Leonie Koban

3.7k total citations · 2 hit papers
44 papers, 2.1k citations indexed

About

Leonie Koban is a scholar working on Cognitive Neuroscience, Social Psychology and Physiology. According to data from OpenAlex, Leonie Koban has authored 44 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Cognitive Neuroscience, 15 papers in Social Psychology and 10 papers in Physiology. Recurrent topics in Leonie Koban's work include Pain Management and Placebo Effect (15 papers), Neural and Behavioral Psychology Studies (13 papers) and Action Observation and Synchronization (12 papers). Leonie Koban is often cited by papers focused on Pain Management and Placebo Effect (15 papers), Neural and Behavioral Psychology Studies (13 papers) and Action Observation and Synchronization (12 papers). Leonie Koban collaborates with scholars based in United States, France and Switzerland. Leonie Koban's co-authors include Tor D. Wager, Gilles Pourtois, Stephan Geuter, Patrik Vuilleumier, Marieke Jepma, Hedy Kober, Marina López‐Solà, Choong‐Wan Woo, Yoni K. Ashar and Jessica R. Andrews‐Hanna and has published in prestigious journals such as Nature Communications, Neuron and Journal of Neuroscience.

In The Last Decade

Leonie Koban

44 papers receiving 2.1k citations

Hit Papers

The self in context: brain systems linking mental and phy... 2021 2026 2022 2024 2021 2021 40 80 120
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.

  1. The self in context: brain systems linking mental and physical health
    2021 121 citations Leonie Koban, Peter J. Gianaros et al. Nature reviews. Neuroscience profile →
  2. Gender Biases in Estimation of Others’ Pain
    2021 121 citations Elizabeth A. Reynolds Losin, Yoni K. Ashar et al. profile →

Peers

Leonie Koban
Trevor T.‐J. Chong Australia
Liane Schmidt France
Kathleen A. Garrison United States
Hamed Ekhtiari Iran
Christina B. Young United States
Madeleine S. Goodkind United States
Nils Kohn Germany
Françoise S. Maheu Canada
Oren Contreras‐Rodríguez Spain
Benjamin M. Robinson United States
Trevor T.‐J. Chong Australia
Leonie Koban
Citations per year, relative to Leonie Koban Leonie Koban (= 1×) peers Trevor T.‐J. Chong

Countries citing papers authored by Leonie Koban

Since Specialization
Citations

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

Fields of papers citing papers by Leonie Koban

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonie Koban

This figure shows the co-authorship network connecting the top 25 collaborators of Leonie Koban. A scholar is included among the top collaborators of Leonie Koban 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 Leonie Koban. Leonie Koban 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.
Simon, Marie‐Christine, et al.. (2024). Impact of the gut microbiome composition on social decision-making. PNAS Nexus. 3(5). pgae166–pgae166. 13 indexed citations
2.
3.
Krawitz, Peter, Peter Stehle, Bernd Weber, et al.. (2024). Beneficial Effects of Synbiotics on the Gut Microbiome in Individuals with Low Fiber Intake: Secondary Analysis of a Double-Blind, Randomized Controlled Trial. Nutrients. 16(13). 2082–2082. 5 indexed citations
4.
Djordjevic, Jelena, Marilyn Jones‐Gotman, Maria G. Veldhuizen, et al.. (2023). Odour-imagery ability is linked to food craving, intake, and adiposity change in humans. Nature Metabolism. 5(9). 1483–1493. 6 indexed citations
5.
Koban, Leonie, et al.. (2023). Brain mediators of biased social learning of self-perception in social anxiety disorder. Translational Psychiatry. 13(1). 292–292. 11 indexed citations
6.
Koban, Leonie, Sangil Lee, Marie‐Christine Simon, et al.. (2023). An fMRI-Based Brain Marker of Individual Differences in Delay Discounting. Journal of Neuroscience. 43(9). 1600–1613. 22 indexed citations
7.
Petre, Bogdan, Philip A. Kragel, Lauren Y. Atlas, et al.. (2022). A multistudy analysis reveals that evoked pain intensity representation is distributed across brain systems. PLoS Biology. 20(5). e3001620–e3001620. 11 indexed citations
8.
Atlas, Lauren Y., Christian Büchel, Jason T. Buhle, et al.. (2022). Individual variability in brain representations of pain. Nature Neuroscience. 25(6). 749–759. 35 indexed citations
9.
Han, Xiaochun, Yoni K. Ashar, Philip A. Kragel, et al.. (2021). Effect sizes and test-retest reliability of the fMRI-based neurologic pain signature. NeuroImage. 247. 118844–118844. 32 indexed citations
10.
Koban, Leonie, Peter J. Gianaros, Hedy Kober, & Tor D. Wager. (2021). The self in context: brain systems linking mental and physical health. Nature reviews. Neuroscience. 22(5). 309–322. 121 indexed citations breakdown →
11.
Geuter, Stephan, Elizabeth A. Reynolds Losin, Mathieu Roy, et al.. (2020). Multiple Brain Networks Mediating Stimulus–Pain Relationships in Humans. Cerebral Cortex. 30(7). 4204–4219. 39 indexed citations
12.
Yu, Hongbo, Leonie Koban, Luke J. Chang, et al.. (2020). A Generalizable Multivariate Brain Pattern for Interpersonal Guilt. Cerebral Cortex. 30(6). 3558–3572. 25 indexed citations
13.
Koban, Leonie, Marieke Jepma, Marina López‐Solà, & Tor D. Wager. (2019). Different brain networks mediate the effects of social and conditioned expectations on pain. Nature Communications. 10(1). 4096–4096. 57 indexed citations
14.
López‐Solà, Marina, Leonie Koban, Anjali Krishnan, & Tor D. Wager. (2017). When pain really matters: A vicarious-pain brain marker tracks empathy for pain in the romantic partner. Neuropsychologia. 145. 106427–106427. 21 indexed citations
15.
Lindquist, Martin A., Anjali Krishnan, Marina López‐Solà, et al.. (2015). Group-regularized individual prediction: theory and application to pain. NeuroImage. 145(Pt B). 274–287. 55 indexed citations
16.
Woo, Choong‐Wan, Leonie Koban, Ethan Kross, et al.. (2014). Separate neural representations for physical pain and social rejection. Nature Communications. 5(1). 5380–5380. 216 indexed citations
17.
Koban, Leonie, Marcel Braß, Margaret T. Lynn, & Gilles Pourtois. (2012). Placebo Analgesia Affects Brain Correlates of Error Processing. PLoS ONE. 7(11). e49784–e49784. 18 indexed citations
18.
Bediou, Benoît, et al.. (2012). Delayed monitoring of accuracy errors compared to commission errors in ACC. NeuroImage. 60(4). 1925–1936. 22 indexed citations
19.
Koban, Leonie, Corrado Corradi‐Dell’Acqua, & Patrik Vuilleumier. (2012). Integration of Error Agency and Representation of Others' Pain in the Anterior Insula. Journal of Cognitive Neuroscience. 25(2). 258–272. 53 indexed citations
20.

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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