Emerging Biomarkers for Child & Family Intervention Studies: A Review of EEG Studies of Parenting

Abstract

Most interventions for childhood mental health problems require significant parental involvement, and treatment programs are increasingly incorporating components aimed at enhancing parents’ own self-regulation in the context of potentially stressful parent-child interactions. This paper discusses the promise of EEG in examining the rapidly unfolding perceptual, cognitive, emotional, and regulatory processes that occur in parenting, in hopes of ultimately informing child and family interventions. First, we review two separate bodies of work that have used EEG with parents: one examining event-related potential (ERP) measures, and the other examining frontal alpha asymmetry (FAA). We discuss benefits of each within the study of parenting, and also suggest other EEG metrics (such as event-related time-frequency analyses) that can be leveraged to fill current gaps in our knowledge. Finally, we discuss the potential for these findings to inform clinical work with children and families, such as identifying biomarkers that could aid in assessment, treatment recommendations, and monitoring response-to-interventions.

Introduction

Virtually all evidence-based interventions for childhood mental health problems require significant parental involvement, typically in the form of implementing new strategies in response to challenging child behaviors (Kazdin, 1997; Eyberg & Bussing, 2011; Webster-Stratton et al., 2004), and supporting children’s effective coping when distressed (Cohen & Mannarino, 2015; Havighurst et al., 2013; Lester et al., 2016). Challenging behaviors and child distress elicit negative emotions in parents (Cole et al., 2013; Dix et al., 2004; Hajal et al., 2019), and require coordination of a number of cognitive processes (e.g., attention, memory, inhibition, and planning) to implement an effective parenting response (Crandall et al., 2015). Parental self-regulation is critically important to consider when treating childhood psychological disorders, as it is well-established that cycles of emotional and behavioral dysregulation of both children and parents are major etiological and maintaining factors (Patterson, 1982; Reid & Patterson, 1989; Smith et al., 2014). Furthermore, the emotional and cognitive processes that underlie psychological disorders are often transmitted intergenerationally, via genetics, the environment, and their interaction (Cole et al., 2017). For example, ADHD, one of the most commonly diagnosed psychological disorders of childhood (Danielson et al., 2018; Sayal et al., 2018), is highly heritable (Faraone & Larsson, 2019); thus, it is not uncommon for children presenting to treatment for ADHD to have parents who also struggle with ADHD symptoms themselves. Parents’ ADHD symptoms have an impact on their parenting behavior, which in turn impacts treatment outcomes for children (Chronis-Tuscano et al., 2011). As the body of work on the importance of parental self-regulation has grown, childhood intervention programs have increasingly begun to include systematic, targeted components to help parents self-regulate their own internal states in the moment of stressful parenting situations (see Hajal & Paley, 2020; Maliken & Katz, 2013). This paper discusses the potential for EEG studies of parents to inform this aspect of child and family interventions.

Clearly, parental emotional and cognitive processes are activated during parent-child interactions, and parents may need to modulate their initial responses (whether consciously or not) to engage in parenting behaviors that will meet the needs of their child as well as any other co-occurring demands. So, why has there been so little research conducted in this area? The issue of timing may play a role, given its significance in parenting, particularly of young children (Feldman, 2007). Contingent responding—in which parents respond to a cue from their child in a clearly connected and coordinated way—is a key factor in the development of the parent-child attachment relationship (Bowlby, 1981). This in turn is critical for children’s development of emotional and behavioral regulation (Schueler & Prinz, 2013), and is a major target of parenting interventions (Eyberg & Bussing, 2011). Research suggests that, for parent-child dyads, a contingent response occurs within 3–5 seconds of child behavior (Bornstein et al., 2008; Van Egeren et al., 2001). This is a very short time span when considering the multiple aspects of the parenting process that occur in those few seconds: parents must monitor their own internal reactions, regulate them (if necessary), and implement an effective behavioral response, all while simultaneously being responsible for the co-regulation of their child (Teti & Cole, 2011).

Furthermore, the most immediate cognitive and emotional responses may happen so quickly that they are outside of awareness and thus cannot be reported on. Alexithymia is elevated in a variety of risk factors that may lead families to seek treatment (e.g., trauma history; Zlotnick et al., 2001) and thus is important to consider when collecting self-report data that could inform clinical work. Social desirability biases may also interfere with parental report of their feelings and behaviors, as most adults are adept at masking their emotions (Ekman & Friesen, 2015). Thus, measures with very fast time resolution that do not rely on subjective report are needed.

Electroencephalography (EEG) methods may be particularly useful in studying parenting behaviors due to excellent time resolution, flexibility with data collection during social interactions or in ecologically valid contexts, and reduced vulnerability to biases in self-report or observation. EEG indexes electrical activity in the brain circa ten millisecond, which is much faster than other imaging methods, such as functional magnetic resonance imaging (fMRI), which captures neural activity on the order of seconds and requires participants to lie perfectly still in a scanner. Additionally, EEG measurements may be less vulnerable to social desirability biases than self-report and observation (Antonak & Livneh, 2000) and thus enables capture of parents’ immediate responses to child cues that may not be available to awareness. This paper will review the EEG research that has been conducted with parents, integrating findings across different types of EEG measures (predominantly event-related potentials [ERP] and frontal alpha asymmetry). Next, we suggest EEG metrics (such as time-frequency analyses and ERPs of reward processing) that can be leveraged to fill current gaps in our knowledge of parenting and child and family interventions. Finally, we discuss the potential for these findings to inform clinical work with children and families, such as identifying biomarkers that could aid in assessment, treatment recommendations, and monitoring response-to-interventions for families.

EEG Studies of Parents

Emerging interest in the neurobiology of human parenting in the late 1990s and early 2000s has contributed to a growing number of EEG studies of parents in the past two decades. Researchers have used a variety of types of EEG measures to index neural correlates of cognitive and emotional processes that are intertwined with parenting. In this section, we review the EEG research that has been conducted with parents, the vast majority of which has used event-related potentials (ERP) and frontal alpha asymmetry measures (see Table 1 for a summary of EEG measures and related constructs used in the parenting literature to date).

Table 1.

EEG and ERP Measures used in Research Studies with Parents.

EEG Measure	Construct being Measured	Time frame of measurement	N of papers	Parenting-related Constructs Measured*
N1001	Auditory processing	~100 ms poststimulus	4	Parental reflective functioning; parent vs. non-parent status
P1002	Early attention and perceptual processing	~100 ms poststimulus	7	Parental bonding; sensitive parenting
N1703	Face processing, including facial expressions of emotion	~170 ms poststimulus	>15	Adult attachment status; History of maltreating; Sensitive parenting, etc.
P2004	Early attention and recognition of relevant stimuli	~200 ms poststimulus	6	Sensitive parenting; history of neglectful parenting; parental bonding; parent-child relationship
P3005	General attention and cognitive processing	~300 ms poststimulus	11	Adult attachment status; History of maltreating, etc.
Late Positive Potential (LPP)6	Emotional processing	~300–900 ms post-stimulus	9	Adult attachment status; History of maltreating, etc.
Resting Frontal Alpha Asymmetry7	Emotional style (i.e., trait-level emotionality)	4–8 continuous minutes during rest	5	Sensitive parenting; Withdrawn/unavailable parenting; Intrusive parenting; Controlling parenting
Task-based Frontal Alpha Asymmetry8	Emotional response to a stimulus or event (i.e., state-related emotion)	10 sec – 5 min during stimulus presentation or behavioral task	5	Secure base script knowledge; Sensitive parenting behavior; Negative parenting behavior;

^*See Tables 2 and 3 for significance and directions of effects.

¹Lowell et al., 2020; Maupin et al., 2015 (review); Rutherford et al., 2017

²Dudek et al., 2020; Endendijk et al., 2018; Maupin et al., 2015 (review)

³Kuzava et al., 2020 (meta-analysis)

⁴Dudek et al., 2020; Endendijk et al., 2018; Grasso et al., 2009; Kuzava et al., 2019; Márquez et al., 2019; Rodrigo et al., 2011

⁵Kuzava et al., 2020 (meta-analysis)

⁶Kuzava et al., 2020 (meta-analysis)

⁷Diego et al., 2001; Field et al., 2003; Killeen & Teti, 2012; Chen et al., 2015; Wang et al., 2018

⁸Killeen & Teti, 2012; Groh et al., 2014; Atzaba-Poria et al., 2017; Hajal et al., 2017; Martin et al., 2018

Event-related potential (ERP) Studies

Event-related potential (ERP) methodology captures electrical activity (measured as voltage) in the brain at specific time points relative to an event (e.g., a stimulus). An ERP represents the grand average of wave forms elicited by an particular event that is characterized primarily by positive and negative voltage within particular time ranges. Several distinct ERP “components” have been identified to occur reliably and are widely studied such as the P300, which is a positive waveform deflection at 300 ms and is generally largest over central scalp. A large body of non-parenting work on ERPs demonstrates associations between specific ERP components and various perceptual, cognitive, and emotional processes, including some that are relevant to parenting. For example, the N170, which is associated with facial processing, is relevant to parenting given that facial expressions are critically important communicative tools for parent-child dyads (particularly for parents of infants and young, pre-verbal children). Given the emotionally evocative nature of caring for children (Dix, 1991; Hajal & Paley, 2020), ERPs associated with emotional processing, such as the P300 and late positive potential (LPP), are also fruitful in the study of parenting and are discussed further below (also see Table 1).

N170.

The N170 is a negative deflection that reaches its peak around 170 ms after presentation of visual face stimuli, and is detected primarily in electrodes over the occipital and temporal cortices. A large body of research on the N170 indicates that its amplitude is larger in response to images of faces than non-faces (Luck, 2014). Furthermore, it is sensitive to facial expressions of emotions, with images of faces displaying anger, fear, and happiness (but not disgust or sadness) eliciting larger N170s than neutral faces (Hinojosa et al., 2015). Although most of the initial research on the N170 involved images of adult faces as stimuli, there has been a growing number of studies that have used child faces as stimuli, including some with parents as participants. In fact, this body of work is large enough to support meta-analytic research. In their meta-analysis of 35 study samples (24 of which consisted of parents), Kuzava and colleagues (2020) replicated previous N170 findings (Hinojosa et al., 2015) with studies that used images of children’s faces as stimuli. Specifically, they found that N170 amplitudes were largest in response to children’s crying expressions, followed by laughing expressions, and finally neutral expressions (Kuzava et al., 2020).

N170 and Parent Characteristics.

The Kuzava et al. (2020) meta-analysis also examined how N170 responses to images of children’s emotion expressions are associated with characteristics of the parent, child, or family context. The meta-analysis included studies that examined a variety of characteristics known to be associated with insensitive caregiving behaviors (e.g., parental mental health symptoms, child protective services involvement, etc.). Coding participants as low- or high-risk for insensitive parenting, the meta-analysis found a moderating effect of risk level on N170 amplitude. Specifically, infant cry stimuli elicited a greater N170 than neutral stimuli only for those at low risk (Kuzava et al., 2020). This finding is consistent with the notion that early discrimination of types of child cues supports effective parenting by allowing parents to modulate their response based on child need (Kuzava et al., 2020), and that failure to discriminate among different types of child emotional cues may be a mechanism by which risk factors lead to ineffective parenting and child maladjustment.

P300 and LPP.

The P300 and LPP are both midline components reflecting positive voltage deflections that begin around 300 ms post-stimulus onset, although the P300 is typically characterized to occur between 300 and 500 ms, whereas the LPP may occur as early as 300 ms, but extends up to several seconds post-stimulus (Hajcak et al., 2010; Luck, 2014). Although the P300 and LPP may be difficult to distinguish given their potential overlap in location and timing, it is generally thought that the P300 reflects general attentional and cognitive processing, while the LPP is associated specifically with processing of emotionally-evocative stimuli (Hajcak et al., 2010; Luck, 2014). Pleasant and unpleasant visual stimuli (such as photos, images of faces, and words) elicit higher P300 and LPP amplitudes than neutral stimuli (Hajcak et al., 2010; Hajcak & Foti, 2020). Moreover, the LPP appears to be sensitive to changes in emotional experience induced by use of emotion regulation strategies. Specifically, studies of both adults and children suggest that when participants are instructed to reduce their emotional reactions to evocative stimuli (e.g., by using cognitive reappraisal and other emotion regulation strategies), LPP amplitude typically decreases (see Hajcak & Foti, 2020). The Kuzava et al. meta-analysis of studies examining adults’ (including parents’) ERP responses to child emotion expressions included studies examining P300 and LPP; findings were consistent with the broader literature, indicating that P300/LPP amplitudes were largest in response to images of children crying, followed by laughing, and finally neutral expressions (Kuzava et al., 2020).

P300/LPP and Parent/Child Characteristics.

The Kuzava et al. meta-analysis also found that child age has a moderating effect on parents’ P300/LPP amplitudes. Specifically, the finding of larger P300/LPP amplitudes to crying vs. neutral stimuli was shown only for parents with children two years and older (Kuzava et al., 2020). One possible explanation is that parents of younger children may have less caregiving experience, and thus allocate less attention to child distress or have more difficulty differentiating it from neutral expressions, however, controlling for parity in caregiving experience would be necessary to test this hypothesis (Kuzava et al., 2020). Another possibility is that parents of younger infants (under 2 years) consider a relatively limited sources of negative emotion (e.g., hunger, proximity seeking, pain, tiredness), and have fewer response options (e.g., feeding for hunger), all of which are almost completely parent-regulated (e.g., parental soothing as opposed to parents’ coaching their children’s self-soothing); as a result processing may not need to be as sustained, which is reflected in a lower P300/LPP amplitude. In children 2 years and older, however, there is more complexity in terms of the range of emotions that children express, as well as parents’ need to meet multiple, sometimes competing goals (i.e., their child’s learning, emotion socialization, and behavioral control as well as safety/survival and other situational demands). As a result, parents of older children may engage in more processing about what the child’s specific emotion is, what caused it, and a much larger repertoire of potential parenting behaviors that must be decided upon and then executed. In the midst of this complex decision-making and responding, parents must also manage a very mobile and verbal interaction partner (their child); all of this sustained processing may be reflected in larger P300/LPP amplitudes.

ERPs and Parent Behaviors.

A primary reason that parents’ ERPs are of interest to child and family clinical researchers is due to their potential ability to shed light on parents’ automatic emotional and cognitive processes in response to child stimuli, which then have downstream effects on parenting behavior with their children. Although ERP studies provide rich information about parents’ immediate responses to child stimuli, they index only a tiny fraction of time in a parent-child interaction (i.e., the first second). Some researchers have begun to examine whether these immediately-measured ERP neural responses are associated with parenting behavior (both self-reported and observed) that occurs following a cue from their child.

Although the body of work examining parents’ ERPs in response to child stimuli is large enough to support meta-analytic studies (e.g., Kuzava et al., 2020), the number of ERP studies examining parents’ actual behavior is much smaller (see Table 2). Most of these studies have examined the N170 and LPP, but other ERP components have also been examined (e.g., P100, P200). Three studies have examined whether sensitive parenting behavior, as observed during standardized parent-child interaction tasks, is associated with mothers’ ERP responses to infant stimuli; two of these studies have examined brain responses to infant distressed and happy faces (Dudek & Haley, 2020; Kuzava et al., 2019). Findings of the two studies employing images of infant emotion expressions support the notion that sensitive parenting behavior is associated with greater immediate neural responsivity to infant distressed faces (versus infant happy or neutral faces, or any type of adult face), in terms of face processing (N170), early attention and recognition of relevant stimuli (P200), and emotional processing (LPP; Dudek & Haley, 2020; Kuzava et al., 2019). Dudek and Haley (2020) found that mothers who exhibited high levels of parenting sensitivity with their 3–5 month old infants showed larger amplitude N170s (measured prenatally) to infant distressed versus happy faces. For mothers who exhibited low parenting sensitivity, prenatal N170 was not modulated by infant emotion expressions. Kuzava and colleagues (2019) also found a relation between observed parenting sensitivity and enhanced neural processing of infant distress versus happy faces, although they used a combined measure of the P200 and LPP, and obtained ERP and parenting data approximately 2–4 weeks apart. Latent class analysis on P200 and LPP, identified two classes: one in which both the P200 and LPP were enhanced in response to infant crying versus laughing faces, and one in which neither the P200 nor the LPP were differentiated by infant expression. They found that likelihood of membership in the enhanced response to distress group was associated with more sensitive parenting behavior, while membership in the undifferentiated group was associated with less sensitive parenting behavior (Kuzava et al., 2019). From an attachment perspective, sensitive parenting is particularly critical in the context of infant distress, and involves contingent responding to infant signals and engagement with the infant to support co-regulation (Leerkes et al., 2012). Thus, the findings of both of these studies are consistent with the idea that sensitive parenting would be facilitated by a strong immediate reaction to infant distress cues as well as increased attentional engagement and elaborative processing of that emotional cue. Furthermore, this interpretation is consistent with a study showing that greater LPP amplitude to infant neutral (but not distressed) faces was associated with mothers’ self-reported difficulty recognizing and understanding their infants’ feelings (Rutherford et al., 2018), which has been linked to less responsive and attuned parenting behavior (Luyten et al., 2017).

Table 2.

Studies Examining Parents’ ERPs and Specific Parenting-related Constructs.

Authors	Sample Size	ERP (Time Window)	Peak Amplitude or Average Activity	ERP Task Stimuli	Parenting construct	Results
Endendijk et al. 2018	N = 33	P100 (100–150ms), P200 (250–350ms), N170 (150–230ms), LPP (300–700ms)	Average activity	Images of infant faces, in high-cute, low-cute, and normal forms	Sensitive and intrusive parenting behaviors (observed during parent-child interaction); Parental Tenderness & Care (self-report questionnaire)	Greater LPP associated with observed intrusiveness. Greater P100 and P200 associated with self-reported tenderness/care.
Rutherford et al., 2018	N = 63	N100*, N170*, P300 (200–600 ms)	Peak amplitude	Auditory: High-distress cry, low-distress cry, neutral tone. Visual: Images of infant happy, distress, neutral	Parental Reflective Functioning (self-report questionnaire)	Greater LPP amplitude to infant neutral (but not distressed) faces was associated with mothers’ self-reported difficulty recognizing and understanding their infants’ feelings.
Dudek & Haley 2020	N = 36	N170 (150–220 ms)	Peak amplitude	Go/No Go task w/images of adult and infant happy and sad faces as background distractors	Sensitive parenting behaviors (observed during parent-child interaction)	For mothers high in sensitivity, prenatal N170 was larger for distressed versus happy infant faces. For mothers low in parenting sensitivity, prenatal N170 was not modulated by infant emotion expression.
Dudek et al., 2020	N = 39	P100 (90–155ms), P200 (190–260ms), N170 (140–200ms), LPP (500–800ms)	Peak amplitude	Go/No Go task w/images of adult and infant happy and sad faces as background distractors	Parental Bonding (self-report questionnaire)	Prenatal to postnatal increases in P100 and P200 responses to infant vs. adult faces were associated with self-reported bonding. No significant findings for pre- to post-natal change in N170 or LPP.
Kuzava et al. 2019	N = 86	N170 (140–180ms), P200 (130–200ms), LPP (300–600ms)	Average activity	Images of infant crying, laughing, or neutral	Sensitive parenting behaviors (observed during parent-child interaction)	Using latent class analysis on P200 and LPP, identified two classes: P200 & LPP not differentiated by infant expression Enhanced P200 & LPP to crying vs. laughing. Membership in group #1 correlated with less sociodemographic risk and more sensitive parenting; vice versa for group #2.
Kuzava et al. 2020	k = 35 (meta-analysis)	N170 (+/− ~25–50ms), LPP (~300+)	Meta-analytic sample included studies using both; included as moderator	Images of infant crying, laughing, or neutral	Risk for insensitive parenting behaviors, e.g., parental mental health symptoms, child protective services involvement, etc. (coded from methodology of studies included in meta-analysis)	Infant cry stimuli elicited a greater N170 than neutral stimuli only for parents at low risk for insensitive parenting behavior

^*In Rutherford et al., 2018, time-windows for N100 and N170 were derived and customized for each participant.

Another study examined observed parenting behaviors in relation to their ERPs to infants’ faces, using neutral face stimuli that varied in cuteness (Endendijk et al., 2018), as opposed to different emotion expressions. None of the components associated with early attention, perception, and face processing (P100, N170, P200) were associated with observed parenting behavior. From an evolutionary perspective, it makes sense that a strong, immediate attentional and visual processing response is not as critical for non-distressed infant faces as it is for distressed faces. This study also showed that greater LPP to infant faces was associated with observed intrusiveness (but not sensitivity, as in Kuzava et al., 2019). Although the discrepancies between the Kuzava and Endendijk studies could be due to methodological differences (they used different systems to code sensitivity, and Kuzava et al. did not code for intrusiveness), it is also possible that discrepant ERP findings were due to the use of different types of infant stimuli (varied emotional expressions vs. neutral). It may be that in the context of infant distress, enhanced attentional engagement and processing of the emotional cue (as found in Kuzava et al., 2019) is critical for actively engaging in co-regulation to soothe the infant. In the context of infant non-distress (as examined in Endendijk et al.), however, sustained cognitive processing may prevent the parent from “following the child’s lead,” which is critical to promoting child autonomy as well as positivity in the parent-child relationship (Choate et al., 2005). Although the literature linking maternal ERPs and parenting behavior is still very new, these initial results indicate the potential practical importance of mothers’ perception of infant facial cues, as well as the specificity of those responses to different types of child cues.

ERPs in Parents: Summary and Future Directions

In sum, there is strong evidence that the N170, P300, and LPP amplitudes in parents are modulated by children’s facial expressions of emotions, with specific child expressions (e.g., happiness, laughter, distress, sadness, crying, neutral) having differential impact. In some cases, parents’ ERP responses were associated with parent and child characteristics (e.g., child age) and risk factors (e.g., parent mental health problems). A much more limited body of work suggests that parents’ immediate neurophysiological responding to child signals (as indexed by N170, P300, and LPP) are associated with measures of actual parenting behavior. In order for ERPs to be a useful biomarker for prevention and intervention, they must be predictive of clinically-relevant characteristics. Thus, more research is needed to confirm and subsequently quantify the predictive validity of ERP associations with parent and child characteristics and parenting behaviors.

Another avenue for future ERP research with parents is further examination of combinations of components (as in Kuzava et al., 2019, reviewed above), of other, less studied ERP components (e.g., N100, P100, P200), and of different types of infant stimuli. For example, two recent studies showed that parents’ P100 and P200 (but not N170 or LPP) in response to non-emotional infant faces (infant faces varying in “cuteness;” infant vs. adult faces), are associated with parents’ reports of general feelings of tenderness and bonding to their infants (Dudek et al., 2020; Endendijk et al., 2018). A few studies have also examined the N100, a component that indicates early auditory processing, in response to audio recordings of infants crying. Generally, studies have shown that mothers have larger N100 amplitudes than non-mothers (see review by Maupin et al., 2015), and that high-distress cries generate larger N100 amplitudes than low-distress cries (Lowell et al., 2020; Rutherford et al., 2017). Furthermore, consistent with research showing that parental risk status modulates enhanced N170 amplitudes to images of infants crying (see Kuzava et al., 2020), a recent study found the same pattern of results for the N100 in response to infant cries. Specifically, healthy mothers had larger N100 amplitudes to high-distress infant cries versus low-distress cries, but N100 amplitudes for mothers who abused substances did not differ significantly across high- versus low-distress cries (Lowell et al., 2020). Thus, the Lowell et al. findings add further ERP evidence (using a different ERP component and a different type of child stimuli) to the notion that early discrimination of child cues supports effective parenting by allowing parents to modulate their response based on child need (Dudek & Haley, 2020; Kuzava et al., 2019) and that failure to discriminate among a variety of types of child emotional cues (facial expression as well as cries) may be a mechanism by which risk factors lead to ineffective parenting and child maladjustment (Kuzava et al., 2020). Future ERP research with parents should expand upon the foundational work reviewed here by replicating findings within and among ERP components and clinically-relevant constructs (e.g., risk status, parenting behavior).

Frontal Alpha Asymmetry Studies of Parents

To date, most of the EEG research that has been conducted with parents has used ERP methodology. There is also a smaller body of work examining parents’ frontal cortical alpha activity, which is of interest to parenting researchers due to its association with the motivational component of emotion (approach/avoidance). Given the critical importance of parental emotion to the way in which a parent responds to child cues (which then has downstream effects on children’s emotion socialization, socioemotional adjustment, and response to treatment; Hajal & Paley, 2020), frontal alpha asymmetry (FAA) is a potentially exciting way of understanding neural processes associated with parenting.

A large body of research collected in many different populations (including adults, children, healthy individuals, clinical populations), indicates that greater alpha band (8–13 Hertz [Hz]) activity measured over the right-frontal lobe relative to the left-frontal lobe (termed “right frontal alpha asymmetry”) is associated with a range of withdrawal-related behaviors and emotions (e.g., sadness, fear, disgust, contentment), while greater left frontal alpha asymmetry is associated with approach behavior and emotions (e.g., joy, anger; Reznik & Allen, 2018). FAA that is measured during a resting period (i.e., no stimulus) is generally thought to reflect trait-like emotionality, such as temperament or risk for psychopathology (Reznik & Allen, 2018). For example, greater relative right FAA at rest is associated with a range of withdrawal-related characteristics (e.g., behavioral inhibition and depression), while greater relative left FAA is associated with approach-related characteristics (e.g., behavioral activation, trait anger; see reviews by Harmon- Jones & Gable, 2018; Reznik & Allen, 2018). Other studies examine changes in FAA in response to a stimuli (i.e., image, video, audio recording) or experimental task (e.g., computer-based activity, interpersonal task). For example, several studies examining the relation between anger and FAA have used frustration-inducing experimental paradigms (e.g., participants are insulted or rejected), showing that self-reported anger in response to these tasks is associated with increased left FAA (controlling for baseline FAA) as well as increased behavioral aggression (Harmon-Jones & Sigelman, 2001; Jensen-Campbell et al., 2007; Verona et al., 2009). Few studies have examined FAA in response to child stimuli, although one small study of families with 6- to 8-month infants examined relations between mothers’ FAA, observed facial expressions of emotions, and (later) self-reported emotions in response to 10-sec videos of their own child. Consistent with the larger literature, shifts to greater right FAA from baseline in response to infant distress videos was associated with greater self-reported sadness, concern, and the absence of joy (Killeen & Teti, 2012) as well as facial expressions of sadness and tension that were longer in duration (Hajal et al., 2017). Notably, shifts to right FAA were also associated with maternal reports of irritability; although this is inconsistent with FAA and anger findings in the broader literature (e.g., Harmon-Jones et al., 2010), it is in line with some non-EEG research of anger in the parenting context specifically (Hajal et al., 2019).

FAA and Parent Characteristics.

Two studies have examined how characteristics associated with parent-child attachment and bonding are associated with FAA while listening to a 3 min auditory cry stimulus. One of these studies examined mothers’ secure base script knowledge, an attachment-related construct thought to support sensitive parenting (Groh et al., 2014). The other examined women’s experience of being parented sensitively in their own family of origin (which would theoretically lead to greater parental sensitivity with their own future children; Martin et al., 2018). Interestingly, despite several similarities in methodology, these studies found discrepant results. The Groh and colleagues study found that the attachment-related construct (secure base script knowledge) was associated with a shift to right FAA from rest to infant cry, while the Martin and colleagues study found that the attachment-related construct (receiving sensitive parenting in own family of origin) was associated with a shift to left asymmetry in response to infant cry. Plausible explanations exist for both sets of results. Groh and colleagues’ right FAA findings are consistent with other studies (including studies of parents, non-parent adults, and children) suggesting a link between right FAA and empathy (Killeen & Teti, 2012; Light et al., 2009; Musser et al., 2012; Tullett et al., 2012). Specifically, witnessing infant distress cues elicits a neural response associated with withdrawal that may indicate negative affect matching as part of empathic distress, and mothers who are more empathic are also more likely to have secure base script knowledge. This interpretation is supported by a study showing that the relation between right FAA and empathic concern is mediated by self-reported sadness (Tullett et al., 2012). Yet, there is also a compelling interpretation for Martin and colleagues’ finding of an association between a predictor of sensitive parenting and left FAA when listening to an infant crying (Martin et al., 2018). Specifically, an increase in approach motivation (reflected by left asymmetry) makes logical sense when considering that a sensitive response to child crying could involve approach behaviors such as increasing proximity and engaging in caretaking behavior (Martin et al., 2018). These discrepancies could also be due to differences between the two samples in the age of children represented (notably, one of the two samples also had a mix of parents and non-parents, but parental status was not shown to moderate findings; Martin et al., 2018).

It is possible that these two sets of seemingly discrepant findings are not mutually exclusive, but instead provide different pieces of the puzzle of responding over a three-minute long infant cry. Recently, parenting researchers have proposed that optimal responding to children’s distress is a multi-layered process—not a single state—that involves activation of certain emotional and motivational responses, as well as modulation of those responses to support effective caregiving (Hajal et al., 2019; Leerkes et al., 2015; Lin et al., 2016; Teti & Cole, 2011). Particularly in the context of parenting, in which the adult is responsible for the survival and well-being of a highly dependent interaction partner, sensitive responding to child distress or challenging behavior is likely to elicit multiple motivational states. This may include withdrawal motivation (perhaps reflecting empathic identification with the distressed child, and/or personal distress due to the inherently aversive nature of the cue), which may be then down-regulated in favor of approach motivation (which would support caregiving). Although this hypothesis has not yet been tested in EEG studies with parents, there is some support from other literatures. Parenting studies using non-EEG psychophysiological measures (skin conductance and vagal suppression) have suggested that maternal arousal and withdrawal during parent-infant interaction is associated with sensitivity-related parenting responses, but only when arousal and withdrawal are accompanied by physiological regulation (Leerkes et al., 2016). Another study used time-series analytic approaches to examine young adults’ continuous ratings of personal distress, empathic concern, and perceived aversiveness as they viewed a 4 min video of an infant crying (Lin et al., 2016). Results showed dynamic changes in all three ratings over the course of the 4 minutes, as well as interplay among them (Lin et al., 2016), suggesting that personal distress and empathy interact dynamically over time. Averaging the second-by-second data to generate a single score for each variable would likely have masked meaningful variation. Finally, a study of school-age children used growth curve modeling to analyze FAA on a second-by-second level over the course of an approximately 2 min social task (as opposed to averaging the second-level EEG data across the entire task, as in all parental FAA studies to date). The study showed that dynamic change from initial right asymmetry, followed by increasing left asymmetry (or, greater withdrawal motivation followed by increasing approach motivation) was present in children observed to exhibit a high degree of empathic concern (measured during a separate task; Light et al., 2009). As in the Lin and colleagues (2016) study, averaging the second-by-second data across the entire task would have lost meaningful variation in the response. Thus, it is plausible that findings from Groh et al. and Martin et al. studies are not fully discrepant, but actually captured different points along a longer, more complex process. Future research could test this hypothesis by using time-series analytic approaches with FAA data.

FAA and Parent Behavior.

Studies examining the relation between FAA and parenting behavior have measured FAA during three types of experimental paradigms: (1) during a standard resting task (several minutes of eyes open and eyes closed, with no stimuli), (2) in response to visual or audio stimuli, (3) during a parent-child interaction task (see Table 3). Studies measuring parental FAA during a resting baseline have shown mixed results. In line with the literature showing links between right FAA and withdrawal, and left FAA and approach, one research group showed that depressed mothers who exhibited withdrawn behavior with their infants (e.g., flat affect, rare touching and vocalizing) during a parent-child interaction showed significantly greater right FAA at rest than mothers who exhibited intrusive parenting behavior (e.g., rough tickling, poking, loud, non-contingent speech; Diego et al., 2001). Furthermore, mothers who were depressed but who exhibited positive parenting had greater right FAA than non-depressed mothers, but less right FAA than depressed mothers who were withdrawn during parent-infant interaction (Field et al., 2003). Other studies, however, did not find significant associations between parents’ resting FAA and their self-reported harsh parenting (Chen et al., 2015) or observed emotional availability with their infants (Killeen & Teti, 2012) and school-aged children (Wang et al., 2018). Thus, the evidence linking resting FAA to parenting behavior is mixed. In applying FAA research to parenting, it is important to remember that resting FAA is associated with trait-like emotionality, and that neither right nor left FAA on its own denotes “good” or “bad” emotionality or parenting; rather, it is likely a matter of degree, context, and flexibility to meet continually changing demands. Thus, it may be more useful to assess modulation of parents’ FAA in response to the types of situations that typically elicit parenting behavior. Studies that examine state-related changes in FAA asymmetry (as opposed to resting asymmetry) address some of these nuances. They are similar to ERP studies in that they examine parental responses to specific child cues, although unlike ERP studies, they examine periods of time well beyond the first post-stimulus second.

Table 3.

Studies Examining Parents’ Frontal Alpha Asymmetry and Specific Parenting-related Constructs.

Authors	N	Task Stimuli	Stimuli length in seconds	Number of trials	Measure of parenting behavior	Results
Diego et al., 2001	60	n/a (EEG during resting baseline only)	-	-	Withdrawn and intrusive parenting behaviors (observed during parent-child interaction)	Mothers who exhibited withdrawn behavior showed significantly greater right FAA than mothers who exhibited intrusive parenting behavior.
Field et al., 2003	140	n/a (EEG during resting baseline only)			Contingent, withdrawn, and intrusive parenting behaviors (observed during parent-child interaction)	Mothers who were depressed but who exhibited positive parenting had greater right FAA than non-depressed mothers, but less right FAA than depressed mothers who were withdrawn during parent-infant interaction.
Chen et al., 2015	121	n/a (EEG during resting baseline only)	-	-	Harsh parenting (self-report questionnaire)	No association between parental asymmetry and parenting behavior.
Wang et al., 2018	39	n/a (EEG during resting baseline only)	-	-	Unavailable and controlling parental behaviors (observed during parent-child interaction)	No association between parental asymmetry and parenting behavior.
Killeen & Teti, 2012	26	Video clips of own infant neutral, distress, joy	10	36	Sensitivity, nonintrusiveness, and structuring (observed during parent-child interaction)	Shift to right FAA in response to infant distress was associated with parenting sensitivity and structuring.
Groh et al., 2014	108	Audio recording of infant crying	180	1	Maternal secure base script knowledge (self-report questionnaire)	Secure base script knowledge associated with shift to right FAA in response to infant cry.
Martin et al., 2018	73	Audio recording of infant crying	180	1	Family of origin experience of having been parented sensitively (observed during parent-child interaction when mother herself was a child)	Family of origin sensitive parenting associated with shift to left FAA in response to infant cry.
Atzaba- Poria et al., 2017	34	Mother-child interaction task	305.98*	1	Maternal & child negative affect & behavior during (observed during the parent-child task in which EEG was also recorded)	Mothers’ right FAA was associated with own negativity and child negativity (but only child negativity was significant when both were included in the same model)

^*Total task length varied per dyad; 305.98 second was sample average.

For example, Killeen and Teti (2012), examined mothers’ FAA in response to 10 second video clips of their own babies, as well as observed parenting behaviors during a separate parent-infant free-play task. A shift to right FAA in response to the infant distress and infant joy videos was associated with two indicators of observed positive parenting (sensitivity and structuring; Killeen & Teti, 2012). This finding is consistent with the work (reviewed above) linking right FAA with empathy and constructs related to sensitive parenting. Finally, one study examined parental FAA during a parent-child interaction task (Atzaba- Poria et al., 2017). Similar to Killeen and Teti, this study showed that children’s observed negativity during the interaction was associated with mothers’ right FAA during the same task. However, unlike Killeen and Teti, who found that shifts toward right asymmetry in response to infant distress was associated with mothers’ positive parenting behaviors. Atzaba-Poria and colleagues found that mothers’ right asymmetry was associated with their own negativity during the parent-child interaction (although notably, this association was not significant when child negativity was included in the analytic model; maternal and child negativity during the task were highly correlated). Differences could be partially accounted for by study design: Killeen and Teti used separate EEG and interaction tasks and measured change in asymmetry in response to infant stimuli (from resting baseline) over the course of only 10 seconds, whereas Atzaba-Poria and colleagues used a single, several minute task for both EEG and behavior, and did not account for resting asymmetry in analyses (in other words, they did not examine a shift toward right FAA from rest to onset of the parent-child interaction). Clearly, more research is needed to examine how FAA in response to child cues relates to parenting behavior, and researchers should consider replicating paradigms that have been previously used when designing future FAA studies so that discrepancies can be attributed to outcomes of interest as opposed to methodological variation.

FAA in parents: Summary and Future Directions

In sum, there is emerging evidence that FAA may be a useful way to examine parents’ emotional responses to children. However, vast methodological differences between studies are important to consider in the interpretation of these studies. This is in contrast to ERPs, which are time-locked and thus there is less variation across studies in terms of type of stimuli (images or brief audio clips), and time at which response is measured (i.e., P300 is defined as a response at approximately 300 ms). There are no similar standards for the design of FAA studies, and even in the very limited research using this measure with parents, there is wide variation in terms of stimuli, response time, and method used to calculate FAA. For example, some studies examine how parents’ FAA at rest (e.g., for several minutes with eyes open and/or closed, but no stimuli) relates to their behaviors during a separate parent-child interaction task. Other studies use audio or visual stimuli paradigms similar to those used in ERP research, but may measure FAA over widely varying periods of time (e.g., as few as 10 sec or as long as 3 min). Another study examined FAA over the course of several minutes of a parent-child interaction task. Furthermore, the FAA metric can be calculated in a variety of different ways. Some studies simply use a difference score, subtracting alpha band power in the left hemisphere from that of the right hemisphere, while others use a multivariate approach to examine each hemisphere’s alpha activity as independent variables. Although all of these study designs offer important information about processes associated with parenting, comparing findings across studies is more difficult and must be considered when interpreting findings.

Future Directions for Parenting Research using EEG

As reviewed above, there is converging evidence from non-EEG research with parents that the emotional and cognitive processing that occurs in the act of parenting is dynamic, and that second-by-second level (and perhaps millisecond-level) change may be meaningful predictors of actual parenting behaviors (Leerkes et al., 2016; Light et al., 2009; Lin et al., 2016). Thus, we argue that a critical next step in parental EEG research involves new ways of thinking about timing, with a focus on EEG recording time frames that are aligned with the time course of the parenting construct of interest. Findings from the current literature reflect averages of an EEG signal across different periods of time, ranging from ~10 milliseconds (30+ ERP studies, such as Dudek & Haley, 2020; Kuzava et al., 2019, 2020), to 10 seconds (Hajal et al., 2017; Killeen & Teti, 2012), to 3 min (Groh et al., 2014; Martin et al., 2018), to approximately 5 min (on average; Atzaba- Poria et al., 2017). Given the range of task durations represented across these studies, would we even expect findings to correspond, particularly when we are studying a process as dynamic as parenting? This is not to say that these studies do not each offer important information—they certainly do. But they may be capturing different information, making it difficult to make sense of neural aspects of the complex processes that underlie parenting.

This begs the question: what IS the best time interval in which to study parenting-related phenomena? As mentioned previously, parenting is a multi-layered process involving perception, cognition, motivation, emotion, and behavior that occur not only over time, but also across different time scales. For example, automatic, immediate perceptual and attentional processing of infant cues occurs before it even reaches a person’s awareness. Thus, the millisecond-level resolution of ERP measures is useful in understanding how the very earliest and fastest processing of information may put parents on a path toward certain types of parenting behaviors. Emotion is another phenomena that is critical to parenting that typically occurs very quickly. Research on facial expressions of emotion have consistently documented meaningful changes in type and intensity of emotions on the second-by-second level (see Rosenberg & Ekman, 2020). Parenting behavior may occur over longer periods of time. For example, parenting termed to be sensitive or responsive involves “contingent responding,” meaning that parents respond to cues from their child in a clearly connected and coordinated way. Research examining when a parental response must occur after a child cue to be considered contingent has generally converged on a time span of 3–5 seconds (Bornstein et al., 2008; Van Egeren et al., 2001). This is substantially longer than ERP studies, but much shorter than parental FAA studies to date. Thus, future studies aimed at understanding emotional, motivational, or cognitive correlates of sensitive parenting might benefit from focusing on brain activity within the time frame that parenting behaviors of interest tend to occur.

Furthermore, in the actual act of parenting, these various components of responding—e.g., perceptual, attentional, emotional, etc.—do not occur independently of one another, but rather as parts of an ongoing process that unfolds over time. Event-related time-frequency analysis (TFA) is an approach that combines elements of both ERP and power spectrum (e.g., FAA) measures. TFA examines EEG spectral power changes across time and in relation to task-based events (e.g., stimulus onset or subject response). Although less common in psychological research than ERP and power spectrum approaches, event-related TFA offers promise in capturing the intricacies of parenting as an unfolding process over the course of several seconds. Furthermore, unlike ERP studies that are a brief snapshot of neural responding in the time domain, or FAA studies that average spectral power across long periods of time (e.g., 10 sec, 3 min, 5 min, etc.), event-related TFA can map millisecond-level changes across multiple frequencies over more extended periods of time, showing the dynamics of neural events unfolding.

Lenartowicz and colleagues (Lenartowicz et al., 2019) provide an example of how dynamics in the EEG signal can be mapped over the course of several seconds using TFA. Specifically, they examined how children’s alpha and theta power changed over the course of a 6.5 sec working memory task, and showed that changes in alpha (but not theta) power were associated with behavioral outcomes. Results indicate that alpha power showed event-related decreases (during WM encoding and retrieval phases) and increases (during the WM maintenance), as well as a frequency shift within the alpha band (11 Hz during encoding/retrieval vs 9.5 Hz during maintenance) that would have been obscured if the alpha power was averaged across the whole WM trial. Furthermore, alpha modulation during the encoding period was associated with specific behavioral outcomes (WM accuracy, reading comprehension and executive function), whereas alpha power during maintenance was not uniquely associated with outcomes over and above its significant association with encoding alpha. Thus, this example illustrates the specific event-related changes in spectral power across time and the specificity of associations with clinically-relevant outcomes by using TFA.

One study of parents has employed time-frequency analysis, although not in relation to clinically relevant outcomes. Esposito and colleague examined mothers’ (N = 21) neural responses to images of their own infant versus an unfamiliar infant (Esposito et al., 2015). Power in five frequency bands was examined during the 500 ms image presentations as well as the first 450 ms of the inter-trial interval. Underscoring the importance of examining changes over time, the authors found that differences in neural responding occurred not only by infant familiarity, but also based on which time window was examined. Specifically, mothers showed higher midline occipital gamma power in response to their own infant relative to an unfamiliar infant, but only during the first 100 ms of viewing the stimulus. Higher gamma power over the occipital lobe suggests that mothers’ recognition of their own infants’ faces (versus unfamiliar infants) occurs virtually automatically. Differences among own and unfamiliar infant conditions were also found during the inter-trial interval (i.e., after stimulus offset); specifically, mothers’ delta and theta power measured over the temporal lobe was lower after viewing their own (versus unfamiliar) infants, potentially reflecting continued cognitive processing of the image even after it was no longer visible, but only when the infant pictured was their own. This study highlights the utility of and putative strengths of TFA in parenting research, given the speed with which multiple processes associated with parenting occur. Future studies aiming to use TFA to inform child and family intervention should specify hypothesized associations between particular frequency bands’ (e.g., alpha, beta, etc.) change over time with measures that are relevant to children’s mental health (such as parental or child psychological symptoms), if possible. If no prior findings are available, TFA would be useful in generating hypotheses regarding neural mechanisms involved in multiple layers of the parenting process.

Moving Toward Clinical Applications for Parental EEG Research

Findings from EEG studies of parents show that their neural responses are modulated by risk factors that commonly lead families to seek treatment (e.g., child behavior problems, parental depression) and that neural responses are associated with types of parenting behavior that are often targets of treatment (e.g., sensitive parenting). Thus, a natural next question is how parental EEG research may inform child and family intervention. Following in the footsteps of EEG researchers more generally, some parenting researchers are incorporating EEG measures into clinical research studies to test mechanisms of treatment response.

Intervention Studies and ERPs.

In the general (i.e., non-parenting) clinical literature, ERPs are increasingly being used as biomarkers of intervention response (e.g., error-related negativity, Hajcak et al., 2019), reward positivity, Luby et al., 2019). Two studies of child and family prevention or intervention programs have also integrated examination of parents’ ERPs in response to child cues into evaluation.

Examination of mothers’ ERPs was included in a follow-up study to a randomized controlled trial (RCT) of Attachment and Biobehavioral Catchup, an intervention for families in which the mother had been referred to Child Protective Services. Approximately 6–7 years after the original RCT, researchers examined mothers’ N170 and LPP during a task for which they were asked to categorize images of distressed, happy, and neutral infant faces. In comparison to mothers who had previously been randomized to the active control condition (n = 21), mothers randomized to the ABC intervention (n = 19) showed greater enhancement of N170 and LPP during infant emotional conditions. Specifically, infants’ crying and laughing faces elicited larger N170 and LPP amplitudes than infant neutral faces, but only for ABC intervention mothers. Furthermore, greater N170 enhancement during infant emotional conditions was related to greater observed sensitive parenting. Although the lack of a pre-intervention EEG assessment prevented examination of ERP modulation as a function of treatment response, it is notable that ABC intervention group mothers exhibited comparable ERP responses to a subsample of low-risk mothers (n = 30) who had no history of CPS involvement and had not received any study intervention.

A recent RCT of a video-feedback intervention to improve positive parenting (VIPP; N = 66), integrated measurement of parents’ N170 and LPP during pre- and post-intervention assessments, enabling rigorous examination of biomarkers of intervention response (Kolijn et al., 2020). Mothers’ N170s and LPPs were examined in response to images of children showing happy, angry, or neutral facial expressions. No intervention effects were found for mothers’ LPP, but mothers who received VIPP showed significantly smaller N170 amplitudes in response to all child emotion expressions, relative to the control group. This finding was interpreted as indicating that the VIPP led to more efficient processing of children’s facial cues (Kolijn et al., 2020). While this interpretation is in line with (non-parenting) ERP literature indicating that N170 amplitude is associated with level of effort, the authors also noted that it is inconsistent with previous studies of the N170 in parents, which suggests that larger N170 in response to emotional versus neutral infant faces is associated with more positive parent-related characteristics and behaviors (Bernard et al., 2015; Kuzava et al., 2020; Lowell et al., 2020). The authors noted several potential reasons for their results differing from the larger literature, including differences in the task, in the sample’s risk level, family compositions, and study designs (Kolijn et al., 2020). Perhaps most important to consider when interpreting these results in relation to previous parental N170 research is that the Kolijn et al. study was of a preventive intervention, and had a healthy, community sample as opposed to the clinically-referred or otherwise high-risk participants included in most other studies. Notably, another non-clinical, community-based study sample did not show relations between mothers’ parenting behavior and N170 or LPP differences based on infant emotion (results were found only when examining a latent profile of P200 and LPP; Kuzava et al., 2019). Together, these findings suggest that examination of N170 and LPP differentiation to different emotions is an important marker of parental responding primarily when considering higher-risk samples. Examining how the Kolijn and colleagues’ (2020) N170 result relates to other, non-ERP treatment outcome measures (e.g., behavioral tasks of executive functioning and observed parent-child interaction), which the RCT is equipped to do (Kolijn et al., 2017), may also clarify these mixed findings. Importantly, however, this study supports the use of ERP measures as biomarkers of change in response to a parenting intervention.

Intervention Studies and FAA.

In the more general, non-parenting literature, FAA has also been examined as a biomarker of response to intervention. Most clinical research studies employing FAA as a measure of treatment response examine resting asymmetry as an indicator of general affective style; these studies have reported mixed results. Some studies have shown treatment effects on resting EEG, including a study of mindfulness-based cognitive therapy for depression (Barnhofer et al., 2007), and one of cognitive behavioral therapy for social anxiety disorder (Moscovitch et al., 2011). Others, however, have found that patterns of resting right FAA persist irrespective of clinical remission of depression in response to mindfulness-based cognitive behavioral therapy (Keune et al., 2011) and behavioral activation treatment (Gollan et al., 2014). More relevant to clinical applications for parenting interventions—in which treatment targets parental responses to specific child behaviors—are studies that examine treatment-related changes in FAA in response to stimuli. For example, in a study of cognitive-behavioral therapy (CBT) for posttraumatic stress disorder from a motor vehicle accident (Rabe et al., 2008), individuals in the CBT group showed a significantly greater treatment-related decrease in right FAA in response to photos of a car wreck than those in the wait-list control group. This reduction in right asymmetry was associated with greater reduction in self-reported posttraumatic stress symptoms. To date, there have not been any studies of changes in parental FAA in response to clinical interventions. However, one group examined the impact of a single session of EEG biofeedback on undergraduate students’ (N = 15) alpha asymmetry in response to infant cries (Tyson, 1996; Tyson & Sobschak, 1994), although they focused on asymmetry over the parietal cortex, which is associated with emotion-related arousal (Nitschke et al., 2000). Women in the biofeedback group showed a significantly greater decrease in right parietal asymmetry than those in the control group, which was also associated with reductions in self-reported anxiety and arousal. These studies suggest that alpha asymmetry in response to treatment-relevant cues (e.g., trauma cues in Rabe et al., and parenting-related cues in Tyson et al.) may change in response to intervention, and thus may be beneficial to include in clinical research on parenting-related interventions.

Future Directions for Research on EEG Clinical Applications for Children and Families

Clinical research employing EEG suggests that both ERP and FAA can provide information about changes in brain activity that may occur over the course of intervention, as well as the neural correlates of more common measures of treatment-outcome (i.e., symptom rating scales). Yet, we are still far from the point of using EEG to inform day-to-day clinical care and decision-making. A longer-term—and more aspirational—goal of clinically-oriented parent EEG research would be to develop standards by which EEG biomarkers could actually be used in the clinical assessment and care of families who present to clinics in need of services to improve child or parental symptoms or family functioning.

This issue is not unique to parenting and family researchers, but is actively discussed in the larger field of EEG biomarkers. Most EEG research has not been designed with psychometric properties in mind (Hajcak et al., 2017), nor has it been geared toward establishing population-based norms (Imburgio et al., 2020) or sensitivity and specificity estimates (Loo et al., 2016) that are necessary to inform psychological assessment. This limits current clinical use of EEG in psychological assessment and treatment. Someday, it may be possible for child and family psychologists to include in their evaluations an EEG recording of parents while viewing or listening to their own child. The results could be taken into account along with other evaluation data (clinical interview, standardized rating scales, observations) to aid in case conceptualization and treatment recommendations. For example, for family in which a parent’s brain response is characterized by left frontal alpha hypoactivation or low Reward Positivity (RewP; a positive deflection that occurs over frontocentral sites approximately 250–300 ms after reward feedback) to child positive stimuli, perhaps dyadic treatment involving relationship enhancement would be recommended. As another example, a parent who exhibits lack of N170 or LPP discrimination to their child’s expressions of different emotions might benefit from a primary focus on emotion identification (for themselves and their child) and training in strategies to support their child’s emotion regulation skills. However, there is currently no established criteria to determine whether an individual parent’s FAA, RewP, N170, or LPP (or any other EEG measure, for that matter) is typical versus atypical. Nor do we have a lot of data on whether specific EEG measures are psychometrically sound.

Some research groups have started working to address some of these hurdles. In non-parenting EEG research, reliability estimates, including test-retest reliability and internal consistency, have been increasingly reported for both specific ERP components (Hajcak et al, 2017) and spectral power measures (Lenartowicz et al., 2019). Efforts have also begun to establish norms in young adult populations for specific ERP components shown to be related to common psychological disorders, including anxiety (the error-related negativity; Imburgio et al., 2020) and depression (the RewP; Hubert et al., 2020). Yet, much work remains to be done before EEG measures can be used in clinical practice, including standardization of tasks and methods for computing EEG scores, determination of cutoffs or thresholds for those scores, and establishment of sensitivity and specificity of those cutoffs in relation to diagnostic or prognostic accuracy (Olbrich & Arns, 2013).

Conclusion

We have highlighted the most promising EEG measures that have been used within the parenting literature. Although there are challenges to using EEG metrics in understanding parent responses and predicting parenting behavior, the foundations have been laid and a nascent literature, as reviewed above, has emerged. The rationale for using EEG measures is strong and early findings show promise. With further standardization of methods, novel approaches to assessing the time course of neural processes associated with parenting, and continued clinical translation of EEG as predictors of parenting behaviors, treatment biomarkers, or intervention targets, we believe that EEG measures can significantly strengthen our understanding of neural mechanisms underlying parenting behaviors, as well as potentially improve clinic-based services for parents and families.

Highlights:

• Most evidence-based interventions for children’s mental health problems require significant involvement of a parent or caregiver, and treatment programs are increasingly incorporating components targeting parents’ own self-regulation.

• There are many challenges in studying parents’ perception, cognition, and emotions within the context of parent-child interactions, during which parents must continually monitor the well-being and needs of both themselves and their children. In the context of treatment-seeking families, these interactions might be especially challenging and require parents’ own self-regulation in addition to helping their children regulate.

• EEG may be a particularly useful tool in the study of parenting, given its excellent time resolution and established associations with many of the perceptual, cognitive, and emotional processes that occur over the course of parent-child interactions.

• Both event-related potential (ERP) and frontal alpha asymmetry research have provided important information about parenting and related processes; future research may benefit from novel EEG metrics not yet used in studies of parenting, such as event-related time frequency analyses.

• Findings from EEG research with parents have potential to ultimately inform clinical work with children and families, such as identifying biomarkers that could aid in assessment, treatment recommendations, and monitoring response-to-interventions.