Mother-infant social and language interactions at 3 months are associated with infants' productive language development in the third year of life.

Previous studies underscore the importance of social interactions for child language development-particularly interactions characterized by maternal sensitivity, infant-directed speech (IDS), and conversational turn-taking (CT) in one-on-one contexts. Although infants engage in such interactions from the third month after birth, the prospective link between speech input and maternal sensitivity in the first half year of life and later language development has been understudied. We hypothesized that social interactions embodying maternal sensitivity, IDS and CTs in the first 3 months of life, are significantly associated with later language development and tested this using a longitudinal design. Using a sample of 40 3-month-old infants, we assessed maternal sensitivity during a structured mother-infant one-on-one (1:1) interaction based on a well-validated scoring system (the Coding Interactive Behavior system). Language input (IDS, CT) was assessed during naturally occurring interactions at home using the Language ENvironment Analysis (LENA) system. Language outcome measures were obtained from 18 to 30 months of age using the MacArthur-Bates Communicative Development Inventory. Three novel findings emerged. First, maternal sensitivity at 3 months was significantly associated with infants' productive language scores at 18, 21, 24, 27, and 30 months of age. Second, LENA-recorded IDS during mother-infant 1:1 interaction in the home environment at 3 months of age was positively correlated with productive language scores at 24, 27, and 30 months of age. Third, mother-infant CTs during 1:1 interaction was significantly associated with infants' productive language scores at 27 and 30 months of age. We propose that infants' social attention to speech during this early period-enhanced by sensitive maternal one-on-one interactions and IDS-are potent factors in advancing language development.

Infants' brain responses to social interaction predict future language growth.

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.

Improving Localization Accuracy of Neural Sources by Pre-processing: Demonstration With Infant MEG Data.

We discuss specific challenges and solutions in infant MEG, which is one of the most technically challenging areas of MEG studies. Our results can be generalized to a variety of challenging scenarios for MEG data acquisition, including clinical settings. We cover a wide range of steps in pre-processing, including movement compensation, suppression of magnetic interference from sources inside and outside the magnetically shielded room, suppression of specific physiological artifact components such as cardiac artifacts. In the assessment of the outcome of the pre-processing algorithms, we focus on comparing signal representation before and after pre-processing and discuss the importance of the different components of the main processing steps. We discuss the importance of taking the noise covariance structure into account in inverse modeling and present the proper treatment of the noise covariance matrix to accurately reflect the processing that was applied to the data. Using example cases, we investigate the level of source localization error before and after processing. One of our main findings is that statistical metrics of source reconstruction may erroneously indicate that the results are reliable even in cases where the data are severely distorted by head movements. As a consequence, we stress the importance of proper signal processing in infant MEG.

Infant brain imaging using magnetoencephalography: Challenges, solutions, and best practices.

The excellent temporal resolution and advanced spatial resolution of magnetoencephalography (MEG) makes it an excellent tool to study the neural dynamics underlying cognitive processes in the developing brain. Nonetheless, a number of challenges exist when using MEG to image infant populations. There is a persistent belief that collecting MEG data with infants presents a number of limitations and challenges that are difficult to overcome. Due to this notion, many researchers either avoid conducting infant MEG research or believe that, in order to collect high-quality data, they must impose limiting restrictions on the infant or the experimental paradigm. In this article, we discuss the various challenges unique to imaging awake infants and young children with MEG, and share general best-practice guidelines and recommendations for data collection, acquisition, preprocessing, and analysis. The current article is focused on methodology that allows investigators to test the sensory, perceptual, and cognitive capacities of awake and moving infants. We believe that such methodology opens the pathway for using MEG to provide mechanistic explanations for the complex behavior observed in awake, sentient, and dynamically interacting infants, thus addressing core topics in developmental cognitive neuroscience.

Using magnetoencephalography to examine word recognition, lateralization, and future language skills in 14-month-old infants.

Word learning is a significant milestone in language acquisition. The second year of life marks a period of dramatic advances in infants' expressive and receptive word-processing abilities. Studies show that in adulthood, language processing is left-hemisphere dominant. However, adults learning a second language activate right-hemisphere brain functions. In infancy, acquisition of a first language involves recruitment of bilateral brain networks, and strong left-hemisphere dominance emerges by the third year. In the current study we focus on 14-month-old infants in the earliest stages of word learning using infant magnetoencephalography (MEG) brain imagining to characterize neural activity in response to familiar and unfamiliar words. Specifically, we examine the relationship between right-hemisphere brain responses and prospective measures of vocabulary growth. As expected, MEG source modeling revealed a broadly distributed network in frontal, temporal and parietal cortex that distinguished word classes between 150-900 ms after word onset. Importantly, brain activity in the right frontal cortex in response to familiar words was highly correlated with vocabulary growth at 18, 21, 24, and 27 months. Specifically, higher activation to familiar words in the 150-300 ms interval was associated with faster vocabulary growth, reflecting processing efficiency, whereas higher activation to familiar words in the 600-900 ms interval was associated with slower vocabulary growth, reflecting cognitive effort. These findings inform research and theory on the involvement of right frontal cortex in specific cognitive processes and individual differences related to attention that may play an important role in the development of left-lateralized word processing.

Infant Directed Speech Enhances Statistical Learning in Newborn Infants: An ERP Study.

Statistical learning and the social contexts of language addressed to infants are hypothesized to play important roles in early language development. Previous behavioral work has found that the exaggerated prosodic contours of infant-directed speech (IDS) facilitate statistical learning in 8-month-old infants. Here we examined the neural processes involved in on-line statistical learning and investigated whether the use of IDS facilitates statistical learning in sleeping newborns. Event-related potentials (ERPs) were recorded while newborns were exposed to12 pseudo-words, six spoken with exaggerated pitch contours of IDS and six spoken without exaggerated pitch contours (ADS) in ten alternating blocks. We examined whether ERP amplitudes for syllable position within a pseudo-word (word-initial vs. word-medial vs. word-final, indicating statistical word learning) and speech register (ADS vs. IDS) would interact. The ADS and IDS registers elicited similar ERP patterns for syllable position in an early 0-100 ms component but elicited different ERP effects in both the polarity and topographical distribution at 200-400 ms and 450-650 ms. These results provide the first evidence that the exaggerated pitch contours of IDS result in differences in brain activity linked to on-line statistical learning in sleeping newborns.

Theta brain rhythms index perceptual narrowing in infant speech perception.

The development of speech perception shows a dramatic transition between infancy and adulthood. Between 6 and 12 months, infants' initial ability to discriminate all phonetic units across the world's languages narrows-native discrimination increases while non-native discrimination shows a steep decline. We used magnetoencephalography (MEG) to examine whether brain oscillations in the theta band (4-8 Hz), reflecting increases in attention and cognitive effort, would provide a neural measure of the perceptual narrowing phenomenon in speech. Using an oddball paradigm, we varied speech stimuli in two dimensions, stimulus frequency (frequent vs. infrequent) and language (native vs. non-native speech syllables) and tested 6-month-old infants, 12-month-old infants, and adults. We hypothesized that 6-month-old infants would show increased relative theta power (RTP) for frequent syllables, regardless of their status as native or non-native syllables, reflecting young infants' attention and cognitive effort in response to highly frequent stimuli ("statistical learning"). In adults, we hypothesized increased RTP for non-native stimuli, regardless of their presentation frequency, reflecting increased cognitive effort for non-native phonetic categories. The 12-month-old infants were expected to show a pattern in transition, but one more similar to adults than to 6-month-old infants. The MEG brain rhythm results supported these hypotheses. We suggest that perceptual narrowing in speech perception is governed by an implicit learning process. This learning process involves an implicit shift in attention from frequent events (infants) to learned categories (adults). Theta brain oscillatory activity may provide an index of perceptual narrowing beyond speech, and would offer a test of whether the early speech learning process is governed by domain-general or domain-specific processes.