Electroencephalography (EEG) continues to be the most popular method to investigate cognitive brain mechanisms in young children and infants. Most infant studies rely on the well-established and easy-to-use event-related brain potential (ERP). As a severe disadvantage, ERP computation requires a large number of repetitions of items from the same stimulus-category, compromising both ERPs’ reliability and their ecological validity in infant research. We here explore a way to investigate infant continuous EEG responses to an ongoing, engaging signal (i.e., “neural tracking”) by using multivariate temporal response functions (mTRFs), an approach increasingly popular in adult EEG research. N = 52 infants watched a 5-min episode of an age-appropriate cartoon while the EEG signal was recorded. We estimated and validated forward encoding models of auditory-envelope and visual-motion features. We compared individual and group-based (‘generic’) models of the infant brain response to comparison data from N = 28 adults. The generic model yielded clearly defined response functions for both, the auditory and the motion regressor. Importantly, this response profile was present also on an individual level, albeit with lower precision of the estimate but above-chance predictive accuracy for the modelled individual brain responses. In sum, we demonstrate that mTRFs are a feasible way of analyzing continuous EEG responses in infants. We observe robust response estimates both across and within participants from only 5 min of recorded EEG signal. Our results open ways for incorporating more engaging and more ecologically valid stimulus materials when probing cognitive, perceptual, and affective processes in infants and young children.
Research Areas and Centers
- Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)