Cerebral Cortex Advance Access originally published online on January 11, 2006
Cerebral Cortex 2006 16(12):1718-1728; doi:10.1093/cercor/bhj107
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Auditory Processing Deficits in Dyslexia: Task or Stimulus Related?
1 Department of Neurobiology, Hebrew University of Jerusalem, Jerusalem 91904, Israel, 2 Department of Psychology and Interdisciplinary Center for Neural Computation, Hebrew University of Jerusalem, Jerusalem 91904, Israel, 3 Current address: Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL 60208, USA
Address correspondence to Dr Merav Ahissar, Department of Psychology, Hebrew University, Mt Scopus, Jerusalem 91905, Israel. Email: msmerava{at}mscc.huji.ac.il.
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Abstract |
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The nature of the fundamental deficit underlying reading disability is the subject of a long-standing debate. We previously found that dyslexics with additional learning difficulties (D-LDs) perform poorly in simple auditory tasks. We now tried to determine whether these deficits relate to stimulus or task complexity. We found that the degree of impairment was dependent on task rather than stimulus complexity. D-LDs could adequately detect and identify mild frequency changes in simple pure tones and minimal phonemic changes in complex speech sounds when task required only simple same–different discriminations. However, when task required the identification of the direction of frequency change or the ordinal position of a repeated tonal or speech stimulus, D-LDs' performance substantially deteriorated. This behavioral pattern suggests that D-LDs suffer from a similar type of deficits when processing speech and nonspeech sounds. In both cases, the extent of difficulties is determined by the structure of the task rather than by stimulus composition or complexity.
Key Words: auditory processing • dyslexia • frequency discrimination • perceptual memory • perceptual processing • working memory
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Introduction |
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Dyslexics are individuals with substantial and continuous reading difficulties in spite of adequate general intelligence and education. They comprise
10% of school children (Lyon 1995
; Shaywitz 1998; Snow and others 1998). Though a subpopulation of dyslexics has particularly high general cognitive abilities, enabling them to compensate for their poor reading, most dyslexics have additional learning difficulties (Fletcher and others 1994).
Most dyslexics, with and without additional learning difficulties, suffer from poor phonological processing (Snowling 2000). They have difficulties "hearing" words that are composed of smaller speech segments and in "manipulating" speech sounds. These impairments are directly linked to their reading difficulty because decoding of the alphabetical script requires mapping visual symbols to basic speech sounds (Snowling 2000).
Another typical characteristic of dyslexia is poor verbal working memory (Siegel and Ryan 1989; Swanson 1993; Vargo and others 1995). Working memory is the ability to retain a set of stimuli while performing additional cognitive operations on them (Baddeley 1986). Basic tasks, like decoding unfamiliar words and simple arithmetic calculations, require holding parts (speech segments or digits) while manipulating other parts of the input stream. Consequently, poor working memory may impede the performance in a broad range of academic tasks including, but not specific to, reading (Gathercole and Pickering 2000).
A 3rd set of observations relates to dyslexics' performance in simple psychoacoustic tasks. Many studies (e.g., Tallal 1980; see review by Wright and others 2000) reported dyslexics' poor performance in such tasks, though both the prevalence and the functional role of these deficits have been heatedly debated (Rosen 1999).
Recently, we found that poor psychoacoustic performance is characteristic of a specific, large, subpopulation of dyslexics with additional learning difficulties (D-LDs). These individuals also suffer from particularly poor verbal working memory, the extent of which is correlated with the degree of their psychoacoustic and reading deficits (Amitay, Ben-Yehudah, and others 2002; Banai and Ahissar 2004). Though D-LDs perform standard problem-solving tasks within the normal range of the general population, they have severe difficulties performing tasks with heavy working memory load, and they often need special academic support to graduate high school (Banai and Ahissar 2004).
The relationships between D-LDs' phonological, psychoacoustic, and working memory deficits are not clear. Because human working memory has mostly been studied with phonological material, it is hard to decipher whether the difficulty in manipulating speech sounds stems from poor processing of sounds—that is, a stimulus-specific deficit—or from a general difficulty in interstimulus retention and manipulation—that is, a task-specific deficit. Similarly, because adequate performance on any psychoacoustic discrimination task requires both encoding of the specific stimuli to be discriminated and the discrimination process itself, that is, the need to serially retain and compare stimuli, when discrimination is impaired, it is hard to dissociate whether poor performance results from a stimulus-specific deficit (encoding auditory stimuli) or from a deficit related to the discrimination task at hand (retention, comparison, decision).
In the current study, we asked whether D-LDs' deficits are stimulus or task specific using both pure tones and complex speech sounds. Specifically, we compared the predictions of 2 types of hypotheses regarding the mechanisms underlying D-LDs' poor performance on auditory discrimination tasks.
- D-LDs have poor representations of auditory stimuli. Hence, they will have difficulties discriminating between similar auditory stimuli, regardless of task complexity. The extent of their difficulties will therefore increase with the subtlety of the required stimulus discrimination. This bottom-up hypothesis is parsimonious and consistent with many previous findings, most notably by Tallal (1980) and the following behavioral (De Weirdt 1988; Reed 1989; Nicolson and others 1995; Hari and Kiesila 1996; Kraus and others 1996; McAnally and Stein 1996; Adlard and Hazan 1998; Witton and others 1998; Hari and others 1999; Heath and others 1999; Talcott and others 1999; Ahissar and others 2000; Waber and others 2000; Amitay, Ahissar, and Nelken 2002; Ramus and others 2003) and electrophysiological (Baldeweg and others 1999; Nagarajan and others 1999; Ahissar and others 2001; Kujala and others 2003; Maurer and others 2003; Renvall and Hari 2003) studies. It predicts that D-LDs' performance will be poor when confronted with a perceptual challenge, that is, when either high-resolution auditory discriminations or complex auditory processing are required, regardless of the behavioral task used.
- D-LDs' ability to perform auditory discriminations is limited by task requirements (i.e., protocol of stimulus presentation and required manipulations). Thus, the same type of stimuli (speech or nonspeech) will induce more severe difficulties when task complexity is increased (i.e., by increasing memory load). Although quite a few previous studies assessed psychoacoustic abilities in related populations, they typically used a single behavioral paradigm (e.g., Ahissar and others 2000; Amitay, Ahissar, and Nelken 2002; Ramus and others 2003) and hence could not dissociate whether difficulties related to basic stimulus processing or to the required manipulations (though see France and others 2002).
To compare the predictions of these 2 hypotheses, we used 3 frequency discrimination tasks, using the same stimuli with different degrees of task complexity, and 2 speech perception tasks, again using the same speech tokens with 2 different procedures.
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Materials and Methods |
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Participants
The study was conducted in 2 test populations. The 1st was composed of 57 8th grade students (all female, aged 14.2 ± 0.4) from 2 classes, 32 from a regular public school, and 25 from a private school for students with mild learning disabilities (LDs). The control (regular) school was chosen based on the similar demographic characteristics of the students in the 2 schools. Two paradigms of frequency discrimination as well as reading, memory, and cognitive measures were administered to this population. Five students had to be removed from data analysis after all assessments were completed: One from the LD class had generally poor cognitive abilities, as measured by standard tests. For 1 control participant, we could not measure a reliable threshold for any of the psychophysical tasks, and we thus removed her data from further analysis as well. Two other students in the control class were found to be reading disabled, and their data were therefore also removed. Data of another student from the control class were removed because of a hearing impairment. We thus report the results of 24 students from the special school and 28 normal learning control students.
The 2nd population comprised 35 7th grade students (all female, aged 13.1 ± 0.4) from the same school for mildly learning-impaired individuals, who participated in this study as a part of a larger research program in which they took part. Data of 1 student suspected of a hearing loss were removed from the analysis, and thus, data of 34 7th grade students are reported.
The parents of all participating students gave their consent after receiving letters with information regarding the study. All participants completed all tasks, unless otherwise noted in the text.
Group Classification
None of the students from the regular school had a history of learning problems, and they were thus defined as a normal-learning control group (control I). Students from the LD school all had a history of LD, reading related or otherwise. For the purpose of the current study, they were divided to 2 groups: one with dyslexia (D-LD) and the other with normal reading and phonological abilities, which served as a same-classroom control group (control II). Classification was based on 2 measures that should be impaired among dyslexics based on current definitions stressing the significance of phonological deficits to the diagnosis of dyslexia (Lyon 1995; Snowling 2000): reading of pseudowords and phonological awareness (see task descriptions subsequently). Based on these 2 measures, we calculated a combined phonological score with respect to normal-learning controls (control I average without the 2 individuals with reading disability). LDs whose phonological score was lower than the controls' average by 1.5 standard deviation or more were defined as dyslexics (n = 15 in the 8th grade and 22 in the 7th grade). The rest, whose phonological abilities were within the range of the controls, were defined as same-classroom controls (control II; n = 9 in the 8th grade and 12 in the 7th grade).
Cognitive Performance
Unlike discrepancy-based definitions of dyslexia, current diagnostic criteria, which were used in this study (Siegel 1992; Waber and others 2000), do not require a discrepancy between reading abilities and intelligence quotient (IQ) scores but rather within the normal IQ (>80). Although we could not conduct a full IQ test during the study, all students in the special school were administered a detailed psychoeducational assessment before being admitted to the school to ensure that they have the potential to graduate with a full high school diploma by the end of the 12th grade. This testing rules out the possibility of IQ < 80 among the students (except for 1 student, whose data were excluded, as explained earlier). In addition, the Raven standard progressive matrices scores (Raven and others 2000) of all these students were 
35, which excludes the lower 25% of the population.
Materials
Psychophysical Tasks
All stimuli were presented to both ears through Sennheiser HD-265 linear headphones and a TDT system III signal generator (Tucker Davis Technologies, Alachua, FL) controlled by a PC in a quiet room in each school.
Auditory frequency discrimination.
Participants made frequency discriminations in 3 conditions. The frequency of the test (higher) tone was always changed in a 2 down/1 up staircase procedure (step size was 40 Hz for the first 5 reversals and 5 Hz thereafter) converging at a performance level of 70.7% (Levitt 1971). The frequency of the reference tone was fixed, 1000 Hz. A pleasant visual feedback was provided for correct responses.
- High–low discrimination (Hi/Lo): Two 50-ms tones with 1000-ms interstimulus interval (ISI) were presented in each trial. The students had to indicate which tone was higher (1st or 2nd). Assessment terminated after 50 trials or 10 reversals. Thresholds were measured twice in the 8th grade, at the beginning and at the end of the 1st session, and the average just noticeable difference (JND) was used in the statistical analysis. Due to the high correlation between the two, only 1 assessment was conducted in the 7th grade.
- Same–different discrimination (2-tone S/D): Two 50-ms tones (with 1000-ms ISI) were presented in each trial. The listener had to indicate whether they were same or different. Same and different trials had an equal probability of appearance. Assessment terminated after 100 trials or 10 reversals (based only on trials with different stimuli). Threshold was measured once in the 2nd testing session.
- Same–different discrimination with 3 tones (3-tone S/D): a fixed reference tone was followed by a 1500-ms silent interval and then by 2 other tones (with 950-ms interval between them), one of which was a repetition of the reference and the other was different. Participants had to indicate which tone (2nd or 3rd) was the same as the reference.
Participants were given a practice block of 15 trials (with a frequency difference of 1000 Hz between the tones) to familiarize them with the task prior to assessment. Initial frequency difference in the test blocks was 500 Hz. If they had 2 errors or more, they were given another practice block. If they still had 2 errors or more, testing begun but with a larger initial frequency difference, 800 Hz. Participants responded to the stimuli in each trial orally, by telling their answer to the experimenter who immediately entered it to the computer to continue the procedure. This mode of response was chosen to minimize errors due to sensory-motor confusions. This interactive mode further ensured that all participants were maximally alert throughout the assessment procedure. However, because it introduced an intervening oral responses (within the sequence of pure tones) and somewhat prolonged the assessment process, it may have elevated the estimated discrimination thresholds.
Calculation of frequency discrimination thresholds.
Frequency JNDs, that is, the minimal frequency difference reliably discriminated, were used as indices of discrimination. For each participant, JNDs were calculated based on the average of her last 5 reversals. Hi/Lo JNDs were obtained for 54 8th grade and all 7th grade students (an equipment failure occurred during the assessment of one of the LD students). Two control students failed to achieve a reliable JND in the 1st assessment (they had no reversals in the last 20 trials), and we thus used only their 2nd thresholds. Given the high correlation between the 2 Hi/Lo measurements (r = 0.79, P < 0.001), we used the average JND for the rest of the students in the 8th grade. S/D JNDs were obtained for 51 8th grade (28 Controls I, 8 Controls II, and 15 D-LDs) and all 7th grade participants.
Auditory duration discrimination. Seventh grade participants heard 2 tones and had to indicate which one was longer, the 1st or the 2nd. Fixed reference duration was 100 ms in 1 condition and 400 ms in the other. Step sizes were 40, 25, and 5 ms in the 100-ms condition and 40, 25, and 5 ms in the 400-ms condition. Step size changed after 3 reversals. All other aspects of the task were identical to the Hi/Lo frequency discrimination task.
Speech discrimination and identification. Eighth grade participants were required to discriminate minimal phonemic pairs. The stimuli were pairs of 2-syllable pseudowords differing in 1 consonant and identical otherwise. The following consonant pairs were used: /d/-/t/, /b/-/d/, /b/-/p/, /v/-/f/, /m/-/n/, and /s/-/z/, appearing either at the beginning or at the end of the word. Between trials, 4 different syllables were used (/a/, /e/, /i/, and /u/). All stimuli were produced by a native female Hebrew speaker. Twenty-four different pairs were used.
The task had 2 conditions with 48 trials in each. 1) Two-word S/D condition in which the 24 different pairs were supplemented with 24 same pairs. 2) Three-word S/D condition in which the participant first heard a pair of pseudowords. After a 2-s interval, one of the pseudowords was repeated, and the task was to indicate which word it was—the 1st or the 2nd. Each pair was repeated twice, each time with a different repeated word.
Speech perception in noise.
Minimal intensity level for accurate speech perception in noisy background (narrow-band amplitude–modulated noise) was tested using the same set of 2-syllable pseudowords described earlier, normalized for intensity and duration. Total noise RMS was 83-dB SPL (for fuller description, see Putter-Katz and others 2005). On each trial, a single pseudoword was played and participants were asked to accurately repeat it. The intensity of the pseudowords was adapted in a 3 down/1 up staircase procedure (converging on 80% correct) while noise level remained fixed. The assessment terminated after 85 trials or 15 reversals. Identification threshold was the arithmetic mean of the last 10 reversals. This assessment was conducted in the 7th grade.
Reading
Oral reading of pointed Hebrew words and pointed nonwords was assessed using a list of 24 pseudowords followed by a list of 24 words (see Ben-Yehudah and others 2001). The pseudowords were designed to mimic the real Hebrew words in the word list. These reading tests, designed by A. Deutsch (for details, see Deutsch and Bentin 1996), were previously found to be reliable indicators of reading difficulties. Subjects had to read aloud, as accurate and as fast as possible from the printed lists presented to them. Both accuracy and speed were recorded.
Phonological Awareness
Phonological awareness was assessed using the Hebrew version of the spoonerism task (developed by Peleg and Ben Dror, unpublished test materials), consisting of phoneme deletion and replacement. Listeners were orally presented with a word pair and were asked to swap the 1st phonemes of the 2 words (e.g., white pig 
pite wig). In the process of introducing the task, all participants successfully performed its simple substeps (phoneme deletion/replacement). Twenty word pairs were presented.
Memory Tests
Verbal memory was assessed using Digit Span, a subtest of Wechsler intelligence scale for children (WISC--R95 Wechsler 1998). This test contains 2 parts. In the 1st part, participants are asked to repeat a list of orally presented digits in the order they were presented. The maximal length of successfully reproduced sequences characterizes the capacity or span of verbal memory. In the 2nd part, subjects are asked to repeat the sequence of digits in the reverse order. The 2nd part is more complex and measures the combined effect of capacity and manipulation in verbal working memory. This test was scored using the Wechsler scaled score.
A Hebrew version of the "sentence span" task adapted by Ben Dror and Shani (1998) from the reading span task originally developed by Daneman and Carpenter (1980) was used to assess retention of words through interfering stimuli and task switching. Seventh grade participants were asked to listen to a series of orally presented short sentences with a missing last word, complete the last word of each sentence, and recall all the last words in the order of completion at the end of the series. Series length increases from 2 to 6 sentences. Scoring emphasizes both the number and the order of correctly recalled words.
Nonverbal Cognitive Abilities
Block design (WISC-R95, Israeli version) was used as a measure of general cognitive abilities. Administration and scoring followed the standard procedure described in the Administration and Scoring manual of the test.
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Results |
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Population Profile
Table 1 shows the average scores of the 3 groups of 8th grade participants: control I, control II, and D-LDs in reading and reading-related tests and in standard cognitive tasks. Table 2 shows reading, reading-related, and standard cognitive scores of the 7th grade participants. As expected, D-LDs' performance was particularly impaired in the reading and phonological tasks compared with both control groups.
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General Cognitive Abilities
The 2 control groups did not differ significantly on any of the reading or cognitive measures administered. Thus, nondyslexic LDs (control II) are similar to normal-learning students in general cognitive abilities and yet form a more adequate control group to D-LDs in terms of having the same educational background and school experience. D-LDs scored lower than control I on block design, a standard measure of general cognitive ability. However, their scores were not significantly lower than those of control II (for 8th graders: t = 1.2, P > 0.22, not corrected, to allow minimum chance of retaining the null hypothesis that the groups do not differ cognitive tasks; for the 7th grade, see Table 2), whose scores were intermediate. Moreover, D-LDs' scores on this task were well within the normal range. Table 2 further shows that scores in the 2 tasks that often serve as a short version for measuring general IQ, vocabulary, and block design (Woerner and Overstreet 1999) did not significantly differ between D-LDs and control II.
Processing Nonspeech Stimuli
Frequency Discrimination
Figure 1 shows average discrimination thresholds (JNDs) of the 3 subject groups on the S/D and the Hi/Lo (1st and 2nd assessments) frequency discrimination tasks. A clear difference in thresholds is evident. The Hi/Lo task yielded higher JNDs than the S/D task (Ftask = 19.2, P < 0.001). However, this difference was the result of D-LDs having huge difficulties with the Hi/Lo task (in both assessments) compared with the 2 other groups. The 2 control groups, on the other hand, did not differ from each other. The average of the 2 measurements was 22 ± 18%, 16 ± 10%, and 52 ± 28% in the control I, control II, and D-LD groups, respectively, with significant group (F = 9.7, P < 0.001) and interaction (F = 6.9, P = 0.002) effects; the 2 post hoc comparisons between D-LDs and the other groups were significant at P < 0.005, whereas those between the 2 control groups were not significant. Percent success around these thresholds did not differ significantly between the 3 groups (81 ± 10%, 83 ± 6%, and 74 ± 17% in the control, LD, and D-LD groups, respectively; F = 1.7, P > 0.18), indicating that group differences do not stem from measuring different levels of performance accuracy.
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On the other hand, on the S/D task, neither performance level (F = 0.38, P = 0.687) nor performance accuracy (average percent correct was 84 ± 6, 84 ± 4 and 82 ± 6 for Controls I, Controls II and D-LDs, respectively) significantly differed between the 3 groups.
Comparing performance in these 2 frequency discrimination tasks on a subject by subject basis, we found no correlation between thresholds (r = 0.09, P > 0.5 in the entire 8th grade group), indicating that different bottlenecks may limit performance in these 2 tasks. Figure 2 illustrates that performance of the D-LD participants in the Hi/Lo (left), but not in the S/D task (right), was significantly correlated with both their verbal memory (i.e., digit span: r = 0.68, P = 0.005) and phonological awareness scores (i.e., spoonerism: r = 0.82, P < 0.001), 2 measures known to be causally linked with reading skills. A similar correlation pattern was observed among LDs (not shown), though it was only marginally significant due to the smaller size of this group (r = 0.72 and 0.55, P = 0.04 and 0.15, respectively, for digit span and spoonerism). Note that S/D JNDs are not correlated with these measures even though they are quite scattered (the range of S/D JNDs among controls is 0.5–40%, i.e., there is no floor effect).
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Duration Discrimination
A plausible explanation for D-LDs' difficulties in the Hi/Lo task relates to the explicit analogy between pitch and height, which is required by this task (participants were asked "which tone was higher?") and could be particularly difficult for D-LDs. In that case, their impaired performance may stem from the specific requirement embedded in frequency discriminations rather than from the general requirement of stimulus evaluation. To assess whether this is indeed the case, we designed another task, using the same behavioral paradigm as in the Hi/Lo discrimination task; however, comparisons referred to an orthogonal dimension—stimulus duration. Stimulus duration discrimination may be a more attention-demanding task in terms of requiring continuous monitoring throughout stimulus presentation and, thus, perhaps requires more complex neural circuitry (Leon and Shadlen 2003). Yet, duration discrimination (which tone is longer?) is an intuitive and straightforward evaluation, which was immediately understood by all participants, and was not susceptible to an interpretation that D-LDs might not have fully understood the task.
We administered the 2 duration discrimination conditions to the 7th grade test group (who showed the same behavioral pattern on the Hi/Lo task as shown below). As shown in Figure 3, D-LDs (n = 19), who had difficulties in performing Hi/Lo frequency discrimination, had similar difficulties in performing long/short duration discriminations around both durations, compared with the control II group (n = 9), with no difficulties in Hi/Lo discriminations (t = 2.9, P = 0.007 for 400-ms reference; t = 2.5, P = 0.016 for the 100-ms reference). Performance accuracy did not differ between the groups in either condition (percent correct in the control II and D-LD groups were 76 ± 4% and 75 ± 4% with 100-ms reference and 73 ± 4% and 73 ± 6% with the 400-ms reference, respectively), indicating that differences in thresholds did not stem from measuring different levels of performance accuracy.
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Taken together, we have shown that the difficulties of our dyslexic participants are not specific to the compared dimension. When subjects had to estimate the direction of change, whether higher or longer, D-LDs had difficulties.
Order Judgments
Participants could adequately perform the S/D task by identifying repetition of the stimulus without having to associate stimulus position (1st or 2nd) with the stimulus type (higher or lower). Though this task clearly requires some form of memory trace, such a trace may be implicit and result from stimulus-specific adaptation mechanisms. These mechanisms yield smaller responses to previously presented stimuli and thereby a greater response to novel stimuli, regardless of "how" they are novel. These perceptual mechanisms thus signal novelty but are not sufficient for determining its nature as required in the Hi/Lo task. An example for such a mechanism at the level of the auditory cortex is the mismatch negativity (MMN) response, which signals change in a repetitive sequence of auditory stimuli (see, e.g., Naatanen and others 2001).
Under S/D conditions, D-LDs had no difficulties, whereas in the Hi/Lo task, they had substantial difficulties. The difference between these tasks may thus stem from the Hi/Lo task being generally more taxing for explicit memory mechanisms or perhaps from its more specific requirement to assess the nature of the difference between the stimuli. To resolve this question, we administered an extended S/D task, using 3 stimuli. In this task, a repetition always occurs, and the listener needs to identify the ordinal position of the repeated stimulus. Moreover, it requires retention through interfering stimuli and often for longer durations (though duration per se is probably not overtaxing for D-LDs, Ben-Yehudah and others 2004). Thus, from a general working memory perspective, it is a taxing task, yet no parametric evaluations are required. Therefore, if D-LDs' difficulties stem from the requirement for parametric stimulus evaluations of the Hi/Lo task, then they are not expected to have difficulties with this task, even though it is demanding from a working memory perspective.
We administered all 3 frequency discrimination tasks to the 7th grade group described earlier. In the repeated tasks (Figure 4, 2 left bars), we replicated our findings (illustrated in Fig. 1) that D-LDs were impaired in Hi/Lo (their average was 37 ± 26% compared with 10 ± 11% in the control II group; t = 4.8, P < 0.001) but not in S/D frequency discrimination (10 ± 10% vs. 8 ± 7%, respectively; t = 1, P > 0.3). In the novel 3-tone S/D task, D-LDs were significantly poorer than LDs (19 ± 15% vs. 8 ± 10%, respectively; t = 3.1, P = 0.004; Fig. 4, rightmost bars), indicating that even S/D comparisons are difficult for them when accurate retention and comparison of previous stimuli is required through subsequent intervening stimuli.
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Taken together, these data show that D-LDs have difficulties in tasks that require explicit retention and comparison of series of simple tones.
Processing Speech Elements
Comparing Speech Sounds
We now asked whether a similar pattern of difficulties would characterize D-LDs' performance in analogous tasks that use complex speech sounds rather than simple tones as test stimuli. Two conditions of a speech discrimination task (described earlier) were administered to the 8th grade D-LD and control II participants: simple 2-stimuli S/D task (15 D-LDs and 9 controls II completed this condition) and 3-stimuli order judgment S/D condition (14 D-LDs and 7 controls II completed this task), similar to the 3-tone S/D frequency discrimination task. Figure 5A shows average scores in these 2 tasks, illustrating that D-LDs were significantly poorer than their peers in discriminating phonological components when the task required judging the ordinal position of the pseudowords but not in the simple 2-stimuli S/D condition (Ftask = 9.6, P = 0.006; Fgroup = 5.2, P = 0.05; the interaction term approached significance Finteraction = 3.5, P = 0.078).
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Similar to the findings with pure tones, the degree of deficit in processing complex speech sounds was thus also dependent on the task: Impairment was revealed only when a 3rd stimulus was introduced. Furthermore, as shown in Figure 6, D-LDs' performance in the 3-pseudoword speech task, but not in the 2-pseudoword task (not shown), was highly correlated with their Hi/Lo frequency JNDs (r = 0.72, P = 0.003). These findings suggest that the nature of D-LDs' deficits may be similar for complex speech components and simple pure tones.
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Speech Perception In Noise
Our findings that S/D comparisons of speech components were not difficult for D-LD individuals suggest that they do not have severe difficulties in speech perception. Yet, given that these stimuli were not very difficult (natural speech presented at a comfortable rate in quiet) and most subjects got most pairs right, more subtle speech perception deficits may have been overlooked due to a ceiling effect. In order to ensure that it was not the relative simplicity of the stimuli we used, we administered an adaptive test of speech perception in noise (with the same pseudowords used for the discrimination tasks but with superimposed noise). In this task (originally described by Putter-Katz and others 2005), the stimuli were very complex, but the memory and cognitive loads were very low because subjects were only asked to repeat a single bisyllabic pseudoword. The minimal signal level needed to achieve 80% correct repetition does not significantly differ between control II and D-LDs (t = 1.7, P > 0.10), as shown in Figure 5B. The finding that increasing signal complexity does not increase D-LD's difficulties indicates that basic perceptual mechanisms underlying immediate auditory perception are adequate in these individuals. Moreover, speech identification thresholds were not correlated with Hi/Lo JNDs among either D-LDs or control II (r = 0.03 and 0.14, respectively, P > 0.59), suggesting that different mechanisms affect performance in these 2 tasks.
Do D-LDs Suffer from a Generalized Cognitive Deficit?
Because it was not possible to fully match D-LDs and the other groups on measures of cognitive ability, it may be claimed that D-LDs' deficits in performing complex discriminations (Hi/Lo, short/long, and 3-stimuli S/D comparisons) arise simply because these tasks have a generally greater cognitive load than those they performed adequately (2-stimuli S/D, a single pseudoword repetition). Thus, their deficit may reflect a general cognitive deficit rather than a task-specific one and is therefore not surprising. For several reasons addressed subsequently, we would like to suggest that this is not the case.
First, where the group differences on Hi/Lo frequency discrimination related to group differences in IQ, we would expect a correlation between block design and Hi/Lo frequency JNDs. This was not the case. No significant correlations between block design and Hi/Lo frequency discrimination were observed in either group (r = 0.2, 0.002, and 0.1 for control I [n = 29], control II [n = 19], and D-LDs [n = 37], respectively, P > 0.29; data pooled from 7th and 8th grades). Furthermore, repeating the statistical analysis of the Hi/Lo and S/D frequency discrimination tasks with block design scores as a covariate did not change any of our findings, as expected from the lack of correlation between block design and frequency discrimination: Main effects for group (F = 9.5, P < 0.001), task (Hi/Lo vs. S/D: F = 5.33, P = 0.02), and a significant task x group interaction (F = 3.88, P = 0.028) were observed, whereas the block design x task interaction (F = 1.43, P > 0.25) was not significant, suggesting that the findings cannot be fully attributed to IQ scores.
Second, as shown in Table 2, D-LDs could perform complex cognitive tasks like sentence span adequately. We chose this task because it is cognitively demanding in similar ways to our previous tasks, that is, it requires information retention through interfering stimuli, and taxes attention and memory in terms of double load of sentence completion as well as retention. Yet, it does not require stimulus manipulation, and retention can be enhanced using the semantic content of the words and sentences.
Taken together, we conclude that D-LDs' unique pattern of deficits in handling auditory stimuli is not a consequence of a general factor limiting their performance in all cognitively demanding tasks (for further discussion, see Banai and Ahissar 2004, 2005).
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Discussion |
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Summary of Results
In this study, we found that D-LDs' performance was adequate in tasks that require identification or simple S/D discrimination of either pure tones or complex speech sounds. On the other hand, given exactly the same physical stimuli, D-LDs had substantial difficulties in tasks that required either parametric comparisons (Hi/Lo and long/short) or judging the ordinal position of the repeated stimulus (whether a tone or a pseudoword). Moreover, high correlations were found between the degree of difficulty in performance of complex tasks using simple tones and speech components. These findings suggest that the mechanisms underlying D-LDs' impaired ability to perform these demanding tasks are common to the 2 types of stimuli. This common impairment is not in reasoning or general cognitive abilities, as indicated by adequate performance on a cognitively demanding, yet largely semantic based, task. We thus propose that D-LDs' deficits involve mechanisms of operating on perceptual aspects of recently processed stimuli, broadly termed working memory mechanisms.
Sex Differences in Dyslexia
All our participants were females because our study was conducted in an all-female school. Thus, although our results are "clean" in the sense that we report within-gender performance and variability (see Liederman and others 2005), we cannot directly generalize our findings to the male population. The issue of prevalence of perceptual impairments among male versus female dyslexics had not been systematically studied. Moreover, its assessment would be complex because it should also address related issues of reasoning abilities, language impairments, and attentional deficits. At present, even the relative prevalence of dyslexia among males and females is still disputed (Shaywitz and others 1990; Share and Silva 2003).
An informal examination of our own accumulated data (200 dyslexic and 200 control participants) suggests no consistent gender-related perceptual differences.
The Underlying Auditory Deficit of D-LD Individuals: Accuracy of Representation or Stimulus Manipulation?
What is it that differentiates the tasks that posed particular difficulties to D-LDs from those that did not? Tasks that pose a great challenge for D-LDs could, in principle, be tasks that require more refined auditory representations. Alternatively, they might be generally more demanding tasks, requiring better reasoning or decision-making abilities. Third, these tasks may pound on specific stimulus operations that are selectively impaired among D-LDs. We argue for the 3rd alternative, even though the range of tasks that we applied is not sufficient for accurate characterization of these operations.
The 1st interpretation can be refuted because increasing stimulus complexity and hence processing requirements to speech stimuli (with and without noise) did not specifically hamper D-LDs' performance. The "difficulty" interpretation can be refuted for the following 3 reasons. First, levels of difficulty, as measured by performance accuracy, were equated across tasks and conditions by applying an adaptive procedure that converged to the same relative level of performance. Second, as shown in Figures 1 and 4, in both control groups, thresholds did not differ between the Hi/Lo and the same–different conditions. These tasks were just not more difficult for them. Third, difficulty per se was not a sufficient impediment to D-LDs, as shown by their adequate performance of the cognitively demanding task of sentence span.
What could be the specific operations that are impaired among D-LDs? Although our set of paradigms can refute the general cognitive or the perceptual difficulty hypotheses, they leave many alternatives unresolved. One is that some aspects of working memory mechanisms are impaired among D-LDs because the tasks that were specifically impaired among D-LDs put a heavier load on working memory. Our previous studies refuted a retention deficit, that is, faster decay of memory trace interpretation, because manipulating ISIs did not affect D-LDs' deficits (Ben-Yehudah and others 2004). Yet, whether it is the buildup of stimulus-specific memory traces or the operation of stimulus comparison that is impaired is beyond the scope of this study. Both may be more taxing in the tasks that posed greater difficulties to D-LDs.
Our finding that the behavioral paradigm used for assessment is crucial to the degree of deficits revealed by dyslexics is consistent with reports of previous studies both in the auditory (e.g., Heath and others 1999; France and others 2002) and in the visual domain (Ben-Yehudah and others 2001). However, most studies applied only a single behavioral paradigm for evaluating thresholds, and thus, the substantial interstudy variability was mainly interpreted in terms of different population samples rather than different behavioral tasks (see Discussion in Banai and Ahissar 2004). An important lesson from our study is that in order to decipher whether it is the task or stimuli that taxes individuals, one needs to assess performance using at least 2 behavioral tasks that greatly differ in their working memory load.
Task-Specific Difficulties and Theories of Dyslexia
According to the dominant "core phonological deficit hypothesis" of dyslexia (Snowling 2000; Vellutino and others 2004), reading disability is a result of a specific deficit in phonological processing. By this account, phonological deficits contribute to the reading deficits, whereas deficits in the processing of nonverbal stimuli stem from a separate source and are irrelevant to reading. Data from the current study does not provide support for a speech-specific deficit. Rather, our findings, coupled with recent findings from imaging studies (LoCasto and others 2004; Burton and others 2005; Luo and others 2005), suggest that processing of both speech and nonspeech stimuli shares at least some common processing that is impaired among D-LDs. Thus, although deficits in nonverbal auditory processing may not be directly relevant to reading, it is part of the same underlying deficit contributing to the phonological processing deficit and consequently poor reading.
The current finding that the degree of discrimination deficit among D-LDs is task dependent and that D-LDs do not have difficulties detecting speech in noise suggests that their auditory processing is not impaired under all circumstances. However, whether we define the deficits we found as "perceptual" (Tallal and others 1993) or "postperceptual" depends on our terminology of perception. We believe that the "auditory experience" (i.e., what one perceives) is different for D-LDs under some conditions, depending on stimulus protocol and behavioral task. Thus, an integrative view of perception as a dynamic, large-scale process, which underlies this experience (Hochstein and Ahissar 2002), attributes these deficits to perceptual processes. This means that somewhere in the circuitry underlying our immediate explicit perception, D-LDs' processing is impaired. However, the cortical circuitry underlying these processes is broad and includes, among others, frontal areas, which are major contributors to the retention and comparison aspects required for adequate performance in most tasks.
Relation to Previous Imaging and Electrophysiological Studies
Based on the strong dependence of D-LDs' manifested deficits on stimulus protocol and on task demands, we suggest that their fundamental deficit does not reside in auditory cortex. This suggestion is based on both lesion and imaging results. Neuropsychological studies suggest that a pervasive lesion of the primary auditory cortex impairs S/D discriminations for both simple tones and speech sounds (Tramo and others 2002), in contrast to our findings in D-LDs. Recent findings from imaging studies have shown that activation patterns in auditory cortex were more related to the nature of the stimulus, whereas patterns of activity in frontal area were more related to task demands (Luo and others 2005). In frontal areas, task characteristics, for example, same–different versus rhyming rather than the stimulus processed (words vs. pseudowords or tones, LoCasto and others 2004; Burton and others 2005), were found to affect activation patterns. Burton and others (2005) suggested that the task-related differences in activation are related to differences in working memory load.
The behavioral impairments we measured are thus consistent with each of the following 2 interpretations.
- D-LDs' deficits may be related to impaired transfer of information between posterior, modality-specific stores and the frontal areas carrying out specific working memory operations (for review, see Curtis and D'Esposito 2003). Such interpretation is consistent with the suggestion that dyslexia is a "disconnection syndrome" in which communication is impaired between different cortical regions (Paulesu and others 1996). In particular, Klingberg and others (2000) have shown an abnormality of white matter tracks in temporoparietal regions in dyslexics, which may carry information from temporal to frontal regions.
- Deficits may stem from impaired function of frontal areas. Thus, information is properly transferred but is not properly operated upon. Studies of executive functions in dyslexia reported that subgroups of the dyslexic population are impaired in tasks considered as reliable correlates of prefrontal function, such as the Wisconsin Card Sorting Test (Helland and Asbjornsen 2000; Brosnan and others 2002). Functional imaging studies also report abnormal patterns of activation in prefrontal areas of dyslexic subjects (Backes and others 2002; Shaywitz and others 2003). Furthermore, the most notable change in activation pattern following an effective auditory behavioral training (which improved reading ability) was observed in prefrontal areas (Temple and others 2003). The typical interpretation of these findings is that dyslexics fail to utilize brain areas that are normally involved in language processing. Language and working memory are, however, hard to disentangle when using verbal tasks. Although the amount of improvement in language abilities in the study of Temple and others (2003) was correlated with the magnitude of increase in activation in the temporoparietal cortex, it could be that both are an outcome of the prefrontal change.
The above "higher level" interpretations seem at odds with previously reported findings of impaired activity of the auditory cortex. Thus, Nagarajan and others (1999) recorded deficits in auditory cortical responses to tones presented with brief intervals. Moreover, abnormal MMN responses to frequency or phonemic oddballs were found among dyslexics (Kraus and others 1996; Baldeweg and others 1999; Kujala and others 2003; Maurer and others 2003; Renvall and Hari 2003; Lachmann and others 2005). This apparent discrepancy probably results from the following 2 reasons. First, the MMN response has multiple generators, including frontal ones (e.g., Rinne and others 2000). Impairment in the frontal generators seems to underlie the deficits revealed in some of these studies, which reported an abnormality in the later portion of the MMN response among children at risk of dyslexia (e.g., Maurer and others 2003). Second, other groups of dyslexics, who were not sampled in the current study (which was focused on D-LDs), may have a different, possibly "lower level" source of impairment. Preliminary evidence that this may be the case was recently reported by Banai and others (2005). They found that a subgroup with a presumably early source of deficit (impaired brainstem responses) had impaired MMNs. Interestingly, the overall LD profile of this group was much milder (e.g., having much better verbal memory) than that of D-LDs.
Analogies to Animal Studies
Consistent with the suggestion of a frontal source of impairment, the pattern of D-LDs' deficits with simple psychoacoustic tasks resembles findings of studies characterizing dorsolateral prefrontal cortex (DLPFC) functions in monkeys. These studies report a similar dissociation between unimpaired perceptual abilities and particularly poor working memory skills. Thus, monkeys with bilateral lesions to DLPFC are impaired in a 3-item task that requires them to remember which items they had already chosen compared with monkeys with bilateral perceptual IT lesions (Petrides 2000). In this task, the same 3 elements were presented in each of the 3 trial stages, though not in the same positions. Monkeys had to touch only an item that they did not choose in a previous stage of the trial. When reduced to a 2-item task, which could be performed as a sequential S/D task, monkeys with bilateral DLPFC lesion could reasonably perform the task. We interpret this ability as reflecting a change-detection strategy, which, unlike interstimulus comparisons, can be subserved by low-level sensory circuitry (of inferotemporal (IT) cortex in this case). Interestingly, retention per se seems to depend on the functioning of IT while comparisons were contingent upon intact prefrontal cortex.
Parametric stimulus comparisons probably also involve prefrontal functions (Romo and Salinas 2003). Thus, neurons in prefrontal cortex have been found active during the delay period of a tactile frequency discrimination task similar to the Hi/Lo task we used (Romo and others 1999; Romo and Salinas 2003), where this activity retained parameters of the 1st stimulus. Though involvement of prefrontal cortex in auditory working memory was not intensively studied, imaging studies in humans (Belin and others 1998; Zatorre and others 1999) and physiological (Romanski and Goldman-Rakic 2002) and anatomical (Kaas and others 1999; Poremba and others 2003) findings from nonhuman primates show that the prefrontal cortex is part of the cortical network dedicated to the analysis of sound.
Taken together, these analogies suggest that the pattern of D-LDs' behavioral deficits is consistent with a mild dorsolateral prefrontal deficit.
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Acknowledgments |
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We thank Ehud Ahissar, Shabtai Barash, Eli Nelken, Udi Zohary, and Ranulfo Romo for helpful comments on the manuscript. We thank the Israel Science Foundation, Center of Excellence grant the Israeli Institute for Psychobiology, and the Volkswagen Foundation for supporting this study.
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