New approach in my lab aims to understand how external and internal signals shape population activity

September 2, 2015

Our decisions are influenced in part by incoming sensory information, and in part by the current cognitive state of the brain. For instance, a rustle in the bushes can make you run away quickly if you are walking the dark and worrying about bears, but have little effect on your behavior if you are deep in thought about something else- your upcoming vacation, for instance. This led us to wonder, how do incoming sensory signals and ongoing cognitive signals interact to guide behavior?

A postdoc in my lab, Farzaneh Najafi, is working to understand this, supported in part by the Simons Collaboration on the Global Brain. We were fortunate to have a collaborator, John Cunningham (Columbia University) visit us today, along with a graduate student in his lab, Gamal Elsayed. Their focus is on understanding neural activity at the population level, and in particular understanding how such populations evolve over time. We hope that their approach can offer insight into our question by helping us evaluate how population dynamics differ depending on the internal cognitive state of the animal. Farzaneh, John and Gamal are pictured below. They are gathered at the 2-photon rig in our lab and are viewing neural activity of labelled inhibitory neurons.

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Fairhall lab

Computational neuroscience at the University of Washington

Pillow Lab Blog

Neural Coding and Computation Lab @ Princeton University

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Perceptual decision-making at Cold Spring Harbor

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