Our previous work has shown that there are individual differences in how infants attend to emotionally salient social information (e.g., angry faces). The early-emergent individual differences in affect-biased attention play a critical role in shaping trajectories of socioemotional development. Cognitive control functions serve to regulate attention and behavior. Early childhood (4 to 7 years) is marked by rapid development of cognitive control functions and the onset of socioemotional problems. Understanding the dynamic interactions between affect-biased attention and cognitive control might provide a key to understanding why some children develop socioemotional problems while others do not.
The project examines the development of affect-biased attention and cognitive control functions during childhood by using a battery of tasks incorporating eye tracking and functional near-infrared spectroscopy (fNIRS) recordings. We characterize the neurocognitive mechanisms underlying children’s attention and cognitive control functions. We also study how individual differences in these functions influence the way that children interact with the social environment and their socioemotional adjustment outcomes.
Reduced attention to social information is a promising biomarker for ASD. In collaboration with Dr. Jessica Bradshaw at USC, we aim to identify social attention patterns and characterize developmental trajectories of social attention associated with early risk for ASD, before a reliable ASD diagnosis can be determined. In the longitudinal study, we assess infants between 1 and 36 months in narrow age intervals. Infants’ attention is measured using eye tracking, lab observations, and parents reports in various task contexts. We also examine infants’ motor, social communication, and language abilities.
Functional near-infrared spectroscopy (fNIRS) is a noninvasive technique that uses sensors placed on the scalp to indirectly measure neural activities in response to the task stimuli. A key advantage of the technology is its ease of use with participants of different ages, hence, allowing researchers to track neurodevelopment across the lifespan. fNIRS data collection, data analysis, and result interpretations require making anatomical inferences about the correspondence between scalp and cortical locations. In collaboration with Dr. John Richards at USC, we leverage the open-access Neurodevelopment MRI Database to compute probabilistic scalp-to-cortex mapping for a wide age range across infancy and adulthood. The products of this project (see also Resources) will help researchers to make anatomical inferences about NIRS/fNIRS data, especially for studies where the participants’ own MRI scans cannot be collected or are unavailable.
