Michelle R. Greene, Ph.D

Affiliations: 
2004-2009 Brain and Cognitive Sciences Massachusetts Institute of Technology, Cambridge, MA, United States 
 2009-2011 Harvard Medical School - Brigham and Women's Hospital 
 2011-2017 Computer Science Stanford University, Palo Alto, CA 
 2015-2016 Computational Science Minerva Schools at KGI 
 2017-2023 Neuroscience Bates College, Lewiston, ME, United States 
 2023- Psychology Barnard College, Columbia University, New York, NY, United States 
Area:
Vision Science
Google:
"Michelle Greene"
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SNBCP
Cross-listing: PsychTree

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Publications

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Hansen BC, Greene MR, Field DJ. (2021) Dynamic Electrode-to-Image (DETI) mapping reveals the human brain's spatiotemporal code of visual information. Plos Computational Biology. 17: e1009456
Greene MR, Hansen BC. (2020) Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience
Hansen BC, Field DJ, Greene MR, et al. (2019) Towards a state-space geometry of neural responses to natural scenes: A steady-state approach. Neuroimage. 116027
Hansen B, Field D, Greene M. (2019) What steady state visual evoked potentials (SSVEP) tell us about the early representation of natural scenes. Journal of Vision. 19: 82
Greene MR, Field DJ, Hansen BC. (2019) Measuring the Information Content of Visually-Evoked Neuroelectric Activity Journal of Vision. 19: 48c
Self JS, Siegart J, Machoko M, et al. (2019) Diagnostic Objects Contribute to Late -- But Not Early-- Visual Scene Processing Journal of Vision. 19: 227
Siegart JL, Zhou W, Lam E, et al. (2019) The role of recurrent processing in visual scene categorization Journal of Vision. 19: 129b
Greene MR, Hansen BC. (2018) Shared spatiotemporal category representations in biological and artificial deep neural networks. Plos Computational Biology. 14: e1006327
Groen II, Greene MR, Baldassano C, et al. (2018) Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior. Elife. 7
Groen II, Greene MR, Baldassano C, et al. (2018) Author response: Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior Elife
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