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White Matter Microstructure and Atypical Visual Orienting in 7-Month-Olds at Risk for Autism
Open accessAbstract
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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“Our findings are consistent with reports of subtle motor differences at 6–7 months with respect to head control [13], lower activity level [52], and saccadic reaction times [9] among infants who go on to develop ASD.”
From Behavioral, cognitive, and adaptive development in infants with autism spectrum disorder in the first 2 years of life (2015) · cites this paper as [9]
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BackgroundInfluentialSelf-citationA developmental neuroscience perspective on affect-biased attention
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The over‐pruning hypothesis of autism
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“There is already good evidence for disruption to the development of attentional control amongst HR infants: infants who later show clinical levels of ASD symptoms tend to show difficulties with exogenously driven disengagement compared with low-risk (LR) controls, with group differences apparent at around 12–14 months…”
BackgroundEarly development of attention to threat-related facial expressions
Leppänen, J. M., Cataldo, J. K., Enlow, M. B., & Nelson, C. A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0197424 · Cited by 93
“Further, given that the infants were tested with a rather lengthy EEG/fNIRS paradigm before the eye-tracking tests (S3 File), the retention rate in the current analysis was only 35 to 54%, which is noticeably lower than the 82 to 100% in previous infant eye-tracking studies using similar paradigms [34, 42, 43].”
ResultCerebrospinal fluid and the early brain development of autism
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BackgroundResultPre-symptomatic intervention for autism spectrum disorder (ASD): defining a research agenda
Grzadzinski, R., Amso, D., Landa, R. J., Watson, L. R., Guralnick, M. J., Zwaigenbaum, L., Deák, G. O., Estes, A. M., Brian, J. A., Bath, K. G., et al. (2021) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-021-09393-y · Cited by 98
“For example, results from infant sibling studies reveal differences in the visual system including the middle occipital gyrus [8] and splenium [35, 102].”
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The Neurodevelopment of Autism from Infancy Through Toddlerhood
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Self-citationBottom-Up Attention Orienting in Young Children with Autism
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“Previous work has shown that ASD groups have difficulty with disengagement of fixations (e.g., Elsabbagh et al. 2009; Elison et al. 2013).”
InfluentialAttitudes of the autism community to early autism research
Fletcher‐Watson, S., Apicella, F., Bonnie Auyeung, B., Beranová, Š., Bonnet‐Brilhault, F., Canal‐Bedia, R., Charman, T., Chericoni, N., Conceição, I. C., Davies, K., et al. (2016) · Autism · doi:10.1177/1362361315626577 · Cited by 79
“However, few of these findings have yet been unequivocally corroborated, with the exception of early attention switching atypicalities (Elison et al., 2013; Elsabbagh et al., 2013; Zwaigenbaum et al., 2005).”
BackgroundEarly Development of Visual Attention: Change, Stability, and Longitudinal Associations
Hendry, A. J., Johnson, M. H., & Holmboe, K. (2019) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-121318-085114 · Cited by 79
Shen, M. D., Swanson, M. R., Wolff, J. J., Elison, J. T., Girault, J. B., Kim, S. H., Smith, R. G., Graves, M. M., Weisenfeld, L. A. H., Flake, L., et al. (2022) · American Journal of Psychiatry · doi:10.1176/appi.ajp.21090896 · Cited by 82
Self-citationJohnson, M. H., Charman, T., Pickles, A. R., & Jones, E. J. H. (2021) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13372 · Cited by 79
“This was subsequently replicated in two eye-tracking studies (Elison et al., 2013; Elsabbagh et al., 2013); Elsabbagh and colleagues further showed that the change in disen-gagement speed between 7 and 14 months was particularly strongly associated with later ASD (Elsabbagh et al., 2013).”
InfluentialBilleci, L., Narzisi, A., Tonacci, A., Sbriscia-Fioretti, B., Serasini, L., Fulceri, F., Apicella, F., Sicca, F., Calderoni, S., & Muratori, F. (2017) · Scientific Reports · doi:10.1038/s41598-017-13053-4 · Cited by 71
Andrews, D. S., Lee, J. K., Solomon, M., Rogers, S. J., Amaral, D. G., & Nordahl, C. W. (2019) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-019-9291-z · Cited by 71
Eye-tracking-based assessment of cognitive function in low-resource settings
Forssman, L., Ashorn, P., Ashorn, U., Maleta, K. M., Matchado, A., Kortekangas, E., & Leppänen, J. M. (2016) · Archives of Disease in Childhood · doi:10.1136/archdischild-2016-310525 · Cited by 67
Is mere exposure enough? The effects of bilingual environments on infant cognitive development
D’Souza, D., Brady, D., Haensel, J. X., & D’Souza, H. (2020) · Royal Society Open Science · doi:10.1098/rsos.180191 · Cited by 67
“…processes and the development of corticospinal tracts connecting brain stem to cerebral cortex [35], the ability to disengage attention — reflected by saccadic reaction times in the overlap condition — is associated with development of the splenium, the thickest part of the corpus callosum [36].”
Mastergeorge, A. M., Kahathuduwa, C. N., & Blume, J. (2020) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-020-04731-w · Cited by 64
Widely applicable MATLAB routines for automated analysis of saccadic reaction times
Leppänen, J. M., Forssman, L., Kaatiala, J., Yrttiaho, S., & Wass, S. V. (2014) · Behavior Research Methods · doi:10.3758/s13428-014-0473-z · Cited by 64
“In essence, eye tracking is a noninvasive technology that has the advantage over other techniques in that it offers the possibility for automated acquisition and analysis of eye movements at a high spatial and temporal resolution, is less labor intensive, and minimizes the possibility of human error or biases (Aslin,…”
BackgroundResultInfluentialWhite matter correlates of sensory processing in autism spectrum disorders
Pryweller, J. R., Schauder, K. B., Anderson, A. W., Heacock, J. L., Foss‐Feig, J. H., Newsom, C. R., Loring, W. A., & Cascio, C. J. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.09.018 · Cited by 64
“The association between SPLEN FA and nonsocial orienting in ASD corroborates recent evidence that inefficient visual orienting and associated SPLEN white matter integrity reduction may be early markers of risk for ASD (Elison et al., 2013).”
Conti, E., Mitra, J., Calderoni, S., Pannek, K., Shen, K., Pagnozzi, A. M., Rose, S., Mazzotti, S., Scelfo, D., Tosetti, M., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23520 · Cited by 66
Role of deep learning in infant brain MRI analysis
Mostapha, M., & Styner, M. A. (2019) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2019.06.009 · Cited by 63
“…example, in studying ASD, It was demonstrated that infants who will later develop ASD show a variety of age-specific, brain differences between 6–24 months, as well as demonstrating early brain changes that correlate with ASD outcome and related behaviors measured at 24 months [69, 70, 71, 72, 73].”
BackgroundSelf-citationSacrey, L.-A. R., Bryson, S. E., Zwaigenbaum, L., Brian, J. A., Smith, I. M., Roberts, W., Szatmári, P., Vaillancourt, T., Roncadin, C., & Garon, N. (2016) · Autism · doi:10.1177/1362361316675120 · Cited by 70
“such as atypical visual orienting and face processing, have been detected by electroencephalogram (EEG) and eye tracking by 6–8 months, yet such technology-based methods are expensive and time-consuming (Chawarska et al., 2013; Cohen et al., 2013; Elison et al., 2013; Elsabbagh et al., 2012; Jones and Klin, 2013).”
BackgroundSelf-citationSabatos‐DeVito, M., Schipul, S. E., Bulluck, J., Belger, A., & Baranek, G. T. (2016) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-015-2681-5 · Cited by 67
“Attention disengagement deficits are amongst the earliest markers in at-risk siblings of children with ASD (Bryson et al. 2007; Elison et al. 2013; Elsabbagh et al. 2009, 2013), and are predictive of a later diagnosis (Zwaigenbaum et al. 2005).”
BackgroundInfluentialPruett, J. R., Kandala, S., Hoertel, S., Snyder, A. Z., Elison, J. T., Nishino, T., Feczko, E., Dosenbach, N. U. F., Nardos, B., Power, J. D., et al. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.01.003 · Cited by 57
“…and the microstructure of the plenium of the corpus callosum in 7-month-old low-risk nfants (Elison et al., 2013b), and a correlation between ractional anisotropy in the right uncinate fasciculus at 6 onths and the infants’ response to joint attention bids at 9 onths (Elison et al., 2013a).”
InfluentialSelf-citationFalck‐Ytter, T. (2015) · Research in Autism · doi:10.1016/j.rasd.2015.06.007 · Cited by 57
Díaz‐Caneja, C. M., State, M. W., Hagerman, R. J., Jacquemont, S., Marín, Ó., Bagni, C., Umbricht, D., Simonoff, E. A., Andres-Trelles, F., Kaale, A., et al. (2021) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2021.02.020 · Cited by 56
Eurosibs: Towards robust measurement of infant neurocognitive predictors of autism across Europe
Jones, E. J. H., Mason, L., Ali, J. B., van den Boomen, C., Braukmann, R., Cauvet, É., Demurie, E., Hessels, R. S., Ward, E. K., Hunnius, S., et al. (2019) · Infant Behavior and Development · doi:10.1016/j.infbeh.2019.03.007 · Cited by 53
Falck‐Ytter, T., Thorup, E., & Bölte, S. (2014) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-014-2278-4 · Cited by 53
“Some studies have indicated that young autistic children have problems disengaging their attention from visual stimuli (Elison et al. 2013; Elsabbagh et al. 2013).”
BackgroundMüller, N., Baumeister, S., Dziobek, I., Banaschewski, T., & Poustka, L. (2016) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-016-2828-z · Cited by 60
Analysis of cortical shape in children with simplex autism
Dierker, D. L., Feczko, E., Pruett, J. R., Petersen, S. E., Schlaggar, B. L., Constantino, J. N., Harwell, J. W., Coalson, T. S., & Van Essen, D. C. (2015) · Cerebral Cortex · doi:10.1093/cercor/bht294 · Cited by 50
Splenium development and early spoken language in human infants
Swanson, M. R., Wolff, J. J., Elison, J. T., Gu, H., Hazlett, H. C., Botteron, K. N., Styner, M. A., Paterson, S., Gerig, G., Constantino, J. N., et al. (2015) · Developmental Science · doi:10.1111/desc.12360 · Cited by 54
Self-citationInfant Visual Brain Development and Inherited Genetic Liability in Autism
Girault, J. B., Donovan, K., Hawks, Z., Talović, M., Forsen, E., Elison, J. T., Shen, M. D., Swanson, M. R., Wolff, J. J., Kim, S. H., et al. (2022) · American Journal of Psychiatry · doi:10.1176/appi.ajp.21101002 · Cited by 49
Self-citationClinical and Translational Implications of an Emerging Developmental Substructure for Autism
Constantino, J. N., Charman, T., & Jones, E. J. H. (2021) · Annual Review of Clinical Psychology · doi:10.1146/annurev-clinpsy-081219-110503 · Cited by 54
“Possible manifestations of this include slower shifting of attention to a novel stimulus when interest is already captured (Elison et al. 2013, Elsabbagh et al. 2013) and increased connectivity in the alpha range (suggestive of greater internal focus) while viewing dynamic videos (Haartsen et al.…”
BackgroundTunç, B., Yankowitz, L., Parker, D., Alappatt, J. A., Pandey, J., Schultz, R., & Verma, R. (2019) · Molecular Autism · doi:10.1186/s13229-019-0301-5 · Cited by 47
Self-citationZhang, S., Chen, D., Tang, Y., & Zhang, L. (2021) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2021.651349 · Cited by 49
“…of EEG & eye-tracking recordings for instance, studies have shown that eye-tracking recordings have strong correlation with EEG acquisitions making it possible for the comprehensive analysis between the behavioral characteristics (eye-tracking) and the brain dynamics (EEG) (Elison et al., 2013).”
BackgroundApplication of Eye Tracking Technology in Medicine: A Bibliometric Analysis
Zammarchi, G., & Conversano, C. (2021) · Vision · doi:10.3390/vision5040056 · Cited by 51
“Some of these studies combined eye tracking with additional techniques such as MRI in order to investigate whether the identified differences in gaze patterns were associated with neurobiological abnormalities [26,27,45].”
BackgroundGlobally weaker and topologically different: resting-state connectivity in youth with autism
Yerys, B. E., Herrington, J. D., Satterthwaite, T. D., Guy, L., Schultz, R. T., & Bassett, D. S. (2017) · Molecular Autism · doi:10.1186/s13229-017-0156-6 · Cited by 48
“These system-specific findings align with imaging studies of toddlers [57] and younger siblings at risk for ASD [58, 59] that demonstrate unusual growth of white matter tracts linking attention and motor systems.”
ResultSelf-citationFranchini, M., Armstrong, V. L., Schaer, M., & Smith, I. M. (2018) · Child Neuropsychology · doi:10.1080/09297049.2018.1490706 · Cited by 52
“…findings may be explained by methodological differences between studies, including in particular that whereas studies by the Bryson group used similar stimuli across trials (Landry & Bryson, 2004; Zwaigenbaum et al., 2005), stimuli changed across trials in the Elison et al. (2013) study.”
BackgroundResultInfluentialUnimpaired attentional disengagement in toddlers with autism spectrum disorder
Fischer, J., Smith, H., Martinez‐Pedraza, F., Carter, A. S., Kanwisher, N., & Káldy, Z. (2015) · Developmental Science · doi:10.1111/desc.12386 · Cited by 47
“Several other gap-overlap studies have required disengagement from social stimuli and reported slower disengagement in children with ASD (Elison et al., 2013; Elsabbagh et al., 2009, 2013; Kawakubo et al., 2007); it is not the case that including social stimuli reduces the ability to detect any Fischer et al.”
Macari, S. L., Milgramm, A., Reed, J., Shic, F., Powell, K. K., Macris, D. M., & Chawarska, K. (2020) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2019.12.012 · Cited by 49
BK Channels Mediate Synaptic Plasticity Underlying Habituation in Rats
Zaman, T., Oliveira, C. D., Smoka, M., Narla, C., Poulter, M. O., & Schmid, S. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3699-16.2017 · Cited by 45
“…impact on social interactions and daily functioning (Hirstein et al., 2001; Minshew et al., 2002; Zwaigenbaum et al., 2005; Leekam et al., 2007; Crane et al., 2009; Schoen et al., 2009; Elison et al., 2013; Elsabbagh et al., 2013; Stroganova et al., 2013; for review, see Sinclair et al., 2016).”
BackgroundAltered lateralization of dorsal language tracts in 6‐week‐old infants at risk for autism
Liu, J., Tsang, T., Jackson, L., Ponting, C., Jeste, S., Bookheimer, S. Y., & Dapretto, M. (2018) · Developmental Science · doi:10.1111/desc.12768 · Cited by 45
Topál, J., Román, V., & Turcsán, B. (2019) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1495 · Cited by 46
Yurkovic‐Harding, J., Lisandrelli, G., Shaffer, R. C., Dominick, K. C., Pedapati, E. V., Erickson, C. A., Kennedy, D. P., & Yu, C. (2021) · Scientific Reports · doi:10.1038/s41598-021-81102-0 · Cited by 42
Telford, E. J., Cox, S. R., Fletcher‐Watson, S., Anblagan, D., Sparrow, S. A., Pataky, R., Quigley, A. J., Semple, S. I. K., Bastin, M. E., & Boardman, J. P. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1455-6 · Cited by 42
“In addition, eye-movement recordings in response to social stimuli have been used to identify early behavioral trajectories associated with autism (Jones and Klin 2013), to link emergent social cognition with white matter microstructure in specific tracts (Elison et al. 2013), and to distinguish between the social cog…”
BackgroundCan Autism Be Diagnosed with Artificial Intelligence? A Narrative Review
Chaddad, A., Li, J., Lu, Q., Li, Y., Okuwobi, I. P., Tanougast, C., Desrosiers, C., & Niazi, T. M. (2021) · Diagnostics · doi:10.3390/diagnostics11112032 · Cited by 43
“This atypical expansion leads to problems such as visual receptivity deficits and neglect of social cues [42].”
BackgroundEye-Tracking Biomarkers and Autism Diagnosis in Primary Care
Keehn, B., Monahan, P. O., Enneking, B. A., Ryan, T., Swigonski, N. L., & Keehn, R. M. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.11190 · Cited by 52
Reducing age of autism diagnosis: developmental social neuroscience meets public health challenge.
Klin, A., Klaiman, C., & Jones, W. (2015) · PubMed · Cited by 39
Reduced visual disengagement but intact phasic alerting in young children with autism
Kleberg, J. L., Thorup, E., & Falck‐Ytter, T. (2016) · Autism Research · doi:10.1002/aur.1675 · Cited by 39
Metadata
- Authors
- Elison, J. T., Paterson, S. J., Wolff, J. J., Reznick, J. S., Sasson, N. J., Gu, H., Botteron, K. N., Dager, S. R., Estes, A. M., Evans, A. C., Gerig, G., Hazlett, H. C., Schultz, R. T., Styner, M., Zwaigenbaum, L., Piven, J., & for the IBIS Network
- Affiliations
- University of North Carolina at Chapel Hill (US)
- ORCID
- Venue
- American Journal of Psychiatry
- Published
- 2013-08
- Volume
- 170
- Issue
- 8
- Pages
- 899-908
- ISSN
- 0002-953X (ISSN-L)
- 1535-7228
- PMC
- PMC3863364
- OpenAlex
- W2133015692
- Cited by
- 277
- References
- 46
- Citations by year
- 2026: 5 · 2025: 13 · 2024: 11 · 2023: 9 · 2022: 14 · 2021: 21 · 2020: 53 · 2019: 26 · 2018: 15 · 2017: 21 · 2016: 30 · 2015: 23 · 2014: 25 · 2013: 11
- FWCI
- 16.21
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- CaltechAUTHORS (California Institute of Technology) (submittedVersion)
- Funders
- Autism Speaks
- Pfizer
- National Institutes of Health (HD 03110, EB005149)
- Intellectual and Developmental Disabilities Research Center (T32 HD40127, P30 HD03110)
- National Institute of Mental Health (R01MH091645)
- National Institute of Biomedical Imaging and Bioengineering (U54EB005149)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (T32-HD-40127, HD055741-S1, P30-HD03110, P30HD003110, T32HD007376, T32HD040127, R01HD055741)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Keywords
- autism spectrum disorder, visual orienting, white matter microstructure, radial diffusivity, splenium of corpus callosum, saccade latency, oculomotor development, familial risk, corticospinal tract, eye tracking, diffusion-weighted imaging, infant development
- MeSH terms
- Attention, Brain, Brain Mapping, Cerebral Cortex, Child Development Disorders, Pervasive, Cognition Disorders, Corpus Callosum, Female, Follow-Up Studies, Humans, Image Interpretation, Computer-Assisted, Infant, Male, Nerve Fibers, Neurons, Orientation, Pyramidal Tracts, Reaction Time, Reference Values, Reticular Formation, Saccades, Superior Colliculi, Visual Pathways, Genetic Predisposition to Disease, Diffusion Magnetic Resonance Imaging, Emotional Intelligence, Leukoencephalopathies
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