Infants' brain responses to social interaction predict future language growth

Abstract

In face-to-face interactions with infants, human adults exhibit a species-specific communicative signal. Adults present a distinctive "social ensemble": they use infant-directed speech (parentese), respond contingently to infants' actions and vocalizations, and react positively through mutual eye-gaze and smiling. Studies suggest that this social ensemble is essential for initial language learning. Our hypothesis is that the social ensemble attracts attentional systems to speech and that sensorimotor systems prepare infants to respond vocally, both of which advance language learning. Using infant magnetoencephalography (MEG), we measure 5-month-old infants' neural responses during live verbal face-to-face (F2F) interaction with an adult (social condition) and during a control (nonsocial condition) in which the adult turns away from the infant to speak to another person. Using a longitudinal design, we tested whether infants' brain responses to these conditions at 5 months of age predicted their language growth at five future time points. Brain areas involved in attention (right hemisphere inferior frontal, right hemisphere superior temporal, and right hemisphere inferior parietal) show significantly higher theta activity in the social versus nonsocial condition. Critical to theory, we found that infants' neural activity in response to F2F interaction in attentional and sensorimotor regions significantly predicted future language development into the third year of life, more than 2 years after the initial measurements. We develop a view of early language acquisition that underscores the centrality of the social ensemble, and we offer new insight into the neurobiological components that link infants' language learning to their early brain functioning during social interaction.

Keywords: MEG; attention; behavior; brain; infant; language development; magnetoencephalography; neuroscience; social interaction; theta oscillations.

Figure 1.. 5-month-old infant in a MEG brain-imaging device with social vs. nonsocial conditions.

(A) During the social condition, the experimenter, signaled by a green light, interacted with the infant by exhibiting the social ensemble of behaviors. (B) During the nonsocial condition, the experimenter, signaled by a red light, turned 45 degrees toward an adult sitting out of view of the infant and spoke to them. For each infant, the conditions were presented randomly and separated by at least 7 s, with a minimum of 16 repetitions for each condition per infant. The recording session lasted about 13 min.

Figure 2.. Mean neural activity during social and nonsocial conditions.

(A) Brain map showing regions of interest (ROI): Inferior Frontal (IF-green), Superior Temporal (ST-blue) and Inferior Parietal (IP-red) in the left and right hemispheres. (B) Mean relative theta power (RTP), as percentage of total power between 0 and 60 Hz, in each ROI for Conditions and Hemispheres. Error bar indicates +/− 1 standard error, ** indicates statistical significance p ≤ 0.01, * indicates p ≤ 0.05, and † indicates trend toward significance p = 0.055, two-tailed paired t-tests.

Figure 3.. Vocabulary growth as a function of age.

Vocabulary growth (see Methods) as a function of age for each of the 21 individual children (grey lines) and the mean vocabulary score for the group (bold). Age is shown in months, and vocabulary in average words produced.

Figure 4.. Scatter plots showing the correlation between neural activity during social and nonsocial conditions at 5 months of age and children’s later language skills at 24 months.

Left two columns show RTP for the social and nonsocial conditions in relation to children’s productive vocabulary score at 24 months for the left hemisphere: inferior frontal (IF), superior temporal (ST), and inferior parietal (IP). Right two columns show the same information for the right hemisphere. Each point represents a single child participant. The x-axis values reflect standardized RTP. Lines are simple linear regression fits, with the variance explained (r²) p-values indicated (Bonferroni corrected p < 0.05). Significant effects are shown in red.