Immanuel Elbau

1.7k total citations
21 papers, 487 citations indexed

About

Immanuel Elbau is a scholar working on Cognitive Neuroscience, Behavioral Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Immanuel Elbau has authored 21 papers receiving a total of 487 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cognitive Neuroscience, 5 papers in Behavioral Neuroscience and 5 papers in Experimental and Cognitive Psychology. Recurrent topics in Immanuel Elbau's work include Functional Brain Connectivity Studies (9 papers), Stress Responses and Cortisol (5 papers) and Tryptophan and brain disorders (4 papers). Immanuel Elbau is often cited by papers focused on Functional Brain Connectivity Studies (9 papers), Stress Responses and Cortisol (5 papers) and Tryptophan and brain disorders (4 papers). Immanuel Elbau collaborates with scholars based in United States, Germany and Austria. Immanuel Elbau's co-authors include Conor Liston, Charles J. Lynch, Elisabeth B. Binder, Jonathan D. Power, Michael Czisch, Cristiana Cruceanu, Philipp G. Sämann, Tanja Furtner, Ulrich Matt and Bianca Doninger and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Neuron.

In The Last Decade

Immanuel Elbau

19 papers receiving 484 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Immanuel Elbau United States 13 172 89 79 68 63 21 487
Elisa Guma Canada 14 168 1.0× 59 0.7× 36 0.5× 24 0.4× 64 1.0× 32 560
Federica Klaus United States 12 112 0.7× 211 2.4× 43 0.5× 94 1.4× 103 1.6× 32 659
Guojun Xie China 10 99 0.6× 40 0.4× 57 0.7× 51 0.8× 165 2.6× 56 465
Kimon Runge Germany 16 153 0.9× 89 1.0× 132 1.7× 22 0.3× 132 2.1× 55 708
Silke Jörgens Germany 14 144 0.8× 141 1.6× 52 0.7× 47 0.7× 88 1.4× 28 790
Ashley Novais Portugal 10 117 0.7× 53 0.6× 39 0.5× 27 0.4× 65 1.0× 11 478
Christina Uhlmann Germany 9 204 1.2× 46 0.5× 107 1.4× 159 2.3× 24 0.4× 12 480
Kyoji Okita Japan 14 128 0.7× 76 0.9× 41 0.5× 67 1.0× 61 1.0× 33 465
Zhong Zheng China 16 112 0.7× 120 1.3× 43 0.5× 32 0.5× 59 0.9× 51 583

Countries citing papers authored by Immanuel Elbau

Since Specialization
Citations

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

Fields of papers citing papers by Immanuel Elbau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Immanuel Elbau

This figure shows the co-authorship network connecting the top 25 collaborators of Immanuel Elbau. A scholar is included among the top collaborators of Immanuel Elbau 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 Immanuel Elbau. Immanuel Elbau 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.
Elbau, Immanuel, et al.. (2024). Discrete Representation Learning for Multivariate Time Series. PubMed. 2024. 1132–1136. 1 indexed citations
2.
3.
Elbau, Immanuel, Charles J. Lynch, Jonathan Downar, et al.. (2023). Functional Connectivity Mapping for rTMS Target Selection in Depression. American Journal of Psychiatry. 180(3). 230–240. 50 indexed citations
4.
Kühnel, Anne, Janine Arloth, Maik Ködel, et al.. (2023). Stress-induced brain responses are associated with BMI in women. Communications Biology. 6(1). 1031–1031. 9 indexed citations
5.
Lynch, Charles J., et al.. (2023). Precision mapping and transcranial magnetic stimulation of individual-specific functional brain networks in humans. STAR Protocols. 4(1). 102118–102118. 4 indexed citations
6.
Kühnel, Anne, Michael Czisch, Philipp G. Sämann, et al.. (2022). Spatiotemporal Dynamics of Stress-Induced Network Reconfigurations Reflect Negative Affectivity. Biological Psychiatry. 92(2). 158–169. 9 indexed citations
7.
Lynch, Charles J., Immanuel Elbau, Tommy Ng, et al.. (2022). Automated optimization of TMS coil placement for personalized functional network engagement. Neuron. 110(20). 3263–3277.e4. 52 indexed citations
8.
Lynch, Charles J., Immanuel Elbau, & Conor Liston. (2021). Improving precision functional mapping routines with multi-echo fMRI. Current Opinion in Behavioral Sciences. 40. 113–119. 21 indexed citations
9.
Lynch, Charles J., Immanuel Elbau, & Conor Liston. (2021). Optimizing TMS coil placement for engagingindividual-specific functional network topology. Brain stimulation. 14(6). 1689–1689. 1 indexed citations
10.
Brückl, Tanja, Victor I. Spoormaker, Philipp G. Sämann, et al.. (2020). The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes. BMC Psychiatry. 20(1). 213–213. 30 indexed citations
11.
Schneider, Max, Immanuel Elbau, Dorothee Pöhlchen, et al.. (2020). Pupil Dilation during Reward Anticipation Is Correlated to Depressive Symptom Load in Patients with Major Depressive Disorder. Brain Sciences. 10(12). 906–906. 15 indexed citations
12.
Kühnel, Anne, Nils B. Kroemer, Immanuel Elbau, et al.. (2020). Psychosocial stress reactivity habituates following acute physiological stress. Human Brain Mapping. 41(14). 4010–4023. 15 indexed citations
13.
Elbau, Immanuel, Cristiana Cruceanu, & Elisabeth B. Binder. (2019). Genetics of Resilience: Gene-by-Environment Interaction Studies as a Tool to Dissect Mechanisms of Resilience. Biological Psychiatry. 86(6). 433–442. 30 indexed citations
14.
Elbau, Immanuel, Manfred Uhr, Janine Arloth, et al.. (2018). The brain’s hemodynamic response function rapidly changes under acute psychosocial stress in association with genetic and endocrine stress response markers. Proceedings of the National Academy of Sciences. 115(43). E10206–E10215. 39 indexed citations
15.
Monje, Francisco J., et al.. (2017). Disrupted Ultradian Activity Rhythms and Differential Expression of Several Clock Genes in Interleukin-6-Deficient Mice. Frontiers in Neurology. 8. 99–99. 10 indexed citations
16.
Müller, N., Boris N. Konrad, Marcel Pawlowski, et al.. (2016). Ghrelin modulates encoding-related brain function without enhancing memory formation in humans. NeuroImage. 142. 465–473. 21 indexed citations
17.
Ronovsky, Marianne, et al.. (2014). Circadian abnormalities in a mouse model of high trait anxiety and depression. Annals of Medicine. 46(3). 148–154. 31 indexed citations
18.
IsHak, Waguih William, et al.. (2013). Quality of Life in Borderline Personality Disorder. Harvard Review of Psychiatry. 21(3). 138–150. 54 indexed citations
19.
Matt, Ulrich, Omar Sharif, Rui Martins, et al.. (2013). WAVE1 mediates suppression of phagocytosis by phospholipid-derived DAMPs. Journal of Clinical Investigation. 123(7). 3014–3024. 22 indexed citations
20.
Schabbauer, Gernot, Ulrich Matt, Joanna Warszawska, et al.. (2010). Myeloid PTEN Promotes Inflammation but Impairs Bactericidal Activities during Murine Pneumococcal Pneumonia. The Journal of Immunology. 185(1). 468–476. 73 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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