Mick Bonner

Mick Bonner

Assistant Professor, Colloquium Chair

Contact Information

Research Interests: Computational neuroscience, cognitive neuroscience, vision, neural networks, deep learning, advanced statistical methods for neuroscience

Education: PhD, University of Pennsylvania

My lab uses computational methods, including deep neural networks and advanced statistical techniques, in combination with neuroimaging and behavioral studies to understand the visual system of the human brain. Our goal is to identify the statistical principles that govern the representations of visual cortex and to build theoretically grounded models of how these representations are computed from sensory inputs. Before joining the Cognitive Science Department at Johns Hopkins, I worked with Russell Epstein as a postdoctoral fellow in the Department of Psychology at the University of Pennsylvania. I completed my PhD in Neuroscience from the University of Pennsylvania, where I was advised by Murray Grossman.

  • AS.050.203/603 Neuroscience: Cognitive
  • AS.050.365/665 Cracking the code: Theory and modeling of information coding in neural activity
  • AS.050.806 Research Seminar in Cognitive Neuroscience and Machine Learning