A custom magnetoencephalography device reveals brain connectivity and high reading/decoding ability in children with autism

Mitsuru Kikuchi, Yuko Yoshimura, Kiyomi Shitamichi, Sanae Ueno, Tetsu Hirosawa, Toshio Munesue, Yasuki Ono, Tsunehisa Tsubokawa, Yasuhiro Haruta, Manabu Oi, Yo Niida, Gerard B Remijn, Tsutomu Takahashi, Michio Suzuki, Haruhiro Higashida, Yoshio Minabe, Mitsuru Kikuchi, Yuko Yoshimura, Kiyomi Shitamichi, Sanae Ueno, Tetsu Hirosawa, Toshio Munesue, Yasuki Ono, Tsunehisa Tsubokawa, Yasuhiro Haruta, Manabu Oi, Yo Niida, Gerard B Remijn, Tsutomu Takahashi, Michio Suzuki, Haruhiro Higashida, Yoshio Minabe

Abstract

A subset of individuals with autism spectrum disorder (ASD) performs more proficiently on certain visual tasks than may be predicted by their general cognitive performances. However, in younger children with ASD (aged 5 to 7), preserved ability in these tasks and the neurophysiological correlates of their ability are not well documented. In the present study, we used a custom child-sized magnetoencephalography system and demonstrated that preserved ability in the visual reasoning task was associated with rightward lateralisation of the neurophysiological connectivity between the parietal and temporal regions in children with ASD. In addition, we demonstrated that higher reading/decoding ability was also associated with the same lateralisation in children with ASD. These neurophysiological correlates of visual tasks are considerably different from those that are observed in typically developing children. These findings indicate that children with ASD have inherently different neural pathways that contribute to their relatively preserved ability in visual tasks.

Figures

Figure 1
Figure 1
(a) A custom, child-sized MEG. (b) A conventional, adult-sized MEG. (c) The schema of the five selected sensors and the 10 intrahemispheric connections of interest in each hemisphere. F = selected sensor in frontal region; C = central; P = parietal; O = occipital; and T = temporal.
Figure 2
Figure 2
(a) The performance of young children with ASD and TD children on the verbal reasoning test, the pattern reasoning test and the reading/decoding test. The error bars represent 1 standard deviation. (b) A scatter plot is depicted of the two scores (i.e., for the verbal reasoning test and the pattern reasoning test) for the children with ASD and the TD children. (c) A scatter plot is depicted of two scores (i.e., the verbal reasoning test and the reading/decoding test) for the children with ASD and the TD children. Certain children with ASD with low verbal-reasoning test scores achieved relatively high scores on pattern reasoning or reading/decoding tests.
Figure 3. The standardised regression coefficients (β…
Figure 3. The standardised regression coefficients (β values) are shown for the pattern reasoning performance (one of the two independent variables) in the multiple regression model that was used to predict (a) left, (b) right intrahemispheric coherence and the corresponding laterality index (c) (i.e., the dependent variables), using age as the other independent variable, in the children with ASD.
In sub-figures (a) and (b), the upward direction (positive β value) signifies a positive correlation between the pattern reasoning ability and the coherence value. In sub-figure (c), the upward direction (negative β value) signifies a positive correlation between the pattern reasoning ability and the rightward brain laterality. The β values are presented for P < 0.05. F = selected sensor in the frontal region; C = central; P = parietal; O = occipital; and T = temporal. *P < 0.00056.
Figure 4. The standardised regression coefficients (β…
Figure 4. The standardised regression coefficients (β values) are shown for reading ability (one of two independent variables) in the multiple regression model that was used to predict (a) left, (b) right intrahemispheric coherence and the corresponding laterality index (c) (i.e., the dependent variables), with age as the other independent variable, in children with ASD.
In sub-figures (a) and (b), the upward direction (positive β value) signifies a positive correlation between the reading ability and the coherence value. In sub-figure (c), the upward direction (negative β value) signifies a positive correlation between the reading ability and the rightward brain laterality. The β values are presented for P < 0.05. F = the selected sensor in frontal region; C = central; P = parietal; O = occipital; and T = temporal. *P < 0.00056.
Figure 5. The standardised regression coefficients (β…
Figure 5. The standardised regression coefficients (β values) are topographically indicated.
These values were calculated for reading ability (i.e., one of the two independent variables) to predict gamma-2 band coherence between the seed sensor and the remaining 150 sensors (i.e., dependent variables) in children with ASD. (a) A seed sensor was selected in the right parietal region. Higher reading ability was a significant predictor of higher coherence between the right parietal region (seed sensor) and the right temporo-occipital region. (b) A seed sensor was selected in the right temporal region. Higher reading ability was a significant predictor of higher coherence between the right temporal region (seed sensor) and the right frontal, the right parietal and the right temporo-occipital regions. The β values are presented for P < 0.05. The yellow star indicates the seed sensor. The open circles indicate the remaining 150 sensors. The open circles with bold lines indicate the sparse alignment of the MEG sensors for the first analysis in the present study. L = left; R = right.
Figure 6. The t-values of intrahemispheric coherence…
Figure 6. The t-values of intrahemispheric coherence for the (a) left and (b) right hemispheres between children with ASD (n = 26) and TD children (n = 26).
Positive values represent greater levels in the ASD group than in the TD group. The t-values are presented for P P < 0.00056.

References

    1. Charman T. et al. IQ in children with autism spectrum disorders: data from the Special Needs and Autism Project (SNAP). Psychol Med 41, 619–627 (2011).
    1. Dawson M., Soulieres I., Gernsbacher M. A. & Mottron L. The level and nature of autistic intelligence. Psychol Sci 18, 657–662 (2007).
    1. Morsanyi K. & Holyoak K. J. Analogical reasoning ability in autistic and typically developing children. Dev Sci 13, 578–587 (2010).
    1. Mottron L. Changing perceptions: The power of autism. Nature 479, 33–35 (2011).
    1. Kikuchi M. et al. Lateralized theta wave connectivity and language performance in 2- to 5-year-old children. J Neurosci 31, 14984–14988 (2011).
    1. Yoshimura Y. et al. Language performance and auditory evoked fields in 2- to 5-year-old children. Eur J Neurosci 35, 644–650 (2012).
    1. Wang X. J. Neurophysiological and computational principles of cortical rhythms in cognition. Physiol Rev 90, 1195–1268 (2010).
    1. Hutsler J. & Galuske R. A. Hemispheric asymmetries in cerebral cortical networks. Trends Neurosci 26, 429–435 (2003).
    1. Eyler L. T., Pierce K. & Courchesne E. A failure of left temporal cortex to specialize for language is an early emerging and fundamental property of autism. Brain 135, 949–960 (2012).
    1. Samson F., Mottron L., Soulieres I. & Zeffiro T. A. Enhanced visual functioning in autism: An ALE meta-analysis. Hum Brain Mapp (2011).
    1. Gage N. M. et al. Rightward hemispheric asymmetries in auditory language cortex in children with autistic disorder: an MRI investigation. J Neurodev Disord 1, 205–214 (2009).
    1. Kaufman A. & Kaufman N. Kaufman Assessment Battery for Children: Administration and Scoring Manual. Circle Pines MN: American Guidance Service (1983).
    1. Newman T. M. et al. Hyperlexia in children with autism spectrum disorders. J Autism Dev Disord 37, 760–774 (2007).
    1. Schalock R. L. et al. The renaming of mental retardation: understanding the change to the term intellectual disability. Intellect Dev Disabil 45, 116–124 (2007).
    1. Fox P. T. & Friston K. J. Distributed processing; distributed functions? Neuroimage 61, 407–426 (2012).
    1. Anderson J. S. et al. Functional connectivity magnetic resonance imaging classification of autism. Brain 134, 3739–3751 (2011).
    1. Just M. A., Cherkassky V. L., Keller T. A. & Minshew N. J. Cortical activation and synchronization during sentence comprehension in high-functioning autism: evidence of underconnectivity. Brain 127, 1811–1821 (2004).
    1. Kana R. K., Keller T. A., Cherkassky V. L., Minshew N. J. & Just M. A. Sentence comprehension in autism: thinking in pictures with decreased functional connectivity. Brain 129, 2484–2493 (2006).
    1. Kleinhans N. M. et al. Abnormal functional connectivity in autism spectrum disorders during face processing. Brain 131, 1000–1012 (2008).
    1. Lee P. S. et al. Functional connectivity of the inferior frontal cortex changes with age in children with autism spectrum disorders: a fcMRI study of response inhibition. Cereb Cortex 19, 1787–1794 (2009).
    1. Koshino H. et al. Functional connectivity in an fMRI working memory task in high-functioning autism. Neuroimage 24, 810–821 (2005).
    1. Duncan J. et al. A neural basis for general intelligence. Science 289, 457–460 (2000).
    1. Kroger J. K. et al. Recruitment of anterior dorsolateral prefrontal cortex in human reasoning: a parametric study of relational complexity. Cereb Cortex 12, 477–485 (2002).
    1. Lee K. H. et al. Neural correlates of superior intelligence: stronger recruitment of posterior parietal cortex. Neuroimage 29, 578–586 (2006).
    1. Prabhakaran V., Smith J. A., Desmond J. E., Glover G. H. & Gabrieli J. D. Neural substrates of fluid reasoning: an fMRI study of neocortical activation during performance of the Raven's Progressive Matrices Test. Cogn Psychol 33, 43–63 (1997).
    1. Soulieres I. et al. Enhanced visual processing contributes to matrix reasoning in autism. Hum Brain Mapp 30, 4082–4107 (2009).
    1. Keehn B., Brenner L., Palmer E., Lincoln A. J. & Muller R. A. Functional brain organization for visual search in ASD. J Int Neuropsychol Soc 14, 990–1003 (2008).
    1. Manjaly Z. M. et al. Neurophysiological correlates of relatively enhanced local visual search in autistic adolescents. Neuroimage 35, 283–291 (2007).
    1. Ring H. A. et al. Cerebral correlates of preserved cognitive skills in autism: a functional MRI study of embedded figures task performance. Brain 122 (Pt7), 1305–1315 (1999).
    1. Everts R. et al. Strengthening of laterality of verbal and visuospatial functions during childhood and adolescence. Hum Brain Mapp 30, 473–483 (2009).
    1. Cohen L. et al. Visual word recognition in the left and right hemispheres: anatomical and functional correlates of peripheral alexias. Cereb Cortex 13, 1313–1333 (2003).
    1. Bitan T., Cheon J., Lu D., Burman D. D. & Booth J. R. Developmental increase in top-down and bottom-up processing in a phonological task: an effective connectivity, fMRI study. J Cogn Neurosci 21, 1135–1145 (2009).
    1. van der Mark S. et al. The left occipitotemporal system in reading: disruption of focal fMRI connectivity to left inferior frontal and inferior parietal language areas in children with dyslexia. Neuroimage 54, 2426–2436 (2011).
    1. Brem S. et al. Brain sensitivity to print emerges when children learn letter-speech sound correspondences. Proc Natl Acad Sci U S A 107, 7939–7944 (2010).
    1. De Giacomo A. & Fombonne E. Parental recognition of developmental abnormalities in autism. Eur Child Adolesc Psychiatry 7, 131–136 (1998).
    1. Wetherby A. M. et al. Early indicators of autism spectrum disorders in the second year of life. J Autism Dev Disord 34, 473–493 (2004).
    1. Holz E. M., Glennon M., Prendergast K. & Sauseng P. Theta-gamma phase synchronization during memory matching in visual working memory. Neuroimage 52, 326–335 (2010).
    1. Sauseng P. et al. Theta coupling in the human electroencephalogram during a working memory task. Neurosci Lett 354, 123–126 (2004).
    1. Sederberg P. B., Kahana M. J., Howard M. W., Donner E. J. & Madsen J. R. Theta and gamma oscillations during encoding predict subsequent recall. J Neurosci 23, 10809–10814 (2003).
    1. Jensen O., Kaiser J. & Lachaux J. P. Human gamma-frequency oscillations associated with attention and memory. Trends Neurosci 30, 317–324 (2007).
    1. Beauchamp M. S., Sun P., Baum S. H., Tolias A. S. & Yoshor D. Electrocorticography links human temporoparietal junction to visual perception. Nat Neurosci 15, 957–959 (2012).
    1. Brookes M. J. et al. GLM-beamformer method demonstrates stationary field, alpha ERD and gamma ERS co-localisation with fMRI BOLD response in visual cortex. Neuroimage 26, 302–308 (2005).
    1. Gregoriou G. G., Gotts S. J., Zhou H. & Desimone R. High-frequency, long-range coupling between prefrontal and visual cortex during attention. Science 324, 1207–1210 (2009).
    1. Keil A., Muller M. M., Ray W. J., Gruber T. & Elbert T. Human gamma band activity and perception of a gestalt. J Neurosci 19, 7152–7161 (1999).
    1. Privman E. et al. Antagonistic relationship between gamma power and visual evoked potentials revealed in human visual cortex. Cereb Cortex 21, 616–624 (2011).
    1. Sokolov A. et al. Gamma-band MEG activity to coherent motion depends on task-driven attention. Neuroreport 10, 1997–2000 (1999).
    1. Tallon-Baudry C. & Bertrand O. Oscillatory gamma activity in humans and its role in object representation. Trends Cogn Sci 3, 151–162 (1999).
    1. Zion-Golumbic E. & Bentin S. Dissociated neural mechanisms for face detection and configural encoding: evidence from N170 and induced gamma-band oscillation effects. Cereb Cortex 17, 1741–1749 (2007).
    1. Orekhova E. V. et al. Excess of high frequency electroencephalogram oscillations in boys with autism. Biol Psychiatry 62, 1022–1029 (2007).
    1. Rojas D. C. et al. Transient and steady-state auditory gamma-band responses in first-degree relatives of people with autism spectrum disorder. Mol Autism 2, 11 (2011).
    1. Stroganova T. A. et al. High-frequency oscillatory response to illusory contour in typically developing boys and boys with autism spectrum disorders. Cortex 48, 701–717 (2012).
    1. Sun L. et al. Impaired gamma-band activity during perceptual organization in adults with autism spectrum disorders: evidence for dysfunctional network activity in frontal-posterior cortices. J Neurosci 32, 9563–9573 (2012).
    1. Sohal V. S., Zhang F., Yizhar O. & Deisseroth K. Parvalbumin neurons and gamma rhythms enhance cortical circuit performance. Nature 459, 698–702 (2009).
    1. Rubenstein J. L. & Merzenich M. M. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes Brain Behav 2, 255–267 (2003).
    1. Gudmundsson S., Runarsson T. P., Sigurdsson S., Eiriksdottir G. & Johnsen K. Reliability of quantitative EEG features. Clin Neurophysiol 118, 2162–2171 (2007).
    1. Gasser T., Jennen-Steinmetz C. & Verleger R. EEG coherence at rest and during a visual task in two groups of children. Electroencephalogr Clin Neurophysiol 67, 151–158 (1987).
    1. Lord C., Rutter M., DiLavore P. & Risi S. Autism Diagnostic Observation Schedule. (Western Psychological Services, Los Angeles, CA, 1999).
    1. Wing L., Leekam S. R., Libby S. J., Gould J. & Larcombe M. The Diagnostic Interview for Social and Communication Disorders: background, inter-rater reliability and clinical use. J Child Psychol Psychiatry 43, 307–325 (2002).
    1. Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (Washington D. C., 1994).
    1. Spreen O., & Strauss E., eds. A Compendium of Neuropsychological Tests (Oxford University Press, New York, 1998).

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