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. Author manuscript; available in PMC: 2026 Apr 28.
Published in final edited form as: Am Psychol. 2023 Jul 13;79(2):210–224. doi: 10.1037/amp0001173

Atypical Child-Parent Neural Synchrony is Linked to Negative Family Emotional Climate and Children’s Psychopathological Symptoms

Haowen Su 1,2,3, Christina B Young 4, Zhuo Rachel Han 5, Jianjie Xu 5, Bingsen Xiong 1,2,3, Jingyi Wang 1,2, Lei Hao 6, Zhi Yang 7, Gang Chen 8, Shaozheng Qin 1,2,3,9,*
PMCID: PMC13112604  NIHMSID: NIHMS2163630  PMID: 37439757

Abstract

Family emotional climate is fundamental to the wellbeing and mental health of children. Family environments filled with negative emotions may lead to increased psychopathological symptoms in the child through dysfunctional child-parent interactions. Single-brain paradigms have uncovered changes in brain systems and networks related to negative family environments, but how the neurobiological reciprocity between child and parent brains is associated with children’s psychopathological symptoms remains unknown. Here we first investigated the relationship between family emotional climate and children’s psychopathological symptoms in 395 child-parent dyads. Using a naturalistic movie-watching functional magnetic imaging technique in a subsample of 50 child-parent dyads, we further investigated the neurobiological underpinnings of how family emotional climates are associated with children’s psychopathological symptoms through child-parent neural synchrony. Children from negative family emotional climate experienced significantly more severe psychopathological symptoms. In comparison to child-stranger dyads, child-parent dyads exhibited higher inter-subject correlations in the dorsal and ventral portions of the medial prefrontal cortex (mPFC), and greater concordance of activity with widespread regions critical for socioemotional skills. Critically, negative family emotional climate was associated with decreased inter-subject functional correlation between the ventral-mPFC and the hippocampus during movie watching in child-parent dyads, which further accounted for higher children’s internalizing symptoms. Together, our findings provide insights into the neurobiological mechanisms that negative family environments can cause and maintain psychopathological symptoms in children through atypical child-parent neural synchrony. This has important implications into a better understanding about how child-parent connections may mediate the relation between environmental risks and developmental outcomes.

Keywords: family emotional climate, psychopathological symptoms, neural synchrony, naturalistic fMRI

Introduction

Children learn how to express and regulate their emotions through observing and modeling their parents’ emotional behaviors (Eisenberg, 2020; McCoy & Raver, 2011), highlighting the importance of family during early socialization. Family emotional climate, including how negative and positive emotions are expressed as well as how emotions impact parenting behaviors, has a large effect in shaping the emotional wellbeing and mental health of a child (Speidel et al., 2020). Research in psychology has recognized that family emotional climate, especially its negative aspects, can cause and maintain various psychopathological symptoms in children (Gong et al., 2021; Rea et al., 2020; Teicher et al., 2016).

Psychosocial views suggest that negative family emotional climates may lead to psychopathological symptoms in children by derailing the coordination of moment-to-moment behaviors between child-parent dyads (Feldman, 2020; Morris et al., 2018). Indeed, previous studies have demonstrated that negative family environments compromise the effectiveness of reciprocal interactions in child-parent dyads (Hoyniak et al., 2021a; Tarullo et al., 2017). Children who experience maladaptive family interactions with parents are prone to develop psychopathological symptoms later in life (Feldman, 2007; Quiñones-Camacho et al., 2021). According to a bio-behavioral synchrony model (Feldman, 2012), the reciprocal coordination of child-parent interactions contains various components such as behavior, autonomic response, hormones, and brain function. These components are closely associated with child developmental outcomes, likely because of shared representations and/or schema involving socioemotional experience, knowledge, values, and beliefs. Although well documented in behavioral (Thomassin & Suveg, 2014) and physiological studies (Davis et al., 2018), the underlying mechanisms of how family emotional climates impact psychopathological symptoms in children through altered reciprocal responses across child-parent brains remain largely unknown.

With a focus on cross-brain associations, an Extended Parent–Child Emotion Regulation Dynamics Model (Morris et al., 2018; Ratliff et al., 2022) proposes that parent-child brain-to-brain concordance is a key mechanism linking family systems (e.g., family emotional climate) to children’s psychopathological symptoms. Guided by this extended framework (Ratliff et al., 2022), researchers have conducted studies to understand how indicators of family environment associated with parent-child brain-to-brain concordance (e.g., interbrain synchrony, shared neural similarity) are associated with children’s psychopathological symptoms. Using functional near-infrared spectroscopy hyperscanning techniques, recent studies have demonstrated neural synchrony in the prefrontal cortex (PFC) across child-parent brains, which is critical for reciprocal interactions including cooperation (Reindl et al., 2018a), joint attention (Quiñones-Camacho et al., 2020), and smiling (Piazza et al., 2020). Family risk factors including parenting stress (Azhari et al., 2019), maternal stress (Nguyen et al., 2020), anxious attachment (Azhari et al., 2020), and sociodemographic risks (Hoyniak et al., 2021) could diminish child-parent shared neural response in the PFC. Moreover, disrupted child-parent prefrontal synchrony was associated with poor emotion regulation (Reindl et al., 2018a) and heightened irritability (Quiñones-Camacho et al., 2020) in typically developing children, as well as salient autism spectrum disorder (ASD) symptoms among children with ASD (Wang et al., 2019). These findings provide initial evidence suggesting that family risk factors may alter child-parent brain-to-brain concordance, which may then impede the development of socioemotional skills in children.

The transmission of shared mental representations of socioemotional experiences may also affect inter-subject concordance between child and parent brains even in the absence of real-time interactions. Children learn social and emotional skills through dyadic interactions with their parents, which can help form and maintain shared meanings or narratives of socioemotional experiences and knowledge in long-term memory (Feldman, 2007a; Fiske & Taylor, 2013). These processes require multiple brain regions and systems to interact and exchange information (Babiloni & Astolfi, 2014). Empirically, researchers have applied a dual-brain fMRI paradigm to examine the psychological function of shared neural responses (Lee et al., 2017, 2018). Lee et al. (2018) found that mother–child dyads with lower levels of family connectedness showed less similar neural response patterns in the anterior insular and dorsal anterior cingulate cortex (dACC), which then accounted for the adolescent’s perceived stress level during stress tasks. In addition, lower levels of whole-brain intrinsic functional connectome similarity were associated with poorer emotional competence in children, which might increase the risk of psychopathological symptoms (Lee et al., 2017). Although previous studies on shared neural responses identified the role of PFC, they were unable to examine deep brain regions such as the hippocampus due to spatial resolution limits of functional near-infrared spectroscopy and electroencephalogram techniques.

Brain systems involving the PFC and deep brain regions support our ability to learn from socioemotional interactions (Carpendale & Lewis, 2004). The mPFC, a core node of social and emotional networks, plays a critical role in transmitting shared socioemotional schema involving knowledge, values, and beliefs across individuals (Krueger et al., 2009a; Roy et al., 2012a). The dmPFC and vmPFC, two key portions of the human mPFC, are responsible for maintaining social and emotional knowledge (Krueger et al., 2009). The dmPFC enables individuals to extract the goals and intentions from others during social interactions (Wagner et al., 2016), and the vmPFC contributes to the social inference as well as self-related emotional experience and knowledge (Benoit et al., 2014). The disruptions of the mPFC systems have been linked to social and emotional dysfunctions in various psychiatric disorders such as anxiety and depression (Hiser & Koenigs, 2018). Beyond the mPFC systems, recent studies have demonstrated that the hippocampus works in concert with distinct portions of the mPFC allowing individuals to learn socio-emotional knowledge and experience through social interactions (Hiser & Koenigs, 2018; Yeshurun et al., 2021). It has been suggested that the mPFC and hippocampus allow individuals to integrate internal information (e.g., memory, experience, and beliefs) in order to respond to the external stimulus. Because they live in the same family environment, child-parent dyads often have reciprocal interactions during various social and emotional scenarios. Therefore, they tend to form shared internal representations to understand and respond to each other.

Methodologically, mapping brain-to-brain concordance has the potential to advance our understanding on how dyadic interactions between children and parents lead to shared socioemotional representations across brains (e.g., Reindl et al., 2018). Recent studies have used naturalistic movie watching fMRI to examine how individuals process and understand the complex socioemotional world based on our internal mental schema including long-term memory, emotion, and prior belief. This paradigm lends itself to inter-subject correlation (ISC) and inter-subject functional connectivity (ISFC), which quantifies brain activity concordance in cortical and subcortical regions across subjects during movie watching (Hasson et al., 2004; Simony et al., 2016). Therefore, these approaches compute functional activity concordance across brains, emerging as a powerful tool for exploring brain function and their neural synchrony across individuals. As such, this approach allows us to identify: 1) shared neural responses across child-parent brains during movie watching, and 2) child-parent dyadic brain predictors underlying the effects of family emotional climate on children’s psychopathological symptoms. Based on the Extended Parent–Child Emotion Regulation Dynamics Model (Ratliff et al., 2022), we hypothesized that child-parent dyads would exhibit increased brain-to-brain concordance in the mPFC and related functional circuits compared to control child-stranger dyads, and that amount of concordance would mediate the association between negative family emotional climate and children’s psychopathological symptoms. Notably, recent neurocognitive models of event segmentation posit that the hippocampus and vmPFC support the segmentation of boundaries among continuous events unfolding over time in a movie and integration of discrete events into meaningfully structured representations namely schema (Baldassano et al., 2017; Ben-Yakov & Henson, 2018; Ezzyat & Davachi, 2021). Our perception and process of such events are actively shaped by existing memories and schematic scripts about experiences in the world (Baldassano et al., 2018). Thus, we hypothesized that children would exhibit a similar pattern of hippocampal responses to during transitions between meaningful events (boundary timepoints) as their parents.

To test the above hypotheses, we conducted two separate studies integrating behavioral assessments of family emotional climate and children’s psychopathological symptoms, as well as dyad-based analysis of movie-watching fMRI data in child-parent and child-stranger dyads. In Study 1, we investigated how family emotional climate related to children’s psychopathological symptoms including internalizing and externalizing symptoms in 395 child-parent dyads (Figure. 1a). We assessed family emotional climate using a well-validated scale that characterizes how often positive and negative emotions are expressed in a family (Halberstadt et al., 1995a). Internalizing and externalizing symptoms were measured by a widely-used child behavior checklist (CBCL)(Achenbach, 1991). In Study 2, we used a child-friendly naturalistic movie-watching paradigm in an fMRI experiment known for its ecological validity (Vanderwal et al., 2019) to measure child-parent shared brain responses in a subsample of 50 child-parent dyads (Figure. 1b). Brain-to-brain concordance metrics in response to movie watching were assessed through ISC and ISFC methods. Given the correlational nature of dyad-based brain concordance, we used an optimized linear mixed effect model with crossed random effects to account for the complex data hierarchical structure (Chen et al., 2017) (Figure. 1c). Mediation analyses were used to examine if child-parent shared brain response accounts for the direct and/or indirect effects of negative family emotional climate on children’s internalizing and externalizing symptoms. Event segmentation analysis was implemented to explore whether children’s neural responses evoked by event boundaries were associated with their parents.

Figure 1: An Illustration of Experimental Design and Inter-Subject Correlation Analysis (ISC).

Figure 1:

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a. Correlations of negative (‘Neg’) and positive (‘Pos’) family emotional climate with children’s internalizing and externalizing symptoms respectively. The difference between the negative (top row) and positive (middle row) family emotional climate is shown with strong statistical evidence. b. Representative frames of a 6-min movie of a 7-year-old girl and her mother used as the movie-watching fMRI paradigm. An illustration of voxel-wise ISC between two time series of a child-parent dyad for each voxel of the grey matter mask. c. A matrix represents pairwise correlations among child and parent subjects, resulting in child-parent dyads (CP, red), child-stranger controls (CS, blue), child-child & parent-parent pairs (CC/PP, grey). Each cell represents a ISC value. *, q < 0.05; **, q < 0.01.

Methods and Materials

Participants and Procedure.

In Study 1, we recruited 446 families (Children ages 6–12) to participated in behavioral measurements of family emotional climate and children’s psychopathological symptoms. Of them, a subsample of Study 1 (50 child-parent dyads, N = 100 subjects) underwent MRI scanning in Study 2. After removing participants with missing values (missing > 20%) in behavioral measures including CBCL and FEQ questionnaire, data of 395 child-parent dyads (children: mean ± S.D. = 9.35 ± 1.64 years old, range 6.28-12.51, 22 boys; parents: mean ± S.D. = 37.42 ± 4.62 years old, range = 27-57, 12 fathers) were analyzed in the correlation between family emotional climate and child’s psychopathological symptoms. All participants had normal or corrected-to-normal vision, and no one reported a history of psychiatric or neurobiological disorders and developmental delays (e.g., language comprehension difficulties, attention difficulties) that would impact their ability to follow the instructions of tasks and the content of videos.

A subset of 50 child-parent dyads completed fMRI scanning while watching a movie clip in Study 2. Nine child-parent dyads were excluded due to children’s head motion with mean framewise displacement larger than 0.5 mm during movie-watching scanning. The final sample consists of 41 child-parent dyads (children: mean ± S.D. = 10.15 ± 1.41 years old, range 7–12 years old, 46.3% boys; parents: mean ± S.D. = 38.91 ± 5.34 years old, range=29–49 years old, 24.4% father). Six child-parent dyads were further excluded for the mediation analyses due to the incomplete family emotional expressiveness questionnaires, and 35 child-parent dyads were included in the mediation analysis. Control analysis was also conducted for resting-state fMRI data to examine whether the observed shared responses in child-parent dyads are specific to the naturalistic paradigm. After excluding subjects with mean framewise displacement larger than 0.5 mm, data of 25 pairs of children and parents were analyzed in the ISC and ISFC (children: mean ± S.D. = 7.8 ± 1.33 years old, range 7.80–2.26 years old, 40% boys; parents: mean ± S.D. = 39.31 ± 5.51 years old, range=29–49 years old, 16% father). All subjects provided written informed consent before their participation and received monetary compensation. The study was approved by the Institutional Review Board (IRB) of the local institute. The schematic view of participants selection is provided in Supplementary Figure. S1.

Materials

Movie Watching

A 6-minute video unfamiliar to all participants was shot for this study, which showed a 7-year-old girl arguing with her mother (Figure. 1b). Critical moments are provided in Table S1. Children and their parents underwent fMRI when separately viewing the video. This video was played with no sound/subtitles to mitigate potential confounds in auditory perception and language comprehension.

Psychopathological Symptoms Assessment

Children’s psychopathological symptoms were assessed by the parent-reported CBCL scores based on parent surveys (Achenbach, 1991), including anxious/depressed syndrome withdrawn/depressed syndrome, somatic, score and rule-breaking, internalizing and externalizing score. The Chinese version of the CBCL has been widely used (Crijnen et al., 1999). The internal consistency of the parent-reported CBCL scales in the present study was α = 0.81 for internalizing symptoms and α = 0.84 for externalizing symptoms. The raw scores of all sub-scales were used in all analyses.

Family Emotional Climate Assessment

Family emotion climate was measured by the Family Expressiveness Questionnaire (EFQ) (Halberstadt et al., 1995b). Parents reported how often positive and negative emotions were expressed in their family on a 9-point Likert scale. Coefficient alphas in the present sample were 0.89 and 0.85 for the positive and negative subscales.

Family Socioeconomic Status Assessment

Family socioeconomic status was measured by a self-report family background questionnaire that used 10- and 6-point scales to assess the education and monthly income of each parent respectively. To form a composite SES score for each parent, the income and education scores were first divided into individual z scores for each parent, which were then averaged.

Brain Imaging Data Acquisition

Whole-brain images were acquired from Siemens 3.0 T scanner (Siemens Magnetom Trio TIM, Erlangen, Germany), using a 12-channel head coil with a T2*-sensitive echo-planar imaging (EPI) sequence based on blood oxygenation level-dependent (BOLD) contrast. Thirty-three axial slices (4 mm thickness, 0.6 mm skip) parallel to the anterior and posterior commissure (AC-PC) line and covering the whole brain. Each participant’s high-resolution anatomical images were acquired through three-dimensional sagittal T1-weighted magnetization-prepared rapid gradient echo (MPRGE) with a total of 192 slices (TR 2530 ms, TE 3.45 ms, FA 9°, inversion time (TI) 1100ms, voxel size 1.0 x 1.0 x 1.0 mm3, acquisition matrix 256 × 256, FOV 256 × 256 mm2, BW 190Hz/Px, slice thickness 1 mm). Seventeen child-parent dyads scanned at site 1 and the remaining 24 child-parent dyads were scanned at site 2, and sites were included into statistical analyses as a covariate of no interest. Both scanners were 3.0T Trio TIM with the same types of head coils and sequence parameters.

Brain Imaging Data Analysis

Preprocessing

Based on previous studies on ISC pre-processing pipelines (Nastase et al., 2019), brain images were preprocessed using statistical parametric mapping (SPM12). Images were corrected for slice acquisition timing and realigned for head motion correction. Subsequently, functional images were co-registered to each participant’s gray matter image segmented from corresponding T1-weighted image, then spatially normalized into a common stereotactic MNI space and resampled into 2-mm isotropic voxels. Images were smoothed by an isotropic 3D gaussian kernel with 6-mm full-width half-maximum (FWHM). The preprocessed images were regressed on a set of nuisance covariates (i.e., motion parameters, the average signal of white matter and cerebrospinal fluid) and 140-sec high-pass filtered using toolbox Nilearn version 0.6.2. Finally, the first 5 volumes and the last 5 ones were removed to minimize stimulus onset and offset effects and the data were z-scored overtime.

Inter-Subject Correlation (ISC) and Statistical Analysis

Whole-brain ISC maps during movie watching were computed for all possible pairs of 41 participants in a gray-matter mask using BrainIAK’s ISC function (Kumar et al., 2020) (Figure 1b). The ISC maps were submitted to further statistical analyses to identify brain regions that show synchronous (shared) neural response across the whole sample. We adopted a linear mixed-effects (LME) model using a crossed random-effects formulation which can accurately interpret the ISC data’s correlation structure (Chen et al., 2017). Participants’ gender, age, and two scanning sites were treated as covariates of no interest in the LME model. False discovery rate (FDR) correction was used to correct multiple comparisons (Benjamini & Hochberg, 1995). Next, we used a two-group formulation of the LME model with three covariates (age, gender, and site) to identify whether brain systems were more synchronous in child-parent dyads than child-stranger pairs. Child-parent dyads were defined by pairing a child and their own parent, and child-stranger dyads were generated by pairing a child with all parents except their own parent. 3dClustSim module of AFNI was used to correct multiple comparisons, with a voxel-wise p < 0.001, cluster-wise < 0.05. We also performed the parallel analysis in resting fMRI dataset to detect child-parent shared neural responses.

Inter-Subject Functional Connectivity (ISFC) Analysis

The ISFC analysis was implemented to identify movie-evoked functional connectivity across participants. We used a seed-based ISFC approach by computing the correlation of a given seed’s [i.e., 6-mm sphere of the peak voxel at MNI coordinate (2, 38, −18) in the vmPFC and (0,56,12) in the dmPFC] time series in one participant with every other voxel’s time series in another participant. The computation of ISFC produced two asymmetric matrices and for r(vmPFCsubject1,Ysubject2) and r(vmPFCsubject2,Ysubject1). We then computed the average correlation, which was treated as the ISFC value between each participant pair where r represents Pearson’s correlation and Y represents time series of each given voxel from participants. Likewise, the LME was used to determine which brain regions showed higher coordination with vmPFC and dmPFC in child-parent pairs than child-stranger pairs. False discovery rate (FDR) was used to correct multiple comparisons.

Intra-Subject Functional Connectivity (FC) Analysis

To verify that child-parent vmPFC-hippocampal ISFC played a unique role in the relationship between negative family emotional climate and children’s internalizing problem, we also examined whether the single-brain’s vmPFC-seeded FC is associated with negative family emotional climate and children’s internalizing symptoms. We examined single-brain FC in children’s and parent’s brains, and ran multiple regressions with negative family emotional climate and children’s internalizing symptoms, as separate regressors, predicting vmPFC-seeded FC. Other settings are identical for above ISFC.

Meta-Analytic Decoding with Neurosynth

The neurosynth allows us infer the psychological domains involved in brain map of the shared vmPFC-circuits in child-parent dyads. Specifically, we correlated the thresholded child-parent vmPFC- and dmPFC-based ISFC map (FDR q < 0.05) to the topics map of 15 general psychological domains involving a range of possible brain processes during movie viewing using the Neurosynth’s python notebook (https://github.com/neurosynth/neurosynth; commit version 948ce7).

Mediation Analysis

Mediation analysis was performed using the Mediation Toolbox developed by Tor Wager’s group (https://github.com/canlab/MediationToolbox). Prior to the mediation analysis, average values representing inter-subject functional connectivity strength with the vmPFC and dmPFC were extracted from significant clusters identified in the above linear mixed model to examine the correlation with negative family emotional climate using FDR corrections to control the false-positives. Next, a mediation model was constructed to investigate the mediating pathways between negative family emotional climate, shared vmPFC-hippocampus ISFC strength, and children’s internalizing symptoms especially anxiety/depressed aspects. The indirect or mediated effect was tested by a bias-corrected bootstrapping method (n = 10000 resamples). All statistical tests here are two-tailed and pass the FDR correction. More details are provided in SI.

Event Boundary Analysis

Event boundaries were collected by an independent group of 20 adult raters (10 males) who watched the same 6-minute silent video. The rates were asked to press a key at the end of one meaningful event and the beginning of another. In line with one previous study (Reagh et al., 2020), we included the boundary timepoints and non-boundary timepoints of this video. Boundaries timepoints were agreed by at least half of the samples, and we found a total of 10 event boundaries of the time series. The onset times of boundary and non-boundary events were next convolved with a canonical HRF to obtain the boundary and non-boundary timeseries. Then, we correlated each participant’s hippocampal and vmPFC timeseries with the event boundary and non-boundary timeseries. Finally, we computed spearman correlation coefficients between children’s hippocampal and vmPFC responses to boundary and non-boundary timeseries while controlling children’s age, gender and sites of no interest.

Results

Negative Family Emotional Climate Linked to Children’s Psychopathological Symptoms

First, we examined how family emotional climate, including positive and negative components was associated with children’s psychopathological (i.e., internalizing, externalizing) symptoms in Study 1. Pearson’s correlation analyses revealed that negative family emotional climate was associated with more severe children’s internalizing symptoms (r = 0.17, q < 0.001, 95% CI = [0.08, 0.26]), including anxious/depressed (r = 0.13, q = 0.024, 95% CI = [0.03, 0.22]), withdrawn/depressed (r = 0.16, q = 0.005, 95% CI = [0.07, 0.25]), and somatic symptoms (r = 0.13, q < 0.001, 95% CI = [0.04, 0.22]), as well as externalizing symptoms (r = 0.23, q < 0.001, 95% CI = [0.14, 0.32]), including aggressive (r = 0.24, q < 0.001, 95% CI = [0.07, 0.24]) and rule-breaking behaviors (r = 0.15, q = 0 .001, 95% CI = [0.14, 0.32]) (all q values were FDR corrected) (Figure. 1a). There were no reliable associations of positive family emotional climate with children’s internalizing and externalizing symptoms (all rs < 0.01, qs > 0.70). Further tests for Fisher’s z-transformed correlation coefficients revealed statistically stronger correlations with negative than positive family emotional climate (all Zs > 1.95, qs < 0.05, FDR corrected). Notably, the positive associations of negative family emotional climate with children’s internalizing and externalizing symptoms remained significant even after controlling for child’s and parent’s age, gender, and socioeconomic status (Supplementary Figure S2). These results indicate that children from negative family environment exhibit more severe internalizing and externalizing symptoms.

Increased Inter-Subject Neural Synchrony in the mPFC during Movie Watching for Child-Parent Dyads

Next, we identified inter-subject shared patterns of temporal neural activity in response to viewing a movie across brains. The ISC maps were computed to represent shared brain activity by correlating time series of the same voxel across participants (Figure. 2a). A linear mixed-effects (LME) model was conducted for ISC maps collapsing across children and parents to identify brain regions showing inter-subject synchrony during movie watching. This analysis revealed significant clusters in unimodal and transmodal association areas (Figure. 2b, q < 0.05 FDR-corrected). This pattern of results is consistent with ISC data from previous fMRI studies (Finn et al., 2018; Hasson et al., 2004).

Figure 2: Primary Results from Inter-Subject Correlation (ISC) Analysis.

Figure 2:

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a. An illustration of inter-subject correlation (ISC) between time series of a given voxel in each child and his/her parent’s brain. b. Brain regions show statistically significant ISC during movie watching in general, with prominent effect in the posterior visual cortex followed by frontal, temporal, and parietal cortices. Statistically significant clusters were thresholded using q < 0.05 FDR corrected. The color bar represents Fisher’s Z-value. c. Representative views of the vmPFC and dmPFC showing stronger inter-subject synchronized activity (ISC) in child-parent dyads as compared to child-stranger controls. Significant clusters were derived from a contrast between child-parent (CP) dyads and child-stranger (CS) controls, with a voxel-wise threshold p < 0.001 (two-tailed) combined with cluster-level threshold significance level α of 0.05 corrected for multiple comparisons.

We conducted dyad-based analysis using ISC maps between each child and their parent in comparison to each child and all stranger’s parents as a control. We implemented an optimized LME model with crossed random effects (Chen et al., 2017), and examined brain systems showing shared temporal neural responses during movie watching unique to child-parent dyads relative to child-stranger controls. This analysis (Figure. 2c, Supplementary Table S3) revealed significant clusters (voxel-wise p < 0.001 two-tailed, cluster-wise significance level < 0.05) in the ventral mPFC (vmPFC) [peak MNI coordinate at (2,38, −18); cluster size k = 116 voxels] and the dorsal mPFC (dmPFC) [peak at (0, 52, 12), k = 122 voxels]. There were no significant clusters when examining greater activity in child-stranger versus child-parent dyads. To verify whether this effect is specific to movie stimulus, we also performed parallel analysis for resting-state fMRI data from 25 child-parent dyads, and there were no statistically reliable ISC effects in the vmPFC and dmPFC(Supplementary Table S5).

Increased Child-Parent vmPFC Connectivity with Social and Emotional Systems during Movie Watching

Given that mPFC-centric circuitry is implicated in human emotion and social cognition (Krueger et al., 2009b; Lieberman et al., 2019), we used the vmPFC and dmPFC clusters identified above as separate seeds to perform inter-subject functional connectivity analyses. The LME model for the vmPFC-seeded ISFC map was examined to identify functional circuits showing higher inter-subject connectivity in child-parent versus child-stranger dyads (Figure 3a). This analysis revealed significant clusters in widespread regions in the frontal, temporal and occipital lobes, including the hippocampus [peak MNI coordinates (−16, −30, −8)], amygdala [peak MNI coordinates (18,2, −16)], and fusiform gyrus [peak MNI coordinates (−32, −48, −8)], FDR q < 0.05 (Figure 3b–d, Supplementary Table S4). Parallel analysis for dmPFC-seeded ISFC maps revealed that child-parent dyads exhibited higher connectivity with the angular gyrus [peak MNI coordinates (−46, −64, 24)] and medial prefrontal gyrus [peak MNI coordinates (0,54,14)] than child-stranger dyads (Supplementary Figure. S3a, Table S4) (FDR q < 0.05). To verify whether this effect is specific to movie watching, we also performed parallel analysis for resting-state fMRI data, and there were no any reliable ISFC effects in child-parent dyads compared to child-stranger controls.

Figure 3: Results from Inter-Subject Functional Connectivity (ISFC) Analysis and Meta-decoding by the Neurosynth.

Figure 3:

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a. An illustration of seed-based ISFC that involves computing the correlation between a seed’s time series in a child brain and all other voxel’s time series of his/her parent brain. b. Compared to child-stranger control dyads, child-parent dyads showed stronger ISFC of the vmPFC with the inferior frontal gyrus, middle cingulum gyrus, precuneus, fusiform, hippocampus and middle occipital gyrus (q < 0.05 FDR corrected). c. Word cloud depicting commonly used terminology associated with regions showing vmPFC connectivity. d. Representative slices of significant clusters in the hippocampus, amygdala and precuneus that show stronger ISFC in child-parent dyads than child-stranger control dyads.

We then used a meta-analytic decoding approach based on a widely used Neurosynth platform (Yarkoni et al., 2011) to determine psychological functions of the above clusters that showed higher inter-subject connectivity with the vmPFC and dmPFC in child-parent than child-stranger dyads. This analysis revealed that child-parent shared vmPFC-based connectivity patterns with widespread regions that are implicated in episodic memory, emotion, and social functions (Figure. 3c), whereas the dmPFC-based connectivity did not exhibit a connectivity pattern implicated in these functions (Supplementary Figure. S3c). These results indicate higher vmPFC connectivity with social and emotional systems in child-parent dyads than child-stranger controls.

Reduced Child-Parent vmPFC Connectivity with the Hippocampus Links to Negative Family Emotional Climate and Children’s Internalizing Symptoms

Given our central hypothesis at issue, we further investigated how negative family emotional climate alters inter-subject correlation of brain activity and connectivity during movie watching in child-parent dyads, and whether such alteration was then associated with children’s psychopathological symptoms. Brain-behavior association analyses were conducted for ISC and ISFC metrics of the vmPFC and dmPFC. With these metrics, we found that negative family emotional climate was significantly correlated with lower child-parent shared vmPFC connectivity with the left hippocampus (Figure. 4b) and right precuneus (q = 0.03, FDR corrected; Supplementary Table S4). Next, we observed a negative correlation of child-parent vmPFC-hippocampal functional connectivity with children’s internalizing symptoms (r = −0.41, q = 0.04, FDR correction). Further analyses indicate that the aforementioned association is mainly driven by the association between functional connectivity and anxious/depressed symptoms (r = −0.43, q = 0.03, FDR correction).

Figure 4. Reduced Inter-subject Neural Functional Connectivity in Child-parent dyads Links to Negative Family Emotional Climate, and Internalizing Symptoms.

Figure 4

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a. Representative view of the vmPFC seed and its intra-subject and inter-subject connectivity with the hippocampus. b. Scatter plots depict the negative correlations (FDR corrected) of inter-subject vmPFC-hippocampal connectivity (red) with negative family emotional climate and children’s anxious/depressed symptoms. This pattern is not observed using intra-subject vmPFC-hippocampal connectivity (gray). c. A mediation model depicts the indirect pathway of negative family emotional climate on children’s interlizing symptoms via the shared vmPFC-hippocampal inter-subject connectivity. Standardized coefficients are depicted. The solid lines represent statistically significant effect. Notes: *q < 0.05. All statistical tests here are two-tailed and pass the FDR correction.

Since child-parent vmPFC-hippocampal connectivity was associated with both negative family emotional climate and children’s internalizing symptoms, we then conducted a mediation analysis to examine whether this inter-subject functional connectivity pathway accounts for the association between negative family emotional climate and children’s internalizing symptoms. This analysis revealed an indirect pathway of reduced vmPFC connectivity with the hippocampus mediating the association between negative family emotional climate and higher children’s internalizing symptoms (Figure 4c, B = 0.17, SE = 0.10, p = 0.028, bootstrapped 95% CI = [0.01,0.42], 56.7% of the total effect size) and children’s anxious/depressed symptoms (B = 0.19, SE = 0.12, p = 0.04, bootstrapped 95% CI = [0.00,0.46], 59.4% of the total effect size). Notably, the mediation effect was significant even when regressing out child-parent’s age and gender (Supplementary Figure. S4b). Since children’s emotional symptoms may also have the possibility of influencing family emotional climate (Rothenberg et al., 2020), we tested an alternative model with children’s internalizing symptoms as input variable and negative family emotional climate as an outcome predictor. Although this model is also valid (Supplementary Figure S4c&d), model comparison with Bayesian Information Criterion (BIC) favors the initial model with family emotional climate affecting child internalizing symptoms (BIC = 113.89) over the reverse alternative model (BIC = 228.34) (Raftery, 1995).

To verify whether negative family emotional climate is associated with children’s internalizing symptoms through shared rather than each individual’s vmPFC-hippocampus responses, we performed vmPFC-seeded functional connectivity within children’s brains (Figure 4a). We did not find any reliable effects pertaining to intra-brain metrics (Figure 4b). In addition, we conducted time-lagged analysis for vmPFC-based ISFC to determine when child-parent dyads exhibited the highest ISFC. This analysis revealed that child-parent dyads exhibited highest vmPFC-hippocampal functional correlation at lag zero (Supplementary Figure. S4). Together, these results indicate that reduced child-parent vmPFC connectivity with the hippocampus accounts for the adverse effects of negative family emotional climate on children’s internalizing symptoms.

Child-Parent vmPFC and Hippocampal Activity Concordance in Event Boundaries during Movie Watching

To test our hypothesis on a shared pattern of neural responses to event boundaries in child-parental dyads, we investigated whether children’s neural responses evoked by boundary versus non-boundary events are similar to their parents. We therefore implemented a dyad-based analysis of brain responses to event segmentation during movie watching to examine whether children’s hippocampal and vmPFC responses to event boundary and non-boundary timepoints are correlated with their parents. As expected, this analysis revealed that children’s hippocampal responses to event boundaries were indeed positively associated with their parent’s responses (r = 0.42, p = 0.008, 95% CI = [0.11,0.65]). This concordance, however, did not emerge for non-boundary time points (r = −0.06 p = 0.703, 95% CI = [−0.38, 0.26]). Further Z-test analysis for two correlation coefficients revealed a significant difference (Z = 2.30, p = 0.01). Interestingly, a parallel analysis revealed an opposite pattern of child-parent concordance for the vmPFC activity. That is, children’s vmPFC responses to non-boundary timepoints were positively correlated with their parents (r = 0.33, p = 0.042, 95% CI = [0.01, 0.59]) but not for event boundaries (r = 0.05, p = 0.75, 95% CI = [−0.27, 0.37]). Further tests revealed a marginally significant difference between the two correlations (Z = −1.39, p = 0.08). Taken together, these results indicate that the vmPFC and hippocampus exhibit interactive activity concordance in child-parent dyads in response to non-boundary and boundary events during movie watching.

Discussion

In this study, we investigated the neural substrates of how negative family emotional climate was associated with children’s psychopathological symptoms by quantifying concordance between child-parent brain-to-brain activity and connectivity during naturalistic movie watching. Compared to child-stranger dyads, child-parent dyads exhibited higher inter-subject correlation in the vmPFC and dmPFC during movie watching, and higher inter-subject connectivity of the vmPFC with widespread regions critical for socioemotional cognition. Critically, reduced child-parent vmPFC-hippocampal connectivity accounted for the association between negative family emotional climate and children’s internalizing symptoms, with the vmPFC and hippocampus exhibiting higher child-parent activity concordance to non-boundary and boundary events, respectively. Our findings provide a neurobehavioral model of how negative family emotional climate is associated with children’s internalizing symptoms through reduced child-parent brain-to-brain concordance in the vmPFC-hippocampal circuitry.

Behaviorally, children in negative family emotional climate experienced more severe internalizing and externalizing symptoms. This is in line with previous findings showing positive associations between family risk factors (e.g., maternal maltreatment, family conflicts) and internalizing and externalizing symptoms in children (Gong et al., 2021; Schleider & Weisz, 2017). According to social learning and bio-behavioral synchrony models (Feldman, 2020; Justyna, 2017), child-parent shared experiences are indispensable for children to learn emotional skills as they socialize with their parents in daily life. Through child-parent reciprocal interactions such as affective synchrony and empathic dialogues, for instance, children regulate themselves to attune to each other’s minds. This helps them develop socioemotional skills such as emotion regulation and theory of mind, which then reduces the risk of suffering psychopathological symptoms (Feldman, 2020; Thomassin & Suveg, 2014).

Socioemotional interactions in a family have also been demonstrated to help child-parent dyads build a shared or synchronous pattern of brain responses (Piazza et al., 2020; Wass et al., 2020). Such shared neural responses can help children learn and form socioemotional kills through reciprocal interactions with their parents in daily life (Reindl et al., 2018b), which in turn serves as a scaffold for future socialization. Conversely, negative family emotional climate may impede child-parent brains from forming effective socioemotional skills, contributing to the emergence of children’s psychopathological symptoms. As discussed below, this account is supported by three aspects of our observed concordance across child-parent brains.

First, our movie-watching fMRI results show that children-parent dyads exhibited higher inter-subject correlation in the vmPFC and dmPFC during movie watching than control child-stranger dyads. This is reminiscent of previous findings showing that the mPFC plays a critical role in characterizing shared neurocognitive processes between children and their parents (Hoyniak et al., 2021a; Itahashi et al., 2020; Piazza et al., 2020). The mPFC is thought to act as a simulator for socioemotional schema that allow us to integrate and summarize social, self and emotional information as events unfold over time (Krueger et al., 2009a). When processing socioemotional events, the dmPFC is important for inferring other’s goal-oriented actions, whereas the vmPFC is crucial for appraisal, evaluation and regulation of values involved in self and affective processes (Bzdok et al., 2013). Such processes could serve as a neurocognitive basis for understanding the intentions and mental states of others (Fiske & Taylor, 2013). Thus, higher inter-subject correlation in the dmPFC and vmPFC across child-parent dyads likely reflect that similar strategies might be employed to perceive and integrate external information with existing knowledge to construct meanings or narratives as continuous events unfold over time during movie watching.

Second, our results also show that child-parent dyads exhibited higher inter-subject correlation of vmPFC- and dmPFC-based functional connectivity with widespread regions of social and emotional brain networks in comparison with child-stranger dyads. Specifically, child-parent dyads shared vmPFC coupling with distributed regions crucial for episodic memory, emotion and social processing (Lieberman et al., 2019; Phillips et al., 2019), while shared dmPFC coupling had relatively uniform connectivity with regions such as TPJ during movie watching. These inferences were drawn from a widely used reverse inference database (Yarkoni et al., 2011). The vmPFC and its coordination with the hippocampus, precuneus, and amygdala are recognized to support the appraisal of perceived socioemotional events (Hiser & Koenigs, 2018) and the reinstatement of existing knowledge and strategies formed over the course of child-parent interactions (Feldman, 2015, 2017). These processes help children learn how to cope with negative emotions (Nawa & Ando, 2019; Roy et al., 2012b). Our data suggest that vmPFC circuitry is critical for integration of disparate events shared by child-parent dyads when viewing emotional movies, likely by promoting transmission of affectivity and sociality across child-parent dyads.

Third, our fMRI results showed that reduced child-parent brain-to-brain concordance in the vmPFC-hippocampal pathway mediated the association between negative family emotional climate and more severe child internalizing symptoms. This finding provides one of the first pieces of empirical evidence for the Extended Parent–Child Emotion Regulation Dynamics Model (Ratliff et al., 2022), showing that cross-brain connectivity between child and parent serves as an important mechanism linking family environment with child emotional development. The vmPFC-hippocampal circuitry may be important for constructing the meaning of emotional events (Nawa & Ando, 2019; Roy et al., 2012b). Both these regions are part of the default mode network, which is s an active and dynamic ‘sense-making’ network that integrates incoming information with existing memory and knowledge to form internal context-dependent models (namely schema) of events as they unfold over time (Hasson et al., 2012; Yeshurun et al., 2021). Child-parent concordance of vmPFC-hippocampal coupling during movie-watching likely reflects their co-construction of socioemotional events according to shared and/or embodied relationships. It is possible that children with higher parental concordance of vmPFC-hippocampal connectivity may develop better socioemotional skills and thus exhibit lower levels of internalizing symptoms. Our observed mediation effect suggests that child-parent vmPFC-hippocampal concordance could serve as a potential biomarker for children in families with emotional disorders. Future work may use neurofeedback techniques to explore the impact of upregulating vmPFC-hippocampus coordination with parents on children’s emotional health.

The vmPFC-hippocampal circuitry is also crucial in updating and integrating new events into existing memory schemas (Gilboa & Marlatte, 2017; Zeithamova et al., 2012). Analysis of event boundary-evoked response revealed that children’s hippocampal responses to event boundaries were positively related to their parent’s responses. Given that segmenting continuous events into meaning units is driven by our experience and mental schemas (Baldassano et al., 2018), child-parent concordance on hippocampal activity during boundary-evoked responses suggests that child-parent dyads utilize their shared episodic memories and schemas to understand and interpret socioemotional events during movie watching. Together with stronger inter-subject vmPFC-hippocampal connectivity observed in child-parent dyads, our results are among the first to suggest that the vmPFC may signal child-parent concordance of hippocampal activity in order to orchestrate long-term memory, emotional and social systems to support their understanding of events during movie watching. However, the event-boundary analysis is a preliminary result to characterize child-parent neural responses to boundary and non-boundary events. Further studies with more optimal task designs are required to investigate the cognitive mechanisms involved in child-parent shared neural response.

Several limitations should be considered in our study. First, we assessed child-parent neural concordance at activity and connectivity levels when viewing a movie showing a girl arguing with her mother. Whether our findings can be generalized into other types of situations remains open for future studies. Second, although we leveraged a naturalistic movie-watching fMRI paradigm, dedicated task designs are needed to complement the interpretation of child-parent shared neural responses in vmPFC and related circuits. Specifically, we did not manipulate child-parent socioemotional events during movie watching. Future studies with optimal task design and manipulations are required to directly assess shared neural representations during socioemotional experiences in child-parent dyads. Third, it is worth noting that we also observed the indirect effect of child-parent shared brain responses in the association of negative family emotional climate with children’s internalizing symptoms. It is thus possible that such relationships are bidirectional (Gong et al., 2021; Nelemans et al., 2020). Longitudinal designs are required to disentangle the directionality effects. Fourth, our study did not have a sufficient sample size to examine potential sex-based (e.g., father-son dyads, mother-daughter dyads, etc.). There may be important sex-specific associations between shared neural response and psychopathological symptoms in children given different parenting roles (Cabrera et al., 2018).

Conclusion

The present study demonstrates brain-to-brain concordance across child-parent dyads during movie watching that was localized to the mPFC and its connectivity with regions in socioemotional networks. Inter-brain concordance in ventral mPFC-hippocampal circuitry, rather than intra-brain metrics, emerged as a key locus that mediates the adverse effect of negative family environment on children’s internalizing symptoms. Our study provides a neurobiological account for how negative family environment influences children’s internalizing symptoms through shared socioemotional representations across brains in child-parent dyads. This work can inform the development of dyad-based prevention and interventions designed to mitigate children’s internalizing symptoms.

Supplementary Material

Supplementary Material

Figure 5. Child-Parent Hippocampal and vmPFC Activity Concordance in Response to Boundary and Non-boundary Events.

Figure 5

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a. An illustration of boundary and non-boundary events for major episodic events during movie watching. b. Child-parent dyads showed higher vmPFC-hippocampus functional coupling during movie watching, and their vmPFC and hippocampal activity concordance were modulated by segmentation of event boundaries. The magenta and green lines represent expected signals of event boundaries and non-boundaries respectively. The yellow and red lines represent neural signals in children and parents separately. c. Child-parent vmPFC activity concordance was marginally significantly lower for boundary than non-boundary time series (Z = −1.39, p = 0.08). d. Child-parent hippocampal activity concordance was significantly higher for boundary than non-boundary event time series (Z = 2.30, p = 0.01).

Significance Statement:

Our study provides a neurobiological account of how negative family emotional climate influences children’s internalizing symptoms through altered s brain-to-brain concordance in child-parent dyads. This work can inform dyad-based prevention and intervention strategies to improve children’s psychological wellbeing.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (grant nos. 32130045, 31522028, and 82021004), and the Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning (grant no. CNLZD1503)

Footnotes

Competing Interests

The authors declare that they have no competing interests.

Data and codes Availability

The raw data supporting the findings of this study are available from the corresponding author on request. All the necessary data and codes are available from https://osf.io/c2gjk/?view_only=ca36371395c14902b0842a34664f53fd

All the necessary behavioral and brain imaging data and codes are available from https://github.com/QinBrainLab/2022_ChildParent_MovieWatching.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material
NIHMS2163630-supplement-Supplementary_Material.docx (1.6MB, docx)

Data Availability Statement

The raw data supporting the findings of this study are available from the corresponding author on request. All the necessary data and codes are available from https://osf.io/c2gjk/?view_only=ca36371395c14902b0842a34664f53fd

All the necessary behavioral and brain imaging data and codes are available from https://github.com/QinBrainLab/2022_ChildParent_MovieWatching.

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