We develop computational tools and mathematical models to solve problems in sensory processing and memory.

Featured article

Cortical traveling waves: mechanisms and computational principles

Nature Reviews Neuroscience 19, 2018
In this article, we reviewed results from recent years that have reshaped our understanding of the spatiotemporal dynamics in cortical circuits. Improvements in neural recording technologies allow neuroscientists to record from cortical populations with high spatial and temporal resolution. These new recording technologies have revealed traveling waves of neural activity in multiple sensory, motor, and cognitive systems. Through advancements in signal processing and computational models, we are beginning to understand how these spatiotemporal patterns of activity can be used for sensory and cognitive computations.
May 2018 Cover by Jennie Vallis
Research themes
Signal/image processing

We develop new computational tools for analyzing large-scale neural recordings and uncovering new dynamics in cortex. We draw techniques from many disciplines in applied mathematics, including signal processing, image processing, and computer vision.

Computer science

Large-scale computational modeling allows us to study how neural networks generate experimental observations. We use advanced techniques in computer science to target higher simulation scales with optimized, low-level programming languages.


Random graph theory allows us to study neural network structure and dynamics with numerical and analytical approaches. In this work, we use tools and techniques from graph theory and discrete mathematics.

Our research is made possible
by generous support from