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Lexical Access in College Students with Learning Disabilities: An Electrophysiological and Performance-Based Investigation.

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Title: Lexical Access in College Students with Learning Disabilities: An Electrophysiological and Performance-Based Investigation.
Language: English
Authors: Rubin, Scott S., Johnson, Clinton M.
Source: Journal of Learning Disabilities. May-Jun 2002 35(3):257-267.
Peer Reviewed: Y
Page Count: 11
Publication Date: 2002
Document Type: Journal Articles
Reports - Research
Descriptors: Cognitive Processes, Higher Education, Learning Disabilities, Neurological Impairments, Reaction Time, Recall (Psychology), Semantics, Student Characteristics, Symptoms (Individual Disorders), Undergraduate Students, Young Adults
ISSN: 0022-2194
Abstract: A study of the semantic processing abilities of undergraduates with learning disabilities (LD) (n=11) and controls (n=11) found no significant differences on the Test of Adolescent/Adult Word Finding; however, students with learning disabilities demonstrated a significantly greater number of delayed responses. Students with LD also showed delays on electrophysiological measures. (Contains references.) (Author/CR)
Journal Code: CIJOCT2002
Entry Date: 2002
Accession Number: EJ647157
Database: ERIC
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  Value: <anid>AN0006626314;led01may.02;2002Jul11.09:17;v1.8</anid> <title id="AN0006626314-1">LEXICAL ACCESS IN COLLEGE STUDENTS WITH LEARNING DISABILITIES: AN ELECTROPHYSIOLOGICAL AND PERFORMANCE-BASED INVESTIGATION </title> <p>The purpose of this study was to compare the semantic processing abilities of college students with learning disabilities (LD) to those of their peers without learning disabilities (NLD) who were matched for age, gender, and intelligence. Participants were compared on results from the Test of Adolescent/Adult Word Finding (TAWF) and from event-related potential (N400) sampling to the processing of semantically incongruous sentences. The LD and NLD groups did not significantly differ in accuracy on the TAWF; however, students with LD demonstrated a significantly greater number of delayed responses. The LD group's N400 responses were significantly delayed at the Pz electrode site. Effect size indicators also revealed somewhat reduced amplitudes at Fz and Cz locations. The significant delays of the students with LD on standardized testing and on N400 suggest an inefficiency in the semantic processing of these individuals, in both automatic and attention-based aspects of lexical access.</p> <hd id="AN0006626314-2"> Abstract </hd> <p>Many students with learning disabilities (LD) exhibit language deficits (Ehren, 1994; German, 1994; Nippold, 1992; Wallach & Liebergott, 1984; Wiig & Semel, 1984; Zirkelbach & Blakesley, 1985). Although it was once thought that children would outgrow these deficits, increasing evidence indicates that the deficits continue into adolescence and young adulthood (Wiig & Semel, 1984). In fact, it has been reported that 78% of adults with LD have limited language abilities (Blalock, 1987). Wallach and Liebergott (1984) described language problems that persist, albeit more subtly, in inferential processing, word retrieval, and pragmatic skills. Obviously, these residual effects could interfere with students' college success or career development, because the increased language competency that is required in a postsecondary setting may place too many demands on students, placing them at risk of school failure (Ehren, 1994).</p> <p>Jarrow (1987)reported that students with LD were the largest population with a disability served on college campuses. Unfortunately, research regarding the language characteristics of this population is limited (Candler & Hildreth, 1990; Harbiger, 1993). In an attempt to define differences between typical college students without learning disabilities (NLD) and students with LD, Morris and Leuenberger (1990) compared the academic and psychometric profiles of the two groups and discovered significant language deficits in the LD group. Students with LD performed significantly lower on the Test of Adolescent Language (TOAL). Furthermore, when a split of 10 or more points occurred between verbal and performance IQ scores on the Wechsler Adult Intelligence Scale—Revised, the verbal scores were the lower of the two.</p> <p>Although the language deficits exhibited by students with LD vary, a number of characteristics are, fairly common (Ehren, 1994). Zirkelbach and Blakesley (1985) defined nine common characteristics of the student with LD and a concomitant language disorder: difficulty with word meanings, off-target responding, inaccurate word selection, word-finding difficulties, use of neologisms, referent errors, problems with topic closure, immature grammatical forms, and disorganization. Ehren (1994) stated that the student with LD may also have difficulty interpreting words with multiple meanings, using language to specify similarities or differences among categories, comprehending metaphors and idioms, and obtaining the central idea of a message. Many of these deficits are semantic in nature and relate to lexical access.</p> <p>A frequent but not consistent language deficit found in the LD population is a word finding/word retrieval deficit (German, 1994; Nippold, 1992; Snyder & Godley, 1992; Wiig & Semel, 1984; Zirkelbach & Blakesley, 1985). Such deficits have been found to occur in the retrieval of words in isolation, in phrases, in sentences, and in discourse. The cause of these deficits is generally attributable to storage or retrieval problems (German, 1994; Nippold, 1992) because adequate word-finding abilities require that information is stored sufficiently and then accessed efficiently (Nippold, 1992).</p> <p>Common characteristics of the language of students with word finding deficits include perseverations, circumlocutions, frequent pauses, repetitions, and fillers (e.g., like, um, you know; Snyder & Godley, 1992). Wiig and Semel (1984) reported that students with LD also use meaningless phrases (e.g., that thingamajig) and overuse words lacking in specificity (e.g., stuff, thing). When attempting to retrieve a word, students with LD may substitute semantically related words (e.g., duck for goose) or phonemically related words (e.g., boat for boot) or use multiword substitutions related to function (e.g., you know, that woman who brings you drinks on the plane; German, 1994). Also, when attempting to remember a word list, students with LD may group words erratically, with no evidence of categorization, rather than semantically clustering the items (Israel, 1984). In all, these findings suggest the possibility of a weakened semantic network in students with LD.</p> <p>One way to directly examine the efficiency of semantic processing may be the use of electrophysiological measures. Event-related potentials (ERPs) have been used to investigate a range of lexical processing behaviors (Nigam, Hoffman, & Simons, 1992; Nobre & McCarthy, 1995; Polich & Donchin, 1988; Rubin, Newhoff, Peach, & Shapiro, 1996; Van Petten & Kutas, 1991). ERPs are brain-generated electrical events that are measured by surface electrodes placed on the scalp. These ERPs are “patterned voltage changes in the on-going electroencephalogram (EEG) that are time locked to sensory, motor, or cognitive events” (Hillyard & Picton, 1987, p. 520). In other words, windows (time-locked to an event) of EEG data are averaged, with the resulting waveforms revealing various stages of stimulus processing. Furthermore, these electrophysiological events may be particularly useful in measuring the processing of perceptual, cognitive, and linguistic events (Hillyard & Picton, 1987), including on-line sentence processing (Gunter, Jackson, & Mulder, 1992).</p> <p>Two late-occurring components of the ERP waveform, the P300 and the N400, are particularly useful when comparing cognitive processing across tasks. These waves are effective measures because of their robust amplitudes and the consistency of their elicitation patterns (Kutas & Van Petten, 1988). The P300 typically responds to surprises or sudden deviations in the ongoing presentation of stimuli; however, the N400 generally results from incongruencies in the context of the message (Hillyard & Picton, 1987).</p> <p>In 1980, Kutas and Hillyard measured ERPs in response to seven-word sentences presented one word at a time. The final words were semantically inappropriate to varying degrees (moderate and strong) or semantically appropriate. These researchers hypothesized that a P300 would appear when the terminal words were inappropriate (e.g., Kathy poured herself a glass of carpet). However, their findings showed a late negative component that appeared around 400 milliseconds following the presentation of the final word (N400). Furthermore, sentences with stronger incongruencies were associated with increased N400 negativity. Sentences that ended with a semantically appropriate word that was physically incongruous (e.g., The pen had blue INK) did not elicit an N400; rather, they elicited a P300. Later, researchers began attempting to elicit the N400 event in a variety of nonlinguistic contexts, including incongruous melody endings (Besson & Macar, 1987) and mental rotation of geometric figures (Stuss, Sarazin, Leech, & Picton, 1983), as well as in additional linguistic contexts such as word pair paradigms (Bentin, McCarthy, & Wood, 1985; Bentin, Kutas, & Hillyard, 1993; Holcomb, 1993; Holcomb & Neville, 1990). Throughout these investigations, N400 has only been elicited by linguistic stimuli in which semantic incongruencies existed. The consistency of N400 response elicitation has led to the suggestion that it reflects lexical processing.</p> <p>However, the N400 remains an event that may be discriminating relative to the stimulus. For example, Mitchell, Andrews, and Ward (1993) defined the N400 as a negative wave that peaks approximately 400 milliseconds following stimulus onset; however, the scalp distribution of the N400 appears to vary with the experimental task. This is an important concept in understanding the relation of N400 to lexical processing. If a word/sentence recognition or memorization task is used, the N400 will appear in a frontocentral distribution (Bentin et al., 1993; McCallum, Farmer, & Pocock, 1984; Stelmack & Miles, 1990). Alternatively, if a lexical decision task is used, the N400 appears maximally in a centroparietal distribution (Bentin et al., 1985; Besson & Macar, 1987; Kutas & Hillyard, 1980). Furthermore, the N400 has been found to occur during both auditory and visual tasks; however, auditorily presented stimuli produce a concomitant temporal distribution and increased amplitude (Holcomb & Neville, 1990; McCallum et al., 1984). There is also contradictory evidence regarding hemispheric activity. For example, whereas Holcomb and Neville (1990) and Besson and Macar (1987) concluded that visual tasks produce a slightly larger effect in the right hemisphere and auditory tasks produce larger N400s in the left hemisphere, others have reported that the N400 does not differ significantly between hemispheres (Bentin et al., 1993; McCallum et al., 1984).</p> <p>With earlier support for the N400 as a measure of cognitive processing in typical populations, Stelmack and Miles (1990) examined the differences in ERP components between children with and without reading disabilities in a picture priming task. In this experiment, a picture preceded a word having the same or a different meaning. The use of a picture reduced the N400 for both groups; however, the N400s in the reading disability group were lower in amplitude and absent in the parietal and occipital distributions. The N400 was present in the frontocentral areas for both groups. The authors suggested that the absence of N400 in the parietal areas for the reading disability group indicated deficits in long-term semantic memory (Stelmack & Miles, 1990). These results support the notion that reading disabilities (i.e., dyslexia) are not simply the result of a visual disturbance but are developmental language disorders (Catts, 1996). Furthermore, given the accepted language basis of most learning disabilities, it might be assumed that individuals previously diagnosed with either language impairment, dyslexia, or learning disabilities may at the very least share a common set of underlying etiological correlates.</p> <p>If this notion is accepted, there is a need for further investigation into the state of the semantic systems of individuals with LD. Furthermore, as reported earlier, the N400 has been demonstrated to be useful as a measure of semantic processing. The purpose of the present study was to identify potential differences in the semantic processing abilities of college students with and without learning disabilities. These differences were examined by assessing word finding using a standardized measure and by assessing semantic activation as reflected by N400 waveform patterns. Specifically, we were interested in whether semantic system deficits would be evidenced in the latency or amplitude of N400 in students with LD.</p> <hd id="AN0006626314-3">Method</hd> <hd1 id="AN0006626314-4"> Participants </hd1> <p>Twenty-two students participated in this study. Eleven were university undergraduates who had no history of learning disabilities (NLD group). The other 11 participants were undergraduates who had been diagnosed with learning disabilities (LD group) and were receiving services through the Learning Disabilities Center (LDC) at the University of Georgia.</p> <p>The LD group consisted of 5 boys and 6 girls who had been identified as having LD by the LDC using the definition established by the Interagency Committee on Learning Disabilities (ICLD; 1989). These participants ranged in age from 18 to 21 (M = 19.9, SD = 0.899) and had to meet the following requirements:</p> <olist> <item> hearing within average range (25 dB HL at 500, 1000, 2000, and 4000 Hz, bilaterally);</item> <item> right-hand dominance of > 80 as measured by a modified version of the Edinburgh Handedness Inventory (Oldfield, 1971);</item> <item> no history of head trauma, attention deficit, psychological impairment, drug or alcohol abuse, or any known neurological impairment;</item> <item> currently taking no medications that might affect neurological functioning; and</item> <item> receptive vocabulary within average range (M = 103.5455, SD = 3.679) as measured by the Peabody Picture Vocabulary Test-Revised (PPVT-R; Dunn & Dunn, 1981).</item> </olist> <p>IQs for the LD group (M = 104.72, SD = 5.74) were full scale scores from the Wechsler Adult Intelligence Scale (WAIS; Wechsler, 1981) or the Kaufman Adult Intelligence Test (KAIT; Kaufman & Kaufman, 1993).</p> <p>The NLD group members were matched to the LD group members by gender and age (within 1 year; range = 19–21, M = 20.6, SD = 0.979). Using the Test of Nonverbal Intelligence (TONI; Brown, Sherbenou, & Johnsen, 1982), the NLD group members were also matched by IQ to the LD group members within 7 points (M = 102.82, SD = 4.97). Although students with LD had current WAIS and KAIT scores, the TONI was selected as the intelligence measure for the control NLD group. The TONI has previously been shown to be a good measure of intelligence and to be valid across populations (Brown et al., 1982). Furthermore, all of the NLD group students scored within the average range on the PPVT-R (M = 107.09, SD = 2.612). See Table 1 for the results of all participant screening and matching measures.</p> <hd1 id="AN0006626314-5"> Procedure </hd1> <p>Testing occurred over two sessions in a quiet room free of distractions.</p> <p> <bold> Word Finding Assessment. </bold> During the first session, each participant signed a consent form and completed the questionnaire and standardized testing, including screening measures, and, to assess word finding abilities, the Test of Adolescent/Adult Word Finding (TAWF; German, 1990).</p> <p>The TAWF consists of five subtests and assesses word finding abilities in a variety of contexts, such as picture naming, sentence completion, naming to description, and naming for varying word classes and categories (German, 1990). The TAWF factors in variables such as word frequency, word category/ class, and response time and accuracy. On the whole, the TAWF provides a complete assessment of word finding ability (Snyder & Godley, 1992). In addition to normed standard scores and percentile ranks, the TAWF incorporates observational data to fully assess lexical access. Two of these measures are the number of delays and the number of verbalizations before responding. Delayed responses are those that occur 4 seconds or more following stimulus item administration during Subtest 1 (picture naming). Verbalizations (e.g., “uh, that's uh, let me think…”) are utterances that occur before the target response is spoken. NLD and LD group members were assessed using composite standard scores, number of delays, and number of verbalizations.</p> <p> <bold> Participant Preparation. </bold> The second session included electrophysiological testing. Initially, the participant was seated in a comfortable chair in a quiet testing room. An Electrode Cap International electrode cap system containing 21 electrodes was used for electrode placement. The participant began the experimental procedure once the electrode placement was established as valid through the use of impedance measures.</p> <p> <bold> Electrophysiological Tasks. </bold> Electrophysiological testing was modeled after McCallum et al. (1984). Because auditory tasks elicited the most robust waveforms in previous studies, participants completed an auditory task containing 435 sentences, spoken one word at a time at a very slow rate by a male voice. The room was darkened and participants were instructed to fixate on a point on the wall and to listen carefully to the sentences in anticipation of a recognition task. Nine breaks, given at varying intervals so the participants did not anticipate them, interrupted the task. The recognition task occurred during these breaks. The participants were shown a card with 4 sentences on it. The participants were asked if they recognized any of the sentences. Their responses were recorded, and the experiment continued when the participants indicated that they were ready.</p> <p> <bold> Auditory Stimuli. </bold> The sentence stimuli varied from six to eight words in length. A majority of the sentences came from a study by Fischler and Bloom (1980). Seventy-two (17%) of the sentences were semantically incongruous and 72 (17%) were physically incongruous (i.e., the last word of the sentence was read by a female voice). The other auditory stimuli (290 sentences, 66%) were semantically congruous. The semantically congruous sentences taken from Fischler and Bloom (1979) had a cloze probability greater than .50. The incongruous sentences had a cloze probability lower than .50, and the final word was replaced with an inappropriate one. Due to sentence length, low level of cloze probability, and other factors, a number of the normed Fischler and Bloom sentences could not be used. For this reason, we created the remaining 201 sentences. These sentences were normed using undergraduate classes. Of these created stimuli, only sentences with a cloze probability of .80 were used. The physically incongruous sentences were creating using the same criteria, except that the final word of the sentence was spoken by a female voice.</p> <p>The sentences were digitized and recorded on Track 1 of a Tascam PortaOne Mini Studio using SoundFX-Pro. They were presented binaurally to the participants through Telephonics TDH-39ZP stereo headphones at 70 dB HL.</p> <p> <bold> Instrumentation. </bold> Event-related potential (ERP) data were gathered using a Bio-Logic Brain Atlas electrodiagnostic testing system and a data sampling program (DSAMP). The Brain Atlas served as an amplification system for DSAMP that collected the ERPs used in data analysis. The sampling window for the Brain Atlas was 1,024 milliseconds. DSAMP had a sampling window set at 1,020 milliseconds. The Brain Atlas and DSAMP were triggered to sample either rare or standard events by the Event Organizer program (Kurki & Rossi, 1992) installed on an Amiga 500 computer. The Amiga 500 was triggered by a signal detector and pulse generator connected to the second-track output of a Tascam PortaOne Mini Studio. The tone that triggered the signal detector was at the point of the final word and was not audible to the participants.</p> <p>The electrodes were silver/silver chloride and the placement followed the international 10/20 system (Jasper, 1958) with linked ear reference and forehead ground. Impedance of all electrodes did not exceed 5.0 kΩ. Signals were filtered between .1 and 30 Hz and were amplified 20,000x. ERPs to each stimulus presentation were stored by DSAMP.</p> <hd1 id="AN0006626314-6"> Preparation of Data for Analysis </hd1> <p>Prior to data analysis, waveforms from semantically congruous and incongruous stimuli were processed using DSAMP. Responses to physically incongruous stimuli were held for analysis at a later time and were not analyzed for the present investigation.</p> <p>Movement artifacts were rejected off-line (samples beyond +/−70 microvolts were rejected as artifact). DSAMP was used to average and baseline-correct all participants' responses. Then, participants' N400 peak amplitudes and latencies were obtained with the DSAMP program. Peak N400 was identified as the highest negative value in the range of 300 ms to 650 ms post stimulus onset.</p> <hd id="AN0006626314-7">Results</hd> <hd1 id="AN0006626314-8"> Performance on the TA WF </hd1> <p>LD and NLD standard scores were analyzed using a two-directional dependent t test. A dependent sample of means yielded no significant difference in the overall word finding ability of students with learning disabilities (LD; M = 104.272, SD = 12.838) and controls (NLD; M = 111.636, SD = 17.884), t(<reflink idref="bib20" id="ref1">20</reflink>) = −1.1093, p > .05. See Table 2 for all participants' standard scores, number of delays, and number of verbalizations. The numbers of delays and verbalizations were also compared between groups using unidirectional dependent t tests. The LD group showed significantly more delays (M = 3.6, SD = 2.292) when compared to the NLD group (M = 1.6, SD = 2.378), t(<reflink idref="bib20" id="ref2">20</reflink>) = 2.0083, p < .05; however, verbalizations for each group were not significantly different, t(<reflink idref="bib20" id="ref3">20</reflink>) = 1.4972, p > .05.</p> <hd1 id="AN0006626314-9"> Electrophysiological Data </hd1> <p> <bold> N400 Amplitudes. </bold> Grand average waveforms comparing the two groups are presented in Figure 1. After obtaining the N400 peak amplitude for each participant, means and standard deviations were calculated for the NLD group (Fz, M = 8.536, SD = 4.272; Cz, M = 8.477, SD = 3.546; Pz, M = 6.502, SD = 3.179) and the LD group (Fz, M = 6.747, SD = 4.103; Cz, M = 6.139, SD = 4.916; Pz, M = 6.289, SD = 4.070) at each electrode site. Although the NLD group's N400 amplitudes were slightly larger than the LD group's (see Table 3), a series of one-way ANOVAs for the data from frontal, F(<reflink idref="bib1" id="ref4">1</reflink>, 20) = 0.91, p > .05, central, F(<reflink idref="bib1" id="ref5">1</reflink>, 20) = 1.49, p > .05, and parietal, F(<reflink idref="bib1" id="ref6">1</reflink>, 20) = 0.02, p > .05, placements revealed no significant differences between the groups. Peak amplitudes for both groups were the highest at Fz, then at Cz, and lowest at Pz. Thus, for both groups the N400 event appeared with a frontocentral distribution.</p> <p>Following these calculations, eta-squared, an effect size indicator, was used to analyze practical significance. Eta-squared supplies an effect size independent of sample size. A .14 level corresponds to a large effect, .06 to a medium effect, and .01 to a small effect (Cohen, 1977). These indicators are useful for identifying possible effects or practical significance when statistical significance may not have been reached (Stevens, 1990). The NLD and LD groups were compared at the Fz, Cz, and Pz electrode sites, and the effect sizes were as follows: Fz was small to medium (η² =.04), Cz was medium to large (η² = .07), and Pz was not of consequence (η² = .0009). These results suggest that if the number of participants were increased in both groups, then the LD group might have demonstrated a significantly lower amplitude than the NLD group at the frontal site, and an even greater difference might have appeared at the central site. Results for the parietal site, however, would likely have remained unchanged.</p> <p> <bold> N400 Latencies. </bold> Table 4 provides the means and standard deviations of N400 latency for each electrode site. ANOVAs conducted for the Fz (NLD, M = 503, SD = 50; LD, M = 540, SD = 61) and Cz (NLD, M = 475, SD = 61; LD, M = 470, SD = 63) electrode sites revealed no significant differences in the time of occurrence of the N400 peak; Fz, F(<reflink idref="bib1" id="ref7">1</reflink>, 20) = 0.91, p > .05; Cz, F(<reflink idref="bib1" id="ref8">1</reflink>, 20) = 1.49, p > .05. Latency at the parietal electrode was significant, F(<reflink idref="bib1" id="ref9">1</reflink>, 20) = 10.34, p < .05. The NLD group had a shorter latency (M = 413, SD = 87) than the LD group (M = 529, SD = 74).</p> <p>As with the amplitude data, an effect size indicator was applied to the N400 latency data. Latencies at the Fz and Pz sites produced effect sizes (Fz, η² = .10; Pz, η² = .34) that were medium to large and large, respectively. There was no effect apparent at the central site (η² = .002). This indicates that with a larger participant pool, frontal latency might possibly yield significant differences along with the parietal site.</p> <hd1 id="AN0006626314-10"> Comprehension Probe </hd1> <p>The comprehension levels during the recognition task were equal for both groups. A dependent t test indicated that the difference between the NLD (M = 3.272, SD = 1.555) and the LD (M = 5, SD = 2.366) groups in their ability to separate actual stimulus items from foils was not significant, t(<reflink idref="bib20" id="ref10">20</reflink>) = 2.0231, p > .05. These results suggest that the groups demonstrated equal effort during the task.</p> <hd id="AN0006626314-11">Discussion</hd> <p>The purpose of this study was twofold:</p> <olist> <item> to identify possible differences in the word finding abilities of college students with and without learning disabilities, and</item> <item> to assess possible differences between these groups in semantic processing as evidenced by ERP waveforms.</item> </olist> <p>Word finding abilities were assessed using a standardized measure (TAWF). Semantic processing was investigated using ERP waveforms that were analyzed for the presence of a negative peak occurring around 400 milliseconds (N400) in response to semantically incongruous sentences. The N400 waveform was measured by its amplitude and by its latency. In comparing the LD and NLD groups, the results of the statistical analyses demonstrated significantly more delays for the LD group on the TAWF, significantly longer N400 latency for the LD group at the Pz electrode site, and, although not statistically significant, a trend toward lower N400 amplitude at the Fz and Cz electrode sites for the LD group.</p> <hd1 id="AN0006626314-12"> Word Finding and Learning Disabilities </hd1> <p>Although the students with learning disabilities (LD) were equally accurate in their responses, it took them longer than students without LD to respond during the picture naming task. These results are not in agreement with the results of Rudel, Denckla, and Broman (1981). These authors examined word finding in children whom they classified as having dyslexia, learning disabilities without dyslexia, and no learning disabilities (control group). Their results showed that the accuracy of both the dyslexia and the LD without dyslexia groups was significantly lower than that of the control group; however, their response times were not. In fact, the group they identified as having learning disabilities without dyslexia responded more quickly than the controls. A possible explanation for these differences is that in Rudd et al.'s study, the receptive vocabulary score (based on the PPVT-R) of the control group was significantly higher than that of the dyslexia and LD without dyslexia groups. This could account for the accuracy differences because the children might not have comprehended the words. This vocabulary weakness would also indicate the presence of an oral language deficit in both experimental groups, at the very least in receptive vocabulary. This fact is difficult to align with a group of participants with LD being described as having no dyslexia, as it is generally assumed that there is a consonance between oral and written language deficits (Catts, 1996). Moreover, the presence of attention-deficit disorder (ADD) was not controlled for in Rudel et al.'s work, as it was in the present study. Perhaps the LD group with no dyslexia included at least some children with ADD. The fact that the participants with LD but without dyslexia responded faster than the controls, but with significantly less accuracy, might then be accounted for by their impulsivity. Regardless, in the present study, with controls exerted for ADD and language, participants with LD were accurate but delayed in their responses.</p> <p>The delayed responses of the LD group support the hypothesis of a deficit in word finding due to processing constraints. Although German (1990) stated that longer latencies are characteristic of word finding disorders, this characteristic has been attributed to a deficit in semantic processing rather than to a deficient semantic network (Stelmack & Miles, 1990). It would seem that when comprehension levels between groups are equal, the word retrieval skills of the LD group are equal in accuracy but unequal in speed of retrieval. Although the students with LD will eventually achieve the correct response, it will take them longer. This could account for the characteristic circumlocution, fillers, and pauses that are often apparent in the speech of persons with learning disabilities.</p> <p>Another aspect of the participants' performance in this study merits addressing. One of the reviewers of this article pointed out that a number of the LD group participants achieved higher scores on the PPVT-R than did their IQ-matched peers. The question was raised as to whether word finding might be considered independent of the factors on which the participants were matched. We would suggest that it is a matter not of independence but rather of differences. These participants were matched on “intelligence” in the broad sense. As a matter of fact, the four LD group participants who scored higher on the TAWF also demonstrated slightly higher IQ scores than their matched peers. It may be that even with a potential deficit in lexical access, greater cognitive capacity or effort resulted in greater success on the word finding task. This reasoning may be supported by the greater delay seen in the LD group (i.e., added effort resulting in greater time required).</p> <hd1 id="AN0006626314-13"> N400 Amplitude </hd1> <p>Visual inspection of the waveforms (see Figure 1) revealed that LD group participants had lower peaks (particularly at the Cz site) than the control group; however, these results were not found to be significant following statistical analysis. Eta-squared analyses suggested that an increase in the number of participants might yield statistically significant results. These findings were both consistent and inconsistent with Stelmack and Miles' (1990) N400 research where five children with dyslexia were compared to five of their typically achieving peers. The results of both studies were consistent in that the waveform distribution was frontocentral, but inconsistent in that in Stelmack and Miles' study, the N400 for the control group was greater in amplitude than the N400 of the dyslexia group in the frontocentral distribution and was absent at the Pz electrode.</p> <p>The first inconsistency may be addressed by the eta-squared analysis, which suggested that increasing the sample size would increase the differences in amplitude between the two groups to a significant level. If this suggestion were upheld with a larger sample size, frontal and central amplitudes might have been significantly reduced in the LD group when compared to the NLD group.</p> <p>The second inconsistency may be explained by the differences in the stimuli used in each study. Stelmack and Miles' (1990) study examined N400s in response to word pair paradigms and picture priming, whereas the present study investigated the N400 using sentences. Barton, Maruszewski, and Urrea (1969) described sentences as the most facilitative context for lexical access. If this is true, then it also would be true that sentences allow for quicker and more accurate entry into the semantic system. In a word pair paradigm, although the first word supplies the context, if followed by an unrelated word, it may not be sufficient to activate long-term semantic memory. In such a case, Stelmack and Miles stated, the semantic processing was incomplete, only activating frontal and central sites.</p> <p>In short, a word pair paradigm may not provide enough contextual constraint for a child with dyslexia to activate semantic memory, thus resulting in the absence of an N400 at parietal locations; however, a sentence context appears to create enough activity to unlock these semantic associations, and an N400 will appear to semantically incongruous sentences.</p> <p>As previously mentioned, a consistency between the present study and Stelmack and Miles' (1990) study was the frontocentral scalp distribution of the N400 across all groups. This N400 distribution, rather than a centroparietal one, is consistent with other experiments using a recognition memory task (Bentin et al., 1993; McCallum et al., 1984). The cause for these differing distributions is still a subject for further investigation (Bentin et al., 1993). One might hypothesize, however, that in order to perform the recognition memory task, short-term memory and attentional processing must be accessed at frontal sites. This frontal activation is required to process the semantically incongruous sentences for a recognition memory task. When the sentence is processed as incongruous in the long-term semantic memory of the parietal area, the meaning is also analyzed by the frontal cortex in short-term memory that recognizes the incongruency and consciously directs attention to the task (Stelmack & Miles, 1990). The resulting allocation of attention causes the frontal amplitude to be higher than that in parietal areas. This would further support Posner and Snyder's (1975a, 1975b) theory that lexical access is achieved by two different processes, one automatic and one attentional.</p> <p>In the automatic response, there is a spreading of activation, and the allocation of attention is not required. This activation generally occurs when the context of a stimulus is related to the response, requiring very little time to respond. It occurs regardless of strategy or expectancies. In contrast to the automatic response, the attentional response is slower and requires effort from the participant (Neely, 1977; Stanovich & West, 1979). When a word is unrelated to the previous context, the automatic response is inhibited due to attentional effort; a related word, however, is facilitated by the context and does not require attention. Holcomb (1988) reported that the N400 is sensitive to automatic spreading activation and to the additional allocation of attentional resources. The present study supports this theory, because the Fz site produced the highest amplitude.</p> <p>One might argue that this two-process theory may not be true because a number of the N400 distributions in other studies have been centroparietal and seemingly required none of the attentional processes discussed. The key seems to be that the majority of these tasks were lexical decision tasks or letter search tasks. Previous experiments did not require participants to process the sentence or the word pair paradigm at a deep level for later use. Generally, when a centroparietal distribution was elicited, the participants had completed that stimulus item and could move on to the next without storing it for retrieval. Thus, the N400 still formed through the automatic spreading activation process, but the attentional allocation was not needed, and the amplitude of the N400 was consequently reduced at the frontal site.</p> <hd1 id="AN0006626314-14"> N400 Latency </hd1> <p>Latencies were not statistically significant at the Fz and Cz sites; however, N400 at the Pz (parietal) site was significantly longer for the participants with LD when compared to the NLD group participants. This may be one of the more interesting results of this study. Parietal and temporal areas have been associated with long-term semantic memory (Stelmack & Miles, 1990). The present N400 latency data could not be compared to Stelmack and Miles' (1990) study of the N400 in children with dyslexia because they did not include any analysis of latency differences between groups. These N400 delays, however, may have some relationship to the delays on the TAWE as they both involve the processing of semantic material. A plausible conclusion could be that the LD group was unable to process the semantic information as efficiently as the controls. Moreover, these data are similar to the TAWF results in that the LD group participants were just as accurate in their comprehension of the sentences during the electrophysiological task as they were in the naming task of the TAWE This again reinforces the point that even when comprehension levels are equal, students with LD will have more difficulty performing lexical processing tasks than their age-matched peers without LD. Furthermore, these delays in parietal N400 latency were elicited by what has been proposed to be the easiest context for accessing lexical material. Rudel et al. (1980, 1981) stated that among lexical access tasks, sentence completion was easiest, picture naming was of intermediate difficulty, and naming to definition was the most difficult.</p> <p>Finally, the effect size indicator eta-squared suggested that the latency at the Fz electrode might become significant with an increase in the number of participants. If this is true, then, combined with the eta-squared amplitude data, it could be surmised that the LD group had difficulty activating long-term semantic memory and the attentional processes necessary to respond to incongruencies. Furthermore, once semantic memory is activated, these responses are delayed.</p> <hd id="AN0006626314-15">Conclusions</hd> <p>The findings of this study suggest that the semantic processing abilities of college students with learning disabilities are not as efficient as those of their peers. These abilities were significantly delayed on standardized and electrophysiological measures. The results also provide support for a relationship between word retrieval and sentence processing. This study provides further support for allowing extended time when assessing the academic abilities of a college student with learning disabilities. The LD group participants in this investigation maintained the same level of accuracy in their responses throughout the experimental procedures, yet they needed more time to do so. In an educational setting, then, it can be expected that testing sessions free of time constraints will more likely reflect the actual knowledge of the student with LD.</p> <hd id="AN0006626314-16">TABLE 1</hd> <p>Demographic Data and Intelligence Scores for Matched Participants With and Without Learning Disabilities</p> <ct id="AN0006626314-17"> Legend for Chart: A - Participant: LD B - Participant: NLD C - Gender D - Age: LD E - Age: NLD F - IQ[a]: LD G - IQ[a]: NLD H - PPVT-R: LD I - PPVT-R: NLD A B C D E F G H I 1 4 F 21 20 109 102 86 95 2 2 F 21 21 98 96 93 98 3 3 M 20 21 91 96 92 998 4 8 M 21 20 110 108 112 125 5 5 F 19 20 109 104 86 101 6 6 F 20 20 110 108 110 111 7 10 M 20 21 105 105 110 117 8 11 M 19 20 102 98 119 101 9 7 F 21 21 108 105 104 117 10 1 F 18 19 102 98 118 115 11 9 M 20 21 109 111 110 100 M — — 21 20 103 105 107 104</ct> <p>Note. LD = participant with learning disabilities; NLD = matched participant without learning disabilities; PPVT-R = Peabody Picture Vocabulary Test-Revised, standard scores. Means have been rounded.</p> <p>a IQ scores for participants with learning disabilities from the Wechsler Adult Intelligence Scale or the Kaufman Adult Intelligence Test. IQ scores for matched control participants from the Test of Nonverbal Intelligence.</p> <hd id="AN0006626314-18">TABLE 2</hd> <p>Word Finding Composite Standard Scores and Numbers of Delays and Verbalizations by Group</p> <ct id="AN0006626314-19"> Legend for Chart: A - Participant B - NLD group: z group C - NLD group: #D D - NLD group: #V E - LD group: z F - LD group: #D G - LD group: #V A B C D E F G 1 106 2 6 86 5 12 2 90 8 5 111 6 9 3 129 2 0 102 4 7 4 102 0 9 106 2 6 5 92 3 6 126 8 2 6 129 0 1 90 1 1 7 118 0 4 116 4 3 8 102 1 2 94 5 7 9 94 2 8 118 1 9 10 140 0 0 106 1 4 11 129 0 1 92 3 5 M 111.636 1.63 3.81 104.272 3.63 3.33</ct> <p>Note. See Table 1 for order of matched participants. NLD = individuals without learning disabilities; LD = individuals with learning disabilities; #D = number of delays; #V = number of verbalizations.</p> <hd id="AN0006626314-20">TABLE 3</hd> <p>N400 Amplitude Means and Standard Deviations by Groups and Electrode Sites</p> <ct id="AN0006626314-21"> Legend for Chart: A - Site B - NLD group: M C - NLD group: SD D - LD group: M E - LD group: SD F - F(1, 20) A B C D E F Fz 8.536 4.272 6.747 4.103 0.91 Cz 8.477 3.546 6.139 4.916 1.49 Pz 6.502 3.179 6.289 4.070 0.02</ct> <p>Note. Amplitudes in microvolts. All differences were nonsignificant. NLD = students without learning disabilities; LD = students with learning disabilities.</p> <hd id="AN0006626314-22">TABLE 4</hd> <p>N400 Latency Means and Standard Deviations by Groups and Electrode Sites</p> <ct id="AN0006626314-23"> Legend for Chart: A - Site B - NLD group: M C - NLD group: SD D - LD group: M E - LD group: SD F - F (1,20) A B C D E F Fz 503 50 540 61 2.25 Cz 475 61 470 63 0.04 Pz 413 87 529 74 10.34[a]</ct> <p>Note. Latencies in milliseconds. NLD = students without learning disabilities; LD = students with learning disabilities.</p> <p>a p < .05.</p> <p>GRAPH: FIGURE 1. Grand average event-related potential waveforms for participants without learning disabilities (NLD, thin line) and participants with learning disabilities (LD, thick line) at Fz, Cz, and Pz elecrode sites.</p> <ref id="AN0006626314-24"> <title> REFERENCES </title> <blist> <bibl id="bib1" idref="ref4" type="bt"></bibl> <bibtext>Barton, M., Maruszewski, M., & Urrea, D. (1969). Variation in stimulus context and its effect on word-finding ability in aphasics. Cortex, 5, 351–365.</bibtext> </blist> <blist> <bibl id="bib2" type="bt"></bibl> <bibtext>Bentin, S., McCarthy, G., & Wood, C. C. (1985). Event-related potentials, lexical decision, and semantic priming. Electroencephalography and Clinical Neuropsychology, 60, 343–355.</bibtext> </blist> <blist> <bibl id="bib3" type="bt"></bibl> <bibtext>Bentin, S., Kutas, M., & Hillyard, S. A. (1993). Electrophysiological evidence for task effects on semantic priming in auditory word processing. Psychophysiology, 30, 161–169.</bibtext> </blist> <blist> <bibl id="bib4" type="bt"></bibl> <bibtext>Besson, M., & Macar, F. (1987). An event-related potential analysis of incongruity in music and other non-linguistic contexts. Psychophysiology, 24, 15–25.</bibtext> </blist> <blist> <bibl id="bib5" type="bt"></bibl> <bibtext>Blalock, J. W. (1987). Auditory language disorders. In D. J. Johnson & J. W. Blalock (Eds.), Adults with learning disabilities (pp. 172–197). San Francisco: Grune & Stratton.</bibtext> </blist> <blist> <bibl id="bib6" type="bt"></bibl> <bibtext>Brown, L., Sherbenou, R. J., & Johnsen, S. (1982). Test of nonverbal intelligence. Austin, TX: PRO-ED.</bibtext> </blist> <blist> <bibl id="bib7" type="bt"></bibl> <bibtext>Candler, A. C., & Hildreth, B. L. (1990). Characteristics of language disorders in learning disabilities. Academic Therapy, 25, 333–343.</bibtext> </blist> <blist> <bibl id="bib8" type="bt"></bibl> <bibtext>Catts, M. (1996). Defining dyslexia as a developmental language disorder: An expanded view. Topics in Language Disorders, 16(2), 14–29.</bibtext> </blist> <blist> <bibl id="bib9" type="bt"></bibl> <bibtext>Cohen, J. (1977). Statistical power analysis for the behavioral sciences. New York: Academic Press.</bibtext> </blist> <blist> <bibl id="bib10" type="bt"></bibl> <bibtext>Connolly, J. E, Stewart, S. H., & Phillips, N. A. (1990). The effects of processing requirements on neurophysiological responses to spoken sentences. Brain and Language, 39, 302–318.</bibtext> </blist> <blist> <bibl id="bib11" type="bt"></bibl> <bibtext>Dobbs, A. R., Friedman, A., & Lloyd, J. (1985). Frequency effects in lexical decisions: A test of the verification model. Journal of Experimental Psychology: Human Perception and Performance, 11, 81–92.</bibtext> </blist> <blist> <bibl id="bib12" type="bt"></bibl> <bibtext>Dunn, L. M., & Dunn, L. M. (1981). Peabody picture vocabulary test-Revised. Circle Pines, MN: American Guidance Service.</bibtext> </blist> <blist> <bibl id="bib13" type="bt"></bibl> <bibtext>Ehren, B. J. (1994). New directions for meeting the academic needs of adolescents with Language learning disabilities. In G. P. Wallach & K. G. Butler (Eds.), Language learning disabilities in school-age children and adolescents (pp. 275–302). New York: Merrill.</bibtext> </blist> <blist> <bibl id="bib14" type="bt"></bibl> <bibtext>Fischler, I., & Bloom, P. A. (1979). Automatic and attentional processes in the effects of sentence context on word recognition. Journal of Verbal Learning and Verbal Behavior, 18, 1–20.</bibtext> </blist> <blist> <bibl id="bib15" type="bt"></bibl> <bibtext>German, D. J. (1990). National College of Education test of adolescent/adult word finding. Allen, TX: DLM Teaching Resources.</bibtext> </blist> <blist> <bibl id="bib16" type="bt"></bibl> <bibtext>German, D. J. (1994). Word finding difficulties in children and adolescents. In G. P. Wallach & K. G. Butler (Eds.), Language learning disabilities in school-age children and adolescents (pp. 130–178). New York: Merrill.</bibtext> </blist> <blist> <bibl id="bib17" type="bt"></bibl> <bibtext>Gunter, T. C., Jackson, J. L., & Mulder, G. (1992). An electrophysiological study of semantic processing in young and middle-aged academics. Psychophysiology, 29, 38–54.</bibtext> </blist> <blist> <bibl id="bib18" type="bt"></bibl> <bibtext>Harbiger, M. L. (1993). A qualitative investigation into the patterns and interactions of microlevel and macrolevel narrative competencies of college students who have learning disabilities. Unpublished doctoral dissertation, The University of Georgia, Athens.</bibtext> </blist> <blist> <bibl id="bib19" type="bt"></bibl> <bibtext>Hillyard, S. A., & Picton, T. W. (1987). Electrophysiology of cognition. In V. B. Mountcastle, E Blum, & S. R. Geiger (Eds.), Handbook of physiology, Section 1: The nervous system (pp. 519–538). Bethesda, MD: American Physiological Society.</bibtext> </blist> <blist> <bibl id="bib20" idref="ref1" type="bt"></bibl> <bibtext>Holcomb, P. J. (1988). Automatic and attentional processing: An event-related potential analysis of semantic priming. Brain and Language, 34, 66–85.</bibtext> </blist> <blist> <bibl id="bib21" type="bt"></bibl> <bibtext>Holcomb, P. J. (1993). Semantic priming and stimulus degradation: Implications for the role of N400 in language processing. Psychophysiology, 30, 47–61.</bibtext> </blist> <blist> <bibl id="bib22" type="bt"></bibl> <bibtext>Holcomb, P. J., & Neville, H. J. (1990). Auditory and visual semantic priming in lexical decision: A comparison using event-related brain potentials. Language and Cognitive Processes, 5, 281–312.</bibtext> </blist> <blist> <bibl id="bib23" type="bt"></bibl> <bibtext>Interagency Committee on Learning Disabilities. (1989). Learning disabilities: A report to the U. S. Congress. Bethesda, MD: National Institutes of Health.</bibtext> </blist> <blist> <bibl id="bib24" type="bt"></bibl> <bibtext>Israel, L. (1984). Word knowledge and word retrieval: Phonological and semantic strategies. In G. P. Wallach & K. G. Butler (Eds.), Language learning disabilities in school-age children and adolescents (pp. 230–250). New York: Merrill.</bibtext> </blist> <blist> <bibl id="bib25" type="bt"></bibl> <bibtext>Jarrow, J. (1987). Integration of individuals with learning disabilities in higher education: A review of the literature. Journal of Post-secondary Education, 5, 38–57.</bibtext> </blist> <blist> <bibl id="bib26" type="bt"></bibl> <bibtext>Jasper, H. H. (1958). The ten twenty electrode system of the international federation. Electroencephalography and Clinical Neurophysiology, 10, 371–375.</bibtext> </blist> <blist> <bibl id="bib27" type="bt"></bibl> <bibtext>Kaufman, A. S., & Kaufman, N. L. (1993). Kaufman adult intelligence test. Circle Pines, MN: American Guidance Service.</bibtext> </blist> <blist> <bibl id="bib28" type="bt"></bibl> <bibtext>Kurki, J., & Rossi, T. (1992). Event organizer [computer software]. Jyväskylä, Finland: Bits and Chips.</bibtext> </blist> <blist> <bibl id="bib29" type="bt"></bibl> <bibtext>Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruency. Science, 207, 203–205.</bibtext> </blist> <blist> <bibl id="bib30" type="bt"></bibl> <bibtext>Kutas, M., & Van Petten, C. (1988). Event-related potential studies of language. Advances in Psychophysiology, 3, 139–187.</bibtext> </blist> <blist> <bibl id="bib31" type="bt"></bibl> <bibtext>McCallum, W. S., Farmer, S. E, & Pocock, P. K. (1984). The effects of physical and semantic incongruencies on auditory event-related potentials. Electroencephalography and Clinical Neuropsychology, 59, 477–488.</bibtext> </blist> <blist> <bibl id="bib32" type="bt"></bibl> <bibtext>Mitchell P. F., Andrews, S., & Ward, P. B. (1993). An event-related potential study of semantic congruity and repetition in a sentence-reading task: Effects of context change. Psychophysiology, 30, 496–509.</bibtext> </blist> <blist> <bibl id="bib33" type="bt"></bibl> <bibtext>Morris, M., & Leuenberger, J. (1990). A report of cognitive, academic, and linguistic profiles for college students with and without learning disabilities. Journal of Learning Disabilities, 23, 355–360.</bibtext> </blist> <blist> <bibl id="bib34" type="bt"></bibl> <bibtext>Neely, J. H. (1977). Semantic priming and retrieval from lexical memory. Journal of Experimental Psychology, 106, 226–254.</bibtext> </blist> <blist> <bibl id="bib35" type="bt"></bibl> <bibtext>Nigam, A., Hoffman, J. E., & Simons, R. F. (1992). N400 to semantically anomalous pictures and words. Journal of Cognitive Neuroscience, 4, 15–22.</bibtext> </blist> <blist> <bibl id="bib36" type="bt"></bibl> <bibtext>Nippold, M. A. (1992). The nature of normal and disordered word-finding in children and adolescents. Topics in Language Disorders, 13(3), 1–14.</bibtext> </blist> <blist> <bibl id="bib37" type="bt"></bibl> <bibtext>Nobre, A. C., & McCarthy, G. (1995). Language-related field potentials in the anterior-medial temporal lobe II: Effects of word type and semantic priming. The Journal of Neuroscience, 15, 1090–1099.</bibtext> </blist> <blist> <bibl id="bib38" type="bt"></bibl> <bibtext>Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9, 97–113.</bibtext> </blist> <blist> <bibl id="bib39" type="bt"></bibl> <bibtext>Polich, J., & Donchin, E. (1988). P300 and the word frequency effect. Electroencephalography and Clinical Neurophysiology, 70, 33–45.</bibtext> </blist> <blist> <bibl id="bib40" type="bt"></bibl> <bibtext>Posner, M. I., & Snyder, C. R. (1975a). Attention and cognitive control. In R. L. Solso (Ed.), Information processing and cognition (pp. 376–400). Hillsdale, NJ: Erlbaum.</bibtext> </blist> <blist> <bibl id="bib41" type="bt"></bibl> <bibtext>Posner, M. I., & Snyder, C. R. (1975b). Facilitation and inhibition in the processing of signals. In p. A. Rabbit & S. Doric (Eds.), Attention and performance V (pp. 72–83). London: Academic Press.</bibtext> </blist> <blist> <bibl id="bib42" type="bt"></bibl> <bibtext>Rubin, S. S., Newhoff, M., Peach, R. K., & Shapiro, L. P. (1996). Electrophysiological indices of lexical processing: The effects of verb complexity and age. Journal of Speech and Hearing Research, 39, 1071–1080.</bibtext> </blist> <blist> <bibl id="bib43" type="bt"></bibl> <bibtext>Rudel, R. G., Denckla, M. B., & Broman, M. (1980). Word-finding as a function of stimulus context: Children compared to aphasic adults. Brain and Language, 6, 52–62.</bibtext> </blist> <blist> <bibl id="bib44" type="bt"></bibl> <bibtext>Rudel, R. G., Denckla, M. B., & Broman, M. (1981). The effect of varying stimulus context on word-finding ability: Dyslexia further differentiated from other learning disabilities. Brain and Language, 13, 130–140.</bibtext> </blist> <blist> <bibl id="bib45" type="bt"></bibl> <bibtext>Rugg, M. D. (1987). Dissociation of semantic priming, word and non-word repetition effects by event-related potentials. The Quarterly Journal of Experimental Psychology, 39, 123–148.</bibtext> </blist> <blist> <bibl id="bib46" type="bt"></bibl> <bibtext>Sheppard, W. D., & Boyer, R. W. (1990). Pre-trial EEG coherence as a predictor of semantic priming effects. Brain and Language, 39, 57–68.</bibtext> </blist> <blist> <bibl id="bib47" type="bt"></bibl> <bibtext>Snyder, L. S., & Godley, D. (1992). Assessment of word-finding disorders in children and adolescents. Topics in Language Disorders, 13(3), 15–32.</bibtext> </blist> <blist> <bibl id="bib48" type="bt"></bibl> <bibtext>Stanovich, K. E., & West, R. F. (1979). The generalizability of context effects on word recognition: A reconsideration of parafoveal priming and sentence context. Memory and Cognition, 7, 77–85.</bibtext> </blist> <blist> <bibl id="bib49" type="bt"></bibl> <bibtext>Stelmack, R. M., & Miles, J. (1990). The effects of picture priming on event-related potentials of normal and disabled readers during a word recognition memory task. Journal of Clinical and Experimental Psychology, 12, 887–903.</bibtext> </blist> <blist> <bibl id="bib50" type="bt"></bibl> <bibtext>Stevens, L. P. (1990). Intermediate statistics: A modern approach. Hillsdale, NJ: Erlbaum.</bibtext> </blist> <blist> <bibl id="bib51" type="bt"></bibl> <bibtext>Stuss, D. T., Sarazin, F. F., Leech, E. E., & Picton, T. W. (1983). Event-related potentials during naming and mental rotation. Electroencephalography and Clinical Neuropsychology, 56, 133–146.</bibtext> </blist> <blist> <bibl id="bib52" type="bt"></bibl> <bibtext>Van Petten, C., & Kutas, M. (1991). Influences of semantic and syntactic context on open— and closed-class words. Memory and Cognition, 19, 95–112.</bibtext> </blist> <blist> <bibl id="bib53" type="bt"></bibl> <bibtext>Wallach, G. P., & Liebergott, J. W. (1984). Who shall be called learning disabled: Some new directions. In G. P. Wallach & K. G. Butler (Eds.), Language learning disabilities in school-age children (pp. 21–36). Baltimore: Williams and Wilkins.</bibtext> </blist> <blist> <bibl id="bib54" type="bt"></bibl> <bibtext>Wechsler, D. (1981). Wechsler adult intelligence scale-Revised. San Antonio, TX: Psychological Corp.</bibtext> </blist> <blist> <bibl id="bib55" type="bt"></bibl> <bibtext>Wiig, E., & Semel, E. (1984). Language assessment and intervention for the learning disabled. Columbus, OH: Merrill.</bibtext> </blist> <blist> <bibl id="bib56" type="bt"></bibl> <bibtext>Zirkelbach, T., & Blakesley, K. (1985). The language deficient child in the classroom. Academic Therapy, 20, 605–613.</bibtext> </blist> </ref> <aug> <p>By Scott S. Rubin and Clinton M. Johnson</p> <p></p> <p>Scott S. Rubin earned his PhD in communication sciences and disorders at the University of Georgia in 1993 and is currently on faculty at The University of South Alabama. His research interest is the electrophysiological investigation of aging and language disorders.</p> <p>Clinton M. Johnson, MS, has been a speech-language pathologist for 6 years. He has experience working in home health, outpatient and inpatient pediatrics, and early intervention. He served as temporary faculty at the University of Georgia for 1 year and also worked at the University of Georgia Learning Disabilities Center assessing the oral and written language of college students. Presently, he is a marketing and product development specialist with Super Duper Publications®. Address: Scott S. Rubin, Department of Speech Pathology and Audiology, University of South Alabama, 2000 University Commons, Mobile, AL 36688-0002; e-mail: srubin@usouthal.edu</p> </aug>
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  Data: Lexical Access in College Students with Learning Disabilities: An Electrophysiological and Performance-Based Investigation.
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  Data: <searchLink fieldCode="AR" term="%22Rubin%2C+Scott+S%2E%22">Rubin, Scott S.</searchLink><br /><searchLink fieldCode="AR" term="%22Johnson%2C+Clinton+M%2E%22">Johnson, Clinton M.</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Learning+Disabilities%22"><i>Journal of Learning Disabilities</i></searchLink>. May-Jun 2002 35(3):257-267.
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  Data: <searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Disabilities%22">Learning Disabilities</searchLink><br /><searchLink fieldCode="DE" term="%22Neurological+Impairments%22">Neurological Impairments</searchLink><br /><searchLink fieldCode="DE" term="%22Reaction+Time%22">Reaction Time</searchLink><br /><searchLink fieldCode="DE" term="%22Recall+%28Psychology%29%22">Recall (Psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Semantics%22">Semantics</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Symptoms+%28Individual+Disorders%29%22">Symptoms (Individual Disorders)</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Young+Adults%22">Young Adults</searchLink>
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  Data: A study of the semantic processing abilities of undergraduates with learning disabilities (LD) (n=11) and controls (n=11) found no significant differences on the Test of Adolescent/Adult Word Finding; however, students with learning disabilities demonstrated a significantly greater number of delayed responses. Students with LD also showed delays on electrophysiological measures. (Contains references.) (Author/CR)
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  Group: ID
  Data: EJ647157
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ647157
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 257
    Subjects:
      – SubjectFull: Cognitive Processes
        Type: general
      – SubjectFull: Higher Education
        Type: general
      – SubjectFull: Learning Disabilities
        Type: general
      – SubjectFull: Neurological Impairments
        Type: general
      – SubjectFull: Reaction Time
        Type: general
      – SubjectFull: Recall (Psychology)
        Type: general
      – SubjectFull: Semantics
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
      – SubjectFull: Symptoms (Individual Disorders)
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Young Adults
        Type: general
    Titles:
      – TitleFull: Lexical Access in College Students with Learning Disabilities: An Electrophysiological and Performance-Based Investigation.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Rubin, Scott S.
      – PersonEntity:
          Name:
            NameFull: Johnson, Clinton M.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2002
          Identifiers:
            – Type: issn-print
              Value: 0022-2194
          Numbering:
            – Type: volume
              Value: 35
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Journal of Learning Disabilities
              Type: main
ResultId 1