Staff Profiles

Justin Kiggins, Ph.D.

Scientist I

Justin Kiggins joined the Allen Institute in 2016 as a scientist working in the Neural Coding group. With a background in neurophysiology, animal behavior, and data science, he works with the Visual Behavior team, working to gain insight into the neuronal mechanisms of perception and cognition through the analysis of population neurophysiology data during behavior and through the development of algorithms to automatically & efficiently train mice on visual behavior tasks that probe their perceptual and cognitive abilities.

Prior to joining the Institute, he earned his PhD in Neurosciences with a Specialization in Computational Neuroscience from UC San Diego, working with Dr. Timothy Gentner. During graduate school, he studied how vocal sequences are encoded the cortex of the European starling and developed open-source software for operant conditioning and analysis pipelines for electrophysiology data. Prior to his Ph.D., he earned a B.S.E. in Biomedical Engineering from Arizona State University.


Research Interests

I'm interested in how information from the world is transformed from the raw, meaningless signals that of the sensory periphery to the meaning-rich signals of the higher cortex and how these signals are used to drive decisions and choices on how to act in the world. I am particularly interested how perceptual boundaries emerge through higher sensory areas, how these boundaries are changed by temporal expectation, and how behavioral state modulates these representations. To this end, I apply the tools and workflows of modern data science to the analysis of large scale behavioral & neurophysiology experiments.


  • Computational Neuroscience
  • Systems Neuroscience
  • Operant Conditioning 
  • Data Science
  • Machine Learning

Research Programs

  • Neural Coding
  • Visual Behavior