Publications

Sereno, A. & Taylor, J. (Eds.) (2027). The Binding Problem in the 21st Century: Perspectives across Mind, Brain, and Machine. Cambridge University Press. Forthcoming.

Xu, Y., Swinchoski, B., Taylor, J., & Chun, M. (2025). Interactive shape and color representation in visual working memory for colored objects in the human occipitotemporal cortex. Imaging Neuroscience, 3, IMAG.a.1049.

Taylor, J. & Xu, Y. (2024). Using fMRI to examine nonlinear mixed selectivity tuning to task and category in the human brain. Imaging Neuroscience, 2, imag-2-00354.

Golan, T., Taylor, J., Schütt, H., Peters, B., Sommers, R. P., Seeliger, K., et al., & Kriegeskorte, N. (2023). Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses. Behavioral and Brain Sciences, 46, e392.

Taylor, J. & Kriegeskorte, N. (2023). Extracting and visualizing hidden activations and computational graphs of PyTorch models with TorchLens. Scientific Reports, 13(1), 14375.

Taylor, J. & Xu, Y. (2023). Comparing the dominance of color and form information across the human ventral visual pathway and convolutional neural networks. Journal of Cognitive Neuroscience, 35(5), 816-840.

Taylor, J. & Xu, Y. (2022). Representation of color, form, and their conjunction across the human ventral visual pathway. NeuroImage, 251, 118941.

Taylor, J. & Xu, Y. (2022). Identifying the neural loci mediating conscious object orientation perception using fMRI MVPA. Cognitive Neuropsychology, 39(1-2), 64-67.

Taylor, J. & Xu, Y. (2021). Joint representation of color and form in convolutional neural networks: A stimulus-rich network perspective. PLOS ONE, 16(6), e0253442.

Vaziri-Pashkam, M., Taylor, J., & Xu, Y. (2019). Spatial frequency tolerant visual object representations in the human ventral and dorsal visual processing pathways. Journal of Cognitive Neuroscience, 31(1), 49-63.

Taylor, J., Shehzad, Z., & McCarthy, G. (2016). Electrophysiological correlates of face-evoked person knowledge. Biological Psychology, 118, 136-146.

Taylor, J., Schütt, H., & Kriegeskorte, N. (2025). Framed RSA: Representational comparisons that honor both geometry and population-mean response preferences. bioRxiv, 2025.07.10.664257.

Shehzad, Z., Taylor, J., & McCarthy, G. (2022). Localized and Distributed Representations of Person Knowledge for Faces. bioRxiv, 2022.03.27.485948.

Taylor, J. & Karakose-Akbiyik, S. (2026). Reimagining the binding problem(s) for the 21st century. 26th annual meeting of the Vision Sciences Society Conference. Symposium organized in St. Pete Beach, FL.

Taylor, J. & Xu, Y. (2026). Joint population coding of color and form in the human ventral pathway and convolutional neural networks. 26th annual meeting of the Vision Sciences Society Conference. Talk presented in St. Pete Beach, FL.

Taylor, J. & Kriegeskorte, N. (2025). Framed RSA: honoring representational geometry and regional-mean response preferences. 9th annual meeting of the Cognitive Computational Neuroscience Conference. Poster presented in Amsterdam, NL.

Taylor, J. & Kriegeskorte, N. (2025). Framed RSA: honoring representational geometry and regional-mean response preferences. 25th annual meeting of the Vision Sciences Society Conference. Talk presented in St. Pete Beach, FL.

Taylor, J. & Kriegeskorte, N. (2023). TorchLens: A Python package for extracting and visualizing hidden activations of PyTorch models. 7th annual meeting of the Cognitive Computational Neuroscience Conference. Poster presented in Oxford, UK.

Taylor, J. & Kriegeskorte, N. (2023). Torchlens: A Python package for extracting and visualizing all hidden layer activations from arbitrary PyTorch models with minimal code. 23rd annual meeting of the Vision Sciences Society Conference. Talk presented in St. Pete Beach, FL.

Taylor, J. & Xu, Y. (2021). The relative coding strength of color and form in the human ventral visual pathway and convolutional neural networks. 21st annual meeting of the Vision Sciences Society Conference. Poster presented in the virtual meeting.

Taylor, J. & Xu, Y. (2020). Conjunctive Coding of Color and Shape in Convolutional Neural Networks. 20th annual meeting of the Vision Sciences Society Conference. Poster presented in the virtual meeting.

Taylor, J. & Xu, Y. (2019). The Coding of Color, Shape, and their Conjunction Across the Human Ventral Visual System. 19th annual meeting of the Vision Sciences Society Conference. Talk presented in St. Pete Beach, FL.

Taylor, J. & Xu, Y. (2019). Conjunctive Coding of Color and Shape in Convolutional Neural Networks. 3rd annual meeting of the Cognitive Computational Neuroscience Conference. Poster presented in Berlin, DE.

Xu, Y., Taylor, J., & Vaziri-Pashkam, M. (2018). Probing Mixed Selectivity with fMRI Voxel Analysis. 18th annual meeting of the Vision Sciences Society Conference. Talk presented in St. Pete Beach, FL.

Taylor, J., Vaziri-Pashkam, M., & Xu, Y. (2017). Effect of task on object category representations across human ventral, dorsal, and frontal brain regions. 17th annual meeting of the Vision Sciences Society Conference. Poster presented in St. Pete Beach, FL.

Taylor, J. & Xu, Y. (2017). To bind or not to bind? Neural coding of color and shape. 47th Annual Meeting of the Society for Neuroscience. Talk presented in Washington D.C.

Taylor, J., Vaziri-Pashkam, M., & Xu, Y. (2016). Attention to Object Form Modulates Informational Connectivity Between Dorsal and Ventral Visual Streams. 46th Annual Meeting of the Society for Neuroscience. Poster presented in San Diego, CA.

Shehzad, Z., Taylor, J., & McCarthy, G. (2015). VATL Contributes to Biographical Knowledge of Faces via Feedback to FFA. 45th Annual Meeting of the Society for Neuroscience. Poster presented in Chicago, IL.