The atmosphere is actually a weak conductor; and if there were no sources of charge, its existing electrical charge would diffuse away in about 10 minutes. There is a "cavity" defined by the surface of the Earth and the inner edge of the ionosphere, whose height fluctuates somewhat. It's been calculated that at any moment, the total charge residing in this cavity is 500,000 coulombs.

There is a vertical current flow between the ground and the ionosphere of 1 &endash; 3 x 10-12 amperes per square metre. The resistance of the atmosphere is 200 ohms. The voltage potential is 200,000 volts. There are about 2,000 lightning storms at any given moment worldwide. Each produces 0.5 to 1 ampere, and these collectively account for the measured current flow in the Earth's "electromagnetic" cavity.

Schumann's resonances are quasi standing-wave electromagnetic waves that exist in this cavity. Like waves on a string, they must be potentiated or "excited" in order to be observed. They are not caused by internal terrestrial factors or Earth's crustal movements or the core, which does produce magnetic fields. They seem to be related to electrical activity in the atmosphere, particularly during times of intense lightning activity. So long as the properties of Earth's electromagnetic cavity remain about the same, these frequencies remain the same. Presumably there is some change due to the solar sunspot cycle, as the Earth's ionosphere changes in response to flares and mass ejections during the 11-year cycle of solar activity. High-energy charges coming off the Sun brush across the upper atmosphere, ionising there.

Since the Earth's atmosphere carries a charge, a current and a voltage, it is not surprising to find such electromagnetic waves. The resonant properties of this terrestrial cavity were first predicted by W. O. Schumann in 1952 and 1957, and first detected by Schumann and Konig in 1954.

Much of the research in the last 20 years has been conducted by the US Department of the Navy, which uses ELF signals for communication with submarines. However, little attention is given by the military and defence contractors to issues of psychobiological health and well-being.

Between the nearly perfectly conducting terrestrial surface and ionosphere, a resonating cavity is formed. Broadband electromagnetic impulses, like those from lightning flashes, fill this cavity and create globally the so-called Schumann's resonances at frequencies in the range of 5&endash;50 Hz (Schumann, 1952; Bliokh et al., 1980; Sentman, 1987). The nominal average frequencies observed are 7.8, 14, 20, 26, 33, 39 and 45 Hz, with slight diurnal variation (Sentman and Fraser, 1991).

Standard magnetometers are not able to measure Schumann's resonances, and even the search coil (i.e., pulsation) magnetometers, which most often sample at about 0.1 Hz, do not allow such studies. Special equipment is thus needed (see, for example, Sentman and Fraser, 1991).

Current findings suggest:1. Schumann's resonances are actually observed by experiment to emerge at several frequencies related to brain waves. They range between 6 and 50 cycles per second, specifically

7.8 (alpha), 14 (low beta), 20 (mid beta), 26 (high beta), 33 (low gamma), 39 (gamma) and 45 Hz (gamma), with daily variation of about ±0.5 Hz.2. The strongest of the seven resonances is 7.83 Hz, in the alpha brain-wave range. If the rise in resonance continues, this primary resonance, the Earth pulse, changes from sub-band low alpha (7&endash;10 Hz) to sub-band high alpha (10&endash;12 Hz), perhaps influencing our ability to relax deeply, balance and integrate our mind/body connection. It could influence REM sleep and dreaming. If it continues to rise, it will breach the threshold into "fast" beta activity. Low beta (12&endash;15 Hz) is associated with lack of focused attention, and can even indicate attention deficit disorder.3. The amplitude (i.e., intensity) of the Schumann's resonances is not constant, and appears to be extremely dependent upon tropical (and hence global) temperature. Indeed, preliminary results seem to indicate that a mere one-degree increase in temperature correlates with a doubling of the SR. This could not be more significant, as it is unknown what psychobiological effect these fluctuations could have on humans.

 

SR AND GLOBAL TEMPERATURE CHANGES

One of the most crucial questions in science today centres on whether or not the planetary temperature is rising, falling or remaining unchanged. Recently global warming has been acknowledged by most in the field, and human interference (technology) is implicated.

On one hand, analyses of thermometer measurements of near-surface global (land and sea) air temperatures suggest the planet has been warming in recent decades. But satellite measurements of the planet's lower atmospheric temperature show no warming from 1979 to 1998.

Temperature data from weather balloons launched throughout the world reveal variations and trends in global temperatures that correspond to those found in the satellite-based measurements. Analysis of pressure thickness measurements from these same balloons also shows no warming in recent decades. It's no wonder we have such an ongoing "heated debate" about the recent temperature history of the Earth! Yet most people recognise that their local weather is markedly different than in past decades.

Scientists have suggested lately that another method may exist to monitor planetary temperature accurately. The idea is simple, though the underlying physics of the processes is complex. The method is based on the well-known fact that thunderstorms and lightning strikes in many parts of the world are directly related to lower-atmospheric air temperatures. Higher temperatures produce more lightning strikes, while lower temperatures tend to depress lightning activity.

Lightning discharges occurring anywhere in the world produce electromagnetic pulses that spread away from the source. Much of the energy is quickly degraded, but some of the energy the lightning produces falls in the extremely low frequency/long-wavelength domain of the electromagnetic spectrum. At these long wavelengths, the energy from a lightning strike is able to circumnavigate the Earth without serious degradation. This low-frequency/long-wavelength energy creates SR signals which can be detected throughout the world.

Understanding SR waves requires a basic appreciation of the vertical structure of the atmosphere. In the upper reaches of the ionosphere, incoming ultraviolet radiation and soft X-rays affect atoms or bonded groups of atoms, causing gains or losses of negatively charged electrons. This interaction creates an environment of positively and negatively charged particles of the high atmosphere that, among other interesting qualities, can readily conduct electricity.

The bulk of our insulating atmosphere lies between two conducting layers of the Earth's surface and the lower boundary of the ionosphere. This spherically concentric cavity, the Earth/ionosphere cavity, is bounded by those electrically conducting walls. Again, lightning discharges within the cavity produce electromagnetic pulses that spread away from the source in the extremely low frequency domain, and the conductive walls of the cavity produce some interesting effects for the low-frequency energy.

For example, energy with a frequency near 7.5 Hz would have a wavelength of about 40,000 km (recall that wavelength = speed of light / frequency). Because this wavelength equals the circumference of the Earth, the energy is able to circumnavigate the Earth/ionosphere cavity without serious degradation. The 100 or so lightning bolts occurring each second in the 1,000 lightning storms around the world contribute to the energy in the 7.5 Hz portion of the spectrum, which can be measured anywhere on the planet. It is these resonance properties of this global spherical capacitor or resonator) that Schumann predicted over 40 years ago.

In an article published in Science, MIT scientist Earle Williams (1992) constructed a powerful argument that links Schumann's resonances to convection and ultimately to widespread tropical and/or global temperature. Williams concluded that a 1°C warming in the tropics should result in a fourfold increase in lightning activity, and he presented empirical data from several locations to support his conclusion. He noted that any measurable parameter nonlinearly related to temperature could be extremely useful in assessing the most subtle changes in global temperature. Others have presented different sensitivities: Price (1993) concluded that a 1°C warming would increase global lightning activity by 7%; Price and Rind (1994) found a 5&endash;6% increase per 1°C sensitivity; while Reeve and Toumi (1998) found the sensitivity to be near 40% per 1°C. Regardless of the exact sensitivity, all these scientists conclude that lightning increases with even moderate amounts of warming worldwide. More lightning would generate a stronger SR, which may be useful in monitoring planetary temperatures.

The link between SR and the number of lightning strikes is supported by a mean day/night temperature fluctuation pattern. A diurnal pattern of worldwide lightning exists with three maxima recorded regularly due to the large number of mid- to late-afternoon thunderstorms in land areas of Africa, South America, and Southeast Asia and Australia. (Storms are first generated in Asia; later they form in Africa; and later each day they arise in South America.)

Global warming has been linked to the suspected rise in SR, and is a threat to its synchronisation with our brain waves. Small changes in temperature pump up into large signals in extremely low frequency (ELF) resonances. Long-term monitoring and study of global climate changes via measurements of ELF electromagnetic waves needs to be conducted more closely. Monitoring the intensity and frequencies of the lightning-induced ELF SR could help monitor changes in the Earth's climate over time.

One Israeli program proposed setting up two or three widely separated ELF field sites. A suggested site for a permanent SR monitoring station was in the Negev Desert in Israel. Members of this proposal want to develop, test and install the appropriate software for the automatic electromagnetic monitoring and preliminary processing of the incoming data. They suggested that simultaneous measurements could be made in Russia and Sweden to test the global nature of the ELF signals measured in Israel. The continuous ELF data measured in Israel could be compared with other ELF data sets from other locations around the world, such as Hungary, USA or Japan. Furthermore, the relevant global climate data sets&emdash;such as surface temperature, satellite observations of the global distribution of deep convection, and global atmospheric water vapour measurements&emdash;could be used for comparisons with SR data to check the reliability of the "global thermometer" hypothesis.

A systematic study of SR parameters during high-energy particle precipitation events has shown that protons and electrons with energies above 1 MeV ionise the upper boundary of the

Earth/ionosphere cavity. This leads to an increase in the resonance frequency and a decrease in the damping of the first Schumann's resonance, as derived from measurements at Arrival Heights, Antarctica. The study used the nine strongest solar proton events of the past Solar Cycle 22 and high-energy electrons emitted periodically from co-rotating interaction regions in the solar wind during 1994&endash;95. The variation of the SR parameters is in qualitative agreement with current SR theories. The study also showed that high-energy particle precipitation (solar ejecta) is not the only relevant source affecting SR parameters. The findings constitute a so far little-explored aspect of solar/terrestrial interaction.

 

FACILITATING OUR POTENTIAL

In conclusion, we postulate that: (1) we are complex electrodynamic, rather than merely chemical beings, sensitive to natural and artificial EM fields; (2) SR frequencies coincide with human brain waves, affecting subtle and gross brain-wave generation, regulating homoeostasis, healing and psi; (3) there is strong correlation between human behavioural disturbance and geomagnetic field turbulence or isolation from SR frequencies.

As human beings we have extraordinary potentials we have hardly begun to study, much less understand. Creative gifts, intuitions and talents that are unpredictable or emergent may become stabilised in generations to come. Hopefully, we can learn to understand both our emergence from an essentially electromagnetic environment and facilitate our potential for healing, growth and non-local communication.

 

About the Authors:

¥ Richard Alan Miller started his professional career as a physicist, biophysicist and instrumentation specialist. In late 1972 he began his foray into paraphysics with experiments in Kirlian photography and developed a field theory to explain the phenomenon. He is an expert in growing and marketing botanicals, and set up his own company, Northwest Botanicals. Visit http://www.nwbotanicals.org for a listing of his writings on subjects as diverse as metaphysics, parapsychology and alternative agriculture. He is currently writing a book on ESP self-induction. Richard is available for lectures and as an outside consultant. He can be contacted at OAK Publishing, Inc., 122 SW 5th Street, Grants Pass, OR 97526, USA; telephone +1 (541) 476 5588, fax +1 (541) 476 1823, email DrRam@magick.net.

¥ Iona Miller is a multimedia artist, hypnotherapist, web author and researcher who works through the Asklepia Foundation (http://www.asklepia.org), Chaosophy Journal and JNLRMI on the relationship between experiential journeys, physics, healing, creativity, dreams, consciousness and chaos theory. She has been collaborating with Richard Alan Miller since the mid-1970s; although they divorced in 1994, they continue to work together on leading-edge studies into consciousness, neurotheology, Qabalah, alchemy and the nature of reality. Email Iona at iona_m@yahoo.com, and visit her homepage at http://www.geocities. com/iona_m/.

 

Notes and References:

¥ The authors give special thanks to Betty Daly-King of Western Australia for getting them started on the completion of Lewis B. Hainsworth's original works on this subject.

¥ Two background papers by Hainsworth are appended to the article "On the Possible Effects of Changes in Schumann's Resonances on Human Psychobiology" at website http://www.nwbotanicals.org. Appendix 1: The Effect of Geophysical Phenomena on Human Health (first published in Speculations in Science and Technology, vol. 6, no. 5, December 1983); Appendix 2: Electrical Technology and Human Evolution (Speculations in Science and Technology, vol. 11, no. 2, 1987)

¥ Additional references for this article can be found at http://www.nwbotanicals.org.

http://www.nexusmagazine.com/Schumann.html