Staff Profiles

Shinya Ito, Ph.D.

Scientist II

Shinya Ito joined the Mindscope Program at the Allen Institute in 2021 as a scientist on the team lead by Anton Arkhipov. As a part of Modeling, Analysis & Theory (MAT) team, he works on biophysically detailed simulations of the mouse visual cortex to shed light on understanding mechanisms of visual information processing. The model is built based on cutting-edge data in the field including those collected at the Allen Institute, and is able to reproduce a wide range of phenomena observed in the visual cortex. Previously, he was a postdoctoral scholar at University of California, Santa Cruz where he studied vision, audition and multi-sensory integration in the mouse superior colliculus using a 256-channel silicon probe recording system that he developed. He developed the first virtual auditory space stimulation system for the mouse to study sound localization in the mouse. He also studied functional connectivity between cortical and hippocampal neurons for his Ph.D. in Physics at Indiana University, Bloomington, and received a B.S. in Physics at Hokkaido University.

Google Scholar profile


Research Interests

As neuroscience is entering the era of big data, one of the goals in the field is to distill them into computational principles and mechanisms. Biophysically detailed modeling is potentially one of the ways to achieve the goal. Shinya’s focus is to take cutting-edge dataset in the field and extract underlying statistics and implement them in the model. The resulting model will bridge between the biophysical structures and the functional properties of the neuronal network and provide a laboratory for testing hypotheses of visual information processing.


  • Computational Neuroscience
  • Statistical Data Analysis
  • Sensory Systems
  • Silicon Probe Electrophysiology

Research Programs

  • Modeling, Analysis & Theory (MAT)

Selected Publications

The mouse superior colliculus: an emerging model for studying circuit formation and function

Frontiers in Neural Circuits
February 13, 2018

Ito S, Feldheim DA

Extending transfer entropy improves identification of effective connectivity in a spiking cortical network model

PloS One
November 15, 2011

Ito S, Hansen ME, Heiland R, Lumsdaine A, Litke AM, Beggs JM