Darby, K. P., Deng, S. W., Walther, D. B., & Sloutsky, V. M. (2020). The Development of Attention to Objects and Scenes: From Object‐Biased to Unbiased. Child Development. PDF

Perfetto, S., Wilder, J., & Walther, D. B. (2020). Effects of Spatial Frequency Filtering Choices on the Perception of Filtered Images. Vision, 4(2), 29.


Rezanejad, M., Downs, G., Wilder, J., Walther, D. B., Jepson, A., Dickinson, S., & Siddiqi, K. (2019). Scene categorization from contours: Medial axis based salience measures. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4116-4124). PDF

Damiano, C., & Walther, D. B. (2019). Distinct roles of eye movements during memory encoding and retrieval. Cognition, 184, 119-129. PDF

Damiano, C, Wilder, J, & Walther DB. (2019). Mid-level feature contributions to category-specific gaze guidance. Attention, Perception, & Psychophysics, 81: 35-46. PDF

Wilder J., Rezanejad M., Dickinson S., Siddiqi K., Jepson A., & Walther D.B. (2019). Local contour symmetry facilitates scene categorization. Cognition, 182: 307-317. PDF


Wilder, J, Dickinson, S, Jepson, A, & Walther DB. (2018). Spatial relationships between contours impact rapid scene classification. Journal of Vision. 18(8):1. PDF

Lowe, MX, Rajsic, J, Ferber, S, & Walther DB. (2018). Discriminating scene categories from brain activity within 100 ms. Cortex 106:275-287. PDF

O’Connell, TP, Sederberg, PB, & Walther DB. (2018). Representational differences between line drawings and photographs of natural scenes: A dissociation between multi-voxel pattern analysis and repetition suppression. Neuropsychologia, 117: 513–519. PDF

Jung, Y., Larsen, B., & Walther, D. B. (2018). Modality-independent coding of scene categories in prefrontal cortex. Journal of Neuroscience, 38(26), 5969-5981. PDF [stimuli]

Jung, Y., Larsen, B., & Walther, D. B. (2018, June). Using decoding error patterns to trace the neural signature of auditory scene perception. In 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI) (pp. 1-4). IEEE. PDF


Berman, D., Golomb, J. D., & Walther, D. B. (2017). Scene content is predominantly conveyed by high spatial frequencies in scene-selective visual cortex. PLoS One, 12(12), e0189828.

Choo, H., & Walther, D. B. (2017, June). Modeling the effect of stimulus perturbations on error correlations between brain and behavior. In 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI) (pp. 1-4). IEEE. PDF

Jung, Y., Larsen, B., & Walther, D. B. (2017). Modality-independent coding of concepts in prefrontal cortex. bioRxiv, 142562.

Choo, H., Nasar, J. L., Nikrahei, B., & Walther, D. B. (2017). Neural codes of seeing architectural styles. Scientific reports, 7(1), 1-8. PDF


Choo, H., & Walther, D. B. (2016). Contour junctions underlie neural representations of scene categories in high-level human visual cortex. Neuroimage, 135, 32-44. PDF


Damiano, C., & Walther, D. B. (2015). Content, not context, facilitates memory for real-world scenes. Visual Cognition, 23(7), 852-855. PDF

Olivetti, E., & Walther, D. B. (2015, June). A Bayesian Test for Comparing Classifier Errors. In 2015 International Workshop on Pattern Recognition in NeuroImaging (pp. 69-72). IEEE. PDF

O’Connell, T. P., & Walther, D. B. (2015). Dissociation of salience-driven and content-driven spatial attention to scene category with predictive decoding of gaze patterns. Journal of vision, 15(5), 20-20. PDF

Richards, M. R., Fields Jr, H. W., Beck, F. M., Firestone, A. R., Walther, D. B., Rosenstiel, S., & Sacksteder, J. M. (2015). Contribution of malocclusion and female facial attractiveness to smile esthetics evaluated by eye tracking. American Journal of Orthodontics and Dentofacial Orthopedics, 147(4), 472-482. PDF


Walther, D. B., & Shen, D. (2014). Nonaccidental properties underlie human categorization of complex natural scenes. Psychological science, 25(4), 851-860. PDF

Kim, K., Lin, K. H., Walther, D. B., Hasegawa-Johnson, M. A., & Huang, T. S. (2014). Automatic detection of auditory salience with optimized linear filters derived from human annotation. Pattern Recognition Letters, 38, 78-85. PDF


Walther, D. B. (2013, June). Using confusion matrices to estimate mutual information between two categorical measurements. In 2013 International Workshop on Pattern Recognition in Neuroimaging (pp. 220-224). IEEE. PDF

Torralbo, A., Walther, D. B., Chai, B., Caddigan, E., Fei-Fei, L., & Beck, D. M. (2013). Good exemplars of natural scene categories elicit clearer patterns than bad exemplars but not greater BOLD activity. PloS one, 8(3), e58594. PDF


Rivera S, Best C, Yim H, Martinez A, Sloutsky V, & Walther DB. (2012). Automatic selection of eye tracking variables in visual categorization for adults and infants. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society: 2240-2245. Austin, TX: Cognitive Science Society. PDF


Walther, D. B., Chai, B., Caddigan, E., Beck, D. M., & Fei-Fei, L. (2011). Simple line drawings suffice for functional MRI decoding of natural scene categories. Proceedings of the National Academy of Sciences (PNAS), 108(23), 9661-9666. PDF

Vo, L. T., Walther, D. B., Kramer, A. F., Erickson, K. I., Boot, W. R., Voss, M. W., … & Simons, D. J. (2011). Predicting individuals’ learning success from patterns of pre-learning MRI activity. PLoS One, 6(1), e16093. PDF


Chai B, Walther DB, Beck DM*, & Fei-Fei L*. (2009). Exploring Functional Connectivities of the Human Brain using Multivariate Information Analysis. In Advances in neural information processing systems (NIPS) (pp. 270-278). PDF

Yao B, Walther DB, Beck DM*, & Fei-Fei L*. (2009). Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions. In Advances in neural information processing systems (NIPS) (pp. 2178-2186). PDF

Walther, D. B., Caddigan, E., Fei-Fei, L., & Beck, D. M. (2009). Natural scene categories revealed in distributed patterns of activity in the human brain. Journal of neuroscience, 29(34), 10573-10581. PDF

Ning, H., Han, T. X., Walther, D. B., Liu, M., & Huang, T. S. (2009). Hierarchical space-time model enabling efficient search for human actions. IEEE Transactions on Circuits and Systems for Video Technology, 19(6), 808-820. PDF

(†,* indicates equal contribution)


Walther, D. B., & Fei-Fei, L. (2007). Task-set switching with natural scenes: measuring the cost of deploying top-down attention. Journal of Vision, 7(11), 9-9. PDF


Walther D. (2006). Interactions of visual attention and object recognition: computational modeling, algorithms, and psychophysics. PhD thesis, California Institute of Technology, Pasadena, CA, 23th February 2006.

Walther, D., & Koch, C. (2006). Modeling attention to salient proto-objects. Neural networks, 19(9), 1395-1407. PDF


Walther D, Rutishauser U, Koch C, & Perona P. (2005). Selective visual attention enables learning and recognition of multiple objects in cluttered scenes. Computer Vision and Image Understanding, 100, 41-63. PDF


Walther, D., Edgington, D. R., & Koch, C. (2004, June). Detection and tracking of objects in underwater video. In Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. (Vol. 1, pp. I-I). IEEE. PDF

Rutishauser, U., Walther, D., Koch, C., & Perona, P. (2004, June). Is bottom-up attention useful for object recognition?. In Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004. (Vol. 2, pp. II-II). IEEE. PDF

Walther, D., Rutishauser, U., Koch, C., & Perona, P. (2004, May). On the usefulness of attention for object recognition. In Workshop on Attention and Performance in Computational Vision at ECCV (pp. 96-103). PDF


Walther, D., Itti, L., Riesenhuber, M., Poggio, T., & Koch, C. (2002, November). Attentional selection for object recognition—a gentle way. In International workshop on biologically motivated computer vision (pp. 472-479). Springer, Berlin, Heidelberg. PDF

Chung D, Hirata R, Mundhenk TN, Ng J, Peters RJ, Pichon E, Tsui A, Ventrice T, Walther D, Williams P, & Itti L. (2002). A new robotics platform for neuromorphic vision: Beobots. In International Workshop on Biologically Motivated Computer Vision (pp. 558-566). Springer, Berlin, Heidelberg. PDF

Book Chapters:

Dirk B. Walther, Diane M. Beck, and Li Fei-Fei. (2012). To err is human: correlating fMRI decoding and behavioral errors to probe the neural representation of natural scene categories. in: Nikolaus Kriegeskorte and Gabriel Kreiman (eds.), Understanding visual population codes – Toward a common multivariate framework for cell recording and functional imaging, MIT Press, Cambridge, Massachusetts. PDF

Dirk B. Walther and Christof Koch. (2007). Attention in Hierarchical Models of Object Recognition. in Paul Cisek, Trevor Drew, and John F. Kalaska (eds.), Computational Neuroscience: Theoretical insights into brain function, Progress in Brain Research, 165: 57-78. PDF