Selected Publications

Rosedahl, L. A., Eckstein, M. P., & Ashby, F. G. (2018). Retinal-specific category learning. Nature Human Behaviour, 2(7), 500–506.

Eckstein, M. P., Koehler, K., Welbourne, L. E., & Akbas, E. (2017). Humans, but Not Deep Neural Networks, Often Miss Giant Targets in Scenes. Current Biology, 27(18), 2827-2832.e3.

Akbas, E., & Eckstein, M. P. (2017a). Object Detection Through Exploration With A Foveated Visual Field. PLOS Computational Biology, 13(10), e1005743.

Juni, M. Z., & Eckstein, M. P. (2017). The wisdom of crowds for visual search. Proceedings of the National Academy of Sciences, 114(21), E4306–E4315.

Eckstein, M. P. (2017). Probabilistic Computations for Attention, Eye Movements, and Search. Annual Review of Vision Science, 3(1), 319–342.

Tsank, Y., & Eckstein, M. P. (2017). Domain Specificity of Oculomotor Learning after Changes in Sensory Processing. Journal of Neuroscience, 37(47), 11469–11484.

Deza, A., & Eckstein, M. (2016). Can peripheral representations improve clutter metrics on complex scenes?. In Advances in Neural Information Processing Systems (pp. 2847-2855).

Peters, J. R., Srivastava, V., Taylor, G. S., Surana, A., Eckstein, M. P., & Bullo, F. (2015). Human supervisory control of robotic teams: integrating cognitive modeling with engineering design. IEEE Control Systems Magazine, 35(6), 57-80.

Ludwig, C. J., Davies, J. R., & Eckstein, M. P. (2014). Foveal analysis and peripheral selection during active visual sampling. Proceedings of the National Academy of Sciences, 111(2), E291-E299.

Preston, T. J., Guo, F., Das, K., Giesbrecht, B., & Eckstein, M. P. (2013). Neural representations of contextual guidance in visual search of real-world scenes. Journal of Neuroscience, 33(18), 7846-7855.

Peterson, M. F., & Eckstein, M. P. (2013). Individual differences in eye movements during face identification reflect observer-specific optimal points of fixation. Psychological science, 24(7), 1216-1225.

Peterson, M. F., & Eckstein, M. P. (2012). Looking just below the eyes is optimal across face recognition tasks. Proceedings of the National Academy of Sciences, 109(48), E3314-E3323.

Eckstein, M. P., Das, K., Pham, B. T., Peterson, M. F., Abbey, C. K., Sy, J. L., & Giesbrecht, B. (2012). Neural decoding of collective wisdom with multi-brain computing. NeuroImage, 59(1), 94-108.

Guo, F., Preston, T. J., Das, K., Giesbrecht, B., & Eckstein, M. P. (2012). Feature-independent neural coding of target detection during search of natural scenes. Journal of Neuroscience, 32(28), 9499-9510.

Eckstein, M. P. (2011). Visual search: A retrospective. Journal of vision, 11(5), 14-14.

Das, K., Giesbrecht, B., & Eckstein, M. P. (2010). Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers. Neuroimage, 51(4), 1425-1437.

Zhang, S., & Eckstein, M. P. (2010). Evolution and optimality of similar neural mechanisms for perception and action during search. PLoS Computational Biology, 6(9), e1000930.

Eckstein, M. P., Drescher, B. A., & Shimozaki, S. S. (2006). Attentional cues in real scenes, saccadic targeting, and Bayesian priors. Psychological science, 17(11), 973-980.

Zhang, Y., Pham, B. T., & Eckstein, M. P. (2006). The effect of nonlinear human visual system components on performance of a channelized Hotelling observer in structured backgrounds. IEEE Transactions on Medical Imaging, 25(10), 1348-1362.

Caspi, A., Beutter, B. R., & Eckstein, M. P. (2004). The time course of visual information accrual guiding eye movement decisions. Proceedings of the National Academy of Sciences, 101(35), 13086-13090.

Eckstein, M. P. (1998). The lower visual search efficiency for conjunctions is due to noise and not serial attentional processing. Psychological Science, 9(2), 111-118.