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EEG and Subjective Correlates of Alpha-Frequency Binaural Beat Stimulation with Alpha Biofeedback

EEG and Subjective Correlates of Alpha-Frequency 
Binaural-Beat Stimulation Combined with Alpha

Dale S. Foster
Memphis State University
May 1990

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.  

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.


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.


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


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.  


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.  


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


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


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,

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

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

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

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.



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.


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).  

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.  

           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.


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.


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.  


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.


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

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).


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
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

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

     |    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

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


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.


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

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

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


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

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

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
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                                      Self-Report Form             
Name:                         Date:        Time:      

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

Level of Relaxation (pre-procedure):

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

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

Level of Relaxation (post-procedure):

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

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



                                      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

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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