Participants

A total of 31 mother-child dyads (13 girls, 18 boys) were recruited through online forums and social media groups (Mean age of mothers = 34.9 years, ±4.16 years; Mean age of children = 41.6 months, ±6.1 months). Mothers were required to be above 21 years of age with a biological child between the ages of 36 and 48 months at recruitment. Both mother and child had to be residing in Singapore and must not suffer from severe cognitive deficits, visual or hearing impairments, or major diseases that could prevent them from understanding and responding to the experimental tasks. Informed consent was obtained from all participants (or their mother in case of minors) prior to the start of the study, and each dyad was remunerated on completion of the study. All methods were performed in accordance with the relevant guidelines and regulations and the study was approved by the Institutional Review Board of Nanyang Technological University. All data are available at this URL: https://doi.org/10.21979/N9/CTR0YX.

Experimental procedure

In the first part of the study, mothers completed home-based online questionnaires which included demographic questions and a 36-item Parenting Stress Index - Short Form (PSI-SF)19, used to examine the perceived total stress that a mother has with regard to her parenting. In the second part of the study, each dyad was randomly assigned to one of six video sequences prior to the start of an fNIRS experiment. Upon entering the child-friendly laboratory, a research assistant explained the entire task to the mother, after which the researcher directed the dyad into an experimental room. The mother sat on a chair while her child sat on her lap throughout the experiment (Fig. 1). NIRS caps of appropriate sizes were placed on the heads of mother and child and recording was conducted in a tandem hyperscanning mode. A short 1-min video clip from the movie ‘Moana’ was screened as a distraction while the NIRS devices were set up. After the caps were in place, the optodes were adjusted to optimise signal quality. The video was screened on a laptop that was placed at the centre of the table at a distance of 40 cm from the dyad. Once the video and fNIRS data-recording started, the researchers exited the experimental room. At the end of the session, the researchers re-entered the room and proceeded to help the dyad remove the devices while a video screening of ‘Peppa Pig’ was played to distract the child. Lastly, the mother was debriefed about the study and remunerated.

Figure 1 Illustration depicting the set-up of devices and sitting arrangement of mother-child dyads during the experimental sessions. Figure illustrated by Nur Hasyimah Bte Johari. Full size image

Parenting stress index - short form

The Parenting Stress Index - Fourth Edition (PSI-4)19 is a screening and diagnostic tool used to measure perceived parenting stress in the parent-child system for a child who is between 1 month and 12 years of age. The short format has 36 items and has been found to have high reliability (alpha coefficient = 0.98)20 and validity21,22,23. Parents read the statements and then rate their response on a 5-point Likert-scale, where 1 indicates strongly disagree and 5 indicates strongly agree. The sample for our study had high internal consistency (alpha coefficient = 0.90).

The Parenting Stress Index - Short Form (PSI-SF) is created by extracting items from the original PSI and consists of three main sub-scales. The 12-item Parental Distress subscale measures personal factors of the parent that contribute to stress and consists of items such as the perceived restriction experienced after having a child (e.g. ‘Since having my child I have been unable to try new and different things.’). The 12-item Parent-Child Dysfunctional Interaction subscale measures the extent to which the parent experiences satisfaction from interactions with her child and the extent to which the child meets her expectations. It includes items such as ‘My child is not able to do as much as I expected’. The 12-item Difficult Child subscale provides an indication of the parent’s perceptions of her child’s characteristics and has items such as ‘My child generally wakes up in a bad mood.’). The total stress perceived by the mother is the sum of the scores of the three subscales, with higher scores representing greater parenting stress.

Video stimulus

This study employed a passive joint video attention task because of the familiarity of this activity for both mothers and children. Three 1-min animation videos from Brave, Peppa Pig and The Incredibles, were selected because of their different emotional valences and audio-visual complexities, so as to increase the generalisability of this dyadic activity. The video clips were edited to equate average volume and brightness. A 5-sec fixation cross was added to the start of each video clip, and a 10-sec inter-stimulus interval (ISI) fixation cross was added between each clip (Fig. 2). To control order effects, the three animation clips were randomised to create a total of six different sequences. The video stimulus was screened on a 15-inch Acer Laptop with both brightness and volume set on the laptop to 60%.

Figure 2 Schematic diagram representing the video stimuli screened to participants. A 5-sec fixation point “+” was presented before the onset of the first video clip. Three 1-min video clips were screened in total, with an inter-stimulus interval of 10 sec between each clip. The order of presentation of the three video clips was randomised such that six video sequences were generated. Mother-child dyads were randomly assigned to one of six video sequences. Full size image

Using Python and the FFmpeg software (v. 3.4.4), each video clip was analysed for its visual complexity (i.e. video complexity) by extracting the video at 12 frames per second (FPS). The audio intensity and audio fundamentals of the video were analysed by first converting the video to an audio file on FFmpeg, before using Praat software (v. 6.0.46) to extract the audio information of the clip. Emotional valence was calculated microanalytically by rating each sec of the video as either positive, neutral, or negative, and the sum of the three 1-min video clips was used as the respective rating of positivity. Results of the visual complexities, audio intensities, audio fundamentals, and valences for each video clip are reported in Table 1.

Table 1 Values of video complexity, audio fundamentals (pitch), audio intensity, and valence of the three animation clips: Brave, Peppa Pig, and The Incredibles. Full size table

Functional near-infrared spectroscopy (fNIRS) data acquisition

fNIRS experimental set-up and pre-processing

Prefrontal cortical (PFC) activity was measured in tandem mode using the non-invasive fNIRS neuroimaging system (NIRSport, NIRx Medical Technologies LLC). This equipment has a scan rate of 7.81 Hz and employs LED emission with source wavelengths of 760 nm and 850 nm. The mother and child NIRS caps have 8 LED sources and 7 detectors to collect optical signals. The inter-optode distance was kept at the optimal maximum of 3 cm. NIRSlab (NIRS v.205 software) software was used to configure a 20-channels-recording system of the PFC, utilizing an 8x7 source-detector montage. fNIRS allows for monitoring local blood oxygenation, with more active brain areas exhibiting a greater concentration of oxygenated haemoglobin (HbO) relative to reduced haemoglobin (HbR)24.

NIRSlab software was used to conduct pre-processing and analysis of NIRS data. First, channels were inspected and those with a significant background noise of gain >8, CV > 7.5 were determined as noisy and excluded from further pre-processing. Next, markers for onset of each of the 3 video stimuli were added. This was followed by manual removal of discontinuities and spike artefacts. A band-pass filter of 0.01–0.2 Hz was applied to remove any physiological and slow signals and baseline shift variations. For each channel, haemodynamic states were then calculated, and the pre-processed signals were converted to changes in concentration of HbO and HbR using the modified Beer-Lambert law. Finally, the signal was manually inspected by two independent coders to detect the presence of further artifacts.

General linear model (GLM) analyses

Two levels of analyses were conducted for NIRS data: within-subject analysis (first-level) and group-level analysis (second-level). In the first-level analysis, a haemodynamic response function (HRF) was specified and pre-whitening was omitted. HRF towards each video was plotted against a time axis using a convolution design matrix where each point of the matrix was checked against the order of stimulus presentation the participants received. This was followed with the application of a Discrete Cosine Transformation (DCT) temporal parameter with a high-pass period cut-off of 128 sec. Next, a Gaussian Full Width at Half Maximum (FWHM) 4 model was applied, and for each individual participant General Linear Models (GLMs) were obtained based on the HbO signals. Using the GLMs, beta-coefficients for each of the 3 videos were obtained and then aggregated to obtain an average beta-coefficient. At the second-level analysis, beta-coefficients obtained from HbO of each participant were aggregated into a group-level GLM.

Dynamic time warping (DTW) time-series analyses

To quantify synchrony between mother and child, a robust algorithm known as Dynamic Time Warping (DTW) was performed on pre-processed time-series data of each dyad. DTW allows for similar but out-of-phase shapes to match within the same time period25, resulting in the transformation of time-series data via arrangement of all sequence points, thereby optimising the alignment of any two sequences26. DTW has been previously used in electrocardiogram27 and word recognition studies28,29,30. A distance index, also known as a cost function26, was generated for each dyad. The greater the distance index, the lesser the synchronisation between members of a dyad31.

Cluster grouping of channels

Given that brain regions are interconnected in networks, investigating PFC in clusters instead of single channels provided a more meaningful and realistic interpretation of the results. Channels were clustered into 4 regions of the PFC - frontal left, frontal right, medial left, and medial right. The four clusters were formed by grouping different channels in near proximity. Figure 3 shows the clusters of channels as well as the Brodmann Area implicated in each cluster.

Figure 3 Schematic diagram depicting locations of the 20 optode channels and their corresponding positions with respect to the superior frontal gyrus (SFG), middle frontal gyrus (MFG), inferior frontal gyrus (IFG), and anterior prefrontal cortex (aPFC). Channels were grouped into the following clusters: frontal left, frontal right, medial left, and medial right. Full size image

Analytic plan: general linear model

Preliminary analyses

All analyses were done in R studio (version 1.0.153, R-core 3.4.2). For each cluster, beta coefficients of the HbO signal were summed and averaged across the channels within that cluster. Preliminary analyses were conducted where child’s gender, mother’s age, and video valence were fitted into 3 linear models individually as factors against each cluster. Video complexity and audio intensity and fundamentals were included as covariates in all three regression models. The analyses were conducted twice - once for mothers and once for children.

Descriptive analyses

The means and standard deviations of the averaged beta values for all 4 clusters for both mothers and children are reported.

Inferential analyses

A multivariate linear regression was conducted for each of the 4 clusters, fitting parenting stress as a factor with video complexity and audio fundamentals as controls (i.e., Beta = Parenting Stress + (Video Complexity + Audio Fundamentals)). A significant relation between a cluster and parenting stress implies that, while engaging in a joint task (i.e., watching videos), the level of parenting stress reported by the mother is associated with activation in that particular PFC cluster. False Discovery Rate (FDR) correction was applied to all p-values to correct for multiple channel comparisons. Regression analysis was executed twice - once for mothers and once for children.

Analytic plan: synchrony analyses

Preliminary analysis

Distance indices for each PFC cluster were summed and averaged across all the channels in each cluster, resulting in an overall distance index for each cluster. We employed normalised distance indices, which applied correction according to the length of the signals thereby allowing us to compare signals of different lengths (e.g., when only a portion of the signal is kept for one individual within the dyad while the other individual has the complete set of signals). A preliminary analysis was conducted where gender, maternal age, and video valence were fitted into 3 models individually as factors against each of the four cluster’s distance index. Video complexity and audio fundamentals were included as covariates in all three regression models.

Descriptive analyses

The means and standard deviations of the distance indices for all 4 clusters are reported.

Inferential analyses

Similarly, general linear regressions were conducted for each of the clusters. A model with parenting stress as a factor with video complexity and audio fundamentals as controls was fitted with each of the 4 clusters’ distance indices (i.e., Distance Index = Parenting Stress + (Video Complexity + Audio Fundamentals). A significant relation between the distance index and parenting stress within a cluster implies that level of synchrony between mother and child for that particular PFC region is associated with the level of parenting stress reported by the mother. FDR correction was then applied to all p-values to correct for multiple comparisons.