Tiangang Zhou

1.5k total citations
40 papers, 1.0k citations indexed

About

Tiangang Zhou is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Cellular and Molecular Neuroscience. According to data from OpenAlex, Tiangang Zhou has authored 40 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Cognitive Neuroscience, 7 papers in Computer Vision and Pattern Recognition and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Tiangang Zhou's work include Visual perception and processing mechanisms (27 papers), Neural dynamics and brain function (20 papers) and Neural and Behavioral Psychology Studies (11 papers). Tiangang Zhou is often cited by papers focused on Visual perception and processing mechanisms (27 papers), Neural dynamics and brain function (20 papers) and Neural and Behavioral Psychology Studies (11 papers). Tiangang Zhou collaborates with scholars based in China, United States and Canada. Tiangang Zhou's co-authors include Fang Fang, Lixia He, Xilin Zhang, Li Zhaoping, Taiyong Bi, Yan Zhuo, Jun Zhang, Ke Zhou, Lin Chen and Nihong Chen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Journal of Neuroscience.

In The Last Decade

Tiangang Zhou

36 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tiangang Zhou China 15 745 153 126 122 89 40 1.0k
Edward F. Ester United States 18 2.0k 2.7× 55 0.4× 155 1.2× 89 0.7× 218 2.4× 31 2.1k
Ivilin Peev Stoianov Italy 17 614 0.8× 407 2.7× 146 1.2× 51 0.4× 111 1.2× 40 1.0k
J. Stephen Mansfield United States 16 975 1.3× 92 0.6× 198 1.6× 76 0.6× 150 1.7× 28 1.5k
Jason Fischer United States 17 1.4k 1.8× 65 0.4× 219 1.7× 129 1.1× 350 3.9× 37 1.6k
Ben M. Harvey Netherlands 21 1.5k 2.0× 581 3.8× 78 0.6× 53 0.4× 137 1.5× 53 1.8k
Christian Bernard France 21 1.1k 1.5× 63 0.4× 120 1.0× 128 1.0× 378 4.2× 43 1.5k
Peter J. Kohler United States 15 433 0.6× 53 0.3× 105 0.8× 85 0.7× 135 1.5× 41 660
Bart Farell United States 16 1.3k 1.8× 104 0.7× 231 1.8× 206 1.7× 326 3.7× 61 1.6k
Matteo Valsecchi Germany 21 1.1k 1.5× 36 0.2× 233 1.8× 166 1.4× 244 2.7× 72 1.3k
Zhuanghua Shi Germany 21 1.1k 1.4× 44 0.3× 147 1.2× 61 0.5× 470 5.3× 93 1.3k

Countries citing papers authored by Tiangang Zhou

Since Specialization
Citations

This map shows the geographic impact of Tiangang Zhou'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 Tiangang Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tiangang Zhou more than expected).

Fields of papers citing papers by Tiangang Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tiangang Zhou. 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 Tiangang Zhou. The network helps show where Tiangang Zhou may publish in the future.

Co-authorship network of co-authors of Tiangang Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Tiangang Zhou. A scholar is included among the top collaborators of Tiangang Zhou 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 Tiangang Zhou. Tiangang Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhou, Tiangang, et al.. (2024). Unravelling the object-based nature of visual working memory: insight from pointers. Memory & Cognition. 53(4). 1178–1186. 1 indexed citations
2.
Yang, Xinxin, Li‐Jun Ma, Chuan Fan, et al.. (2024). Efficacy and acceptability of brain stimulation for anxiety disorders, OCD, and PTSD: A systematic review and network meta-analysis of randomized controlled trials. Journal of Affective Disorders. 370. 62–75. 5 indexed citations
3.
Zuo, Zhentao, et al.. (2024). Brain-inspired dual-pathway neural network architecture and its generalization analysis. Science China Technological Sciences. 67(8). 2319–2330.
4.
Wang, Guoyin, Qun Liu, Tiangang Zhou, et al.. (2024). Brain-inspired artificial intelligence research: A review. Science China Technological Sciences. 67(8). 2282–2296. 11 indexed citations
5.
Zuo, Zhentao, Zejian Yuan, Tiangang Zhou, et al.. (2023). Neural representation of gestalt grouping and attention effect in human visual cortex. Journal of Neuroscience Methods. 399. 109980–109980.
6.
Zuo, Zhentao, et al.. (2023). Hybrid attention mechanism of feature fusion for medical image segmentation. IET Image Processing. 18(1). 77–87. 6 indexed citations
7.
Wang, Huan, Sainan Liu, Jun Huang, et al.. (2023). Form Properties of Moving Targets Bias Smooth Pursuit Target Selection in Monkeys. Neuroscience Bulletin. 39(8). 1246–1262. 2 indexed citations
8.
9.
Wei, Ning, Tiangang Zhou, & Lin Chen. (2017). Objective measurement of gestalts: Quantifying grouping effect by tilt aftereffect. Behavior Research Methods. 50(3). 963–971. 3 indexed citations
10.
Chen, Nihong, et al.. (2016). Perceptual learning modifies the functional specializations of visual cortical areas. Proceedings of the National Academy of Sciences. 113(20). 5724–5729. 62 indexed citations
11.
Chen, Cheng, Xilin Zhang, Yizhou Wang, Tiangang Zhou, & Fang Fang. (2016). Neural activities in V1 create the bottom-up saliency map of natural scenes. Experimental Brain Research. 234(6). 1769–1780. 12 indexed citations
12.
Chen, Nihong, Taiyong Bi, Tiangang Zhou, et al.. (2015). Sharpened cortical tuning and enhanced cortico-cortical communication contribute to the long-term neural mechanisms of visual motion perceptual learning. NeuroImage. 115. 17–29. 42 indexed citations
13.
Bi, Taiyong, Juan Chen, Tiangang Zhou, Yong He, & Fang Fang. (2014). Function and Structure of Human Left Fusiform Cortex Are Closely Associated with Perceptual Learning of Faces. Current Biology. 24(2). 222–227. 59 indexed citations
14.
Zhang, Xilin, Li Zhaoping, Tiangang Zhou, & Fang Fang. (2012). Neural Activities in V1 Create a Bottom-Up Saliency Map. Neuron. 73(1). 183–192. 150 indexed citations
15.
Huang, Yan, Tiangang Zhou, & Lin Chen. (2011). The precedence of topological change over top-down attention in masked priming. Journal of Vision. 11(12). 9–9. 13 indexed citations
16.
Zhou, Ke, Huan Luo, Tiangang Zhou, Yan Zhuo, & Lin Chen. (2010). Topological change disturbs object continuity in attentive tracking. Proceedings of the National Academy of Sciences. 107(50). 21920–21924. 56 indexed citations
17.
Chen, Juan, Tiangang Zhou, Hua Yang, & Fang Fang. (2010). Cortical Dynamics Underlying Face Completion in Human Visual System. Journal of Neuroscience. 30(49). 16692–16698. 14 indexed citations
18.
Bi, Taiyong, et al.. (2009). The effect of crowding on orientation-selective adaptation in human early visual cortex. Journal of Vision. 9(11). 13–13. 56 indexed citations
19.
Han, Shihui, Yi Jiang, Glyn W. Humphreys, Tiangang Zhou, & Peng Cai. (2004). Distinct neural substrates for the perception of real and virtual visual worlds. NeuroImage. 24(3). 928–935. 63 indexed citations
20.
Rao, Hengyi, Tiangang Zhou, Yan Zhuo, Silu Fan, & Lin Chen. (2002). Spatiotemporal activation of the two visual pathways in form discrimination and spatial location: A brain mapping study. Human Brain Mapping. 18(2). 79–89. 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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