Effects of socioeconomic status on brain development, and how cognitive neuroscience may contribute to levelling the playing field
1
Neukom Institute for Computational Science, Dartmouth College, Hanover, NH, USA
2
Helen Wills Neuroscience Institute, University of California at Berkeley, CA, USA
The study of socioeconomic status (SES) and the brain finds itself in a circumstance unusual for Cognitive Neuroscience: large numbers of questions with both practical and scientific importance exist, but they are currently under-researched and ripe for investigation. This review aims to highlight these questions, to outline their potential significance, and to suggest routes by which they might be approached. Although remarkably few neural studies have been carried out so far, there exists a large literature of previous behavioural work. This behavioural research provides an invaluable guide for future neuroimaging work, but also poses an important challenge for it: how can we ensure that the neural data contributes predictive or diagnostic power over and above what can be derived from behaviour alone? We discuss some of the open mechanistic questions which Cognitive Neuroscience may have the power to illuminate, spanning areas including language, numerical cognition, stress, memory, and social influences on learning. These questions have obvious practical and societal significance, but they also bear directly on a set of longstanding questions in basic science: what are the environmental and neural factors which affect the acquisition and retention of declarative and nondeclarative skills? Perhaps the best opportunity for practical and theoretical interests to converge is in the study of interventions. Many interventions aimed at improving the cognitive development of low SES children are currently underway, but almost all are operating without either input from, or study by, the Cognitive Neuroscience community. Given that longitudinal intervention studies are very hard to set up, but can, with proper designs, be ideal tests of causal mechanisms, this area promises exciting opportunities for future research.