## Abstract

Developmental dyslexia (DD) is a heritable neurodevelopmental reading disorder that could arise from auditory, visual, and cross-modal integration deficits. A deletion in intron 2 of the DCDC2 gene (hereafter DCDC2d) increases the risk for DD and related phenotypes. In this study, first we report that illusory visual motion perception—specifically processed by the magnocellular-dorsal (M-D) stream—is impaired in children with DD compared with age-matched and reading-level controls. Second, we test for the specificity of the DCDC2d effects on the M-D stream. Children with DD and DCDC2d need significantly more contrast to process illusory motion relative to their counterpart without DCDC2d and to age-matched and reading-level controls. Irrespective of the genetic variant, children with DD perform normally in the parvocellular-ventral task. Finally, we find that DCDC2d is associated with the illusory motion perception also in adult normal readers, showing that the M-D deficit is a potential neurobiological risk factor of DD rather than a simple effect of reading disorder. Our findings demonstrate, for the first time, that a specific neurocognitive dysfunction tapping the M-D stream is linked with a well-defined genetic susceptibility.

## Introduction

The DCDC2 gene has been identified as 1 of the leading susceptibility genes in both developmental dyslexia (DD) and DD-related phenotypes (Deffenbacher et al. 2004; Meng et al. 2005; Harold et al. 2006; Schumacher et al. 2006; Brkanac et al. 2007; Wilcke et al. 2009; Newbury et al. 2011; Cope et al. 2012; Marino et al. 2012; Zhong et al. 2012; Powers et al. 2013) but also in reading abilities in the normal range (Lind et al. 2010; Scerri et al. 2011). Nevertheless, negative results for the association between DCDC2 and DD have also been reported (Ludwig et al. 2008; Paracchini et al. 2011; Becker et al. 2013). Data suggest that the DCDC2 gene is involved in neuronal migration (Meng et al. 2005; Burbridge et al. 2008; Massinen et al. 2011). The embryonic knockdown of the Dcdc2 protein function in rodent neocortical progenitor cells results in a disturbance in neuronal migration, when assessed both 4–7 days post-transfection (Meng et al. 2005) and postnatally in the cerebral cortex (Burbridge et al. 2008). However, recently, Che et al. (2014) found neuronal excitability as the main effect of Dcdc2 global deletion in mice and no neuronal migration deficits were found. The Dcdc2 protein subcellular localization is in the primary cilium (Massinen et al. 2011), which is an organelle with a role in cortical morphogenesis (Willaredt et al. 2008), and neurogenesis (Breunig et al. 2008), found in nearly all vertebrate cell types and tissues. The Dcdc2 protein affects ciliary morphology and several important signaling pathways (Massinen et al. 2011). A 168-base pair, purine-rich region located in intron 2 of the DCDC2 gene harboring a highly polymorphic, short tandem repeat (BV677278) was reported (Meng et al. 2005). This non-coding region contains 131 putative transcription factor binding sites; consistent with a role as a regulatory region, it is rather conserved across species (Meng et al. 2011). It has been shown that BV677278 specifically binds some unknown nuclear proteins expressed in the human brain and that it has the capacity for enhancer activity: BV677278 changes reporter gene expression from the DCDC2 promoter in an allele-specific manner (Meng et al. 2011). Recently, Powers et al. (2013) identified the BV677278-binding protein as the transcription factor ETV6, confirmed BV677278 as a regulatory element, and proposed a new name for BV677278 as “READ1” or “regulatory element associated with dyslexia 1.” As such, READ1 could substantially act as a modifier of the DCDC2 gene expression and thereby influence neuronal migration. Noteworthy, a naturally occurring deletion in intron 2 of the DCDC2 gene (hereafter DCDC2d), which encompasses the entire READ1 within its breakpoints, was found to be associated with DD and DD-related phenotypes (Harold et al. 2006; Brkanac et al. 2007; Wilcke et al. 2009; Cope et al. 2012; Marino et al. 2012), although negative findings have also been reported (Ludwig et al. 2008; Powers et al. 2013).

In adult healthy humans, the DCDC2 gene has been associated with fiber tracts connecting the left middle temporal gyrus with the angular and supramarginal gyri, to the superior longitudinal fasciculus, and to the corpus callosum (Darki et al. 2012). All these fiber tracts are commonly found altered in neuroimaging studies of reading and DD (Vandermosten et al. 2012; Wandell and Yeatman 2013). Noteworthy, DCDC2d has been associated with brain structural or functional measures in subjects with DD (Cope et al. 2012; Marino et al. 2014) and in healthy individuals (Meda et al. 2008; Marino et al. 2014). These latter findings offered an initial support for a specific role of DCDC2d in human brain morphology and function.

In this study, to better understand the role of DCDC2d in reading (dis)abilities and to unveil the pathways from gene to behavior, we investigated the genetic association of DCDC2d with a quantifiable DD-related intermediate phenotype. Intermediate phenotypes are helpful in investigating neurocognitive pathways and can constitute a more solid, alternative basis compared with behavioral phenotypes (Gottesman and Gould 2003; Gould and Gottesman 2006; Flint and Munafò 2007). An assumption of this approach is that the genetic determination of an intermediate phenotype is likely to be relatively less complex than that of the related behavioral/clinical phenotype, given that the latter incorporates multiple neural systems and summarizes the influences of both genes and environmental etiologic variables (Cannon 2005; Pennington 2006). Intermediate phenotypes may be, indeed, neurocognitive, neurophysiological, neurodevelopmental, biochemical, endocrinological, or neuroanatomical traits.

Extensive research has shown that the brain bases of both normal and impaired reading are distributed across complex neural networks (Wandell and Yeatman 2013). The nature of the cognitive bases of reading (dis)ability remains a matter of intense debate. A number of reports found that auditory-phonological processing is essential to reading (Goswami 2003, 2011) and that phonological deficits are consistently found in DD (Snowling 2001; Ziegler and Goswami 2005). Nevertheless, phonological deficits could be either primary or correlated with poor input tuning into the regions mediating grapheme–phoneme integration (Blau et al. 2009; Dehaene et al. 2010; Thiebaut de Schotten et al. 2014). Multiple neurocognitive domains, such as rapid auditory processing (Tallal 1980, 2004), spatial (e.g., Vidyasagar 1999; Hari et al. 2001; Franceschini et al. 2012; Zorzi et al. 2012; Ronconi et al. 2014; Ihnen et al. 2015), and non-spatial (Hari et al. 1999; Ruffino et al. 2010, 2014) attention, motion perception (Bavelier et al. 2002; Schneider and Kastner 2009) specifically processed by the magnocellular-dorsal (M-D) stream (e.g., Galaburda and Livingstone 1993; Walsh 1995; Stein and Walsh 1997; Stein and Talcott 1999; Laycock and Crewther 2008; Vidyasagar and Pammer 2010; Gori and Facoetti 2014; Gori, Cecchini et al. 2014), have been widely recognized as correlates of reading acquisition (Gabrieli 2009), reading failure (Reed 1989; Heiervang et al. 2002; Cohen-Mimran and Sapir 2007; Facoetti, Trussardi et al. 2010), and reading (dis)abilities prediction (Kevan and Pammer 2008; Facoetti, Corradi et al. 2010; Franceschini et al. 2012).

Imaging-related abnormalities associated with the DCDC2 gene have been found in brain areas relevant for the integration of auditory-language processes and, interestingly, in key nodes of the M-D stream. Motion is processed specifically by the M-D stream, which is blind to colors (Hubel and Livingstone 1990), and responds optimally to contrast differences, low spatial (Lee et al. 1990; Nowak et al. 1997) and high temporal frequencies (Kaplan et al. 1990; Lee et al. 1990). Even if the role of the magnocellular deficit in DD is still debated (Olulade et al. 2013), the M-D stream seems to be impaired in individuals with DD (Galaburda and Livingstone 1993; Stein and Walsh 1997; Stein and Talcott 1999; Laycock and Crewther 2008; Vidyasagar and Pammer 2010; Gori and Facoetti 2014). The other major parallel pathway of the visual system, that is, the parvocellular-ventral (P-V) stream, is instead intact (e.g., Pammer and Wheatley 2001; Kevan and Pammer 2008; McLean et al. 2011; Gori, Cecchini et al. 2014). The P-V pathway is characterized by both lower temporal resolution and superior sensitivity to high spatial frequencies, and it is also sensitive to color changes (Kaplan and Shapley 1986; Kaplan et al. 1990).

In this study, we tested illusory motion perception by 2 illusory phenomena. First, we employed the Rotating-Tilted-Lines Illusion (RTLI; Fig. 1A), which is the simplest pattern able to trigger illusory rotation in the presence of only radial expansion motion on the retina (Gori and Hamburger 2006). The misperception of motion seems to be caused by the aperture problem faced by the small receptive fields of the primary visual cortex (Gori and Yazdanbakhsh 2008; Yazdanbakhsh and Gori 2008). The illusory effect appears to be strongly reduced or even to disappear with isoluminant colors (Hamburger 2012). Our second motion illusion employed was the Accordion Grating Illusion (AGI; Fig. 1C) consisting in a square-wave grating which exhibits 2 distinct illusory effects (Gori et al. 2011, 2013; Yazdanbakhsh and Gori 2011). Approaching this pattern, it appears: 1) to expand only perpendicularly to the stripes while 2) the rigidity of the stripes is lost and a curvature is experienced. Also the origin of this illusory effect seems to rely on the aperture problem (introducing the concept of 3-dimensional aperture problem; Yazdanbakhsh and Gori 2011), and on the competition between motion signals originating from 2 different motion-processing units in V1 (Gori et al. 2011). Interestingly, AGI's illusory effect is weaker than RTLI's effect, fitting perfectly the role of internal control in our experiments. Illusory motion perception is processed by the V5/MT complex (Ruzzoli et al. 2011), which is a core, neural station of the M-D pathway. The RTLI and the AGI represent appropriate candidates for testing the functioning of this visual pathway. The choice of testing illusory motion is not only interesting for itself but it provides some advantages in comparison with testing the real motion perception. The main technical advantage is that the illusory motion requires more contrast than real motion to be perceived, which provided us a larger window to vary our independent variable. The direct consequence is having a more sensitive instrument to test the M-D pathway functionality. Moreover, most of the evidence for the visual M-D deficit in DD has derived from studies of coherent dot motion perception. However, the impairment in motion perception was only found in the presence of high external noise (Sperling et al. 2006). Our illusory motion tasks are the first able to measure the more dorsal portion of the M-D pathway, and they are also clearly independent from any noise exclusion mechanism.

Figure 1.

Psychophysical tasks. To test the magnocellular-dorsal (M-D) functioning, we used 2 illusory motion phenomena embedded in a similar task procedure: 1) the Rotating-Tilted Line Illusion (RTLI; A, B) and, 2) the Accordion Grating Illusion (AGI; C, D). Ten levels of contrast between the illusory figures and the background were used as stimuli for both the RTLI and the AGI task. To test the P-V functioning, we used a grating orientation identification task with 5 levels of superimposed random noise (E).

Figure 1.

Psychophysical tasks. To test the magnocellular-dorsal (M-D) functioning, we used 2 illusory motion phenomena embedded in a similar task procedure: 1) the Rotating-Tilted Line Illusion (RTLI; A, B) and, 2) the Accordion Grating Illusion (AGI; C, D). Ten levels of contrast between the illusory figures and the background were used as stimuli for both the RTLI and the AGI task. To test the P-V functioning, we used a grating orientation identification task with 5 levels of superimposed random noise (E).

In the present study, we set a 2-fold aim:

1. To demonstrate that DD is associated with an M-D deficit, we tested the performance in 2 illusory motion perception tasks able to measure the M-D functioning in children with DD, chronological-age controls and reading-level controls, irrespective of their genetic background (Study 1);

2. To demonstrate that DCDC2d is selectively associated with an impairment of the M-D visual stream, we compared the sensitivity with illusory motion perception (Spillmann 2009; Azzopardi and Hock 2011) in 2 groups of children with DD, with and without DCDC2d (hereafter DD+ and DD−, respectively) (Study 2). To strengthen our finding, we further compared illusory motion perception in normal readers with and without DCDC2d (hereafter NR+ and NR−, respectively) (Study 3). NR+ represents an ideal subgroup to test our hypothesis because according to the multifactorial threshold model of liability to DD, they present genetic alterations without having the full-blown picture of DD. This is the first study to investigate subjects with DD and normal readers with an identified element of genetic susceptibility (i.e., DCDC2d) at a neurophysiological level by means of an illusory motion perception task. To test the specificity of our finding, we concurrently tested the efficiency of the P-V pathway by measuring the ability to recognize an isoluminant grating orientation, in conditions of different levels of added noise (Kaplan and Shapley 1986; Kaplan et al. 1990).

## Materials and Methods

The protocol was approved by the Bioethics Committee of the Scientific Institute Eugenio Medea, Bosisio Parini, Lecco, Italy.

### Study 1

#### Participants

Children with a DSM-IV diagnosis of DD (American Psychiatric Association 1994) were recruited at our research center. Controls were collected from schools in the North of Italy. Children were included if they had: 1) normal IQ, and 2) no certification of a diagnosis of Specific Learning Disorder and/or Attention Deficit-Hyperactivity Disorder, and 3) no neurological or sensory disorders. Eleven children with DD (mean age 11 years; 3 females), and 19 controls (11 matched for chronological age, mean age 11 years; 6 females, and 8 matched for reading level, mean age 7 years; 5 females) participated to the study. Their parents gave written informed consent to participate. All children had normal or corrected-to-normal visual acuity.

#### Assessment

Each child included in the study was evaluated with neuropsychological tests and computer-based psychophysical experiments.

Neuropsychological tests investigated: 1) cognitive ability, as assessed by 2 subtests of the Wechsler Intelligence Scale for Children, third edition—WISC-III, that is, Vocabulary and Block Design (Wechsler 2006). These 2 tests were used to provide a prorated, full-scale IQ score, since they show a high correlation (r) with, respectively, verbal IQ (r = 0.85; Wechsler 2006), and performance IQ (r = 0.73; Wechsler 2006). Participants were included if the mean standard score of Vocabulary and Block Design subtests was >7 (mean = 10, SD = 3), regardless of their reading performance; 2) reading, as assessed by text, word, and non-word reading tasks; speed (seconds) and accuracy (number of errors) were recorded and scores were standardized on grade norms (Sartori et al. 1995).

Computer-based psychophysical experiments included:

Figure 1D depicts the AGI task (Gori et al. 2011, 2013; Yazdanbakhsh and Gori 2011). Ten Michelson's contrast values (0, 2, 5, 10, 15, 20, 25, 30, 35 and 40%) between the AGI and the background were used. All these stimuli contracted and expanded continuously on the screen varying in size in the range of 12.7° to 14.6° with a speed of 5.33 mm/s. Before the experiment started, the subject familiarized with a 98% contrast AGI and with an isoluminant colored version watching these patterns contracting and expanding on the screen. All participants reported to see both illusory effects in the high-contrast AGI and no illusory effects but only radial expansion in the isoluminant AGI (Fig. 1D). Given that AGI was proposed in our experiments as an internal control for the RTLI experiment, it was collected only in children with DD and chronological-age controls.

### Study 2

#### Participants

Children (mean age 12 years; 9 females) with a DSM-IV diagnosis of DD (American Psychiatric Association 1994) were recruited from a sample of an ongoing genetic study cohort, which has been genotyped for READ1 of the DCDC2 gene for genetic association tests (Marino et al. 2012). There was no overlap with children with DD recruited in Study 1. Their parents gave written informed consent to participate. All children had normal or corrected-to-normal visual acuity.

#### Assessment

Neuropsychological tests were the same of Study 1.

Computer-based psychophysical experiments included: Figure 1E depicts the P-V task. The high spatial colored isoluminant grating with 4 possible degrees of rotation were superimposed with different levels of colored, random, isoluminant noise. This task presents all the characteristics to tap the P-V pathway functionality (Kaplan and Shapley 1986; Kaplan et al. 1990).

1. The RTLI task (see “Materials and Methods” section, “Study 1—Assessment” paragraph). Given that AGI was proposed in Study 1 as an internal control for the RTLI experiment, it was not collected again in Studies 2 and 3.

2. The P-V task: the grating orientation identification.

##### Apparatus, stimuli, and procedure

Visual stimuli were presented in the center of the computer screen. The experiment was carried out in a dimly lit (luminance of 1.5 cd/m2) and quiet room. Participants were seated 40 cm away from the screen. The fixation point consisted of a cross displayed at the center of the screen (0.5°). Stimuli were circular isoluminant grating (7.4°, 40 cd/m2) characterized by high spatial frequency (1.4 cycles/degree). The grating were oriented in 4 possible degrees of rotation (i.e., 40°, 85°, 130° and 175°, chance level = 0.25). Five levels of colored random isoluminant noise were superimposed to the stimulus ranging from 0 (absence of noise) to 4 (maximum level of noise) as shown in Figure 1E. Participants viewed each stimulus binocularly. Each trial began with the fixation mark. Participants were instructed to keep their eyes on the fixation mark throughout the duration of the trial. After 500 ms, the stimulus was displayed for 102 ms. Participants were instructed to identify the grating orientation among 4 possible degrees of rotation displayed on the screen until the response was given (Fig. 1E). Each participant was instructed to use all the time he/she needed to identify the target as accurately as possible. Responses were pointed by participants and entered by the experimenter by pressing the corresponding keys; no feedback was provided. The experimental session consisted of 40 trials (4 directions × 5 different noises × 2 repetitions). The noise level was the independent variable whereas the response accuracy was the dependent variable.

### Study 3

#### Participants

Normal readers were recruited from a genetic study on emotional and behavioral problems in a general population sample of adolescents (Frigerio et al. 2006; Nobile et al. 2007) who were genotyped for READ1 of the DCDC2 gene. For the present study, the same inclusion criteria of Study 1 were adopted. Twenty-three subjects (mean age 21 years, 14 females), 11 NR+ and 12 NR−, gave written informed consent to participate. All participants had normal or corrected-to-normal visual acuity.

#### Assessment

Each subject included in the study was assessed by the same neuropsychological tests of Study 1, with the exception of cognitive ability, which was assessed by same subtests of the Italian Wechsler Adult Intelligence Scale—Revised (WAIS-R; Wechsler 1981).

## Results

### Study 1

With regard to the RTLI task, all children reached the 100% of detection for the stimulus at 1% Michelson's contrast, showing that the contrast detection in this specific condition did not differ between groups. The individual curves, representing the performance at the illusory effect task, in which the observers had to report whether rotation was perceived, were fitted by a logistic function for each group. The upper bound was set at 1, and the lower bound at y0 = 0, where y = 0 means that the illusory rotation was never perceived, and y = 1 that it was always perceived. The only free parameters of the function were b (the function slope) and t (the 50% threshold). The resulting logistic function (already used in Gori et al. 2008; Giora and Gori 2010; Gori and Spillmann 2010; Ronconi et al. 2012) is as follows:

(1)
$y=1/1+e−b(x−t)$

In this equation, x represents the percentage of contrast increment between the RTLI and the background, and y the relative response frequency.

For each group, the means of the individual threshold and slope were plotted (Fig. 2A, B). The 50% mean threshold for the children with DD group corresponded to a contrast of 4.52%, of 1.58% for the chronological-age, and of 1.35% for reading-level control group. The means' ratio was 2.86 between DD and chronological-age groups and 3.35 between DD and reading-level groups. Children with DD needed more than the double of the contrast to perceive the illusion even if the threshold of the contrast detection did not differ in each group. The difference among the 3 groups' thresholds, measured by a one-way ANOVA, was statistically significant (F2,27 = 14.77, P < 0.05). Also the slopes of the fitted curves for each group differed significantly (F2,27 = 3.48, P < 0.05), showing how the illusory perception changed differently in the 3 groups as a function of the contrast. Planned comparisons showed that children with DD were significantly different from chronological-age and reading-level control groups on both threshold (t13.94 = −4.25, P < 0.05 and t14.69 = −4.44, P < 0.05, respectively; Figure 2A) and slope (t10.24 = 2.28, P < 0.05 and t7.10 = 2.43, P < 0.05, respectively; Figure 2B). The 2 control groups did not differ for neither threshold (t17 = −0.51, P > 0.05; Figure 2A) nor slope (t17 = 0.55, P > 0.05; Figure 2B).

Figure 2.

Study 1 results. The 50% threshold mean for the RTLI task in the 3 groups of children (DD = developmental dyslexia; CA = chronological-age controls; RL = reading-level controls) (A). The slope mean of the fitted function for the RTLI in the 3 groups (B). The 50% threshold mean (C) and the slope mean (D) of the fitted function for the AGI task in the DD and CA groups. Error bars represent the standard error and * represents a significant difference (P < 0.05).

Figure 2.

Study 1 results. The 50% threshold mean for the RTLI task in the 3 groups of children (DD = developmental dyslexia; CA = chronological-age controls; RL = reading-level controls) (A). The slope mean of the fitted function for the RTLI in the 3 groups (B). The 50% threshold mean (C) and the slope mean (D) of the fitted function for the AGI task in the DD and CA groups. Error bars represent the standard error and * represents a significant difference (P < 0.05).

In the AGI task, all children, regardless the group, reached the 100% of detection for the AGI stimulus at 2% of contrast, showing how the contrast detection in this specific condition was not different between children with DD and chronological-age controls. The individual curves for the illusory effect task in the 2 groups were fitted by the same logistic function employed in the RTLI task. The 50% threshold for the chronological-age controls corresponds to a contrast of 3.56%, whereas the threshold for children with DD equals to 12.63%. The resulting ratio is 3.55. The difference between the 2 groups’ thresholds is statistically significant (t11.97 = −3.87, P < 0.05; Figure 2C). The slopes of the fitted curves for the 2 groups also differed significantly (t20 = 2.37, P < 0.05; Figure 2D), showing how the illusory perception changed differently in each group as a function of the contrast. Children with DD needed more contrast to perceive the illusion although the contrast detection threshold did not differ between the groups.

These data show an M-D deficit in children with DD, who require more information (luminance difference) to process the illusory deformation. These results cannot be attributed to a deficit in the perceptual-noise exclusion (Sperling et al. 2005, 2006) in DD because no noise at all was present in the stimulation. Finally, the AGI showed a higher contrast threshold than the RTLI supporting the latter as a valid internal control of our experiment. The difference in thresholds between the 2 tasks, and the similar ratios found between children with DD and controls were both coherent with the different strength of the 2 motion illusions and confirmed that the children performed the task based on the illusory effect and not on the visibility of the pattern.

### Study 2

No statistically significant differences were found in the neuropsychological measures between children with DD of Studies 1 and 2. One-way ANOVA was used to compare means of RTLI among children with DD of Study 2 (n = 26), the chronological-age and reading-level controls of Study 1. Children with DD needed more than the double of the contrast to perceive the illusion, even if the threshold of the contrast detection did not differ among the 3 groups. The 50% mean threshold for the group of children with DD corresponded to a contrast of 4.32%, leading to a means' ratio of 2.73 and 3.20 with the chronological-age and reading-level control groups, respectively. The difference among the 3 groups' thresholds was statistically significant (F2,42 = 4.21, P < 0.05). The slopes of the fitted curves for the 3 groups also differed significantly (F2,42 = 3.56, P < 0.05), showing how the illusory perception changed differently in each group as a function of the contrast. Planned comparisons showed that children with DD were significantly different from both chronological-age and reading-level control groups on threshold (t30.44 = 3.19, P < 0.05 and t30.97 = 3.39, P < 0.05, respectively). Regarding the slope, children with DD were significantly different from the reading-level matched group (t8.40 = −1.93, P < 0.05), but not from the chronological-age control group (t13.45 = −1.62, P > 0.05).

Figure 3.

Study 2 results. The 50% threshold mean for the RTLI task in the 4 groups of children (DD+ = children with developmental dyslexia and DCDC2d; DD− = children with developmental dyslexia without DCDC2d; CA = chronological-age controls; RL = reading-level controls) (A). The slope mean of the fitted function for the RTLI in the 4 groups (B). Error bars represent the standard error and * represents a significant difference (P < 0.05).

Figure 3.

Study 2 results. The 50% threshold mean for the RTLI task in the 4 groups of children (DD+ = children with developmental dyslexia and DCDC2d; DD− = children with developmental dyslexia without DCDC2d; CA = chronological-age controls; RL = reading-level controls) (A). The slope mean of the fitted function for the RTLI in the 4 groups (B). Error bars represent the standard error and * represents a significant difference (P < 0.05).

Interestingly, the means' ratio between DD+ and DD− was 2.42. DD+ needed more than the double of contrast to perceive the illusion. The difference between the 2 groups' thresholds was statistically significant (t12.46 = 2.34, P < 0.05; Figure 3A). Also the slopes of the fitted curves for the 2 groups differed significantly (t13.05 = −1.83, P < 0.05; Figure 3B), showing how the illusory perception changed differently in the 2 groups as a function of the contrast.

The same analysis was applied to the P-V dataset. The curves, representing the degree of grating rotation discrimination, were fitted by the above-reported logistic function (see Results section of Study 1) for DD+ and DD−. In this case, x represents the noise level and y the relative response frequency. The 50% mean threshold for DD+ corresponded to a noise level of 3.23% and of 3.65% for DD−. The means' ratio was 0.88. No significant difference either between the 2 groups’ thresholds (t22 = −0.60, P > 0.05) or between the  2 slopes of the fitted curves (t22 = 0.99, P > 0.05) was found.

### Study 3

No statistically significant differences between groups for the neuropsychological measures were observed. For each group, RTLI means of the threshold and of the slope were plotted (Fig. 4A, B, respectively). The 50% mean threshold corresponded to a contrast of 2.42% for NR− and of 4.90% for NR+; the means' ratio was 2.02. NR+ needed more contrast to perceive the illusion, even if the threshold of the contrast detection did not differ in the 2 groups. The difference between the 2 groups' thresholds was statistically significant (t18 = 2.34, P < 0.05; Figure 4A). The slopes of the fitted curves for the 2 groups also differed significantly (t18 = −2.44, P < 0.05; Fig. 4B), showing how the illusory perception changed differently in the 2 groups as a function of the contrast.

Figure 4.

Study 3 results. The 50% threshold mean for the RTLI task in the 2 groups of young adults (NR+ = normal readers with DCDC2d; NR− = normal readers without DCDC2d) (A). The slope mean of the fitted function for the RTLI in the 4 groups (B). Error bars represent the standard error and * represents a significant difference (P < 0.05).

Figure 4.

Study 3 results. The 50% threshold mean for the RTLI task in the 2 groups of young adults (NR+ = normal readers with DCDC2d; NR− = normal readers without DCDC2d) (A). The slope mean of the fitted function for the RTLI in the 4 groups (B). Error bars represent the standard error and * represents a significant difference (P < 0.05).

The same analysis was applied to the P-V dataset. The 50% mean threshold corresponded to a noise level of 4.19% for NR−, and of 3.49% for NR+. The means' ratio was 1.20. Both thresholds (t21 = −1.42, P > 0.05) and slope (t10.05 = −0.91, P > 0.05) did not statistically differ between the 2 groups.

In addition, further analyses were carried out in the children with DD of Study 2 and the adults without DD of Study 3. Although the 2 groups differ for age, which makes the reliability of this analysis weaker, the rationale is to check how much of the observed M-D deficits can be explained by the DCDC2d, and how much additional variance can be explained by the diagnosis of DD. After controlling for chronological age by using 3-step fixed-entry multiple regression analysis, DCDC2d significantly explained RTLI threshold (r2 change = 0.20, P < 0.05) whereas no additional variance was explained by the DD diagnosis. Moreover, after controlling for chronological age by using 3-step fixed-entry multiple regression analysis, DCDC2d significantly explained also RTLI slope (r2 change = 0.17, P < 0.05), whereas no additional variance was explained by the DD diagnosis.

## Discussion

In Study 1, we investigated the performance of children with DD, chronological-age and reading-level controls in 2 motion perception tasks tapping the M-D stream. Both tasks tested the sensitivity to illusory motion perception. Motion illusion is a noninvasive, low-cost tool, for understanding the neurobiology of the visual system (e.g., Azzopardi and Hock 2011; Spillmann 2009 for a review). It refers to a perception of motion that is absent (e.g., Gori et al. 2006; Kumar and Glaser 2006; Troncoso et al. 2008; Ashida et al. 2012; Otero-Millan et al. 2012) and/or different in direction, strength, etc. (e.g., Lorenceau et al. 1993; Liden and Mingolla 1998; Pinna and Brelstaff 2000; Gori and Hamburger 2006; Gori et al. 2010; Gori et al. 2011; Otero-Millan et al. 2011) from what is present in the physical stimulus. Our findings show that the RTLI tags the M-D deficit in DD and can be considered an appropriate neurocognitive “proxy” of this visual stream sensitivity, because it tests for characteristics that are processed specifically by the M-D pathway, that is, motion, high temporal frequency and luminance difference. The interest of the AGI experiment was not only to replicate the previous results but also to provide an internal control that assured the reliability of the participants’ response in the illusory perception task.

To unveil pathways between DCDC2d and behavior, we were interested in testing the genetic association with a quantifiable DD-related intermediate phenotype. We hypothesized that DCDC2d might be selectively associated with an impairment of the M-D visual stream since the brain areas associated with the DCDC2 gene are compatible with those underlying the dorsal portion of the M-D pathway (e.g., Darki et al. 2012; Vandermosten et al. 2012; Wandell and Yeatman 2013). We therefore studied the performance of both children with DD and young normal readers grouped according to the presence/absence of the DCDC2d in 2 visual perception tasks. The sensitivity to illusory motion perception (i.e., the RTLI task) was used to test the M-D stream, whereas the ability to recognize an isoluminant grating orientation, in conditions of different levels of added noise (Kaplan and Shapley 1986; Kaplan et al. 1990), was concurrently analyzed to assess the efficiency of the P-V pathway.

Our data show that subjects with DCDC2d needed more contrast to process the illusory rotation in the RTLI task, whereas they perform similarly to the individuals without this genetic variant in the grating orientation identification task, irrespective of their diagnostic status. Moreover, DD+ showed a significant worse performance in the M-D task in comparison with DD−. These data suggest that this genetic risk variant might impair the function of the M-D pathway and that it might have specific downstream effects, leaving the P-V pathway undamaged. The M-D deficit was significantly explained by the presence/absence of the DCDC2d showing an association between this genetic variant and the M-D pathway. Finally, given that the P-V task—which is a perceptual-noise exclusion paradigm—did not differ significantly among the groups, our findings cannot be attributed to a deficit in the perceptual-noise exclusion (Sperling et al. 2005, 2006).

Our study is also relevant in unveiling possible genetic basis of the illusory motion perception. It is known that a small percentage of the population hardly perceive the motion illusions (Billino et al. 2009 for humans; Gori, Agrillo et al. 2014 for fish). Fraser and Wilcox (1979) showed that the ability to perceive illusory motion could be genetically determined but which genes could contribute to its etiology is still unknown. Our results pave the way to study the genetic contribution in perceiving illusory motion, and they would potentially be an important contribution in better understanding the development of the visual system. These findings show that visual motion deficits, which have been found in DD (Galaburda and Livingstone 1993; Stein and Walsh 1997; Stein and Talcott 1999; Laycock and Crewther 2008; Vidyasagar and Pammer 2010; Gori and Facoetti 2014), are specifically linked to the DCDC2d both in subjects with DD and in a normal-reading population, validating the multifactorial threshold model of inheritance of reading (dis)ability and the generalist gene hypothesis (Plomin and Kovas 2005). Our findings are consistent with a recent study in which it has been found that young adults with DD and DCDC2d present motion blindness (Morrone et al. 2011).

By showing that DCDC2d is associated with worse illusory motion perception in normal-reading young adults, we provide strong evidence that this correlation is not the result of reduced exposure to print and/or different reading level, as it might be the case if it was found in subjects with DD. The association that we found in our dataset is less likely to be biased by either inadequate reading acquisition (e.g., Blau et al. 2009; Dehaene et al. 2010), or treatments or compensation strategies that have been shown to change the neural substrate of subjects with DD (e.g., Eden et al. 2004; Franceschini et al. 2013).

The involvement of the M-D pathway in DD is well known (Stein and Walsh 1997; Stein and Talcott 1999; Gori and Facoetti 2014 for reviews), independently from the genetic susceptibility background. There is strong evidence that subjects with DD often suffer from an impaired development of the M cells in the lateral geniculate nucleus (Livingstone et al. 1991; Pammer and Wheatley 2001; Gori, Cecchini et al. 2014). The cortical dorsal “where” pathway is dominated by the M input, and abnormalities have been found in subjects with DD in this pathway as well. Specifically, anomalies have been reported in the primary visual cortex—V1 (Lovegrove et al. 1980; Chase and Jenner 1993; Mason et al. 1993; Cornelissen et al. 1995; Felmingham and Jakobson 1995; Talcott et al. 1998; Bednarek and Grabowska 2002; Edwards et al. 2004), in the extra-striate visual motion area—V5/MT (Cornelissen et al. 1995; Richardson et al. 2000; Talcott et al. 2000; Hill and Raymond 2002; Downie et al. 2003; Samar and Parasnis 2005), in the posterior parietal cortex and in the prefrontal cortex (Rao 1997).

Our study takes also an important step forward in order to disentangle the complex pathways that connect genetic variants to measures of specific, reading-related, neurocognitive processes, and to understand the effect that the DCDC2 gene exerts on human brain development (Harold et al. 2006; Brkanac et al. 2007; Meda et al. 2008; Wilcke et al. 2009; Marino et al. 2012). Since the DCDC2 gene is involved in neuronal migration (Meng et al. 2005; Burbridge et al. 2008), and in cortical morphogenesis and neurogenesis (Breunig et al. 2008; Willaredt et al. 2008), it is plausible that a variant of this candidate gene could selectively impinge on the development of the M-D pathways at early stages of the neural patterning, and, if combined with other risk factors, that it could later affect the reading acquisition process. The M cells play, indeed, a crucial part in signaling letter order (Stein 2012).

In summary, our findings provide the first evidence for a neurocognitive deficit tapping the M-D pathway both in subjects with DD and in normal readers with a genetic susceptibility. Our results demonstrate that cognitive intermediate phenotypes may be crucial to disentangle the role of genetic variants in the etiology of complex cognitive function, such as reading. To understand the function of neuronal migration genes and their relationships with cognitive developmental vulnerability and to establish links between such susceptibility variants and neuroanatomical phenotypes must be of utmost importance for future research.

## Funding

This work was supported by the “International Scientific and Technological Cooperation projects in the areas of food and agriculture, energy and the environment, health and advanced manufacturing,” by Lombardy Region, 2010 (Grant Number: SAL-57).

## Notes

We thank all subjects who took part in this study. We are also grateful to Vittoria Trezzi for reading and commenting the manuscript. Conflict of Interest: None declared.

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