EXPLORATORY INVESTIGATION OF NEURAL EFFICIENCY
IN RETARDED, LEARNING DISABLED & NORMAL CHILDREN

Patrick n. Slattery
Esther A. Beck

Auburn University at Montgomery

Presented at Twenty-Seventh Annual Meeting of the American Association

Of Psychiatric Services for Children, New Orleans, Louisiana, 1975.

Since Catou’s work In 1077 there has been an Interest In the measurement of spontaneous electrical activity of the brain. The techniques for performing such measurement were crude and unreliable until the 1950’s when improvement in apparatus enabled researchers to record average evoked potentials from the intact scalp, rather than from the cortical surface (Dawson, 1954). Relatively recent work has involved the electroencephalogram, or EEG, and techniques for interpreting its graphic recordings (Halter, 1954). Further developments and refinements 1n the analysis of EEGs led to electronic averaging devices and the application of computer technology to the field of brain wave analysis (Brazier, 1962). Brain wave analysis has become a major area of study during the past decade with some significant contributions being made to the understanding of human Intelligence and behavior (Ertl 4 Schafer, 1968; Ertl & Schafer, 1969; Weinberg,1969: Ertl, 1971).

Modern brain wave analysis techniques have facilitated the study of personality and other correlates of the “alpha rhythm” - a wave of between 5 and 15 microvolts (at the scalp) which has a frequency of between 3 and 12 hertz (Brown, 1971). Some investigations have concentrated on the relationship betweenvarious kinds of brain pathology and alpha waves.

Artemieva and Momskaya (1973) investigated the average amount of asymmetry of alpha waves during signaling and non-signaling stimuli presented to normal and brain-damaged patients. They found that lesions of the frontal lobes impede brain structures responsible for the regulation of activity states and are indicated by alpha asymmetry.

Results of brain wave analysis to date suggest certain important questions needing investigation. Do brain waves reflect the psycho-educational status of the individual? That 1s, are there differences for persons with independently diagnosed conditions of retardation, learning disability, and normalcy? Can brain waves be used to categorize persons as normal, learning disabled, or mentally retarded? If brain waves differ between persons and groups is there a sufficient difference to provide useful diagnostic Information? What differences, if any, are, likely to result from age, racial, and cultural factors? Are there sex-related differences in brain waves?

Such questions as these prompted the present authors to undertake an extensive normative study of children who are served by a university diagnostic and evaluation clinic. The clinic provides contract services primarily to retarded persons. The clinic has In Its possession a brain wave analyzer designed by John Ertl. The machine was obtained for diagnostic purposes, and is used as an adjunctive tool along with other methods of Information gathering, most of which have been well standardized. Because the clinic serves primarily children who are suspected of being mentally retarded or children previously diagnosed as retarded, 1t was necessary for us to obtain a small number of youngsters who were not clinic clients to use as research subjects.

1. The Clinic 1s located at Auburn University at Montgomery and operates under auspices of the State of Alabama Departments of Mental Health and Pensions and Security.

2. The device was purchased by the State of Alabama Department of Mental Health. The Ertl 02 Brain Wave Analyzer (BHA) consists of a small computer, a headset, a paper tape machine, an oscilloscope and a battery charger, when operational, the BWA 1s powered by batteries which eliminate the possibility of electrical shock. The headset consists of four electrodes, two of which fit on
the scalp over the motor cortex, and two of which are attached to the client’s ear lobes. The machine makes no sound and it provides rapid readings, every 1, 5, or 10 seconds. While our machine has a biofeedback capability, we are not prepared to discuss this feature at this time. The BWA was delivered in late 1974 and it has been in operation continuously. During nearly eleven months of use 1t has analyzed the brain waves of nearly 600 humans. Of that number, 191 are children between the ages of 3 years and nine months and 17 years eleven months.

These are the subjects of the present paper. Subjects were initially categorized according to their referral reason as
either retarded, learning disabled, or normal. But after a short time, a re-classification process was undertaken based on independent diagnostic findings. The results reported herein are based on the Independent classification system.

According to the inventor of the BWA, its utility lies in Its measuring brain waves as a function of temporal variables. The analyzer provides several scores through a digital display. One score describes the client’s broad band EEG in milliseconds. Another score in Hertz describes the occurrence of alpha waves. A third score is in degrees of phase difference between waves of the right and left cerebral hemispheres. The final score is in terms of milli-seconds difference between hemispheres.

The brain wave analysis technique measures individuals so that overall neural efficiency can be assessed. Neural efficiency is roughly equivalent to the common sense understanding of intelligence. The BWA’s inventor, Ertl, states a three factor theory of human intelligence. The factors are: time, quantity, and entropy. They are related to human intelligence through concepts of cybernetics and neurophysiology. Ertl’s research with the brain wave analysis technique has produced two major variables: neural information transfer rate (MIT), and hemispheric synchronization. Both variables are found to be independently related to general intelligence, and together they are thought to account for approximately 20 percent of individual differences in intelligence.

According to Ertl, the electrical activity of the brain which is detectable on the scalp represents the statistical behavior of millions of information processing neurons. The measurement of many different frequencies and their mixture results in a composite spectrum which 1s sharply peaked 1n the alpha band for humans. Because alpha is very large when compared to other frequencies, alpha spreads all over the scalp and both obscures and distorts other brain wave frequencies. Therefore, the brain wave analyzer must aid in removing the alpha rhythm in the analysis of brain waves as related to human intelligence.

The basic hypotheses underlying this method of brain wave analysis are as follows:

1. The average frequency of non-alpha wave activity should be related to Information processing efficiency.

If in tests measure some aspect of general Intelligence, significant correlations will occur.

2. The efficiency of an Information processing system is related to
the frequency used or required by the system.

3. The time required for hemispheric synchronization of information
effects neural efficiency.

With this review of the basic theoretical foundations of the Ertl 02 brain Wave Analyzer, results of the normative effort are reported. The number of subject’s in each of the three categories of normal, learning disabled, and retarded is displayed in Table 1. Mean score for functions of the group are shown in Table 2. Since samples almost invariably differ somewhat, the question is whether differences among the samples signify genuine population differences or whether they represent merely chance variations as are to be expected among several random samples from the same population. To provide a statistical check as to whether or not the samples were from different populations, the Kruskal-Wallis one-way analysis of variance test was employed. Table 3 gives the results of the K-W Anova for each function measured by the brain wave analyzer for ease of data management; the three groups were equalized in terms of number through randomization.

Based on Table 3, there 1s very good evidence that the three groups are different from one another. The brain wave analysis technique clearly
differentiates between the categories of normal, learning disabled, and mentally retarded in all areas except one. The phase angle measure is not definitive. Because there 1s such strong evidence that brain wave analysis distinguishes persons of the three groups there may be justification 1n using the machine for classification of persons, or assignment to groups. This has not yet been done. It is likely that individual cases need to be treated differently than groups.

Because of the existence of independent diagnostic Information (in Scores) it was possible to compute a coefficient of validation which is. 78 on twenty five randomly selected cases. Reliability of the test/retest type on ten subjects gives a 90% probability that scores will remain essentially the same over time. Our conclusion 1s that the Ertl 02 BWA does Indeed allow for differentiation between persons in the three categories. In an effort to deal with important psycho-social issues of sex, aqe, race and cultural bias, the following is presented: Inspectional analysis of tape records of female subjects compared to male subjects yields no distinguishing characteristics. There seems to be no way of identifying black youngsters in contrast with white youngsters without the use of a key. Age may be important, but further data is needed.

Assessment of this technique produces the following conclusions which are supported by present evidence:

1. The measurement 1s very rapid, usually less than 5 minutes is spent per subject.

2. The technique 1s simple, a technician can be instructed to use and operate the device 1n less than 10 minutes.

3. The results appear very stable over time.

4. The device offers good promise for rapid screening of suspected syndromes.

5. Cultural, racial, and sexual bias is absent. Preliminary work to modify the brain waves of human subjects has Indicated that human brain waves are extremely stable and robust. Ordinary academically related tasks, such as memory work and pattern tracing seem not to alter brain waves. We have some reason to believe that consumption of alcohol and drugs will influence the results.

We do not know what effect fatigue or illness have on the results.

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