Measuring brain maturation in individual children
Most scientific research focuses on making inferences about groups; we are interested in understanding individuals.
Over the past decade non-invasive techniques to measure the living human brain have dramatically improved to the point where it is now possible to monitor changes in the developing brain and relate these changes to environmental influences. Based on these technical achievements, the biological foundation of cognitive development can now be scientifically studied. Properties of cellular organization including the density of tissue macromolecules, the concentration of myelin, and even the caliber of axons within the white matter can be accurately estimated using recently developed quantitative magnetic resonance imaging (qMRI) techniques. For the first time, we can begin to develop models of the biological processes that underlie the development of uniquely human skills such as learning to speak a language or rapidly recognize written text. We can extend fundamental principals of brain development, such as critical, or sensitive periods, to the maturational time course of developing infants. Additionally, we can begin to use brain measurements to predict learning difficulties in individual infants with the possibility of harnessing this new information to develop intervention programs that to target the mechanisms underlying individual variation in language learning. Our goal is to develop innovative techniques for measuring brain maturation in individual children and applying these measurements to understand the neurobiological basis of cognitive development.
How does the brain learn to read?
Learning to read depends on the brain’s capacity for plasticity. Over years of training and practice, the brain constructs circuits to rapidly and accurately translate an arbitrary system of symbols into a meaningful language representation. We are running a number of studies that are focused on understanding the structural and functional changes that underlie learning to read.
Some children effortlessly learn how to read while others struggle. We would like to understand the mechanisms underlying this variability.The long-term goal of this work is to develop education and intervention programs that are tailored to a child’s unique pattern of brain maturation.
How does brain circuit structure relate to cortical computation?
There are a wealth of tools for quantitatively measuring both the structure and function of the living human brain. By combining these measurement modalities we can develop models that predict functional responses based on a knowledge of the structure of a brain circuit within an individual’s brain.
A computational model of word recognition in the brain
Within ventral occipitotemporal cortex there are regions that selectively respond to different visual categories such as words and faces. A region, termed the visual word form area (VWFA), is believed to be essential for the recognition of printed words. The VWFA is highly connected with visual, auditory and language processing regions; responses within this region are driven both by properties of the visual stimulus and properties of the cognitive task. In collaboration with Kendrick Kay’s lab at the University of Minnesota, we are interested in developing a computational model that predicts the responses within the VWFA as a function of feedforward, stimulus-driven computations and cognitive, task-related processing.