Research

Our research investigates reading and mathematical development in school-aged children. We primarily use oscillatory brainwave paradigms (EEG, SSVEP) to examine how brain responses are indicative of developing reading and mathematical abilities, and to capture how these neural signals change over the course of a child’s learning experiences in school. We also aim to link our brain-based findings to educational outcomes and investigate differences among learner profiles (e.g., students with dyslexia). 

We are currently pursuing studies in three general project areas:

Visual Word Processing

Reading involves the ability to recognize printed (i.e., visual) words — a process that eventually becomes a quick and automatic ability in adult expert readers.  Broadly, we are interested in capturing the developmental trajectory of visual word processing in K-8 readers, and relating these insights to students’ learning experiences and reading outcomes in school.

Audiovisual Integration

The ability to integrate visual and auditory (i.e., phonological) information is critical for early reading. In school, pre-readers begin by learning to link a letter with its corresponding speech sound, and with reading experience, this letter-sound pairing ability eventually becomes automatic and effortless. Looking at the brain resources involved in audiovisual (AV) integration, previous fMRI studies have found a "congruency effect" where there are stronger brain responses when corresponding letters and sounds are presented in unison. This effect disappears for adults and children with dyslexia (Blau et al. 2009 & 2010), and neural markers of AV integration have been related to future reading outcomes (Karipidis et. al, 2018). We are exploring AV integration in English.

Mathematical Ability

We are exploring the development of mathematical ability in learners, with a focus on dot enumeration (i.e., counting dots), single digit arithmetic, and double digit arithmetic. We are currently probing the construct of “math fluency” using data collected from tablet-based math assessments, paired with individual metrics such as performance in school, standardized test scores, and measures of executive function. Broadly, we are interested in identifying early factors that may predict later mathematical ability and extending this investigation to brain-related factors.