Tadros, T., Cullen, N., Greene, M.R., & Cooper, E.A. Assessing Neural Network Scene Classification from Degraded Images. ACM Transactions on Applied Perception, 14.4(2019): 21.

Hansen, B. C., Field, D. J., Greene, M. R., Olson, C., & Miskovic, V. Towards a state-space geometry of neural responses to natural scenes: A steady-state approach. NeuroImage, 201, 116027.

Greene, M. R. (2019). The information content of scene categories.. In Federmeier & Beck (eds) Knowledge and Vision: Volume 70.


Greene, M. R., & Hansen, B. C. (2018). Shared spatiotemporal category representations in biological and artificial deep neural networks. PLoS Computational Biology, 14(7), e1006327.
Data Link at Open Science Framework

Greene, M. R., & Hansen, B. C. (2018). From Pixels to Scene Categories: Unique and Early Contributions of Functional and Visual Features. Computational Cognitive Neuroscience. Winner, Best Paper Award

Groen, I. I., Greene, M. R., Baldassano, C., Fei-Fei, L., Beck, D. M., & Baker, C. I. (2018). Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior. Elife, 7, e32962.


Greene, M. R., Baldassano, C., Esteva, A., Beck, D. M., & Fei-Fei, L. (2016). Visual scenes are categorized by function. Journal of Experimental Psychology: General, 145(1), 82.

Iordan, M. C., Greene, M. R., Beck, D. M., & Fei-Fei, L. (2016). Typicality sharpens category representations in object-selective cortex. Neuroimage, 134, 170-179.

Greene, M. R. (2016). Estimations of object frequency are frequently overestimated. Cognition, 149, 6-10.

Vessel, E. A., Biederman, I., Subramaniam, S., & Greene, M. R. (2016). Effective signaling of surface boundaries by L-vertices reflect the consistency of their contrast in natural images. Journal of Vision, 16(9), 15-15.


Greene, M. R., Botros, A. P., Beck, D. M., & Fei-Fei, L. (2015). What you see is what you expect: rapid scene understanding benefits from prior experience. Attention, Perception, & Psychophysics, 77(4), 1239-1251.

Iordan, M. C., Greene, M. R., Beck, D. M., & Fei-Fei, L. (2015). Basic level category structure emerges gradually across human ventral visual cortex. Journal of Cognitive Neuroscience, 27(7), 1427-1446.


Greene, M. R., & Fei-Fei, L. (2014). Visual categorization is automatic and obligatory: Evidence from Stroop-like paradigm. Journal of Vision, 14(1), 14-14.


Greene, M. R. (2013). Statistics of high-level scene context. Frontiers in Psychology, 4, 777.

Boucart, M., Moroni, C., Thibaut, M., Szaffarczyk, S., & Greene, M. (2013). Scene categorization at large visual eccentricities. Vision Research, 86, 35-42.


Greene, M. R., Liu, T., & Wolfe, J. M. (2012). Reconsidering Yarbus: A failure to predict observers’ task from eye movement patterns. Vision Research, 62, 1-8.


Greene, M. R., & Wolfe, J. M. (2011). Global image properties do not guide visual search. Journal of Vision, 11(6), 18-18.

Wolfe, J. M., Võ, M. L. H., Evans, K. K., & Greene, M. R. (2011). Visual search in scenes involves selective and nonselective pathways. Trends in Cognitive Sciences, 15(2), 77-84.

Park, S., Brady, T. F., Greene, M. R., & Oliva, A. (2011). Disentangling scene content from spatial boundary: complementary roles for the parahippocampal place area and lateral occipital complex in representing real-world scenes. Journal of Neuroscience, 31(4), 1333-1340.


Greene, M. R., & Oliva, A. (2010). High-level aftereffects to global scene properties. Journal of Experimental Psychology: Human Perception and Performance, 36(6), 1430.


Greene, M. R., & Oliva, A. (2009). Recognition of natural scenes from global properties: Seeing the forest without representing the trees. Cognitive Psychology, 58(2), 137-176.

Greene, M. R., & Oliva, A. (2009). The briefest of glances: The time course of natural scene understanding. Psychological Science, 20(4), 464-472.