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Understanding the dynamics of life

Kennedy lab at Scripps Research

From single neurons to social groups, biological systems integrate external cues with their own internal state to act on their surroundings in intricate feedback loops. As theoretical neuroscientists, we use mathematical modeling and model-informed analyses to understand how the organization of nervous systems relates to this function. We ask questions like:

  • How can the brain modulate neuronal properties to control what a neural circuit computes?

  • Why do neurons' physiological properties vary across and within cell types? Can this diversity be leveraged in computation?

  • How do animals change their behavioral policies in response to their needs? What neural processes underlie this change?

  • How are priors for "optimal" balancing of survival needs built into the structure of the brain?

  • How do highly decentralized nerve nets carry out coordinated actions?

  • How does activity of motor control systems account for the physics of body-environment interactions?

  • How does the meso-scale structure of neural circuits reflect their computational function?

  • How does evolution tune neural circuits to alter emergent species-level phenomena like social group structure?

Our work blends dynamical systems, control theory, reinforcement learning, and machine learning to investigate neural dynamics and behavior across multiple scales, brain regions, and model organisms. We value open science, clear communication, and creation of community resources. We collaborate enthusiastically with theorists and experimentalists in San Diego and beyond!

In the News

Ann receives a 2024 McKnight Scholars Award.

June 2024

Ann is named a 2023 Sloan Research Fellow.

Feb 2023

Profile in The Transmitter on the lab's work on computational analysis of behavior.

July 2022

Ann is quoted in a Quanta Magazine article on behavior quantification.

Dec 2019

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