Nitzan Censor

2.6k total citations
50 papers, 1.8k citations indexed

About

Nitzan Censor is a scholar working on Cognitive Neuroscience, Neurology and Experimental and Cognitive Psychology. According to data from OpenAlex, Nitzan Censor has authored 50 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Cognitive Neuroscience, 7 papers in Neurology and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Nitzan Censor's work include Neural dynamics and brain function (23 papers), Memory and Neural Mechanisms (19 papers) and Neural and Behavioral Psychology Studies (15 papers). Nitzan Censor is often cited by papers focused on Neural dynamics and brain function (23 papers), Memory and Neural Mechanisms (19 papers) and Neural and Behavioral Psychology Studies (15 papers). Nitzan Censor collaborates with scholars based in Israel, United States and Germany. Nitzan Censor's co-authors include Leonardo G. Cohen, Dov Sagi, Eran Dayan, Marco Sandrini, Ethan R. Buch, Avi Karni, Michael A. Dimyan, Marlene Bönstrup, Iñaki Iturrate and Ayelet Arazi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Neuron and Journal of Neuroscience.

In The Last Decade

Nitzan Censor

47 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nitzan Censor Israel	21	1.4k	555	261	182	163	50	1.8k
Bradley R. King United States	20	1.4k 0.9×	324 0.6×	207 0.8×	157 0.9×	299 1.8×	58	1.6k
Anke Ninija Karabanov Denmark	23	1.1k 0.8×	866 1.6×	174 0.7×	220 1.2×	136 0.8×	47	1.6k
Anna Fertonani Italy	13	1.2k 0.9×	1.1k 2.1×	232 0.9×	165 0.9×	98 0.6×	14	1.6k
Jason D. Forte Australia	20	1.4k 1.0×	1.1k 1.9×	190 0.7×	195 1.1×	137 0.8×	48	1.8k
Matteo Feurra Italy	19	1.2k 0.8×	776 1.4×	199 0.8×	111 0.6×	145 0.9×	54	1.5k
Alexandre Zénon Belgium	20	1.2k 0.9×	192 0.3×	217 0.8×	133 0.7×	213 1.3×	52	1.7k
Anna Floyer-Lea United Kingdom	6	881 0.6×	354 0.6×	270 1.0×	225 1.2×	56 0.3×	6	1.3k
Marco Sandrini Italy	26	1.9k 1.3×	1.5k 2.7×	244 0.9×	257 1.4×	212 1.3×	44	2.5k
Stephan A. Brandt Germany	22	2.7k 1.9×	401 0.7×	246 0.9×	103 0.6×	326 2.0×	56	3.2k
Valeria Della‐Maggiore Argentina	22	1.2k 0.8×	264 0.5×	154 0.6×	172 0.9×	107 0.7×	41	1.6k

Countries citing papers authored by Nitzan Censor

Since Specialization

Citations

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

Fields of papers citing papers by Nitzan Censor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nitzan Censor

This figure shows the co-authorship network connecting the top 25 collaborators of Nitzan Censor. A scholar is included among the top collaborators of Nitzan Censor 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 Nitzan Censor. Nitzan Censor 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

Sasaki, Yuka, et al.. (2025). Brief memory reactivations enable generalization of offline visual perceptual learning mechanisms. Scientific Reports. 15(1). 22137–22137.

Shahar, Moni, et al.. (2024). Convolutional neural networks uncover the dynamics of human visual memory representations over time. Cerebral Cortex. 34(11).

Sharon, Haggai, et al.. (2024). Distinct Neural Plasticity Enhancing Visual Perception. Journal of Neuroscience. 44(36). e0301242024–e0301242024. 1 indexed citations

Bar‐Haim, Yair, et al.. (2024). Memory modulation: Dominance of negative visual context over neutral verbal memory. PLoS ONE. 19(10). e0312042–e0312042. 1 indexed citations

Shahar, Moni, et al.. (2023). Initial motor skill performance predicts future performance, but not learning. Scientific Reports. 13(1). 11359–11359. 3 indexed citations

Censor, Nitzan, et al.. (2023). Modulating temporal dynamics of performance across retinotopic locations enhances the generalization of perceptual learning. iScience. 26(11). 108276–108276. 3 indexed citations

Rosenblatt, Jonathan D., et al.. (2022). A distinct route for efficient learning and generalization in autism. Current Biology. 32(14). 3203–3209.e3. 4 indexed citations

Dotan, Dror, et al.. (2022). Brief memory reactivations induce learning in the numeric domain. npj Science of Learning. 7(1). 18–18.

Sharon, Haggai, et al.. (2021). Reactivation-induced motor skill learning. Proceedings of the National Academy of Sciences. 118(23). 20 indexed citations

10.

Bar‐Haim, Yair, et al.. (2021). Intrinsic Functional Connectivity of the Anterior Cingulate Cortex Is Associated with Tolerance to Distress. eNeuro. 8(5). ENEURO.0277–21.2021. 5 indexed citations

11.

Bönstrup, Marlene, Iñaki Iturrate, Martin N. Hebart, Nitzan Censor, & Leonardo G. Cohen. (2020). Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data. npj Science of Learning. 5(1). 7–7. 54 indexed citations

12.

Bar‐Haim, Yair, et al.. (2020). Intrusive memories: A mechanistic signature for emotional memory persistence. Behaviour Research and Therapy. 135. 103752–103752. 19 indexed citations

13.

Gabitov, Ella, Arnaud Boutin, Basile Pinsard, et al.. (2019). Susceptibility of consolidated procedural memory to interference is independent of its active task-based retrieval. PLoS ONE. 14(1). e0210876–e0210876. 7 indexed citations

14.

Censor, Nitzan, et al.. (2017). Memory Reactivation Enables Long-Term Prevention of Interference. Current Biology. 27(10). 1529–1534.e2. 20 indexed citations

15.

Censor, Nitzan, et al.. (2016). A dissociation between consolidated perceptual learning and sensory adaptation in vision. Scientific Reports. 6(1). 38819–38819. 17 indexed citations

16.

Arazi, Ayelet, Nitzan Censor, & Ilan Dinstein. (2016). Neural Variability Quenching Predicts Individual Perceptual Abilities. Journal of Neuroscience. 37(1). 97–109. 59 indexed citations

17.

Censor, Nitzan. (2013). Generalization of perceptual and motor learning: A causal link with memory encoding and consolidation?. Neuroscience. 250. 201–207. 42 indexed citations

18.

Censor, Nitzan & Leonardo G. Cohen. (2010). Using repetitive transcranial magnetic stimulation to study the underlying neural mechanisms of human motor learning and memory. The Journal of Physiology. 589(1). 21–28. 48 indexed citations

19.

Censor, Nitzan, Yoram Bonneh, Amos Arieli, & Dov Sagi. (2009). Early-vision brain responses which predict human visual segmentation and learning. Journal of Vision. 9(4). 12–12. 27 indexed citations

20.

Censor, Nitzan & Dov Sagi. (2008). Benefits of efficient consolidation: Short training enables long-term resistance to perceptual adaptation induced by intensive testing. Vision Research. 48(7). 970–977. 50 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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