Brain enlargement has been observed in children with autism spectrum disorder (ASD), but the timing of this phenomenon, and the relationship between ASD and the appearance of behavioural symptoms, ...are unknown. Retrospective head circumference and longitudinal brain volume studies of two-year olds followed up at four years of age have provided evidence that increased brain volume may emerge early in development. Studies of infants at high familial risk of autism can provide insight into the early development of autism and have shown that characteristic social deficits in ASD emerge during the latter part of the first and in the second year of life. These observations suggest that prospective brain-imaging studies of infants at high familial risk of ASD might identify early postnatal changes in brain volume that occur before an ASD diagnosis. In this prospective neuroimaging study of 106 infants at high familial risk of ASD and 42 low-risk infants, we show that hyperexpansion of the cortical surface area between 6 and 12 months of age precedes brain volume overgrowth observed between 12 and 24 months in 15 high-risk infants who were diagnosed with autism at 24 months. Brain volume overgrowth was linked to the emergence and severity of autistic social deficits. A deep-learning algorithm that primarily uses surface area information from magnetic resonance imaging of the brain of 6-12-month-old individuals predicted the diagnosis of autism in individual high-risk children at 24 months (with a positive predictive value of 81% and a sensitivity of 88%). These findings demonstrate that early brain changes occur during the period in which autistic behaviours are first emerging.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social deficits and repetitive behaviors that typically emerge by 24 months of age. To develop effective early ...interventions that can potentially ameliorate the defining deficits of ASD and improve long-term outcomes, early detection is essential. Using prospective neuroimaging of 59 6-month-old infants with a high familial risk for ASD, we show that functional connectivity magnetic resonance imaging correctly identified which individual children would receive a research clinical best-estimate diagnosis of ASD at 24 months of age. Functional brain connections were defined in 6-month-old infants that correlated with 24-month scores on measures of social behavior, language, motor development, and repetitive behavior, which are all features common to the diagnosis of ASD. A fully cross-validated machine learning algorithm applied at age 6 months had a positive predictive value of 100% 95% confidence interval (CI), 62.9 to 100, correctly predicting 9 of 11 infants who received a diagnosis of ASD at 24 months (sensitivity, 81.8%; 95% CI, 47.8 to 96.8). All 48 6-month-old infants who were not diagnosed with ASD were correctly classified specificity, 100% (95% CI, 90.8 to 100); negative predictive value, 96.0% (95% CI, 85.1 to 99.3). These findings have clinical implications for early risk assessment and the feasibility of developing early preventative interventions for ASD.
Infant vocalizations are early‐emerging communicative markers shown to be atypical in autism spectrum disorder (ASD), but few longitudinal, prospective studies exist. In this study, 23,850 infant ...vocalizations from infants at low (LR)‐ and high (HR)‐risk for ASD (HR‐ASD = 23, female = 3; HR‐Neg = 35, female = 13; LR = 32, female = 10; 80% White; collected from 2007 to 2017 near Philadelphia) were analyzed at 6, 12, and 24 months. At 12 months, HR‐ASD infants produced fewer vocalizations than HR‐Neg infants. From 6 to 24 months, HR‐Neg infants demonstrated steeper vocalization growth compared to HR‐ASD and LR infants. Finally, among HR infants, vocalizing at 12 months was associated with language, social phenotype, and diagnosis at age 2. Infant vocalizing is an objective behavioral marker that could facilitate earlier detection of ASD.
Abstract Background Autism Spectrum Disorder (ASD) is a developmental disorder defined by behavioural features that emerge during the first years of life. Research indicates that abnormalities in ...brain connectivity are associated with these behavioural features. However, inclusion of individuals past the age of onset of the defining behaviours complicates interpretation of the observed abnormalities: they may be cascade effects of earlier neuropathology and behavioural abnormalities. Our recent study of network efficiency in a cohort of 24-month-olds at high and low familial risk for ASD reduced this confound; we reported reduced network efficiencies in toddlers classified as ASD. The current study maps the emergence of these inefficiencies in the first year of life. Methods The study utilizes data from 260 infants at 6 and 12 months of age, including 116 infants with longitudinal data. As in our earlier study, we use diffusion data to obtain measures of the length and strength of connections between brain regions in order to compute network efficiency. We assess group differences in efficiency within linear mixed-effects models determined by the Akaike information criterion. Results Inefficiencies in high-risk infants later classified as ASD were detected from 6 months onward in regions involved in low-level sensory processing. Additionally, within the high-risk infants, these inefficiencies predicted 24-month symptom severity. Conclusion These results suggest that infants with ASD, even before 6 months of age, have deficits in connectivity related to low-level processing, which contribute to a developmental cascade affecting brain organization, and eventually higher-level cognitive processes and social behaviour.
Prediction of Individual Brain Maturity Using fMRI Dosenbach, Nico U. F.; Nardos, Binyam; Cohen, Alexander L. ...
Science (American Association for the Advancement of Science),
09/2010, Letnik:
329, Številka:
5997
Journal Article
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Group functional connectivity magnetic resonance imaging (fcAARI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector ...machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.
Initiating joint attention (IJA), the behavioral instigation of coordinated focus of 2 people on an object, emerges over the first 2 years of life and supports social-communicative functioning ...related to the healthy development of aspects of language, empathy, and theory of mind. Deficits in IJA provide strong early indicators for autism spectrum disorder, and therapies targeting joint attention have shown tremendous promise. However, the brain systems underlying IJA in early childhood are poorly understood, due in part to significant methodological challenges in imaging localized brain function that supports social behaviors during the first 2 years of life. Herein, we show that the functional organization of the brain is intimately related to the emergence of IJA using functional connectivity magnetic resonance imaging and dimensional behavioral assessments in a large semilongitudinal cohort of infants and toddlers. In particular, though functional connections spanning the brain are involved in IJA, the strongest brain-behavior associations cluster within connections between a small subset of functional brain networks; namely between the visual network and dorsal attention network and between the visual network and posterior cingulate aspects of the default mode network. These observations mark the earliest known description of how functional brain systems underlie a burgeoning fundamental social behavior, may help improve the design of targeted therapies for neurodevelopmental disorders, and, more generally, elucidate physiological mechanisms essential to healthy social behavior development.
Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has ...universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep. We find that important functional connectivity features seen during infant sleep closely resemble those seen during adult sleep, including reduced default mode network functional connectivity. However, we also find differences between infant and adult sleep, especially in thalamic BOLD signal propagation patterns. These findings highlight the importance of considering sleep state when drawing developmental inferences in infant rs-fMRI.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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.
Social motivation—the psychobiological predisposition for social orienting, seeking social contact, and maintaining social interaction—manifests in early infancy and is hypothesized to be ...foundational for social communication development in typical and atypical populations. However, the lack of infant social‐motivation measures has hindered delineation of associations between infant social motivation, other early‐arising social abilities such as joint attention, and language outcomes. To investigate how infant social motivation contributes to joint attention and language, this study utilizes a mixed longitudinal sample of 741 infants at high (HL = 515) and low (LL = 226) likelihood for ASD. Using moderated nonlinear factor analysis (MNLFA), we incorporated items from parent‐report measures to establish a novel latent factor model of infant social motivation that exhibits measurement invariance by age, sex, and familial ASD likelihood. We then examined developmental associations between 6‐ and 12‐month social motivation, joint attention at 12–15 months, and language at 24 months of age. On average, greater social‐motivation growth from 6–12 months was associated with greater initiating joint attention (IJA) and trend‐level increases in sophistication of responding to joint attention (RJA). IJA and RJA were both positively associated with 24‐month language abilities. There were no additional associations between social motivation and future language in our path model. These findings substantiate a novel, theoretically driven approach to modeling social motivation and suggest a developmental cascade through which social motivation impacts other foundational skills. These findings have implications for the timing and nature of intervention targets to support social communication development in infancy.
Highlights
We describe a novel, theoretically based model of infant social motivation wherein multiple parent‐reported indicators contribute to a unitary latent social‐motivation factor.
Analyses revealed social‐motivation factor scores exhibited measurement invariance for a longitudinal sample of infants at high and low familial ASD likelihood.
Social‐motivation growth from ages 6–12 months is associated with better 12−15‐month joint attention abilities, which in turn are associated with greater 24‐month language skills.
Findings inform timing and targets of potential interventions to support healthy social communication in the first year of life.
We describe a novel, theoretically based model of infant social motivation wherein multiple parent‐reported indicators contribute to a unitary latent social‐motivation factor. Analyses revealed social‐motivation factor scores exhibited measurement invariance for longitudinal sample of infants at high and low familial ASD likelihood. Social motivation growth from ages 6–12 months is associated with better 12–15 moths joint attention abilities, which in turn are associated with greater 24‐month language skills.
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