Doris Y. Tsao

11.9k total citations · 2 hit papers
65 papers, 6.8k citations indexed

About

Doris Y. Tsao is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Doris Y. Tsao has authored 65 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Cognitive Neuroscience, 20 papers in Computer Vision and Pattern Recognition and 8 papers in Social Psychology. Recurrent topics in Doris Y. Tsao's work include Face Recognition and Perception (34 papers), Neural dynamics and brain function (32 papers) and Visual perception and processing mechanisms (26 papers). Doris Y. Tsao is often cited by papers focused on Face Recognition and Perception (34 papers), Neural dynamics and brain function (32 papers) and Visual perception and processing mechanisms (26 papers). Doris Y. Tsao collaborates with scholars based in United States, Germany and United Kingdom. Doris Y. Tsao's co-authors include Winrich A. Freiwald, Margaret S. Livingstone, Sebastian Moeller, Roger B. H. Tootell, Le Chang, Bevil R. Conway, Joseph B. Mandeville, T. Knutsen, Shay Ohayon and Wim Vanduffel and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Doris Y. Tsao

62 papers receiving 6.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Cortical Region Consisting Entirely of Face-Selective Cells

2006 810 citations Doris Y. Tsao, Winrich A. Freiwald et al. Science profile →
The Code for Facial Identity in the Primate Brain

2017 364 citations Le Chang, Doris Y. Tsao Cell profile →

Peers

Doris Y. Tsao

CN

CVPR

ECP

SP

CMN

Geoffrey M. Boynton United States

Yukiyasu Kamitani Japan

Winrich A. Freiwald United States

Josh H. McDermott United States

Kalanit Grill‐Spector United States

Leslie G. Ungerleider United States

Denis Fize France

Manfred Fahle Germany

Andrew T. Smith United Kingdom

Tirin Moore United States

Geoffrey M. Boynton United States

Doris Y. Tsao

7.5k ×1.3

CN

604 ×0.5

CVPR

1.3k ×1.3

ECP

633 ×0.7

SP

965 ×1.7

CMN

Citations per year, relative to Doris Y. Tsao Doris Y. Tsao (= 1×) peers Geoffrey M. Boynton

Countries citing papers authored by Doris Y. Tsao

Since Specialization

Citations

This map shows the geographic impact of Doris Y. Tsao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Doris Y. Tsao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Doris Y. Tsao more than expected).

Fields of papers citing papers by Doris Y. Tsao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Doris Y. Tsao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Doris Y. Tsao. The network helps show where Doris Y. Tsao may publish in the future.

Co-authorship network of co-authors of Doris Y. Tsao

This figure shows the co-authorship network connecting the top 25 collaborators of Doris Y. Tsao. A scholar is included among the top collaborators of Doris Y. Tsao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Doris Y. Tsao. Doris Y. Tsao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Wekselblatt, Joseph B., et al.. (2025). A compressed hierarchy for visual form processing in the tree shrew. Nature. 646(8086). 872–882.

2.

Tsao, Doris Y., et al.. (2025). A circuit that integrates drive state and social contact to gate mating. Nature. 646(8084). 394–403.

3.

Guo, Hongsun, Di Wu, Sangjin Yoo, et al.. (2023). Effects of focused ultrasound in a “clean” mouse model of ultrasonic neuromodulation. iScience. 26(12). 108372–108372. 12 indexed citations

4.

Ma, Yi, Doris Y. Tsao, & Heung‐Yeung Shum. (2022). On the principles of Parsimony and Self-consistency for the emergence of intelligence. Frontiers of Information Technology & Electronic Engineering. 23(9). 1298–1323. 30 indexed citations

5.

Richards, Blake A., Doris Y. Tsao, & Anthony M. Zador. (2022). The application of artificial intelligence to biology and neuroscience. Cell. 185(15). 2640–2643. 17 indexed citations

6.

Chang, Le, Bernhard Egger, Thomas Vetter, & Doris Y. Tsao. (2021). Explaining face representation in the primate brain using different computational models. Current Biology. 31(13). 2785–2795.e4. 30 indexed citations

7.

Higgins, Irina, Le Chang, Demis Hassabis, et al.. (2021). Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons. Nature Communications. 12(1). 6456–6456. 74 indexed citations

8.

Huang, Yujia, et al.. (2020). Neural Networks with Recurrent Generative Feedback. CaltechAUTHORS (California Institute of Technology). 33. 535–545. 3 indexed citations

9.

Bao, Pinglei, Liang She, Mason McGill, & Doris Y. Tsao. (2020). A map of object space in primate inferotemporal cortex. Nature. 583(7814). 103–108. 195 indexed citations

10.

Chang, Le & Doris Y. Tsao. (2017). The Code for Facial Identity in the Primate Brain. Cell. 169(6). 1013–1028.e14. 364 indexed citations breakdown →

11.

Chang, Le, Pinglei Bao, & Doris Y. Tsao. (2017). The representation of colored objects in macaque color patches. Nature Communications. 8(1). 2064–2064. 40 indexed citations

12.

Hesse, Janis K. & Doris Y. Tsao. (2016). Consistency of Border-Ownership Cells across Artificial Stimuli, Natural Stimuli, and Stimuli with Ambiguous Contours. Journal of Neuroscience. 36(44). 11338–11349. 21 indexed citations

13.

Dubois, Julien, et al.. (2015). Single-Unit Recordings in the Macaque Face Patch System Reveal Limitations of fMRI MVPA. Journal of Neuroscience. 35(6). 2791–2802. 111 indexed citations

14.

Kornblith, Simon, Xueqi Cheng, Shay Ohayon, & Doris Y. Tsao. (2013). A Network for Scene Processing in the Macaque Temporal Lobe. Neuron. 79(4). 766–781. 100 indexed citations

15.

Moeller, Sebastian, et al.. (2013). Faces in Motion: Selectivity of Macaque and Human Face Processing Areas for Dynamic Stimuli. Journal of Neuroscience. 33(29). 11768–11773. 46 indexed citations

16.

Ohayon, Shay, Winrich A. Freiwald, & Doris Y. Tsao. (2012). What Makes a Cell Face Selective? The Importance of Contrast. Neuron. 74(3). 567–581. 98 indexed citations

17.

Freiwald, Winrich A. & Doris Y. Tsao. (2011). Taking Apart the Neural Machinery of Face Processing. Oxford University Press eBooks. 9 indexed citations

18.

Freiwald, Winrich A. & Doris Y. Tsao. (2010). Functional Compartmentalization and Viewpoint Generalization Within the Macaque Face-Processing System. Science. 330(6005). 845–851. 481 indexed citations

19.

Conway, Bevil R. & Doris Y. Tsao. (2005). Color Architecture in Alert Macaque Cortex Revealed by fMRI. Cerebral Cortex. 16(11). 1604–1613. 70 indexed citations

20.

Livingstone, Margaret S. & Doris Y. Tsao. (1999). Receptive fields of disparity-selective neurons in macaque striate cortex. Nature Neuroscience. 2(9). 825–832. 34 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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