Modeling intra-individual inter-trial EEG response variability in autism.

Autism spectrum disorder (autism) is a prevalent neurodevelopmental condition characterized by early emerging impairments in social behavior and communication. EEG represents a powerful and non-invasive tool for examining functional brain differences in autism. Recent EEG evidence suggests that greater intra-individual trial-to-trial variability across EEG responses in stimulus-related tasks may characterize brain differences in autism. Traditional analysis of EEG data largely focuses on mean trends of the trial-averaged data, where trial-level analysis is rarely performed due to low neural signal to noise ratio. We propose to use nonlinear (shape-invariant) mixed effects (NLME) models to study intra-individual inter-trial EEG response variability using trial-level EEG data. By providing more precise metrics of response variability, this approach could enrich our understanding of neural disparities in autism and potentially aid the identification of objective markers. The proposed multilevel NLME models quantify variability in the signal's interpretable and widely recognized features (e.g., latency and amplitude) while also regularizing estimation based on noisy trial-level data. Even though NLME models have been studied for more than three decades, existing methods cannot scale up to large data sets. We propose computationally feasible estimation and inference methods via the use of a novel minorization-maximization (MM) algorithm. Extensive simulations are conducted to show the efficacy of the proposed procedures. Applications to data from a large national consortium find that children with autism have larger intra-individual inter-trial variability in P1 latency in a visual evoked potential (VEP) task, compared to their neurotypical peers.

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.

Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.

Impact of autism genetic risk on brain connectivity: a mechanism for the female protective effect.

The biological mechanisms underlying the greater prevalence of autism spectrum disorder in males than females remain poorly understood. One hypothesis posits that this female protective effect arises from genetic load for autism spectrum disorder differentially impacting male and female brains. To test this hypothesis, we investigated the impact of cumulative genetic risk for autism spectrum disorder on functional brain connectivity in a balanced sample of boys and girls with autism spectrum disorder and typically developing boys and girls (127 youth, ages 8-17). Brain connectivity analyses focused on the salience network, a core intrinsic functional connectivity network which has previously been implicated in autism spectrum disorder. The effects of polygenic risk on salience network functional connectivity were significantly modulated by participant sex, with genetic load for autism spectrum disorder influencing functional connectivity in boys with and without autism spectrum disorder but not girls. These findings support the hypothesis that autism spectrum disorder risk genes interact with sex differential processes, thereby contributing to the male bias in autism prevalence and proposing an underlying neurobiological mechanism for the female protective effect.

Systematic review: emotion dysregulation and challenging behavior interventions for children and adolescents on the autism spectrum with graded key evidence-based strategy recommendations.

Challenging behavior, such as aggression, is highly prevalent in children and adolescents on the autism spectrum and can have a devastating impact. Previous reviews of challenging behavior interventions did not include interventions targeting emotion dysregulation, a common cause of challenging behavior. We reviewed emotion dysregulation and challenging behavior interventions for preschoolers to adolescents to determine which evidence-based strategies have the most empirical support for reducing/preventing emotion dysregulation/challenging behavior. We reviewed 95 studies, including 29 group and 66 single case designs. We excluded non-behavioral/psychosocial interventions and those targeting internalizing symptoms only. We applied a coding system to identify discrete strategies based on autism practice guidelines with the addition of strategies common in childhood mental health disorders, and an evidence grading system. Strategies with the highest quality evidence (multiple randomized controlled trials with low bias risk) were Parent-Implemented Intervention, Emotion Regulation Training, Reinforcement, Visual Supports, Cognitive Behavioral/Instructional Strategies and Antecedent-Based Interventions. Regarding outcomes, most studies included challenging behavior measures, while few included emotion dysregulation measures. This review highlights the importance of teaching emotion regulation skills explicitly, positively reinforcing replacement/alternative behaviors, using visuals and metacognition, addressing stressors proactively, and involving parents. It also calls for more rigorously designed studies and for including emotion dysregulation as an outcome/mediator in future trials.

Multilevel hybrid principal components analysis for region-referenced functional electroencephalography data.

Electroencephalography experiments produce region-referenced functional data representing brain signals in the time or the frequency domain collected across the scalp. The data typically also have a multilevel structure with high-dimensional observations collected across multiple experimental conditions or visits. Common analysis approaches reduce the data complexity by collapsing the functional and regional dimensions, where event-related potential (ERP) features or band power are targeted in a pre-specified scalp region. This practice can fail to portray more comprehensive differences in the entire ERP signal or the power spectral density (PSD) across the scalp. Building on the weak separability of the high-dimensional covariance process, the proposed multilevel hybrid principal components analysis (M-HPCA) utilizes dimension reduction tools from both vector and functional principal components analysis to decompose the total variation into between- and within-subject variance. The resulting model components are estimated in a mixed effects modeling framework via a computationally efficient minorization-maximization algorithm coupled with bootstrap. The diverse array of applications of M-HPCA is showcased with two studies of individuals with autism. While ERP responses to match vs mismatch conditions are compared in an audio odd-ball paradigm in the first study, short-term reliability of the PSD across visits is compared in the second. Finite sample properties of the proposed methodology are studied in extensive simulations.

A neurogenetic analysis of female autism.

Females versus males are less frequently diagnosed with autism spectrum disorder (ASD), and while understanding sex differences is critical to delineating the systems biology of the condition, female ASD is understudied. We integrated functional MRI and genetic data in a sex-balanced sample of ASD and typically developing youth (8-17 years old) to characterize female-specific pathways of ASD risk. Our primary objectives were to: (i) characterize female ASD (n = 45) brain response to human motion, relative to matched typically developing female youth (n = 45); and (ii) evaluate whether genetic data could provide further insight into the potential relevance of these brain functional differences. For our first objective we found that ASD females showed markedly reduced response versus typically developing females, particularly in sensorimotor, striatal, and frontal regions. This difference between ASD and typically developing females does not resemble differences between ASD (n = 47) and typically developing males (n = 47), even though neural response did not significantly differ between female and male ASD. For our second objective, we found that ASD females (n = 61), versus males (n = 66), showed larger median size of rare copy number variants containing gene(s) expressed in early life (10 postconceptual weeks to 2 years) in regions implicated by the typically developing female > female functional MRI contrast. Post hoc analyses suggested this difference was primarily driven by copy number variants containing gene(s) expressed in striatum. This striatal finding was reproducible among n = 2075 probands (291 female) from an independent cohort. Together, our findings suggest that striatal impacts may contribute to pathways of risk in female ASD and advocate caution in drawing conclusions regarding female ASD based on male-predominant cohorts.

Higher Depressive Symptoms Predict Lower Social Adaptive Functioning in Children and Adolescents with ASD.

Objective: Despite the frequent occurrence of depressive symptoms in children and adolescents with autism spectrum disorder (ASD), few studies have investigated the relationship between depressive symptoms and adaptive functioning. The present study explored the impact of depressive symptoms on different domains of adaptive functioning in children and adolescents with ASD.Methods: Depressive symptoms and adaptive functioning were analyzed in 62 children and adolescents with ASD (20 females) and 36 children and adolescents (15 females) with typical development between 5 and 18 years of age.Results: After controlling for IQ, age and sex, higher depressive symptoms predicted lower functioning in the social domain among children and adolescents with ASD. Depressive symptoms did not significantly predict communication or daily living skills.Conclusions: These findings highlight the relevance of depression in social adaptive function in ASD and emphasize the importance of assessing depressive symptomatology when evaluating social skills and planning treatment for children and adolescents with ASD.

Autism spectrum traits predict higher social psychological skill.

Social-cognitive skills can take different forms, from accurately predicting individuals' intentions, emotions, and thoughts (person perception or folk psychology) to accurately predicting social phenomena more generally. Past research has linked autism spectrum (AS) traits to person perception deficits in the general population. We tested whether AS traits also predict poor accuracy in terms of predicting generalized social phenomena, assessed via participants' accuracy at predicting social psychological phenomena (e.g., social loafing, social projection, group think). We found the opposite. In a sample of ∼6,500 participants in 104 countries, AS traits predicted slightly higher social psychological skill. A second study with 400 participants suggested that heightened systemizing underlies this relationship. Our results indicate that AS traits relate positively to a form of social cognitive skill-predicting social psychological phenomena-and highlight the importance of distinguishing between divergent types of social cognition.

Sex Differences in Functional Connectivity of the Salience, Default Mode, and Central Executive Networks in Youth with ASD.

Autism spectrum disorder (ASD) is associated with the altered functional connectivity of 3 neurocognitive networks that are hypothesized to be central to the symptomatology of ASD: the salience network (SN), default mode network (DMN), and central executive network (CEN). Due to the considerably higher prevalence of ASD in males, however, previous studies examining these networks in ASD have used primarily male samples. It is thus unknown how these networks may be differentially impacted among females with ASD compared to males with ASD, and how such differences may compare to those observed in neurotypical individuals. Here, we investigated the functional connectivity of the SN, DMN, and CEN in a large, well-matched sample of girls and boys with and without ASD (169 youth, ages 8-17). Girls with ASD displayed greater functional connectivity between the DMN and CEN than boys with ASD, whereas typically developing girls and boys differed in SN functional connectivity only. Together, these results demonstrate that youth with ASD exhibit altered sex differences in these networks relative to what is observed in typical development, and highlight the importance of considering sex-related biological factors and participant sex when characterizing the neural mechanisms underlying ASD.

Autism's existential crisis: a reflection on Livingston et al. (2018).

Livingston and colleagues present an empirical investigation of the compensatory framework describing the autism clinical phenotype as the sum of intrinsic neurocognitive deficits and compensatory mechanisms. This commentary highlights several methodologic features of the study that are pertinent to interpretation and reflects on the reduction of social behavior to cognitive processes. Taken together, the notion of compensation calls into question the validity and utility of the current behavioral diagnosis of autism.

Autistic and alexithymic traits modulate distinct aspects of face perception.

BACKGROUND: Atypical face processing is a prominent feature of autism spectrum disorder (ASD) but is not universal and is subject to individual variability. This heterogeneity could be accounted for by reliable yet unidentified subgroups within the diverse population of individuals with ASD. Alexithymia, which is characterized by difficulties in emotion recognition and identification, serves as a potential grouping factor. Recent research demonstrates that emotion recognition impairments in ASD are predicted by its comorbidity with alexithymia. The current study assessed the relative influence of autistic versus alexithymic traits on neural indices of face and emotion perception. METHODS: Capitalizing upon the temporal sensitivity of event-related potentials (ERPs), it investigates the distinct contributions of alexithymic versus autistic traits at specific stages of emotional face processing in 27 typically developing adults (18 female). ERP components reflecting sequential stages of perceptual processing (P100, N170 and N250) were recorded in response to fear and neutral faces. RESULTS: The results indicated that autistic traits were associated with structural encoding of faces (N170), whereas alexithymic traits were associated with more complex emotion decoding (N250). CONCLUSIONS: These findings have important implications for deconstructing heterogeneity within ASD.

Normalization of Speech Processing After Whole-Vault Cranioplasty in Sagittal Synostosis.

BACKGROUND: Neurocognitive studies have found impairments in language-related abilities in nonsyndromic craniosynostosis, highlighting clinical importance of early language processing. In this study, neural response to speech sounds in infants with nonsyndromic sagittal craniosynostosis (NSC) is compared, preoperatively and postoperatively, using event-related potentials (ERPs) to objectively characterize development in language processing. METHODS: Electroencephalogram was recorded while 39 infants (12 NSC and 27 controls; ages 73-283 days) listened to the Hindi dental /(Equation is included in full-text article.)a/ and retroflex /da/ phonemes (non-native phonemic discrimination task). The mismatch negativity (MMN) ERP was extracted as the peak amplitude of the largest negative deflection in the difference wave over 80 to 300 milliseconds poststimulus. Differences in MMN were analyzed using repeated measures analysis of variance. RESULTS: The MMN amplitude was attenuated in the infants with NSC preoperatively compared with controls (P = 0.047). A significant region by group interaction (P = 0.045) was observed, and infants with NSC displayed attenuated MMN in the frontal electrodes compared with controls (P = 0.010). Comparing the preoperative and postoperative MMN, a time by group interaction trend (P = 0.070) was observed. Pair-wise comparisons showed a trend for increase in MMN amplitude from preoperatively to postoperatively in the infants with NSC (P = 0.059). At the postoperative time point, infants with NSC showed no significant difference in MMN from controls (P = 0.344). CONCLUSION: Infants with NSC demonstrated atypical neural response to language preoperatively. After undergoing surgery, infants with NSC showed increased MMN amplitude which was not significantly different from controls. These findings support the idea that whole vault cranioplasty may improve neurocognitive outcomes in sagittal craniosynostosis.

Considerations in biomarker development for neurodevelopmental disorders.

PURPOSE OF REVIEW: Despite significant progress in recognizing the biological bases of autism spectrum disorder, diagnosis and treatment rely primarily on subjective evaluation of behavior. This review highlights the challenges unique to neurodevelopmental disorders that have limited biomarker development. RECENT FINDINGS: The field of neurodevelopmental disorders requires objective quantification of biological processes to enable designation of subgroups likely to benefit from specific treatments, index diagnostic status/risk, demonstrate engagement of targeted systems, and provide more rapid assessment of change than traditional clinical observation and caregiver report measures. SUMMARY: Useful biomarkers for neurodevelopmental disorders must be reliable across development, evident at the individual level, and specific to a unit of analysis, be it diagnostic status or functional process. The ultimate value of biomarkers for neurodevelopmental disorders will relate to their ease of use, cost, scalability, sensitivity, and methodological objectivity.

Direct brain recordings reveal impaired neural function in infants with single-suture craniosynostosis: a future modality for guiding management?

BACKGROUND: Patients with single-suture craniosynostosis (SSC) are at an elevated risk for long-term learning disabilities. Such adverse outcomes indicate that the early development of neural processing in SSC may be abnormal. At present, however, the precise functional derangements of the developing brain remain largely unknown. Event-related potentials (ERPs) are a form of noninvasive neuroimaging that provide direct measurements of cortical activity and have shown value in predicting long-term cognitive functioning. The current study used ERPs to examine auditory processing in infants with SSC to help clarify the developmental onset of delays in this population. METHODS: Fifteen infants with untreated SSC and 23 typically developing controls were evaluated. ERPs were recorded during the presentation of speech sounds. Analyses focused on the P150 and N450 components of auditory processing. RESULTS: Infants with SSC demonstrated attenuated P150 amplitudes relative to typically developing controls. No differences in the N450 component were identified between untreated SSC and controls. CONCLUSIONS: Infants with untreated SSC demonstrate abnormal speech sound processing. Atypicalities are detectable as early as 6 months of age and may represent precursors to long-term language delay. Electrophysiological assessments provide a precise examination of neural processing in SSC and hold potential as a future modality to examine the effects of surgical treatment on brain development.

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.

Interactive social neuroscience to study autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) demonstrate difficulty with social interactions and relationships, but the neural mechanisms underlying these difficulties remain largely unknown. While social difficulties in ASD are most apparent in the context of interactions with other people, most neuroscience research investigating ASD have provided limited insight into the complex dynamics of these interactions. The development of novel, innovative "interactive social neuroscience" methods to study the brain in contexts with two interacting humans is a necessary advance for ASD research. Studies applying an interactive neuroscience approach to study two brains engaging with one another have revealed significant differences in neural processes during interaction compared to observation in brain regions that are implicated in the neuropathology of ASD. Interactive social neuroscience methods are crucial in clarifying the mechanisms underlying the social and communication deficits that characterize ASD.

From Kanner to DSM-5: autism as an evolving diagnostic concept.

Seven decades have elapsed since Leo Kanner described the syndrome he termed early infantile autism. Over this time, and particularly over the past two decades, noteworthy changes have occurred in how the condition is conceptualized. Here we provide an overview of these changes, beginning with a brief discussion of the significance of classification in general before discussing Kanner's original paper and subsequent changes. We touch on relevant issues, such as comorbidity, dimensional aspects of diagnosis and screening, and the complex issue of diagnosis relative to eligibility for services. Approaches to diagnosis have tended to swing from emphasizing overarching groups (lumping) to focusing on potentially distinct subgroups (splitting). Autism raises particular problems given the broad range of syndrome expression over age and developmental level. The most recent revision of the American Psychiatric Association's diagnostic taxonomy marks a significant departure from its predecessor and has been the focus of much debate. It remains unclear which of the currently existing categorical approaches will ultimately be most widely applied. We hope to convey a sense of areas in which consensus has been achieved and areas of continued controversy.