Early Life Neuroimaging: The Generalizability of Cortical Area Parcellations Across Development.

The cerebral cortex comprises discrete cortical areas that form during development. Accurate area parcellation in neuroimaging studies enhances statistical power and comparability across studies. The formation of cortical areas is influenced by intrinsic embryonic patterning as well as extrinsic inputs, particularly through postnatal exposure. Given the substantial changes in brain volume, microstructure, and functional connectivity during the first years of life, we hypothesized that cortical areas in 1-to-3-year-olds would exhibit major differences from those in neonates and progressively resemble adults as development progresses. Here, we parcellated the cerebral cortex into putative areas using local functional connectivity gradients in 92 toddlers at 2 years old. We demonstrated high reproducibility of these cortical regions across 1-to-3-year-olds in two independent datasets. The area boundaries in 1-to-3-year-olds were more similar to adults than neonates. While the age-specific group parcellation fitted better to the underlying functional connectivity in individuals during the first 3 years, adult area parcellations might still have some utility in developmental studies, especially in children older than 6 years. Additionally, we provided connectivity-based community assignments of the parcels, showing fragmented anterior and posterior components based on the strongest connectivity, yet alignment with adult systems when weaker connectivity was included.

Where do neurodevelopmental conditions fit in transdiagnostic psychiatric frameworks? Incorporating a new neurodevelopmental spectrum.

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Parent attitudes towards predictive testing for autism in the first year of life.

BACKGROUND: Emerging biomarker technologies (e.g., MRI, EEG, digital phenotyping, eye-tracking) have potential to move the identification of autism into the first year of life. We investigated the perspectives of parents about the anticipated utility and impact of predicting later autism diagnosis from a biomarker-based test in infancy. METHODS: Parents of infants were interviewed to ascertain receptiveness and perspectives on early (6-12 months) prediction of autism using emerging biomarker technologies. One group had experience parenting an older autistic child (n=30), and the other had no prior autism parenting experience (n=25). Parent responses were analyzed using inductive qualitative coding methods. RESULTS: Almost all parents in both groups were interested in predictive testing for autism, with some stating they would seek testing only if concerned about their infant's development. The primary anticipated advantage of testing was to enable access to earlier intervention. Parents also described the anticipated emotions they would feel in response to test results, actions they might take upon learning their infant was likely to develop autism, attitudes towards predicting a child's future support needs, and the potential impacts of inaccurate prediction. CONCLUSION: In qualitative interviews, parents of infants with and without prior autism experience shared their anticipated motivations and concerns about predictive testing for autism in the first year of life. The primary reported motivators for testing-to have more time to prepare and intervene early-could be constrained by familial resources and service availability. Implications for ethical communication of results, equitable early intervention, and future research are discussed.

A subset of brain regions within adult functional connectivity networks demonstrate high reliability across early development.

The human cerebral cortex contains groups of areas that support sensory, motor, cognitive, and affective functions, often categorized as functional networks. These areas show stronger internal and weaker external functional connectivity (FC) and exhibit similar FC profiles within rather than between networks. Previous studies have demonstrated the development of these networks from nascent forms present before birth to their mature, adult-like topography in childhood. However, analyses often still use definitions based on adult functional networks. We aim to assess how this might lead to the misidentification of functional networks and explore potential consequences and solutions. Our findings suggest that even though adult networks provide only a marginally better than-chance description of the infant FC organization, misidentification was largely driven by specific areas. By restricting functional networks to areas showing adult-like network clustering, we observed consistent within-network FC both within and across scans and throughout development. Additionally, these areas were spatially closer to locations with low variability in network identity among adults. Our analysis aids in understanding the potential consequences of using adult networks "as is" and provides guidance for future research on selecting and utilizing functional network models based on the research question and scenario.

Multi-site EEG studies in early infancy: Methods to enhance data quality.

Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors.

The infant parasympathetic nervous system is socially embedded and dynamic at multiple timescales, within and between people.

Human interpersonal capacities emerge from coordinated neural, biological, and behavioral activity unfolding within and between people. However, developmental research to date has allocated comparatively little focus to the dynamic processes of how social interactions emerge across these levels of analysis. Second-person neuroscience and dynamic systems approach together to offer an integrative framework for addressing these questions. This study quantified respiratory sinus arrhythmia and social behavior (∼360 observations per system) from 44 mothers and typically developing 9-month-old infants during a novel modified "still-face" (text message perturbation) task. Stochastic autoregression models indicate that the infant parasympathetic nervous system is coupled within and between people second by second and is sensitive to social context. Intraindividual, we found positive coupling between infants' parasympathetic nervous system activity and their social behavior in the subsequent second, but only during the moments and periods of active caregiver engagement. Between people, we found a bidirectional coregulatory feedback loop: Mothers' parasympathetic activity positively predicted that of their infant in the subsequent second, a form of synchrony that decreased during the text message perturbation and did not fully recover. Conversely, infant parasympathetic activity negatively predicted that of their mother at the subsequent second, a form of synchrony that was invariant over social context. Findings reveal unidirectional parasympathetic coupling within infants and a complementary allostatic feedback loop between mother and infant parasympathetic systems. They offer novel evidence of a dynamic, socially embedded parasympathetic system at previously undocumented timescales, contributing to both basic science and potential clinical targets to better support adaptive, multisystem social development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Atypical functional connectivity between the amygdala and visual, salience regions in infants with genetic liability for autism.

The amygdala undergoes a period of overgrowth in the first year of life, resulting in enlarged volume by 12 months in infants later diagnosed with ASD. The overgrowth of the amygdala may have functional consequences during infancy. We investigated whether amygdala connectivity differs in 12-month-olds at high likelihood (HL) for ASD (defined by having an older sibling with autism), compared to those at low likelihood (LL). We examined seed-based connectivity of left and right amygdalae, hypothesizing that the HL and LL groups would differ in amygdala connectivity, especially with the visual cortex, based on our prior reports demonstrating that components of visual circuitry develop atypically and are linked to genetic liability for autism. We found that HL infants exhibited weaker connectivity between the right amygdala and the left visual cortex, as well as between the left amygdala and the right anterior cingulate, with evidence that these patterns occur in distinct subgroups of the HL sample. Amygdala connectivity strength with the visual cortex was related to motor and communication abilities among HL infants. Findings indicate that aberrant functional connectivity between the amygdala and visual regions is apparent in infants with genetic liability for ASD and may have implications for early differences in adaptive behaviors.

Neurobehavioral outcomes of neonatal asymptomatic congenital cytomegalovirus infection at 12-months.

BACKGROUND: Congenital cytomegalovirus (cCMV) is the most common congenital viral infection in the United States. Symptomatic infections can cause severe hearing loss and neurological disability, although ~ 90% of cCMV infections are asymptomatic at birth. Despite its prevalence, the long-term neurobehavioral risks of asymptomatic cCMV infections are not fully understood. The objective of this work was to evaluate for potential long-term neurobehavioral sequelae in infants with asymptomatic cCMV. METHODS: Infants with cCMV were identified from a universal newborn cCMV screening study in a metropolitan area in the midwestern United States. Asymptomatic infants with cCMV were enrolled in a longitudinal neurodevelopmental study (N = 29). Age- and sex-matched healthy control infants (N = 193) were identified from the Baby Connectome Project (BCP), a longitudinal study of brain and behavioral development. The BCP sample supplemented an additional group of healthy control infants (N = 30), recruited from the same participant registry as the BCP specifically for comparison with infants with asymptomatic cCMV. Neurobehavioral assessments and parent questionnaires, including the Mullen Scales of Early Learning, the Repetitive Behavior Scales for Early Childhood (RBS-EC), and the Infant Toddler Social Emotional Assessment (ITSEA) were administered at 12 months of age. Neurobehavioral scores were compared between infants with asymptomatic cCMV and all identified healthy control infants. RESULTS: Infants with asymptomatic cCMV performed equivalently compared to healthy control infants on the neurobehavioral measures tested at 12 months of age. CONCLUSIONS: These results indicate that at 12 months of age, infants with asymptomatic cCMV are not statistically different from controls in a number of neurobehavioral domains. Although follow-up is ongoing, these observations provide reassurance about neurobehavioral outcomes for infants with asymptomatic cCMV and inform the ongoing discussion around universal screening. Additional follow-up will be necessary to understand the longer-term outcomes of these children.

Neural Correlates of Novelty-Evoked Distress in 4-Month-Old Infants: A Synthetic Cohort Study.

BACKGROUND: Observational assessments of infant temperament have provided unparalleled insight into prediction of risk for social anxiety. However, it is challenging to administer and score these assessments alongside high-quality infant neuroimaging data. In the current study, we aimed to identify infant resting-state functional connectivity associated with both parent report and observed behavioral estimates of infant novelty-evoked distress. METHODS: Using data from the OIT (Origins of Infant Temperament) study, which includes deep phenotyping of infant temperament, we identified parent-report measures that were associated with observed novelty-evoked distress. These parent-report measures were then summarized into a composite score used for imaging analysis. Our infant magnetic resonance imaging sample was a synthetic cohort, harmonizing data from 2 functional magnetic resonance imaging studies of 4-month-old infants (OIT and BCP [Baby Connectome Project]; n = 101), both of which included measures of parent-reported temperament. Brain-behavior associations were evaluated using enrichment, a statistical approach that quantifies the clustering of brain-behavior associations within network pairs. RESULTS: Results demonstrated that parent-report composites of novelty-evoked distress were significantly associated with 3 network pairs: dorsal attention-salience/ventral attention, dorsal attention-default mode, and dorsal attention-control. These network pairs demonstrated negative associations with novelty-evoked distress, indicating that less connectivity between these network pairs was associated with greater novelty-evoked distress. Additional analyses demonstrated that dorsal attention-control network connectivity was associated with observed novelty-evoked distress in the OIT sample (n = 38). CONCLUSIONS: Overall, this work is broadly consistent with existing work and implicates dorsal attention network connectivity in novelty-evoked distress. This study provides novel data on the neural basis of infant novelty-evoked distress.

White matter development and language abilities during infancy in autism spectrum disorder.

White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.

Multi-level fMRI analysis applied to hemispheric specialization in the language network, functional areas, and their behavioral correlations in the ABCD sample.

Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term "Wernicke's area" near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.

Infants who develop autism show smaller inventories of deictic and symbolic gestures at 12 months of age.

Gestures are an important social communication skill that infants and toddlers use to convey their thoughts, ideas, and intentions. Research suggests that early gesture use has important downstream impacts on developmental processes, such as language learning. However, autistic children are more likely to have challenges in their gestural development. The current study expands upon previous literature on the differences in gesture use between young autistic and non-autistic toddlers by collecting data using a parent-report questionnaire called the MCDI-Words and Gestures at three time points, 12, 18, and 24 months of age. Results (N = 467) showed that high-likelihood infants who later met diagnostic criteria for ASD (n = 73 HL-ASD) have attenuated gesture growth from 12 to 24 months for both deictic gestures and symbolic gestures when compared to high-likelihood infants who later did not meet criteria for ASD (n = 249 HL-Neg) and low-likelihood infants who did not meet criteria for ASD (n = 145 LL-Neg). Other social communicative skills, like play behaviors and imitation, were also found to be impacted in young autistic children when compared to their non-autistic peers. Understanding early differences in social communication growth before a formal autism diagnosis can provide important insights for early intervention.

Associations between early trajectories of amygdala development and later school-age anxiety in two longitudinal samples.

Amygdala function is implicated in the pathogenesis of autism spectrum disorder (ASD) and anxiety. We investigated associations between early trajectories of amygdala growth and anxiety and ASD outcomes at school age in two longitudinal studies: high- and low-familial likelihood for ASD, Infant Brain Imaging Study (IBIS, n = 257) and typically developing (TD) community sample, Early Brain Development Study (EBDS, n = 158). Infants underwent MRI scanning at up to 3 timepoints from neonate to 24 months. Anxiety was assessed at 6-12 years. Linear multilevel modeling tested whether amygdala volume growth was associated with anxiety symptoms at school age. In the IBIS sample, children with higher anxiety showed accelerated amygdala growth from 6 to 24 months. ASD diagnosis and ASD familial likelihood were not significant predictors. In the EBDS sample, amygdala growth from birth to 24 months was associated with anxiety. More anxious children had smaller amygdala volume and slower rates of amygdala growth. We explore reasons for the contrasting results between high-familial likelihood for ASD and TD samples, grounding results in the broader literature of variable associations between early amygdala volume and later anxiety. Results have the potential to identify mechanisms linking early amygdala growth to later anxiety in certain groups.

Endophenotype trait domains for advancing gene discovery in autism spectrum disorder.

Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Confronting Epistemic Injustice and Inequity in IDD Research: The Value of Theorizing Beyond Dominant Culture's Perspective.

This commentary highlights pervasive challenges related to the science of intellectual and developmental disabilities (IDD), which we often take for granted. We argue that social power asymmetry and entrenched patterns of epistemic injustices undermine our science and call attention to the need to maximize our efforts to undo these unfair practices to enhance future care and research in IDD.

Interactions between Bifidobacterium and Bacteroides and human milk oligosaccharides and their associations with infant cognition.

While ample research on independent associations between infant cognition and gut microbiota composition and human milk (HM) oligosaccharides (HMOs) has been reported, studies on how the interactions between gut microbiota and HMOs may yield associations with cognitive development in infancy are lacking. We aimed to determine how HMOs and species of Bacteroides and Bifidobacterium genera interact with each other and their associations with cognitive development in typically developing infants. A total of 105 mother-infant dyads were included in this study. The enrolled infants [2.9-12 months old (8.09 ± 2.48)] were at least predominantly breastfed at 4 months old. A total of 170 HM samples from the mothers and fecal samples of the children were collected longitudinally. Using the Mullen Scales of Early Learning to assess cognition and the scores as the outcomes, linear mixed effects models including both the levels of eight HMOs and relative abundance of Bacteroides and Bifidobacterium species as main associations and their interactions were employed with adjusting covariates; infant sex, delivery mode, maternal education, site, and batch effects of HMOs. Additionally, regression models stratifying infants based on the A-tetrasaccharide (A-tetra) status of the HM they received were also employed to determine if the associations depend on the A-tetra status. With Bacteroides species, we observed significant associations with motor functions, while Bif. catenulatum showed a negative association with visual reception in the detectable A-tetra group both as main effect (value of p = 0.012) and in interaction with LNFP-I (value of p = 0.007). Additionally, 3-FL showed a positive association with gross motor (p = 0.027) and visual reception (p = 0.041). Furthermore, significant associations were observed with the interaction terms mainly in the undetectable A-tetra group. Specifically, we observed negative associations for Bifidobacterium species and LNT [breve (p = 0.011) and longum (p = 0.022)], and positive associations for expressive language with 3'-SL and Bif. bifidum (p = 0.01), 6'-SL and B. fragilis (p = 0.019), and LNFP-I and Bif. kashiwanohense (p = 0.048), respectively. Our findings suggest that gut microbiota and HMOs are both independently and interactively associated with early cognitive development. In particular, the diverse interactions between HMOs and Bacteroides and Bifidobacterium species reveal different candidate pathways through which HMOs, Bifidobacterium and Bacteroides species potentially interact to impact cognitive development in infancy.

Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life.

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.

BIBSNet: A Deep Learning Baby Image Brain Segmentation Network for MRI Scans.

Objectives: Brain segmentation of infant magnetic resonance (MR) images is vitally important in studying developmental mental health and disease. The infant brain undergoes many changes throughout the first years of postnatal life, making tissue segmentation difficult for most existing algorithms. Here, we introduce a deep neural network BIBSNet (Baby and Infant Brain Segmentation Neural Network), an open-source, community-driven model that relies on data augmentation and a large sample size of manually annotated images to facilitate the production of robust and generalizable brain segmentations. Experimental Design: Included in model training and testing were MR brain images on 84 participants with an age range of 0-8 months (median postmenstrual ages of 13.57 months). Using manually annotated real and synthetic segmentation images, the model was trained using a 10-fold cross-validation procedure. Testing occurred on MRI data processed with the DCAN labs infant-ABCD-BIDS processing pipeline using segmentations produced from gold standard manual annotation, joint-label fusion (JLF), and BIBSNet to assess model performance. Principal Observations: Using group analyses, results suggest that cortical metrics produced using BIBSNet segmentations outperforms JLF segmentations. Additionally, when analyzing individual differences, BIBSNet segmentations perform even better. Conclusions: BIBSNet segmentation shows marked improvement over JLF segmentations across all age groups analyzed. The BIBSNet model is 600x faster compared to JLF and can be easily included in other processing pipelines.

A Prospective Evaluation of Infant Cerebellar-Cerebral Functional Connectivity in Relation to Behavioral Development in Autism Spectrum Disorder.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder diagnosed based on social impairment, restricted interests, and repetitive behaviors. Contemporary theories posit that cerebellar pathology contributes causally to ASD by disrupting error-based learning (EBL) during infancy. The present study represents the first test of this theory in a prospective infant sample, with potential implications for ASD detection. Methods: Data from the Infant Brain Imaging Study (n = 94, 68 male) were used to examine 6-month cerebellar functional connectivity magnetic resonance imaging in relation to later (12/24-month) ASD-associated behaviors and outcomes. Hypothesis-driven univariate analyses and machine learning-based predictive tests examined cerebellar-frontoparietal network (FPN; subserves error signaling in support of EBL) and cerebellar-default mode network (DMN; broadly implicated in ASD) connections. Cerebellar-FPN functional connectivity was used as a proxy for EBL, and cerebellar-DMN functional connectivity provided a comparative foil. Data-driven functional connectivity magnetic resonance imaging enrichment examined brain-wide behavioral associations, with post hoc tests of cerebellar connections. Results: Cerebellar-FPN and cerebellar-DMN connections did not demonstrate associations with ASD. Functional connectivity magnetic resonance imaging enrichment identified 6-month correlates of later ASD-associated behaviors in networks of a priori interest (FPN, DMN), as well as in cingulo-opercular (also implicated in error signaling) and medial visual networks. Post hoc tests did not suggest a role for cerebellar connections. Conclusions: We failed to identify cerebellar functional connectivity-based contributions to ASD. However, we observed prospective correlates of ASD-associated behaviors in networks that support EBL. Future studies may replicate and extend network-level positive results, and tests of the cerebellum may investigate brain-behavior associations at different developmental stages and/or using different neuroimaging modalities.