Markdown lines 880–1075 · Part 2 of 9
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:
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.
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.
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.
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.
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:
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.
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.
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.
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