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Articles   |    
White Matter Microstructure and Atypical Visual Orienting in 7-Month-Olds at Risk for Autism
Jed T. Elison, Ph.D.; Sarah J. Paterson, Ph.D.; Jason J. Wolff, Ph.D.; J. Steven Reznick, Ph.D.; Noah J. Sasson, Ph.D.; Hongbin Gu, Ph.D.; Kelly N. Botteron, M.D.; Stephen R. Dager, M.D.; Annette M. Estes, Ph.D.; Alan C. Evans, Ph.D.; Guido Gerig, Ph.D.; Heather C. Hazlett, Ph.D.; Robert T. Schultz, Ph.D.; Martin Styner, Ph.D.; Lonnie Zwaigenbaum, M.D.; Joseph Piven, M.D.; for the IBIS Network
Am J Psychiatry 2013;170:899-908. doi:10.1176/appi.ajp.2012.12091150
View Author and Article Information

Dr. Evans is cofounder of and holds equity in Biospective, Inc.; he has also received consulting fees from Johnson & Johnson and Pfizer. Dr. Hazlett has received travel support from Autism Speaks. All other authors report no financial relationships with commercial interests.

Supported by grants awarded to Dr. Piven from NIH/National Institute of Child Health and Development (NICHD) (Autism Center of Excellence, R01 HD055741 and HD055741-S1; Intellectual and Developmental Disabilities Research Center, P30 HD03110 and T32 HD40127), Autism Speaks, and the Simons Foundation. Dr. Elison was supported by a National Research Service Award (5-T32-HD007376) from NICHD, and aspects of this work contributed to his doctoral dissertation. Further support was provided by the National Alliance for Medical Image Computing, funded by NIH through grant U54 EB005149.

The Infant Brain Imaging Study (IBIS) Network is an NIH-funded Autism Center of Excellence project and consists of a consortium of seven universities in the United States and Canada. Clinical sites: University of North Carolina: J. Piven (IBIS Network principal investigator), H.C. Hazlett, and J.C. Chappell; University of Washington: S. Dager, A. Estes, and D. Shaw; Washington University: K. Botteron, R. McKinstry, J. Constantino, and J. Pruett; Children’s Hospital of Philadelphia: R. Schultz and S. Paterson; University of Alberta: L. Zwaigenbaum; Data Coordinating Center: Montreal Neurological Institute: A.C. Evans, D.L. Collins, G.B. Pike, P. Kostopolous, and S. Das; Image Processing Core: University of Utah: G. Gerig; University of North Carolina: M. Styner; Statistical Analysis Core: University of North Carolina: H. Gu; Genetics Analysis Core: University of North Carolina: P. Sullivan and F. Wright.

From the Carolina Institute for Developmental Disabilities and the Departments of Psychiatry, Psychology, and Computer Science, University of North Carolina at Chapel Hill; Division of Humanities and Social Sciences, California Institute of Technology, Pasadena; Center for Autism Research, Children’s Hospital of Philadelphia and University of Pennsylvania, Philadelphia; School of Behavioral and Brain Sciences, University of Texas at Dallas; Department of Psychiatry, Washington University, St. Louis; Departments of Radiology and Speech and Hearing Sciences, University of Washington, Seattle; Montreal Neurological Institute, McGill University, Montreal; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City; Department of Pediatrics, University of Alberta, Edmonton.

Presented in part at the International Meeting for Autism Research, Toronto, May 17–19, 2012.

Address correspondence to Dr. Elison (jelison@caltech.edu) or Dr. Piven (jpiven@med.unc.edu).

Copyright © 2013 by the American Psychiatric Association

Received September 02, 2012; Revised November 09, 2012; Revised December 11, 2012; Accepted December 17, 2012.

Abstract

Objective  The authors sought to determine whether specific patterns of oculomotor functioning and visual orienting characterize 7-month-old infants who later meet criteria for an autism spectrum disorder (ASD) and to identify the neural correlates of these behaviors.

Method  Data were collected from 97 infants, of whom 16 were high-familial-risk infants later classified as having an ASD, 40 were high-familial-risk infants who did not later meet ASD criteria (high-risk negative), and 41 were low-risk infants. All infants underwent an eye-tracking task at a mean age of 7 months and a clinical assessment at a mean age of 25 months. Diffusion-weighted imaging data were acquired for 84 of the infants at 7 months. Primary outcome measures included average saccadic reaction time in a visually guided saccade procedure and radial diffusivity (an index of white matter organization) in fiber tracts that included corticospinal pathways and the splenium and genu of the corpus callosum.

Results  Visual orienting latencies were longer in 7-month-old infants who expressed ASD symptoms at 25 months compared with both high-risk negative infants and low-risk infants. Visual orienting latencies were uniquely associated with the microstructural organization of the splenium of the corpus callosum in low-risk infants, but this association was not apparent in infants later classified as having an ASD.

Conclusions  Flexibly and efficiently orienting to salient information in the environment is critical for subsequent cognitive and social-cognitive development. Atypical visual orienting may represent an early prodromal feature of an ASD, and abnormal functional specialization of posterior cortical circuits directly informs a novel model of ASD pathogenesis.

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FIGURE 1. The Modified Gap/Overlap Procedurea

a During gap trials, a fixation image appeared in the center of a visual display for a variable duration; the central image then disappeared and was followed by a 250-ms temporal gap before a target image appeared in the peripheral visual field (all images subtended a visual angle of 5–7°, visual angle between images subtended 8–10°). During overlap trials, the central image remained present after the appearance of the peripheral target for the duration of the peripheral target presentation (i.e., 2 seconds).

FIGURE 2. Regions of Interest for Label Map Seeding in a Study of White Matter Microstructure and Visual Orienting in Infants at Risk for Autisma

a Panel A shows regions of interest for the genu (yellow) and splenium (red) of the corpus callosum as applied to the centermost sagittal slice of the study atlas. Panel B shows axial regions of interest for left and right corticospinal white matter passing through the posterior limb of the internal capsule.

FIGURE 3. Group Differences in Oculomotor and Visual Orienting Behavior in 7-Month-Oldsa

a Low-risk=infants with low familial risk; high-risk-negative=infants with high familial risk who did not meet autism spectrum disorder (ASD) criteria on the Autism Diagnostic Observation Scale (ADOS) at the 24-month clinical visit; high-risk-ASD=infants with high familial risk who met ASD criteria on the ADOS at the 24-month clinical visit. In the gap condition, latencies for the three groups appear to represent a trend toward a familial marker model. In the overlap condition, latencies for the three groups conformed to a disorder-specific model of impairment (i.e., high-risk-ASD > high-risk-negative = low-risk). Error bars indicate standard deviations.

b Least significant difference pairwise group differences, p<0.05.

FIGURE 4. Brain-Behavior Double Dissociation in 7-Month-Olds at Low Risk for Autism (N=34)a

a In panel A, regression lines within the scatterplot represent the zero-order correlation between radial diffusivity in the left corticospinal tract and overlap latencies (blue circles; r=−0.128, p=0.472) and gap latencies (red circles; r=0.592, p<0.001), respectively. See Figure S1 in the online data supplement for results on the right corticospinal tract. In panel B, regression lines within the scatterplot represent the zero-order correlation between radial diffusivity in the splenium and overlap latencies (blue circles; r=−0.499, p=0.003) and gap latencies (red circles; r=0.006, p=0.975), respectively.

FIGURE 5. Functional Coupling Between Visual Orienting and the Spleniuma

a Low-risk=infants with low familial risk; high-risk-negative=infants with high familial risk who did not meet autism spectrum disorder (ASD) criteria on the Autism Diagnostic Observation Scale (ADOS) at the 24-month clinical visit; high-risk-ASD=infants with high familial risk who met ASD criteria on the ADOS at the 24-month clinical visit. Group membership significantly moderates the association between individual differences in radial diffusivity in the splenium and average saccadic latency in the overlap condition.

Anchor for Jump
TABLE 1.Characteristics of Infants With Low or High Familial Risk of Autism Spectrum Disorders (ASDs), With and Without ASD Symptoms at 24 Monthsa
Table Footer Note

a Low-risk=infants with low familial risk; high-risk-negative=infants with high familial risk who did not meet ASD criteria on the Autism Diagnostic Observation Scale (ADOS) at the 24-month clinical visit; high-risk-ASD=infants with high familial risk who met ASD criteria on the ADOS at the 24-month clinical visit.

Table Footer Note

b No significant difference between groups in sex ratio (Fisher’s exact test).

Table Footer Note

c In the Mullen Scales of Early Learning, the early learning composite score is a composite of the receptive language, expressive language, fine motor, and visual reception standard scores; the nonverbal developmental quotient is the average age equivalent scores for the fine motor and visual reception subscales divided by chronological age multiplied by 100; the verbal developmental quotient is the average age equivalent scores for the receptive language and expressive language subscales divided by chronological age multiplied by 100.

Table Footer Note

d The ADOS was administered when the child was between 23.6 and 32.7 months of age. The ADOS yields a social affect subscale score and a restricted and repetitive behavior subscale score, and the total ADOS score is the sum of the two subscales. All children in the ASD group met diagnostic criteria for a provisional autism spectrum diagnosis according to the ADOS.

Anchor for Jump
TABLE 2.Summary of Performance in the Gap/Overlap Paradigma
Table Footer Note

a Low-risk=infants with low familial risk; high-risk-negative=infants with high familial risk who did not meet ASD criteria on the Autism Diagnostic Observation Scale (ADOS) at 24 months; high-risk-ASD=infants with high familial risk who met ASD criteria on the ADOS at 24 months.

Table Footer Note

b Effect size based on Cohen’s d, using pooled variance as the denominator.

Table Footer Note

c Average saccade rate/velocity (in degrees/second) for overlap trials and gap trials. A minimum velocity threshold was set at 80°/second.

Table Footer Note

d Average latency (in ms) to initiate saccade toward the lateral target in the overlap condition and the gap condition.

Table Footer Note

e Coefficient of variation (CoV) for saccade latencies in the overlap condition and the gap condition. The CoV is a standardized index of dispersion or variability and is derived by estimating the ratio of the standard deviation to the mean for each individual.

Table Footer Note

f The gap effect value represents the difference (in ms) between average overlap latency and average gap latency. While it is a common metric extracted from this task, the gap effect value violates the assumption of pure insertion, as there is likely more than one cognitive/neural component active in one condition and not the other.

Table Footer Note

g “Late or no saccade” represents the number of trials that were excluded because the infant failed to initiate a saccade toward the lateral target between 100 and 1000 ms after the onset of the lateral target. This value also includes saccades that were more than two standard deviations from the mean, which always fell at the upward end of the distribution.

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1.
A unique behavioral feature differentiates 7 month-old high-risk infants later classified with an autism spectrum disorder (ASD) from similar-aged infants who do not develop ASD. What is that behavioral feature?
2.
The association between which white matter fiber tract and visual orienting latencies (overlap condition of the eye tracking paradigm) significantly differed between the low-risk group and the high-risk infants later classified with ASD, and subsequently implicates this structure in the early development of ASD?
3.
The diagnostic features of ASD emerge or unfold over time. What is the significance of identifying features that differentiate infants who will later develop ASD prior to the consolidation of the diagnostic profile?
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