Stratifying the autistic phenotype using electrophysiological indices of social perception

A multimodal neural signature of face processing in autism within the fusiform gyrus

Atypical face processing is commonly reported in autism. Its neural correlates have been explored extensively across single neuroimaging modalities within key regions of the face processing network, such as the fusiform gyrus (FFG). Nonetheless, it is poorly understood how variation in brain anatomy and function jointly impacts face processing and social functioning. Here we leveraged a large multimodal sample to study the cross-modal signature of face processing within the FFG across four imaging modalities (structural magnetic resonance imaging (MRI), resting-state functional magnetic resonance imaging, task-functional magnetic resonance imaging and electroencephalography) in 204 autistic and nonautistic individuals aged 7-30 years (case-control design). We combined two methodological innovations-normative modeling and linked independent component analysis-to integrate individual-level deviations across modalities and assessed how multimodal components differentiated groups and informed social functioning in autism. Groups differed significantly in a multimodal component driven by bilateral resting-state functional MRI, bilateral structure, right task-functional MRI and left electroencephalography loadings in face-selective and retinotopic FFG. Multimodal components outperformed unimodal ones in differentiating groups. In autistic individuals, multimodal components were associated with cognitive and clinical features linked to social, but not nonsocial, functioning. These findings underscore the importance of elucidating multimodal neural associations of social functioning in autism, offering potential for the identification of mechanistic and prognostic biomarkers.

Differential late-stage face processing in autism: a magnetoencephalographic study of fusiform gyrus activation

BACKGROUND

Autism is associated with alterations of social communication, such as during face-to-face interactions. This study aimed to probe face processing in autistics with normal IQ utilizing magnetoencephalography to examine event-related fields within the fusiform gyrus during face perception.

METHODS

A case-control cohort of 22 individuals diagnosed with autism and 20 age-matched controls (all male, age 29.3 ± 6.9 years) underwent magnetoencephalographic scanning during an active task while observing neutral faces, face-like pareidolic objects, and non-face objects. The fusiform face area was identified using a face localizer for each participant, and the cortical activation pattern was normalized onto an average brain for subsequent analysis.

RESULTS

Early post-stimulus activation amplitudes (before 100-200 ms) indicated differentiation between stimuli containing fundamental facial features and non-face objects in both groups. In contrast, later activation (400-550 ms) differentiated real faces from both pareidolic and non-face objects across both groups and faces from objects in controls but not in autistics. There was no effect of autistic-like traits.

CONCLUSIONS

The absence of group differences in early activation suggest intact face detection in autistics possessing a normal IQ. Later activation captures a greater degree of the complexity and social information from actual faces. Although both groups distinguished faces from pareidolic and non-face objects, the control group exhibited a slightly heightened differentiation at this latency, indicating a potential disadvantage for autistics in real face processing. The subtle difference in late-stage face processing observed in autistic individuals may reflect specific cognitive mechanisms related to face perception in autism.

A Genetic Bridge Between Medicine and Neurodiversity for Autism

Autism represents a large spectrum of diverse individuals with varying underlying genetic architectures and needs. For some individuals, a single de novo or ultrarare genetic variant has a large effect on the intensity of specific dimensions of the phenotype, while, for others, a combination of thousands of variants commonly found in the general population are involved. The variants with large impact are found in up to 30% of autistic individuals presenting with intellectual disability, significant speech delay, motor delay, and/or seizures. The common variants are shared with those found in individuals with attention-deficit/hyperactivity disorder, major depressive disorders, greater educational attainment, and higher cognitive performance, suggesting overlapping genetic architectures. The genetic variants modulate the function of chromatin remodeling and synaptic proteins that influence the connectivity of neuronal circuits and, in interaction with the environment of each individual, the subsequent cognitive and personal trajectory of the child. Overall, this genetic heterogeneity mirrors the phenotypic diversity of autistic individuals and provides a helpful bridge between biomedical and neurodiversity perspectives. We propose that participative and multidisciplinary research should use this information to understand better the assessment, treatments, and accommodations that individuals with autism and families need.

Sex differences in social brain neural responses in autism: temporal profiles of configural face-processing within data-driven time windows

Face-processing timing differences may underlie visual social attention differences between autistic and non-autistic people, and males and females. This study investigates the timing of the effects of neurotype and sex on face-processing, and their dependence on age. We analysed EEG data during upright and inverted photographs of faces from 492 participants from the Longitudinal European Autism Project (141 neurotypical males, 76 neurotypical females, 202 autistic males, 73 autistic females; age 6-30 years). We detected timings of sex/diagnosis effects on event-related potential amplitudes at the posterior-temporal channel P8 with Bootstrapped Cluster-based Permutation Analysis and conducted Growth Curve Analysis (GCA) to investigate the timecourse and dependence on age of neural signals. The periods of influence of neurotype and sex overlapped but differed in onset (respectively, 260 and 310 ms post-stimulus), with sex effects lasting longer. GCA revealed a smaller and later amplitude peak in autistic female children compared to non-autistic female children; this difference decreased in adolescence and was not significant in adulthood. No age-dependent neurotype difference was significant in males. These findings indicate that sex and neurotype influence longer latency face processing and implicates cognitive rather than perceptual processing. Sex may have more overarching effects than neurotype on configural face processing.

Discovering the gene-brain-behavior link in autism via generative machine learning

Autism is traditionally diagnosed behaviorally but has a strong genetic basis. A genetics-first approach could transform understanding and treatment of autism. However, isolating the gene-brain-behavior relationship from confounding sources of variability is a challenge. We demonstrate a novel technique, 3D transport-based morphometry (TBM), to extract the structural brain changes linked to genetic copy number variation (CNV) at the 16p11.2 region. We identified two distinct endophenotypes. In data from the Simons Variation in Individuals Project, detection of these endophenotypes enabled 89 to 95% test accuracy in predicting 16p11.2 CNV from brain images alone. Then, TBM enabled direct visualization of the endophenotypes driving accurate prediction, revealing dose-dependent brain changes among deletion and duplication carriers. These endophenotypes are sensitive to articulation disorders and explain a portion of the intelligence quotient variability. Genetic stratification combined with TBM could reveal new brain endophenotypes in many neurodevelopmental disorders, accelerating precision medicine, and understanding of human neurodiversity.

The 'PSILAUT' protocol: an experimental medicine study of autistic differences in the function of brain serotonin targets of psilocybin

BACKGROUND

The underlying neurobiology of the complex autism phenotype remains obscure, although accumulating evidence implicates the serotonin system and especially the 5HT2A receptor. However, previous research has largely relied upon association or correlation studies to link differences in serotonin targets to autism. To directly establish that serotonergic signalling is involved in a candidate brain function our approach is to change it and observe a shift in that function. We will use psilocybin as a pharmacological probe of the serotonin system in vivo. We will directly test the hypothesis that serotonergic targets of psilocybin - principally, but not exclusively, 5HT2A receptor pathways-function differently in autistic and non-autistic adults.

METHODS

The 'PSILAUT' "shiftability" study is a case-control study autistic and non-autistic adults. How neural responses 'shift' in response to low doses (2 mg and 5 mg) of psilocybin compared to placebo will be examined using multimodal techniques including functional MRI and EEG. Each participant will attend on up to three separate visits with drug or placebo administration in a double-blind and randomized order.

RESULTS

This study will provide the first direct evidence that the serotonin targets of psilocybin function differently in the autistic and non-autistic brain. We will also examine individual differences in serotonin system function.

CONCLUSIONS

This work will inform our understanding of the neurobiology of autism as well as decisions about future clinical trials of psilocybin and/or related compounds including stratification approaches.

TRIAL REGISTRATION

NCT05651126.

Neural correlates of face processing among preschoolers with fragile X syndrome, autism spectrum disorder, autism siblings, and typical development

The current study examined patterns of event-related potential (ERP) responses during a face processing task in groups of preschoolers uniquely impacted by autism spectrum disorder (ASD), including (1) children with ASD; (2) children with fragile X syndrome (FXS); (3) children with familial risk for ASD, but without a diagnosis (i.e., ASIBs); and (4) a low-risk control (LRC) group. Children with FXS have a high incidence of ASD diagnoses, but there have been no studies of the ERP response to faces in children with FXS and little work focused on children with ASD who have cognitive impairment. The current study examined children's ERP responses to faces and houses in four groups: LRC (N = 28, age = 5.2 years), ASIB (N = 23, age = 5.5 years), FXS (N = 19, age = 5.82 years), and ASD (N = 23, age = 5.5 years). The FXS and ASD groups were characterized by the presence of cognitive impairment. Pictures of upright and inverted faces and houses were presented while recording EEG with a 128-channel system. The N170 occurred at about 200 ms post stimulus onset, was largest on the posterior-lateral electrodes, and was larger for faces than houses. The P1 and N170 ERP components were larger for the FXS group than for the other three groups. The N170 ERP amplitude for the ASD and ASIB groups was smaller than both the LRC and FXS groups, and the LRC and FXS groups had the largest N170 responses on the right side. No difference was found in N170 latency between groups. The similarity of the ASD and ASIB responses suggest a common genetic or environmental origin of the reduced response. Although children with FXS have a high incidence of ASD outcomes, they differed from ASD and ASIB children in this study. Specifically, the children with FXS were hyperresponsive to all stimulus types while the ASD and ASIB groups showed attenuated responses for specific stimuli.

EEG Biomarkers for Autism: Rational, Support, and the Qualification Process

In this chapter, we highlight the advantages, progress, and pending challenges of developing electroencephalography (EEG) and event-related potential (ERP) biomarkers for use in autism spectrum disorder (ASD). We describe reasons why global efforts towards precision treatment in ASD are utilizing EEG indices to quantify biological mechanisms. We overview common sensory processing and attention biomarkers and provide translational examples examining the genetic etiology of autism across animal models and human subgroups. We describe human-specific social biomarkers related to face perception, a complex social cognitive process that may prove informative of autistic social behaviors. Lastly, we discuss outstanding considerations for quantifying EEG biomarkers, the challenges associated with rigor and reproducibility, contexts of future use, and propose opportunities for combinatory multidimensional biomarkers.

A neurophysiological signature of dynamic emotion recognition associated with social communication skills and cortical gamma-aminobutyric acid levels in children

Introduction

Emotion recognition is a core feature of social perception. In particular, perception of dynamic facial emotional expressions is a major feature of the third visual pathway. However, the classical N170 visual evoked signal does not provide a pure correlate of such processing. Indeed, independent component analysis has demonstrated that the N170 component is already active at the time of the P100, and is therefore distorted by early components. Here we implemented, a dynamic face emotional paradigm to isolate a more pure face expression selective N170. We searched for a neural correlate of perception of dynamic facial emotional expressions, by starting with a face baseline from which a facial expression evolved. This allowed for a specific facial expression contrast signal which we aimed to relate with social communication abilities and cortical gamma-aminobutyric acid (GABA) levels.

Methods

We recorded event-related potentials (ERPs) and Magnetic Resonance (MRS) measures in 35 typically developing (TD) children, (10-16 years) sex-matched, during emotion recognition of an avatar morphing/unmorphing from neutral to happy/sad expressions. This task allowed for the elimination of the contribution low-level visual components, in particular the P100, by morphing baseline isoluminant neutral faces into specific expressions, isolating dynamic emotion recognition. Therefore, it was possible to isolate a dynamic face sensitive N170 devoid of interactions with earlier components.

Results

We found delayed N170 and P300, with a hysteresis type of dependence on stimulus trajectory (morphing/unmorphing), with hemispheric lateralization. The delayed N170 is generated by an extrastriate source, which can be related to the third visual pathway specialized in biological motion processing. GABA levels in visual cortex were related with N170 amplitude and latency and predictive of worse social communication performance (SCQ scores). N170 latencies reflected delayed processing speed of emotional expressions and related to worse social communication scores.

Discussion

In sum, we found a specific N170 electrophysiological signature of dynamic face processing related to social communication abilities and cortical GABA levels. These findings have potential clinical significance supporting the hypothesis of a spectrum of social communication abilities and the identification of a specific face-expression sensitive N170 which can potentially be used in the development of diagnostic and intervention tools.

Does the current state of biomarker discovery in autism reflect the limits of reductionism in precision medicine? Suggestions for an integrative approach that considers dynamic mechanisms between brain, body, and the social environment

Over the past decade, precision medicine has become one of the most influential approaches in biomedical research to improve early detection, diagnosis, and prognosis of clinical conditions and develop mechanism-based therapies tailored to individual characteristics using biomarkers. This perspective article first reviews the origins and concept of precision medicine approaches to autism and summarises recent findings from the first "generation" of biomarker studies. Multi-disciplinary research initiatives created substantially larger, comprehensively characterised cohorts, shifted the focus from group-comparisons to individual variability and subgroups, increased methodological rigour and advanced analytic innovations. However, although several candidate markers with probabilistic value have been identified, separate efforts to divide autism by molecular, brain structural/functional or cognitive markers have not identified a validated diagnostic subgroup. Conversely, studies of specific monogenic subgroups revealed substantial variability in biology and behaviour. The second part discusses both conceptual and methodological factors in these findings. It is argued that the predominant reductionist approach, which seeks to parse complex issues into simpler, more tractable units, let us to neglect the interactions between brain and body, and divorce individuals from their social environment. The third part draws on insights from systems biology, developmental psychology and neurodiversity approaches to outline an integrative approach that considers the dynamic interaction between biological (brain, body) and social mechanisms (stress, stigma) to understanding the origins of autistic features in particular conditions and contexts. This requires 1) closer collaboration with autistic people to increase face validity of concepts and methodologies; (2) development of measures/technologies that enable repeat assessment of social and biological factors in different (naturalistic) conditions and contexts, (3) new analytic methods to study (simulate) these interactions (including emergent properties), and (4) cross-condition designs to understand which mechanisms are transdiagnostic or specific for particular autistic sub-populations. Tailored support may entail both creating more favourable conditions in the social environment and interventions for some autistic people to increase well-being.