Even a momentary lapse of attention can be catastrophic for what we detect or what we remember. My research shows we can predict when these lapses will occur, by using sophisticated quantitative tools to track brain and behavior dynamics in real time. I propose that these moment-to-moment dynamics are critical for understanding a broad range of higher-level cognitive processes, including attention and memory. I further demonstrate that brain-computer interfaces are a powerful tool for basic science research in psychology and neuroscience, to trace cognitive states in unprecedented detail and intervene at specific moments.


I develop innovative quantitative solutions to examine brain states in real time, including brain-computer interfacing techniques that describe and manipulate human cognition in real time. My research encompasses behavioral paradigms as well as several cognitive neuroscience modalities, including fMRI, EEG, and pupillometry. I have pioneered techniques to track cognitive fluctuations in real time in conjunction with direct and causal interventions, such as neurofeedback, closed-loop systems, and adaptive experimental designs. My research demonstrates how real-time neurofeedback can modulate cognitive dynamics and improve behavior (e.g., deBettencourt et al., Nature Neuroscience, 2015; deBettencourt et al., NeuroImage, 2019). In a complementary line of work, my research shows how real-time triggering can target optimal or suboptimal cognitive states in real time (e.g., deBettencourt et al., Nature Human Behaviour, 2019; deBettencourt et al., Psychonomic Bulletin & Review, 2018).