Atypicality of the N170 Event-Related Potential in Autism Spectrum Disorder: A Meta-analysis

Background: Autism spectrum disorder (ASD) is associated with impaired face processing. The N170 event-related potential (ERP) has been considered a promising neural marker of this impairment. However, no quantitative review to date has integrated the literature to assess whether the N170 response to faces in individuals with ASD differs from that of typically developing (TD) individuals.

Methods: This meta-analysis examined the corpus of literature investigating difference in N170 response to faces in individuals with ASD and without ASD. Data from 23 studies (NASD = 374, NTD = 359) were reviewed. Meta-analysis was used to examine the effect size of the difference in N170 latency and amplitude among individuals with ASD and without ASD. Analyses were also conducted examining hemispheric differences, potential moderators, and publication bias.

Results: On average, N170 latencies to faces were delayed in individuals with ASD, but amplitudes did not differ for individuals with ASD and TD individuals. Moderator analyses revealed that N170 amplitudes were smaller in magnitude in the ASD participants relative to the TD participants in adult samples and in those with higher cognitive ability. However, effects differed as a function of hemisphere of recording. No evidence of publication bias was found.

Conclusions: Atypicality of N170-particularly latency-to faces appears to be a specific biomarker of social-communicative dysfunction in ASD and may relate to differential developmental experiences and use of compensatory cognitive mechanisms. Future research should examine phenotypic differences that contribute to N170 heterogeneity, as well as specificity of N170 differences in ASD versus non-ASD clinical populations, and N170 malleability with treatment.

Keywords: Autism spectrum disorder (ASD); Electroencephalography (EEG); Event-related potential (ERP); Face processing; Meta-analysis; N170.

The parts of the body that are used to produce and perceive signed languages (the hands, face, and visual system) differ from those used to produce and perceive spoken languages (the vocal tract and auditory system). In this paper we address two factors that have important consequences for sign language acquisition. First, there are three types of lexical signs: one-handed, two-handed symmetrical, and two-handed asymmetrical. Natural variation in hand dominance in the population leads to varied input to children learning sign. Children must learn that signs are not specified for the right or left hand but for dominant and non-dominant. Second, we posit that children have at least four imitation strategies available for imitating signs: anatomical (Activate the same muscles as the sign model), which could lead learners to inappropriately use their non-dominant hand; mirroring (Produce a mirror image of the modeled sign), which could lead learners to produce lateral movement reversal errors or to use the non-dominant hand; visual matching (Reproduce what you see from your perspective), which could lead learners to produce inward-outward movement and palm orientation reversals; and reversing (Reproduce what the sign model would see from his/her perspective). This last strategy is the only one that always yields correct phonological forms in signed languages. To test our hypotheses, we turn to evidence from typical and atypical hearing and deaf children as well as from typical adults; the data come from studies of both sign acquisition and gesture imitation. Specifically, we posit that all children initially use a visual matching strategy but typical children switch to a mirroring strategy sometime in the second year of life; typical adults tend to use a mirroring strategy in learning signs and imitating gestures. By contrast, children and adults with autism spectrum disorder (ASD) appear to use the visual matching strategy well into childhood or even adulthood. Finally, we present evidence that sign language exposure changes how adults imitate gestures, switching from a mirroring strategy to the correct reversal strategy. These four strategies for imitation do not exist in speech and as such constitute a unique problem for research in language acquisition.

Keywords: American Sign Language (ASL); Autism Spectrum Disorders (ASD); imitation; language acquisition; sign language; visual perspective-taking.

Electroenchephalography (EEG) recordings collected with developmental populations present particular challenges from a data processing perspective. These EEGs have a high degree of artifact contamination and often short recording lengths. As both sample sizes and EEG channel densities increase, traditional processing approaches like manual data rejection are becoming unsustainable. Moreover, such subjective approaches preclude standardized metrics of data quality, despite the heightened importance of such measures for EEGs with high rates of initial artifact contamination. There is presently a paucity of automated resources for processing these EEG data and no consistent reporting of data quality measures. To address these challenges, we propose the Harvard Automated Processing Pipeline for EEG (HAPPE) as a standardized, automated pipeline compatible with EEG recordings of variable lengths and artifact contamination levels, including high-artifact and short EEG recordings from young children or those with neurodevelopmental disorders. HAPPE processes event-related and resting-state EEG data from raw files through a series of filtering, artifact rejection, and re-referencing steps to processed EEG suitable for time-frequency-domain analyses. HAPPE also includes a post-processing report of data quality metrics to facilitate the evaluation and reporting of data quality in a standardized manner. Here, we describe each processing step in HAPPE, perform an example analysis with EEG files we have made freely available, and show that HAPPE outperforms seven alternative, widely-used processing approaches. HAPPE removes more artifact than all alternative approaches while simultaneously preserving greater or equivalent amounts of EEG signal in almost all instances. We also provide distributions of HAPPE’s data quality metrics in an 867 file dataset as a reference distribution and in support of HAPPE’s performance across EEG data with variable artifact contamination and recording lengths. HAPPE software is freely available under the terms of the GNU General Public License at https://github.com/lcnhappe/happe.

Keywords: EEG; EEG processing; artifact removal; automated; data quality; development; electroencephalography; pipeline.

2018Alycia Halladay

Background: The male predominance in the prevalence of autism spectrum disorder (ASD) has motivated research on sex differentiation in ASD. Multiple sources of evidence have suggested a neurophenotypic convergence of ASD-related characteristics and typical sex differences. Two existing, albeit competing, models provide predictions on such neurophenotypic convergence. These two models are testable with neuroimaging. Specifically, the Extreme Male Brain (EMB) model predicts that ASD is associated with enhanced brain maleness in both males and females with ASD (i.e., a shift-towards-maleness). In contrast, the Gender Incoherence (GI) model predicts a shift-towards-maleness in females, yet a shift-towards-femaleness in males with ASD.

Methods: To clarify whether either model applies to the intrinsic functional properties of the brain in males with ASD, we measured the statistical overlap between typical sex differences and ASD-related atypicalities in resting-state fMRI (R-fMRI) datasets largely available in males. Main analyses focused on two large-scale R-fMRI samples: 357 neurotypical (NT) males and 471 NT females from the 1000 Functional Connectome Project and 360 males with ASD and 403 NT males from the Autism Brain Imaging Data Exchange.

Results: Across all R-fMRI metrics, results revealed coexisting, but network-specific, shift-towards-maleness and shift-towards-femaleness in males with ASD. A shift-towards-maleness mostly involved the default network, while a shift-towards-femaleness mostly occurred in the somatomotor network. Explorations of the associated cognitive processes using available cognitive ontology maps indicated that higher-order social cognitive functions corresponded to the shift-towards-maleness, while lower-order sensory motor processes corresponded to the shift-towards-femaleness.

Conclusions: The present findings suggest that atypical intrinsic brain properties in males with ASD partly reflect mechanisms involved in sexual differentiation. A model based on network-dependent atypical sex mosaicism can synthesize prior competing theories on factors involved in sex differentiation in ASD.

Keywords: Autism spectrum disorder; Extreme Male Brain; Gender Incoherence; Resting-state fMRI; Sex differentiation; Sex mosaicism.

Neurons in the primate medial temporal lobe (MTL) respond selectively to visual categories such as faces, contributing to how the brain represents stimulus meaning. However, it remains unknown whether MTL neurons continue to encode stimulus meaning when it changes flexibly as a function of variable task demands imposed by goal-directed behavior. While classically associated with long-term memory, recent lesion and neuroimaging studies show that the MTL also contributes critically to the online guidance of goal-directed behaviors such as visual search. Do such tasks modulate responses of neurons in the MTL, and if so, do their responses mirror bottom-up input from visual cortices or do they reflect more abstract goal-directed properties? To answer these questions, we performed concurrent recordings of eye movements and single neurons in the MTL and medial frontal cortex (MFC) in human neurosurgical patients performing a memory-guided visual search task. We identified a distinct population of target-selective neurons in both the MTL and MFC whose response signaled whether the currently fixated stimulus was a target or distractor. This target-selective response was invariant to visual category and predicted whether a target was detected or missed behaviorally during a given fixation. The response latencies, relative to fixation onset, of MFC target-selective neurons preceded those in the MTL by ∼200 ms, suggesting a frontal origin for the target signal. The human MTL thus represents not only fixed stimulus identity, but also task-specified stimulus relevance due to top-down goal relevance.

Keywords: amygdala; category selectivity; goal relevance; hippocampus; human single neuron; medial frontal cortex; medial temporal lobe; response latency; target detection; visual search.

Social neuroscience research investigating autism spectrum disorder (ASD) has yielded inconsistent findings, despite ASD being well-characterized by difficulties in social interaction and communication through behavioral observation. In particular, specific etiologies and functional and structural assays of the brain in autism have not been consistently identified. To date, most social neuroscience research has focused on a single person viewing static images. Research utilizing interactive social neuroscience featuring dual-brain recording offers great promise for the study of neurodevelopmental disabilities. Reward processing has been implicated in the pathology of ASD, yet mixed findings have brought uncertainty about the role reward processing deficits may play in ASD. The current study employed dual-brain EEG recording to examine reward processing during live interaction and its relation to autistic traits. Sixteen typically developing (TD) adults played a competitive treasure-hunt game against a computer and against a human partner. EEG results revealed enhanced neural sensitivity to reward outcome during live interaction with a human competitor. Further, individuals with higher levels of autistic traits demonstrated reduced sensitivity to reward outcome during live interaction. These findings provide novel insight into reward processing mechanisms associated with autistic traits, as well as support the necessary utility of interactive social neuroscience techniques to study developmental disorders.

Keywords: Autism spectrum disorder; EEG/ERP; interactive social neuroscience; reward.