January 2017
Volume 58, Issue 1
Open Access
Clinical and Epidemiologic Research  |   January 2017
Visual Perception and Reading: New Clues to Patterns of Dysfunction Across Multiple Visual Channels in Developmental Dyslexia
Author Affiliations & Notes
  • Ana Pina Rodrigues
    Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
  • José Rebola
    Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
  • Helena Jorge
    Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
  • Maria José Ribeiro
    Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
  • Marcelino Pereira
    Faculty of Psychology and Education Sciences, University of Coimbra, Coimbra, Portugal
  • Marieke van Asselen
    Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
  • Miguel Castelo-Branco
    Institute for Biomedical Imaging and Life Sciences (CNC.IBILI), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
  • Correspondence: Ana Pina Rodrigues, Azinhaga de Santa Comba, 3000-548 Coimbra, Coimbra, Portugal; ana.pina.rodrigues@gmail.com
  • Footnotes
     MvA and MC-B are joint senior authors.
  • Footnotes
     APR and JR contributed equally to the work presented here and should therefore be regarded as equivalent authors.
Investigative Ophthalmology & Visual Science January 2017, Vol.58, 309-317. doi:10.1167/iovs.16-20095
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      Ana Pina Rodrigues, José Rebola, Helena Jorge, Maria José Ribeiro, Marcelino Pereira, Marieke van Asselen, Miguel Castelo-Branco; Visual Perception and Reading: New Clues to Patterns of Dysfunction Across Multiple Visual Channels in Developmental Dyslexia. Invest. Ophthalmol. Vis. Sci. 2017;58(1):309-317. doi: 10.1167/iovs.16-20095.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: The specificity of visual channel impairment in dyslexia has been the subject of much controversy. The purpose of this study was to determine if a differential pattern of impairment can be verified between visual channels in children with developmental dyslexia, and in particular, if the pattern of deficits is more conspicuous in tasks where the magnocellular–dorsal system recruitment prevails. Additionally, we also aimed at investigating the association between visual perception thresholds and reading.

Methods: In the present case–control study, we compared perception thresholds of 33 children diagnosed with developmental dyslexia and 34 controls in a speed discrimination task, an achromatic contrast sensitivity task, and a chromatic contrast sensitivity task. Moreover, we addressed the correlation between the different perception thresholds and reading performance, as assessed by means of a standardized reading test (accuracy and fluency). Group comparisons were performed by the Mann-Whitney U test, and Spearman's rho was used as a measure of correlation.

Results: Results showed that, when compared to controls, children with dyslexia were more impaired in the speed discrimination task, followed by the achromatic contrast sensitivity task, with no impairment in the chromatic contrast sensitivity task. These results are also consistent with the magnocellular theory since the impairment profile of children with dyslexia in the visual threshold tasks reflected the amount of magnocellular–dorsal stream involvement. Moreover, both speed and achromatic thresholds were significantly correlated with reading performance, in terms of accuracy and fluency. Notably, chromatic contrast sensitivity thresholds did not correlate with any of the reading measures.

Conclusions: Our evidence stands in favor of a differential visual channel deficit in children with developmental dyslexia and contributes to the debate on the pathophysiology of reading impairments.

Developmental dyslexia is a neurodevelopmental disorder characterized by a reading impairment in spite of normal intellectual functioning and educational opportunities.1 Although the prevalence of this condition is fairly high (7%),2 its causes and mechanisms remain under debate and are currently a subject of intensive research. Phonological deficits are usually described as the core impairment in dyslexia and constitute the basis for the most dominant theory in the field: the phonological theory.3 This causal hypothesis states that an inadequate correspondence between phonemes and graphemes is accountable for the reading deficits in this population. Nonetheless, in-depth study of this condition has revealed perceptual and sensory dysfunctions,46 which cannot be discarded. To take these into account, a number of alternative theories have therefore been put forward. Among those, a widely discussed yet controversial sensory theory is the magnocellular account.7,8 
The magnocellular and parvocellular retinocortical pathways carry the majority of visual information from the retina into the cortex.9 The route from primary visual cortex (V1) projecting to V5 (MT) and to posterior parietal regions is termed dorsal stream. Magnocellular input is thought to dominate this stream, often called the magnocellular–dorsal (M-D) stream. The route from V1 projecting to V4 and on to the inferior temporal cortex is referred as the ventral stream (V).10 The two systems have distinct characteristics, and while the M-D system is specialized in processing high temporal frequencies and low spatial frequencies, the V stream processes low temporal frequencies and high spatial frequencies.11,12 According to the magnocellular theory, the visual perception of people with dyslexia is characterized by an abnormal functioning of the M-D stream.13,14 Several studies have provided evidence that either favor or oppose this theory. Initially, it was supported by anatomic evidence from postmortem studies in adults with dyslexia. In their studies, Galaburda and Livingstone15 and Livingstone et al.16 reported anatomically abnormal magno cells in the lateral geniculate nucleus (LGN), a thalamic structure that receives information from the retina and projects to V1. Electrophysiological17,18 and fMRI1922 studies have also corroborated these findings by highlighting abnormal neural responses to magnocellular stimuli. Moreover, psychophysical studies have shown that both children and adults with dyslexia fail to reach a normal level of motion processing,20,2328 attributed to the M-D stream. Other studies focused on the differences in contrast sensitivity thresholds between dyslexic patients and controls to identify M-D differences.5,2834 A study by Iles et al.24 raised an important question by adressing the upstream influence of low-level deficits on higher-level visual tasks that are mainly dependent on M-D functioning. These authors found that the adults with dyslexia who had elevated motion coherence thresholds were also impaired on visual search tasks probing the posterior parietal function, which is known to be involved in reading. Additionally, to fully understand the implications of the M-D impairment in reading deficits, a number of studies addressed its correlation with reading measures, finding significant links.28,3537 
Nonetheless, as already mentioned, the literature is not unanimous on the claim of particular M-D impairment in dyslexia. A number of studies report normal thresholds of motion processing3840 and on other M-D functioning measures,4145 as well as considerable performance variability in the population.24,32,4648 Other studies question the specificity of visual channel impairment4952 or its mechanistic link with reading problems.5355 These discrepancies are partly explained by task variability and the difficulty in isolating each visual stream.51,56 However, by compiling multiple tasks one can build an informative test battery based on different levels of M-D/V contribution. 
In the present study we tested multiple visual channels to verify if a differential pattern of impairment could be found in children with and without dyslexia and to investigate whether the pattern of results can be interpreted as a function of their relative contribution to each of the visual streams. The second goal of the study was to investigate the associations between different visual thresholds and reading performance. To achieve these goals we assessed visual function in Portuguese children with developmental dyslexia and examined the link between low-level visual processing and reading performance. We chose a battery of low-level visual tasks ranging from color to achromatic contrast sensitivity and speed discrimination. These tasks seem to differentially involve M-D and V streams. In other words, they likely lead either to a preferential M-D activation (speed discrimination task) or to V activation (chromatic contrast sensitivity task). The achromatic contrast sensitivity task using intermediate spatial frequencies probably leads to a more even pattern of activation of both streams.57,58 Our concept of a gradient of M-D involvement was developed to overcome the known difficulty to ensure an exclusive activation of M-D stream. Our battery of tasks followed, therefore, a gradient of M-D stream contribution (from strong in local speed discrimination, to mild in the intermediate spatial frequency contrast sensitivity task and weak in the chromatic task), which allowed us to establish a profile of low-level visual deficits in terms of a gradient of M-D recruitment, instead of having to rely on the assumption of exclusive activation of the stream. Finally, scores on visual function were then confronted with reading fluency and accuracy indexes, as measured through text reading. 
Methods
Ethics Statement
This study and all procedures were reviewed and approved by the Ethics Committee of the Faculty of Medicine of the University of Coimbra and were conducted in accordance with the tenets of the Declaration of Helsinki. Written informed consent was obtained from the legal representatives of the participants, after explanation of the nature of the study. 
Participants
Participants included 33 children with dyslexia (mean age: 9.88 ± 1.45 years) and 34 age-matched controls (mean age: 10.06 ± 1.39 years). Both groups were assessed in terms of IQ and reading level with the Wechsler Intelligence Scale for Children (WISC-III, Portuguese version)59 and the Fluency and Accuracy Reading Assessment Test: The King,60 widely used in Portugal for reading assessment. This reading test has two outcomes that were further analyzed as reading measures: the Accuracy Index (AI) and the Fluency Index (FI). Accuracy Index was calculated using the formula (WCR / WR) × 100, where WCR stands for the number of words correctly read and WR for the total number of words read. Fluency Index was calculated using the formula (WRC / RT) × 60, where RT stands for the total time necessary to read the text (maximum of 180 seconds). 
The recruitment period of the clinical and control samples spanned 18 months. Children with dyslexia were recruited from the diagnostic and treatment center of the Faculty of Psychology and Education Sciences of the University of Coimbra. The inclusion criteria were a 2-year lag in reading speed and/or reading accuracy on the Fluency and Accuracy Reading Assessment Test: The King,60 and a normal level of intelligence assessed by the WISC III, Portuguese version (IQ above 90).59 The presence of comorbid attention-deficit/hyperactivity disorder was established as exclusion criterion. The clinical sample consisted of volunteer children who fulfilled the inclusion and exclusion criteria, assessed either during the period of recruitment or previously assessed at the center. The control group comprised volunteer children recruited through distribution of flyers in local schools. These typically developing children had no history of learning, developmental, cognitive, neurologic, or neuropsychiatric problems. Groups were matched for age, education, sex, and IQ. All participants had normal or corrected-to-normal vision (visual acuity of 20/20). Characteristics of participants are summarized in Table 1
Table 1
 
Summary Statistics for the Two Groups of Participants
Table 1
 
Summary Statistics for the Two Groups of Participants
Procedure
Three tasks were applied to assess low-level visual function: a speed discrimination task (Local Speed Discrimination), an achromatic contrast sensitivity task (Intermediate Spatial Frequency), and a chromatic contrast sensitivity task (Cambridge Colour Test). The tasks took place in a darkened room. Children executed the tasks monocularly (only the dominant eye was tested) with an opaque patch occluding the other eye. A chin and forehead rest was used to ensure a stable viewing position throughout testing. 
Local Speed Discrimination (LSD).
The LSD task was developed in our laboratory (adapted from Ref. 61). The task was programmed in MATLAB (MATLAB 2011a; The Mathworks, Inc., Natick, MA, USA), using the Psychophysics Toolbox (PTB-3) extension. Children were seated at a viewing distance of 50 cm. All stimuli were presented on a gamma-corrected 24-inch LCDIPS monitor (ColorEdge CG243W; Eizo, Hakusan, Japan) with a resolution of 1920 × 1200 pixels and a refresh rate of 60 Hz. Spectral and luminance measurements were made using a spectroradiometer (PR-650 SpectraScan Colorimeter; Photo Research, Inc., Chatsworth, PA, USA). The background luminance was ∼0 cd/m2
The LSD is a psychophysical task that requires the discrimination of motion speed between two separated moving single dots (a reference dot and a target dot) (see Fig. 1a). In each trial the reference and target dots (two white dots moving at different velocities) were simultaneously presented for 400 ms. Stimuli consisted of squared dots measuring 0.3° × 0.3°. The reference dot velocity was always 5°/s (visual degrees per second), while the target dot velocity started at 24°/s and was then adjusted by the logarithmic staircase procedure (maximum step size of 1 decibel [dB] and minimum of 0.05 dB). Children were asked to fixate a black central cross (size of 1°) during the test. After each trial, participants were asked to press a button on a keyboard indicating which dot was moving faster (“Left/Right” for the horizontal and oblique meridians or “Up/Down” for the vertical meridian). The motion was then adjusted in the following trial, driven by a correct or incorrect response, by using a logarithmic staircase procedure. The tests ended after six reversals, and a discrimination threshold was calculated using the arithmetic mean of the last four reversals. This threshold represents the discriminated difference, in °/s, between test and reference stimulus. The test was repeated four times, corresponding to four different meridian/eccentricity pairs (the horizontal meridian, 0°, tested at 7.5° of eccentricity; the vertical meridian, 90°, at 10°; and the oblique meridians, 45° and 135°, at 15°). The four thresholds obtained from the four different meridians were averaged into a grand average in order to obtain a measure of the global motion perception of these children. 
Figure 1
 
Schematic representation of the visual tests. (a) Representation of the location, at the horizontal meridian 0°, where the moving dots were presented in the speed discrimination task. Three additional meridians were tested (vertical 90°, tested at 10° of eccentricity; and oblique 45° and 135°, at 15° of eccentricity). The central cross represents the fixation cross. (b) Representation of the sizes and shapes of the nine locations (represented in different shades of gray and black) within the visual field where the gratings with intermediate spatial frequency were presented. Note that in the actual experiment the shaded areas and the separating lines were not present. The stimuli were shown at these locations against an overall gray background. The black square in the middle of the figure represents the fixation square. (c) Illustration of the stimuli used in the chromatic contrast sensitivity task (Cambridge Colour Test) representing a luminance noise stimulus with superimposed chromatic target (Landolt C shape, colored in red).
Figure 1
 
Schematic representation of the visual tests. (a) Representation of the location, at the horizontal meridian 0°, where the moving dots were presented in the speed discrimination task. Three additional meridians were tested (vertical 90°, tested at 10° of eccentricity; and oblique 45° and 135°, at 15° of eccentricity). The central cross represents the fixation cross. (b) Representation of the sizes and shapes of the nine locations (represented in different shades of gray and black) within the visual field where the gratings with intermediate spatial frequency were presented. Note that in the actual experiment the shaded areas and the separating lines were not present. The stimuli were shown at these locations against an overall gray background. The black square in the middle of the figure represents the fixation square. (c) Illustration of the stimuli used in the chromatic contrast sensitivity task (Cambridge Colour Test) representing a luminance noise stimulus with superimposed chromatic target (Landolt C shape, colored in red).
Intermediate Spatial Frequency (ISF).
The ISF contrast sensitivity task, developed in our laboratory,62,63 uses static achromatic vertical gratings with an intermediate profile. Stimuli were static vertical gratings, with a spatial frequency of 3.5 cyc/deg (mean background luminance of 51 cd/m2, constant throughout the experiment) displayed on a 21-inch monitor (Trinitron GDM–F520 monitor; Sony, Tokyo, Japan). 
The width of each stimulus was 10° of visual angle (35 grating cycles) (see Fig. 1b). Stimulus duration was 200 ms, and the interstimulus interval varied randomly between 2300 and 2800 ms. The stimuli were presented within nine locations of the visual field. Children were seated at a viewing distance of 36 cm and were instructed to fixate the black square in the center of the screen and report the presence of the targets by pressing a button. Participants' reliability was evaluated by the inclusion of false-positive (0% contrast stimuli) and false-negative (100% contrast in the central location) “catch trials.” Experiments with a false-positive or false-negative rate above 33% were aborted. The task was then repeated after a small rest period. If the participant still responded with a high number of false positives or false negatives, the data were not used in the analysis. 
Luminance contrast of the stimulus was expressed according to Michelson. Contrast sensitivity results were expressed in terms of decibel units, dB = 20 × log (1/c), with contrast c measured as a percentage. To obtain the psychophysical thresholds, the test uses nine randomly interleaved logarithmic staircases, one for each location tested. The contrast value used for a given trial was calculated using the previous trial value plus or minus the step size in dB. The step size used was 3 dB. Staircases were run for a total of four reversals. The contrast at the final two reversals was averaged to estimate the contrast threshold. For this task, data could not be collected from one of the control children. 
Cambridge Colour Test (CCT).
Finally, to test chromatic contrast sensitivity we used a task that establishes a threshold of color discrimination, the Cambridge Colour Test (CCT; Cambridge Research Systems, Rochester, UK). Stimuli were displayed on a 21-inch monitor (GDM-F520; Sony) and consisted of static patterns of circles of various sizes and luminances with superimposed chromatic contrast defining the letter C (gap size: 1.6°; outer diameter: 7.6°; inner diameter: 3.81°) (see Fig. 1c). Participants were positioned at a viewing distance of 1.8 m and were instructed to indicate the position of the C's gap by pressing one of four buttons (up, down, left, or right). We used a color version of the test (Trivector; CCT), where the targets differ from the background along one of the three color confusion lines, each activating one type of cone receptor: protan, deutan, or tritan. We took as the threshold for the red–green (parvocellular) chromatic channel the average of the thresholds along protan and deutan lines (CCT-PD). The test uses three randomly interleaved staircases to dynamically adjust the chromaticity of the target according to the participant's performance to establish the chromaticity difference between target and background needed for reliable report of the orientation of the C. Occasional control trials, with a target presented at maximal chromatic saturation, were introduced to ensure that the participant was alert. Testing on any one staircase was terminated after 11 reversals, and the mean of the last 6 reversals was taken as the threshold estimate for the direction being tested, as has been previously established.61,62 Psychophysical thresholds were expressed in CIE 1976 u'v' color space units. 
Statistical Analysis.
All statistical analyses were performed using the IBM SPSS statistical software package, version 20.0 (SPSS, Inc., Chicago, IL, USA). Since data significantly deviated from normal distributions (verified using the Kolmogorov-Smirnov normality check and Levene homogeneity tests), we applied nonparametric statistical methods. Group comparisons were performed by Mann-Whitney U test. Participants scoring more than 3 SD away from the group mean were considered outliers and therefore not included in the between-group analyses. This resulted in the exclusion of one participant with dyslexia from the CCT-PD task comparison. Correlational analyses were performed using Spearman rank correlation coefficient (ρ). As in other studies,36,64 correlations were assessed for the population as a whole. Once again, participants scoring more than 3 SD away from the overall population mean were considered outliers and therefore not included in the analyses. This was the case for five children with dyslexia: two in the ISF task, one in the CCT-PD task, and two in the AI measure. 
Results
Low-Level Visual Perception in Dyslexia
The low-level visual function was assessed through a battery of tasks: the LSD, the ISF, and the CCT. Results are summarized in Table 2. Mann-Whitney U test analyses showed that cases and controls had similar CCT-PD thresholds (P = 0.644), indicating a preserved color discrimination in the dyslexic group (see Fig. 2, top). In contrast, the ISF task already revealed a significant difference between groups (P = 0.001; effect size r = 0.410), with poorer perception thresholds for children with dyslexia (see Fig. 2, middle). This performance difference between groups was further increased in the LSD task (P < 0.0001; effect size r = 0.519) (see Fig. 2, bottom). 
Table 2
 
Low-Level Visual Perception Thresholds of Children With and Without Dyslexia
Table 2
 
Low-Level Visual Perception Thresholds of Children With and Without Dyslexia
Figure 2
 
Performance of controls and dyslexics in the CCT-PD (top), ISF (middle), and LSD (bottom). Moving from top to bottom, note that dyslexics show normal chromatic contrast sensitivity, mildly impaired achromatic contrast sensitivity, and considerable speed discrimination impairment. (Box boundaries correspond to upper and lower 25th percentiles, outer bars to the 10th percentiles, and middle bar to the median).
Figure 2
 
Performance of controls and dyslexics in the CCT-PD (top), ISF (middle), and LSD (bottom). Moving from top to bottom, note that dyslexics show normal chromatic contrast sensitivity, mildly impaired achromatic contrast sensitivity, and considerable speed discrimination impairment. (Box boundaries correspond to upper and lower 25th percentiles, outer bars to the 10th percentiles, and middle bar to the median).
Taken together, results showed that children with dyslexia were more impaired in the LSD task, followed by the ISF task, with no impairment in the CCT-PD task and, therefore, argue against a generalized visual perception deficit. 
Correlations Between Low-Level Visual Functions and Reading
In order to address the link between visual perception and reading, Spearman correlations were computed between the low-level visual thresholds (LSD, ISF, and CCT-PD) and the reading measures (AI and FI). 
No significant correlations were found between the CCT-PD thresholds and the reading measures (AI: ρ = −0.054 [P = 0.670]; FI: ρ = −0.148 [P = 0.236]). Thus, we did not find evidence of an association between chromatic sensitivity and reading. On the contrary, achromatic contrast sensitivity and speed discrimination were correlated with reading performance, in terms of both accuracy (AI) and fluency (FI). In the case of the ISF thresholds, the correlation coefficients were ρ = −0.413 (P = 0.0009) for the AI and ρ =−0.412 (P = 0.0007) for the FI. For the LSD task, correlation analysis identified significant correlations with the AI (ρ = −0.440; P = 0.0003) and with FI (ρ = −0.520; P < 0.0001) (Fig. 3). Therefore, we found that the lower the achromatic contrast sensitivity and speed discrimination thresholds, the better the reading performance, in terms of both accuracy and fluency. 
Figure 3
 
Scatter plots illustrating the correlations between the Accuracy and Fluency Indexes from the reading test with chromatic sensitivity (CCT-PD) and speed discrimination (LSD) perception thresholds. Controls (empty dots). Dyslexics (filled triangles).
Figure 3
 
Scatter plots illustrating the correlations between the Accuracy and Fluency Indexes from the reading test with chromatic sensitivity (CCT-PD) and speed discrimination (LSD) perception thresholds. Controls (empty dots). Dyslexics (filled triangles).
Discussion
The present work compared children with and without developmental dyslexia (mean age: 9.88 and 10.06, respectively, which means that our results may not be generalizable to other age cohorts) on a battery of visuoperceptual tasks assessing chromatic and achromatic contrast sensitivity and speed discrimination. The fundamental aim of this work was to probe multiple visual channels in children diagnosed with developmental dyslexia in order to verify if a differential pattern of impairment is present in these children. 
We demonstrate that Portuguese children with dyslexia are substantially impaired when asked to discriminate speed, corroborating previous studies that addressed motion processing.20,26,28,49 It should be noted that motion perception has traditionally been assessed by coherent motion detection thresholds instead of speed discrimination. However, the output of this particular type of task across studies is contradictory (see Refs. 2325, 27, 65, but also 38 and 39). Moreover, deficits in motion coherence are present in several neurodevelopmental disorders, such as autism66,67 and Williams syndrome.68,69 On the contrary, speed discrimination impairments seem to be preserved in, at least, some of these disorders.70,71 Thus, it seems that speed discrimination deficits may represent more specific motion deficits in dyslexia than coherent motion deficits. Additionally, recent genetic studies showed that some motion deficits, including coherent motion but not speed discrimination, are particularly strong in dyslexic individuals with a deletion in intron 2 of the DCDC2 gene rather than in the whole dyslexic population.47,72 
The second main finding of our study is that children with dyslexia have preserved chromatic contrast sensitivity. Chromatic vision in these patients, contrary to other visual functions, has not been comprehensively studied. To our knowledge there are few studies on this subject,52,64,7375 and only Ahmadi et al.52 reported abnormal chromatic contrast thresholds in children with dyslexia. However, the task used in their study to assess chromatic contrast sensitivity consisted of chromatic natural scenes, which suggests that neural responses and performance may be distinct for natural chromatic scenes. Moreover, we must acknowledge that our chromatic contrast sensitivity testing was limited to the red–green chromatic channel, since it also aimed at probing V stream functioning. Nonetheless, the present study endorses the majority of the previous literature by adding supportive evidence of a preserved chromatic channel in a population where other visual channels were concomitantly studied. Finally, we show, for the first time, that children with dyslexia were mildly affected when an ISF channel was tested. Taken together, our results indicate differential low-level visual deficits in children with developmental dyslexia, arguing against the notion of a generalized visuoperceptual impairment. 
The study of visual function in dyslexia has been mainly related to the debate on the magnocellular theory.7,8 According to this theory, dyslexics suffer from specific M-D stream difficulties. Magnocellular-dorsal stream is known to activate preferentially to stimuli with low spatial frequencies and high temporal frequencies, and many studies have used these properties to vouch for or contradict a M-D deficit in dyslexia.23,33,34,42,44,7678 Nonetheless, there is not a definite consensus because for most frequency ranges, activation is not exclusive to this stream. In fact, the range of spatial frequencies used as a hallmark of M-D functioning has been a target for criticism.51,56 Another marker that has been used to claim M-D deficits in dyslexia is abnormal visual coherent motion (e.g., Refs. 2224, 26, 33, 78, 79). However, the reliability of this measure to assess M-D sensitivity has also been challenged.80 Thus, the validation of the magnocellular theory is undermined by a fundamental issue: the difficulty, or even the impossibility, of exclusively activating M-D stream. In order to overcome this difficulty, here we designed a battery of visuoperceptual tasks with different levels of M-D contribution. Therefore, having a battery of three tasks, we can establish a profile of low-level visual deficits in terms of a “gradient” of M-D recruitment, instead of relying on the assumption of exclusive activation of this stream. In this manner, we can think of our tasks as ranging from strong (speed discrimination) to weak (chromatic sensitivity) M-D involvement. According to the magnocellular theory, we found that the higher the M-D involvement, the higher the differences between groups. Therefore, using this procedure, we report compelling evidence for a preferential M-D deficit in children with dyslexia. 
To conclude, we demonstrate that speed discrimination thresholds are the ones that show the strongest correlation with reading, followed by the ISF thresholds. Notably, chromatic contrast sensitivity thresholds did not correlate with any of the reading measures. These results highlight the notion that the link between low-level visual function and reading is not generalized across different visual systems. This result is in agreement with studies both in individuals with dyslexia and in controls.20,28,36,37 Following the M-D gradient mentioned above, we found that the higher the involvement of M-D mechanisms in the administered tasks, the stronger the correlation to both accuracy and fluency indices. This result is also in accordance with the roles that the M-D system may play in reading-related tasks. These include accurate letter position encoding through precise shifts in visual attention,35,81,82 the ability to process information that changes rapidly over the course of time,64 or the rapid delivery of a low-pass representation of words to guide further processing.83 Actually, a very recent study84 showed that M-D stream training significantly improved reading fluency and reading comprehension in individuals with dyslexia, supporting the hypothesis of a causal link between M-D processing deficits and dyslexia. 
Finally, the link between low-level visual performance and reading is perhaps as important as the establishment of low-level visual deficits in dyslexia. In future studies, attention should be devoted to the understanding of how these particular visuoperceptual deficits underlie reading impairment. Only a clear unfolding of this issue can unequivocally establish those deficits as contributing to reading difficulties in dyslexia. Studies of indirect19,34,83,85 and direct interference (TMS)86 are already paving the way on this matter. 
Acknowledgments
Supported by the Foundation for Science and Technology Portugal under Grants PTDC/SAU-NSC/113471/2009, SFRH/BD/75083/2010, and UID/NEU/04539/2013–COMPETE, POCI-01-0145-FEDER-007440. 
Disclosure: A. Pina Rodrigues, None; J. Rebola, None; H. Jorge, None; M.J. Ribeiro, None; M. Pereira, None; M. van Asselen, None; M. Castelo-Branco, None 
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Figure 1
 
Schematic representation of the visual tests. (a) Representation of the location, at the horizontal meridian 0°, where the moving dots were presented in the speed discrimination task. Three additional meridians were tested (vertical 90°, tested at 10° of eccentricity; and oblique 45° and 135°, at 15° of eccentricity). The central cross represents the fixation cross. (b) Representation of the sizes and shapes of the nine locations (represented in different shades of gray and black) within the visual field where the gratings with intermediate spatial frequency were presented. Note that in the actual experiment the shaded areas and the separating lines were not present. The stimuli were shown at these locations against an overall gray background. The black square in the middle of the figure represents the fixation square. (c) Illustration of the stimuli used in the chromatic contrast sensitivity task (Cambridge Colour Test) representing a luminance noise stimulus with superimposed chromatic target (Landolt C shape, colored in red).
Figure 1
 
Schematic representation of the visual tests. (a) Representation of the location, at the horizontal meridian 0°, where the moving dots were presented in the speed discrimination task. Three additional meridians were tested (vertical 90°, tested at 10° of eccentricity; and oblique 45° and 135°, at 15° of eccentricity). The central cross represents the fixation cross. (b) Representation of the sizes and shapes of the nine locations (represented in different shades of gray and black) within the visual field where the gratings with intermediate spatial frequency were presented. Note that in the actual experiment the shaded areas and the separating lines were not present. The stimuli were shown at these locations against an overall gray background. The black square in the middle of the figure represents the fixation square. (c) Illustration of the stimuli used in the chromatic contrast sensitivity task (Cambridge Colour Test) representing a luminance noise stimulus with superimposed chromatic target (Landolt C shape, colored in red).
Figure 2
 
Performance of controls and dyslexics in the CCT-PD (top), ISF (middle), and LSD (bottom). Moving from top to bottom, note that dyslexics show normal chromatic contrast sensitivity, mildly impaired achromatic contrast sensitivity, and considerable speed discrimination impairment. (Box boundaries correspond to upper and lower 25th percentiles, outer bars to the 10th percentiles, and middle bar to the median).
Figure 2
 
Performance of controls and dyslexics in the CCT-PD (top), ISF (middle), and LSD (bottom). Moving from top to bottom, note that dyslexics show normal chromatic contrast sensitivity, mildly impaired achromatic contrast sensitivity, and considerable speed discrimination impairment. (Box boundaries correspond to upper and lower 25th percentiles, outer bars to the 10th percentiles, and middle bar to the median).
Figure 3
 
Scatter plots illustrating the correlations between the Accuracy and Fluency Indexes from the reading test with chromatic sensitivity (CCT-PD) and speed discrimination (LSD) perception thresholds. Controls (empty dots). Dyslexics (filled triangles).
Figure 3
 
Scatter plots illustrating the correlations between the Accuracy and Fluency Indexes from the reading test with chromatic sensitivity (CCT-PD) and speed discrimination (LSD) perception thresholds. Controls (empty dots). Dyslexics (filled triangles).
Table 1
 
Summary Statistics for the Two Groups of Participants
Table 1
 
Summary Statistics for the Two Groups of Participants
Table 2
 
Low-Level Visual Perception Thresholds of Children With and Without Dyslexia
Table 2
 
Low-Level Visual Perception Thresholds of Children With and Without Dyslexia
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