null Curtis Baker, BSc, PhD
vision • neurophysiology • perception • psychophysics
My research focuses on understanding human visual perception, particularly low-level neural mechanisms that are functionally relevant in everyday life. Natural scenes in our visual world are filled with objects delineated from their backgrounds not only by simple changes in luminance or colour, but also by differences in other attributes such as contrast, texture, or motion. An important goal is to understand how early visual processing detects and utilizes these rich cues to provide a robust perception of "figure-ground" and local depth relationships in the real world. Projects within the lab employ a variety of approaches, including human psychophysics, single unit electrophysiology, optical imaging, and computational modeling.
Dimattina D, Baker CL Jr (2019) Modeling second-order boundary perception: A machine learning approach. PLOS Computational Biology 15(3): e1006829. PMID: 30883556.
Sun H-C, Kingdom FKK, Baker CL Jr (2019) Perceived regularity of a texture is influenced by the regularity of a surrounding texture. Scientific Reports 9:1637, 1-11 (2019). PMID: 30733482.
Buckthought A, Yoonessi A, Baker CL Jr (2017) Dynamic perspective cues enhance depth perception from motion parallax. Journal of Vision 17(1):10,1-19. PMID: 28114478.
Gharat A, Baker CL Jr (2016) Nonlinear Y-like receptive fields in the early visual cortex: An intermediate stage for building cue-invariant receptive fields from subcortical Y cells. Journal of Neuroscience 37(4):998-1013. PMID: 22673328.
Li G, Yao Z, Wang Z, Yuan N, Talebi V, Tan J, Wang Y, Zhou Y, Baker CL Jr (2014) Form-cue invariant second-order neuronal responses to contrast modulation in primate area V2. Journal of Neuroscience 34(36):12081-12092. PMID: 25186753.