White Matter and Visuospatial Processing in Autism: A Constrained Spherical Deconvolution Tractography Study

Autism spectrum disorders (ASDs) are associated with a marked disturbance of neural functional connectivity, which may arise from disrupted organization of white matter. The aim of this study was to use constrained spherical deconvolution (CSD)‐based tractography to isolate and characterize major intrahemispheric white matter tracts that are important in visuospatial processing. CSD‐based tractography avoids a number of critical confounds that are associated with diffusion tensor tractography, and to our knowledge, this is the first time that this advanced diffusion tractography method has been used in autism research. Twenty‐five participants with ASD and aged 25, intelligence quotient‐matched controls completed a high angular resolution diffusion imaging scan. The inferior fronto‐occipital fasciculus (IFOF) and arcuate fasciculus were isolated using CSD‐based tractography. Quantitative diffusion measures of white matter microstructural organization were compared between groups and associated with visuospatial processing performance. Significant alteration of white matter organization was present in the right IFOF in individuals with ASD. In addition, poorer visuospatial processing was associated in individuals with ASD with disrupted white matter in the right IFOF. Using a novel, advanced tractography method to isolate major intrahemispheric white matter tracts in autism, this research has demonstrated that there are significant alterations in the microstructural organization of white matter in the right IFOF in ASD. This alteration was associated with poorer visuospatial processing performance in the ASD group. This study provides an insight into structural brain abnormalities that may influence atypical visuospatial processing in autism. Autism Res 2013, ●●: ●●–●●. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.

[1]  Guido Gerig,et al.  Differences in white matter fiber tract development present from 6 to 24 months in infants with autism. , 2012, The American journal of psychiatry.

[2]  T. Grabowski,et al.  Disconnection's renaissance takes shape: Formal incorporation in group-level lesion studies , 2008, Cortex.

[3]  Luise Poustka,et al.  Fronto-temporal disconnectivity and symptom severity in children with autism spectrum disorder , 2012, The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry.

[4]  Dawn P. Flanagan,et al.  The Wechsler Intelligence Scale for Children-Fourth Edition in Neuropsychological Practice , 2010 .

[5]  Alexander Leemans,et al.  The B‐matrix must be rotated when correcting for subject motion in DTI data , 2009, Magnetic resonance in medicine.

[6]  P. Bartolomeo,et al.  White matter (dis)connections and gray matter (dys)functions in visual neglect: Gaining insights into the brain networks of spatial awareness , 2008, Cortex.

[7]  Ross T. Whitaker,et al.  Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism , 2010, NeuroImage.

[8]  M. Just,et al.  From the SelectedWorks of Marcel Adam Just 2011 Autonomy of lower-level perception from global processing in autism : Evidence from brain activation and functional connectivity , 2016 .

[9]  W. Tseng,et al.  The loss of asymmetry and reduced interhemispheric connectivity in adolescents with autism: A study using diffusion spectrum imaging tractography , 2011, Psychiatry Research: Neuroimaging.

[10]  Alan Connelly,et al.  Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution , 2007, NeuroImage.

[11]  M. Behen,et al.  Alterations in frontal lobe tracts and corpus callosum in young children with autism spectrum disorder. , 2010, Cerebral cortex.

[12]  Derek K. Jones,et al.  RESTORE: Robust estimation of tensors by outlier rejection , 2005, Magnetic resonance in medicine.

[13]  David Rudrauf,et al.  Damage to Association Fiber Tracts Impairs Recognition of the Facial Expression of Emotion , 2009, The Journal of Neuroscience.

[14]  I. Koerte,et al.  Diffusion Tensor Imaging , 2014 .

[15]  B. Hubert,et al.  Enhanced Perceptual Functioning in Autism: An Update, and Eight Principles of Autistic Perception , 2006, Journal of autism and developmental disorders.

[16]  Douglas L. Rosene,et al.  The Geometric Structure of the Brain Fiber Pathways , 2012, Science.

[17]  V. Wedeen,et al.  Mapping fiber orientation spectra in cerebral white matter with Fourier-transform diffusion MRI , 2000 .

[18]  L. Mottron,et al.  Cognitive mechanisms, specificity and neural underpinnings of visuospatial peaks in autism. , 2006, Brain : a journal of neurology.

[19]  J. Belliveau,et al.  Neuroimaging of the functional and structural networks underlying visuospatial vs. linguistic reasoning in high-functioning autism , 2010, Neuropsychologia.

[20]  F. Dell’Acqua,et al.  Fronto-striatal circuitry and inhibitory control in autism: Findings from diffusion tensor imaging tractography , 2012, Cortex.

[21]  Max A. Viergever,et al.  The influence of complex white matter architecture on the mean diffusivity in diffusion tensor MRI of the human brain , 2012, NeuroImage.

[22]  Max A. Viergever,et al.  Partial volume effect as a hidden covariate in DTI analyses , 2011, NeuroImage.

[23]  M. Catani,et al.  Can spherical deconvolution provide more information than fiber orientations? Hindrance modulated orientational anisotropy, a true‐tract specific index to characterize white matter diffusion , 2013, Human brain mapping.

[24]  Derek K. Jones,et al.  Diffusion tensor imaging. , 2011, Methods in molecular biology.

[25]  Susumu Mori,et al.  Fiber tracking: principles and strategies – a technical review , 2002, NMR in biomedicine.

[26]  Derek K. Jones,et al.  Temporal association tracts and the breakdown of episodic memory in mild cognitive impairment , 2012, Neurology.

[27]  Talma Hendler,et al.  Abnormal white matter integrity in young children with autism , 2011, Human brain mapping.

[28]  Giuseppe Iaria,et al.  Disconnection in prosopagnosia and face processing , 2008, Cortex.

[29]  Randy L. Gollub,et al.  Reproducibility of quantitative tractography methods applied to cerebral white matter , 2007, NeuroImage.

[30]  Alan Connelly,et al.  Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution , 2004, NeuroImage.

[31]  B. Leventhal,et al.  The Autism Diagnostic Observation Schedule—Generic: A Standard Measure of Social and Communication Deficits Associated with the Spectrum of Autism , 2000, Journal of autism and developmental disorders.

[32]  Richard B. Ivry,et al.  Hemispheric Asymmetries , 2000, Encyclopedia of Personality and Individual Differences.

[33]  P. Basser,et al.  Water Diffusion Changes in Wallerian Degeneration and Their Dependence on White Matter Architecture , 2000 .

[34]  Max A. Viergever,et al.  Mutual-information-based registration of medical images: a survey , 2003, IEEE Transactions on Medical Imaging.

[35]  Stephen M. Smith,et al.  DTI measures in crossing-fibre areas: Increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease , 2011, NeuroImage.

[36]  Jacques-Donald Tournier,et al.  Diffusion tensor imaging and beyond , 2011, Magnetic resonance in medicine.

[37]  M. Catani,et al.  A diffusion tensor imaging tractography atlas for virtual in vivo dissections , 2008, Cortex.

[38]  S. Arridge,et al.  Detection and modeling of non‐Gaussian apparent diffusion coefficient profiles in human brain data , 2002, Magnetic resonance in medicine.

[39]  M. Catani,et al.  The arcuate fasciculus and the disconnection theme in language and aphasia: History and current state , 2008, Cortex.

[40]  Mara Cercignani,et al.  Twenty‐five pitfalls in the analysis of diffusion MRI data , 2010, NMR in biomedicine.

[41]  Klaas E. Stephan,et al.  Neurophysiological correlates of relatively enhanced local visual search in autistic adolescents , 2007, NeuroImage.

[42]  Chandan J. Vaidya,et al.  Atypical neural substrates of Embedded Figures Task performance in children with Autism Spectrum Disorder , 2007, NeuroImage.

[43]  S. Dehaene,et al.  Pure alexia as a disconnection syndrome: New diffusion imaging evidence for an old concept , 2008, Cortex.

[44]  Hugues Duffau,et al.  Anatomic dissection of the inferior fronto-occipital fasciculus revisited in the lights of brain stimulation data , 2010, Cortex.

[45]  A. Couteur,et al.  Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders , 1994, Journal of autism and developmental disorders.

[46]  M. Just,et al.  Cortical underconnectivity coupled with preserved visuospatial cognition in autism: Evidence from an fMRI study of an embedded figures task , 2010, Autism research : official journal of the International Society for Autism Research.

[47]  Xenophon Papademetris,et al.  Diffusion Tensor Imaging in Autism Spectrum Disorders: Preliminary Evidence of Abnormal Neural Connectivity , 2011, The Australian and New Zealand journal of psychiatry.

[48]  H. Chugani,et al.  Sharp Curvature of Frontal Lobe White Matter Pathways in Children with Autism Spectrum Disorders: Tract-Based Morphometry Analysis , 2011, American Journal of Neuroradiology.

[49]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[50]  Scott Peltier,et al.  Abnormalities of intrinsic functional connectivity in autism spectrum disorders, , 2009, NeuroImage.

[51]  H. Moser,et al.  Imaging cortical association tracts in the human brain using diffusion‐tensor‐based axonal tracking , 2002, Magnetic resonance in medicine.

[52]  B. Jeurissen,et al.  Improved Sensitivity to Cerebral White Matter Abnormalities in Alzheimer’s Disease with Spherical Deconvolution Based Tractography , 2012, PloS one.

[53]  D. Wechsler Wechsler Intelligence Scale for Children , 2020, Definitions.

[54]  Carl-Fredrik Westin,et al.  Processing and visualization for diffusion tensor MRI , 2002, Medical Image Anal..

[55]  Gottfried Schlaug,et al.  Atypical hemispheric asymmetry in the arcuate fasciculus of completely nonverbal children with autism , 2012, Annals of the New York Academy of Sciences.

[56]  Jeremy D. Schmahmann,et al.  Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers , 2008, NeuroImage.

[57]  Christine Delmaire,et al.  Visualization of disconnection syndromes in humans , 2008, Cortex.

[58]  L. Frank Characterization of anisotropy in high angular resolution diffusion‐weighted MRI , 2002, Magnetic resonance in medicine.

[59]  Declan G. M. Murphy,et al.  Altered cerebellar feedback projections in Asperger syndrome , 2008, NeuroImage.

[60]  Mark W. Woolrich,et al.  Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? , 2007, NeuroImage.

[61]  Declan G. M. Murphy,et al.  The anatomy of extended limbic pathways in Asperger syndrome: A preliminary diffusion tensor imaging tractography study , 2009, NeuroImage.

[62]  Jan Sijbers,et al.  Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution , 2011, Human brain mapping.

[63]  Charles D. Smith,et al.  Neuronal fiber pathway abnormalities in autism: An initial MRI diffusion tensor tracking study of hippocampo-fusiform and amygdalo-fusiform pathways , 2008, Journal of the International Neuropsychological Society.

[64]  Eric Fombonne,et al.  Preface , 1998 .

[65]  L. Lagae,et al.  Is there a common neuroanatomical substrate of language deficit between autism spectrum disorder and specific language impairment? , 2012, Cerebral cortex.

[66]  Alex Martin,et al.  Facial Emotion Recognition in Autism Spectrum Disorders: A Review of Behavioral and Neuroimaging Studies , 2010, Neuropsychology Review.

[67]  M. Just,et al.  Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity. , 2004, Brain : a journal of neurology.

[68]  Katherine A. Johnson,et al.  Atypical Visuospatial Processing in Autism: Insights from Functional Connectivity Analysis , 2012, Autism research : official journal of the International Society for Autism Research.

[69]  Chun-Hung Yeh,et al.  Resolving crossing fibres using constrained spherical deconvolution: Validation using diffusion-weighted imaging phantom data , 2008, NeuroImage.

[70]  U. Frith,et al.  The Weak Coherence Account: Detail-focused Cognitive Style in Autism Spectrum Disorders , 2006, Journal of autism and developmental disorders.

[71]  C. Wheeler-Kingshott,et al.  About “axial” and “radial” diffusivities , 2009, Magnetic resonance in medicine.

[72]  T. Zeffiro,et al.  Enhanced mental image mapping in autism , 2011, Neuropsychologia.

[73]  P. Boesiger,et al.  SENSE: Sensitivity encoding for fast MRI , 1999, Magnetic resonance in medicine.

[74]  Stuart Crozier,et al.  Apparent Fibre Density: A novel measure for the analysis of diffusion-weighted magnetic resonance images , 2012, NeuroImage.

[75]  M. Just,et al.  Functional and anatomical cortical underconnectivity in autism: evidence from an FMRI study of an executive function task and corpus callosum morphometry. , 2007, Cerebral cortex.

[76]  Derek K. Jones,et al.  Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging , 2013, Human brain mapping.

[77]  Haiqing Huang,et al.  Detecting abnormalities of corpus callosum connectivity in autism using magnetic resonance imaging and diffusion tensor tractography , 2011, Psychiatry Research: Neuroimaging.

[78]  Marlene Behrmann,et al.  The anatomy of the callosal and visual-association pathways in high-functioning autism: A DTI tractography study , 2011, Cortex.

[79]  Max A. Viergever,et al.  elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.

[80]  Jan Sijbers,et al.  ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data , 2009 .