Computational neuroscience research on human visual cognition.
Luo, A.F., Wehbe, L., Tarr, M.J., & Henderson, M.M. (2023). Neural Selectivity for Real-World Object Size in Natural Images. bioRxiv; under review.
Henderson, M.M. (2025). Visual input statistics and behavioral relevance jointly constrain higher visual cortex organization. Commentary in Cognitive Neuroscience. (pdf)
Yu, M., Nan, M., Adeli, H., Prince, J.S., Pyles, J.A., Wehbe, L., Henderson, M.M., Tarr, M.J., & Luo, A.F. (2025). Meta-learning an in-context transformer model of human higher visual cortex. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS).
Lahner, B., Luo, A., Prince, J.S., Deb, M., Henderson, M.M., Pyles, J.A., Wehbe, L., Oliva, A., Ratan Murty, N.A., & Tarr, M.J (2025). CONFORM: A Project to Create Crowd-Sourced Open Neuroscience fMRI Foundation Models. NeurIPS Foundation Models for the Brain and Body Workshop, NeurIPS Data on the Brain & Mind Workshop (tutorial).
Henderson, M.M., Serences, J.T., & Rungratsameetaweemana, N. (2025). Dynamic categorization rules alter representations in human visual cortex. Nature Communications. (pdf). Featured in: Columbia Engineering News.
Yeung, J., Luo, A.F., Sarch, G.H., Henderson, M.M., Ramanan, D., & Tarr, M.J. (2025). Reanimating images using neural representations of dynamic stimuli. Conference on Computer Vision and Pattern Recognition (CVPR); oral presentation.
Henderson, M.M., Tarr, M.J., & Wehbe, L. (2025). Origins of food selectivity in human visual cortex. Trends in Neurosciences. (pdf). Featured in: CMU Dietrich College News.
Luo, A.F., Yeung, J., Zawar, R., Dewan, S., Henderson, M.M., Wehbe, L., & Tarr, M.J. (2025). Brain Mapping with Dense Features: Grounding Cortical Semantic Selectivity in Natural Images with Vision Transformers. Proceedings of the International Conference on Learning Representations (ICLR).
Luo, A.F., Henderson, M.M., Tarr, M.J, & Wehbe, L. (2024). BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity. Proceedings of the International Conference on Learning Representations (ICLR).
Luo, A.F., Henderson, M.M., Wehbe, L., & Tarr, M.J. (2023). Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models. Proceedings of the Conference on Neural Information Processing Systems (NeurIPS); oral presentation.
Henderson, M.M., Tarr, M.J., & Wehbe, L. (2023). A texture statistics encoding model reveals hierarchical feature selectivity across human visual cortex. Journal of Neuroscience. (pdf)
Henderson, M.M., Tarr, M.J., & Wehbe, L. (2023). Low-level tuning biases in higher visual cortex reflect the semantic informativeness of visual features. Journal of Vision. (pdf)
Jain, N., Wang, A., Henderson, M.M., Lin, R., Prince, J.S., Tarr, M.J., & Wehbe, L. (2023). Selectivity for food in human ventral visual cortex. Communications Biology. (pdf)
Jinsi, O.* , Henderson, M.M.*, & Tarr, M.J. (2023). Early experience with low-pass filtered images facilitates visual category learning in a neural network model. PLOS ONE. (pdf)
Henderson, M.M., Rademaker, R.L., & Serences, J.T. (2022). Flexible utilization of spatial- and motor-based codes for the storage of visuo-spatial information. eLife. (pdf)
Henderson, M.M., & Serences, J.T. (2021). Biased orientation representations can be explained by experience with non-uniform training set statistics. Journal of Vision. (pdf)
Henderson, M.M.* , Vo, V.A.* , Chunharas, C., Sprague, T.C., & Serences, J.T. (2019). Multivariate analysis of BOLD activation patterns recovers graded depth representations in human visual and parietal cortex. eNeuro. (pdf)
Henderson, M.M. & Serences, J.T. (2019). Human frontoparietal cortex represents behaviorally relevant target status based on abstract object features. Journal of Neurophysiology. (pdf)
*These authors made equal contributions.