Autistic Traits Research Articles

Uh and um in autism: The case of hesitation marker usage in Dutch-speaking autistic preschoolers.

English-speaking autistic children use the hesitation marker um less often than non-autistic children but use uh at a similar rate. It is unclear why this is the case. We employed a sample of Dutch-speaking children from the Preschool Brain Imaging and Behavior Project to examine hesitation markers in autistic and non-autistic preschoolers with the aim to 1) make a crosslinguistic comparison of hesitation marker usage and 2) examine hypotheses regarding the underlying linguistic mechanisms of hesitation markers: the symptom hypothesis and the signal hypothesis. We found initial group differences in all hesitation markers but these results were rendered insignificant after controlling for age, sex and nonverbal cognition. We found significant correlations between hesitation marker usage and expressive and receptive language, but not autism traits. Lastly, we show interesting cross-linguistic differences in hesitation marker usage between Dutch-speaking participants and previously described English-speaking participants, such as a preference for um over uh.

Individuals with high autism traits show top-down attention bias towards threatening stimuli

Individuals with autistic traits (AT) are widely distributed in the general population. Strengthening understanding of AT can provide a broader perspective for autism research as well as more accurate diagnosis and personalized treatment plans for clinical practice. Previous studies on attention bias among high-AT individuals have yielded inconsistent results, which may relate to different stages of attention. In this study, we selected two groups with high and low level AT from the general population, and then adopted the odd-one-out search task, combined with Event-related potential (ERP) technique, conducted both attention orientation and attention dissociation tasks, to explore attention bias and electroencephalogram (EEG) characteristics towards threatening emotional faces in these groups. The behavioral data showed no accelerated attention orientation to angry faces and neutral faces; however, there was attention dissociation difficulty for angry faces. Compared with low-AT individuals, the EEG results showed that high-AT individuals have acceleration of attention orientation and attention dissociation difficulty for threatening emotional faces. From the perspective of top-down concept-driven processing, these findings suggest that high-AT individuals have attention bias for cognitive processing of threatening stimuli, which is mainly due to acceleration of attention orientation and attention dissociation difficulties for threatening information.

Factors of Bullying Victimization Among Students on the Autism Spectrum: A Systematic Review

AbstractStudies have increasingly suggested that autistic students face a heightened risk of bullying. Understanding the underlying factors for high rates of bullying victimization among autistic students is crucial for intervention, but the complexity of bullying and the heterogeneity of ASD (autism spectrum disorder) traits have made it challenging to explain these factors. Hence, this study systematically reviewed and summarized findings in this area, providing recommendations for intervention. It synthesized 34 studies investigating the predictive variable of bullying victimization among autistic students. Our review observed the role of schools, parents, and peers and of individual variables with respect to autistic traits and behavioral difficulties. We then proposed prevention and intervention strategies against bullying victimization toward autistic students.

Association between autistic traits and sleep quality among Chinese junior high school students: The chain mediating roles of self‐control and mindfulness

Association between autistic traits and sleep quality among Chinese junior high school students: The chain mediating roles of self‐control and mindfulness

Sleep disturbance and other co-occurring conditions in autistic children: A network approach to understanding their inter-relationships.

Autistic children frequently have one or more co-occurring psychological, behavioral, or medical conditions. We examined relationships between child behaviors, sleep, adaptive behavior, autistic traits, mental health conditions, and health in autistic children using network analysis. Network analysis is hypothesis generating and can inform our understanding of relationships between multiple conditions and behaviors, directing the development of transdiagnostic treatments for co-occurring conditions. Participants were two child cohorts from the Autism Treatment Network registry: ages 2-5 years (n = 2372) and 6-17 years (n = 1553). Least absolute-shrinkage and selection operator (LASSO) regularized partial correlation network analysis was performed in the 2-5 years cohort (35 items) and the 6-17 years cohort (36 items). The Spinglass algorithm determined communities within each network. Two-step expected influence (EI2) determined the importance of network variables. The most influential network items were sleep difficulties (2 items) and aggressive behaviors for young children and aggressive behaviors, social problems, and anxious/depressed behavior for older children. Five communities were found for younger children and seven for older children. Of the top three most important bridge variables, night-waking/parasomnias and anxious/depressed behavior were in both age-groups, and somatic complaints and sleep initiation/duration were in younger and older cohorts respectively. Despite cohort differences, sleep disturbances were prominent in all networks, indicating they are a transdiagnostic feature across many clinical conditions, and thus a target for intervention and monitoring. Aggressive behavior was influential in the partial correlation networks, indicating a potential red flag for clinical monitoring. Other items of strong network importance may also be intervention targets or screening flags.

Autistic trans camouflaging: an early phenomenological exploration

ABSTRACT Autistic people often camouflage, i.e. they adopt certain behaviors in order to fit in in neurotypical environments. Autobiographical accounts suggest that autistic trans people experience camouflaging in a unique, more complex and often heightened way than cis autistic people, and this has not been studied. They have autistic traits to mask, as well as gendered traits, in a hostile neuronormative and cisnormative world. This intersection of experience is worthy of exploration, not least because this group of people are typically misunderstood and silenced, as well as being particularly at risk of the mental distress that can come from camouflaging. In this paper I discuss autistic trans people’s accounts of camouflaging and begin a preliminary phenomenological analysis. I draw primarily from Simone de Beauvoir’s concept of “doubling”, whereby (cis) women experience being both oneself and the image of oneself, under patriarchal objectification. One can argue that autistic people are similarly “doubled” when camouflaging, experiencing their neurodivergent selves as well as their more neurotypical presentation. Going beyond de Beauvoir, it can be further argued that many trans people experience “tripling” and therefore that trans autistic people experience being at least “quadrupled” if not “quintupled”.

High autistic traits linked with reduced performance on affective task switching: An ERP study

Few studies have investigated affective flexibility in individuals with high autistic traits. In the present study, we employed affective task-switching paradigm combined with event related potential (ERP) technology to explore affective flexibility in individuals with high autistic traits. Participants were instructed to switch between identifying the gender (gender task) and emotion (emotion task) of presented faces. Two groups of participants were recruited based on the Autism Spectrum Quotient (AQ) scores: a High Autistic Group (HAG) and a Low Autistic Group (LAG). The results confirmed that the HAG exhibited greater behavioral emotion switch costs and increased N2 and decreased P3 components when switching to the emotion task. Additionally, we identified an affective asymmetric switch cost in the HAG, where the switch cost for the emotion task was larger than for the gender task at both behavioral and electrophysiological levels. In contrast, a symmetrical switch cost was observed in the LAG. These findings indicate that the HAG experiences difficulties with affective flexibility, particularly in tasks involving emotional processing. The patterns of affective asymmetric switch costs observed in both groups differed from previous results in autistic children and the general population, suggesting that the relative dominance of gender and emotion tasks may vary between the two groups. We propose that the dominance of emotion tasks declines as autistic traits increase.

Differential item functioning in the autism behavior checklist in children with autism spectrum disorder based on a machine learning approach.

Our study utilized the Rasch analysis to examine the psychometric properties of the Autism Behavior Checklist (ABC) in children with autism spectrum disorder (ASD). A total of 3,319 children (44.77 ± 23.52 months) were included. The Rasch model (RM) was utilized to test the reliability and validity of the ABC. The GPCMlasso model was used to test the differential item functioning (DIF). The response pattern of this sample showed acceptable fitness to the RM. The analysis supported the unidimensionality assumption of the ABC. Disordered category functions and DIF were found in all items in the ABC. The participants responded to the ABC items differently depending not only on autistic traits but also on age groups, gender, and symptom classifications. The Rasch analysis produces reliable evidence to support that the ABC can precisely depict clinical ASD symptoms. Differences in population characteristics may cause unnecessary assessment bias and lead to overestimated or underestimated symptom severity. Hence, special consideration for population characteristics is needed in making an ASD diagnosis.

From dynamic FMR1 mutation to variable phenotypes: A case series from a large Tunisian family

AbstractBackgroundFragile X messenger ribonucleoprotein 1 gene (FMR1) disorders result from a mutation in the FMR1 gene, leading to a deficiency or absence of the FMRP. Full mutations and premutations of the FMR1 gene are known to cause completely different symptoms.AimTo determine the clinical phenotype of individuals with a full mutation or premutation of the FMR1 gene.MethodsWe report 6 patients of the same Tunisian family with different clinical phenotypes. We gathered recent findings on the clinical spectrum of FMR1 mutations from 2020 to 2024 using PubMed, Google Scholar, ScienceDirect, and Web of Science.ResultsOur observations revealed two first cousins, aged 4 and 13 years, respectively, with a medical history of recurrent infections. They exhibited developmental delay, hyperactivity, concentration difficulties, and autistic traits, with characteristic facial dysmorphia. Family investigation revealed a history of early menopause and primary ovary insufficiency diagnosis in their mothers and one aunt. The 79‐year‐old grandfather presented with recent memory and sleep disturbances, with signs suggestive of fragile X‐associated tremor/ataxia syndrome (FXTAS) on brain MRI. The genetic assessment confirmed the fragile X syndrome (FXS) in children and the fragile X‐associated primary ovarian insufficiency (FXPOI) in their mothers. Our search in literature uncovered a genetically diverse disorder exhibiting clinical variability influenced by factors such as gene size, methylation mosaicism, and the presence of premutations or full mutations, alongside various pathophysiological mechanisms.ConclusionClinical signs highlighted in our family report should alert clinicians to consider FXS, particularly facial dysmorphia and intellectual disability or language developmental delay, FXPOI for early menopause, and FXTAS for tremor and ataxia within the family context of FXS.

Association between Reported Sleep Disorders and Behavioral Issues in Children with Myotonic Dystrophy Type 1-Results from a Retrospective Analysis in Italy.

Background: Sleep disorders have been poorly described in congenital (CDM) and childhood (ChDM) myotonic dystrophy despite being highly burdensome. The aims of this study were to explore sleep disorders in a cohort of Italian CDM and ChDM and to assess their association with motor and respiratory function and disease-specific cognitive and behavioral assessments. Methods: This was an observational multicenter study. Reported sleep quality was assessed using the Pediatric Daytime Sleepiness Scale (PDSS) and Pediatric Sleep Questionnaire (PSQ). Sleep quality was correlated to motor function (6 min walk test, 6MWT and grip strength; pulmonary function (predicted Forced Vital Capacity%, FVC% pred.); executive function assessed by BRIEF-2; autism traits assessed by Autism Spectrum Screening Questionnaire (ASSQ) and Repetitive Behavior Scale-revised (RBS-R); Quality of life (PedsQL) and disease burden (Congenital Childhood Myotonic Dystrophy Health Index, CCMDHI). Results: Forty-six patients were included, 33 CDM and 13 ChDM, at a median age of 10.4 and 15.1 years. Daytime sleepiness and disrupted sleep were reported by 30% children, in both subgroups of CDM and ChDM. Daytime sleepiness correlated with autism traits in CDM (p < 0.05). Disrupted sleep correlated with poorer executive function (p = 0.04) and higher disease burden (p = 0.03). Conclusions: Sleep issues are a feature of both CDM and ChDM. They correlate with behavioral issues and impact on disease burden.

B - 22 Self-Reported Traumatic Brain Injury and its Biopsychosocial Risk Factors in Siblings of Individuals with Neurodevelopmental Conditions

Abstract Objective Siblings of individuals with neurodevelopmental conditions (NDCs) are situated within a complex system of transdiagnostic risk and resilience factors for poor psychosocial, cognitive and behavioral outcomes. Many such factors experienced by NDC siblings overlap with risk for traumatic brain injury (TBI) and correlate with poorer recovery trajectories. Method With data from an online self-report survey, the present study used Bayesian analyses to characterize and compare TBI and biopsychosocial risk factors amongst 632 siblings (207 NDC, 425 controls; mean age 20.54 years, range 10–30, 78.48% female), and examine correlations between clinical, biological, and social determinant of health variables. Results NDC siblings had a higher self-reported lifetime history of TBI compared to controls (14.98% versus 6.35%), with most NDC siblings reporting more than one TBI, and at an earlier mean age. TBI history was associated with psychiatric diagnoses and subclinical NDC features, including hyperactivity and impulsivity, inattention, conduct problems, and autistic traits. Family and structural factors related to TBI included poorer parent–child relationship, NDC diagnoses of autism or fetal alcohol spectrum disorder, minority ethnicity and lower income. Conclusions Findings have important clinical and policy implications for health literacy, TBI education and screening, development of prevention and intervention strategies, and implementation of family support to target social and structural determinants of health impacting NDC sibling wellbeing.

Atypical dynamic trust learning in individuals with high autistic traits in a multi-round trust game with multiple trustworthiness cues

BackgroundUnderstanding the trust-building process, especially in contexts requiring the integration of multiple trustworthiness cues, is a fundamental aspect of social interactions among individuals with high autistic traits (ATs). It can offer valuable insights into the social functioning of these individuals. MethodParticipants with high and low ATs (N = 120; 30 in each group for two experiments) completed a 10-round trust game that embedded various trustworthiness cues, including reputation, advice (Experiment 1 = direct advice; Experiment 2 = social-emotional advice), and reciprocity. Linear mixed-effects models with investment rates as the dependent variable were used to analyze the data. ResultsMethodologically, the experimental results elucidated the fundamental characteristics of dynamic trust formation within the context of multidimensional trust information. Furthermore, High-AT individuals showed assigned less weight to reciprocity but relied heavily on reputation, and exhibited maladaptive advice-taking. Unlike low-AT individuals, high-AT individuals did not adaptively reduce reputational effect over rounds. ConclusionsOur findings highlight the unique challenges faced by individuals with high ATs when navigating complex social interactions.

Parent-child interaction at age 5 months: genetic and environmental contributions and associations with later socio-communicative development.

Characteristics of parent-child interaction (PCI) early in life have been associated with later development in the child. Twin studies can help to disentangle child contributions to parent-child interaction, for example, by assessing the influence of the child's genetics on his/her social environment, which includes parental behaviour. Infant twins from a community sample [354 monozygotic (MZ), 268 same-sex dizygotic (DZ)] were assessed in terms of PCI at age 5 months. We used the classical twin design to map the aetiology of several parent and child PCI scales and their covariation. We investigated the relations between PCI and later parent-rated child's social communication, language, and autistic traits at ages 2 and 3. Heritability was below 20% for all the included PCI traits. Unique (nonshared) environmental influences substantially overlapped across several PCI scales, suggesting that idiosyncrasies linked to each session shaped the scoring of several traits in a systematic way. Factor analysis revealed three uncorrelated latent factors, which were conceptualized as 'child negative affect', 'positive affective interaction', and 'parent's supportive strategies'. Parents who were rated highly on 'sensitive responsiveness' at 5 months tended to rate their offspring higher in terms of socio-communicative and language development and lower in terms of autistic traits in the second and third years of life. This study maps the phenotypic and aetiological structure of PCI in early infancy and supports the view that parents' sensitive responsiveness towards their infant is associated with later developmental gains in several domains. We did not find strong evidence of any so-called evocative genetic effects on parents' behaviour. We discuss the results considering the general challenge for lab-based observational PCI measures to capture the richness of parent-child interaction.

Conspiracy mentality in autistic and non-autistic individuals

ABSTRACT Background Belief in conspiracy theories has emerged across times and cultures. While previous accounts attributed conspiracy beliefs to mental health conditions, accumulating research suggests that conspiracy theories are common among the general population. In the present study we examined whether conspiracy mentality – that is, a general predisposition to believe conspiracy theories – differed between a group of autistic adults and a general population sample. Methods This study included an autistic sample (n = 682) and a general population sample (n = 4358). Participants’ conspiracy mentality was measured using the Conspiracy Mentality Questionnaire (CMQ). Results A one-way ANCOVA (controlling for participants’ age, gender, educational level, and ethnicity) revealed no difference in conspiracy mentality between an autism and a community sample. Conclusions The current study suggests that being autistic, or having more autistic traits, does not predict conspiracy mentality. These findings underscore that autism does not predispose people to conspiracy theories and suggest that autism is neither a risk factor for, nor a protective factor against, conspiracy mentality.

Person-environment fit and social camouflaging in autism

Social camouflaging is a set of behaviours used by autistic people to conceal social differences. This paper provides an analysis of social camouflaging within the developmental context of autistic persons. We suggest that autistic people achieve person-environment fit with their social environment by using social camouflaging as an inauthentic form of trait expression whereby autistic traits are masked and neurotypical traits are displayed. The resulting consequences for autistic individuals may be interpersonally beneficial, but conversely intrapersonally detrimental, when considering existing theories or models of person-environment fit throughout development. The current paper explores this dichotomy and suggests implications for future social camouflaging research in autism, such as considering a broader developmental context through which to study the consequences of camouflaging. Clinical implications include an increased focus on reciprocity between autistic individuals and their social environment.

Urine metabolomic profiles of autism and autistic traits-A twin study.

Currently, there are no reliable biomarkers for autism diagnosis. The heterogeneity of autism and several co-occurring conditions are key challenges to establishing these. Here, we used untargeted mass spectrometry-based urine metabolomics to investigate metabolic differences for autism diagnosis and autistic traits in a well-characterized twin cohort (N = 105). We identified 208 metabolites in the urine samples of the twins. No clear, significant metabolic drivers for autism diagnosis were detected when controlling for other neurodevelopmental conditions. However, we identified nominally significant changes for several metabolites. For instance, phenylpyruvate (p = 0.019) and taurine (p = 0.032) were elevated in the autism group, while carnitine (p = 0.047) was reduced. We furthermore accounted for the shared factors, such as genetics within the twin pairs, and report additional metabolite differences. Based on the nominally significant metabolites for autism diagnosis, the arginine and proline metabolism pathway (p = 0.024) was enriched. We also investigated the association between quantitative autistic traits, as measured by the Social Responsiveness Scale 2nd Edition, and metabolite differences, identifying a greater number of nominally significant metabolites and pathways. A significant positive association between indole-3-acetate and autistic traits was observed within the twin pairs (adjusted p = 0.031). The utility of urine biomarkers in autism, therefore, remains unclear, with mixed findings from different study populations.

Enhanced motor noise in an autism subtype with poor motor skills

BackgroundMotor difficulties are common in many, but not all, autistic individuals. These difficulties can co-occur with other problems, such as delays in language, intellectual, and adaptive functioning. Biological mechanisms underpinning such difficulties are less well understood. Poor motor skills tend to be more common in individuals carrying highly penetrant rare genetic mutations. Such mechanisms may have downstream consequences of altering neurophysiological excitation-inhibition balance and lead to enhanced behavioral motor noise.MethodsThis study combined publicly available and in-house datasets of autistic (n = 156), typically-developing (TD, n = 149), and developmental coordination disorder (DCD, n = 23) children (age 3–16 years). Autism motor subtypes were identified based on patterns of motor abilities measured from the Movement Assessment Battery for Children 2nd edition. Stability-based relative clustering validation was used to identify autism motor subtypes and evaluate generalization accuracy in held-out data. Autism motor subtypes were tested for differences in motor noise, operationalized as the degree of dissimilarity between repeated motor kinematic trajectories recorded during a simple reach-to-drop task.ResultsRelatively ‘high’ (n = 87) versus ‘low’ (n = 69) autism motor subtypes could be detected and which generalize with 89% accuracy in held-out data. The relatively ‘low’ subtype was lower in general intellectual ability and older at age of independent walking, but did not differ in age at first words or autistic traits or symptomatology. Motor noise was considerably higher in the ‘low’ subtype compared to ‘high’ (Cohen’s d = 0.77) or TD children (Cohen’s d = 0.85), but similar between autism ‘high’ and TD children (Cohen’s d = 0.08). Enhanced motor noise in the ‘low’ subtype was also most pronounced during the feedforward phase of reaching actions.LimitationsThe sample size of this work is limited. Future work in larger samples along with independent replication is important. Motor noise was measured only on one specific motor task. Thus, a more comprehensive assessment of motor noise on many other motor tasks is needed.ConclusionsAutism can be split into at least two discrete motor subtypes that are characterized by differing levels of motor noise. This suggests that autism motor subtypes may be underpinned by different biological mechanisms.

HCBiLSTM-WOA: hybrid convolutional bidirectional long short-term memory with water optimization algorithm for autism spectrum disorder

Autism Spectrum Disorder (ASD) is a type of brain developmental disability that cannot be completely treated, but its impact can be reduced through early interventions. Early identification of neurological disorders will better assist in preserving the subjects’ physical and mental health. Although numerous research works exist for detecting autism spectrum disorder, they are cumbersome and insufficient for dealing with real-time datasets. Therefore, to address these issues, this paper proposes an ASD detection mechanism using a novel Hybrid Convolutional Bidirectional Long Short-Term Memory based Water Optimization Algorithm (HCBiLSTM-WOA). The prediction efficiency of the proposed HCBiLSTM-WOA method is investigated using real-time ASD datasets containing both ASD and non-ASD data from toddlers, children, adolescents, and adults. The inconsistent and incomplete representations of the raw ASD dataset are modified using preprocessing procedures such as handling missing values, predicting outliers, data discretization, and data reduction. The preprocessed data obtained is then fed into the proposed HCBiLSTM-WOA classification model to effectively predict the non-ASD and ASD classes. The initially randomly initialized hyperparameters of the HCBiLSTM model are adjusted and tuned using the water optimization algorithm (WOA) to increase the prediction accuracy of ASD. After detecting non-ASD and ASD classes, the HCBiLSTM-WOA method further classifies the ASD cases into respective stages based on the autistic traits observed in toddlers, children, adolescents, and adults. Also, the ethical considerations that should be taken into account when campaign ASD risk communication are complex due to the data privacy and unpredictability surrounding ASD risk factors. The fusion of sophisticated deep learning techniques with an optimization algorithm presents a promising framework for ASD diagnosis. This innovative approach shows potential in effectively managing intricate ASD data, enhancing diagnostic precision, and improving result interpretation. Consequently, it offers clinicians a tool for early and precise detection, allowing for timely intervention in ASD cases. Moreover, the performance of the proposed HCBiLSTM-WOA method is evaluated using various performance indicators such as accuracy, kappa statistics, sensitivity, specificity, log loss, and Area Under the Receiver Operating Characteristics (AUROC). The simulation results reveal the superiority of the proposed HCBiLSTM-WOA method in detecting ASD compared to other existing methods. The proposed method achieves a higher ASD prediction accuracy of about 98.53% than the other methods being compared.

Autistic traits as predictors of post-traumatic stress symptoms among patients with borderline personality disorder.

Autistic traits (AT) seem to be particularly frequent among patients with borderline personality disorder (BPD). Moreover, the autism spectrum is considered a vulnerability factor for the development of post-traumatic stress disorder (PTSD) symptoms, increasing the vulnerability of BPD subjects toward the development of a stress-related disorder. The study aimed to investigate the association between AT and trauma-related symptoms in a clinical sample of patients with BPD. A total of 48 patients with a clinical diagnosis of BPD and 52 healthy control (HC) subjects were recruited and assessed with the Adult Autism Subthreshold Spectrum Self-Report (AdAS Spectrum) questionnaire and the Trauma and Loss Spectrum-Self-Report questionnaire (TALS-SR). The BPD group was divided into two subgroups: BPD with a symptomatological diagnosis of PTSD (pBPD = 25) and BPD not diagnosed with PTSD (No-pBPD = 23). The clinical sample scored significantly higher in almost all AdAS domains. Moreover, pBPD groups reported higher AdAS and TALS-SR scores in the total and in various domains than the No-pBPD group, which scored higher in several domains than HC. AdAS Restricted interests and rumination domain scores were positive predictors of BPD presence independently from PTSD, while Inflexibility and adherence to routine domain was a negative predictor. Finally, AdAS Hyper/hyporeactivity to sensory stimuli domain was a positive predictor only for inclusion in the pBPD group. Our study confirmed the existence of a statistically significant relationship between the autism spectrum and BPD, while BPD subjects diagnosed with PTSD seem to show a higher autism spectrum burden.

Individualized cortical gyrification in neonates with congenital heart disease.

Congenital heart disease is associated with impaired early brain development and adverse neurodevelopmental outcomes. This study investigated how individualized measures of preoperative cortical gyrification index differ in 142 infants with congenital heart disease, using a normative modelling approach with reference data from 320 typically developing infants. Gyrification index Z-scores for the whole brain and six major cortical areas were generated using two different normative models: one accounting for post-menstrual age at scan, post-natal age at scan and sex, and another additionally accounting for supratentorial brain volume. These Z-scores were compared between congenital heart disease and control groups to test the hypothesis that cortical folding in infants with congenital heart disease deviates from the normal developmental trajectory. The relationships between whole-brain gyrification index Z-scores from the two normative models and both cerebral oxygen delivery and neurodevelopmental outcomes were also investigated. Global and regional brain gyrification was significantly reduced in neonates with congenital heart disease, but not when supratentorial brain volume was accounted for. This finding suggests that whilst cortical folding is reduced in congenital heart disease, it is primarily driven by a reduction in brain size. There was a significant positive correlation between cerebral oxygen delivery and whole-brain gyrification index Z-scores in congenital heart disease, but not when supratentorial brain volume was accounted for. Cerebral oxygen delivery is therefore likely to play a more important role in the biological processes underlying volumetric brain growth than cortical folding. No significant associations between whole-brain gyrification index Z-scores and motor/cognitive outcomes or autism traits were identified in the 70 infants with congenital heart disease who underwent neurodevelopmental assessment at 22-months. Our results suggest that chronic in utero and early post-natal hypoxia in congenital heart disease is associated with reductions in cortical folding that are proportional to reductions in supratentorial brain volume.