Dobromir Rahnev

4.6k total citations
72 papers, 2.0k citations indexed

About

Dobromir Rahnev is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Developmental and Educational Psychology. According to data from OpenAlex, Dobromir Rahnev has authored 72 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Cognitive Neuroscience, 13 papers in Experimental and Cognitive Psychology and 7 papers in Developmental and Educational Psychology. Recurrent topics in Dobromir Rahnev's work include Neural and Behavioral Psychology Studies (43 papers), Neural dynamics and brain function (30 papers) and Visual perception and processing mechanisms (29 papers). Dobromir Rahnev is often cited by papers focused on Neural and Behavioral Psychology Studies (43 papers), Neural dynamics and brain function (30 papers) and Visual perception and processing mechanisms (29 papers). Dobromir Rahnev collaborates with scholars based in United States, Netherlands and United Kingdom. Dobromir Rahnev's co-authors include Hakwan Lau, Floris P. de Lange, Medha Shekhar, Rachel N. Denison, Peter Kok, Janneke F. M. Jehee, Ji Won Bang, Tobias H. Donner, Brian Maniscalco and Eugene M. Caruso and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

Dobromir Rahnev

68 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dobromir Rahnev United States 21 1.7k 403 192 126 125 72 2.0k
Brian Maniscalco United States 19 1.8k 1.1× 388 1.0× 229 1.2× 140 1.1× 144 1.2× 33 2.1k
Casimir J. H. Ludwig United Kingdom 23 1.4k 0.8× 341 0.8× 163 0.8× 119 0.9× 108 0.9× 55 1.7k
Vincent de Gardelle France 22 1.7k 1.0× 458 1.1× 197 1.0× 115 0.9× 127 1.0× 62 2.0k
Hannes Schröter Germany 17 1.4k 0.8× 567 1.4× 296 1.5× 207 1.6× 160 1.3× 45 1.7k
Jordan M. Province United States 7 933 0.5× 376 0.9× 275 1.4× 253 2.0× 116 0.9× 7 1.5k
Vera Maljkovic United States 10 2.2k 1.3× 556 1.4× 255 1.3× 129 1.0× 78 0.6× 17 2.5k
Filip Van Opstal Belgium 21 1.3k 0.7× 324 0.8× 187 1.0× 339 2.7× 140 1.1× 42 1.6k
Jérôme Sackur France 18 2.1k 1.3× 575 1.4× 324 1.7× 135 1.1× 64 0.5× 54 2.5k
Alejandro Lleras United States 24 1.9k 1.1× 557 1.4× 352 1.8× 170 1.3× 37 0.3× 92 2.4k
Patryk A. Laurent United States 14 1.5k 0.9× 384 1.0× 134 0.7× 120 1.0× 175 1.4× 19 1.7k

Countries citing papers authored by Dobromir Rahnev

Since Specialization
Citations

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

Fields of papers citing papers by Dobromir Rahnev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dobromir Rahnev

This figure shows the co-authorship network connecting the top 25 collaborators of Dobromir Rahnev. A scholar is included among the top collaborators of Dobromir Rahnev 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 Dobromir Rahnev. Dobromir Rahnev 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.
2.
Kim, Ji‐Hyun, et al.. (2025). Multiple brain activation patterns for the same perceptual decision-making task. Nature Communications. 16(1). 1785–1785. 1 indexed citations
3.
Shekhar, Medha, et al.. (2025). Similarities and differences in the effects of different stimulus manipulations on accuracy and confidence. Consciousness and Cognition. 136. 103942–103942. 1 indexed citations
4.
Rahnev, Dobromir, et al.. (2024). Task learning is subserved by a domain-general brain network. Cerebral Cortex. 34(2). 2 indexed citations
5.
Shekhar, Medha, et al.. (2024). Challenging the Bayesian confidence hypothesis in perceptual decision-making. Proceedings of the National Academy of Sciences. 121(48). e2410487121–e2410487121. 1 indexed citations
6.
Gao, Yi, et al.. (2024). Dynamics of sensory and decisional biases in perceptual decision making: Insights from the face distortion illusion. Psychonomic Bulletin & Review. 32(1). 317–325. 1 indexed citations
7.
Shekhar, Medha & Dobromir Rahnev. (2024). Human-like dissociations between confidence and accuracy in convolutional neural networks. PLoS Computational Biology. 20(11). e1012578–e1012578. 3 indexed citations
8.
Rahnev, Dobromir, et al.. (2024). Threat Expectation Does Not Improve Perceptual Discrimination despite Causing Heightened Priority Processing in the Frontoparietal Network. Journal of Neuroscience. 44(15). e1219232023–e1219232023. 2 indexed citations
9.
Gao, Yi, et al.. (2024). Objectively quantifying subjective phenomena: Measuring the flashed face distortion effect. Cognition. 250. 105861–105861. 2 indexed citations
10.
Rahnev, Dobromir, et al.. (2023). The timing of confidence computations in human prefrontal cortex. Cortex. 168. 167–175. 10 indexed citations
11.
Kim, Jihyun, et al.. (2023). Quantifying the contribution of subject and group factors in brain activation. Cerebral Cortex. 33(22). 11092–11101. 4 indexed citations
12.
Rahnev, Dobromir, et al.. (2020). The suboptimality of perceptual decision making with multiple alternatives. Nature Communications. 11(1). 3857–3857. 17 indexed citations
13.
Rahnev, Dobromir. (2020). Confidence in the Real World. Trends in Cognitive Sciences. 24(8). 590–591. 6 indexed citations
14.
Bang, Ji Won, et al.. (2019). Post-training TMS abolishes performance improvement and releases future learning from interference. Communications Biology. 2(1). 320–320. 14 indexed citations
15.
Verhaeghen, Paul, et al.. (2019). Resolving Age-Related Differences in Working Memory: Equating Perception and Attention Makes Older Adults Remember as Well as Younger Adults. Experimental Aging Research. 45(2). 120–134. 13 indexed citations
16.
Rahnev, Dobromir, et al.. (2018). On the nature of the perceptual representation at the decision stage. OSF Preprints (OSF Preprints). 1 indexed citations
17.
Michel, Matthias, Stephen M. Fleming, Hakwan Lau, et al.. (2018). An Informal Internet Survey on the Current State of Consciousness Science. Frontiers in Psychology. 9. 2134–2134. 23 indexed citations
18.
Bang, Ji Won & Dobromir Rahnev. (2017). Stimulus expectation alters decision criterion but not sensory signal in perceptual decision making. Scientific Reports. 7(1). 17072–17072. 68 indexed citations
19.
Lau, H. & Dobromir Rahnev. (2011). The paradoxical negative relationship between attention-related spontaneous neural activity and perceptual decisions. Journal of Vision. 11(11). 20–20. 1 indexed citations
20.
Kok, Peter, Dobromir Rahnev, Janneke F. M. Jehee, Hakwan Lau, & Floris P. de Lange. (2011). Attention Reverses the Effect of Prediction in Silencing Sensory Signals. Cerebral Cortex. 22(9). 2197–2206. 291 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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