Cristopher Niell - Neural circuits for natural vision
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Neural circuits for natural vision
Abstract
Natural visual processing entails a complex interplay between sensory input, behavioral context, and on-going brain dynamics. Our lab seeks to understand how these processes give rise to goal-directed visual behaviors, by exploring the neural circuits mediating ethologically relevant behaviors that laboratory mice perform, including prey capture and distance estimation. We are also implementing novel experimental approaches to investigate neural coding of the visual scene as animals freely move through their environment. Finally, I will present a new research direction studying the completely different, yet largely unexplored, visual system of the octopus.In this work, we are elucidating both the functional and cell type organization to identify both shared and novel aspects of visual computation.
Cristopher Niell
University of Oregon
Cristopher Niell received his B.S. in physics at Stanford University, doing research in single-molecule biophysics with Dr. Steven Chu. He then remained at Stanford to obtain his PhD with Dr. Stephen Smith, studying the development and function of the zebrafish visual system. He then moved to UCSF to perform post-doctoral study with Dr. Michael Stryker, where he initiated studies of visual processing and behavioral state in the mouse cortex. He established his lab at University of Oregon in 2011, where he is now a Full Professor in the Department of Biology and Institute of Neuroscience. His lab uses a combination of neural recording and imaging methods, operant and ethological behaviors, and computational analysis to study the neural circuits that underlie visually guided behavior and perception.
Hosted by Owen Lab
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About the Wu Tsai Neurosciences Seminar Series
The Wu Tsai Neurosciences Institute seminar series brings together the Stanford neuroscience community to discuss cutting-edge, cross-disciplinary brain research, from biochemistry to behavior and beyond.
Topics include new discoveries in fundamental neurobiology; advances in human and translational neuroscience; insights from computational and theoretical neuroscience; and the development of novel research technologies and neuro-engineering breakthroughs.
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