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.
St-Amand, D., Baker, C.L. Jr.: Model-based approach shows ON pathway afferents elicit a transient decrease of V1 responses. J Neuroscience 43:1920-1932 (2023). PMID: 36759194.
Ramirez AL, Thompson LW, Rosenberg A, Baker CL Jr.: Behavioral signatures of Y-like neuronal responses in human vision. Scientific Reports 12:19116 (2022). PMID: 36352245.
Sun, H-C, St-Amand, D., Baker, C.L. Jr., Kingdom, F.K.K.: Visual perception of texture regularity: conjoint measurements and a wavelet response-distribution model. PLOS Computational Biology, 17(10): e1008802 (2021). PMID: 34653176.
Dimattina D, Baker CL Jr (2019) Modeling second-order boundary perception: A machine learning approach. PLOS Computational Biology 15(3): e1006829. PMID: 30883556.
Gharat, A., and Baker, C.L. Jr.: 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 (2017). PMID: 28123031.