Altered task‐related modulation of long‐range connectivity in children with autism

Pillai, Ajay S.; McAuliffe, Danielle; Lakshmanan, Balaji M.; Mostofsky, Stewart H.; Crone, Nathan E.; Ewen, Joshua B.

doi:10.1002/aur.1858

Cited by 24 publications

(13 citation statements)

References 78 publications

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“…We selected regions of interest (ROI) targeting the left and right primary cortex based on experience with prior motor‐control datasets (Ewen et al, ; Ewen, Lakshmanan, et al, ; Ewen, Pillai, et al, ; Pillai et al, ; Figure ). For ease of language, we will refer to brain activity relative to the side of the intentional movement.…”

Section: Methodsmentioning

confidence: 99%

Increased mirror overflow movements in ADHD are associated with altered EEG alpha/beta band desynchronization

McAuliffe

Hirabayashi

Adamek

et al. 2019

Eur J of Neuroscience

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Children with ADHD show developmentally abnormal levels of mirror overflowunintentional movements occurring symmetrically opposite of intentional movements. Because mirror overflow correlates with ADHD behavioral symptoms, the study of disinhibition in motor control may shed light on physiologic mechanisms underlying impaired behavioral/cognitive control. This is a case-controlled study of EEG recording from 25 children with ADHD and 25 typically developing (TD) controls performing unilateral sequential finger tapping, with overflow movements measured using electronic goniometers. Consistent with previously published findings, children with ADHD showed increased mirror overflow as compared with TD peers. EEG findings revealed less lateralized alpha modulation (event-related desynchronization; ERD) and decreased magnitude of beta ERD in ADHD; both alpha and beta ERD reflect cortical activation. Moderation analysis revealed a significant association between beta ERD and overflow, independent of diagnosis; and an equivocal (p = .08) effect of diagnosis on the relationship between alpha ERD and overflow, with a significant effect in children with ADHD but not TD children. These results suggest two mechanisms involved with mirror overflow: one reflected in beta ipsilateral to the intentional movement and relevant to both children with ADHD and controls, and the other seemingly more specific to ADHD (alpha, contralateral to movement). K E Y W O R D SEEG, moderation analysis, motor control, sensory-motor rhythm 1816 | MCAULIFFE Et AL.

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Section: Methodsmentioning

confidence: 99%

Increased mirror overflow movements in ADHD are associated with altered EEG alpha/beta band desynchronization

McAuliffe

Hirabayashi

Adamek

et al. 2019

Eur J of Neuroscience

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“…Tsiaras et al ( 2011 ) used a well-established graph measures which served as features in classifying controls and young adults with ASD. Pillai et al ( 2018 ) used the electroencephalography (EEG) and a movement-based paradigm to examine the FC changes in ASD children while performing specific tasks. Anderson et al ( 2011 ) characterized a whole-brain functional connectivity abnormalities in a data-driven fashion to identify the regions showing greatest differences between individual subjects with autism and developing controls.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis

Soussia

Rekik

2018

Front. Neuroinform.

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Brain disorders, such as Autism Spectrum Disorder (ASD), alter brain functional (from fMRI) and structural (from diffusion MRI) connectivities at multiple levels and in varying degrees. While unraveling such alterations have been the focus of a large number of studies, morphological brain connectivity has been out of the research scope. In particular, shape-to-shape relationships across brain regions of interest (ROIs) were rarely investigated. As such, the use of networks based on morphological brain data in neurological disorder diagnosis, while leveraging the advent of machine learning, could complement our knowledge on brain wiring alterations in unprecedented ways. In this paper, we use conventional T1-weighted MRI to define morphological brain networks (MBNs), each quantifying shape relationship between different cortical regions for a specific cortical attribute at both low-order and high-order levels. While typical brain connectomes investigate the relationship between two ROIs, we propose high-order MBN which better captures brain complex interactions by modeling the morphological relationship between pairs of ROIs. For ASD identification, we present a connectomic manifold learning framework, which learns multiple kernels to estimate a similarity measure between ASD and normal controls (NC) connectional features, to perform dimensionality reduction for clustering ASD and NC subjects. We benchmark our ASD identification method against both supervised and unsupervised state-of-the-art methods, while depicting the most discriminative high- and low-order relationships between morphological regions in the left and right hemispheres.

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“…Motor impairments have been known in ASD since Kanner's original description [Kanner, ] and are highly prevalent in the disorder [Vanvuchelen, Roeyers, & De Weerdt, ; Weimer, Schatz, Lincoln, Ballantyne, & Trauner, ]. They may be either reflective of the similar pathophysiological processes that cause the cardinal symptoms of ASD or even causally involved in the pathophysiology of the social‐communicative phenotype [Denckla, ; Ewen et al, ; Gowen & Hamilton, ; Lloyd, MacDonald, & Lord, ; Mostofsky et al, ; Mostofsky & Ewen, ; Mous et al, ; Pillai et al, ]. Severe congenital motor deficits—cerebral palsy—are independently associated with epilepsy [Gururaj, Sztriha, Bener, Dawodu, & Eapen, ; Wallace, ], but such severe deficits make up only a small fraction of the high proportion of children with ASD who often have more subtle motor deficits.…”

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confidence: 99%

Epilepsy and Autism Severity: A Study of 6,975 Children

Ewen

Marvin²,

Law

et al. 2019

Autism Research

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Epilepsy is known to occur in a higher-than-expected proportion of individuals with autism spectrum disorders (ASDs). Prior studies of this heterogeneous disorder have suggested that intelligence quotient (IQ) may drive this relationship. Because intellectual disability (ID) is, independently of ASD, a risk factor for epilepsy, current literature calls into question the long-understood unique relationship between ASD and epilepsy. Second, data have been unclear about whether developmental regression in ASD is associated with epilepsy. Using two cohorts from an online research registry, totaling 6,975 children with ASD, we examined the independent role of four ASD severity measures in driving the relationship with epilepsy: ID, language impairment, core ASD symptom severity, and motor dysfunction, controlling for two known relevant factors: age and sex. We also examined whether developmental regression and epilepsy have an independent statistical link. All four ASD severity factors showed independent statistical associations with epilepsy in one cohort, and three in the other. ID showed the largest relative risk (RR) in both cohorts. Effect sizes were modest. Regression similarly showed an independent statistical association with epilepsy, but with small effect size. Similar to previous work, ID showed the greatest contribution to RR for epilepsy among children with ASD. However, other ASD severity markers showed statistical associations, demonstrating that the ASD-epilepsy association is not reducible to the effect of ID. Inconsistencies in the literature may be due to underpowered studies, yet moving forward with larger-n studies, clinical significance and scientific relevance may be dictated by effect size and not merely statistical significance.Lay Summary: Epilepsy is known to occur more often in individuals with autism spectrum disorders (ASDs) than is the case in the general population. The association between ASD and epilepsy is of interest because studying the two disorders in combination may help advance our understanding of genetic, molecular, and cellular mechanisms-as well as therapies-for both. Recent studies have suggested that intelligence quotient (IQ) alone in individuals with ASD may account for the increased prevalence of epilepsy. However, our approach was to look at a range of severity factors relevant to ASD and to look for correlations between each severity factor and epilepsy, within two large samples of children with ASD. In summary, we found that each severity factor-presence of intellectual disability, presence of language atypicalities, ASD-specific symptoms severity, and presence of motor issues-independently predicted a small increased risk for epilepsy, countering the argument that IQ alone is a risk factor. We also examined whether epilepsy is associated with developmental regression. Although severe epilepsy syndromes such as Landau-Kleffner syndrome are known to cause autistic-like symptoms following developmental regression, there is controversy about whether other forms of epil...

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Altered task‐related modulation of long‐range connectivity in children with autism

Cited by 24 publications

References 78 publications

Increased mirror overflow movements in ADHD are associated with altered EEG alpha/beta band desynchronization

Increased mirror overflow movements in ADHD are associated with altered EEG alpha/beta band desynchronization

Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis

Epilepsy and Autism Severity: A Study of 6,975 Children

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