How ‘generalized’ is the ‘slowed processing’ in SLI? The case of visuospatial attentional orienting

Neuropsychologia 42 (2004) 661–671

How ‘generalized’ is the ‘slowed processing’ in SLI? The case of visuospatial attentional orienting夽 Rina Schul a,∗ , Joan Stiles b , Beverly Wulfeck c , Jeanne Townsend d a

SDSU/UCSD Joint Doctoral Program in Clinical Psychology, Rina Schul, Department of Cognitive Science (Stiles Lab), University of California, San Diego, Gilman Drive, La Jolla, CA 92093-0515, USA b Department of Cognitive Science, University of California, San Diego, CA, USA c Department of Communicative Disorders, San Diego State University, San Diego, CA, USA d Department of Neurosciences, University of California, San Diego, CA, USA Received 5 April 2002; received in revised form 27 August 2003; accepted 7 October 2003

Abstract The study was designed to assess the speed and efficiency of visuospatial attentional orienting and the speed of visual processing and motor response in school-age children diagnosed with specific language impairment (SLI). Fifteen participants with SLI (7–15 years old) and their gender- and age-matched normally developing peers performed two formats of a simple visual discrimination task, one requiring the use of attentional orienting for accurate performance, and the other not requiring shifts of attention. The SLI group was characterized by (a) slower visual processing, and (b) slower motor response, but (c) similar attentional orienting speed, relative to the control group. The results are discussed in relation to the ‘generalized slowing hypothesis’ in SLI and the neural underpinning of visuospatial attentional orienting and SLI. © 2003 Elsevier Ltd. All rights reserved. Keywords: Specific language impairment; Visuospatial attention; Generalized slowing hypothesis

1. Introduction Children who display significant limitations in language abilities in the absence of accompanying hearing impairment, low nonverbal intelligence scores, social-emotional disorder or frank neurological damage are typically diagnosed with specific language impairment (SLI). The use of ‘specific’ implies that the areas of deficit are directly and exclusively related to language processes. However, careful scrutiny of the full array of behavioral observations in this population suggests that this is not the case. In addition to having significant weaknesses in syntax, morphology, semantics and phonology (Aram & Eisele, 1994; Leonard, 1998; Marchman, Wulfeck, & Weismer, 1999; Rapin, 1996; Reilly, Weckerly, & Wulfeck, in press), children with SLI present with a variety of perceptual, motor and cognitive processing problems that together share the common feature of performance slowness, or generalized slowness in processing. 夽 Project in Cognitive and Neural Development, University of California, San Diego. ∗ Corresponding author. Tel.: +1-858-822-0798; fax: +1-858-534-2344. E-mail address: [email protected] (R. Schul).

0028-3932/$ – see front matter © 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.neuropsychologia.2003.10.010

For instance, children with SLI have been shown to perform more slowly on perceptual tasks. They demonstrated poorer performance relative to matched controls when asked to detect, discriminate or sequence short (100 ms or shorter) tones, synthetic vowels, consonants, or vowel-consonant stimuli, or longer stimuli presented with short inter-stimulus intervals (ISIs). Their performance reached the level of controls’ when the same stimuli were presented for longer durations (200 ms or longer) or with longer ISIs, suggesting a deficit in their ability to process auditory stimuli only when these are presented rapidly (Lowe & Campbell, 1965; Tallal & Piercy, 1973a,b, 1974, 1975; Tallal, Stark, & Mellits, 1985; Wright, Bowen, & Zecker, 2000). This characteristic was also demonstrated in other modalities, suggesting a more generalized processing deficit in SLI. For example, children with SLI performed poorly on tasks of visual discrimination of simple forms presented rapidly (Tallal, Stark, Kallman, & Mellits, 1981), and on tasks requiring discrimination of tactile stimuli presented with short, but not long, ISIs (Tallal et al., 1985). Language impaired children have also demonstrated motor slowness on a variety of tasks (Hill, 2001), including finger tapping (Hughes & Sussman, 1983; Preis, Schittler, & Lenard, 1997), finger opposition (Katz, Curtiss, &

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Tallal, 1992), peg-moving (Bishop & Edmundson, 1987; Owen & McKinlay, 1997; Preis et al., 1997), ball-rolling with the foot and clapping-and-catching (Powell & Bishop, 1992), bead-threading (Owen & McKinlay, 1997; Powell & Bishop, 1992), pantomiming the functional use of objects, and uttering single and multiple syllables (Katz et al., 1992). A positive relationship between the severity of the language impairment and the degree of motor slowing has also been demonstrated (Bishop & Edmundson, 1987; Katz et al., 1992; Schwartz & Regan, 1996). Slowness of processing in SLI has also been demonstrated on tasks of ‘higher cognition’ (i.e. tasks that are not purely perceptual or motor). For instance, language impaired children searched visual arrays of simple nonsense figures more slowly than children with normal language (Miller, Kail, Leonard, & Tomblin, 2001), and also were slower on a task requiring mental rotation of simple geometric figures (Johnston & Weismer, 1983; Miller et al., 2001). Since in both tasks, speed was measured via a manual strike on a response key, one could claim that the observed slowness could be attributed to motor slowness per se. However, the SLI group was not slow on a simple task requiring a key strike in response to a visual signal (Miller et al., 2001). This suggests that their slowness on the search and imagery tasks was not merely perceptual or motor. Finally, SLI children scanned auditory items held in short term memory almost four times slower than their linguistically normal peers (Sininger, Klatzky, & Kirchner, 1989). Their speed of processing on this task was assessed using ‘yes’/’no’ rather than manual responses. A number of investigators have attempted to estimate the degree to which children with SLI are slower than age-matched controls across a variety of tasks (Kail, 1994; Miller et al., 2001; Windsor & Hwang, 1999). Specifically, they examined the reaction time data of children with and without SLI in a large number of different tasks that varied in their complexity and their linguistic demands. They found that when all tasks were considered, the response speed of children with SLI could be described as a linear function of the response speed of their matched peers, with a slope ranging between 1.10 and 1.32. A slope of 1.00 would mean that children with and without SLI have overall equivalent performance speeds. Based on the calculated slopes, the authors suggested that children with SLI perform 10–30% more slowly than their matched peers and that this performance difference reflects some general, non-task specific, component of their cognitive processing. One neurocognitive domain that has received relatively little exploration in relation to SLI is ‘attentional orienting’; this is in spite of the possibility that this operation, as well, might be adversely affected by generalized slowed processing in SLI. Visuospatial attentional orienting has been described as a mental ‘spotlight’ moving in space in response to the occurrence of an attentional cue (Posner, 1980). The covert movement of attention, independently of the overt movement of the eyes, takes place in the order of a few

tens of milliseconds. After approximately 200 ms, overt orienting (a saccade) may follow the covert orienting (Groner & Groner, 1989). The efficiency of visuospatial attentional orienting has been shown to improve with age (Akhtar & Enns, 1989; Enns & Brodeur, 1989; Nougier, Azemar, Stein, & Ripoll, 1992; Pearson & Lane, 1990; Schul, Townsend, & Stiles, 2003). The speed of attentional orienting has been shown to systematically increase throughout the school-age years and reach adult levels around the end of adolescence (Pearson & Lane, 1990; Schul et al., 2003). Since covert attentional orienting relies on relatively brief neurocognitive operations, it seems likely to be affected in children with SLI due to their generalized slowed processing. Studies examining attentional functioning in children with SLI are rare and the evidence is scarce. Mackworth, Grandstaff, and Pribram (1973) studied a group of 10 children characterized by a wide variety of language handicaps with varying degree of impairment in speech comprehension. They reported that those with relatively mild language impairment, who also had low non-verbal IQs (suggestive of mild retardation), were slow to notice a change in the color properties of a stimulus, and once noticing the change, tended to look away from the display. In contrast, those with severe language impairment and higher non-verbal IQs immediately oriented to the stimulus and remained glued to it for longer periods than matched controls. These observations have been interpreted as reflecting impaired attentional orienting and increased habituation to a new stimulus in association with mild language impairment. However, given the low non-verbal IQs in the mild language impaired group and the opposite behavioral pattern in the severe language impaired group, relating the attentional problems to the degree of language impairment seems rather speculative. In another study, Nichols, Townsend, and Wulfeck (1995) assessed the performance of children with SLI on a cost-benefit cueing attentional task with either central or peripheral cues. They found slower reaction time for SLI children relative to normal controls across all task conditions, which was consistent with the generalized slowing hypothesis in SLI; however, since reaction time was the only outcome measure used, it is unclear whether the reported slowing represented motor slowing per se, slowing due to attentional functioning, or both. Finally, Tallal, Townsend, Curtiss, and Wulfeck (1991) compared SLI children with positive family history for SLI to SLI children with negative family histories with respect to their scores on different scales of the Achenbach Child Behavioral Checklist (Achenbach & Edlebrock, 1983). They reported that children with positive family histories were rated by their parents as more “Hyperactive” and by their teachers as more “Inattentive” than language impaired children with negative family history. They further noted that the “Hyperactive” and “Inattentive” scales had considerable item overlap with the higher loading common items relating to the areas of sustained attention and concentration (e.g. cannot concentrate, daydreams, inattentive,

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confused). Based on the observation of higher prevalence of attention-related behavioral problems in SLI children with positive family histories for SLI, the authors proposed that these attentional deficits might be genetically linked to SLI. Interestingly, attention deficit-hyperactivity disorder (ADHD) is by far the most common psychiatric diagnosis reported to be associated with language disorders, accounting for approximately two-thirds of the psychiatric disorders reported (Baker & Cantwell, 1982; Tallal, 1980). Moreover, a comparison of the performance on a battery of neuropsychological tests of children with SLI alone, ADHD alone, and SLI + ADHD revealed that SLI and ADHD are associated with different deficits, respectively, and that the severity of these deficits is additive when the two disorders co-occur in the same individual (Williams, Stott, Goodyer, & Sahakian, 2000). Given these observations, it is possible that the “inattention” problems reported for children with SLI in Tallal’s study represented a subset of the SLI group with comorbid ADHD. Attentional processing has been more systematically discussed with regard to a disorder closely related to SLI, namely developmental dyslexia. It has been suggested that as in SLI, individuals with dyslexia have difficulties processing rapid stimulus sequences (Laasonen, Tomma-Halme, Lahti-Nuuttila, Service, & Virsu, 2000; Laasonen, Service, & Virsu, 2001; Laasonen, Lahti-Nuuttila, & Virsu, 2002; Reed, 1989; Tallal, 1980). Moreover, these difficulties have been proposed to be secondary to a more fundamental attentional deficit in this population that reflects a weakened parietal-lobe-supported attentional capture, which affects all sensory modalities (Hari & Renvall, 2001). Attentional deficits observed in dyslexic individuals cited in support of this hypothesis include a right-hemifield advantage in speeded detection of visual stimuli (referred to as ‘a left-sided mini-neglect’; Hari, Renvall, & Tanskanen, 2001), a prolonged attentional blink interval (referred to as ‘a prolonged attentional dwell time’; Hari, Valta, & Uutela, 1999), and lack of attention gradient effect bilaterally or in the right hemifield (referred to as ‘diffused and asymmetrical distribution of attentional resources’; Facoetti & Molteni, 2001; Facoetti, Paganoni, & Lorusso, 2000). Hari and Renvall (2001) labeled the hypothesized underlying deficit—‘Sluggish Attentional Shifting’. While their main focus was on dyslexia, they noted that this mechanism also might account for the observed slowed auditory processing in SLI. The present study was designed to address the hypothesis that visuospatial attentional orienting would be slowed in school-age children diagnosed with SLI relative to their non-language impaired peers. The speed of attentional orienting was assessed in conjunction with the assessment of the speed of visual processing and the speed of motor response in the same groups of children. Toward that end, we used two formats of a simple visual discrimination task, one requiring the use of attentional orienting for accurate performance (the SHIFT task), and the other not requiring

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shifts of attention (the FOCUSED task). In the Focused task, participants were presented with a visual target that was immediately masked, and their task was to indicate the orientation of the target (up, down, left, right) via a manual response. The mask was used to limit the amount of time available for sensory and perceptual processing. By varying the target-to-mask interval, we were able to assess the amount of processing time required for accurate visual discrimination. The long (2 s) response interval allowed even slow-responders to execute a response. We recorded the response time within this interval, thus estimating the speed of motor response when the sensory/perceptual time window was held constant. The Shift task followed the same format except that the target was presented in one of two locations, preceded by a location (attention) cue, which was valid (80%) or invalid (20%). Target discrimination depended on efficient use of attentional orienting in response to the presentation of the attention cue. By holding the perceptual time window constant and varying the cue-to-target interval, we were able to assess the speed of attentional orienting necessary for accurate performance on this task. These tasks have been successfully used with different populations, including normal, autistic, and brain damaged children and adults (Schul et al., 2003; Townsend et al., 1999; Townsend, Harris, & Courchesne, 1996). We hypothesized that children with SLI would exhibit less efficient attentional orienting relative to age-matched controls due to slowed attentional orienting. Accordingly, their performance on the attention task would improve with longer cue-to-target intervals, which would allow them more time to shift their attention. We also hypothesized that SLI children would exhibit slowed visual processing and slowed motor responses consistent with the literature. Their performance in the visual domain might reach that of matched controls when given more time to process the stimulus.

2. Methods 2.1. Participants Fifteen children (11 males; 4 females) diagnosed with specific language impairment (SLI) participated in the study. They were recruited through speech-language pathologists, psychologists and physicians from the local community, and had documented language impairment. All participants met the following criteria for SLI: (1) expressive and/or receptive language scores or composite 1.5 or more standard deviations below the mean; (2) performance IQ of 80 or higher; (3) no major neurologic abnormalities; (4) hearing and corrected vision within normal limits; (5) absence of known developmental disorders such as mental retardation or autism. All SLI children participated in a larger neurodevelopmental study on language and cognition. See Table 1 for more information on the SLI group.

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Table 1 Characteristics of the SLI group Characteristic

Mean

Standard deviation

Range

Age Full scale IQ Performance IQ Verbal IQ CELF—expressive score CELF—receptive score

10.7 92.4 100.9 86.2 65.6 80.4

2.4 11.3 10.5 15.3 7.7 13.1

7.3–15.4 70.0–109.0 80.0–115.0 54.0–113.0 50.0–76.0 63.0–103.0

Table 2 Comparison of SLI group to TD group Variable

SLI

TD

Total N Number of males Mean age Median age Standard deviation of age Age range

15 11 10.7 10.3 2.4 7.3–15.4

90 66 10.8 10.4 2.4 7.1–15.7

Each participant with SLI was matched to six typically developing (TD) children of the same gender, whose age was within ±1 year of the age of the target SLI participant. These children were randomly sampled from a larger pool of typically developing children, recruited from a number of public schools in San Diego (Schul et al., 2003); according to teachers’ report, they did not have any obvious learning or language disabilities. IQ or language data were not available for the TD group.1 See Table 2 for comparison of the SLI and TD groups. 2.2. Procedure Participants were individually tested in a separate room. Each participant performed two tasks of visual discrimination. The first task—the FOCUSED task—was designed to assess the speed of visual processing. The second task—the SHIFT task—was designed to test visual discrimination with and without attention (based on Schul et al., 2003; Townsend et al., 1996, 1999). In the Focused task, participants were seated 55 cm in front of a 36-cm monitor. The basic display was a central fixation point marked by a white cross on a dark background, and flanked on the right and the left at 8.3◦ of visual angle by two 4-cm2 green boxes (see Fig. 1). The task included two blocks of 80 trials. In the first block, each trial started

with the box on the left side brightening up (‘cue’), followed 500 ms later by the presentation of the target stimulus in that box (‘target’). The target was a block figure “E” that could be oriented in one of four directions (i.e. up, down, left, right). The target was masked after 50, 100, 250, 500 or 1000 ms by a figure that included all possible features of the target in any orientation (‘mask’). The participant’s task was to move a joystick in the direction that the target was pointing (i.e. up, down, left, right). The masked target was displayed until the participant responded, or for a maximum of 2000 ms duration. Any response shorter than 200 ms or longer than 2000 ms was counted as a ‘miss’. The inter-trial interval was randomly distributed between 500 and 2000 ms. Participants received a short break after completing the first block. The second block was identical to the first one, except that the cue and the target were presented on the right side. Prior to testing, participants received 20 practice trials that simulated the actual task. The basic procedure for the Shift task was the same as the Focused task, with the following exceptions: The Shift task included three blocks of 128 trials, with breaks between them. Participants were instructed to focus on the central fixation point. Each trial began with the brightening of either the right or left box (the ‘cue’). After a cue-to-target delay of 100 or 800 ms, the target was presented either in the cued location (“valid trials”; 80%) or in the uncued location (“invalid trials”; 20%). Target-to-mask interval was 50 or 100 ms. See Fig. 1 for summary of the two tasks. Total testing time was 30–45 min, with task 1 taking about a third of this time. Participants received small prizes during task breaks to increase their motivation. In some cases, younger participants reported fatigue, and the task was paused and then resumed after a short rest. 2.3. Standardized tests The SLI participants were also administered the following standardized tests: (1) Wechsler intelligence scale for children—revised (WISC-R; Wechsler, 1974) or Wechsler intelligence scale for children—Third edition (WISC-3; Wechsler, 1991); (2) clinical evaluation of language fundamentals—revised (CELF-R; Semel, Wiig, & Secord, 1987). The tests were administered within ±1 year from the administration time of the Focused and Shift tasks for 13 participants and within 2 years for additional two participants. 2.4. Analysis of data

1

We cannot rule out the possibility that the TD group included some children with SLI undetected by their teachers. Large epidemiological studies suggest that the prevalence of SLI during the early school years is approximately 7% (e.g. Leonard, 1998). It is therefore highly likely that the majority of the TD group (e.g. 90% or more) did not have SLI and was representative of the normal population. Moreover, we took extra precaution by matching a large group of controls to the SLI sample (i.e. there were six times as many TD participants as SLI participants) in order to ‘wash out’ any possible deviations from normality.

Two outcome measures, performance accuracy and reaction time (RT), were taken in the Focused and Shift tasks. Percent response accuracy was computed for each participant in each experimental condition, and then averaged within each group. Correct responses were those that were both correct and within the time frame allowed for response (200–2000 ms). For the RT measure, median response time

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Fig. 1. Schematic summary of the Focused task and the Shift task employed in this study.

was computed for each participant in each experimental condition for correct responses only, and then averaged within each group. Accuracy and RT data were separately analyzed. For the Focused Task, 2 × 5 repeated measures analysis of covariance (ANCOVA) was performed with GROUP as a between subject factor (SLI, TD) and TARGET-MASK INTERVAL (T-M) as the within subject factor (50, 100, 250, 500, 1000 ms). Since AGE was shown to affect the performance on the Focused task (Schul et al., 2003), it was included as a covariate. α < 0.05 was considered significant. When appropriate, follow-up tests were performed to assess group differences in each T-M level: five one-way ANCOVAs were carried out with GROUP as a between subject factor and AGE as a covariate. α level was adjusted to 0.01, using Bonferroni correction. For the Shift Task, 2 × 2 × 2 × 2 repeated measures ANCOVA was carried out with GROUP (LI, TD) as the between subject factor, and VALIDITY (valid, invalid), CUE-TARGET INTERVAL (C-T; 100, 800 ms) and TARGET-MASK INTERVAL (T-M; 50, 100 ms) as the within subject factors. AGE was shown to affect the performance on the Shift task (Schul et al., 2003), and was therefore used as a covariate. 2.5. Speed indices Three performance indices representing ‘perceptual processing speed’, ‘motor speed’ and ‘attentional orienting speed’ were extracted from the data of the Focused and Shift tasks. Standardized scores (z scores) were computed using means and standard deviations of these indices as calculated in gender- and age-matched groups of typically developing children (n = 20 in each group).2 2 For the z scores, we used data of normally developing participants, as described in the normative study preceding this study (Schul et al., 2003). We used large groups from the normative study (rather than n = 6) in order to establish stable z scores.

1. Perceptual processing speed: Based on the literature (e.g. Tallal & Piercy, 1973a,b, 1974, 1975), we expected that slowed visual processing in SLI individuals might take the form of poorer performance relative to the TD group on the Focused task with short T-M intervals but not (or not to the same extent) with the longer T-M intervals. We thus expressed in z scores the difference between performance accuracy with T-M 50 ms on the one hand and the average of performance accuracies with T-M 100, 250, 500, and 1000 ms intervals on the other. Lower (e.g. more negative) z scores on this index represented slower visual processing speed. 2. Motor speed: RT was averaged across all T-M conditions of the Focused task for each SLI individual and converted to z scores. Lower scores on this index represented slower motor speed. 3. Attentional orienting speed: A ‘validity score’ (performance accuracy on valid trials minus performance accuracy on invalid trials) was separately calculated for each C-T interval (100 and 800 ms) for the T-M 50 ms condition of the Shift task. A typical performance profile for school-age children is characterized by larger validity score for the longer C-T condition than for the shorter one, reflecting more efficient use of attentional mechanisms when more time is available for attentional orienting (Pearson & Lane, 1990; Schul et al., 2003). This difference between performances on long versus short C-T intervals diminishes with age (Schul et al., 2003), reflecting age-related increase in the speed of attentional orienting. Accordingly, in our study, a relatively large difference in validity scores between the C-T 800 and C-T 100 ms conditions (as expressed in z scores) was considered to represent relatively slower speed of attentional orienting in SLI individuals. Using the SLI data, each index was compared to a test value of 0, and was correlated with the other indices and with AGE.

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Reaction time (Fig. 2b): Similar main effects for GROUP (SLI: 779 ms, TD: 700 ms; F(1,192) = 4.9; P < 0.03) and T-M INTERVAL (T-M 50: 798 ms, T-M 100: 769 ms, T-M 250: 730 ms, T-M 500: 704 ms, T-M 1000: 696 ms; F(4,99) = 7.4; P < 0.000) were obtained with the RT measure, however, the GROUP by T-M INTERVAL interaction was not significant. 3.2. Shift task

Fig. 2. (a) Performance accuracy and (b) reaction time of the SLI and TD groups on the Focused task (mean, S.E.M.).

3. Results 3.1. Focused task Performance accuracy (Fig. 2a): Analysis revealed significant main effects for GROUP (SLI: 87%, TD: 93%; F(1,102) = 11.0; P < 0.001) and for T-M INTERVAL (T-M 50: 82%, T-M 100: 90%, T-M 250: 93%, T-M 500: 93%, T-M 1000: 92%; F(4,99) = 6.4; P < 0.000). These main effects were qualified by a significant GROUP by T-M interaction (F(4,99) = 4.4; P < 0.002). Follow up tests revealed that the TD group had significantly higher performance accuracy for the T-M 50, T-M 250, and T-M 500 intervals (α < 0.01). Further exploration of the actual group differences revealed that the largest group difference occurred with T-M 50 ms ( = 14%), followed by similar difference for T-M 100, T-M 250, and T-M 500 ms ( = 6, 7, and 6%, respectively), and almost no difference for the T-M 1000 ms condition ( = 0.6%).

Performance accuracy (Fig. 3a and b): Significant main effects were detected for GROUP (SLI: 62%, TD: 71%; F(1,102) = 9.5; P < 0.003), VALIDITY (valid: 76%, invalid: 57%; F(1,102) = 58.6; P < 0.000), and C-T INTERVAL (C-T 100: 64%, C-T 800: 69%; F(1,102) = 8.1; P < 0.005). These effects were qualified by a significant VALIDITY by C-T INTERVAL interaction: (F(1,102) = 55.2; P < 0.000), which was characterized by a larger difference between valid and invalid trials (i.e. ‘validity effect’) with the 800 ms C-T interval ( = 27%) than with the 100 ms C-T interval ( = 11%). Additional analyses demonstrated that the validity effect (better performance for valid than for invalid trials) was significant for both groups at the 100 ms C-T interval during which overt orienting is not possible (F(1,103) = 27.25; P < 0.0001), and that there was no significant difference between groups in this advantage (F(1,103) = 0.53; P > 0.46). Reaction time (Fig. 3c and d): A significant main effect was observed for the VALIDITY factor (valid: 768 ms, invalid: 926 ms; F(1,102) = 47.2; P < 0.000). Additionally, a significant C-T INTERVAL by VALIDITY interaction was observed (F(1,102) = 27.4; P < 0.000), which was characterized by a larger difference between valid and invalid trials on C-T 800 ms ( = 210 ms) than on C-T 100 ms ( = 106 ms). The T-M INTERVAL by GROUP interaction was also significant (F(1,102) = 4.7; P < 0.03), suggesting a larger improvement in RT for the TD group ( = 40 ms) than for the SLI group (∆ = 8 ms) when comparing performance with T-M 50 ms to that with T-M 100 ms. The GROUP effect was not significant. Speed indices and correlations: Table 3 presents means, standard deviations and range values for the speed indices. Consistent with the results reported above, analysis of speed indices demonstrated significantly slower visual processing (t14 = −3.5; P < 0.003), and motor speed (t14 = −2.6; P < 0.02) in SLI children, but normal speed of attentional orienting. There were no significant correlations among the speed indices or between the speed indices and AGE, using α level of 0.05 or 0.1. Table 3 Speed indices of the SLI group (z scores) Index/score

Mean

Standard deviation

Range

Visual processing speed Motor speed Attentional orienting speed

−1.1 −0.6 −0.3

1.2 0.9 1.2

[−3.4]–[+1.0] [−2.4]–[+0.8] [−1.7]–[+2.7]

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Fig. 3. Performance accuracy (a and b) and reaction time (c and d) of the SLI and TD groups on the Shift task (mean, S.E.M.). ‘C-T 100’ is cue-to-target interval of 100 ms. ‘C-T 800’ is cue-to-target interval of 800 ms. Target-to-mask intervals are 50 ms (a and c) and 100 ms (b and d). ‘Valid’ is valid trials; ‘invalid’ is invalid trials. Both the SLI and TD groups demonstrate validity effects (difference between performance on valid and invalid trials) on all cue-to-target and target-to-mask conditions.

4. Discussion This study was designed to assess the efficiency of visuospatial attentional orienting in a sample of school-age children diagnosed with SLI. This was done in conjunction with the assessment of the rate of motor response and the accuracy of visual discrimination under conditions that varied in the demand for speeded processing. Our results point to a dissociation between attentional processing on the one hand and visual and motor processing on the other in SLI. Children with SLI showed slow visual processing and slow motor response relative to non-language impaired matched controls but did not differ from their matched peers in the speed of visuospatial attentional orienting or the use of attentional cues. To our knowledge, this is the first demonstration of such a dissociation in a systematic study of visuospatial attentional orienting in SLI.

We used two versions of a simple visual discrimination task to assess our constructs of interest, speed of perceptual processing, motor response and attentional orienting. In the Focused task, participants were required to indicate via a manual response the direction of a figure that was visually displayed for an interval that ranged between 50 and 1000 ms and then masked. Our SLI group was 14% less accurate than their matched controls when the time allowed for visual processing was 50 ms. Their performance accuracy approached that of controls (performance difference ∼6%) when 100, 250 or 500 ms were allowed for visual processing, and it was essentially indistinguishable from that of controls with a 1000 ms interval. This performance profile suggests that the SLI sample had specific difficulty in visual processing with short processing intervals but not with longer ones. This is consistent with previous reports of difficulties of SLI children on tasks of discrimination of discrete

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auditory stimuli presented for short durations (to distinguish from presentation of multiple stimuli with short ISIs), for instance, discrimination of short tones or short phonemes (Tallal & Piercy, 1973a,b, 1974, 1975; Tallal et al., 1985). Likewise, our results are supportive of the hypothesis of generalized slowed processing in SLI (reviewed in Tallal, Miller, & Fitch, 1993; Tallal, Sainburg, & Jernigan, 1991). Our SLI sample also demonstrated a consistent pattern of slowed motor response on the Focused task across all target-to-mask conditions. The degree of motor slowing was approximately 10% of that expected based on the motor speed of matched controls, which is consistent with the degree of general slowing in SLI estimated by Miller, Kail, Leonard, and Tomblin (2001) and Windsor and Hwang (1999). The difference in RT between the SLI and TD groups did not interact with the length of the time allowed for visual processing, suggesting that this group effect was due to motor slowing per se rather than to a combination of motor and perceptual slowing. These observations are consistent with previous reports of motor slowing in SLI as demonstrated on a large number of different tasks (reviewed in Hill, 2001). The SLI group also demonstrated slower motor responses than the TD group on the Shift attention task; this group difference (of approximately 2%), however, was not statistically significant. This resulted from a larger drop in RT in the TD group than in the SLI group for the Focused versus Shift tasks (TD: 700 versus 840 ms; SLI: 779 versus 853 ms). Considering both tasks, then, it appears that the SLI group was near ‘floor-level’ performance in RT (maximal slowing) in the Focused task, therefore, needing to slow down only a little more on the harder attention task. In contrast, the TD group, who was likely at ‘ceiling’ on the Focused task, exhibited relatively more slowing on the harder attention task, as a consequence rendering the group difference in RT on the Shift task non-significant. The primary use of the Shift task was to assess the speed and efficiency of attentional orienting in SLI. Our results suggest that SLI children use their attentional orienting mechanisms similarly to TD children both qualitatively and quantitatively, as follows. Our task was patterned after Posner’s cost-benefit paradigm (Posner, 1980) and it yielded compatible results. Thus, accuracy of performance was overall higher and reaction time was overall faster on valid than on invalid trials, demonstrating the benefits associated with attentional orienting and the costs associated with misdirection of attention (Posner & Cohen, 1984). Moreover, the effect of cue validity significantly interacted with the effect of the cue-to-target parameter, reflecting a larger validity effect (valid minus invalid) with longer than with shorter cue-to-target intervals. Similar observations were reported by Pearson and Lane (1990) and Schul et al. (2003), and are consistent with the idea that school-age children, in contrast to adults, cannot complete an attention shift within a 100 ms interval, and require longer cue-to-target intervals in order to fully benefit from the presence of an attentional cue. Our

data further showed that both the effect of cue validity and the interactive effect of cue validity by cue-to-target interval similarly applied to the SLI and TD groups (see Fig. 3a–d). This suggested that from a qualitative point of view, the two groups utilized visuospatial attentional mechanisms in a similar manner. A question still remained whether we would find any quantitative differences between the groups that would point to slowed attentional orienting in SLI, as predicted by the generalized slowing hypothesis. The SLI group was significantly less accurate than their matched peers across all conditions of the Shift task regardless of the amount of time to orient attention. If the poorer performance of the SLI group was due primarily to slowed attentional orienting, we would expect their performance to benefit more from a longer cue-to-target interval (800 ms) for orienting their attention than that observed in the control group. This was not the case; both groups showed equivalent improvement in performance with the longer interval. We, therefore, suggest that the SLI group was not slow to orient attention. The possibility still remains, however, that were we to use even longer cue-to-target intervals (e.g. 1200 ms), we might observe significant improvement in SLI performance, suggesting that their attentional orienting is slowed. However, since we saw no difference between the groups in the rate of performance improvement with longer intervals (i.e. no GROUP by C-T interaction), we believe that this would not be the case. It therefore seems unlikely that slowed orienting characterized the SLI group or accounted for their performance profile; rather, it seems more likely that the generally slower and less accurate response of the SLI group on the Shift task is attributable to slowed visual processing combined with slowed motor response, as suggested by the data on the Focused task. An important issue that we have discussed at length in the report of the normative study that preceded the current study is the distinction between covert and overt attentional orienting (Schul et al., 2003). While a 100 ms C-T interval allows for only covert orienting to occur, an 800 ms interval allows for either covert or overt orienting to occur (Groner & Groner, 1989). The ability to suppress saccades to a peripheral stimulus is relatively poor in children just entering school, and it improves during the school-age years (e.g. Ross, Radant, Young, & Hommer, 1994). Therefore, it is likely that many young participants (e.g. 7–8 year olds) given 800 ms to orient, orient overtly, even when given clear instructions to fixate (see Methods Section). In contrast, older participants (after 9–10 years of age), who are more efficient in suppressing reflexive saccades, as well as faster and more efficient in covert orienting, are more likely to utilize covert orienting even at the longer interval. In support of this suggestion, we demonstrated in the normative study (Schul et al., 2003) that the 7–8 year olds performed at chance level on the invalid trials with C-T interval of 800 ms, suggesting that they did indeed shift their gaze toward the invalid cue and away from the target. In contrast, the 9–10 year olds and older performed well above chance

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level in that same condition, suggesting that they did not overtly orient to the invalid cue; rather they used covert attentional orienting even with the longer (800 ms) C-T interval. The number of participants with SLI included in the present study did not allow us to analyze the data from a developmental perspective, as we did in the normative study. However, our data suggest that the SLI participants, as a group, used covert orienting with the 800 ms interval, as their performance with this interval is well above chance level (for valid and invalid trials)—just as it was for the 9–10 year olds in the normative study. Moreover, analysis of the data at the 100 ms interval (where only covert orienting is possible) demonstrated that both the SLI and the TD groups had significant validity effects, and that these validity effects were not statistically different for the two groups. This suggests that the effects that we observed were covert orienting effects and not merely due to eye movement at least at the short cue-to-target interval, and that the SLI and TD groups were similar with regard to these effects. We should note that the only significant group effect associated with the Shift task was a group by target-to-mask interaction, which was obtained with the RT measure. This interaction suggested that the TD group alone improved their response time with longer (>50 ms) target presentation time. In contrast, the SLI group, whose response time was generally slower than that of the TD group, was not able to benefit from this relatively small change in stimulus parameter. This is consistent with our previously discussed suggestion that the SLI children showed an RT ‘floor’ reflecting slowed motor response that is relatively independent of task demands. Our observation of normal speed of attentional orienting in SLI may appear inconsistent with the Sluggish Attentional Shifting (SAS) hypothesis, in which attention-related prolongation of input chunks underlies the impaired processing of rapid stimuli in dyslexic individuals (Hari & Renvall, 2001). However, a growing number of investigators have recently argued that despite the high comorbidity rates of SLI and dyslexia, these disorders should not be treated as synonymous (Heath, Hogben, & Clark, 1999; Leonard et al., 2002; Leonard, 1998; McArthur & Bishop, 2001; Rice, Wexler, & Redmond, 1999; Snowling, Bishop, & Stothard, 2000). Moreover, the stimulus parameters and experimental conditions on which the SAS hypothesis was based differ from those in the present study; as noted by the authors themselves, these factors could have profound effects on the results obtained in rapid stimulus sequence studies (Hari & Renvall, 2001). All in all, given the non-identity of populations and methods, further studies will be required to assess the applicability of the SAS hypothesis to the SLI population. Normal speed of attention orienting in the SLI group seems consistent with what is currently known about the brain substrates of spatial attention and identified brain abnormalities in SLI. Many different brain areas including the posterior parietal cortex (disengaging attention), superior colliculus, cerebellum, frontal eye field, and dorsolateral

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frontal cortex (moving attention), pulvinar nucleus of the thalamus (engaging attention), and cingulate cortex (motivational aspects of attentional orienting) have been found to play some role in visuospatial orienting (Coull & Nobre, 1998; Courchesne et al., 1994; Damasio, Damasio, & Chui, 1980; Paus et al., 1991; Posner, 1995; Posner & DiGirolamo, 1998; Posner, Walker, Friedrich, & Rafal, 1984; Rafal, Posner, Friedman, Inhoff, & Bernstein, 1988; Townsend et al., 1999; Watson, Heilman, Cauthen, & King, 1973). None of these areas, however, have been found to be abnormal in individuals with SLI. One recent study found a variety of non-specific brain abnormalities on MRI in a group of SLI children including ventricular enlargement, central volume loss and white matter abnormalities (Trauner, Wulfeck, Tallal, & Hesselink, 2000). Otherwise, the brains of individuals with SLI are generally characterized by smaller leftward asymmetry in the planum temporale and larger rightward asymmetry in the pars triangularis relative to those of normal controls (Cohen, Campbell, & Yaghmai, 1989; Gauger, Lombardino, & Leonard, 1997; reviewed in Lane, Foundas, & Leonard, 2001; Leonard, 1998; Plante, Swisher, Vance, & Rapcsak, 1991). Our findings of normal spatial attention orienting in this group are consistent with what might be expected given the apparent lack of overlap between the brain areas involved in spatial attention orienting and those that are implicated in SLI. To summarize, the SLI participants, as a group, were characterized by (a) slower visual processing, and (b) slower motor response, but (c) similar attentional orienting speed, relative to their gender- and age-matched peers. In the SLI children, the degrees of slowing in visual processing, motor response, or attentional orienting were not significantly correlated. In other words, those individuals who displayed, for instance, the greatest degree of slowing in visual processing, did not necessarily display motor slowing or slowed attentional orienting. Accordingly, it is possible that the mechanisms responsible for slowing in the aforementioned domains do not necessarily work in concert. Also, age alone was not predictive of slowing in any of the studied domains: some slowing was observed in some younger SLI individuals but not in others, and the same was true for older SLI participants. We should note, though, that we cannot rule out the possibility that the lack of correlations results from a relatively low statistical power in our study (due to a small sample size), an issue that can be addressed in future studies.

Acknowledgements This work was supported by a McDonnell-Pew fellowship to R.S., the National Institute of Child Health and Human Development Grant R01-HD25077 to J.S., the National Institute of Neurological Disorders and Stroke Grant RO1-NS34155 to J.T., and the National Institute of Neurological Disorders and Stroke Grant #P50-NS22343—Neurobehavioral studies of language

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