Early alterations of social brain networks in young children with autism

Sperdin, Holger Franz; Coito, Ana; Kojovic, Nada; Rihs, Tonia A.; Jan, Reem Kais; Franchini, Martina; Plomp, Gijs; Vulliémoz, Serge; Eliez, Stéphan; Michel, Christoph M.; Schaer, Marie

doi:10.7554/elife.31670

Cited by 40 publications

(29 citation statements)

References 90 publications

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“…These results would suggest the presence of alterations within these areas in children with ASD while viewing the social scenes. Recently, using directed functional connectivity analyses, based on electrical source imaging, we found altered connectivity in the theta frequency band within several of the frontal and the cingulate regions while children with ASD were watching movies of biological motion (28). This would suggest that alterations in the spatio-temporal EEG microstates and the directed functional connectivity are already present at early developmental stages in ASD.…”

Section: Discussionmentioning

confidence: 99%

“…EEG studies have shown that an abnormal pattern of brain activity in response to faces versus objects is present early in life in ASD (24–26) and that this abnormal pattern is also present in 10-month-old infants at risk for autism, suggesting that abnormality in face versus object processing is an early indicator of risk for developing ASD (27). Recently, by combining high-density EEG and eye-tracking, we found that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD (28, 29).…”

Section: Introductionmentioning

confidence: 99%

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Neural Processing of Dynamic Animated Social Interactions in Young Children With Autism Spectrum Disorder: A High-Density Electroencephalography Study

Jan

Rihs²,

Kojovic

et al. 2019

Front. Psychiatry

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Background: Atypical neural processing of social visual information contributes to impaired social cognition in autism spectrum disorder. However, evidence for early developmental alterations in neural processing of social contingencies is scarce. Most studies in the literature have been conducted in older children and adults. Here, we aimed to investigate alterations in neural processing of social visual information in children with autism spectrum disorder compared to age-matched typically developing peers. Methods: We used a combination of 129-channel electroencephalography and high-resolution eye-tracking to study differences in the neural processing of dynamic cartoons containing human-like social interactions between 14 male children with autism spectrum disorder and 14 typically developing male children, aged 2–5 years. Using a microstate approach, we identified four prototypical maps in both groups and compared the temporal characteristics and inverse solutions (activation of neural sources) of these maps between groups. Results: Inverse solutions of the group maps that were most dominant during free viewing of the dynamic cartoons indicated decreased prefrontal and cingulate activation, impaired activation of the premotor cortex, and increased activation of parietal, temporal, occipital, and cerebellar regions in children with autism spectrum disorder compared to their typically developing peers. Conclusions: Our findings suggest that impairments in brain regions involved in processing social contingencies embedded in dynamic cartoons are present from an early age in autism spectrum disorder. To the best of our knowledge, this is the first study to investigate neural processing of social interactions of children with autism spectrum disorder using dynamic semi-naturalistic stimuli.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Neural Processing of Dynamic Animated Social Interactions in Young Children With Autism Spectrum Disorder: A High-Density Electroencephalography Study

Jan

Rihs²,

Kojovic

et al. 2019

Front. Psychiatry

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“…Given that connectivity algorithms take scalar time-series as their input, and as ESI outputs 3D time-series (amplitudes in the x, y, and z direction), we then determined the predominant dipole orientation for each epoch and projected the x, y, and z time-series onto this dipole to obtain a scalar time-series, in the same way that we have previously described (Coito, Michel, van Mierlo, Vulliemoz, & Plomp, 2016;Sperdin et al, 2018). Following previous work, we first computed an average dipole direction considering only the 10% strongest norms of the dipoles across time and epochs.…”

Section: Electrical Source Imaging and Selection Of Regions Of Intementioning

confidence: 99%

Directed functional connections underlying spontaneous brain activity

Coito

Michel

Vulliémoz

et al. 2018

Human Brain Mapping

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Neuroimaging studies have shown that spontaneous brain activity is characterized as changing networks of coherent activity across multiple brain areas. However, the directionality of functional interactions between the most active regions in our brain at rest remains poorly understood. Here, we examined, at the whole‐brain scale, the main drivers and directionality of interactions that underlie spontaneous human brain activity by applying directed functional connectivity analysis to electroencephalography (EEG) source signals. We found that the main drivers of electrophysiological activity were the posterior cingulate cortex (PCC), the medial temporal lobes (MTL), and the anterior cingulate cortex (ACC). Among those regions, the PCC was the strongest driver and had both the highest integration and segregation importance, followed by the MTL regions. The driving role of the PCC and MTL resulted in an effective directed interaction directed from posterior toward anterior brain regions. Our results strongly suggest that the PCC and MTL structures are the main drivers of electrophysiological spontaneous activity throughout the brain and suggest that EEG‐based directed functional connectivity analysis is a promising tool to better understand the dynamics of spontaneous brain activity in healthy subjects and in various brain disorders.

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“…ASD is a neurodevelopmental disorder characterized by deficits in the social domain which represent hallmark early characteristics ( Sperdin et al, 2018 ). Even for simple visualization of FE, the literature is somewhat inconsistent: while some studies show group differences both in behavioral performance and neural responses, other studies show no identifiable deficits at all (for a compreensive review, see Monteiro et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

A Novel Biomarker of Compensatory Recruitment of Face Emotional Imagery Networks in Autism Spectrum Disorder

et al. 2018

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Imagery of facial expressions in Autism Spectrum Disorder (ASD) is likely impaired but has been very difficult to capture at a neurophysiological level. We developed an approach that allowed to directly link observation of emotional expressions and imagery in ASD, and to derive biomarkers that are able to classify abnormal imagery in ASD. To provide a handle between perception and action imagery cycles it is important to use visual stimuli exploring the dynamical nature of emotion representation. We conducted a case-control study providing a link between both visualization and mental imagery of dynamic facial expressions and investigated source responses to pure face-expression contrasts. We were able to replicate the same highly group discriminative neural signatures during action observation (dynamical face expressions) and imagery, in the precuneus. Larger activation in regions involved in imagery for the ASD group suggests that this effect is compensatory. We conducted a machine learning procedure to automatically identify these group differences, based on the EEG activity during mental imagery of facial expressions. We compared two classifiers and achieved an accuracy of 81% using 15 features (both linear and non-linear) of the signal from theta, high-beta and gamma bands extracted from right-parietal locations (matching the precuneus region), further confirming the findings regarding standard statistical analysis. This robust classification of signals resulting from imagery of dynamical expressions in ASD is surprising because it far and significantly exceeds the good classification already achieved with observation of neutral face expressions (74%). This novel neural correlate of emotional imagery in autism could potentially serve as a clinical interventional target for studies designed to improve facial expression recognition, or at least as an intervention biomarker.

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Early alterations of social brain networks in young children with autism

Cited by 40 publications

References 90 publications

Neural Processing of Dynamic Animated Social Interactions in Young Children With Autism Spectrum Disorder: A High-Density Electroencephalography Study

Neural Processing of Dynamic Animated Social Interactions in Young Children With Autism Spectrum Disorder: A High-Density Electroencephalography Study

Directed functional connections underlying spontaneous brain activity

A Novel Biomarker of Compensatory Recruitment of Face Emotional Imagery Networks in Autism Spectrum Disorder

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