Dr. Peter's research aims to reveal how the brain represents and uses uncertainty, and performs adaptive computations based on noisy, incomplete information. Specifically, she focuses on how these abilities support metacognitive evaluations of the quality of (mostly perceptual) decisions, and how these processes might relate to phenomenology and conscious awareness. She uses neuroimaging, computational modeling, machine learning and neural stimulation techniques to study these topics.

Key Research Areas:

Perception, metacognition, consciousness, computational modeling, fMRI