Research Spotlights November 2020

Research Spotlights November 2020

Differences in EEG brain connectivity during language processing in 3-month-old infants at risk for Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in which there are impairments in social communication skills and behaviors. Typically, ASD is not diagnosed until at least age three, despite the emergence of behavioral symptoms between the ages of one and two. In a recent publication, research supported by the NICHD, NIGMS, Autism Speaks, the Achievement Rewards for College Scientists Foundation, and the University of California Los Angeles investigated if there are differences in brain function and connection in early infancy during language processing that could predict symptoms of autism, including language outcomes.

In the general population 1–2% of children develop ASD. However, up to 20% of children that have a familial risk, defined as having at least one older sibling with ASD, meet criteria for ASD. Previous research has shown that language development is a shared affected domain among many children with ASD and other neurodevelopmental disabilities. Studying the neural networks underlying language processing in early infancy may help to determine the exact timing and mechanisms underlying atypical developmental trajectories and potentially identify early neural markers of ASD and language delay.

For this study, the researchers used a prospective longitudinal infant-sibling study design to study children from early infancy prior to exhibiting any overt behavioral symptoms. Infants in this study were tested at 3 months of age for language processing while brain activity was recorded through electroencephalography (EEG). Language processing was measured through an auditory statistical learning (ASL) paradigm, also known as “word segmentation.” The ability to use ASL has been documented in infants from newborn to one year of age and is considered essential to learning language. The EEG ASL paradigm consisted of infants being passively exposed to a continuous stream of concatenated syllables that consisted of four different trisyllabic pseudo-words (“pabiku”, “daropi”, “tibudo, “golatu”) presented in a continuous speech stream that lasted approximately 2 and a half minutes. A total of 74 participants (40 with familial risk, 34 at low risk) completed the EEG ASL task at 3 months to quantify levels of putative language networks.

Brain region connectivity was measured in the form of phase coherence in the theta (4–6 Hz) and alpha (6–12 Hz) frequency bands. Phase coherence is a measure of synchronization between two signals of the same frequency, and it quantifies the extent to which the two frequencies share a constant oscillating frequency and phase difference. Neuronal sources share information by oscillating with high phase coherence.

Behavioral measures were later assessed in the same infants at age 18-months. Developmental abilities and language skills were also evaluated using the Mullen Scales of Early Learning test and the MacArthur Communicative Development Inventory Words and Gestures checklist (n=54). Infants were divided into two groups based on their ASD symptoms at 18 months which were assessed using the Autism Diagnostic Observation Scale Toddler Module, ASD-concern (n = 14) and No-ASD-concern (n = 49).

Across both risk groups, alpha phase coherence at 3 months, measured using EEG testing, was associated with greater word production at 18 months of age, and infants that had the highest phase coherence at 3-months did not develop ASD symptoms by 18-months of age. At age 3 months, the researchers also identified a trend of reduced left fronto‐central phase coherence in both theta and alpha frequency bands in infants during ASL testing who later showed ASD symptoms at 18 months.

In summary, this study revealed differences in functional connectivity during language processing that could be detected as early as 3 months of age. These results indicate the potential utility of these EEG analytic methods to identify early differences in brain connectivity that may underlie neurodevelopmental impairments in infants at risk for ASD. Measurement of these brain differences before the emergence of behavioral or clinical signs of atypical development may help to improve risk stratification. In addition, these brain measurements may help identify infants that could benefit from increased monitoring or early interventions to improve overall developmental outcomes. There are several limitations of this study, such as small sample size and unbalanced sex ratio (more males than females), which will require future studies to replicate these findings.

Citation:
Tran XA, McDonald N, Dickinson A, Scheffler A, Frohlich J, Marin A, Kure Liu C, Nosco E, Şentürk D, Dapretto M, Spurling Jeste S. 2020. Functional connectivity during language processing in 3-month-old infants at familial risk for autism spectrum disorder. Eur J Neurosci. doi: 10.1111/ejn.15005. Epub ahead of print. PMID: 33043498.

Violence exposure in childhood impacts brain network connectivity into adolescence

Adverse experiences in childhood can have long-term consequences on physical and mental health that continue to persist into adulthood. Present hypotheses suggest that these experiences induce lifelong changes by impacting neural mechanisms in the brain. Different adverse environments, such as violence exposure and social deprivation, have distinct neural correlates in the brain related to emotion, fear, and reward processing. It is unknown the extent to which adverse environments impact brain function, including connectivity of different brain regions which is characterized by total number of connections with any other brain region (density) and number of connections with another specific brain region (node degree). A recent study supported by the NIMH, NICHD, NCRR, the Doris Duke Foundation, and the Jacobs Foundation sought to determine if violence exposure and social deprivation during childhood are associated with long-lasting brain network connectivity into adolescence.

This study performed an observational, population-based longitudinal cohort study conducted predominantly with understudied, underserved African American adolescents to determine whether environmental data collected throughout childhood correlated with neuroimaging data collected during adolescence. Study participants were recruited from an established population-based cohort of children. At three, five, and nine years of age, levels of violence exposure and social deprivation were established by reports from the child’s primary caregiver. Violence exposure was defined as physical or emotional abuse directed at the child, caretaker, or other community members. Social deprivation was defined by emotional or physical neglect to the child, lack of romantic partner support for the caretaker, or lack of neighborhood cohesion.

During adolescence, participants (n=175, 56% girls, 73% racial/ethnic minorities, mean age at enrollment = 15.88 years, from Detroit, Michigan; Toledo, Ohio; or Chicago, Illinois) underwent magnetic resonance imaging (MRI) to obtain resting state functional connectivity (rsFC) of two brain neural networks: the salience network, which is a task-positive network that identifies/integrates salient input and incudes the anterior insula brain region, and the default mode network, which is a task-negative network that is linked to internal thought, memory, and social-cognitive processes and includes the inferior parietal lobe brain region. Due to the variability in rsFC to environmental stress, this study aimed to capture individual patterns in brain circuitry and subdivided participants into groups based on neural connectivity patterns between the brain’s salience network and default mode network.

Adolescents exposed to violence during childhood were 3.06 times more likely to demonstrate high heterogeneity (few shared connections between other participants). Adolescents exposed to violence during childhood also demonstrated reduced density (sparsity) within the salience network of the brain but not within the default mode network of the brain. In addition, childhood violence exposure was related to reduced connections between the salience network and the default mode network, which was likely driven by the reduced node degree for the right insula (a region within the brain’s salience network) and left interior parietal lobule (a region within the brain’s default mode network). These patterns were specific to violence exposure as individuals who suffered social deprivation without violence exposure did not show these features. In addition, race, sex, pubertal development, current life stress, or maternal marital status or education level at the time of the participant’s birth could not account for the differences in neural circuitry.

This study provides a unique analysis of an understudied and underserved population and suggests that childhood violence exposure, but not social deprivation, is associated with patterns in neural circuitry that lasts until adolescence, and likely beyond. The heterogeneity of neural network patterns in participants suggests that childhood violence exposure may lead to person-specific alterations in neural circuity associated with salience detection, attention, and social-cognitive processes. However, since the MRI was only performed once, it is unknown whether connectivity patterns reflect stable or changing neural features and whether these neural differences predated exposure to adversity. Based on these findings, neurobiological research investigating adverse childhood experiences should continue to consider individual differences in response to stress.

In summary, this study finds that childhood violence exposure, but not social deprivation, was associated with neural network sparsity and individual differences in adolescent brain regions involved in salience detection and higher-level cognitive processes. These findings have implications for understanding how dimensions of adversity affect brain development, which may inform future interventions for childhood adversity.

Citation:
Goetschius LG, Hein TC, McLanahan SS, Brooks-Gunn J, McLoyd VC, Dotterer HL, Lopez-Duran N, Mitchell C, Hyde LW, Monk CS, Beltz AM. 2020. Association of Childhood Violence Exposure with Adolescent Neural Network Density. JAMA Netw Open. doi: 10.1001/jamanetworkopen.2020.17850.

The higher the hypothetical risk of disease, the more willing Americans are to get vaccinated

During the current COVID-19 pandemic, many experts are asking the question about why Americans choose to (or choose against) using vaccines? Research sponsored by the NIGMS aimed to address this question. Vaccine propensity is defined as a change in the willingness to vaccinate with a change in perceived risk of infection—holding fixed other considerations such as vaccine confidence and convenience. The purpose of this study was to better understand how risk perception can influence vaccine willingness.

The authors used an online survey instrument that presents seven vaccine-preventable “new” diseases to a sample of 2,411 Americans in 2018. The survey had three major components: First, they collected information regarding the locations where participants live and visit. The survey was designed to match survey respondents on five major dimensions: age, sex, income, race, and census region. Second, participants were given seven hypothetical disease outbreaks and asked how they would respond. Third, they collected sociodemographic information - including race, age, sex, income, education, population size of a respondent’s hometown, population sizes of all cities commuted to during a typical week, number of children, age of youngest child (if applicable), political ideology, religious affiliation, religiosity (importance of religion and frequency of attending religious services), and the self-reported health of the respondent. Descriptive statistics of the sample population were a mean age of 43.80 years, 47% male and 53% female, 38.5% with a college degree, and 24% nonwhite.

Consistent with the literature, the authors found that the risk of mortality invoked a larger proportion of individuals willing to vaccinate than mere morbidity (P = 0.0002). Specifically, older populations are more willing to vaccinate than younger ones (P<0.0001), as were individuals in the highest income bracket (>$90,000/year) as compared to all others (P = 0.0001). Men were also more willing to get vaccinated than women (P = 0.0011). The proportion of individuals willing to vaccinate was related to both to political ideology and the level of perceived risk (P = 0.004).

Furthermore, authors found an overall change of at least 30% in the proportion willing to vaccinate as risk of infection increases. This finding was conditional on both the perceived risk and the impact of the infection proposed. When considering morbidity, for example, the percentage willing to vaccinate went from 47.6% at zero local cases of disease to 87.1% at 100 local cases. On the other hand, in terms of mortality the proportion went from 52.6% at zero local cases of disease to 91.6% at 100 local cases.

Political orientation was related to willingness to vaccinate. They found that those that identified as very conservative make up a larger fraction of the vaccine-hesitant relative to those identifying as liberal. However, across risk scenarios, there was a change in vaccine propensity regardless of political orientation. For instance, although liberals as compared to conservatives will vaccinate when there are zero local cases, increases in infection risk were associated with increased vaccine propensity for both groups. However, those who were “middle of the road” ideologically were the least likely to be willing to vaccinate but, as risk increases to the highest level, they are among the highest in willingness to seek vaccination. This is consistent with findings that suggest that people with stronger or more extreme ideological views are less responsive to changes in the world than those with more moderate views. In brief, the more entrenched or strong a person’s ideological leaning, the more steadfast they will be in their position to vaccinate or not in response to changes in risk.

This study does have some limitations including that it does not consider how other factors (such as social influence, imperfect information, etc.) interact with local case counts in people’s vaccine decision-making, and it cannot discern vaccine propensity between different degrees of severity in morbidity or mortality. Additionally, since the sample was internet-based, it does not capture the part of the US that is not online, nor does it directly address the question of vaccine fear/trust on vaccine propensity. In conclusion, insights from this study into how perceived risk influences an individual's willingness to vaccinate could aid efforts to increase vaccination and may also help improve predictive models of disease spread that incorporate individual feedback on an individual’s vaccination decisions.

Citation:
Baumgaertner B, Ridenhour BJ, Justwan F, Carlisle JE, Miller CR. 2020. Risk of disease and willingness to vaccinate in the United States: A population-based survey. PLoS Med.17(10) :e1003354. doi: 10.1371/journal.pmed.1003354.

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