Research
EEG and Subjective Correlates of Alpha-Frequency Binaural-Beat Stimulation Combined
with Alpha Biofeedback
by Dale S. Foster, Ph.D.
This study is dedicated to my Mom and Dad, my sisters, Denise
and Diann, and my brother Doug without whose encouragement and support this
project would have been much more difficult.
Acknowledgments
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
brainwave production and subjective experience of mental and physical relaxation.
The study compared the alpha brainwave 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 brainwave 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
self-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.
H(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.
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.
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-beat 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 .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- beat-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* Grp. | 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
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*
Grp. | 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-beat
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
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.
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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.
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