Erratum to: A computer-generated animated face stimulus set for psychophysiological research.

Erratum to: Behav Res. DOI 10.3758/s13428-014-0491-x. The affiliations for four authors were erroneously printed. The correct affiliation for Adam Naples and James C. McPartland is: Yale Child Study Center, 230 South Frontage Road, New Haven 06520, CT, USA. The correct affiliation for Raphael Bernier and Anna Kresse is: University of Washington, Seattle, WA, USA.

A computer-generated animated face stimulus set for psychophysiological research.

Human faces are fundamentally dynamic, but experimental investigations of face perception have traditionally relied on static images of faces. Although naturalistic videos of actors have been used with success in some contexts, much research in neuroscience and psychophysics demands carefully controlled stimuli. In this article, we describe a novel set of computer-generated, dynamic face stimuli. These grayscale faces are tightly controlled for low- and high-level visual properties. All faces are standardized in terms of size, luminance, location, and the size of facial features. Each face begins with a neutral pose and transitions to an expression over the course of 30 frames. Altogether, 222 stimuli were created, spanning three different categories of movement: (1) an affective movement (fearful face), (2) a neutral movement (close-lipped, puffed cheeks with open eyes), and (3) a biologically impossible movement (upward dislocation of eyes and mouth). To determine whether early brain responses sensitive to low-level visual features differed between the expressions, we measured the occipital P100 event-related potential, which is known to reflect differences in early stages of visual processing, and the N170, which reflects structural encoding of faces. We found no differences between the faces at the P100, indicating that different face categories were well matched on low-level image properties. This database provides researchers with a well-controlled set of dynamic faces, controlled for low-level image characteristics, that are applicable to a range of research questions in social perception.

Frontal EEG alpha asymmetry in youth with autism: Sex differences and social-emotional correlates.

In youth broadly, EEG frontal alpha asymmetry (FAA) associates with affective style and vulnerability to psychopathology, with relatively stronger right activity predicting risk for internalizing and externalizing behaviors. In autistic youth, FAA has been related to ASD diagnostic features and to internalizing symptoms. Among our large, rigorously characterized, sex-balanced participant group, we attempted to replicate findings suggestive of altered FAA in youth with an ASD diagnosis, examining group differences and impact of sex assigned at birth. Second, we examined relations between FAA and behavioral variables (ASD features, internalizing, and externalizing) within autistic youth, examining effects by sex. Third, we explored whether the relation between FAA, autism features, and mental health was informed by maternal depression history. In our sample, FAA did not differ by diagnosis, age, or sex. However, youth with ASD had lower total frontal alpha power than youth without ASD. For autistic females, FAA and bilateral frontal alpha power correlated with social communication features, but not with internalizing or externalizing symptoms. For autistic males, EEG markers correlated with social communication features, and with externalizing behaviors. Exploratory analyses by sex revealed further associations between youth FAA, behavioral indices, and maternal depression history. In summary, findings suggest that individual differences in FAA may correspond to social-emotional and mental health behaviors, with different patterns of association for females and males with ASD. Longitudinal consideration of individual differences across levels of analysis (e.g., biomarkers, family factors, and environmental influences) will be essential to parsing out models of risk and resilience among autistic youth.

Language and Aggressive Behaviors in Male and Female Youth with Autism Spectrum Disorder.

Aggressive behaviors are common among youth with autism spectrum disorder (ASD) and correlate with pervasive social-emotional difficulties. Communication skill is an important correlate of disruptive behavior in typical development, and clarification of links between communication and aggression in ASD may inform intervention methods. We investigate child/family factors and communication in relation to aggression among 145 individuals with ASD (65 female; ages 8-17 years). Overall, more severe aggression was associated with younger age, lower family income, and difficulties with communication skills. However, this pattern of results was driven by males, and aggression was unrelated to child or family characteristics for females. Future work should incorporate these predictors in conjunction with broader contextual factors to understand aggressive behavior in females with ASD.

Modeling temporal dynamics of face processing in youth and adults.

A hierarchical model of temporal dynamics was examined in adults (n = 34) and youth (n = 46) across the stages of face processing during the perception of static and dynamic faces. Three ERP components (P100, N170, N250) and spectral power in the mu range were extracted, corresponding to cognitive stages of face processing: low-level vision processing, structural encoding, higher-order processing, and action understanding. Youth and adults exhibited similar yet distinct patterns of hierarchical temporal dynamics such that earlier cognitive stages predicted later stages, directly and indirectly. However, latent factors indicated unique profiles related to behavioral performance for adults and youth and age as a continuous factor. The application of path analysis to electrophysiological data can yield novel insights into the cortical dynamics of social information processing.

Resting state EEG in youth with ASD: age, sex, and relation to phenotype.

BACKGROUND: Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy. METHODS: We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations. RESULTS: Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD. CONCLUSIONS: Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

Electrophysiological Signals of Familiarity and Recency in the Infant Brain.

Electrophysiological work in nonhuman primates has established the existence of multiple types of signals in the temporal lobe that contribute to recognition memory, including information regarding a stimulus's relative novelty, familiarity, and recency of occurrence. We used high-density event-related potentials (ERPs) to examine whether young infants represent these distinct types of information about previously experienced items. Twenty-four different highly familiar and initially novel items were each repeated exactly once either immediately (Experiment 1), or following one intervening item (Experiment 2). A late slow wave (LSW) component of the ERP exhibited neural responses consistent with recency signals over right-central leads, but only when there were no intervening stimuli between repetitions. The LSW also exhibited responses consistent with familiarity signals over anterior-temporal leads, but only when there were intervening stimuli between repetitions. A mid-latency negative component (i.e., the Nc) also distinguished familiar from novel items, but did not exhibit a pattern of responding consistent with familiarity signals. These findings suggest that infants encode information about a variety of objects from their natural environments into long-term memory, and can discriminate between familiar and unfamiliar items, and between recently seen and new items, very quickly (within 1 sec). They also suggest that infants represent information about not only whether a stimulus is familiar or unfamiliar but also whether it has been seen recently.

Exploring the heterogeneity of neural social indices for genetically distinct etiologies of autism.

BACKGROUND: Autism spectrum disorder (ASD) is a genetically and phenotypically heterogeneous disorder. Promising initiatives utilizing interdisciplinary characterization of ASD suggest phenotypic subtypes related to specific likely gene-disrupting mutations (LGDMs). However, the role of functionally associated LGDMs in the neural social phenotype is unknown. METHODS: In this study of 26 children with ASD (n = 13 with an LGDM) and 13 control children, we characterized patterns of mu attenuation and habituation as children watched videos containing social and nonsocial motions during electroencephalography acquisition. RESULTS: Diagnostic comparisons were consistent with prior work suggesting aberrant mu attenuation in ASD within the upper mu band (10-12 Hz), but typical patterns within the lower mu band (8-10 Hz). Preliminary exploration indicated distinct social sensitization patterns (i.e., increasing mu attenuation for social motion) for children with an LGDM that is primarily expressed during embryonic development. In contrast, children with an LGDM primarily expressed post-embryonic development exhibited stable typical patterns of lower mu attenuation. Neural social indices were associated with social responsiveness, but not cognition. CONCLUSIONS: These findings suggest unique neurophysiological profiles for certain genetic etiologies of ASD, further clarifying possible genetic functional subtypes of ASD and providing insight into mechanisms for targeted treatment approaches.

Face processing among twins with and without autism: social correlates and twin concordance.

Autism spectrum disorder (ASD) has a strong heritable basis, as evidenced by twin concordance rates. Within ASD, symptom domains may arise via independent genetic contributions, with varying heritabilities and genetic mechanisms. In this article, we explore social functioning in the form of (i) electrophysiological and behavioral measures of face processing (P1 and N170) and (ii) social behavior among child and adolescent twins with (N = 52) and without ASD (N = 66). Twins without ASD had better holistic face processing and face memory, faster P1 responses and greater sensitivity to the effects of facial inversion on P1. In contrast, N170 responses to faces were similar across diagnosis, with more negative amplitudes for faces vs non-face images. Across the sample, stronger social skills and fewer social difficulties were associated with faster P1 and N170 responses to upright faces, and better face memory. Twins were highly correlated within pairs across most measures, but correlations were significantly stronger for monozygotic vs dizygotic pairs on N170 latency and social problems. We suggest common developmental influences across twins for face processing and social behavior, but highlight (i) neural speed of face processing and (ii) social difficulties as important avenues in the search for genetic underpinnings in ASD.

Modulation of mu attenuation to social stimuli in children and adults with 16p11.2 deletions and duplications.

BACKGROUND: Copy number variations (CNV) within the recurrent ~600 kb chromosomal locus of 16p11.2 are associated with a wide range of neurodevelopmental disorders, including autism spectrum disorder (ASD). However, little is known about the social brain phenotype of 16p11.2 CNV and how this phenotype is related to the social impairments associated with CNVs at this locus. The aim of this preliminary study was to use molecular subtyping to establish the social brain phenotype of individuals with 16p11.2 CNV and how these patterns relate to typical development and ASD. METHODS: We evaluated the social brain phenotype as expressed by mu attenuation in 48 children and adults characterized as duplication carriers (n = 12), deletion carriers (n = 12), individuals with idiopathic ASD (n = 8), and neurotypical controls (n = 16). Participants watched videos containing social and nonsocial motion during electroencephalogram (EEG) acquisition. RESULTS: Overall, only the typical group exhibited predicted patterns of mu modulation to social information (e.g., greater mu attenuation for social than nonsocial motion). Both 16p11.2 CNV groups exhibited more mu attenuation for nonsocial than social motion. The ASD group did not discriminate between conditions and demonstrated less mu attenuation compared to the typical and duplication carriers. Single-trial analysis indicated that mu attenuation decreased over time more rapidly for 16p11.2 CNV groups than the typical group. The duplication group did not diverge from typical patterns of mu attenuation until after initial exposure. CONCLUSIONS: These results indicate atypical but unique patterns of mu attenuation for deletion and duplication carriers, highlighting the need to continue characterizing the social brain phenotype associated with 16p11.2 CNVs.

EEG mu rhythm in typical and atypical development.

Electroencephalography (EEG) is an effective, efficient, and noninvasive method of assessing and recording brain activity. Given the excellent temporal resolution, EEG can be used to examine the neural response related to specific behaviors, states, or external stimuli. An example of this utility is the assessment of the mirror neuron system (MNS) in humans through the examination of the EEG mu rhythm. The EEG mu rhythm, oscillatory activity in the 8-12 Hz frequency range recorded from centrally located electrodes, is suppressed when an individual executes, or simply observes, goal directed actions. As such, it has been proposed to reflect activity of the MNS. It has been theorized that dysfunction in the mirror neuron system (MNS) plays a contributing role in the social deficits of autism spectrum disorder (ASD). The MNS can then be noninvasively examined in clinical populations by using EEG mu rhythm attenuation as an index for its activity. The described protocol provides an avenue to examine social cognitive functions theoretically linked to the MNS in individuals with typical and atypical development, such as ASD.