Christopher DiMattina Profile

• Ph.D. Neuroscience (Systems/Computational), Johns Hopkins University
• B.A. Mathematics and Psychology, Cornell University

• Vision science
• Computational neuroscience
• Cognitive neuroscience

I am an experimental vision scientist and computational neuroscientist who is interested in understanding information processing in the early visual system. In collaboration with colleagues at McGill University (Montreal, Canada), I am currently working on understanding how luminance and texture cues are combined to detect image region boundaries. Our ultimate goal is to understand the computations which enable the visual system to segment natural images.

I also have a longstanding interest in applying various machine learning methods (neural networks, adaptive stimulus optimization) to problems in neuroscience and cognitive science, and supervise student research projects in the broad areas of cognition + perception.

• PSB-4002: Brain & Behavior
• EXP-3202: Sensation and Perception
• PSY-3205: Survey of Analytical Techniques

Representative Publications

• DiMattina, C. & Baker, C.L. (2021). Segmenting surface boundaries using luminance cues. Scientific Reports 11: 10074.
• Pipitone, R.N., & DiMattina, C. (2020). Object clusters or spectral energy? Assessing the relative contributions of image phase and amplitude spectra to Trypophobia. Frontiers in Psychology: Perception Science 11: 1847.
• DiMattina, C. & Baker, C.L. (2019). Modeling second-order boundary perception: A machine learning approach. PLoS Computational Biology 15(3): e1006829.)