The Computational Perception Laboratory is interested in developing computational
models of sensory processing, with an emphasis on mid-level vision problems like texture
segmentation and shadow detection. The PI is a member of the Vision Science Society.
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Education
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- Ph.D. Neuroscience (Computational), Johns Hopkins University
- B.A. Mathematics and Psychology, Cornell University
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Specialties
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- Vision science
- Computational neuroscience
- Cognitive neuroscience
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Research and Teaching Interests
Toggle Research and Teaching InterestsI am a vision scientist and computational neuroscientist who is interested in understanding
information processing in biological sensory systems. 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.
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Courses Offered
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- PSB-4002: Brain & Behavior
- EXP-3202: Sensation and Perception
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Publications
Toggle PublicationsRepresentative Publications
- DiMattina, C., Burnham, J. J., Guner, B. N., & Yerxa, H. B. (2022). Distinguishing
shadows from surface boundaries using local achromatic cues. PLoS Computational Biology,
18(9), e1010473.
- 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.)
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Grants & Awards
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- NIH Grant NIH-R15-EY032732-01
Editorial Boards
- Associate Editor: Frontiers in Psychology: Perception Science
- Associate Editor: Frontiers in Neuroscience: Perception Science
Dr. DiMattina's Lab webpage