Disrupted Brain Network in Children with Autism Spectrum Disorder

Zeng, Ke; Kang, Jiannan; Ouyang, Gaoxiang; Li, Jingqing; Han, Jifeng; Wang, Yao; Sokhadze, Estate M.; Casanova, Manuel F.; Li, Xiaoli

doi:10.1038/s41598-017-16440-z

Cited by 61 publications

(45 citation statements)

References 53 publications

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“…This also encourages a better account of EEG complexity such as the spatial and electrophysiologic properties of information transfer between brain regions ( Mohammad-Rezazadeh et al, 2016 ). For example, graph methods were recently used to test both the temporal synchronization and the spatial organization of the resting state signal ( Zeng et al, 2017 ). They observed a deficit in synchronization between regions in ASD, mainly affecting the theta (fronto-occipital pathways) and the alpha bands (inter-hemispheric desynchronization), associated with a more significant deficit in the local clustering than in the long-range connections.…”

Section: Discussionmentioning

confidence: 99%

Alpha Waves as a Neuromarker of Autism Spectrum Disorder: The Challenge of Reproducibility and Heterogeneity

et al. 2018

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Background: There is no consensus in the literature concerning the presence of abnormal alpha wave profiles in patients with autism spectrum disorder (ASD). This may be due to phenotypic heterogeneity among patients as well as the limited sample sizes utilized. Here we present our results of alpha wave profile analysis based on a sample larger than most of those in the field, performed using a robust processing pipeline.Methods: We compared the alpha waves profiles at rest in children with ASD to those of age-, sex-, and IQ-matched control individuals. We used linear regression and non-parametric normative models using age as covariate forparsing the clinical heterogeneity. We explored the correlation between EEG profiles and the patient’s brain volumes, obtained from structural MRI. We automatized the detection of the alpha peak and visually quality controled our MRI measurements. We assessed the robustness of our results by running the EEG preprocessing with two different versions of Matlab as well as Python.Results: A simple linear regression between peak power or frequency of the alpha waves and the status or age of the participants did not allow to identify any statistically significant relationship. The non-parametric normative model (which took account the non-linear effect of age on the alpha profiles) suggested that participants with ASD displayed more variability than control participants for both frequency and amplitude of the alpha peak (p < 0.05). Independent of the status of the individual, we also observed weak associations (uncorrected p < 0.05) between the alpha frequency, and the volumes of several cortical and subcortical structures (in particular the striatum), but which did not survive correction for multiple testing and changed between analysis pelines.Discussions: Our study did not find evidence for abnormal alpha wave profiles in ASD. We propose, however, an analysis pipeline to perform standardized and automatized EEG analyses on large cohorts. These should help the community to address the challenge of clinical heterogeneity of ASD and to tackle the problems of reproducibility.

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Section: Discussionmentioning

confidence: 99%

Alpha Waves as a Neuromarker of Autism Spectrum Disorder: The Challenge of Reproducibility and Heterogeneity

et al. 2018

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“…Impaired cross-sensory phaseresetting, as might be predicted by reduced subcortical and cortical connectivity, would likely result in impaired integrative abilities. In autism, there is evidence for such disrupted connectivity (Zeng et al, 2017;Arnold Anteraper et al, 2018), although these findings are mixed and somewhat inconclusive (Vasa et al, 2016). Nevertheless, disrupted connectivity could in turn lead to impaired cross-sensory phaseresetting and hence contribute to impaired multisensory processing in ASD.…”

Section: Neural Basis Of Impaired Multisensory Processing In Autismmentioning

confidence: 99%

Developmental Recovery of Impaired Multisensory Processing in Autism and the Cost of Switching Sensory Modality

Crosse

Foxe

Molholm

2019

Preprint

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11Children with autism spectrum disorder (ASD) are often impaired in their ability to cope with and process 12 multisensory information, which may contribute to some of the social and communicative deficits that 13 are prevalent in this population. Amelioration of such deficits in adolescence has been observed for 14 ecologically-relevant stimuli such as speech. However, it is not yet known if this recovery generalizes to 15 the processing of nonsocial stimuli such as more basic beeps and flashes, typically used in cognitive 16 neuroscience research. We hypothesize that engagement of different neural processes and lack of 17 environmental exposure to such artificial stimuli leads to protracted developmental trajectories in both 18 neurotypical (NT) individuals and individuals with ASD, thus delaying the age at which we observe this 19 "catch up". Here, we test this hypothesis using a bisensory detection task by measuring human response 20 times to randomly presented auditory, visual and audiovisual stimuli. By measuring the behavioral gain 21 afforded by an audiovisual signal, we show that the multisensory deficit previously reported in children 22with ASD recovers in adulthood by the mid-twenties. In addition, we examine the effects of switching 23 between sensory modalities and show that teenagers with ASD incur less of a behavioral cost than their 24 NT peers. Computational modelling reveals that multisensory information interacts according to different 25 rules in children and adults, and that sensory evidence is weighted differently too. In ASD, weighting of 26 sensory information and allocation of attention during multisensory processing differs to that of NT 27 individuals. Based on our findings, we propose a theoretical framework of multisensory development in 28 NT and ASD individuals. 29

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“…Even though it is generally recognized that ASD is related to structural [2][3][4] and functional [5][6][7] network abnormalities, description of its extent and overall pattern has been rather heterogeneous. Indeed, while several attempts have been made to label the main neuroimaging phenotype of ASD, none of the frameworks have been without controversy.…”

Section: Introductionmentioning

confidence: 99%

Superior temporal sulcus hypoperfusion in children with autism spectrum disorder: an arterial spin-labeling magnetic resonance study

Saitovitch

Rechtman

Lemaître

et al. 2019

Preprint

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Advances in neuroimaging techniques have significantly improved our understanding of the neural basis of autism spectrum disorder (ASD). Several attempts have been made to label the main neuroimaging phenotype of ASD, mostly by anatomical and functional activation studies, but none of the frameworks have been without controversy. Over the past decade, a renewed interest for rest brain functioning has emerged in the scientific community, reflected on a large number of resting state fMRI (rs-fMRI) studies, but results remain heterogeneous. It is possible today to investigate rest brain functioning by measuring rest cerebral blood flow (CBF) with MRI using arterial spin labeling (ASL). Here, we investigated rest CBF abnormalities using noninvasive ASL-MRI in 18 children with ASD without cognitive delay (10.4 ± 2.8 y) and 30 typically developing children (10.6 ± 3.0 y). Following quality control, images from a final sample of 12 children with ASD (11.2 ± 2.9 y) and 28 typically developing children (10.1 ± 2.5 y) were analyzed. Whole brain voxel-by-voxel analysis showed significant rest CBF decrease in temporal regions, mainly in the superior temporal sulcus (STS), in children with ASD. This hypoperfusion was individually detected in 83% of children with ASD. Finally, negative correlation was observed between ASD severity scores and rest CBF in the right posterior STS. Strikingly, despite the small sample studied here, our results are extremely similar to previous PET and SPECT findings describing decreased rest CBF in the same superior temporal regions at group and individual levels, as well as correlation with symptoms severity. The congruence between these results, with different methods and in different ASD profiles, reinforce the strength of rest functional abnormalities within these superior temporal regions in ASD and strongly indicates it might be a core characteristic of the disorder. Identifying a core dysfunctional region in ASD bears direct implications to the development of novel therapeutic interventions, such as transcranial magnetic stimulation. In addition, if confirmed in a larger sample, rest temporal hypoperfusion could become a reliable brain imaging biomarker in ASD.

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Disrupted Brain Network in Children with Autism Spectrum Disorder

Cited by 61 publications

References 53 publications

Alpha Waves as a Neuromarker of Autism Spectrum Disorder: The Challenge of Reproducibility and Heterogeneity

Alpha Waves as a Neuromarker of Autism Spectrum Disorder: The Challenge of Reproducibility and Heterogeneity

Developmental Recovery of Impaired Multisensory Processing in Autism and the Cost of Switching Sensory Modality

Superior temporal sulcus hypoperfusion in children with autism spectrum disorder: an arterial spin-labeling magnetic resonance study

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