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. Author manuscript; available in PMC: 2025 Apr 1.
Published in final edited form as: Dev Psychobiol. 2024 Apr;66(3):e22476. doi: 10.1002/dev.22476

Examining the Impact of Prenatal Maternal Internalizing Symptoms and Socioeconomic Status on Children’s Frontal Alpha Asymmetry and Psychopathology

Alexis Hernandez 1,*, Ayesha Sania 2, Maureen E Bowers 3, Stephanie C Leach 4, Marco McSweeney 3, Lydia Yoder 3, William Fifer 2, Amy J Elliott 5, Lauren Shuffrey 2, Virginia Rauh 6, Deana Around Him 7, Nathan A Fox 3, Santiago Morales 1
PMCID: PMC10936576  NIHMSID: NIHMS1967752  PMID: 38433442

Abstract

Prenatal maternal internalizing psychopathology (depression and anxiety) and socioeconomic status (SES) have been independently associated with higher risk for internalizing and externalizing problems in children. However, the pathways behind these associations are not well understood. Numerous studies have linked greater right frontal alpha asymmetry to internalizing problems; however, findings have been mixed. Several studies have also linked maternal internalizing psychopathology to children’s frontal alpha asymmetry. Additionally, emerging studies have linked SES to children’s frontal alpha asymmetry. To date, only a limited number of studies have examined these associations within a longitudinal design, and the majority have utilized relatively small samples. The current preregistered study utilizes data from a large prospective study of young children (N=415; Meanage=7.27 years; Rangeage=5–11 years) to examine the association between prenatal maternal internalizing symptoms, children’s frontal alpha asymmetry, and behavior problems. Prenatal maternal internalizing symptoms did not predict children’s frontal alpha asymmetry and there was no association between frontal alpha asymmetry and behavior problems. However, mothers’ internalizing symptoms during pregnancy predicted children’s internalizing and externalizing outcomes. Non-preregistered analyses showed that lower prenatal maternal SES predicted greater child right frontal alpha asymmetry and internalizing problems. Additional non-preregistered analyses did not find evidence for frontal alpha asymmetry as a moderator of the relation between prenatal maternal internalizing psychopathology and SES to children’s behavior problems. Future research should examine the impact of SES on children’s frontal alpha asymmetry in high-risk samples.

Current Study

Prenatal maternal internalizing problems, including prenatal anxiety and depression, are known to impact children’s neural and behavioral development (see reviews by Monk et al., 2019; Van den Bergh et al., 2020). For instance, children of mothers with higher anxiety and depressive symptoms during pregnancy displayed higher risk for internalizing and externalizing problems (e.g., Cents et al., 2013; Leis et al., 2014; O’Donnell et al., 2014; Pickles et al., 2016). In addition to prenatal maternal psychopathology being an important determinant of children’s outcomes, low socioeconomic status (SES) has also been implicated as a factor for increased risk for children’s behavioral problems (Bradley & Carwyn, 2002; Monk et al., 2019). This may be due to low resources and increased stress for both the child and parent. However, limited studies have examined the impact of prenatal SES on children’s internalizing and externalizing problems (e.g., Ahmad et al., 2022; Spann et al., 2020). Given these associations between prenatal maternal psychopathology and early SES in relation to children’s behavioral problems, it is important to understand potential developmental pathways underlying the relations between prenatal maternal internalizing psychopathology symptoms, SES, and psychopathology risk in children. A possible neural mechanism that may act as a mediator in this relation is frontal alpha asymmetry, which has been associated with psychopathology in children and adults (Feng et al., 2012). In addition, maternal internalizing psychopathology and SES have also been associated in studies examining the development of frontal alpha asymmetry in children; however, this research has been mostly limited to concurrent associations and relatively small samples that may not be powered to detect potential associations (e.g., Gatzke-Kopp et al., 2014; Lopez-Duran et al., 2012; Mulligan et al., 2022; Peltola et al., 2014). The current preregistered study aimed to address these gaps in the literature by examining the association between prenatal maternal internalizing symptoms, children’s frontal alpha asymmetry, and internalizing and externalizing outcomes in a large sample of children. Moreover, in non-preregistered analyses, we also examined associations with prenatal SES, as well as the potential role of alpha asymmetry as a moderator of the longitudinal associations between prenatal risk factors (maternal psychopathology and SES) and child behavior problems.

Elevated maternal psychopathology symptoms have been shown to increase the risk for internalizing and externalizing problems in children. Dawson et al. (2003) found that preschool children who had mothers with a history of depression had higher levels of internalizing and externalizing problems compared to children of mothers without a history of depression. Similarly, a review paper noted that children of mothers with heightened levels of anxiety and depression during the prenatal stage of pregnancy had increased risks for psychopathology in distinct domains such as anxiety, depression, and hyperactivity (Van den Bergh et al., 2020). Research has examined numerous factors that may account for the relations between maternal psychopathology and children’s internalizing and externalizing problems (Alink et al. 2009; Frigoletto et al., 2022). Research has indicated that risk factors for internalizing and externalizing problems in children include maternal psychopathology (which can disrupt typical mother-child interactions), an adverse prenatal environment (e.g., neuroendocrine abnormalities), and an increased genetic predisposition to internalizing psychopathology (Goodman & Gotlib, 1999).

One possible mechanism is that prenatal risk factors (maternal psychopathology and SES) impact children’s approach and withdrawal tendencies (Peltola et al., 2014; Thibodeau et al., 2006). Normative variations in approach and withdrawal motivation have been linked to one’s own processing of affective emotions and behaviors, serving an important affective function (Davidson, 1999; Davidson & Fox, 1982; Peltola et al., 2014). More specifically, approach motivation is linked to the processing of positive stimuli and anger whereas withdrawal motivation is linked to the processing of negative internalizing affective emotions and behaviors like sadness and anxiety (Davidson, 1999; Peltola et al., 2014). Studies have examined the processing of affective emotions and behaviors, that is dependent upon approach and withdrawal motivation, using behavioral observations and self-reports (e.g., Alink et al., 2009). These approach and withdrawal tendencies are often considered on a continuum (Fox, 1991), which at the extreme may be linked to risk for psychopathology. Specifically, approach motivation has been linked to externalizing problems, whereas withdrawal motivation has been linked to internalizing problems (Peltola et al., 2014). Even so, behavioral observations and self-reports may not fully capture the underlying mechanisms related to these tendencies. Moreover, approach and withdrawal tendencies are theorized to be associated with children’s frontal brain activity (see review by Harmon-Jones & Gable, 2018). Hence, exploring a neurobiological indicator such as frontal alpha asymmetry could offer unique insight into these tendencies, enabling a comprehensive examination of the underlying mechanisms of approach and withdrawal motivation for children’s internalizing and externalizing behaviors. One neurobiological risk factor, frontal alpha asymmetry, may act as a possible mechanism linking early risk factors to children’s negative emotions and behaviors (Coan & Allen, 2004).

Frontal alpha asymmetry is defined as differences of cortical activation in one hemisphere in relation to the other (Davidson & Fox, 1982; Marshall et al., 2002). Alpha activity has been inversely related to brain activity such that higher alpha activity is linked to reduced brain activation (Harmon-Jones & Gable, 2018). Reduced frontal alpha asymmetry (i.e., less left alpha signal relative to right) or “right frontal” is linked to withdrawal motivation and the processing of negative affect. In contrast, greater frontal alpha asymmetry (i.e., more left alpha signal relative to right) or “left frontal” is linked to approach motivation and the processing of positive affect (Davidson & Fox, 1982; McLaughlin et al., 2011; McManis et al., 2002; Peltola et al., 2014). Moreover, frontal cortical activation is theorized as an underlying basis for processing affective and emotional information (Davidson, 1992; Davidson & Fox, 1982). For example, a study by McManis et al. (2001) examined reactivity and fearfulness (i.e., withdrawal tendencies) in children and found children who were more fearful and reactive to unfamiliar events showed greater right frontal activation than children who were less fearful and reactive. In contrast, research has found that greater left frontal activation is related to approach motivational tendencies (e.g., self-reports of anger; Harmon-Jones & Allen, 1998). Given the connection of frontal cortical activation in relation to the processing of emotions, numerous studies have examined frontal alpha asymmetry in relation to psychopathology risk. Greater right frontal alpha asymmetry has been linked to higher internalizing problems such as depression risk, whereas greater left frontal alpha asymmetry has been linked, although inconsistently,to externalizing problems in children (e.g., Feng et al., 2012; Gatzke-Kopp et al., 2014; Harmon-Jones & Allen, 1998; Lopez-Duran et al., 2012; Mulligan et al., 2022; van de Ven et al., 2020). However, a meta-analysis that examined the relation between children’s frontal alpha asymmetry and children’s negative outcomes found non-significant effect sizes for overall internalizing (d = .19) and externalizing (d = .04) disorders (Peltola et al., 2014). It is important to note that most of the studies included in the meta-analysis used relatively small samples (Mean= 64.55; range: 24–135 children); reducing power and increasing the likelihood of false positives. Thus, more research with large samples is needed to better understand the relation between frontal alpha asymmetry and internalizing and externalizing disorders in children.

Studies have also examined maternal characteristics (e.g., psychopathology, SES) as predictors for children’s frontal alpha asymmetry. Numerous studies have found longitudinal associations between early maternal psychopathology and children’s frontal alpha asymmetry (e.g., Forbes et al., 2008; Lopez-Duran et al., 2012; Peltola et al., 2014). Goldstein et al. (2016) found that children of mothers with depression showed greater right frontal alpha asymmetry from three to six years of age, compared to children of mothers without depression. Additionally, studies have also examined prenatal maternal psychopathology symptoms in relation to infant’s frontal alpha asymmetry (Diego et al., 2004; Diego et al., 2006; Field et al., 2004; Field & Diego, 2009). A study by Field et al. (2004) examining prenatal maternal psychopathology symptoms (e.g., depression, anxiety) and infants’ frontal alpha asymmetry found that infants of mothers with higher depressive or anxiety symptoms during pregnancy showed right frontal alpha asymmetry. Furthermore, a recent study by Hill et al. (2020) examined the intergenerational transmission of frontal alpha asymmetry among mother-infant dyads and found moderate correlations between mothers’ and infants’ frontal alpha asymmetry, indicating narrow-sense heritability. This study also found that infants of mothers with current depressive symptoms showed greater right frontal alpha asymmetry (Hill et al., 2020). However, results have been inconsistent (e.g., Bruder et al., 2005; Forbes et al., 2006). A study by Bruder et al. (2005) examined parent’s lifetime history of depression as a predictor for frontal alpha asymmetry in their offspring (i.e., children and adults; age range: 8–47 years) and found no differences between offspring of one or two parents with a history of depression compared to offspring of parents without a history of depression. Even so, most studies examining this relation have been conducted using relatively small sample sizes.

In addition, early SES may play a role in frontal alpha asymmetry; although, only a few studies have examined this relation (Gatzke-Kopp et al., 2014; Mulligan et al., 2022). A study by Gatzke-Kopp et al. (2014) found that increased right frontal alpha asymmetry was associated with increased internalizing symptoms in kindergarten aged children from a low SES background. However, to our knowledge, no study to date has examined early SES as a predictor for later frontal alpha asymmetry in children. Therefore, research is still needed to examine the relative contribution of maternal internalizing psychopathology symptoms and SES on frontal alpha asymmetry in a large, longitudinal sample of children. Given that frontal alpha asymmetry has been linked to both early risk factors (maternal psychopathology and SES) and childhood outcomes such as internalizing problems, we wanted to examine if frontal alpha asymmetry could serve a mediator of the relation between prenatal risk factors and children’s internalizing problems.

In addition to functioning as a potential mediator, frontal alpha asymmetry may also serve as a moderator in the relation between early risk factors and emotional and behavioral outcomes (Reznik & Allen, 2017). For example, several studies have examined how frontal alpha asymmetry may moderate the relation between maternal internalizing psychopathology, SES, and children’s internalizing symptoms (e.g., Forbes et al., 2008; Tomarken et al., 2004). For example, a study by Forbes et al. (2008) found that children with greater right frontal alpha asymmetry who had mothers with depression showed greater depressive symptoms. Thus, frontal alpha asymmetry may also act as a possible moderator for early maternal psychopathology and SES in relation to children’s internalizing and externalizing symptoms. However, results have been inconsistent (see review by Reznik & Allen, 2017); thus, the current study aims to explore (non-preregistered) frontal alpha asymmetry as a moderator for the relation between early maternal internalizing symptoms and SES and children’s internalizing and externalizing outcomes.

The goal of the study was to examine if the longitudinal relations between prenatal maternal characteristics including internalizing symptoms (e.g., depression, anxiety) and SES and children’s internalizing and externalizing problems were mediated or moderated by children’s frontal alpha asymmetry. Because internalizing and externalizing problems tend to be correlated between individuals (Morales et al., 2020), we decided to examine relations to both internalizing and externalizing problems even if externalizing problems have been inconsistently linked to left frontal alpha asymmetry (Peltola et al., 2014). This allowed us to test the specificity of the relations with internalizing versus externalizing problems. Specifically, we had four aims. The first aim was to examine the associations of prenatal maternal internalizing symptoms and SES, with children’s internalizing and externalizing problems, as well as frontal alpha asymmetry. Specifically, higher prenatal maternal internalizing symptoms and low SES would be associated with higher internalizing (H1a) and externalizing (H1b) problems in children. These hypotheses are in line with previous research finding of associations between maternal internalizing psychopathology, SES, and children’s internalizing and externalizing problems (Dawson et al., 2003; Monk et al., 2019; Van den Bergh et al., 2020). Lastly, we hypothesized that higher prenatal maternal internalizing symptoms and low SES would be associated with greater right frontal alpha asymmetry (i.e., reduced left alpha signal; H1c; Forbes et al., 2008; Gatzke-Kopp et al., 2014; Goldstein et al., 2016; Mulligan et al., 2022)

The second aim was to examine the associations between right frontal alpha asymmetry in children and their internalizing and externalizing problems. We hypothesized that right frontal alpha asymmetry (i.e., reduced left alpha signal) in children would be associated with higher internalizing problems (H2a). In addition, we did not expect a significant association between right frontal alpha asymmetry and externalizing problems (H2b). Previous research has found a relation between right frontal alpha asymmetry and internalizing problems in children (e.g., Lopez-Duran et al., 2012; Mulligan et al., 2022). Past literature examining the relations between right frontal alpha asymmetry and externalizing problems have not found a link between these variables (see review by Thibodeau et al., 2006). This finding suggests that the mechanisms of right frontal alpha asymmetry are more closely linked to withdrawal and internalizing processes rather than externalizing processes (Davidson & Fox, 1982).

The third aim was to examine if right frontal alpha asymmetry in children mediated or moderated the associations between prenatal maternal psychopathology, SES, and children’s internalizing and externalizing problems. We hypothesized that higher prenatal maternal internalizing symptoms and low SES would be associated with right alpha asymmetry (i.e., reduced left alpha signal), which would be concurrently associated with higher internalizing problems, supporting a significant mediation (H3a). We did not expect to observe a significant mediation in predicting child externalizing problems because the relation between alpha asymmetry and externalizing has not been consistently found (H3b; Ashman et al., 2008; Feng et al., 2012; Peltola et al., 2014). To note, the reason for analyzing the non-significant hypothesis was to examine the specificity of this mediation model, as it may only be evident with internalizing problems, rather than overall psychopathology. Therefore, we hypothesized a mediation between these variables for child internalizing problems, while accounting for externalizing problems.

Lastly, in an exploratory analysis, we examined if frontal alpha asymmetry moderated the relation between prenatal maternal internalizing symptoms and SES in relation to children’s internalizing problems. We hypothesized that children with greater right frontal alpha asymmetry (i.e., reduced left alpha signal) would show a stronger relation between prenatal risk factors (maternal internalizing and SES) and their internalizing problem scores (H4a; Forbes et al., 2006; Forbes et al., 2008). We did not expect to observe a significant moderation predicting child externalizing problems (H4b).

We preregistered our analytic plan and hypothesized that prenatal maternal internalizing symptoms will predict children’s frontal alpha asymmetry as well as internalizing and externalizing problems (https://osf.io/v2n6a). In addition, our analytic plan included examining SES as a covariate. Given the significant findings for SES, we chose to examine SES in a more in-depth manner, as another predictor of children’s brain activity and behavioral outcomes. The inclusion of SES in the hypotheses stated above (H1a, H1b, H3a, H3b) as well as the moderation analyses (H4a, H4b) were not preregistered.

Methods

Participants

Participants were originally enrolled in the Prenatal Alcohol in SIDS and Stillbirth (PASS) study, with the study design and data collection procedures detailed by Dukes and colleagues (2014). A subset of these subjects was then reenrolled as part of the Environmental influences on Child Health Outcomes (ECHO) study in South Dakota (Blaisdell et al., 2021). As part of the larger ECHO study, children were invited to participate in an EEG assessment by age. EEG collection was conducted in Sioux Falls and Rapid City (South Dakota) by the Avera Center for Pediatric and Community Research (CPCR). As part of the ECHO study, children participated in an EEG assessment at 5-, 7-, 9-, 11-years of age (N=415).

Participants were primarily White (79.76%), followed by American Indian (12.77%), and other (7.47%; see Table 1). Children’s age distribution was as follows: 5-year-old participants (n=126), 7-year-old participants (n=164), 9-year-old participants (n=69), and 11-year-old participants (n=56). Of the 415 participants with EEG data, 35.67% were missing information pertaining to internalizing and externalizing problem scores. Next, monthly income varied, but more than half of the mothers noted their income to be $2,000 or higher (25.30% were missing monthly income information). Mothers’ education levels varied, but the majority completed college (23.86% were missing education information). In addition, 66.88% of mothers reported having commercial health insurance (24.33% were missing health insurance information). Lastly, maternal age varied (Mage=28.4 years, SDage=4.7, age range= 16–43 years).

Table 1.

Demographic Characteristics of Children (n = 415) and Mothers (n= 415)

Child Characteristics n % Maternal Characteristics n %
Sex Race
 Female 221 53.25  White 343 82.65
 Male 194 46.75  American Indian 54 13.01
Race  Other 18 4.34
 White 331 79.76 Ethnicity
 American Indian 53 12.77  Non-Hispanic Latinx 401 96.63
 Other 31 7.47  Hispanic Latinx 14 3.37
Ethnicity Health Insurance
 Non-Hispanic Latinx 396 95.42  Commercial 210 50.60
 Hispanic Latinx 19 4.58  Public Assistance 104 25.06
 Missing 101 24.34
Married
 Yes 299 72.05
 No 17 4.10
 Missing 99 23.85
Education
 Some Primary School 1 0.24
 Completed Primary School 3 0.72
 Some High School 15 3.61
 Completed High School 24 5.78
 Some College 88 21.20
 Completed College 127 30.60
 Postgraduate 58 13.98
 Missing 99 23.86
Monthly Income
 less than $500 7 1.69
 $501 to $1000 19 4.58
 $1,001 to $2,000 53 12.77
 $2,001 to $3,000 64 15.42
 $3,001 to $4,000 58 13.97
 $4,001 to $5,000 50 12.05
 more than $5,000 59 14.22
 Missing 105 25.30
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Note: Children’s characteristics were collected during infancy. Maternal characteristics were measured during the prenatal period.

Prior to data collection, informed consent and informed assent (when of age) were obtained from both the primary caregiver and the child. Mothers filled out questionnaires pertaining to internalizing symptoms and provided demographic information during pregnancy. During the first EEG laboratory visit at either 5, 7, 9, or 11 years of age, mothers filled out questions assessing their children’s behavioral problems. During the laboratory visit, children sat about 70 centimeters in front of a computer screen while wearing an EEG net on their head and completed a 3-minute baseline recording as part of the EEG task, altering between eyes open (EO) and eyes closed (EC) every 30 seconds. Instructions for the task were presented in E-Prime 2.0.10 (Psychology Software Tools, Pittsburgh, PA). Upon completion of the laboratory visit, families received compensation and children were given a small gift (e.g., toy). Both data collection sites had trained researchers utilizing the exact same protocols and EEG equipment. The PASS and ECHO studies have been approved by Avera’s Institutional Review Board.

EEG Data Acquisition

EEG was collected using a 64-channel HydroCel Geodesic Sensor Net via EGI software at 500 Hz (Net Station Version 5.4; Electrical Geodesics, Inc., Eugene, OR). To explore additional psychophysiological measures like heart rate, four face channels (61–64) were excluded from the nets. Impedance values were checked prior to data collection for all the EEG channels to ensure they were below 50kΩ.

EEG Preprocessing

For EEG preprocessing, EEGLAB toolbox (Delorme & Makeig, 2004) was used with custom MATLAB scripts (The MathWorks, Natick, MA) via procedures from the Maryland Analysis of Developmental EEG (MADE) pipeline (Debnath et al., 2020, https://github.com/ChildDevLab/MADE-EEG-preprocessing-pipeline). The preprocessing methods have been described in detail in previous publications (Morales et al., 2022). The continuous EEG data underwent high-pass offline filtering at 0.3 Hz and low-pass filtering at 49 Hz. Additionally, bad channels within the data set were identified and removed via EEGLAB plug-in FASTER (Nolan et al., 2010). For the removal of ocular artifacts, an independent component analysis (ICA) was performed on a copied dataset at 1 second epochs. Moreover, noisy segments within the data (e.g., muscle movement) were rejected using a combined voltage threshold of +/−1000 μV and spectral threshold (range −100 dB to +30 dB) within the 20–40 Hz frequency band. If this rejection process identified an artifact in more than 20% epochs for a given channel, the channel was then removed from both the ICA copied dataset and original dataset.

Using this dataset, ICA decomposition was performed, and ICA weights were then copied back to the original continuous dataset (Debener et al., 2010). Using the Adjusted-ADJUST algorithm, artificial ICs were removed from the original data set (Leach et al., 2020; Mognon et al., 2011). Next, EEG data was split into 2 second epochs and went through two additional steps of artifact rejection. The first step was to identify any residual ocular activity that was not removed through ICA; epochs in which ocular channels (1, 5, 10, and 17) voltages that exceeded ±150 μV were rejected. The second step interpolated channels where epochs from voltages from non-ocular channels voltages surpassed ±125 μV. If more than 10% of the channels (not considering globally rejected channels) exceeded ±125 μV, then the epoch was rejected instead. If there were any missing channels, then they were interpolated using the spherical spline method (Perrin et al., 1989). Lastly, the data were referenced to the average reference. Power spectra were computed from the artifact-free epochs using Welch’s method from 1 to 49 Hz with a hamming window in EEGLAB with a frequency resolution of 0.5 Hz.

Measures

Frontal Alpha Asymmetry.

Children’s frontal alpha asymmetry was measured using EEG data during Baseline (i.e., resting state) recording. We estimated absolute alpha power as an average of alpha power (7–13 Hz). The alpha power was then averaged by the electrode clusters corresponding to F3 and F4 locations (F3: 9, 11, 12, 13, 14; F4: 2, 3, 57, 59, 60). Analyses were performed for the EO condition. Lastly, asymmetry scores were computed using differences between transformed power scores within the mid-frontal region (lnF4–lnF3; Vincent et al., 2021). Positive scores indicated greater left frontal alpha asymmetry whereas negative scores indicated greater right frontal alpha asymmetry. We estimated the internal consistency using split-half reliability with a subsampling approach described in Morales et al. (2022). The internal consistency of frontal alpha asymmetry in the present study was high (rsb=0.97), which is similar to other studies (e.g., Groppe et al., 2009; Hill et al., 2020; Towers & Allen, 2009). Finally, in an exploratory analysis, we utilized a novel way of characterizing the power spectrum by characterizing alpha peaks at the individual level using specparam (Donoghue et al., 2021).

Maternal Depression and Anxiety Symptoms.

Maternal depressive symptoms were assessed during pregnancy using the Edinburgh Postnatal Depression Scale (EPDS; Cox et al., 1987). This 10-item self-report questionnaire assessed the mother’s thoughts and emotions within the past seven days for symptoms of depression. Each item had four multiple choice answers that varied from negative to positive responses. Sample items included, “I have felt sad or miserable” and “The thought of harming myself has occurred to me.” Individual item responses were averaged for a possible total score that could range from 0–30, whereby higher total scores indicate increasing levels of depressive symptoms. The EPDS is a valid and reliable measure of maternal prenatal depressive symptoms (Bergink et al., 2011). For the current study, the Cronbach’s alpha for maternal depressive symptoms was 0.82, showing high internal consistency.

Maternal anxiety symptoms were assessed using the Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983). This 40-item self-report questionnaire assesses an individual’s thoughts and emotions that coincide with either state (20 items) or trait (20 items) anxiety symptoms. The format for each item is a 4-point Likert scale ranging from 1 meaning “Not at all” to 4 meaning “Very much so.” The current study focused on both state and trait anxiety items. Sample items that were assessed for state anxiety included, “I feel jittery” and “I am tense”. Sample items that assessed trait anxiety included, “I feel like a failure” and “I feel inadequate.” Individual item responses were first re-scaled with an item level range of 0–3 and then averaged for a total score for either state or trait anxiety symptoms that could range from 0–60 (for either state or trait anxiety symptoms), whereby higher total scores indicate increasing levels of state or trait anxiety symptoms. The STAI is a valid measure of state and trait anxiety symptoms during pregnancy (Gunning et al., 2010). The Cronbach’s alpha for maternal state anxiety symptoms was 0.88 and for trait anxiety symptoms it was 0.90, showing high internal consistency.

Maternal Socioeconomic Status.

Maternal socioeconomic status (SES) was assessed during pregnancy using a self-reported demographic questionnaire. Mothers reported their maternal education level, monthly gross income, and type of health insurance. Highest level of education was reported using categories ranging from 1 (some primary school) to 7 (postgraduate). Mothers reported their monthly gross income using a range of income options from 1(<250) to 7 (>5,000). Lastly, type of health insurance was reported using two different options (0 = Commercial Health Insurance/Commercial HMO and 1 = Public Assistance). These items (maternal education level, monthly gross income, and type of health insurance) were combined as a factor variable for overall SES within structural equation models.

Child Internalizing and Externalizing Symptoms.

Children’s internalizing and externalizing psychopathologies were assessed using the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997). Mothers filled out a 25-item questionnaire pertaining to their child’s thoughts, behaviors, and peer relations over the last six months. The format for each item is a 3-point scale ranging from “Not true,” “Somewhat true,” to “Certainly true.” The SDQ is composed of subscales that include emotional, conduct, hyperactivity, peer problems, and prosocial. The internalizing scale utilizes the emotional and peer problems subscales, whereas the externalizing scale utilizes the hyperactivity and conduct subscales.

The current study focused on the internalizing (10 items) and externalizing (10 items) subscales. Sample items for internalizing items include “Many fears, easily scared” and “Picked on or bullied by other youth.” Sample items for externalizing items include “often loses temper” and “Easily distracted, concentration wanders” (Goodman, 1997). Maternal responses for each of the items were then averaged to create the corresponding subscale scores. High scores indicated increased levels of internalizing and externalizing problems. The SDQ is a valid measure for children’s internalizing and externalizing problems across differing age groups (e.g., 5–11 years of age; Goodman, 2001; Riso et al., 2010; Van Roy et al., 2008). The Cronbach’s alphas for the internalizing and externalizing problem items were 0.67 and 0.84, respectively.

Statistical Analyses

To test aim one, separate path analyses were conducted for each component of prenatal maternal internalizing symptoms (H1a; i.e., predictor, maternal depression and anxiety) as well as overall SES (H1b; i.e., predictor, monthly gross income, and type of maternal health insurance) to examine their overall relations with child frontal alpha asymmetry, as well as externalizing and internalizing symptoms. To test aim two, another path analysis was used to examine the relations between child frontal alpha asymmetry and internalizing (H2a) and externalizing problems (H2b). To examine aim three, a one path model was run to examine the unique association of each predictor controlling for the other predictors (H3a, H3b, H3c). Given the correlation between variables of maternal internalizing symptoms, the main analysis combined maternal depression and state and trait anxiety into a one factor variable (i.e., prenatal maternal internalizing symptoms). Maternal education level, monthly gross income, and type of maternal health insurance were combined into a one factor variable to measure SES. To examine the fourth aim, a moderation model was tested using a path analysis to examine whether frontal alpha asymmetry moderated the association between maternal internalizing symptoms and SES during pregnancy and children’s internalizing (H4a) and externalizing (H4b) problems. Factor scores from the maternal internalizing and SES factor variables were extracted and used as manifest variables to create interaction terms with the frontal alpha asymmetry scores (see Supplement Table S1 to Table S7). Missing data were handled using full information maximum likelihood (FIML) to account for missingness as well as reduce potential bias in the parameter estimates (Enders & Bandalos, 2001).

Results

Descriptive Results

Tables 1 and 2 show the descriptive statistics for variables of interest for the mother and child participants. Furthermore, table 2 shows the zero-order correlations among the main variables. Maternal prenatal depressive symptoms were positively correlated with maternal prenatal state and trait anxiety symptoms. Mothers’ prenatal depressive, state, and trait anxiety symptoms were longitudinally associated with children’s higher internalizing and externalizing scores. Monthly income was positively correlated with maternal internalizing symptoms and children’s internalizing and externalizing scores (see Table 2). Lastly, children’s internalizing and externalizing scores were positively associated with each other.

Table 2.

Correlation Matrix for Maternal and Child Characteristics of Interest

Variable M SD N Min Max 1 2 3 4 5 6 7 8 9
1. Prenatal Maternal Depression 4.45 3.45 411 0 17 -
2. Family Monthly Income 3156.45 1438.93 310 250 5000 −0.23 -
3. Maternal Education 5.56 1.11 316 1 7 −0.04 0.56 -
4. Health insurance - - 314 - - 0.16 −0.55 −0.58 -
5. Prenatal Maternal Trait Anxiety 29.17 7.51 411 20 63 0.69 −0.23 −0.07 0.19 -
6. Prenatal Maternal State Anxiety 25.76 6.64 411 20 59 0.53 −0.19 −0.04 0.13 0.66 -
7. Child Alpha Asymmetry Score −0.02 0.34 415 −1.13 1.02 0.02 −0.08 −0.15 0.13 0.00 0.00 -
8. Child Externalizing 4.58 3.37 267 0 16 0.21 −0.21 −0.06 0.11 0.21 0.20 0.04 -
9. Child Internalizing 2.88 2.52 267 0 11 0.22 −0.25 −0.12 0.18 0.24 0.19 0.08 0.40 -
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Note: Maternal depression and anxiety scores were measured during the prenatal period, child frontal alpha asymmetry, internalizing, and externalizing problems were measured at 5, 7, 9, or 11 years of age. Health insurance was coded as a categorical variable (0 = commercial health insurance, 1 = public assistance).

We examined if demographic variables (i.e., race, ethnicity, child sex, child age, and maternal age) and maternal substance use (i.e., maternal drinking, smoking, drug use, and opioids) were associated with the study variables. The results showed no significant patterns except for child sex and child age. Therefore, child sex and age were added as covariates to the main path analyses (for results without covariates, see Supplement Table S1 to Table S7).

Main Analyses

The first hypothesis stated that higher prenatal maternal internalizing symptoms and low SES would be associated with higher internalizing (H1a) and externalizing (H1b) problems in children. Additionally, higher prenatal maternal internalizing symptoms and low SES were hypothesized to be associated with right frontal alpha asymmetry in children (H1c). Results from the path models are shown in Table 3 and Figure 1. In support for our hypothesis, prenatal maternal internalizing symptoms were found to be associated with children’s externalizing (β = 0.22, p < 0.001) and internalizing problems (β = 0.22, p < 0.001). Separate analyses showed that similar results were found for each component of maternal internalizing symptoms (depression, state anxiety, trait anxiety) predicting children’s internalizing and externalizing problems (not shown). Moreover, results revealed that prenatal SES was predictive of children’s internalizing (b = −0.59, p = 0.01) problems. In addition, there was a significant negative association between prenatal SES predicting children’s right frontal alpha asymmetry scores (b = −0.17, p = 0.006), such that children whose mothers reported lower SES showed greater right frontal alpha asymmetry. However, not supporting our hypothesis, results indicated prenatal maternal internalizing symptoms did not predict children’s right frontal alpha asymmetry. Similarly, when examining each component of maternal internalizing symptoms separately (depression, state anxiety, trait anxiety), there were no significant relations with children’s frontal alpha asymmetry scores.

Table 3.

Maternal Internalizing Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Predictors/Outcome β b SE z p CI Lower CI Upper
Model 1
Child Absolute Asymmetry
Child Sex −0.05 −0.04 0.03 −1.04 0.30 −0.10 0.03
Child Age 0.02 0.00 0.01 0.34 0.73 −0.01 0.02
Prenatal Maternal Internalizing Symptoms −0.04 −0.01 0.01 −0.74 0.46 −0.02 0.01
Prenatal SES −0.17 −0.07 0.03 −2.73 0.01 −0.12 −0.02
Child Internalizing
Child Sex 0.01 0.04 0.30 0.14 0.89 −0.58 0.62
Child Age −0.04 −0.05 0.08 −0.68 0.50 −0.21 0.10
Prenatal Maternal Internalizing Symptoms 0.22 0.22 0.06 3.25 0.00 0.09 0.35
Child Absolute Asymmetry 0.05 0.37 0.45 0.81 0.42 −0.60 1.28
Prenatal SES −0.20 −0.59 0.24 −2.49 0.01 −1.15 −0.10
Child Externalizing
Child Sex −0.29 −1.92 0.38 −5.05 0.00 −2.70 −1.15
Child Age −0.14 −0.24 0.10 −2.33 0.02 −0.42 −0.04
Prenatal Maternal Internalizing Symptoms 0.22 0.29 0.09 3.31 0.00 0.13 0.47
Child Absolute Asymmetry −0.06 0.08 0.58 0.14 0.89 −1.08 1.20
Prenatal SES −0.16 −0.48 0.30 −1.60 0.11 −1.12 0.10
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Model Fit Statistics: (χ2 = 37.10, df = 32; CFI = 0.99, TLA = 0.994, RMSEA = 0.02)

Note: Maternal Internalizing Symptoms: Prenatal maternal depressive, state anxiety, and trait anxiety symptoms; Children frontal alpha asymmetry: Children’s frontal alpha asymmetry scores at 5, 7, 9, or 11 years of age; Children Internalizing and Externalizing: Children’s internalizing and externalizing scores at 5, 7, 9, or 11 years of age; Maternal SES variable was mean-centered

Figure 1:

Figure 1:

Open in a new tab

Significant Results Examining Relations of Maternal Internalizing Symptoms, SES, Children’s Alpha Asymmetry, Children’s Internalizing Problem Scores

The second hypothesis stated that right frontal alpha asymmetry in children would be associated with higher internalizing problem scores (H2a). Additionally, we did not expect a significant association between children’s right frontal alpha asymmetry and externalizing problems (H2b). Path analyses were conducted to examine the effects of child’s alpha asymmetry on internalizing and externalizing problems. The results revealed non-significant associations between children’s frontal alpha asymmetry and internalizing and externalizing problems (see Table 3 and Figure 1). Children’s right frontal alpha asymmetry was not significantly associated with either internalizing or externalizing problems.

The third hypothesis stated that higher prenatal maternal internalizing symptoms and low SES would be associated with right alpha asymmetry, which would predict higher internalizing problems and support a significant mediation (H3a). We did not expect to observe a significant mediation of the relation between prenatal maternal internalizing symptoms, low SES, and child externalizing problems (H3b). All predictors were examined in one model. Results revealed no significant mediation between prenatal maternal internalizing or externalizing symptoms predicting children’s frontal alpha asymmetry and internalizing problems (see Table 3 and Figure 1).

The fourth hypothesis stated that children’s frontal alpha asymmetry would moderate the relations between prenatal maternal internalizing symptoms and SES (H4a). We did not expect to observe a significant moderation of the relation with child externalizing problems (H4b). Results revealed no significant moderation between prenatal maternal internalizing symptoms and SES predicting children’s frontal alpha asymmetry and internalizing or externalizing problems (for results, see Supplement Table S1 to Table S7).

Exploratory Analyses

Because the peak and range of alpha oscillations may vary across age and individuals (Bazanova & Vernon, 2014; Sander et al., 2012), in an exploratory analysis, we employed novel ways of characterizing the power spectrum by using specparam (Donoghue et al., 2021). The specparam algorithm removes the 1/f component of the spectrum and uses an iterative procedure to identify peaks (e.g., alpha peaks; see McSweeney et al., 2023). Path analyses were conducted as with the traditionally computed alpha. Results from this exploratory analysis revealed the same significant and non-significant effects as shown in the main path analyses, suggesting that differences in how alpha power is estimated does not significantly influence the results.

Discussion

The purpose of the current study was to examine the role of children’s frontal alpha asymmetry in the associations between prenatal maternal internalizing symptoms and SES on children’s internalizing and externalizing problems. This study was the first to examine the long-term impact of prenatal maternal internalizing symptoms and SES on children’s frontal alpha asymmetry as well as to examine their relations to children’s internalizing symptoms in a large sample. Results revealed a significant association between prenatal maternal SES with children’s frontal alpha asymmetry as well as with children’s internalizing problems. In addition, mothers’ prenatal internalizing symptoms predicted later internalizing and externalizing problems in their children. Alpha asymmetry did not relate to children’s internalizing symptoms, nor moderated the association between early risk (prenatal maternal internalizing and SES) and later child behavior problems. Follow-up exploratory analyses revealed non-significant associations between maternal internalizing symptoms and children’s frontal alpha asymmetry even when using a novel approach to identification of the alpha frequency. However, SES was still predictive of children’s frontal alpha asymmetry. Moreover, frontal alpha asymmetry did not moderate the relations between prenatal maternal risk factors (internalizing and SES) and children’s internalizing and externalizing problems. Overall, the results suggest that children’s alpha asymmetry is not related to mothers’ internalizing symptoms or concurrently related to children’s internalizing and externalizing problems. However, our results also suggests that future research should examine the associations between early SES, children’s frontal alpha asymmetry and internalizing problems, as those significant associations were not preregistered.

Prenatal maternal internalizing symptoms and SES were significantly associated with children’s internalizing problems. More specifically, higher maternal internalizing symptoms during pregnancy predicted higher internalizing problems in children. Additionally, lower SES reported during the prenatal stage predicted higher internalizing scores in children. These findings are consistent with previous literature that separately reported associations between early maternal internalizing symptoms, SES, and children’s negative outcomes (e.g., Bradely & Corwyn, 2002; Goodman et al., 2001; Dawson et al., 2003; Monk et al., 2019). Higher prenatal maternal internalizing symptoms also predicted higher externalizing problem scores in children. However, early SES was not predictive of later externalizing problem scores in children. Lastly, exploratory analyses showed that prenatal maternal internalizing symptoms and SES did not interact to predict alpha asymmetry or children’s behavior problems.

There was no evidence found of children’s frontal alpha asymmetry mediating or moderating the relation between prenatal maternal risk factors (internalizing symptoms and SES) and children’s internalizing and externalizing problems. First, prenatal maternal internalizing symptoms did not predict children’s frontal alpha asymmetry at 5 to 11 years of age. This result differed from previous research that found associations between early maternal internalizing symptoms predicting children’s right frontal alpha asymmetry in relation to negative childhood outcomes (Forbes et al., 2008; Lopez-Duran et al., 2012) though findings are mixed. For example, in line with our findings, a study by Bruder et al. (2005) did not find a significant association between parental psychopathology and children’s frontal alpha asymmetry. There may be several reasons for the inconsistency across studies. First, previous studies examining this relation have had relatively small samples (Forbes et al., 2008; Lopez-Duran et al., 2012), reducing power and increasing the likelihood of false positives. Second, studies have also measured maternal psychopathology in different ways such as examining onset of depression in childhood (Forbes et al., 2006), clinical diagnosis of depression (Lopez-Duran et al., 2012), or lifetime history of depression (Bruder et al. 2005). Previous studies that found significant associations between early maternal psychopathology and children’s frontal alpha asymmetry tended to examine children of mothers with diagnosed depression (either during childhood and/or lifetime history) compared to children of mothers without a history of depression (e.g., Feng et al., 2012; Forbes et al., 2008; Lopez-Duran et al., 2012). Our current study only examined prenatal maternal internalizing symptoms in a community sample and most mothers had a relatively low number of symptoms. Associations between early maternal psychopathology and children’s frontal alpha asymmetry seem to be found more often when mothers have a diagnosis of psychopathology; thus, future studies should examine effects at clinically meaningful levels of maternal internalizing symptoms.

When examining SES as a predictor for children’s frontal alpha asymmetry, results indicated that lower maternal prenatal SES was predictive of children’s right frontal alpha asymmetry. This finding is in line with previous studies that reported concurrent relations between low SES and right frontal alpha asymmetry (Gatzke-Kopp et al., 2014). The current study extends those findings by examining this relation long term. However, children’s frontal alpha asymmetry did not mediate or moderate the relations between SES and children’s internalizing and externalizing problems. This is one of the first studies to examine this mediation as well as prenatal SES longitudinally predicting children’s frontal alpha asymmetry. In addition, this is also one of the few studies to examine this in a moderation model. Thus, future research is still needed to better understand the relation between SES and children’s frontal alpha asymmetry.

Results showed a non-significant relation between children’s frontal alpha asymmetry and their internalizing and externalizing problems. In addition, given the non-significant association between frontal alpha asymmetry and children’s internalizing and externalizing problems, there was no support for mediation. This non-significant finding is counter to previous research that reported a relation between children’s right frontal alpha asymmetry and their internalizing problems (e.g., Feng et al., 2012; Thibodeau et al., 2006). However, a meta-analysis by Peltola et al. (2014) found non-significant associations between children’s frontal alpha asymmetry and their internalizing and externalizing problems. Findings from the current study suggest that frontal alpha asymmetry may not be a robust predictor for socio-emotional problems in normative samples of children. It is important to note that the current study examined frontal alpha asymmetry using resting state EEG data. Several other studies have measured frontal alpha asymmetry while eliciting affective states in experimental tasks. A study by Mulligan et al. (2022) examined the relation between frontal alpha asymmetry and children’s externalizing problems while completing a stressful task. The study found that children who had higher externalizing problems showed left frontal alpha asymmetry during the stressor. Resting state data was also collected by the researchers; they did not find any association between frontal alpha asymmetry and externalizing problems when examining resting state data (Mulligan et al., 2022). In addition, studies have indicated that anger, an emotion related to externalizing behavior, is more closely associated with left frontal alpha asymmetry due to trait-like approach motivation tendencies (Harmon-Jones & Allen, 1998). The current study only examined differences in brain activation during resting state; therefore, there may have been potential differences in alpha asymmetry if participants were presented with a task that elicited an affective state. Thus, future research should examine if it is more beneficial to measure frontal alpha asymmetry during a stressor-related task rather than during resting state.

Limitations

There are several limitations for the current study. The current study was a relatively low-risk sample. Most mothers in our sample had predominantly low internalizing symptoms scores. Additionally, in our sample had relatively low internalizing and externalizing problems scores as well. Future research should include a more diverse sample with a wider range of SES, maternal internalizing symptoms, and children’s internalizing and externalizing symptoms. Furthermore, our study solely focused on maternal internalizing symptoms and SES without accounting for changes in these characteristics from pregnancy to the child’s age of 5 to 11 years. For example, SES or maternal psychopathology could have changed between pregnancy and childhood. Future research could examine the trajectory of changes in maternal internalizing symptoms and SES from the prenatal period to the time of EEG data collection to better understand if unique developmental periods are associated with increased risk.

Despite these limitations, results from this study suggest several theoretical and practical implications. First, the current study was the first to examine the longitudinal impact of prenatal maternal internalizing symptoms and SES on children’s frontal alpha asymmetry in relation to their internalizing and externalizing problems in a large sample. The significant findings of prenatal maternal internalizing symptoms and SES predicting higher internalizing problems in children add to a large corpus of studies highlighting the importance of prenatal maternal characteristics on later socioemotional outcomes for children. Nonetheless, our findings suggest that frontal alpha asymmetry is not a mediator or moderator of these relations. Future studies should examine other factors that may underlie or ameliorate such relations. Moreover, our findings highlight the need for interventions during pregnancy to combat increased risk for socioemotional problems later on in children. Thus, results from the current study can be used to further advocate for early intervention programs for pregnant mothers that may help alleviate or reduce internalizing symptoms as well as better financial assistance during pregnancy. Positive supports during pregnancy, either psychopathology and/or financial, are important for maternal and children’s well-being.

Conclusion

Overall, the current study highlights the importance of examining whether maternal characteristics assessed prenatally may independently relate to later assessment of children’s frontal alpha asymmetry and internalizing and externalizing problems. More research is needed to further examine the impact of early SES on children’s frontal alpha asymmetry and both their role in the development of internalizing and externalizing outcomes. In addition, this study contributes to the growing body of research examining associations between prenatal factors and later child socioemotional outcomes. Our study in a large community sample suggests that alpha asymmetry at rest may not be a strong correlate of children’s internalizing or externalizing problems. Future research should examine other neurobiological factors that may mediate or moderate the link between prenatal risk factors and their association with child socio-emotional development.

Supplementary Material

Supinfo

Table S1 Model without covariates: Maternal Internalizing Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S2 Model with covariates: Maternal Depressive Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S3 Model without covariates; Maternal Depressive Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S4 Model with covariates; Maternal Anxiety Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S5 Model without covariates; Maternal Anxiety Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S6 Model with covariates; Maternal Internalizing Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S7 Model without covariates; Maternal Internalizing Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Acknowledgments:

We thank the many research assistants involved in collecting the data and the participating families without whom the study would not have been possible.

Funding:

This research was supported by grants from the National Institute of Health (UH3 OD023279) to Amy Elliott.

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Associated Data

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Supplementary Materials

Supinfo

Table S1 Model without covariates: Maternal Internalizing Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S2 Model with covariates: Maternal Depressive Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S3 Model without covariates; Maternal Depressive Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S4 Model with covariates; Maternal Anxiety Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S5 Model without covariates; Maternal Anxiety Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S6 Model with covariates; Maternal Internalizing Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

Table S7 Model without covariates; Maternal Internalizing Symptoms at the Prenatal Period Predicting Children’s frontal alpha asymmetry and Internalizing/Externalizing Problems at 5, 7, 9, or 11 Years of Age (n = 415)

NIHMS1967752-supplement-Supinfo.docx (34.1KB, docx)

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