Edited by: Alan James Power, University of Cambridge, UK
Reviewed by: Nicholas Allan Badcock, Macquarie University, Australia; Manon Wyn Jones, Bangor University, UK
*Correspondence: Milena Ruffino, Child Psychopathology Unit, Scientific Institute, IRCCS Eugenio Medea, Via Don Luigi Monza, 20, Bosisio Parini, Lecco 23842, Italy e-mail:
This article was submitted to the journal Frontiers in Human Neuroscience.
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Although the dominant view posits that developmental dyslexia (DD) arises from a deficit in phonological processing, emerging evidence suggest that DD could result from a more basic cross-modal letter-to-speech sound integration deficit. Letters have to be precisely selected from irrelevant and cluttering letters by rapid orienting of visual attention before the correct letter-to-speech sound integration applies. In the present study the time-course of spatial attention was investigated measuring target detection reaction times (RTs) in a cuing paradigm, while temporal attention was investigated by assessing impaired identification of the first of two sequentially presented masked visual objects. Spatial and temporal attention were slower in dyslexic children with a deficit in pseudoword reading (
Developmental dyslexia (DD) is a neurodevelopmental disorder identified in about 10% of children which refers to a pattern of learning difficulties characterized by problems with accurate or fluent word recognition, poor decoding and poor spelling abilities, despite normal intelligence, and adequate access to conventional instruction (American Psychiatric Association,
According to the dual-route model (see Perry et al.,
The underlying neurocognitive mechanisms that lead to the observed reading impairments are still hotly debated (see Vidyasagar and Pammer,
Emerging evidence suggested that DD could arise from a more basic cross-modal letter-to-speech sound integration deficit (e.g., Blau et al.,
A specific relationship between non-linguistic deficits referred to as attentional shifting has been proposed by Hari and Renvall (
It is important to highlight that spatial attention is involved in perceptual noise exclusion (e.g., Carrasco et al.,
SAS may be a crucial factor behind difficulties in learning to read (Hari and Renvall,
Although it has already been demonstrated that visual spatial and temporal attention deficits could contribute independently to the poor reading outcome of dyslexic individuals, as yet, no studies have shown that both spatial and temporal attentional deficits co-occur in the same group of children with DD. These findings indicate that a sluggish shifting of spatial attention is specifically related to a perceptual noise exclusion deficit in DD.
Thus, in the current study, we investigated whether both spatial and temporal attention are impaired in DD with poor phonological decoding, and if they have a specific predictive relationship with phonological decoding skill.
We measured the time-course of visual spatial attention (VSA) and visual temporal attention (VTA) in two groups of dyslexic children, classified on the basis of their phonological decoding (dis)ability, and one group of controls matched for chronological age and IQ.
VSA has been extensively studied by using spatial cuing paradigms (Posner,
VTA was measured by using an identification task in which the first of two sequentially and centrally presented, forward and backward masked objects had to be recognized (i.e., signal + noise condition; Duncan et al.,
Participants were 32 Italian children with DD recruited at the Child Psychopathology Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco. Chronological age ranged from 8 to 14 (mean = 10,
In order to study the sub-lexical route efficiency, dyslexic children were divided into two groups on the basis of their accuracy in phonological decoding. In particular, their ability to read aloud was measured on a list of 50 Italian regular and 50 Italian irregular
We administered a Pseudowords Phoneme Blending (PPB) task and a Pseudoword Short-Term Memory (PSTM) task to the participants.
In the PPB task, single phonemes were presented, and participants were asked to pronounce the resulting pseudowords from their synthesis (i.e., G-A-S-T-I-B-O = GASTIBO). Performances were calculated on the basis of the number of pseudowords correctly pronounced (the number of words administered were one for familiarization, nine experimental; the number of phonemes included in each pseudoword ranged from 7 to 10). The PSTM task consisted of repeating lists of pseudoword trigrams orally presented (i.e., two items ranging from 2 to 8 trigrams) in the same order as originally presented. Performances were indexed as the number of phonemes correctly repeated in the correct position (the maximum score was 210 phonemes). The number of list items increased with correct responses until participants made an error in both list items administered of the same length. For additional details see Supplementary Material.
Testing was carried out in a dimly lit (luminance of 1.5 cd/m2) and quiet room (approximately 50 dB SPL). Participants were seated in front of a computer screen (background luminance of 0.5 cd/m2), with their head positioned on a chinrest so that the eye-screen distance was 40 cm. Stimuli were white on a black background and had a luminance of 24 cd/m2. Each trial started with the onset of the fixation point (1° visual angle; 500 ms). Two circles (2.5°) were displayed peripherally (8° eccentricity, one to the left and one to the right of the fixation point) and 500 ms later the visual cue was shown, consisting of an arrow (1.5° visual angle) displayed for 50 ms above one of the circles. In response trials, a target (dot, 0.5°; duration 50 ms) was presented after one of two cue-target stimulus onset asynchronies (SOA, 100 or 350 ms) in one of the two possible locations. The probability that the cue was presented in the target location was about 80% (i.e., the cue location was predictive of target location). In contrast, in catch trials the target was not presented and participants did not have to respond. Catch trials were intermixed with response trials. Participants were instructed to react as quickly as possible to the onset of the visual targets by pressing the spacebar on the computer keyboard (detection task). Simple RTs and error rates were recorded by the computer. The maximum time allowed to respond was 1500 ms. The inter-trial interval was 1000 ms, after that time the trial started automatically. The experimental session consisted of 128 trials divided into two blocks of 64 trials each, which were distributed as follows: 40 valid trials (20 targets in the right visual field and 20 in the left visual field, 10 for each SOA), 12 invalid trials (6 targets in the right visual field and 6 in the left visual field, 3 for each SOA), and 12 catch trials (6 for each SOA; see Figure
The experimental environment was the same as described above for the spatial attention task. Each trial began with the onset of the fixation mark (0.3° of visual angle; duration 500 ms). Participants were instructed to keep their eyes on the fixation mark throughout the duration of the trial. Two conditions, a “signal alone” (O) and “signal + noise” (O+noise), were randomly presented to each participant. In the O condition a single object (duration 100 ms) was displayed and the aim was to measure the participants' ability to identify the experimental stimuli. In the O+noise condition an 8 digital clock-face font comprising seven line segments was displayed for a variable time exposure (175, 225, 275, or 325 ms) acting as a pre-mask, two successive objects (black O1 and red O2) were presented for 100 ms by removing some of the line segments (see Figure
Before the start of the experimental session, participants viewed each of the four different stimuli one by one with no time constraint (familiarization phase). After each trial all four possible targets were presented on the screen together (two targets per line). Participants responded by pointing on the screen. These responses were registered by the experimenter by pressing the corresponding key on a computer keyboard and no feedback was provided. The experimental session consisted of 40 trials (16 for the O condition and 24 for the O+noise condition; see Figure
The differences between the three groups in age, Performance IQ, experimental reading paradigm (the accuracy in regular, irregular word, and pseudoword reading) and phonological tasks (pseudowords and phonemes correctly reported in the PPB and PSTM task, respectively) were analyzed. Results showed no significant differences in age or Performance IQ [
Age (months) | 122.23 | 27.87 | 122.50 | 20.00 | 122.57 | 25.45 | −0.04 | >0.05 | −0.01 | −0.04 | >0.05 | −0.01 | 0.01 | >0.05 | −0.003 |
Performance IQ (ss) | 13.65 | 2.61 | 12.11 | 3.41 | 13.07 | 2.43 | 1.17 | >0.05 | 0.51 | 0.76 | >0.05 | 0.23 | −0.93 | >0.05 | −0.32 |
Regular words reading (%) | 99.67 | 0.75 | 90.56 | 15.76 | 93.57 | 3.16 | 2.45 | 0.82 | 7.17 | 2.66 | −0.80 | >0.05 | −0.26 | ||
Irregular words reading (%) | 98.28 | 2.64 | 88.94 | 16.77 | 89.00 | 7.51 | 2.35 | 0.78 | 4.53 | 1.65 | −0.01 | >0.05 | −0.005 | ||
Pseudowords reading (%) | 93.77 | 6.02 | 78.78 | 14.83 | 64.43 | 10.14 | 4.15 | 1.32 | 10.25 | 3.52 | −3.24 | 1.13 | |||
Number of correct pseudowords | 5.44 | 1.76 | 3.50 | 2.75 | 2.18 | 1.99 | 2.77 | 0.84 | 5.46 | 1.73 | −1.57 | >0.05 | 0.55 | ||
Number of correct phonemes | 56.74 | 17.20 | 40.61 | 15.41 | 35.86 | 11.97 | 3.60 | 0.99 | 5.05 | 1.41 | −0.98 | >0.05 | 0.34 |
Mean correct detection RTs were analyzed with a mixed ANOVA that had target condition (valid and invalid) and SOA (100 and 350 ms) as within-subject factors, and group (NR, DDP+, and DDP−) as between-subject factor. The target condition main effect was significant,
100 ms cue-target delay | 37.56 | 38.15 | 43.83 | 44.50 | 12.74 | 44.51 | −0.52 | >0.05 | −0.01 | 2.03 | 0.88 | 1.96 | 0.96 | ||
350 ms cue-target delay | 36.79 | 39.26 | 32.25 | 67.74 | 59.19 | 62.91 | 0.27 | >0.05 | 0.08 | −1.26 | >0.05 | −0.43 | −1.15 | >0.05 | −0.41 |
In summary, the data highlighted a marked offset of the time-course of visual attention in DDP−, which suggests a sluggish VSA, because differences were selectively present only for the shorter SOA. DDP− group show that for the longer SOA, VSA was abnormally oriented.
The identification accuracy mean in the O condition was analyzed by a One-Way ANOVA with Group as the between subjects factor. The group main effect was not significant [
O | 94 | 8.27 | 93 | 10.53 | 89.50 | 9.30 |
O+noise | 64 | 21.89 | 64 | 21.66 | 47 | 23.83 |
“intrusion” errors (O+noise condition) | 35.81 | 12.19 | 34.44 | 10.97 | 42.14 | 11.22 | 0.43 | >0.05 | 0.003 | −5.3 | 8.03 | −1.79 | 0.051 | 1.05 | −1.94 | 0.113 | 0.36 |
Our results demonstrate a specific VSA and VTA deficit in the DDP− group. In order to investigate a possible relationship between individual measures of the cuing effect (VSA) time-course, the perceptual noise exclusion mechanism (VTA), and phonological decoding skill across our entire sample of dyslexic children (
The main results showed that phonological decoding was significantly correlated with both spatial and temporal attention as well as phoneme blending (see Figures
Irregular words reading (%) | – | |||||
Pseudowords reading (%) | – | |||||
Number of correct pseudowords | 0.336 | – | ||||
Number of correct phonemes | 0.172 | 0.159 | – | |||
VTA | 0.056 | 0.120 | −0.063 | 0.012 | – | |
VSA | −0.322 | −0.239 | −0.325 | |||
Irregular words reading (%) | – | |||||
Pseudowords reading (%) | – | |||||
Number of correct pseudowords | – | |||||
Number of correct phonemes | – | |||||
VTA | 0.117 | 0.206 | 0.168 | 0.181 | – | |
VSA | −0.203 |
To determine predictive relationships between visual attention and reading (pseudoword and irregular) accuracy, we computed two four-step fixed-entry multiple regression analyses on the individual data of the dyslexic children to control for the effects of age, Performance IQ, attentional mechanisms, and phonological processing.
Descriptive statistics of variables included in the multiple regression analysis are reported in Table
Age (months) | 122.53 | 22.16 |
Performance IQ (ss) | 12.53 | 3.02 |
Pseudowords reading (%) | 72.5 | 14.70 |
VSA | 13.81 | 79.50 |
VTA | 56.59 | 23.84 |
Number of correct phonemes | 38.53 | 14 |
Age and performance IQ | 0.283 | 0.080 | 0.080 | 1.265 | 2 | 29 | >0.05 |
VSA | 0.501 | 0.251 | 0.171 | 6.380 | 1 | 28 | |
VTA | 0.506 | 0.256 | 0.005 | 0.187 | 1 | 27 | >0.05 |
PPB | 0.628 | 0.394 | 0.138 | 5.908 | 1 | 26 |
In the second multiple regression analysis the dependent variable was irregular word reading accuracy and the predictors entered at the four steps were the same as in the first analysis. Only the PPB entered at the last step accounted for 12% (
Age and performance IQ | 0.266 | 0.071 | 0.071 | 1.102 | 2 | 29 | >0.05 |
VSA | 0.402 | 0.162 | 0.072 | 0.091 | 1 | 28 | >0.05 |
VTA | 0.438 | 0.192 | 0.030 | 1.006 | 1 | 27 | >0.05 |
PPB | 0.556 | 0.309 | 0.117 | 4.381 | 1 | 26 |
Our results demonstrate that both spatial and temporal attention were impaired only in dyslexics with a poor phonological decoding (DDP−), confirming the relationship between visual attentional mechanisms and graphemic parsing processes. It is important to note that attentional graphemic parsing precedes the letter-to-speech sound integration.
The attentional cuing effect was present at the shortest cue-target delay (100 ms) in both NR and DDP+, as predicted by automatic capture theories (for a review, see Klein,
Moreover, object identification in the object task without noise was not impaired in poor phonological decoders, excluding a possible general visual perception deficit. In contrast, DDP− showed a specific identification deficit in comparison to NR and DDP+ when the object was displayed with noise (i.e., masks and a second object), demonstrating an inefficient perceptual-noise exclusion mechanism. Although the DDP− group showed a larger second object substitution, it would be important for future research to incorporate a baseline measure including O1+mask, but excluding O2, which would better isolate the role of specific O2 interference on O1. This condition could be relevant to even better isolate the pure role of the O2 interference, otherwise it would be difficult to exclude that unknown processing speed differences between the groups may play a role in the results.
According to the phonological hypothesis, it is important to note that poor pseudoword reading accuracy is strongly related to impaired phonological awareness (Frith,
Our attention indices allowed us to discriminate between dyslexics with poor phonological decoding and dyslexics with unimpaired phonological decoding or normal readers. Our results suggest that visual attention impairments are the core deficit in dyslexics characterized by poor (i.e., inaccurate) phonological decoding. This finding was supported by the predictive relationship of reading performance and visual attentional tasks, even after controlling for age and Performance IQ. Attentional graphemic parsing was significantly related to phonological decoding because it represents the first step that precedes not only letter-to-speech sound integration but also phonemic blending (significantly related to pseudoword reading) during the reading process.
It is important to stress that the predictive relationship between attention and reading skills held across the entire sample of dyslexics, independently of any a priori classification or subtyping of the dyslexic children. Thus, regardless of whether children in the DDP+ group constitute a specific subtype in shallow orthographies (Wimmer,
Our findings are consistent with previous results (e.g., Roach and Hogben,
Clearly, these results are inconsistent with the hypothesis that DD is an exclusively phonological deficit. The present link between deficits in spatial and temporal attention and impaired phonological decoding is consistent with the hypothesis that visual selection (i.e., the perceptual-noise exclusion mechanism) operates on graphemes as the basic component of the phonological assembly process (Cestnick and Coltheart,
Neural coding by brain oscillations is a major focus in neuroscience (e.g., Buzsaki and Draghun,
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
This work was supported by a grant from University of Padua (“Progetto di Ateneo 2009 and 2011” to Andrea Facoetti and “Assegni di Ricerca 2009 and 2011” to Simone Gori). The contributions of the staff members of Eugenio Medea Scientific Institute as well as of the children and their families are gratefully acknowledged. We thank Marc Pomplun for his reading of the manuscript.
The Supplementary Material for this article can be found online at:
1Italian irregular words are defined as words stressed at third or fourth syllable from last (e.g., rùvido, dòllaro, àbitano, dèlegano).
2The main effect of the O1 pre-mask variable time exposure (175, 225, 275 or 325 msec) and the interaction effect with the group were not significant (