pillow lab @ princeton

neural coding & computation group

The Pillow lab is a computational neuroscience and statistical machine learning group at Princeton University. We develop statistical methods for studying neural systems and behavior.


Our research focuses on statistical models and methods for characterizing neural population responses and extracting structure from high-dimensional neural data. We collaborate closely with experimental groups to study how neural populations encode, decode, and process information in different brain areas. We also study perception, decision-making, learning, and behavior, and the theoretical principles governing the design of neural systems.

Current research topics include:

  • - point process regression models
  • - latent variable models for spike train and imaging data
  • - receptive field estimation
  • - inference for detailed biophysical models
  • - spike sorting
  • - statistical signal processing for calcium imaging data
  • - active learning / closed-loop experimental design
  • - Bayesian optimization
  • - perceptual decision making
  • - visual motion perception

See our lab blog for more information about our latest activities.