(1999) Tallal - Children With Lang Impairment

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Brain and Language 69, 222–229 (1999)

Article ID brln.1999.2134, available online at http://www.idealibrary.com on

NOTES AND DISCUSSION

Children with Language Impairment Can Be Accurately

Identified Using Temporal Processing Measures:

A Response to Zhang and Tomblin,

Brain and Language, 65, 395–403 (1998)

Paula Tallal

Center for Molecular and Behavioral Neuroscience Rutgers,

The State University of New Jersey, Newark, New Jersey

In the early to mid 1980s, Tallal, Stark, and colleagues published over 30articles detailing the results of a large, multidisciplinary NIH-funded contract

that comprehensively assessed a wide range of sensory, perceptual, motor,neurodevelopmental, and speech skills in a cohort of children with specificlanguage impairments (SLI), reading impairment, or articulation disorder, aswell as well-matched controls. A book, reporting and synthesizing the datafrom this large project, was also published (Stark & Tallal, 1988). One of the articles reporting data from this project, Tallal, Stark, and Mellits, 1985(TSM), is the focus of a recent critique by Zhang and Tomblin (1998).

The TSM article in question reported the results of a discriminant function

analysis. Using a broad battery of 160 sensory, perceptual, motor, neuro-developmental, speech, and demographic variables, the discriminant func-tion analysis identified six variables that, taken in combination, correctlyclassified 98% of 59 subjects as language impaired (LI) or normal (N). Allsix variables identified assessed ‘‘temporal processing.’’

Zhang and Tomblin (1998) used three computer simulations to challengethese results. They question ‘‘What true predictive power is required of 160

temporal processing variables in order for six variables from them to identifychildren’s language status of the TSM’s sample with a level of 98% accu-racy?’’ The premise of the Zhang and Tomblin critique is to show that com-

Address correspondence and reprint requests to Paula Tallal, Ph.D., Center for Molecularand Bahavioral Neurosciences, Rutgers, The State University of New Jersey, Newark, NewJersey 07102. E-mail: [email protected].

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0093-934X/99 $30.00Copyright ! 1999 by Academic Press

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NOTES AND DISCUSSION 223

puter simulations with any large variable set including ‘‘160 temporal pro-cessing variables’’ can result in selecting six temporal processing variablesthat will have high predictive accuracy between two populations. Therefore,they warn against using the results from the TSM study to support a relation-

ship between temporal processing deficits and language impairment.We would agree with Zhang and Tomblin if in fact the TSM study had

used a set of 160 temporal processing variables from which six temporalprocessing variables were selected. But, this was not what was done in theTSM study and, as such, the conclusions reached by Z & T’s simulationsare not valid.

In TSM we explicitly stated that the goal of the study was to determine(1) whether a comprehensive set of 160 sensory, perceptual, motor, neurode-velopmental, speech and demographic variables could correctly classify chil-dren as language-impaired (LI) or controls and, if so, (2) which variables,taken in combination best classified the highest number of children correctly.To accomplish this goal a comprehensive battery of nonverbal and speechperception and motor tests was developed. The nonverbal battery assessedsensory and perceptual abilities in the auditory, visual, and tactile modalitiesas well as cross-modally. The battery included the assessment of detection,

association, discrimination, temporal resolution, sequencing, rate processing,and serial memory abilities. A broad range of nonverbal and verbal motortests was also included in the battery. A comprehensive neurodevelopmental‘‘soft sign’’ battery measured general motor control and coordination, bal-ance and station, tactile sensation and perception, and laterality. Demo-graphic and case history variables were also documented. A detailed descrip-tion of each variable, as well as testing procedures, is reported in Stark andTallal, 1988. Together these measures comprised the 160 variables that wereentered into a discriminant function analysis.

The results reported in TSM showed that from this wide range of 160sensory, perceptual, motor, speech, neurological ‘‘soft sign,’’ and demo-graphic variables, the analysis identified six variables. Interestingly, all sixturned out to assess temporal perceptual and production abilities (i.e., theability to perceive or produce two or more events, simultaneously or in veryrapid succession). These six variables, in combination, correctly classified

98% of the participating subjects as LI or controls.The focus of this article was a detailed behavioral analysis of the six vari-

ables derived from this discriminant function analysis. Specifically, we ex-plicitly stated in TSM that ‘‘The use of linear discriminant function analysisto classify pathological subjects into groups, is a two-stage process. Thisstudy addresses the first step, that is the identification of the variables thatbest discriminate between groups. The second and essential step is cross-validation’’ which was not within the scope of this study. We went on toemphasize, however, that ‘‘it is not the primary purpose of this study todevelop procedures for identifying LI children and discriminating them from


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224 NOTES AND DISCUSSION

TABLE 1Studies That Demonstrate That Individuals with Language Learning Impairment HaveDeficits in Processing Brief, Rapidly Successive Acoustic Cues in Nonverbal Stimuli

Lowe & Campbell, 1965 McCrosky & Kidder, 1980 McAnnally & Stein, 1997

Stark, 1967 Tallal et al., 1981 Wright et al., 1997Aten & Davis, 1968 Thal & Barone, 1983 Protopappas et al., 1997Griffith, 1972 Robin et al., 1989 Llinas et al., 1998Tallal & Piercy, 1973a Stefanatos et al., 1989 Nagarajan et al., 1998Tallal & Piercy, 1973b Lincoln et al., 1992 Witton et al., 1998Kracke, 1975 Tomblin et al., 1992 Ribary et al., 1998Lea, 1975 Neville et al., 1993Tallal et al., 1976 Hari & Kiesla, 1996Haggerty & Stamm, 1978 Benasich & Tallal, 1996

Tallal, 1980

normally developing children for clinical purposes. . . . Rather, the purposeof this study was to further enhance our understanding of the neurologicalmechanisms that may underlie normal and abnormal development of lan-guage.’’

The results add considerable weight to the findings of a series of previous

and subsequent studies from many different laboratories (see Tables 1 and2) that have demonstrated that LI children are significantly impaired in theirability to both perceive and produce rapidly successive acoustic cues nonver-bally as well as within speech. Thus the results of the TSM study stronglysupported the theoretical interpretation of many previous and subsequentstudies by demonstrating that from a comprehensive set of 160 variables(only a few of which assessed very rapid temporal perceptual or productionabilities) discriminant function analysis isolated six variables that correctlyclassified 98% of children as LI or normal, and all six variables had in com-mon the assessment of specific temporal capabilities, either in perception or

TABLE 2Studies That Demonstrate That Individuals with

Language Learning Impairment Have Deficits inProcessing Brief, Rapidly Successive Acoustic Cues inVerbal Stimuli

McReynolds, 1966 Alexander & Frost, 1982Rosenthal, 1972 Werker & Teas, 1987Tallal & Piercy, 1974 Elliott & Hammer, 1988Tallal & Piercy, 1975 Elliott et al., 1989Henderson, 1978 Reed, 1989Thibodeau & Sussman, 1979 Sussman, 1993Frumkin & Rapin, 1980 Kraus et al., 1995Tallal et al., 1980a,b Kraus et al., 1996

Tallal & Stark, 1981 Stark & Heinz, 1996Godfrey et al., 1981 Leonard, 1998


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in production. The point of the TSM article was not that six variables couldbe selected, but that the six variables that were selected showed a highlyselective pattern.

The first variable, rapid speech production, measured the ability to articu-

late correctly three repetitions of a multisyllabic word (such as refrigerator)in rapid succession. Variable two, a finger-identification subtest, assessedthe subject’s ability to identify two touches presented simultaneously on twodifferent fingers. Other finger-identification subtests, requiring the identifi-cation of only a single touch on the fingers, or two touches presented moreslowly, did not enter the equation. The third variable entering the equationwas the discrimination of the computer-synthesized syllables /ba/ vs. /da/,with 40-ms-duration formant transitions. Tallal and Piercy (1975) had previ-ously reported that LI children have particular difficulty discriminatingspeech stimuli such as these, which are characterized by rapidly changingacoustic spectra. Importantly, tests assessing perception of speech stimulisynthesized with less rapidly changing acoustic spectra, (e.g., /ba/ vs. /da/with 80-ms-duration transitions, 250-ms-duration syllables /dab/ vs. /daeb/,/sa/ vs. /sta/, and /"/ vs. ae) did not enter the equation. The fourth variableentering the equation assessed the subject’s ability to integrate nonverbal stim-

uli presented cross-modally at rapid rates. Sequences of tones and light flasheswere presented cross-modally in random order and subjects were trained toindicate what they perceived by pressing buttons on a response panel. Again,it was only the trials in which stimuli were presented rapidly in succession thatentered the equation. Similar trials, in which the same stimuli were presentedmore slowly (with longer interstimulus intervals), did not enter the equation.Sequencing the letters e and k, when presented rapidly in succession, enteredthe equation, whereas the trials in which the same letters were presented moreslowly(withlongerintervals)didnotenter.Thesixthandfinalvariableenteringthe equation assessed the ability of subjects to locate two touches presentedsimultaneously to the cheeks and/or hands on either side of the body. Again,this is a test which assesses the perception of more than one stimulus presentedin a brief time period (in this case, simultaneously). Thus, each of the six vari-ablesenteringtheequation,whichaccuratelydiscriminatedLIfromNchildren,assessed the ability to produce or perceive information either simultaneously

or rapidly in succession, regardless of whether the information was verbal ornonverbal.

We certainly agree with Zhang and Tomblin that if we had entered ‘‘160temporal processing variables’’ (as they incorrectly stated as the basis of their simulations) into a discriminant function analysis, as their simulationshows, we could have come up with six temporal processing variables thatcorrectly classified a high percentage of subjects as LI or N. However, thisis not what was done in the TSM study. Rather, the purpose of the TSMstudy was to complete a comprehensive assessment of the many and varioussensory, perceptual, motor, neurodevelopmental, and speech functions that


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had previously been reported to be impaired in LI children, certainly not justtemporal functions. The goal was to determine if there is a specific patternof sensory, perceptual, and/or motor deficits that would emerge from acomprehensive study of neuropsychological functions, within a large, well-

classified population of children with LI, when compared to well-matchedcontrols.

Zhang and Tomblin do not appear to have understood either the goal of the TSM study or the diversity of variables that were included in the TSMdiscriminant function analyses. Rather, they ran their computer simulationsassuming that all 160 variables were temporal processing variables. In simu-lation experiment III for example, they state that their simulation experimentwas designed to address the question of how much true predictive power isrequired of 160 temporal processing variables in order for them to producesix temporal processing variables that are as predictive as the six variablesfound by TSM’s study. They further state that the answer for this questionwill estimate the true predictive power that is required of 160 variables inorder for them to be as predictive as the 160 temporal processing variablesin TSM’s study.

Thus, Zhang and Tomblin clearly set up a ‘‘straw-man’’ as the basis of

their simulations. Even so, it is interesting to note that, even when stackingthe deck with 900 temporal processing variables, Zhang and Tomblin’s com-puter simulations were not able to find six variables that could match the98% accuracy in classifying 59 children correctly as LI or normal found inthe TSM study. Given that only a minority of the 160 variables actuallyincluded in the TSM study assessed rapid temporal processing, what wasparticularly notable was that it was rapid temporal processing variables alonethat entered the discriminant function equation. Indeed, that is the entire basisfor the TSM article.

We agree with Zhang and Tomblin that there are potential pitfalls of usingdiscriminant function analysis in nontheoretically driven studies. The criticalflaw in the Zhang and Tomblin critique of TSM, however, is the failureto apply any theoretical framework to their computer simulation. Althoughdiscriminant function analyses certainly can be run on strictly a random num-bers basis, as was done by Zhang and Tomblin, this violates the basic re-

search purposes for which these analyses were designed. More to the pointhere is the simple fact that the simulations run by Zhang and Tomblin tocriticize the conclusions of TSM neither simulate nor replicate the actualmethodology employed in TSM. Therefore, their conclusions cannot be ap-plied to the original TSM study and, as such, are meaningless.

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