Elizabeth E. Steinberg

4.5k total citations · 2 hit papers
12 papers, 3.0k citations indexed

About

Elizabeth E. Steinberg is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Elizabeth E. Steinberg has authored 12 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cellular and Molecular Neuroscience, 6 papers in Molecular Biology and 5 papers in Cognitive Neuroscience. Recurrent topics in Elizabeth E. Steinberg's work include Photoreceptor and optogenetics research (7 papers), Neural dynamics and brain function (4 papers) and Neuroscience and Neuropharmacology Research (4 papers). Elizabeth E. Steinberg is often cited by papers focused on Photoreceptor and optogenetics research (7 papers), Neural dynamics and brain function (4 papers) and Neuroscience and Neuropharmacology Research (4 papers). Elizabeth E. Steinberg collaborates with scholars based in United States, Switzerland and Sweden. Elizabeth E. Steinberg's co-authors include Karl Deisseroth, Patricia H. Janak, Ilana B. Witten, Michael M. Merzenich, Daniel B. Polley, Josiah R. Boivin, Kevin T. Beier, Liqun Luo, Ronald Keiflin and Katherine E. DeLoach and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

Elizabeth E. Steinberg

12 papers receiving 2.9k citations

Hit Papers

Circuit Architecture of VTA Dopamine Neurons Revealed by ... 2013 2026 2017 2021 2015 2013 200 400 600
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. Circuit Architecture of VTA Dopamine Neurons Revealed by Systematic Input-Output Mapping
    2015 697 citations Kevin T. Beier, Elizabeth E. Steinberg et al. Cell profile →
  2. A causal link between prediction errors, dopamine neurons and learning
    2013 595 citations Elizabeth E. Steinberg, Ronald Keiflin et al. Nature Neuroscience profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Elizabeth E. Steinberg United States 11 1.9k 1.7k 904 273 259 12 3.0k
Jeremiah Y. Cohen United States 19 1.3k 0.7× 1.8k 1.0× 631 0.7× 180 0.7× 201 0.8× 41 2.5k
Katherine E. DeLoach United States 7 1.3k 0.7× 1.0k 0.6× 623 0.7× 304 1.1× 247 1.0× 8 2.1k
Jonathan T. Ting United States 21 2.1k 1.1× 2.0k 1.2× 1.3k 1.4× 181 0.7× 228 0.9× 41 3.9k
Donna J. Calu United States 23 1.8k 0.9× 1.5k 0.9× 673 0.7× 153 0.6× 347 1.3× 39 2.6k
Rutsuko Ito Canada 21 1.7k 0.9× 1.5k 0.9× 688 0.8× 118 0.4× 339 1.3× 49 2.6k
Christina K. Kim United States 16 1.8k 0.9× 1.4k 0.8× 748 0.8× 243 0.9× 379 1.5× 22 2.8k
Nadine Gogolla Germany 18 1.4k 0.7× 1.5k 0.9× 661 0.7× 177 0.6× 498 1.9× 20 3.2k
Matthias Prigge Germany 15 2.7k 1.4× 1.7k 1.0× 981 1.1× 287 1.1× 407 1.6× 22 3.8k
Ingo Willuhn Netherlands 23 1.8k 0.9× 1.1k 0.6× 772 0.9× 128 0.5× 368 1.4× 46 2.6k
Kyle S. Smith United States 22 1.7k 0.9× 1.6k 0.9× 549 0.6× 507 1.9× 498 1.9× 40 3.4k

Countries citing papers authored by Elizabeth E. Steinberg

Since Specialization
Citations

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

Fields of papers citing papers by Elizabeth E. Steinberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Elizabeth E. Steinberg. 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 Elizabeth E. Steinberg. The network helps show where Elizabeth E. Steinberg may publish in the future.

Co-authorship network of co-authors of Elizabeth E. Steinberg

This figure shows the co-authorship network connecting the top 25 collaborators of Elizabeth E. Steinberg. A scholar is included among the top collaborators of Elizabeth E. Steinberg 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 Elizabeth E. Steinberg. Elizabeth E. Steinberg is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Steinberg, Elizabeth E., Felicity Gore, Boris D. Heifets, et al.. (2020). Amygdala-Midbrain Connections Modulate Appetitive and Aversive Learning. Neuron. 106(6). 1026–1043.e9. 60 indexed citations
2.
Davidson, Thomas J., Matthew Brodsky, Ofer Yizhar, et al.. (2020). Recombinase-Driver Rat Lines: Tools, Techniques, and Optogenetic Application to Dopamine-Mediated Reinforcement. UNC Libraries. 1 indexed citations
3.
Heifets, Boris D., Paul Hoerbelt, Daniel F. Cardozo Pinto, et al.. (2019). Distinct neural mechanisms for the prosocial and rewarding properties of MDMA. Science Translational Medicine. 11(522). 72 indexed citations
4.
Beier, Kevin T., Elizabeth E. Steinberg, Katherine E. DeLoach, et al.. (2015). Circuit Architecture of VTA Dopamine Neurons Revealed by Systematic Input-Output Mapping. Cell. 162(3). 622–634. 697 indexed citations breakdown →
5.
Lammel, Stephan, Elizabeth E. Steinberg, Csaba Földy, et al.. (2015). Diversity of Transgenic Mouse Models for Selective Targeting of Midbrain Dopamine Neurons. Neuron. 85(2). 429–438. 259 indexed citations
6.
Berndt, A., Soo Yeun Lee, Jonas Wietek, et al.. (2015). Structural foundations of optogenetics: Determinants of channelrhodopsin ion selectivity. Proceedings of the National Academy of Sciences. 113(4). 822–829. 158 indexed citations
7.
Steinberg, Elizabeth E., Josiah R. Boivin, Benjamin T. Saunders, et al.. (2014). Positive Reinforcement Mediated by Midbrain Dopamine Neurons Requires D1 and D2 Receptor Activation in the Nucleus Accumbens. PLoS ONE. 9(4). e94771–e94771. 106 indexed citations
8.
Steinberg, Elizabeth E., Daniel J. Christoffel, Karl Deisseroth, & Robert C. Malenka. (2014). Illuminating circuitry relevant to psychiatric disorders with optogenetics. Current Opinion in Neurobiology. 30. 9–16. 56 indexed citations
9.
Steinberg, Elizabeth E., Ronald Keiflin, Josiah R. Boivin, et al.. (2013). A causal link between prediction errors, dopamine neurons and learning. Nature Neuroscience. 16(7). 966–973. 595 indexed citations breakdown →
10.
Steinberg, Elizabeth E. & Patricia H. Janak. (2012). Establishing causality for dopamine in neural function and behavior with optogenetics. Brain Research. 1511. 46–64. 36 indexed citations
11.
Witten, Ilana B., Elizabeth E. Steinberg, Soo Yeun Lee, et al.. (2011). Recombinase-Driver Rat Lines: Tools, Techniques, and Optogenetic Application to Dopamine-Mediated Reinforcement. Neuron. 72(5). 721–733. 490 indexed citations
12.
Polley, Daniel B., Elizabeth E. Steinberg, & Michael M. Merzenich. (2006). Perceptual Learning Directs Auditory Cortical Map Reorganization through Top-Down Influences. Journal of Neuroscience. 26(18). 4970–4982. 429 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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