114 research outputs found
Developing customized NIRS-EEG for infant sleep research: methodological considerations
Significance:
Studies using simultaneous functional near-infrared spectroscopy (fNIRS)-electroencephalography (EEG) during natural sleep in infancy are rare. Developments for combined fNIRS-EEG for sleep research that ensure optimal comfort as well as good coupling and data quality are needed.
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Aim:
We describe the steps toward developing a comfortable, wearable NIRS-EEG headgear adapted specifically for sleeping infants ages 5 to 9 months and present the experimental procedures and data quality to conduct infant sleep research using combined fNIRS-EEG.
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Approach:
N = 49 5- to 9-month-old infants participated. In phase 1, N = 26 (10 = slept) participated using the non-wearable version of the NIRS-EEG headgear with 13-channel-wearable EEG and 39-channel fiber-based NIRS. In phase 2, N = 23 infants (21 = slept) participated with the wireless version of the headgear with 20-channel-wearable EEG and 47-channel wearable NIRS. We used QT-NIRS to assess the NIRS data quality based on the good time window percentage, included channels, nap duration, and valid EEG percentage.
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Results:
The infant nap rate during phase 1 was ∼40 % (45% valid EEG data) and increased to 90% during phase 2 (100% valid EEG data). Infants slept significantly longer with the wearable system than the non-wearable system. However, there were more included good channels based on QT-NIRS in study phase 1 (61%) than phase 2 (50%), though this difference was not statistically significant.
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Conclusions:
We demonstrated the usability of an integrated NIRS-EEG headgear during natural infant sleep with both non-wearable and wearable NIRS systems. The wearable NIRS-EEG headgear represents a good compromise between data quality, opportunities of applications (home visits and toddlers), and experiment success (infants’ comfort, longer sleep duration, and opportunities for caregiver–child interaction)
Developmental Paths to Anxiety in an Autism-Enriched Infant Cohort: The Role of Temperamental Reactivity and Regulation.
The aim of this study was to explore the associations between temperamental reactivity and regulation and the emergence of anxiety traits in a longitudinal sample of infants enriched for later ASD. Parents of 143 infants who were at high- and low-risk for ASD rated their child's temperament traits when they were 9, 15 and 24Â months old; they rated anxiety and ASD traits when they were 36Â months old. The findings suggest that behavioural inhibition may be an early predictor of later anxiety in children with and without ASD and that lower levels of effortful control in children who later develop ASD may contribute to the higher expression of anxiety within this population
EEG hyper-connectivity in high-risk infants is associated with later autism
- Background: It has been previously reported that structural and functional brain connectivity in individuals with autism spectrum disorders (ASD) is atypical and may vary with age. However, to date, no measures of functional connectivity measured within the first 2 years have specifically associated with a later ASD diagnosis.
- Methods: In the present study, we analyzed functional brain connectivity in 14-month-old infants at high and low familial risk for ASD using electroencephalography (EEG). EEG was recorded while infants attended to videos. Connectivity was assessed using debiased weighted phase lag index (dbWPLI). At 36 months, the high-risk infants were assessed for symptoms of ASD.
- Results: As a group, high-risk infants who were later diagnosed with ASD demonstrated elevated phase-lagged alpha-range connectivity as compared to both low-risk infants and high-risk infants who did not go on to ASD. Hyper-connectivity was most prominent over frontal and central areas. The degree of hyper-connectivity at 14 months strongly correlated with the severity of restricted and repetitive behaviors in participants with ASD at 3 years. These effects were not attributable to differences in behavior during the EEG session or to differences in spectral power.
- Conclusions: The results suggest that early hyper-connectivity in the alpha frequency range is an important feature of the ASD neurophysiological phenotype
Annual Research Review: Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND)-a systems neuroscience approach to common developmental disorders.
Funder: UK Medical Research Council Programme Grant MR/T003057/1; Id: http://dx.doi.org/10.13039/501100000265We present the Anterior Modifiers in the Emergence of Neurodevelopmental Disorders (AMEND) framework, designed to reframe the field of prospective studies of neurodevelopmental disorders. In AMEND we propose conceptual, statistical and methodological approaches to separating markers of early-stage perturbations from later developmental modifiers. We describe the evidence for, and features of, these interacting components before outlining analytical approaches to studying how different profiles of early perturbations and later modifiers interact to produce phenotypic outcomes. We suggest this approach could both advance our theoretical understanding and clinical approach to the emergence of developmental psychopathology in early childhood
Using multi-modal neuroimaging to characterise social brain specialisation in infants
The specialised regional functionality of the mature human cortex partly emerges
through experience-dependent specialisation during early development. Our existing understanding
of functional specialisation in the infant brain is based on evidence from unitary imaging modalities
and has thus focused on isolated estimates of spatial or temporal selectivity of neural or haemodynamic activation, giving an incomplete picture. We speculate that functional specialisation will
be underpinned by better coordinated haemodynamic and metabolic changes in a broadly orchestrated physiological response. To enable researchers to track this process through development, we
develop new tools that allow the simultaneous measurement of coordinated neural activity (EEG),
metabolic rate, and oxygenated blood supply (broadband near-infrared spectroscopy) in the awake
infant. In 4- to 7-month-old infants, we use these new tools to show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal
junction, a core hub region of the adult social brain. During non-social processing, coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest
with high-frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high-frequency brain activity. The development of simultaneous
multimodal neural measures will enable future researchers to open new vistas in understanding functional specialisation of the brain
Infant regulatory function acts as a protective factor for later traits of autism spectrum disorder and attention deficit/hyperactivity disorder but not callous unemotional traits.
BACKGROUND: Reduced executive functions (EF) are commonly associated with developmental conditions (e.g., autism spectrum disorder, ASD; attention deficit/hyperactivity disorder, ADHD), although EF seems to be typical in children with callous unemotional (CU) traits. Regulatory function (RF) is a proposed infant precursor that maps on onto factors driving later EF. Here, we first test whether RF is specifically and negatively associated with ASD and ADHD traits, but not CU traits. Second, we test whether RF can act as a protective factor, by moderating the association between infant markers and subsequent ASD and ADHD traits. METHODS: Participants were 79 infants at high (N = 42) and low (N = 37) familial risk for ASD. Data come from the 14-month infant visit (Autism Observational Scale for Infants; AOSI; activity level and RF from the Infant Behavior Questionnaire; IBQ) and the 7-year visit (ASD traits: Social Responsiveness Scale, SRS; ADHD traits: Conners 3, CU traits: Inventory of Callous Unemotional Traits). RESULTS: Infant RF was negatively associated with later traits of ASD (B = - 0.5, p = 0.01) and ADHD inattention (B = - 0.24, p = 0.02) but not hyperactivity (B = - 0.25, p = 0.10) or CU traits (B = 0.02, p = 0.86). RF moderated the association between infant AOSI score and ASD traits, with a significant effect in those with low RF (B = 0.10, p = 0.006), not high RF (B = 0.01, p = 0.78). Similarly, for ADHD, infant activity level was associated with later ADHD inattention in those with low (B = 0.17, p = 0.04) but not high RF (B = 0.07, p = 0.48). For ADHD hyperactivity symptoms, activity level was predictive at both high and low levels of RF. CONCLUSIONS: Strong RF may allow children to compensate for other atypicalities, thus attenuating the association between infant markers and later disorder traits. Whilst infant RF was associated with both ASD and ADHD inattention traits, there was no association with ADHD hyperactivity or CU traits. This suggests that any protective effect may not be universal and emphasises the need for a better understanding of the underlying moderating mechanisms
Transformer-based normative modelling for anomaly detection of early schizophrenia
Despite the impact of psychiatric disorders on clinical health, early-stage
diagnosis remains a challenge. Machine learning studies have shown that
classifiers tend to be overly narrow in the diagnosis prediction task. The
overlap between conditions leads to high heterogeneity among participants that
is not adequately captured by classification models. To address this issue,
normative approaches have surged as an alternative method. By using a
generative model to learn the distribution of healthy brain data patterns, we
can identify the presence of pathologies as deviations or outliers from the
distribution learned by the model. In particular, deep generative models showed
great results as normative models to identify neurological lesions in the
brain. However, unlike most neurological lesions, psychiatric disorders present
subtle changes widespread in several brain regions, making these alterations
challenging to identify. In this work, we evaluate the performance of
transformer-based normative models to detect subtle brain changes expressed in
adolescents and young adults. We trained our model on 3D MRI scans of
neurotypical individuals (N=1,765). Then, we obtained the likelihood of
neurotypical controls and psychiatric patients with early-stage schizophrenia
from an independent dataset (N=93) from the Human Connectome Project. Using the
predicted likelihood of the scans as a proxy for a normative score, we obtained
an AUROC of 0.82 when assessing the difference between controls and individuals
with early-stage schizophrenia. Our approach surpassed recent normative methods
based on brain age and Gaussian Process, showing the promising use of deep
generative models to help in individualised analyses.Comment: 10 pages, 2 figures, 2 tables, presented at NeurIPS22@PAI4M
Early differences in auditory processing relate to Autism Spectrum Disorder traits in infants with Neurofibromatosis Type I.
BackgroundSensory modulation difficulties are common in children with conditions such as Autism Spectrum Disorder (ASD) and could contribute to other social and non-social symptoms. Positing a causal role for sensory processing differences requires observing atypical sensory reactivity prior to the emergence of other symptoms, which can be achieved through prospective studies.MethodsIn this longitudinal study, we examined auditory repetition suppression and change detection at 5 and 10 months in infants with and without Neurofibromatosis Type 1 (NF1), a condition associated with higher likelihood of developing ASD.ResultsIn typically developing infants, suppression to vowel repetition and enhanced responses to vowel/pitch change decreased with age over posterior regions, becoming more frontally specific; age-related change was diminished in the NF1 group. Whilst both groups detected changes in vowel and pitch, the NF1 group were largely slower to show a differentiated neural response. Auditory responses did not relate to later language, but were related to later ASD traits.ConclusionsThese findings represent the first demonstration of atypical brain responses to sounds in infants with NF1 and suggest they may relate to the likelihood of later ASD
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Behavioural Measures of Infant Activity but Not Attention Associate with Later Preschool ADHD Traits.
Behavioural Measures of Infant Activity but Not Attention Associate with Later Preschool ADHD Traits.
Mapping infant neurocognitive differences that precede later ADHD-related behaviours is critical for designing early interventions. In this study, we investigated (1) group differences in a battery of measures assessing aspects of attention and activity level in infants with and without a family history of ADHD or related conditions (ASD), and (2) longitudinal associations between the infant measures and preschool ADHD traits at 3 years. Participants (N = 151) were infants with or without an elevated likelihood for ADHD (due to a family history of ADHD and/or ASD). A multi-method assessment protocol was used to assess infant attention and activity level at 10 months of age that included behavioural, cognitive, physiological and neural measures. Preschool ADHD traits were measured at 3 years of age using the Child Behaviour Checklist (CBCL) and the Child Behaviour Questionnaire (CBQ). Across a broad range of measures, we found no significant group differences in attention or activity level at 10 months between infants with and without a family history of ADHD or ASD. However, parent and observer ratings of infant activity level at 10 months were positively associated with later preschool ADHD traits at 3 years. Observable behavioural differences in activity level (but not attention) may be apparent from infancy in children who later develop elevated preschool ADHD traits
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