Auditory Evoked Potentials in Low-achieving Gifted Adolescents.

There is increasing awareness that some gifted children have learning disabilities (Maker, 1977, Waldron and Saphire, 1992). Most of these children are labeled as underachievers which may be due to a learning disability concealing their true potential. These children are a source of frustration for classroom teachers because the nature of the problem is unclear. Without early identification, the learning disability may lead to academic, social and emotional problems.

Determining the underlying processing deficits in underachieving gifted children has been considered key to addressing the problem of identification and intervention. Various perception and processing deficits have been investigated including central auditory processing disorder (CAPD) (Kraft, 1993; Silverman, Chitwood & Waters, 1986; Silverman 1989; Waldron & Sphire, 1990, 1992). CAPD is defined as the inability or impaired ability to attend to, discriminate, recognize, remember, or to comprehend auditory information even though the individual has normal intelligence and hearing acuity (Keith, 1994). Past research has revealed deficits in the central auditory skills of underachieving gifted children in such areas as short-term auditory memory, auditory attention, auditory sequencing and auditory discrimination. These investigators used assessment procedures such as WISC-R profiles (Silverman, 1989; Waldron & Saphire, 1990), the Wepman Auditory Discrimination Test (Waldron & Saphire, 1990) or medical histories (Silverman et al., 1986).

More recently, Rigo, Arehole and Hayes (in press) studied low-achieving gifted students using formal behavioral tests of central auditory processing ability. They found that low-achieving gifted children performed less well on various auditory processing tasks when compared to achieving gifted students and students of average intelligence. Furthermore, the performance of low-achieving gifted children was similar to that of children identified as learning disabled.

Formal central auditory processing evaluation may include both behavioral and electrophysiologic assessment techniques. The behavioral technique involves presentation of tape-recorded speech material to the listener through ear phones. The listener is required to respond by repeating the speech stimuli presented. The test technique usually includes an assessment of auditory processing in several areas. Typically, the auditory behaviors tested are the ability to perceive distorted or degraded speech (auditory closure), the ability to listen to speech in background noise (selective attention), the ability to separate speech material presented to both ears simultaneously (binaural separation), the ability to integrate information presented to both ears (binaural integration), and the ability to recall the sequence of auditory inputs (temporal sequencing). Even though these behavioral measures have demonstrated performance deficits among children with central auditory processing disorders, their subjectivity sometimes limits their reliability. It has been shown that behavioral tests of auditory processing demonstrate increased variability, especially in young children (Willeford, 1977), because the response depends heavily on the child's motivation and cooperation. Furthermore, argument exists in the literature that behavioral techniques are one step removed from the direct measurement of auditory processing by the brain. In light of the potential problems of the behavioral technique, it has been recommended that electrophysiologic measures be incorporated into the clinical assessment of central auditory processing ability.

The electrophysiologic technique involves the measurement of auditory evoked potentials (AEP). AEPs are changes in the brain's neuro-electric activity in response to the reception of auditory signals. AEPs are time-locked responses that coexist with ongoing electroencephalic activity. They can be recorded by placing electrodes on the scalp of an individual and presenting several auditory clicks or tonebursts. The AEP waveform consists of discrete peaks that can be visualized after the neuro-electric response undergoes signal averaging, amplification and filtering. The response appears as several peaks and valleys that represent microvolt changes in auditory neuro-electric activity across time. The anatomical structures responsible for the various wave peaks depend on the latency at which each peak occurs. Peaks occurring within a latency of 10 msec. originate from the brainstem (Moller, Jannetta & Moller, 1981), and are called the auditory brainstem response (ABR). Peaks recorded between latencies of 12 to 50 msec are called the middle latency response (MLR). The MLR has a complex generating system which involves the auditory structures from the midbrain to the cortex, regions of the reticular formation, and the non-primary divisions of the auditory thalamo-cortical pathway (McGee, Kraus, Comperatore & Nicol, 1991). The MLR is followed by the long latency response (LLR) which consists of wave peaks occurring within a time period of 50 to 250 msec. The generators contributing to the LLR have been shown to encompass the subcortical structures and the superior temporal lobe (Clayworth & Woods, 1987; Wood & Wolpaw, 1982).

The P300 is another evoked response that is used to evaluate the integrity of auditory processing. The P300 response is seen as a large positive peak approximately 300 msec. after stimulus presentation. It is generated when listeners make auditory discrimination decisions and involves processes such as attention and recognition. The most common way of obtaining the P300 response is by way of the "oddball" paradigm. In this technique, a low frequency stimulus is presented repeatedly. At infrequent and random intervals, a high frequency stimulus is substituted for a low frequency stimulus. The subject's task is to count the number of high frequency stimuli that are presented. A complex array of generators is responsible for the P300 and includes the hippocampus, parahippocampal gyrus, amygdala, thalamic nuclei, temporoparietal area and prefrontal cortex. (Halgren, Squires & Wilson, 1980; Knight, Scabini & Woods, 1989).

The components of the response that are used to determine the normalcy of the AEP waveform include the latency, amplitude, and morphology of its response peaks. Latency is defined as the time in milliseconds taken for a specific peak to appear after the stimulus is presented. Amplitude is defined as the size in microvolts of a response peak. Morphology refers to the overall appearance of the waveform including factors such as the size and slope of the response peaks. Researchers have also used intra-aural latency differences to identify abnormal patterns of response. In this technique, the latency of the response from one ear is compared to that obtained from the other ear.

MLR and P300 responses have been found to be effective in identifying the existence of CAPD in LD children. Researchers have reported poorer wave morphology and larger inter-aural latency differences in the MLR responses of LD children compared to non-LD children (Arehole, Augustine & Simhadri, 1995; Jerger, Martin & Jerger, 1987; Jerger et al., 1991; Fifer & Sierra-Irizarry, 1988). Previous studies have also demonstrated longer latencies and reduced amplitudes in the P300 responses of LD children when compared to non-LD children (Byring & Jarvilehto, 1985; Frank, Seiden & Napolitano, 1994; Jirsa & Clontz, 1990; Lubar, Gross, Shively & Mann, 1990; Lubar, Mann, et al. 1992).

Both the MLR and P300 response are critical measures of particular aspects of auditory processing ability. The MLR response is an important measure because the reticular formation serves as one of its generators. Specifically, the reticular formation modulates the general arousal and receptiveness to sensory inputs, and assists the cerebral cortex in selecting incoming stimuli (Magoun, 1963). The P300 measure is important because it does not merely assess the reception of the stimulus by the brain, but can also tap the decision-making processes of stimulus recognition, discrimination, and categorization. Although these electrophysiologic techniques have been used extensively to identify CAPD in LD children, the use of these measures in identifying CAPD in underachieving gifted children is limited. Only one study has reported the use of auditory evoked electrophysiologic measures with the underachieving gifted population. Birley, Languis and Williamson (1992) recorded P300 from gifted LD children and found that their responses were delayed and asymmetrical when compared to a control group. However, the interpretation and generalization of their findings is restricted due to limitations in the study's subject selection, reporting procedures, and experimental design.

The results of the studies summarized above indicate that the auditory evoked electrophysiologic technique may provide valuable insight concerning the auditory processing abilities of low-achieving gifted children. Past research, using behavioral test techniques, has demonstrated the existence of CAPD in low-achieving gifted children (Rigo, Arehole & Hayes, in press). However, the use of electrophysiologic techniques with this population is limited. The purpose of our study was to obtain a more complete understanding of the central auditory processing capabilities of underachieving gifted children and to determine the effectiveness of the electrophysiologic technique for the identification CAPD in these children. Specifically, our study was designed to determine (1) whether CAPD can be identified in low-achieving gifted children using MLR and P300 measures and, if so, (2) which of these two measures is more effective in identifying the existence of CAPD in this population.

Method

Subjects

Four groups of subjects were included in the study: low-achieving gifted (LA/GT), achieving gifted (A/GT), learning disabled (LD) and average (AV). Each group contained 13 subjects. The mean age was 15 years 5 months for the LA/GT group, 15 years 11 months for the A/GT group, 16 years 9 months for the LD group, and 15 years 10 months for the AV group. Subjects were drawn from public high schools in two local school districts.

All gifted subjects had been previously identified as gifted by their respective school systems. The state criteria for gifted eligibility include: a score of at least 2 standard deviations above the mean on an individually or group administered test of intellectual abilities; a score of at least 7 on the Standard Matrix, with at least 2 points earned on the aptitude/intelligence test; or a score of at least 6 on the Standard Matrix and a recommendation for classification as gifted from the pupil appraisal team. Louisiana's Standard Matrix points are assigned based on a given student's scores in three areas: aptitude/intelligence (determined by a standardized IQ test), reading achievement, and math achievement (Louisiana Department of Education, 1993). The LA/GT group consisted of students who exhibited a noticeable discrepancy between their intellectual ability and academic performance and showed evidence of academic difficulty for at least 2 years in one or more subject areas. Because the two school districts did not have an operational definition of "underachievement" or "low-achievement" for gifted students, the determination of level of achievement was based primarily on the subjective evaluations of participating teachers and supplemented by report cards, reports from former teachers, reports from related professionals, and other sources of documentation. Although these children demonstrated discrepancies between their potential and achievement, their degree of academic difficulties did not qualify them for classification as LD students. The A/GT group was composed of students who had no history of learning problems and who presented no discrepancy between their measured potential and academic achievement based on report card grades and teacher reports.

The two school districts from which the gifted subjects were drawn utilized either the WISC-R or the Otis-Lennon School Ability Test to measure intellectual ability. In the A/GT group, 4 were assessed with the WISC-R and 9 with the Otis-Lennon. In the LA/GT group, 9 were tested with the WISC-R and 4 with the Otis-Lennon. The mean WISC-R full scale score was 135 for the A/GT group (range 126 to 145) and 129 for the LA/GT group (range 120 to 142). The mean Otis-Lennon deviation IQ score was 132 for the A/GT group (range 125 to 141) and 133 for the LA/GT group (range 129 to 137).

The LD group included students who were identified as learning disabled by their school systems. The state criterion for learning disabilities requires evidence of a severe discrepancy between achievement and ability as measured by performance comparisons in the student's strongest and weakest academic areas (Louisiana Department of Education, 1993). All LD subjects had primarily reading and/or writing disabilities.

The AV group was made up of students who were nondisabled, non-exceptional, and were drawn from regular education classrooms. All AV subjects were performing academically at grade level.

Informed consent was obtained for all children after the experimental procedure was fully explained. Subjects were reimbursed $10.00 for their participation according to procedures recommended by the American Psychological Association (APA, 1992). The hearing of all subjects was screened to assure normal hearing sensitivity.

Electrophysiologic Tests

A Nicolet Compact Auditory Evoked Response System (Nicolet CA 2000) was used to obtain the MLR and P300 responses. Standard silver chloride disc electrodes filled with electrode paste were secured to four scalp locations: the vertex, behind each earlobe, and the forehead. Electrode placement followed the international 10-20 system (Hall, 1995). Electrode placement procedures were identical to those used routinely in medical applications of EEG.

MLR recording. MLR was recorded for a series of short duration (100 sec) auditory clicks. The click stimuli were presented through TDH-39 ear phones at an intensity of 70 dB nHL. A total of 2000 clicks were presented at a repetition rate of 7.7 clicks per sec to obtain each MLR waveform. Responses were obtained for each ear separately. Subjects were required to sit in a relaxed and quiet manner during MLR recording.

P300 recording. The P300 response was obtained by presenting 1000 Hz and 2000 Hz pure tones in a randomized sequence. The 1000 Hz tone was presented 240 times and the 2000 Hz tone was presented 60 times to obtain each P300 waveform. The stimuli were presented binaurally through TDH-39 earphones at an intensity of 70 dB HL. Subjects were required to count silently the number of 2000 Hz tones presented during each test run. All subjects were capable of counting these tones accurately.

All testing was performed in a quiet room with the subject seated in a reclining chair. A typical recording session lasted about one and one-half hours. Each waveform obtained was replicated to ensure response reliability. The data was stored on a floppy disk during the test session and later retrieved for analysis.

Data Analysis

The response measures used to evaluate P300 included absolute latency, amplitude, and wave morphology. The absolute latency of P300 was identified as the largest positive peak after 250 msec (see Figure 1). The amplitude of P300 was measured by calculating the difference in microvolts ([micro]v) between the wave peak and the baseline response. Wave morphology of the P300 response was judged as being "good" or "poor" after an inspection of each response by three independent judges trained in P300 administration and interpretation. The analysis was based on the slope, amplitude, repeatability, and overall appearance of the waveforms.

[Figure 1 ILLUSTRATION OMITTED]

Results

For each MLR and P300 measure, a two-factor ANOVA was performed on the group means for each ear. The main effects studied were giftedness (the two gifted groups [A/GT & LA/GT] versus the two non-gifted groups [AV & LD]) and achievement (the two achieving groups [A/GT & AV] versus the two low-achieving groups [LA/GT & LD]).

P300 Findings

As previously mentioned, the three P300 response measures that were analyzed were wave morphology, absolute latency, and amplitude. Significant differences among subject groups were found for the wave morphology measure only. ANOVA revealed that neither the two main effects nor the interaction was significantly different (p [is greater than] 0.05) for absolute latency and amplitude.

The proportions of subjects in each group that demonstrated poor P300 wave morphology are shown in Table 1. The differences among subject groups were analyzed statistically using ANOVA after arcsin transformations were applied to the binomial proportions (Winer, 1971). The analysis of main effects revealed that a significantly larger proportion of subjects from the low achieving groups (LA/GT and LD) manifested poor P300 wave morphology when compared to the achieving groups (A/GT and AV) (F=6.46, p [is less than] .025). The main effect of giftedness was not found to be significant (p [is greater than] .05) and there was no significant interaction (p [is greater than] .05).

Table 1

Proportion of Subjects from each Group with Poor P300 Wave Morphology

SUBJECT GROUPS

A/GT   AV     LA/GT   LD

23.1   38.5   61.5    69.2

Simple comparisons revealed that a significantly larger proportion of LA/GT subjects had poor P300 wave morphology when compared to the A/GT group. Although a larger proportion of LA/GT subjects demonstrated poor P300 wave morphology when compared to AV subjects, the difference was not significant 09 [is greater than] .05). Lastly, the proportion of subjects displaying poor P300 wave morphology in the LA/GT and LD groups was not significantly different (p [is greater than] .05).

MLR findings

MLR response measures analyzed were absolute latency and inter-aural latency differences. For both of these measures, the analysis did not reveal significant differences for either of the two main effects (p [is greater than] 0.05) or for the interaction (p [is greater than] 0.05).

Summary of Analyses

These results indicate that the P300 response was better able to identify patterns of deficits among the four subject groups than was the MLR response. Neither the analysis of MLR latencies nor MLR inter-aural latency values revealed significant group differences. However, the analysis of P300 wave morphology demonstrated that a significantly higher proportion of low-achieving subjects exhibited poor morphology when compared to achieving subjects. Further, it is important to note that the proportion of poor morphology noted in the low-achieving gifted group was similar to that found in the LD group. Finally, although the ANOVAs of P300 absolute latency and amplitude did not demonstrate significant main effects, both the main effect of giftedness in the latency analysis (p [is less than] .064) and the main effect of achievement in the amplitude analysis (p [is less than] .070) approached the level of confidence that was set in the study (p [is less than] .05).

Case Studies

Case 1. Figure 2 shows the MLR and P300 waveforms for a 14 year 6 month-old LA/GT subject. The MLR waveform is within normal limits. The P300 recording, however, demonstrates poor wave morphology. Specifically, the P300 amplitude is lower than what would be expected in a normal response (see Figure 1).

[Figure 2 ILLUSTRATION OMITTED]

Case 2. Figure 3 displays the results for a 14 year 5 month-old LA/GT subject. Again, the subject displays a normal MLR response and an abnormal P300 response. The amplitude, slope, and repeatability of the P300 waveform are abnormal.

[Figure 3 ILLUSTRATION OMITTED]

Discussion

This study was designed to determine whether auditory evoked potentials can be used to identify central auditory processing deficits in low-achieving gifted children and, if so, which electrophysiologic measure is most able to segregate low-achieving gifted children from other subject groups. The proportion of LA/GT subjects that demonstrated poor P300 wave morphology was significantly higher than the proportions obtained for the two achieving groups (A/GT and AV). Further, the proportion of subjects that demonstrated poor P300 morphology did not differ between the LA/GT and LD groups. Although the LA/GT students did not qualify for LD placement, our findings indicate that, as a group, these subjects not only demonstrate poorer auditory processing abilities than their gifted and non-gifted achieving counterparts but also demonstrate an incidence of CAP difficulties comparable to LD children.

The statistical analysis also revealed that the P300 wave morphology was not influenced by level of giftedness. This suggests that formal measures of CAP abilities, such as P300 morphology, may be better able to identify deficits associated with learning disabilities in underachieving gifted students than the more traditional techniques of identification (IQ tests, analysis of academic achievement patterns, etc.). As Silverman (1989) states:

   The problem is that when two exceptionalities exist in one child they tend
   to mask one another so that neither the giftedness nor the disability is
   immediately evident. Disabilities depress these children's IQ and
   achievement scores, disqualifying them for gifted programs; in addition,
   high intelligence enables them to compensate well enough for their weakness
   to maintain grade level expectations, which prevents them from being
   detected as learning-disabled or qualifying for special education services.
   (p. 37)

The two other P300 measures, amplitude and latency, did not reach statistical significance in this study. In our study, mean amplitudes were lower in both the LA/GT and LD groups when compared to the two achieving groups, although these differences were not significant. One reason for our findings may be the heterogeneous make-up of the low-achieving subjects. The subjects in the LA/GT group were selected solely on the basis of teacher reports and academic history. Therefore, this group may have included children who were low-achievers for reasons other than CAPD. In our analysis, the P300 latencies of the two gifted groups were shorter than those of the two non-gifted groups, but like the P300 amplitude measure, the differences were not statistically significant. This may have been due to the inherent variability of the P300 measure. The P300 is a relatively broad response which results in a large range of latency values. This variability may have led to a near-miss significance level.

In this study, the MLR measures did not appear to be as effective as the P300 measures in differentiating low-achieving gifted subjects from the other subject groups. No significant results were obtained for either the MLR absolute latency or inter-aural latency measure. The reasons for our non-significant findings may be maturational in nature. The primary MLR generator in children under 12 years of age is the reticular formation, but as the auditory pathway matures the main contributor to the MLR response shifts from the reticular formation to the thalamus and primary auditory cortex (McGee et al., 1991). Thus, when the MLR response matures around 12 years of age, its generator shifts from the reticular formation to higher centers in the central auditory system. If we follow the argument that the reticular formation is responsible for selective attention and that children with learning problems present selective attention difficulties, it is expected that the MLR would be affected in younger LD subjects. However, in subjects older than 12 years of age, selective attention difficulties may not be reflected in the MLR response due to its maturational shift from the reticular formation to higher auditory centers.

Our study indicates that the evaluation of P300 wave morphology holds promise as a diagnostic tool for the identification of CAPD in low-achieving gifted children. Traditionally, central auditory processing has been assessed by using a battery of behavioral tests. Previous research using behavioral techniques has been successful in identifying central auditory processing differences between low-achieving gifted and gifted subjects. For example, Rigo et al. (in press) found significant differences between these two subject groups on behavioral measures involving the reception of distorted speech, selective attention, and binaural separation and integration of speech stimuli. However, as noted previously, the behavioral test technique requires the willing participation and overt response of subjects. One advantage of the P300 measure is that it only requires that the subject count sequences of simple tonal stimuli.

A second advantage of the P300 technique is that it is a direct measure of brain activity. It has been argued that behavioral tests of central auditory processing reflect not only auditory processing skills, but may also be influenced by receptive and expressive language ability. The P300 response does not require the processing of linguistic stimuli, and therefore, can assess central auditory processing capabilities independent of language skills.

It is evident that both electrophysiologic and behavioral assessment techniques of central auditory processing may be useful in identifying CAPD in low-achieving gifted children. Each technique, however, has unique limitations. The behavioral technique requires a voluntary response and may be effected by abilities other than central auditory skill. Electrophysiologic techniques require expensive instrumentation and extensive training to administer and interpret the various tests, and therefore, may not be as suited for use in school settings. In light of the advantages and limitations of each technique, we recommend the use of a battery of behavioral tests, in combination with P300 assessment, to identify the existence of central auditory processing disorders in low-achieving gifted children.

Conclusions

The finding of this study demonstrating significant differences in P300 wave morphology between the LA/GT group and achieving subjects is very encouraging. The identification of differential patterns of brain activity may bring us closer to an understanding of one of the causes of low achievement in the gifted population and may lead to further improvements in remediation. It is recommended that clinical evaluation of CAPD in this group include both behavioral and electrophysiologic techniques to optimize the identification of this condition. Future research should focus on establishing correlations between behavioral and electrophysiologic results in the low-achieving gifted population.

REFERENCES

American Psychological Association. (1992). Ethical principles of psychologists and code of conduct. American Psychologist, 47, 1597-1611.

Arehole, S., Augustine, L. E., & Simhadri, R. (1995). Middle latency responses in children with learning disorder: Preliminary findings. Journal of Communication Disorder, 28, 21-38.

Birley, M., Languis, M., & Williamson, T. (1992). Physiological uniqueness: A new perspective on the learning disabled/gifted child. Roeper Review, 15(2), 101-107.

Byring, R., & Jarvilehto, T. (1985). Auditory and visual evoked potentials of schoolboys with spelling disabilities. Developmental Medicine & Child Neurology, 27, 141-148.

Clayworth, C. C., & Woods, D. L. (1987). Subcortical contributions to the auditory N1: a comparison of distributions of the N1 and wave V of BAEP. In R. Johnson, J. W. Rohbraugh, & R. Parasurama (Eds). Current Trends in Event Related Potentials. (pp. 445-451). Amsterdam: Elsevier.

Fifer, R. C., & Sierra-Irizarry, B. (1988). Clinical applications of the auditory middle latency response. The American Journal of Otology, 9, 47-56.

Frank, Y., Seiden, J. A., & Napolitano, B. (1994). Event-related potentials to an "oddball" auditory paradigm in children with learning disabilities with or without attention deficit disorder. Clinical Electroencephalography. 25(4), 136-141.

Halgren, E., Squires, N. K., & Wilson, C. L. (1980). Endogenous potentials generated in the human hippocampal formation and amygdala by infrequent events. Science, 210, 803-805.

Jerger, S., Martin, R. C., & Jerger, J. (1987). Specific auditory perceptual dysfunction in a learning disabled child. Ear and Hearing, 8(2), 78-86.

Jerger, J., Johnson, K., Jerger, S., Coker, N., Pirozzolo, F., & Gray, L. (1991). Central auditory processing disorder: a case study. Journal of American Academy of Audiology, 2(1), 36-54.

Jirsa, R. E., & Clontz, K. B. (1990). Long latency auditory event-related potentials from children with auditory processing disorders. Ear and Hearing, 11, 222-232.

Keith, R.W. (1994). SCAN: A: A test for auditory processing disorders in adolescents and adults. San Antonio: Harcourt Brace & Company.

Knight, R. T., Scabini, D., & Woods, D. L. (1989). Contributions of temporal-parietal junction to the human auditory P3. Brain Research, 502, 109-116.

Kraft, H. R. (1993). Deficits in auditory sequential processing found for both gifted and average IQ reading-impaired boys. Annals of New York Academy of Sciences, 682, 366-368.

Louisiana department of Education. (1993). Bulletin 1508: Pupil appraisal handbook. Baton Rouge, LA: Louisiana Department of Education.

Lubar, J. F., Gross, D. M., Shively, M. S., & Mann, C. A. (1990). Differences between normal, learning disabled and gifted children based upon an auditory evoked potential task. Journal of Psychophysiology, 4, 249-260.

Lubar, J, F., Mann, C, A., Gross, D, M., & Shively, M. S. (1992). Differences in semantic event-related potentials in learning-disabled, normal and gifted children. Biofeedback and Self-Regulation, 17(1), 41-56.

Magoun, H. (1963). The waking Brain (ed 2). Springfield, IL: Charles C. Thomas.

Maker, J. C. (1977). Providing programs for the handicapped. Reston, Virginia: Council for Exceptional Children.

McGee, T., Kraus, N., Comperatore, C., & Nicol, T. (1991). Subcortical and cortical components of the MLR generating system, Brain Research, 544, 211-220.

Moller, A. R., Jannetta, P. J., & Moller, M. B. (1981). Neural generators of brainstem evoked potentials: Results from human intracranial recordings. Annals of Otology, Rhinology, and Laryngology, 90, 591-596.

Rigo, T. G., Arehole, S., & Hayes, P. H. (in Press). Central auditory processing abilities of low-achieving gifted adolescents. Journal of Secondary Gifted Education.

Silverman, L. K. (1989). Invisible gifts, invisible handicaps. Roeper Review, 12, 37-42.

Silverman, L. K., Chitwood, D. G., & Waters, J. L. (1986). Young gifted children: Can parents identify giftedness? Topics in Early Childhood Education, 6, 23-38.

Waldron, K. A., & Saphire, D. G. (1990). An analysis of WISC-R factors for gifted students with learning disabilities. Journal of Learning Disabilities, 23, 491-498.

Waldron, K.A., & Saphire, D.G. (1992). Perceptual and academic patterns of learning-disabled/gifted students. Perceptual and Motor Skills, 74, 599-609

Winer, B.J. (1971). Statistical principles in experimental design (2nd ed.). New York: McGraw-Hill.

Willeford, J. (1977). Assessing central auditory behavior in children: A test battery approach. In R. Keith (Ed). Central auditory dysfunction, pp, 43-72, New York: Grunne and Stratton.

Wood, C., & Wolpaw, J. (1982). Scalp distribution of human auditory evoked potentials. 11. Evidence of overlapping sources and involvement of auditory cortex. Electroencephalography and Clinical Neurophysiology, 54, 25-38.

Manuscript submitted April, 1998.

Revision accepted September, 1998.

Drs. Shalini Arehole and Thomas Rigo are Associate Professors of Audiology in the Department of Communicative Disorders at the University of SW Louisiana. Dr. Arehole's work involves assessment of auditory processing in children with learning disability using electrophysiologic techniques. Dr. Rigo's work involves assessment of auditory processing in the low-achieving gifted population using behavioral techniques.3