My dissertation research focused on the integration of attention systems in the brain with numerical magnitude processing mechanisms. In a series of three studies, this work demonstrates that attention is an important mechanism to consider in how numerical perception relates to math ability, both for typically developing children and for those with math difficulties. I look forward to integrating these new findings with existing models of numerical cognition.
Little is known about how representation of number and mathematical knowledge works with with the neural mechanisms of executive function (working memory, inhibitory control, and rule switching). But, based on the behavioral literature, we do know that this link is very important! Some of my current work using ultra-high field fMRI focuses on understanding the integration of these networks.
An estimated 3-6% of the population is affected by the specific mathematics learning disability developmental dyscalculia (DD). Individuals with DD display difficulties with fundamental aspects of numerical processing from very early ages and continue to struggle with math, even when given the same schooling opportunities as their peers. A further 10-20% of the population have so much trouble with math that it impairs their ability to use information effectively in adult life. However, the nature of these numerical deficits and their relation to the abilities of typically developing populations remains poorly understood. By understanding the neurocognitive roots of math difficulties, I hope to do research that informs pedagogical techniques for struggling learners, diagnosis of learning disabilities, and remediation of math deficits.
One of the neuroimaging advances that I’m excited about is ultra-high field strengths. Both my PhD institution, Vanderbilt, and my postdoc institution, Western, have 7 Tesla MRI magnets. The use of such high field strengths for research in functional imaging has led to increased data quality and some really neat neuroimaging techniques.
I am committed to making my research transparent, reproducible, and accessible using open science practices. If you’re interested in learning more about it see here and here. In essence it is just a way of practicing science that prioritizes transparency in research (which makes for good science) and openness in dissemination (which creates science for the common good) leading to the democratization of knowledge. It also facilitates collaboration amongst colleagues.