Parent-infant neural connectedness and early learning - Leong, Victoria (2020)
During early life, social interactions between infants and caregivers – such as play - provide a powerful stimulant for learning. Yet current neuroscience frameworks are ill-equipped to explain how social interactions potentiate learning in the infant brain. By necessity, neuroscientific learning models adopt a reductionist approach to the relationship between the inner mental world of the infant learner and her outer world. Hebbian learning is automatic and predictable: the infant observes a temporal or causal association between physical objects or events; repeated exposure strengthens synaptic connections that hard-wire this new knowledge into neural network architecture. However, social learning - learning from and with social partners – is variable and voluntary. Whilst information about the physical world is epistemically transparent and stable, social information (from human behaviour such as vocalisations and facial expressions) varies dynamically in relation to oneself, one’s partner, and the wider social context. Early social learning, therefore, is better understood as a negotiation between teacher and learner as they perform a mental dance around what (if any) learning will occur. Explaining this capricious, but fundamental, form of early human learning requires a paradigmatically different type of “two-person” neuroscience. Here, I will present dyadic (adult-infant) neural data that exemplify a co-constructivist approach to understanding how early learning occurs in social contexts like play.