BBThoughts · Dynamics of mental representations and learning in preverbal infants

Understanding the initial architecture and learning algorithms of the human brain are central goals for cognitive neuroscience. Anatomical and functional brain-imaging studies have revealed that a complex brain architecture is already present at birth, including features associated with adult brains such as structural and functional asymmetries, long-distance connectivity and activations in prefrontal cortex. Despite such advances, little is known about the depth of information processing and the richness of mental representations in human infants. To address this issue, I propose to study the dynamics of information processing and conscious access in 34-month-old-infants. Using high-density EEG (128-280 channels), combined with new methodological approaches such as decoding, single-trial analyses of variability patterns, and new paradigms that monitor infants attention with frequency tagging, pupillometry and eye-tracking, I will separate infants short-lived, externally triggered versus sustained, internally driven responses and shed light on their roles in early learning. WP1 will study whether the properties associated with conscious access in adults (ignition, top-down amplification, serial bottleneck) are already present in infants, and explore how ongoing neural activity, top-down expectations, and bottom-up stimulus features combine to modulate conscious access. WP2 will investigate the dynamics of acquisition and manipulation of symbolic representations. Experimental manipulations combined with fine-grained analysis of the temporal dynamics of EEG signals will clarify the time constants of infant cognition: how fast a stimulus enters perceptual awareness, how long attention can be maintained, how robust is this central representation to competing inputs, and how quickly it leads to stable learning. This project aims to enhance our understanding of early cognition, as well as provide new paradigms to shed light on early learning disabilities.