Assistant Professor of Brain and Cognitive Sciences
Jessica Cantlon explores whether children learn about quantities and counting from their environment, or whether they are born with a basic ability to grasp these concepts. Her work suggests that the brain has a fundamental understanding of mathematical concepts that is common across species. She uses a variety of approaches to better understand cognition, from neuroimaging and developmental psychology to nonhuman primate research.
Harnessing the potential of data science through better tools to analyze data, she says, will inform and enrich her research. “Data science will help tease out new insights about how the brain works,” says Cantlon. “Although there are some people who are bridging the fields of cognitive science and computer science, we are just at the beginning of this. The potential is huge.”
Today, most of the research by cognitive scientists is done through behavioral studies. Canton, though, has innovated some novel approaches. For instance, she was the first researcher able to conduct functional magnetic resonance imaging (fMRI) studies of very young children, which requires perfect stillness from subjects. She is conducting fMRI studies of number representations on monkeys—another first.
In addition, she was the first build a unique software program that analyzes the temporal correlations between the brains of young children and adults to measure neural response maturity, which is an indicator of mathematical ability.
In the future, data science tools will help her and others identify subtle patterns in information. “More finely tuned analytic approaches will benefit us and help make full use of all the available data,” she adds. “Collaboration between those in cognitive science and those in computer science will help with this as well—these relationships are critical for making sense of massive data sets.”
The greatest limitation in advancing work in cognitive science, according to Cantlon, is technological ability. “If we have access to more sophisticated algorithms, we can better characterize neural responses and our understanding of the brain. For students who will be the next generation of cognitive scientists, growing their computational skill set is essential.”
Cantlon’s research provides insights into the origins and foundations of our human mathematical capabilities as well as logical reasoning. The more progress cognitive scientists can make in interpreting neural data and understanding what brain development really looks like and how it relates to cognition, the closer they will get to reliably diagnosing and characterizing different types of disorders. This will help them understand not just developmental disorders but also basic learning impairments.
Cantlon completed her doctorate in cognitive science at Duke University and was a postdoctoral fellow at Carnegie Mellon University before joining the University of Rochester in 2009. She was named a James P. Wilmot Assistant Professor in 2012 and a James S. McDonnell Scholar in 2011. She is also a 2013 Sloan Research Fellow.
Jessica Cantlon, assistant professor of brain and cognitive sciences, is focused on finding the building blocks of cognition. Her research provides insights into the origins and foundations of our human mathematical capabilities as well as logical reasoning.