Jan Haaker

2.7k total citations
42 papers, 1.3k citations indexed

About

Jan Haaker is a scholar working on Cognitive Neuroscience, Behavioral Neuroscience and Social Psychology. According to data from OpenAlex, Jan Haaker has authored 42 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Cognitive Neuroscience, 19 papers in Behavioral Neuroscience and 16 papers in Social Psychology. Recurrent topics in Jan Haaker's work include Memory and Neural Mechanisms (21 papers), Stress Responses and Cortisol (19 papers) and Neuroendocrine regulation and behavior (15 papers). Jan Haaker is often cited by papers focused on Memory and Neural Mechanisms (21 papers), Stress Responses and Cortisol (19 papers) and Neuroendocrine regulation and behavior (15 papers). Jan Haaker collaborates with scholars based in Germany, Sweden and United States. Jan Haaker's co-authors include Tina B. Lonsdorf, Raffaël Kalisch, Andreas Olsson, Armita Golkar, Dirk Hermans, Dirk Schümann, Mareike M. Menz, Nico Bunzeck, Matthias Gamer and Stefanie Brassen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Jan Haaker

40 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Haaker Germany 20 826 505 386 281 272 42 1.3k
David T. Hsu United States 19 512 0.6× 408 0.8× 349 0.9× 332 1.2× 278 1.0× 34 1.3k
Lindsey Ossewaarde Netherlands 11 584 0.7× 593 1.2× 424 1.1× 255 0.9× 409 1.5× 14 1.7k
Marijn C. W. Kroes Netherlands 24 1.2k 1.5× 332 0.7× 218 0.6× 344 1.2× 368 1.4× 39 1.6k
Marta Andreatta Germany 20 854 1.0× 361 0.7× 242 0.6× 225 0.8× 521 1.9× 63 1.4k
Justin M. Moscarello United States 16 739 0.9× 364 0.7× 327 0.8× 456 1.6× 230 0.8× 28 1.2k
Armita Golkar Sweden 19 797 1.0× 335 0.7× 346 0.9× 215 0.8× 351 1.3× 30 1.2k
Kelimer Lebrón‐Milad United States 13 833 1.0× 973 1.9× 622 1.6× 408 1.5× 218 0.8× 16 1.6k
Maxine Norcross United States 12 566 0.7× 438 0.9× 283 0.7× 332 1.2× 398 1.5× 13 1.3k
Ruben P. Alvarez United States 13 1.4k 1.7× 514 1.0× 264 0.7× 297 1.1× 649 2.4× 18 1.8k
F. Caroline Davis United States 16 1.4k 1.7× 339 0.7× 359 0.9× 206 0.7× 663 2.4× 27 2.1k

Countries citing papers authored by Jan Haaker

Since Specialization
Citations

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

Fields of papers citing papers by Jan Haaker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Haaker

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Haaker. A scholar is included among the top collaborators of Jan Haaker 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 Jan Haaker. Jan Haaker 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.
Cohen, Oded, et al.. (2024). Downstream effects of observational threat learning: Generalization and reversal learning across development. Behaviour Research and Therapy. 184. 104670–104670.
3.
Fadai, Tahmine, et al.. (2024). Nicotine reduces discrimination between threat and safety in the hippocampus, nucleus accumbens and amygdala. Translational Psychiatry. 14(1). 319–319. 1 indexed citations
4.
Kanske, Philipp, et al.. (2023). Acetylcholine and metacognition during sleep. Consciousness and Cognition. 117. 103608–103608. 10 indexed citations
5.
Eikemo, Marie, et al.. (2022). Opioid antagonism in humans: a primer on optimal dose and timing for central mu-opioid receptor blockade. Neuropsychopharmacology. 48(2). 299–307. 16 indexed citations
6.
Haaker, Jan, et al.. (2022). Smokers show increased fear responses towards safety signals during fear generalization, independent from acute smoking. Scientific Reports. 12(1). 8692–8692. 3 indexed citations
7.
Esser, Roland W., et al.. (2022). Acquisition of threat responses are associated with elevated plasma concentration of endocannabinoids in male humans. Neuropsychopharmacology. 47(11). 1931–1938. 7 indexed citations
8.
Tinnermann, Alexandra, Christian Büchel, & Jan Haaker. (2021). Observation of others’ painful heat stimulation involves responses in the spinal cord. Science Advances. 7(14). 10 indexed citations
9.
Mancke, Falk, Sabine C. Herpertz, Martin Jungkunz, et al.. (2020). Intact Classical Fear Conditioning to Interpersonally Threatening Stimuli in Borderline Personality Disorder. Psychopathology. 53(2). 84–94. 1 indexed citations
10.
Haaker, Jan, Tina B. Lonsdorf, Dirk Schümann, et al.. (2017). Where There is Smoke There is Fear—Impaired Contextual Inhibition of Conditioned Fear in Smokers. Neuropsychopharmacology. 42(8). 1640–1646. 10 indexed citations
11.
Lindström, Björn, Jan Haaker, & Andreas Olsson. (2017). A common neural network differentially mediates direct and social fear learning. NeuroImage. 167. 121–129. 53 indexed citations
12.
Haaker, Jan, Armita Golkar, Ida Selbing, & Andreas Olsson. (2017). Assessment of social transmission of threats in humans using observational fear conditioning. Nature Protocols. 12(7). 1378–1386. 46 indexed citations
13.
Biedermann, Sarah V., Matthias K. Auer, Klaus Wiedemann, et al.. (2017). An elevated plus-maze in mixed reality for studying human anxiety-related behavior. BMC Biology. 15(1). 125–125. 95 indexed citations
14.
Haaker, Jan, Tina B. Lonsdorf, & Raffaël Kalisch. (2015). Effects of post-extinction l-DOPA administration on the spontaneous recovery and reinstatement of fear in a human fMRI study. European Neuropsychopharmacology. 25(10). 1544–1555. 32 indexed citations
15.
Golkar, Armita, et al.. (2015). Neural correlates of biased social fear learning and interaction in an intergroup context. NeuroImage. 121. 171–183. 28 indexed citations
16.
Haaker, Jan, Tina B. Lonsdorf, Dirk Schümann, et al.. (2015). Deficient inhibitory processing in trait anxiety: Evidence from context-dependent fear learning, extinction recall and renewal. Biological Psychology. 111. 65–72. 59 indexed citations
17.
Lonsdorf, Tina B., Armita Golkar, Kara M. Lindström, et al.. (2014). BDNFval66met affects neural activation pattern during fear conditioning and 24 h delayed fear recall. Social Cognitive and Affective Neuroscience. 10(5). 664–671. 35 indexed citations
18.
Haaker, Jan, Armita Golkar, Dirk Hermans, & Tina B. Lonsdorf. (2014). A review on human reinstatement studies: an overview and methodological challenges. Learning & Memory. 21(9). 424–440. 137 indexed citations
19.
Haaker, Jan, Stefano Gaburro, Anupam Sah, et al.. (2013). Single dose of l -dopa makes extinction memories context-independent and prevents the return of fear. Proceedings of the National Academy of Sciences. 110(26). E2428–36. 133 indexed citations
20.
Strange, Bryan A., et al.. (2013). Dopamine receptor 4 promoter polymorphism modulates memory and neuronal responses to salience. NeuroImage. 84. 922–931. 11 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026