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Research Article  |   June 2010
Asymmetry of visual sensory mechanisms: Electrophysiological, structural, and psychophysical evidences
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Journal of Vision June 2010, Vol.10, 26. doi:10.1167/10.6.26
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      Maria Fátima Silva, Catarina Mateus, Aldina Reis, Sandrina Nunes, Pedro Fonseca, Miguel Castelo-Branco; Asymmetry of visual sensory mechanisms: Electrophysiological, structural, and psychophysical evidences. Journal of Vision 2010;10(6):26. doi: 10.1167/10.6.26.

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

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Abstract

Psychophysical visual field asymmetries are widely documented and have been attributed to anatomical anisotropies both at the retinal and cortical levels. This debate on whether such differences originate within the retina itself or are due to higher visual processing may be illuminated if concomitant anatomical, physiological, and psychophysical measures are taken in the same individuals. In the current study, we have focused on the study of objective functional and structural asymmetries at the retinal level and examined their putative correlation with visual performance asymmetries. Forty healthy participants (80 eyes; 13 male and 27 female subjects) were included in this study. Objective functional/structural asymmetries were probed using the multifocal electroretinogram (mfERG) technique and optical coherence tomography (OCT), respectively. A nasal/temporal pattern of asymmetry (nasal visual hemifield disadvantage) was found for all methods (retinal thickness, contrast sensitivity, and mfERG P1 amplitude). Furthermore, superior/inferior asymmetries could be documented only with psychophysics and structural measures. These patterns likely arise at different levels of the retina as inferred by partly independent correlation patterns. We conclude that patterns of structural/functional asymmetries arise at different levels of visual processing with a strong retinal contribution.

Introduction
Spatial asymmetry in the neural density and population responses of visual neurons may lead to psychophysical spatial anisotropies. Even in normal subjects, visual spatial performance is indeed asymmetrical (Carrasco, Giordano, & McElree, 2004; Carrasco, Talgar, & Cameron, 2001; Silva et al., 2008). A wide range of tasks has proven to yield superior/inferior anisotropies (Altpeter, Mackeben, & Trauzettel-Klosinski, 2000; Edgar & Smith, 1990; He, Cavanagh, & Intrilligator, 1996; Levine & McAnany, 2005; McAnany & Levine, 2007; Previc, 1990), all suggesting better performance in the superior hemiretina (inferior visual field) over the inferior hemiretina (superior visual field). Although some of these performance differences have been attributed to cortical processing, functional retinal asymmetries could also be documented. Accordingly, Miyake, Shiroyama, Horiguchi, and Ota (1989) have demonstrated an asymmetry of the focal electroretinogram (ERG) in the human macular region, with disadvantage of the inferior retina. This asymmetry was also confirmed by Nagatomo, Nao-i, Mariuiwa, Arai, and Sawada (1998), using mfERG in normal subjects. 
Nasal/temporal asymmetries have also been documented namely in hyperacuity tasks (Fahle & Schmid, 1988). We have previously documented a disadvantage of the temporal retina (nasal hemifield), using a contrast sensitivity CS task, with gratings at 3.5 cycles per degree (cpd). This retinal anisotropy could be functionally separated from a right cortical hemispheric dominance pattern (Silva et al., 2008). Concerning objective electrophysiological data on naso/temporal asymmetries, early studies used focal cone ERGs (e.g., Miyake, 1990; Miyake et al., 1989). Interestingly, distinct patterns of nasal/temporal differences are found concerning the amplitude of focal and multifocal oscillatory potentials (OPs), such that OPs in the temporal retina are larger than those in the nasal retina (Bearse, Shimada, & Sutter, 2000; Fortune, Bearse, Cioffi, & Johnson, 2002; Miyake, 1990; Miyake et al., 1989; Rangaswamy, Hood, & Frishman, 2003; Wu & Sutter, 1995). This pattern is more conspicuous and opposite to the asymmetry observed for the P1 wave amplitude (see normative data in the studies of Kondo et al., 1996; Nagatomo et al., 1998; Parks et al., 1996). The study of Sutter and Tran (1992) was particularly revealing, since a nasal/temporal asymmetry was observed in all subjects with higher response densities in the nasal retina (temporal hemifield) within the central 23° outside the blind spot. The implicit time topography of mfERG has been less explored (see Parks et al., 1996 and Seeliger, Kretschmann, Apfelstedt-Sylla, & Zrenner, 1998 work in normal control groups). 
It is unknown whether such differences originate within the retina itself or are due to higher visual processing. Some answers to this question have been suggested by studying the standing potential of the eye (Skrandies & Baier, 1986), which reflects the function of the retinal pigment epithelium and is also larger in the superior retina; or by the anatomical asymmetry of the human retina, since it is known for a long time that there is a higher density of ganglion cells in the superior retina (Croner & Kaplan, 1995; Curcio & Allen, 1990; for cone data, see Curcio, Sloan, Kalina, and Hendrickson, 1990). It is also known that, at equivalent eccentricities, cone density is higher in nasal compared to temporal retina (Curcio et al., 1990; Curcio, Sloan, Packer, Hendrickson, & Kalina, 1987; Jonas, Schneider, & Naumann, 1992), as well as for ganglion cells (Curcio & Allen, 1990). 
Scarce data are available concerning direct comparison of relationships between local psychophysical and mfERG measures. Most studies have only examined eccentricity-dependent psychophysical performance (Seiple & Holopigian, 1996; Seiple, Holopigian, Szlyk, & Wu, 2004; Virsu & Rovamo, 1979, see also references therein). Seiple et al. (2004) mapped acuity, CS, and temporal sensitivity in terms of retinal eccentricity and meridian but did not study specifically visual field VF asymmetries. They also compared psychophysical data with local electrophysiological data and to Humphrey VF thresholds. 
The focus of this study was to probe objective functional and structural asymmetries at the retinal level and examine their putative correlation with visual performance asymmetries. Visual CS was examined using intermediate spatial frequency (ISF) 3.5 cpd stimuli (Silva et al., 2008). In this study, we separated for the first time retinal and cortical mechanisms underlying psychophysical asymmetries of visual CS. Retinal function was objectively assessed by using the multifocal ERG (mfERG, Castelo-Branco et al., 2007; Hood, 2000; Lam, 2005; Sutter, 2001; Sutter & Tran, 1992) and thickness of neural layers by optical coherence tomography (Stratus OCT3) to probe whether superior and nasal quadrants were thickest (Castelo-Branco et al., 2007; Chan, Duker, Ko, Fujimoto, & Schuman, 2006) and correlated with psychophysical function. 
Material and methods
Participants
Forty healthy participants (80 eyes; 13 male and 27 female subjects) with mean age of 43 ± 16 years were included in this study. They were submitted to a complete ophthalmic examination, including best-corrected visual acuity (VA-Snellen chart), IOP measurement (Goldman applanation tonometer), slit lamp biomicroscopy, and fundus examination (Goldman lens). Central visual (macular) function was tested by mfERG and ISF test, and macular thickness was determined by OCT. 
Exclusion criteria included the following: cataract or other eye disease that might interfere with fundus examination, retinal diseases, or optic nerve pathology, and high emmetropia (sphere dpt > 4 and cylinder dpt > 2). In this study, all subjects were right-handed and naive to the purpose of the tests performed, and had normal best corrected visual acuity. 
The study followed the tenets of the Declaration of Helsinki. Informed consent was obtained from each patient after procedures of the research had been fully explained. 
Optical coherence tomography
Optical coherence tomography (OCT) is a high-resolution cross-sectional imaging technique that allows in vivo measurement of tissue thickness. We have used an OCT device (Stratus OCT3, Carl Zeiss Meditec, Dublin, CA, USA) to obtain cross-sectional images centered in the macula (Brancato & Lumbroso, 2004; Castelo-Branco et al., 2007; Eriksson & Alm, 2009; Polito, Del Borrello, Isola, Zemella, & Bandello, 2005) with axial resolution ≤10 μm, transversal resolution of 20 μm, and 2 mm of longitudinal scan range. The Fast Macular Thickness Protocol (FMTP) was used to obtain macular thickness measurements, which we will refer to retinal thickness (RT) measures. This measure does take into account only the neural layers of the retina. Using FMTP, 6 radial, 6 mm in length, line scans, 30° apart and of 128 A-scans each, were obtained in 1.92 s. 
Stratus OCT 3 software calculates retinal thickness as the distance between the vitreoretinal interface and the junction between the inner and outer segments of the photoreceptors, which is just above the retinal pigment epithelium. Three concentric circles with default diameters of 1 mm (3.3°), 3 mm (3.3°–10°), and 6 mm (10°–20°), were used to divide the macular thickness map into three zones: fovea (Zone 1), inner macula (Zone 2), and outer macula (Zone 3), with the aim of verifying retinal morphometric asymmetries at different eccentricities (see Figure 1). 
Figure 1
 
Layout of the OCT zones where RT was analyzed.
Figure 1
 
Layout of the OCT zones where RT was analyzed.
Electrophysiological recordings
We recorded mfERG with a RETIscan System (Roland Consult, Wiesbaden, Germany). The stimulus used in the mfERG consisted of 61 hexagons, covering a visual field of up to 30° of radius and presented on a 20-inch monitor at a viewing distance of 33 cm. Maximum luminance was 120 cd/m2. The hexagon areas increased with eccentricity in order to compensate for local differences in signal amplitude due to differences in cone density across the retina (leading to a fourfold change in hexagon area size). Each hexagon was temporally modulated between light and dark according to a binary m-sequence (frame rate: 60 Hz). Observers were instructed to fixate a small red cross in the center of the stimulus. Fixation was continuously checked by means of online video monitoring during the approximately 8-min recording sessions. To improve fixation stability, sessions were broken into 47-s segments and 8 trials were recorded in total. Signals were amplified with a gain of 100,000 and band-pass filtered (5–100 Hz). 
We used DTL fiber electrodes (recording electrodes), after a light adaptation of 10 min and pupil dilation with tropicamide 1%. The reference and ground electrodes were attached to the ipsilateral outer canthus and forehead, respectively. The surface electrode impedance was less than 10 kΩ. Refractive errors were corrected. Analyses were performed with the system software (RETIscan; Roland). First-order kernels were used for mfERG evaluation. First-order kernels were analyzed because of their closer correlation with the function of the outer retina and to avoid temporal adaptation mechanisms that are generally considered to influence higher order kernel analyses (Hood, Seiple, Holopigian, & Greenstein, 1997). The local ERG responses were normalized by the area of the stimulus delivery in order to obtain a density response (nV/deg2). For analysis of mfERG data, the peak amplitude of P1 (defined as the difference between N1 and P1 amplitudes) of each hexagon was calculated. 
Local 61 mfERG responses were also divided in five regional areas in order to evaluate these asymmetries at distinct eccentricities (see Figure 2 and Supplementary Material): Zone 1 (4.4° diameter), Zone 2 (4.4°–13.6°), Zone 3 (13.6°–25.8°), Zone 4 (25.8°–40.8°), and Zone 5 (40.8°–58.7°). 
Figure 2
 
Layout of local stimulus hexagons and division in five analysis zones, according to eccentricity with Zone 1 being the central region.
Figure 2
 
Layout of local stimulus hexagons and division in five analysis zones, according to eccentricity with Zone 1 being the central region.
To perform spatial asymmetry analysis, central region, blind spot region, and horizontal or vertical midline regions were excluded (for testing superior/inferior or nasal/temporal asymmetries, respectively), to prevent contribution of regions that are irrelevant to the concept of asymmetry or (in the case of the blind spot) may even lead to erroneous results (see Figure 3). 
Figure 3
 
Scheme of analyzed asymmetries, white regions have been excluded from the analysis (see text).
Figure 3
 
Scheme of analyzed asymmetries, white regions have been excluded from the analysis (see text).
Intermediate spatial frequency (ISF) contrast sensitivity test
We have applied CS multiple interleaved staircase testing at multiple locations, where stimuli were patches of 3.5 cpd of vertically oriented sinusoidal gratings and 0-Hz temporal frequency (Maia-Lopes et al., 2008; Silva et al., 2005, 2008), displayed on a gamma-corrected 21-inch Trinitron GDM-F520 Sony color monitor (frame rate of 100 Hz) at a viewing distance of 36 cm. Standard voltage–luminance curves were measured for each phosphor with software and hardware (including a Minolta colorimeter) provided by CRS (CRS/VSG 2/5 graphics card, Cambridge Research Systems, Rochester, UK), which ensured gamma correction. Background luminance was 51 cd/m2
Luminance contrast or modulation of the stimulus was expressed according to Michelson luminance contrast (%) = 100 * (L maxL min) / (L max + L min). An adaptive logarithmic staircase strategy was used to obtain psychophysical thresholds. Staircases were run for a total of four reversals, with the contrast at the final two reversals being averaged to estimate the contrast threshold. Results were expressed in terms of decibels (dB), dB = 20 * log (1/c), with c = Michelson luminance contrast (%). 
This spatial testing procedure was performed monocularly, and both eyes were tested in all participants, the first eye being randomly chosen (since ocular dominance does not appear to affect VF test results, see Spry, Furber, & Harrad, 2002). Subjects were instructed to fixate a black square (1° × 1°) in the center of the screen and report the presence of vertical “striped” targets (detection task) by means of a button press. Stimulus duration was 200 ms and ISI was jittered between 2300 and 2800 s. Participants reliability was evaluated by the inclusion of false positive and negative “catch trials”, and all results with false positive and false negative errors ≥33% were excluded, according to standard criteria (Caprioli, 1991; Clement, Goldberg, Healey, & Graham, 2009). Fixation loss was monitored with our custom eye-tracking methodology (CRS device), which provides detailed measurements of eye position. 
In sum, CS was assessed independently for each random location (see all tested 9 locations in Figure 4). For analysis purposes, 3 zones were defined: Zone 1 (10° diameter of visual field), Zone 2 (10°–20°), and Zone 3 (20°–40°). 
Figure 4
 
Basic scheme of the nine visual field locations tested in our CS-ISF task. Sinusoidal gratings were used as detection target stimuli (for details see Material and methods section).
Figure 4
 
Basic scheme of the nine visual field locations tested in our CS-ISF task. Sinusoidal gratings were used as detection target stimuli (for details see Material and methods section).
Statistical analysis
Two analysis steps were conducted in this study. In the first step, visual spatial asymmetries of retinal thickness (RT), contrast sensitivity, and P1 amplitude (using OCT3, ISF, and mfERG techniques, respectively) were independently assessed. It is important to note that all results from the left eye were converted into right eye (retina) format (orientation) for analysis. Asymmetries were analyzed using a multivariate approach for the 4 retinal hemifields, i.e., superior, inferior, nasal, and temporal. After verifying the normality assumption for the different parameters among the 4 hemifields (Kolmogorov–Smirnov test), an ANOVA repeated measures analysis was conducted using a Bonferroni correction for multiple comparisons. We have used a standard statistical measure of effect size, Cohen's d, in addition to % differences (Cohen, 1992). 
In the second step, the correlation between structural and functional parameters was assessed by the Pearson correlation coefficient. All statistical analyses were performed using the SPSS software version 16.0 (SPSS, Chicago, IL, USA). Statistically significant results were considered at a cutoff p-value of 0.05. 
Results
A naso/temporal asymmetry pattern was found for all studied outcome measures, with nasal hemifield disadvantage (see Tables 1 and 2). With respect to superior/inferior asymmetry, it was present only for the ISF-CS task and OCT measures. Mean retinal thicknesses by area are shown in Figure 5 for a representative individual and the global values (mean ± standard error of the mean) in Tables 1 and 2
Table 1
 
Mean values of superior and inferior VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Table 1
 
Mean values of superior and inferior VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Methods Zones Superior VF (inferior R) Inferior VF (superior R) p-value
OCT (μm) Global average 254.1 ± 1.5 261.0 ± 1.5 <0.0001
Zone 2 274.8 ± 1.7 281.1 ± 1.7 <0.0001
Zone 3 233.4 ± 1.7 240.9 ± 1.6 <0.0001
ISF (dB) Global average 21.9 ± 0.6 23.2 ± 0.5 <0.0001
Zone 2 26.4 ± 0.6 28.0 ± 0.6 <0.0001
Zone 3 17.4 ± 0.6 18.5 ± 0.5 0.054
mfERG (nV/deg2) Global average 19.8 ± 0.4 19.6 ± 0.4 n.s.
Zone 2 40.1 ± 0.8 39.5 ± 0.8 n.s.
Zone 3 26.3 ± 0.6 26.4 ± 0.5 n.s.
Zone 4 18.1 ± 0.5 17.3 ± 0.3 n.s.
Zone 5 14.8 ± 0.4 14.4 ± 0.3 n.s.
Table 2
 
Mean values of nasal and temporal VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Table 2
 
Mean values of nasal and temporal VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Methods Zones Temporal VF (nasal R) Nasal VF (temporal R) p-value
OCT (μm) Global average 270.6 ± 1.6 243.9 ± 1.5 <0.0001
Zone 2 280.0 ± 1.6 264.8 ± 1.5 <0.0001
Zone 3 261.2 ± 1.9 223.0 ± 1.6 <0.0001
ISF (dB) Global average 23.2 ± 0.5 21.9 ± 0.5 <0.0001
Zone 2 27.5 ± 0.6 26.8 ± 0.6 n.s.
Zone 3 18.9 ± 0.6 16.9 ± 0.5 <0.0001
mfERG (nV/deg2) Global average 20.7 ± 0.4 20.1 ± 0.4 0.003
Zone 2 40.8 ± 0.9 38.8 ± 0.8 0.001
Zone 3 26.6 ± 0.6 25.4 ± 0.5 0.002
Zone 4 17.4 ± 0.4 17.9 ± 0.4 n.s.
Zone 5 14.8 ± 0.3 14.4 ± 0.3 n.s.
Figure 5
 
Retinal thickness map (μm) of a representative individual (right eye) with strong nasal/temporal and superior/inferior asymmetries for all retinal zones (color-coded map: red, high value; black, low).
Figure 5
 
Retinal thickness map (μm) of a representative individual (right eye) with strong nasal/temporal and superior/inferior asymmetries for all retinal zones (color-coded map: red, high value; black, low).
The analysis of structural retinal asymmetries (OCT measures) demonstrated significant naso/temporal and superior/inferior global asymmetries, with reduced thickness of temporal and inferior retinas (nasal and superior visual fields). These asymmetries were also present in Zones 2 and 3 (see Tables 1 and 2). 
Using mfERG, we found the expected higher P1 amplitudes in the central ring (4.4°), with a mean value of 77.9 ± 2.0 nV/deg2. The inter-individual variance in response density is greatest at the central fovea, reducing toward more peripheral locations. A naso/temporal asymmetry was found for global hemifield means, with vulnerability of temporal retina (nasal hemifield, see Table 2). This asymmetry was significant in Zones 3 and 4 (13.6° and 25.8°), disappearing in the most eccentric zones (40.8° and 58.7°; see Table 2). In Figure 6, we show for the mfERG technique a representative individual with nasal/temporal asymmetry for P1 amplitude. 
Figure 6
 
P1 wave amplitude map of mfERG (nV/deg2) in terms of visual field, obtained from a representative individual (right eye). Note a significant nasal/temporal VF asymmetry specifically for Zones 2 and 3.
Figure 6
 
P1 wave amplitude map of mfERG (nV/deg2) in terms of visual field, obtained from a representative individual (right eye). Note a significant nasal/temporal VF asymmetry specifically for Zones 2 and 3.
In terms of P1 implicit time, a superior/inferior asymmetry was found (except for Zone 2), with higher values in the superior retina (mean: 35.4 ± 0.2 ms) and no statistical difference between the nasal and temporal retinas. 
Visual field anisotropies were found also for contrast sensitivity CS testing, with temporal and inferior retinas presenting lower CS mean values (see Tables 1 and 2), see also Figure 7 for a representative subject in terms of visual field VF (where one can see reduction of the CS in nasal and superior hemifields). 
Figure 7
 
Representative CS map (right eye) obtained using the ISF-CS test (in dB) in terms of visual field coordinates. Darker blue regions correspond to areas of lower CS (the central region is red due to high CS value). In this task, nasal/temporal and superior/inferior asymmetries are present in Zones 2 and 3.
Figure 7
 
Representative CS map (right eye) obtained using the ISF-CS test (in dB) in terms of visual field coordinates. Darker blue regions correspond to areas of lower CS (the central region is red due to high CS value). In this task, nasal/temporal and superior/inferior asymmetries are present in Zones 2 and 3.
Analysis of size effects
Analysis of effect sizes using both % differences and Cohen's d showed that OCT structural measures yielded large effects in particular for naso/temporal asymmetries, which is consistent with the notion that this type of asymmetry is generated in the retina (Cohen's d well above 1—2.1 and 3.6 for inner and outer naso/temporal asymmetries—which surpasses the 0.8 criterion for large effects). mfERG measures (which sample photoreceptor and bipolar cell populations) showed a moderate effect (Cohen's d of 0.42 and 0.44). Taken together these findings show that naso/temporal asymmetries have a retinal origin and dominate in the inner retina (ganglion cell level). These findings were corroborated using measures of % change, which confirmed that effects are stronger in the periphery (with 17% effect in terms of structural measures and 16% concerning psychophysical measures of naso/temporal asymmetry and only 6% for mfERG measures). These findings confirm the notion that behavioral performance is partly explained by retinal asymmetries in particular (but not exclusively) concerning inner retinal layers (which is documented by Cohen's d values above 0.5, for the CS task). Concerning inferior/superior asymmetries, Cohen's measures were in the moderate range and effect sizes were percentually smaller concerning structural measures (∼3%) than for psychophysical measures (∼8–10%) suggesting that psychophysical up/down asymmetries have an additional significant cortical contribution. 
Correlation analysis
To further evaluate whether psychophysical and electrophysiological measurements conveyed independent information, we performed correlation analysis between functional ISF-CS and mfERG measures. Significant correlations were present between global values of CS and implicit time of the P1 component (r = −0.619, p < 0.0001). Pearson's analyses between corresponding areas revealed significant correlations (psychophysical ISF-CS measures and physiological mfERG implicit times), within inner pericentral zones, r = −0.537, p < 0.0001, and outer pericentral zones, r = −0.641, p < 0.0001. 
Correlations between CS and implicit time (P1) measures, in terms of hemifields for the corresponding areas, are shown in Table 3
Table 3
 
Correlation coefficients (r) between CS and implicit time of P1 measures per corresponding zone in visual hemifields, with the p-values in parenthesis.
Table 3
 
Correlation coefficients (r) between CS and implicit time of P1 measures per corresponding zone in visual hemifields, with the p-values in parenthesis.
Hemifields Inner pericentral (CS)—Zone 3 (mfERG) Outer pericentral (CS)—Zone 4 (mfERG)
Superior −0.483 (p < 0.0001) −0.64 (p < 0.0001)
Inferior −0.388 (p = 0.0003) −0.496 (p < 0.0001)
Nasal −0.478 (p < 0.0001) −0.575 (p < 0.0001)
Temporal −0.451 (p < 0.0001) −0.603 (p < 0.0001)
A simultaneous representation of the corresponding zones for all methods used in this study can by found in the Supplementary Material
As expected, the analysis between non-corresponding areas revealed only weak correlations. Finally, no significant correlations were found between central areas (Zone 1) of both methods (ISF-CS and mfERG). 
We also performed correlation analysis between morphological data obtained by OCT and objective functional parameters of mfERG (P1 amplitude and implicit time). Only a weak correlation was found between RT measures and P1 amplitude for Zone 1 (r = −0.374, p = 0.001). The weak correlations between macular thickness (OCT) and physiological/behavioral measures may be due to the fact that they measure non-overlapping retinal components. 
In general, patterns of asymmetry likely arise at different levels of the retina as inferred by the observed partly independent correlation patterns (only part of the explained variance being common to all measures). 
Discussion
Here we have demonstrated for the first time concomitant and partially correlated retinal asymmetries, identified by psychophysics, structural imaging, and neurophysiology. 
The specific relationship between behavioral, structural, and physiological effects is well illustrated by the observed correlation patterns, which suggest that some of the behavioral effects have a retinal origin. 
The extent into which these measures are related is also explained by what part of the retinal circuitry contributes to each measure. mfERG measures are mostly dominated by the outer retina (photoreceptor and bipolar cell components) and showed the smallest contribution to the naso/temporal asymmetry effects. Psychophysical measures were accordingly better explained (but not exclusively) by the efferent output (inner part) of retina. The notion that behavioral performance is partly explained by retinal asymmetries was jointly corroborated by correlation and effect size analyses. Concerning inferior/superior asymmetries, effect size measures suggested that psychophysical up/down asymmetries have an additional significant cortical contribution. It is worth pointing out that nasal/temporal asymmetries are inherently retinal and are dissociable from left/right cortical asymmetry patterns (see also Silva et al., 2008). The findings that naso/temporal asymmetries have a retinal origin and dominate in the inner retina (ganglion cell level) are consistent with the notion that there are 300% more retinal ganglion cells in the nasal retina (Curcio & Allen, 1990). A contribution of retina mechanisms to psychophysical performance patterns was already observed before in patients (see also Castelo-Branco et al., 2007). Our findings are therefore consistent with the notion that cortical contributions are mostly relevant concerning left/right and up/down asymmetries (Connolly & Van Essen, 1984; Van Essen, Newsome, & Maunsell, 1984) but cannot explain nasal/temporal asymmetries (see also Silva et al., 2008). 
This study does therefore provide further elucidation on the sensory contribution to the interplay between visual and attentional factors in the generation of functional asymmetries and visual performance fields (Carrasco et al., 2004). 
Multidimensional mapping of structure and function of the healthy visual system is an important starting point for understanding the perceptual consequences of visual disease. Even a slight reduction in local contrast can have an adverse effect on reading performance, mobility, orientation, and other daily visual activities. Given the layout of the retina, with specific rod and cone distributions and different populations of bipolar and retinal ganglion cells, it is expectable that the spatial and temporal sensitivities of different parts of the retina are not uniform (Altpeter et al., 2000; Dacey & Petersen, 1992; Perry & Cowey, 1985; Silva et al., 2005, 2008; Thibos, Cheney, & Walsh, 1987). 
Our photopic CS testing conditions were validated in previous studies (Maia-Lopes et al., 2008; Silva et al., 2008) and yielded results consistent with anatomical studies of photoreceptors and ganglion cell distribution in the human retina. Concerning ganglion cell densities, they are higher in the superior retina as compared to the inferior part, as well as in the nasal retina as compared with the temporal counterpart (Croner & Kaplan, 1995; Curcio & Allen, 1990). These known anatomical facts are consistent with our results of ISF CS, which showed a pattern of nasal/temporal asymmetry, significantly higher in the 20°–40° eccentricity range, with lower CS in the temporal retina (nasal hemifield); as well as a superior/inferior asymmetry, with lower CS in the inferior retina (superior hemifield). In our previous work (Silva et al., 2008), similar naso/temporal patterns were found, although no superior/inferior asymmetry was present. This difference may be explained by the fact that our sample is higher in the present study with increased statistical power (see also the results of Carrasco et al., 2004, 2001). 
Anatomical anisotropies within the retina (Curcio et al., 1990) are also consistent with our own mfERG data. A nasal/temporal asymmetry was found for global means with disadvantage of the temporal retina (nasal hemifield). This asymmetry reflects the fact that cone density is 40–45% higher in the nasal retina and suggests that asymmetric distribution of cone receptors in the retina is more remarkable near the fovea (Curcio, Sloan, & Meyers, 1989; Curcio et al., 1990; Osterberg, 1935). In addition, the topography of ERG responses (photopic luminance response) found in Sutter and Tran's (1992) study shares all these expected properties based on the known density of retinal cones. 
Finally, our structural data confirmed the predictions of previous anatomical studies (Curcio & Allen, 1990; Curcio et al., 1990; Dacey, 1993; Drasdo, Millican, Katholi, & Curcio, 2007; see also Chan et al., 2006; Hee et al., 1995). 
An outstanding question in our study was whether there was any significant structure–function correlation between the concomitantly measured variables. Our analysis showed that these measures shared common variance but also diverged to some extent, suggesting that patterns of asymmetry likely arise at different levels of the retina and even of the cortex, as revealed by the partly unexplained variance observed in the case of psychophysical measures. 
It is however worth pointing out that central mechanisms are also important as determined by comparing naso/temporal versus left/right performance patterns (Silva et al., 2008) and from functional imaging studies of cortical retinotopic anisotropies (Liu, Heeger, & Carrasco, 2006). This is important in particular in which concerns up/down patterns of asymmetry. Anatomical asymmetry patterns in the LGN (Connolly & Van Essen, 1984) and cortex (Van Essen et al., 1984) provide important evidence for the additional role of central structures. 
Finally, it is important to point out that distinct temporal dynamics at different locations of the visual field (temporal performance fields, Carrasco et al., 2004) may combine with the spatial psychophysical patterns described here. 
Conclusion
In conclusion, functional asymmetries can be concomitantly documented at multiple levels of the human visual system, within a significant retinal contribution, as assessed by comparison of psychophysical, electrophysiological, and structural measures. Our results are consistent with the different anatomical anisotropies in terms of cone and ganglion cell densities and suggest an inner retinal dominance in terms of the origin of naso/temporal asymmetries and a dual retinal and cortical contribution to up/down asymmetries. The results of this study are relevant for the design of psychophysical paradigms and development of clinical training programs, such as the case of patients with heterogeneous VF loss and who need reuse the most functional parts of their retina. 
Supplementary Materials
Supplementary Figure - Supplementary Figure 
Acknowledgments
This research was supported by the following Grants: Portuguese Foundation for Science and Technology (FCT), POCI_SAU_OBS_57070_2004, PTDC_SAU_NEU_68483_2006, and Gulbenkian Foundation Ageing Grant. M. F. S. was supported by individual fellowships from FCT: SFRH/BD/18777/2004. The authors would like to thank Raquel Lemos for contributing to the participant's selection and Barbara Oliveiros for advice concerning statistical analysis. 
Commercial relationships: none. 
Corresponding author: Miguel Castelo-Branco. 
Email: mcbranco@ibili.uc.pt. 
Address: Centre of Ophthalmology, IBILI, Faculty of Medicine, Az. de Sta. Comba, 3000-354 Coimbra, Portugal. 
References
Altpeter E. Mackeben M. Trauzettel-Klosinski S. (2000). The importance of sustained attention for patients with maculopathies. Vision Research, 40, 1539–1547. [PubMed] [CrossRef] [PubMed]
Bearse M. A., Jr. Shimada Y. Sutter E. E. (2000). Distribution of oscillatory components in the central retina. Documenta Ophthalmologica, 100, 185–205. [PubMed] [CrossRef] [PubMed]
Brancato R. Lumbroso B. (2004). Guide to optical coherence tomography interpretation. Rome: Innovation-News-Communication.
Caprioli J. (1991). Automated perimetry in glaucoma. American Journal of Ophthalmology, 111, 235–239. [PubMed] [CrossRef] [PubMed]
Carrasco M. Giordano A. M. McElree B. (2004). Temporal performance fields: Visual and attentional factors. Vision Research, 44, 1351–1365. [PubMed] [CrossRef] [PubMed]
Carrasco M. Talgar C. P. Cameron E. L. (2001). Characterizing visual performance fields: Effects of transient covert attention, spatial frequency, eccentricity, task and set size. Spatial Vision, 15, 61–75. [PubMed] [CrossRef] [PubMed]
Castelo-Branco M. Mendes M. Sebastião A. R. Reis A. Soares M. Saraiva J. (2007). Visual phenotype in Williams–Beuren syndrome challenges magnocellular theories explaining human neurodevelopmental visual cortical disorders. Journal of Clinical Investigation, 117, 3720–3729. [PubMed] [PubMed]
Chan A. Duker J. S. Ko T. H. Fujimoto J. G. Schuman J. S. (2006). Normal macular thickness measurements in healthy eyes using Stratus optical coherence tomography. Archives of Ophthalmology, 124, 193–198. [PubMed] [Article] [CrossRef] [PubMed]
Clement C. I. Goldberg I. Healey P. R. Graham S. (2009). Humphrey matrix frequency doubling perimetry for detection of visual-field defects in open-angle glaucoma. British Journal of Ophthalmology, 93, 582–588. [PubMed] [CrossRef] [PubMed]
Cohen J. (1992). A power primer. Psychological Bulletin, 112, 155–159. [CrossRef] [PubMed]
Connolly M. Van Essen D. (1984). The representation of the visual field in parvocellular and magnocellular layers of the lateral geniculate nucleus in the macaque monkey. Journal of Comparative Neurology, 266, 544–564. [PubMed] [CrossRef]
Croner L. J. Kaplan E. (1995). Receptive fields of P and M ganglion cells across the primate retina. Vision Research, 35, 7–24. [PubMed] [CrossRef] [PubMed]
Curcio C. A. Allen K. A. (1990). Topography of ganglion cells in human retina. Journal of Comparative Neurology, 300, 5–25. [PubMed] [CrossRef] [PubMed]
Curcio C. A. Sloan K. R. Kalina R. E. Hendrickson A. E. (1990). Human photoreceptor topography. Journal of Comparative Neurology, 292, 497–523. [PubMed] [CrossRef] [PubMed]
Curcio C. A. Sloan K. R. Meyers D. (1989). Computer methods for sampling, reconstruction, display and analysis of retinal whole mounts. Vision Research, 29, 529–540. [PubMed] [CrossRef] [PubMed]
Curcio C. A. Sloan, Jr. K. R. Packer O. Hendrickson A. E. Kalina R. E. (1987). Distribution of cones in human and monkey retina: Individual variability and radial asymmetry. Science, 236, 579–582. [PubMed] [CrossRef] [PubMed]
Dacey D. M. (1993). The mosaic of midget ganglion cells in the human retina. Journal of Neuroscience, 13, 5334–5355. [PubMed] [PubMed]
Dacey D. M. Petersen M. R. (1992). Dendritic field size and morphology of midget and parasol ganglion cells of the human retina. Proceedings of the National Academy of Sciences, 89, 9666–9670. [PubMed] [Article] [CrossRef]
Drasdo N. Millican C. L. Katholi C. R. Curcio C. A. (2007). The length of Henle fibers in the human retina and a model of ganglion receptive field density in the visual field. Vision Research, 47, 2901–2911. [PubMed] [Article] [CrossRef] [PubMed]
Edgar G. K. Smith A. T. (1990). Hemifield differences of perceived spatial frequency. Perception, 19, 759–766. [PubMed] [CrossRef] [PubMed]
Eriksson U. Alm A. (2009). Repeatability in and interchangeability between the macular and the fast macular thickness map protocols: A study on normal eyes with Stratus optical coherence tomography. Acta Ophthalmologica, 87, 725–730. [PubMed] [CrossRef] [PubMed]
Fahle M. Schmid M. (1988). Naso-temporal asymmetry of visual perception and of the visual cortex. Vision Research, 28, 293–300. [CrossRef] [PubMed]
Fortune B. Bearse M. A., Jr. Cioffi G. A. Johnson C. A. (2002). Selective loss of an oscillatory component from temporal retinal multifocal ERG responses in glaucoma. Investigative Ophthalmology & Visual Science, 43, 2638–2647. [PubMed] [Article] [PubMed]
He S. Cavanagh P. Intrilligator J. (1996). Attentional resolution and the locus of visual awareness. Nature, 383, 334–337. [PubMed] [CrossRef] [PubMed]
Hee M. R. Izatt J. A. Swanson E. A. Huang D. Schuman J. S. Lin C. P. et al.(1995). Optical coherence tomography of the human retina. Archives of Ophthalmology, 113, 325–332. [PubMed] [CrossRef] [PubMed]
Hood D. C. (2000). Assessing retinal function with the multifocal technique. Progress in Retinal and Eye Research, 19, 607–646. [PubMed] [CrossRef] [PubMed]
Hood D. C. Seiple W. Holopigian K. Greenstein V. (1997). A comparison of the components of the multifocal and full-field ERGs. Visual Neuroscience, 14, 533–544. [PubMed] [CrossRef] [PubMed]
Jonas J. B. Schneider U. Naumann G. O. (1992). Count and density of human retinal photoreceptors. Graefe's Archive for Clinical and Experimental Ophthalmology, 230, 505–510. [PubMed] [CrossRef] [PubMed]
Kondo M. Miyake Y. Horiguchi M. Suzuki S. Ito Y. Tanikawa A. (1996). Normal values of retinal response densities in multifocal electroretinogram. Nippon Ganka Gakkai Zasshi, 100, 810–816. [PubMed] [PubMed]
Lam B. L. (2005). Electrophysiology of vision: Clinical testing and applications. Boca Raton, FL: Taylor & Francis.
Levine M. W. McAnany J. J. (2005). The relative capabilities of the upper and lower visual hemifields. Vision Research, 45, 2820–2830. [PubMed] [CrossRef] [PubMed]
Liu T. Heeger D. J. Carrasco M. (2006). Neural correlates of the visual vertical meridian asymmetry. Journal of Vision, 6, (11):12, 1294–1306, http://www.journalofvision.org/content/6/11/12, doi:10.1167/6.11.12. [PubMed] [Article] [CrossRef]
Maia-Lopes S. Silva E. D. Silva M. F. Reis A. Faria P. Castelo-Branco M. (2008). Evidence of widespread retinal dysfunction in patients with Stargardt disease and morphologically unaffected carrier relatives. Investigative Ophthalmology & Visual Science, 49, 1191–1199. [PubMed] [Article] [CrossRef] [PubMed]
McAnany J. J. Levine M. W. (2007). Magnocellular and parvocellular visual pathway contributions to visual field anisotropies. Vision Research, 47, 2327–2336. [PubMed] [CrossRef] [PubMed]
Miyake Y. (1990). Macular oscillatory potentials in humans Macular OPs. Documenta Ophthalmologica, 75, 111–124. [PubMed] [CrossRef] [PubMed]
Miyake Y. Shiroyama N. Horiguchi M. Ota I. (1989). Asymmetry of focal ERG in human macular region. Investigative Ophthalmology & Visual Science, 30, 1743–1749. [PubMed] [PubMed]
Nagatomo A. Nao-i N. Maruiwa F. Arai M. Sawada A. (1998). Multifocal electroretinograms in normal subjects. Japanese Journal of Ophthalmology, 42, 129–135. [PubMed] [CrossRef] [PubMed]
Osterberg G. (1935). Topography of the layer of rods and cones in the human retina. Acta Ophthalmologica, 13, 1–103.
Parks S. Keating D. Williamson T. H. Evans A. L. Elliot A. T. Jay J. L. (1996). Functional imaging of the retina using the multifocal electroretinograph: A control study. British Journal of Ophthalmology, 80, 831–834. [PubMed] [CrossRef] [PubMed]
Perry V. H. Cowey A. (1985). The ganglion cell and cone distribution in the monkey retina: Implications for central magnification factors. Vision Research, 25, 1795–1810. [PubMed] [CrossRef] [PubMed]
Polito A. Del Borrello M. Isola M. Zemella N. Bandello F. (2005). Repeatability and reproducibility of fast macular thickness mapping with Stratus optical coherence tomography. Archives of Ophthalmology, 123, 1330–1337. [PubMed] [CrossRef] [PubMed]
Previc F. H. (1990). Functional specialization in the lower and upper visual fields in humans: Its ecological origins and neurophysiological implications. Behavioral and Brain Sciences, 13, 519–575. [CrossRef]
Rangaswamy N. V. Hood D. C. Frishman L. J. (2003). Regional variations in local contributions to the primate photopic flash ERG: Revealed using the slow-sequence mfERG. Investigative Ophthalmology & Visual Science, 44, 3233–3247. [CrossRef] [PubMed]
Seeliger M. W. Kretschmann U. H. Apfelstedt-Sylla E. Zrenner E. (1998). Implicit time topography of multifocal electroretinograms. Investigative Ophthalmology & Visual Science, 39, 718–723. [PubMed] [PubMed]
Seiple W. Holopigian K. (1996). Outer-retina locus of increased flicker sensitivity of the peripheral retina. Journal of the Optical Society of America A, Optics, Image Science, and Vision, 13, 658–666. [PubMed] [CrossRef] [PubMed]
Seiple W. Holopigian K. Szlyk J. P. Wu C. (2004). Multidimensional visual field maps: Relationships among local psychophysical and local electrophysiological measures. Journal of Rehabilitation Research and Development, 41, 359–372. [PubMed] [CrossRef] [PubMed]
Silva M. F. Faria P. Regateiro F. S. Forjaz V. Januario C. Freire A. et al.(2005). Independent patterns of damage within magno-, parvo- and koniocellular pathways in Parkinson's disease. Brain, 128, 2260–2271. [PubMed] [CrossRef] [PubMed]
Silva M. F. Maia-Lopes S. Mateus C. Guerreiro M. Sampaio J. Faria P. et al.(2008). Retinal and cortical patterns of spatial anisotropy in contrast sensitivity tasks. Vision Research, 48, 127–135. [PubMed] [CrossRef] [PubMed]
Skrandies W. Baier M. (1986). The standing potential of the human eye reflects differences between upper and lower retinal areas. Vision Research, 26, 577. [CrossRef] [PubMed]
Spry P. G. Furber J. E. Harrad R. A. (2002). The effect of ocular dominance on visual field testing. Optometry & Vision Science, 79, 93–97. [PubMed] [CrossRef]
Sutter E. E. (2001). Imaging visual function with the multifocal m-sequence technique. Vision Research, 41, 1241–1255. [PubMed] [CrossRef] [PubMed]
Sutter E. E. Tran D. (1992). The field topography of ERG components in man—I. The photopic luminance response. Vision Research, 32, 433–446. [PubMed] [CrossRef] [PubMed]
Thibos L. N. Cheney F. E. Walsh D. J. (1987). Retinal limits to the detection and resolution of gratings. Journal of the Optical Society of America A, Optics, Image Science, and Vision, 4, 1524–1529. [PubMed] [CrossRef]
Van Essen D. C. Newsome W. T. Maunsell J. H. R. (1984). The visual field representation in striate cortex of the macaque monkey: Asymmetries, anisotropies, and individual variability. Vision Research, 24, 429–448. [PubMed] [CrossRef] [PubMed]
Virsu V. Rovamo J. (1979). Visual resolution, contrast sensitivity, and the cortical magnification factor. Experimental Brain Research, 37, 475–494. [PubMed] [CrossRef] [PubMed]
Wu S. Sutter E. E. (1995). A topographic study of oscillatory potentials in man. Visual Neuroscience, 12, 1013–1025. [PubMed] [CrossRef] [PubMed]
Figure 1
 
Layout of the OCT zones where RT was analyzed.
Figure 1
 
Layout of the OCT zones where RT was analyzed.
Figure 2
 
Layout of local stimulus hexagons and division in five analysis zones, according to eccentricity with Zone 1 being the central region.
Figure 2
 
Layout of local stimulus hexagons and division in five analysis zones, according to eccentricity with Zone 1 being the central region.
Figure 3
 
Scheme of analyzed asymmetries, white regions have been excluded from the analysis (see text).
Figure 3
 
Scheme of analyzed asymmetries, white regions have been excluded from the analysis (see text).
Figure 4
 
Basic scheme of the nine visual field locations tested in our CS-ISF task. Sinusoidal gratings were used as detection target stimuli (for details see Material and methods section).
Figure 4
 
Basic scheme of the nine visual field locations tested in our CS-ISF task. Sinusoidal gratings were used as detection target stimuli (for details see Material and methods section).
Figure 5
 
Retinal thickness map (μm) of a representative individual (right eye) with strong nasal/temporal and superior/inferior asymmetries for all retinal zones (color-coded map: red, high value; black, low).
Figure 5
 
Retinal thickness map (μm) of a representative individual (right eye) with strong nasal/temporal and superior/inferior asymmetries for all retinal zones (color-coded map: red, high value; black, low).
Figure 6
 
P1 wave amplitude map of mfERG (nV/deg2) in terms of visual field, obtained from a representative individual (right eye). Note a significant nasal/temporal VF asymmetry specifically for Zones 2 and 3.
Figure 6
 
P1 wave amplitude map of mfERG (nV/deg2) in terms of visual field, obtained from a representative individual (right eye). Note a significant nasal/temporal VF asymmetry specifically for Zones 2 and 3.
Figure 7
 
Representative CS map (right eye) obtained using the ISF-CS test (in dB) in terms of visual field coordinates. Darker blue regions correspond to areas of lower CS (the central region is red due to high CS value). In this task, nasal/temporal and superior/inferior asymmetries are present in Zones 2 and 3.
Figure 7
 
Representative CS map (right eye) obtained using the ISF-CS test (in dB) in terms of visual field coordinates. Darker blue regions correspond to areas of lower CS (the central region is red due to high CS value). In this task, nasal/temporal and superior/inferior asymmetries are present in Zones 2 and 3.
Table 1
 
Mean values of superior and inferior VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Table 1
 
Mean values of superior and inferior VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Methods Zones Superior VF (inferior R) Inferior VF (superior R) p-value
OCT (μm) Global average 254.1 ± 1.5 261.0 ± 1.5 <0.0001
Zone 2 274.8 ± 1.7 281.1 ± 1.7 <0.0001
Zone 3 233.4 ± 1.7 240.9 ± 1.6 <0.0001
ISF (dB) Global average 21.9 ± 0.6 23.2 ± 0.5 <0.0001
Zone 2 26.4 ± 0.6 28.0 ± 0.6 <0.0001
Zone 3 17.4 ± 0.6 18.5 ± 0.5 0.054
mfERG (nV/deg2) Global average 19.8 ± 0.4 19.6 ± 0.4 n.s.
Zone 2 40.1 ± 0.8 39.5 ± 0.8 n.s.
Zone 3 26.3 ± 0.6 26.4 ± 0.5 n.s.
Zone 4 18.1 ± 0.5 17.3 ± 0.3 n.s.
Zone 5 14.8 ± 0.4 14.4 ± 0.3 n.s.
Table 2
 
Mean values of nasal and temporal VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Table 2
 
Mean values of nasal and temporal VF hemifields for RT (OCT), CS (ISF), and P1 wave amplitude (mfERG) per zone. Statistically significant results were considered for p < 0.05 (ANOVA repeated measures with Bonferroni correction).
Methods Zones Temporal VF (nasal R) Nasal VF (temporal R) p-value
OCT (μm) Global average 270.6 ± 1.6 243.9 ± 1.5 <0.0001
Zone 2 280.0 ± 1.6 264.8 ± 1.5 <0.0001
Zone 3 261.2 ± 1.9 223.0 ± 1.6 <0.0001
ISF (dB) Global average 23.2 ± 0.5 21.9 ± 0.5 <0.0001
Zone 2 27.5 ± 0.6 26.8 ± 0.6 n.s.
Zone 3 18.9 ± 0.6 16.9 ± 0.5 <0.0001
mfERG (nV/deg2) Global average 20.7 ± 0.4 20.1 ± 0.4 0.003
Zone 2 40.8 ± 0.9 38.8 ± 0.8 0.001
Zone 3 26.6 ± 0.6 25.4 ± 0.5 0.002
Zone 4 17.4 ± 0.4 17.9 ± 0.4 n.s.
Zone 5 14.8 ± 0.3 14.4 ± 0.3 n.s.
Table 3
 
Correlation coefficients (r) between CS and implicit time of P1 measures per corresponding zone in visual hemifields, with the p-values in parenthesis.
Table 3
 
Correlation coefficients (r) between CS and implicit time of P1 measures per corresponding zone in visual hemifields, with the p-values in parenthesis.
Hemifields Inner pericentral (CS)—Zone 3 (mfERG) Outer pericentral (CS)—Zone 4 (mfERG)
Superior −0.483 (p < 0.0001) −0.64 (p < 0.0001)
Inferior −0.388 (p = 0.0003) −0.496 (p < 0.0001)
Nasal −0.478 (p < 0.0001) −0.575 (p < 0.0001)
Temporal −0.451 (p < 0.0001) −0.603 (p < 0.0001)
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