The meaning of a sensory stimulus can change depending on the current situation, and the ability to flexibly and appropriately adjust behavioral responses in changing contexts is critical for survival. The goal of my research is to understand the circuit mechanisms that control the flow of information between brain regions. How do networks filter out irrelevant information? How does incoming sensory information interact with the animal’s internal brain state?
To answer these and related questions, we use in two-photon imaging, genetic labeling, and optogenetic manipulation of specific cell classes in mice performing perceptual tasks. Specifically, we wish to understand how incoming signals interact at different points in the cortical hierarchy, how inhibitory subcircuits control the transmission of these signals, and how neuromodulatory inputs allow changing brain states and external contexts to alter sensory processing. In the longer term, we will build on this foundation to enable new approaches to understanding disruptions in network communication in complex brain disorders such as schizophrenia and addiction.
Runyan, C.A., Piasini, E., Panzeri, S., & Harvey, C.D. (2017) Distinct timescales of population coding across cortex. Nature, 548(7665): 92-96.
Runyan, C.A., & Sur, M. (2013). Response selectivity is correlated to dendritic structure in parvalbumin-expressing inhibitory neurons in visual cortex. Journal of Neuroscience. 33(28): 11724-33.
Wilson, N.R., Schummers, J., Runyan, C.A., Yan, S., Chen, R., Deng, Y., Sur, M. (2013) Two-way communication with neural networks in vivo using focused light. Nature Protocols, 8, 1184-1203.
Wilson, N.R.*, Runyan, C.A.*, Wang, F.L., & Sur, M. (2012). Division and subtraction by distinct cortical inhibitory networks in vivo. Nature, 488: 343-348.
Runyan, C. A.*, Schummers, J.*, Van Wart, A.*, Kuhlman, S. J., Wilson, N. R., Huang, Z. J., & Sur, M. (2010). Response features of parvalbumin-expressing interneurons suggest precise roles for subtypes of inhibition in visual cortex Neuron, 67(5), 847–857. doi:10.1016/j.neuron.2010.08.006