Neonatal EEG linked to individual differences in socioemotional outcomes and autism risk in toddlers

Prenatal family income, but not parental education, is associated with resting brain activity in 1-month-old infants

Childhood socioeconomic disadvantage is associated with disparities in development and health, possibly through adaptations in children's brain function. However, it is not clear how early in development such neural adaptations might emerge. This study examined whether prenatal family socioeconomic status, operationalized as family income and average years of parental education, prospectively predicts individual differences in infant resting electroencephalography (EEG; theta, alpha, beta, and gamma power) at approximately 1 month of age (N = 160). Infants of mothers reporting lower family income showed more lower-frequency (theta) and less higher-frequency (beta and gamma) power. These associations held when adjusting for other prenatal and postnatal experiences, as well as infant demographic and health-related factors. In contrast, parental education was not significantly associated with infant EEG power in any frequency band. These data suggest that lower prenatal family income is associated with developmental differences in brain function that are detectable within the first month of life.

The importance of decomposing periodic and aperiodic EEG signals for assessment of brain function in a global context

Measures of early neuro-cognitive development that are suitable for use in low-resource settings are needed to enable studies of the effects of early adversity on the developing brain in a global context. These measures should have high acquisition rates and good face and construct validity. Here, we investigated the feasibility of a naturalistic electroencephalography (EEG) paradigm in a low-resource context during childhood. Additionally, we examined the sensitivity of periodic and aperiodic EEG metrics to social and non-social stimuli. We recorded simultaneous 20-channel EEG and eye-tracking in 72 children aged 4-12 years (45 females) while they watched videos of women singing nursery rhymes and moving toys, selected to represent familiar childhood experiences. These measures were part of a feasibility study that assessed the feasibility and acceptability of a follow-up data collection of the South African Safe Passage Study, which tracks environmental adversity and brain and cognitive development from before birth up until childhood. We examined whether data quantity and quality varied with child characteristics and the sensitivity of varying EEG metrics (canonical band power in the theta and alpha band and periodic and aperiodic features of the power spectra). We found that children who completed the EEG and eye-tracking assessment were, in general, representative of the full cohort. Data quantity was higher in children with greater visual attention to the stimuli. Out of the tested EEG metrics, periodic measures in the theta frequency range were most sensitive to condition differences, compared to alpha range measures and canonical and aperiodic EEG measures. Our results show that measuring EEG during ecologically valid social and non-social stimuli is feasible in low-resource settings, is feasible for most children, and produces robust indices of social brain function. This work provides preliminary support for testing longitudinal links between social brain function, environmental factors, and emerging behaviors.

Associations between maternal stress and infant resting brain activity among families residing in poverty in the U.S

Growing evidence suggests that maternal experiences of stress shape children's functional brain activity in the first years of life. Individuals living in poverty are more likely to experience stress from a variety of sources. However, it is unclear how stress is related to resting brain activity among children born into poverty. The present study examines whether infants born into households experiencing poverty show differences in brain activity associated with maternal reports of experiencing stress. The analytic sample comprised 247 mother-infant dyads who completed maternal questionnaires characterizing stress, and for whom recordings of infant resting brain activity were obtained at 1 year of age (M=12.93 months, SD=1.66; 50% female). Mothers (40% Black, non-Hispanic, 40% Hispanic, 12% White, non-Hispanic) who reported higher stress had infants who showed more resting brain activity in the lower end of the frequency spectrum (relative theta power) and less resting brain activity in the middle range of the frequency spectrum (relative alpha power). While statistically detectable at the whole-brain level, follow-up exploratory analyses revealed that these effects were most apparent in electrodes over frontal and parietal regions of the brain. These findings held after adjusting for a variety of potentially confounding variables. Altogether, the present study suggests that, among families experiencing low economic resources, maternal reports of stress are associated with differences in patterns of infant resting brain activity during the first year of life.

A scoping review of physiological biomarkers in autism

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by pervasive deficits in social interaction, communication impairments, and the presence of restricted and repetitive behaviors. This complex disorder is a significant public health concern due to its escalating incidence and detrimental impact on quality of life. Currently, extensive investigations are underway to identify prospective susceptibility or predictive biomarkers, employing a physiological biomarker-based framework. However, knowledge regarding physiological biomarkers in relation to Autism is sparse. We performed a scoping review to explore putative changes in physiological activities associated with behaviors in individuals with Autism. We identified studies published between January 2000 and June 2023 from online databases, and searched keywords included electroencephalography (EEG), magnetoencephalography (MEG), electrodermal activity markers (EDA), eye-tracking markers. We specifically detected social-related symptoms such as impaired social communication in ASD patients. Our results indicated that the EEG/ERP N170 signal has undergone the most rigorous testing as a potential biomarker, showing promise in identifying subgroups within ASD and displaying potential as an indicator of treatment response. By gathering current data from various physiological biomarkers, we can obtain a comprehensive understanding of the physiological profiles of individuals with ASD, offering potential for subgrouping and targeted intervention strategies.

Effects of repetitive transcranial magnetic stimulation combined with action-observation-execution on social interaction and communication in autism spectrum disorder: Feasibility study

OBJECTIVE

To investigate the feasibility of a combined high-frequency rTMS (HF-rTMS) with action observation and execution (AOE) on social interaction and communication in children with Autistic Spectrum Disorder (ASD).

MATERIALS AND METHODS

Fifteen children underwent 10 sessions of 5-Hz HF-rTMS on the right inferior frontal gyrus combined with AOE. An experimental group received the real HF-rTMS while the control group received the sham one. For the AOE protocol, they were instructed to watch and imitate a video showing the procedure, including reaching and grasping tasks, gustatory tasks, and facial expressions. Their behavioural outcomes were evaluated using the Vineland Adaptive Behaviour Scale (VABS) and electroencephalograms (EEGs) recorded at three time points: baseline, immediately after each treatment, and at the 1-week follow-up after the 10th treatment.

RESULTS

There were increased VABS subitem scores in the experimental group, including the receptive, expressive, domestic, and community scores but no such increase was observed in the control group. For the EEG, the beta rhythm at C3 and C4 increased in the experimental group. Additionally, positive correlations were observed between changes in the scores for the expressive subitem and changes in the beta rhythm on the C4 electrode at baseline and immediately after treatment in the experimental group. The control group showed no significant differences in any items for both observation and imitation times.

CONCLUSION

Ten sessions of HF-rTMS combined with AOE could improve both the subitems of communication and daily living skills domain in children aged 7-12 years with ASD. Although it is still inconclusive, this behavioural improvement may be partly attributable to increased cortical activity, as evidenced by beta rhythms.

Supplementation With Iron Syrup or Iron-Containing Multiple Micronutrient Powders Alters Resting Brain Activity in Bangladeshi Children

BACKGROUND

Anemia and iron deficiency have been associated with poor child cognitive development. A key rationale for the prevention of anemia using supplementation with iron has been the benefits to neurodevelopment. However, little causal evidence exists for these gains.

OBJECTIVES

We aimed to examine effects of supplementation with iron or multiple micronutrient powders (MNPs) on brain activity measures using resting electroencephalography (EEG).

METHODS

Children included in this neurocognitive substudy were randomly selected from the Benefits and Risks of Iron Supplementation in Children study, a double-blind, double-dummy, individually randomized, parallel-group trial in Bangladesh, in which children, starting at 8 mo of age, received 3 mo of daily iron syrup, MNPs, or placebo. Resting brain activity was recorded using EEG immediately after intervention (month 3) and after a further 9-month follow-up (month 12). We derived EEG band power measures for delta, theta, alpha, and beta frequency bands. Linear regression models were used to compare the effect of each intervention with that of placebo on the outcomes.

RESULTS

Data from 412 children at month 3 and 374 at month 12 were analyzed. At baseline, 43.9% were anemic and 26.7% were iron deficient. Immediately after intervention, iron syrup, but not MNPs, increased the mu alpha-band power, a measure that is associated with maturity and the production of motor actions (iron vs. placebo: mean difference = 0.30; 95% CI: 0.11, 0.50 μV²; P = 0.003; false discovery rate adjusted P = 0.015). Despite effects on hemoglobin and iron status, effects were not observed on the posterior alpha, beta, delta, and theta bands, nor were effects sustained at the 9-month follow-up.

CONCLUSIONS

The effect size for immediate effects on the mu alpha-band power is comparable in magnitude with psychosocial stimulation interventions and poverty reduction strategies. However, overall, we did not find evidence for long-lasting changes in resting EEG power spectra from iron interventions in young Bangladeshi children. This trial was registered at www.anzctr.org.au as ACTRN12617000660381.

HAPPILEE: HAPPE In Low Electrode Electroencephalography, a standardized pre-processing software for lower density recordings

Lower-density Electroencephalography (EEG) recordings (from 1 to approximately 32 electrodes) are widely-used in research and clinical practice and enable scalable brain function measurement across a variety of settings and populations. Though a number of automated pipelines have recently been proposed to standardize and optimize EEG pre-processing for high-density systems with state-of-the-art methods, few solutions have emerged that are compatible with lower-density systems. However, lower-density data often include long recording times and/or large sample sizes that would benefit from similar standardization and automation with contemporary methods. To address this need, we propose the HAPPE In Low Electrode Electroencephalography (HAPPILEE) pipeline as a standardized, automated pipeline optimized for EEG recordings with lower density channel layouts of any size. HAPPILEE processes task-free (e.g., resting-state) and task-related EEG (including event-related potential data by interfacing with the HAPPE+ER pipeline), from raw files through a series of processing steps including filtering, line noise reduction, bad channel detection, artifact correction from continuous data, segmentation, and bad segment rejection that have all been optimized for lower density data. HAPPILEE also includes post-processing reports of data and pipeline quality metrics to facilitate the evaluation and reporting of data quality and processing-related changes to the data in a standardized manner. Here the HAPPILEE steps and their optimization with both recorded and simulated EEG data are described. HAPPILEE's performance is then compared relative to other artifact correction and rejection strategies. The HAPPILEE pipeline is freely available as part of HAPPE 2.0 software under the terms of the GNU General Public License at: https://github.com/PINE-Lab/HAPPE.

Paid maternal leave is associated with infant brain function at 3 months of age

The first months of life are critical for establishing neural connections relevant for social and cognitive development. Yet, the United States lacks a national policy of paid family leave during this important period of brain development. This study examined associations between paid leave and infant electroencephalography (EEG) at 3 months in a sociodemographically diverse sample of families from New York City (N = 80; 53 males; 48% Latine; data collection occurred 05/2018-12/2019). Variable-centered regression results indicate that paid leave status was related to differences in EEG power (ps < .02, R² s > .12). Convergent results from person-centered latent profile analyses demonstrate that mothers with paid leave were 7.39 times as likely to have infants with EEG profiles characterized by increased higher-Hz power (95% CI, 1.9-36.9), potentially reflecting more mature patterns of brain activity.

Aperiodic electrophysiological activity in preterm infants is linked to subsequent autism risk

Approximately 7% of preterm infants receive an autism spectrum disorder (ASD) diagnosis. Yet, there is a significant gap in the literature in identifying prospective markers of neurodevelopmental risk in preterm infants. The present study examined two electroencephalography (EEG) parameters during infancy, absolute EEG power and aperiodic activity of the power spectral density (PSD) slope, in association with subsequent autism risk and cognitive ability in a diverse cohort of children born preterm in South Africa. Participants were 71 preterm infants born between 25 and 36 weeks gestation (34.60 ± 2.34 weeks). EEG was collected during sleep between 39 and 41 weeks postmenstrual age adjusted (40.00 ± 0.42 weeks). The Bayley Scales of Infant Development and Brief Infant Toddler Social Emotional Assessment (BITSEA) were administered at approximately 3 years of age adjusted (34 ± 2.7 months). Aperiodic activity, but not the rhythmic oscillatory activity, at multiple electrode sites was associated with subsequent increased autism risk on the BITSEA at three years of age. No associations were found between the PSD slope or absolute EEG power and cognitive development. Our findings highlight the need to examine potential markers of subsequent autism risk in high-risk populations other than infants at familial risk.

Annual Research Review: The contributions of the RDoC research framework on understanding the neurodevelopmental origins, progression and treatment of mental illnesses

The National Institute of Mental Health (NIMH) proposed the Research Domain Criteria (RDoC) initiative as an alternate way to organize research of mental illnesses, by looking at dimensions of functioning rather than being tied to categorical diagnoses. This paper briefly discusses the motivation for and organization of RDoC, and then explores the NIMH portfolio and recent work to monitor the utility and progress that RDoC has afforded developmental research. To examine how RDoC has influenced the NIMH developmental research portfolio over the last decade, we employed a natural language processing algorithm to identify the number of developmental science grants classified as incorporating an RDoC approach. Additional portfolio analyses examine temporal trends in funded RDoC-relevant grants, publications and citations, and research training opportunities. Reflecting on how RDoC has influenced the focus of grant applications, we highlight examples from research on Attention-Deficit Hyperactivity Disorder (ADHD), childhood irritability, and Autism Spectrum Disorder (ASD). Lastly, we consider how the dimensional and transdiagnostic approaches emphasized in RDoC have facilitated research on personalized intervention for heterogeneous disorders and preventive/early interventions targeting emergent or subthreshold psychopathology.

Neonatal quantitative electroencephalography and long-term outcomes: a systematic review

AIM

To evaluate quantitative electroencephalogram (EEG) measures as predictors of long-term neurodevelopmental outcome in infants with a postconceptional age below 46 weeks, including typically developing infants born at term, infants with heterogeneous underlying pathologies, and infants born preterm.

METHOD

A comprehensive search was performed using PubMed, Embase, and Web of Science from study inception up to 8th January 2021. Studies that examined associations between neonatal quantitative EEG measures, based on conventional and amplitude-integrated EEG, and standardized neurodevelopmental outcomes at 2 years of age or older were reviewed. Significant associations between neonatal quantitative EEG and long-term outcome measures were grouped into one or more of the following categories: cognitive outcome; motor outcome; composite scores; and other standardized outcome assessments.

RESULTS

Twenty-four out of 1740 studies were included. Multiple studies showed that conventional EEG-based absolute power in the delta, theta, alpha, and beta frequency bands and conventional and amplitude-integrated EEG-related amplitudes were positively associated with favourable long-term outcome across several domains, including cognition and motor performance. Furthermore, a lower presence of discontinuous background pattern was also associated with favourable outcomes. However, interpretation of the results is limited by heterogeneity in study design and populations.

INTERPRETATION

Neonatal quantitative EEG measures may be used as prognostic biomarkers to identify those infants who will develop long-term difficulties and who might benefit from early interventions.

The Value of Brain Imaging and Electrophysiological Testing for Early Screening of Autism Spectrum Disorder: A Systematic Review

Given the significance of validating reliable tests for the early detection of autism spectrum disorder (ASD), this systematic review aims to summarize available evidence of neuroimaging and neurophysiological changes in high-risk infants to improve ASD early diagnosis. We included peer-reviewed, primary research in English published before May 21, 2021, involving the use of magnetic resonance imaging (MRI), electroencephalogram (EEG), or functional near-infrared spectroscopy (fNIRS) in children with high risk for ASD under 24 months of age. The main exclusion criteria includes diagnosis of a genetic disorder and gestation age of less the 36 weeks. Online research was performed on PubMed, Web of Science, PsycINFO, and CINAHL. Article selection was conducted by two reviewers to minimize bias. This research was funded by Massachusetts General Hospital Sundry funding. IRB approval was not submitted as it was deemed unnecessary. We included 75 primary research articles. Studies showed that high-risk infants had divergent developmental trajectories for fractional anisotropy and regional brain volumes, increased CSF volume, and global connectivity abnormalities on MRI, decreased sensitivity for familiar faces, atypical lateralization during facial and auditory processing, and different spectral powers across multiple band frequencies on EEG, and distinct developmental trajectories in functional connectivity and regional oxyhemoglobin concentrations in fNIRS. These findings in infants were found to be correlated with the core ASD symptoms and diagnosis at toddler age. Despite the lack of quantitative analysis of the research database, neuroimaging and electrophysiological biomarkers have promising value for the screening of ASD as early as infancy with high accuracy, which warrants further investigation.

The impact of a poverty reduction intervention on infant brain activity

This study demonstrates the causal impact of a poverty reduction intervention on early childhood brain activity. Data from the Baby’s First Years study, a randomized control trial, show that a predictable, monthly unconditional cash transfer given to low-income families may have a causal impact on infant brain activity. In the context of greater economic resources, children’s experiences changed, and their brain activity adapted to those experiences. The resultant brain activity patterns have been shown to be associated with the development of subsequent cognitive skills.

Early childhood poverty is a risk factor for lower school achievement, reduced earnings, and poorer health, and has been associated with differences in brain structure and function. Whether poverty causes differences in neurodevelopment, or is merely associated with factors that cause such differences, remains unclear. Here, we report estimates of the causal impact of a poverty reduction intervention on brain activity in the first year of life. We draw data from a subsample of the Baby’s First Years study, which recruited 1,000 diverse low-income mother–infant dyads. Shortly after giving birth, mothers were randomized to receive either a large or nominal monthly unconditional cash gift. Infant brain activity was assessed at approximately 1 y of age in the child’s home, using resting electroencephalography (EEG; n = 435). We hypothesized that infants in the high-cash gift group would have greater EEG power in the mid- to high-frequency bands and reduced power in a low-frequency band compared with infants in the low-cash gift group. Indeed, infants in the high-cash gift group showed more power in high-frequency bands. Effect sizes were similar in magnitude to many scalable education interventions, although the significance of estimates varied with the analytic specification. In sum, using a rigorous randomized design, we provide evidence that giving monthly unconditional cash transfers to mothers experiencing poverty in the first year of their children’s lives may change infant brain activity. Such changes reflect neuroplasticity and environmental adaptation and display a pattern that has been associated with the development of subsequent cognitive skills.

Sex differences in neuronal systems function and behaviour: beyond a single diagnosis in autism spectrum disorders

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is associated with functional brain alterations that underlie the expression of behaviour. Males are diagnosed up to four times more than females, and sex differences have been identified in memory, cognitive flexibility, verbal fluency, and social communication. Unfortunately, there exists a lack of information on the sex-dependent mechanisms of ASD, as well as biological markers to distinguish sex-specific symptoms in ASD. This can often result in a standardized diagnosis for individuals across the spectrum, despite significant differences in the various ASD subtypes. Alterations in neuronal connectivity and oscillatory activity, such as is observed in ASD, are highly coupled to behavioural states. Yet, despite the well-identified sexual dimorphisms that exist in ASD, these functional patterns have rarely been analyzed in the context of sex differences or symptomology. This review summarizes alterations in neuronal oscillatory function in ASD, discusses the age, region, symptom and sex-specific differences that are currently observed across the spectrum, and potential targets for regulating neuronal oscillatory activity in ASD. The need to identify sex-specific biomarkers, in order to facilitate specific diagnostic criteria and allow for more targeted therapeutic approaches for ASD will also be discussed.

Resting state EEG in youth with ASD: age, sex, and relation to phenotype

BACKGROUND

Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy.

METHODS

We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations.

RESULTS

Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD.

CONCLUSIONS

Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

EEG Phase-Amplitude Coupling Strength and Phase Preference: Association with Age over the First Three Years after Birth

Phase-amplitude coupling (PAC), the coupling of the phase of slower electrophysiological oscillations with the amplitude of faster oscillations, is thought to facilitate dynamic integration of neural activity in the brain. Although the brain undergoes dramatic change and development during the first few years of life, how PAC changes through this developmental period has not been extensively studied. Here, we examined PAC through electroencephalography (EEG) data collected during an awake, eyes-open EEG collection paradigm in 98 children between the ages of three months and three years. We employed non-parametric clustering methods to identify areas of significant PAC across a range of frequency pairs and electrode locations, and examined how PAC strength and phase preference develops in these areas. We found that PAC, primarily between the α-β and γ frequencies, was positively correlated with age from early infancy to early childhood (p = 2.035 × 10-6). Additionally, we found γ over anterior electrodes coupled with the rising phase of the α-β waveform, while γ over posterior electrodes coupled with the falling phase of the α-β waveform; this regionalized phase preference became more prominent with age. This opposing trend may reflect each region's specialization toward feedback or feedforward processing, respectively, suggesting opportunities for back translation in future studies.

Electroencephalographic Abnormalities in Autism Spectrum Disorder: Characteristics and Therapeutic Implications

A large body of literature reports the higher prevalence of epilepsy in subjects with Autism Spectrum Disorder (ASD) compared to the general population. Similarly, several studies report an increased rate of Subclinical Electroencephalographic Abnormalities (SEAs) in seizure-free patients with ASD rather than healthy controls, although with varying percentages. SEAs include both several epileptiform discharges and different non-epileptiform electroencephalographic abnormalities. They are more frequently associated with lower intellectual functioning, more serious dysfunctional behaviors, and they are often sign of severer forms of autism. However, SEAs clinical implications remain controversial, and they could represent an epiphenomenon of the neurochemical alterations of autism etiology. This paper provides an overview of the major research findings with two main purposes: to better delineate the state-of-the-art about EEG abnormalities in ASD and to find evidence for or against appropriateness of SEAs pharmacological treatment in ASD.

Neuroimaging Markers of Risk and Pathways to Resilience in Autism Spectrum Disorder

Autism spectrum disorder is a complex, heterogeneous neurodevelopmental condition of largely unknown etiology. This heterogeneity of symptom presentation, combined with high rates of comorbidity with other developmental disorders and a lack of reliable biomarkers, makes diagnosing and evaluating life outcomes for individuals with autism spectrum disorder a challenge. We review the growing literature on neuroimaging-based biomarkers of risk for the development of autism and explore evidence for resilience in some autistic individuals. The current literature suggests that neuroimaging during early infancy, in combination with prebirth and early genetic studies, is a promising tool for identifying biomarkers of risk, while studies of gene expression and DNA methylation have provided some key insights into mechanisms of resilience. With genetics and the environment contributing to both risk for the development of autism spectrum disorder and conditions for resilience, additional studies are needed to understand how risk and resilience interact mechanistically, whereby factors of risk may engender conditions for adaptation. Future studies should prioritize longitudinal designs in global cohorts, with the involvement of the autism community as partners in research to help identify domains of functioning that hold value and importance to the community.

Associations among the home language environment and neural activity during infancy

Characteristics of the home language environment, independent of socioeconomic background, may account for disparities in early language abilities. Past studies have reported links between the quantity of language input within the home and differences in brain function during early childhood. The current study examined associations between home language input and EEG brain activity in a socioeconomically diverse sample of 6- to 12-month-old infants (N = 94). Replicating past studies, a positive correlation was found between measures of socioeconomic status and language input. Examining links between language input and brain activity, analyses yielded a negative association, with children who heard more adult words in the home demonstrating reduced EEG beta power (13-19 Hz) in the parietal region. Exploratory analyses revealed a significant interaction between language input and the amount of chaos and disorganization in the home. Specifically, among children living in high-chaos households, children who heard more adult words tended to have reduced EEG activity. Among children living in low-chaos homes, there was no link between adult word count and children's EEG activity. These findings demonstrate the importance of the early home environment context in shaping neurocognitive trajectories.

Association Between Prenatal Exposure to Alcohol and Tobacco and Neonatal Brain Activity: Results From the Safe Passage Study

IMPORTANCE

Research to date has not determined a safe level of alcohol or tobacco use during pregnancy. Electroencephalography (EEG) is a noninvasive measure of cortical function that has previously been used to examine effects of in utero exposures and associations with neurodevelopment.

OBJECTIVE

To examine the association of prenatal exposure to alcohol (PAE) and tobacco smoking (PTE) with brain activity in newborns.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study enrolled mother-newborn dyads from December 2011 through August 2015, with data analyzed from June 2018 through June 2019. Pregnant women were recruited from clinical sites in Cape Town, South Africa, and the Northern Plains region of the US. Participants were a subset of newborns enrolled in the Safe Passage Study. Exclusions included birth at less than 37 or more than 41 weeks' gestation, multiple birth, or maternal use of psychiatric medication during pregnancy.

EXPOSURES

PAE and PTE groups were determined by cluster analysis.

MAIN OUTCOMES AND MEASURES

Analyses of covariance were run on EEG spectral power at 12 scalp locations across the frequency spectrum from 1 to 45 Hz in 3-Hz bins by sleep state.

RESULTS

The final sample consisted of 1739 newborns (median [interquartile range] gestational age at birth, 39.29 [1.57] weeks; 886 [50.9%] were female; median [interquartile range] newborn age at assessment, 48.53 [44.96] hours). Newborns whose mothers were in the low continuous (95% CI, -0.379 to -0.031; P < .05; 95% CI, -0.379 to -0.045; P < .05), quit (95% CI, -0.419 to -0.127; P < .001; 95% CI, -0.398 to -0.106; P < .005), and moderate or high continuous (95% CI, -0.430 to -0.124; P < .001; 95% CI, -0.420 to -0.119; P < .005) PAE clusters had increased 4- to 6-Hz and 7- to 9-Hz left-temporal EEG power. Newborns with moderate or high continuous PTE had decreased 19- to 21-Hz (95% CI, 0.034 to 0.327; P < .05) and 22- to 24-Hz (95% CI, 0.022 to 0.316; P < .05) right-central EEG compared with newborns with no PTE. Newborns with moderate or high continuous PTE had significantly decreased 22- to 36-Hz right-central EEG power compared with the quit smoking group (22-24 Hz, 95% CI, 0.001 to 0.579; P < .05; 25-27 Hz, 95% CI, 0.008 to 0.586; P < .05; 28-30 Hz, 95% CI, 0.028 to 0.607; P < .05; 31-33 Hz, 95% CI, 0.038 to 0.617; P < .05; 34-36 Hz, 95% CI, 0.057 to 0.636; P < .05).

CONCLUSIONS AND RELEVANCE

These findings suggest that even low levels of PAE or PTE are associated with changes in offspring brain development.