In the brain, cellular components are inconstant, proteins turn over in seconds to hours, and experience is a powerful modifier. Despite this, neural computation is stable for the lifetime of an organism. We seek to understand how the brain generates reliable dynamics on long timescales. Ultimately, all brain function relies upon the capacity of networks to self-organize and maintain stable function across dynamic and variable environments.
Our research interests are rooted in the active self-organization of intact neural networks that support sensation, perception and cognition, and how appropriate information transmission in these systems is established during development and disrupted in disease.
Currently, we're investigating the role of brain states, behavioral contexts, cell-types, network structure, and synaptic mechanisms in shaping emergent properties of neuronal networks.
USING ADVANCED TECHNOLOGY TO ANSWER CHALLENGING QUESTIONS
[Silicon probe by J. Scholvin]
chronic in vivo neurophysiology
In the pursuit of understanding how neurons contribute to networks, and how mechanisms influence neurons, we study the interaction of all three.