Joshua D. Berke

9.9k total citations · 5 hit papers
57 papers, 6.5k citations indexed

About

Joshua D. Berke is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Joshua D. Berke has authored 57 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Cellular and Molecular Neuroscience, 41 papers in Cognitive Neuroscience and 16 papers in Molecular Biology. Recurrent topics in Joshua D. Berke's work include Neural dynamics and brain function (32 papers), Neuroscience and Neuropharmacology Research (27 papers) and Neurotransmitter Receptor Influence on Behavior (16 papers). Joshua D. Berke is often cited by papers focused on Neural dynamics and brain function (32 papers), Neuroscience and Neuropharmacology Research (27 papers) and Neurotransmitter Receptor Influence on Behavior (16 papers). Joshua D. Berke collaborates with scholars based in United States, United Kingdom and France. Joshua D. Berke's co-authors include Steven E. Hyman, Howard Eichenbaum, Robert Schmidt, Jeffrey R. Pettibone, Anatol C. Kreitzer, Arif Hamid, Robert T. Kennedy, Vaughn L. Hetrick, Murat Okatan and Ali Mohebi and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Joshua D. Berke

56 papers receiving 6.4k citations

Hit Papers

Acute Effects of Cocaine ... 1997 2026 2006 2016 1997 2000 2018 2015 2019 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Joshua D. Berke 4.4k 3.3k 1.8k 887 401 57 6.5k
Henry H. Yin 5.2k 1.2× 4.4k 1.3× 1.8k 1.0× 1.1k 1.2× 820 2.0× 89 8.2k
Charles D. Blaha 5.3k 1.2× 2.1k 0.6× 2.4k 1.4× 1.3k 1.5× 648 1.6× 165 7.7k
Linda J. Porrino 5.1k 1.2× 3.0k 0.9× 1.8k 1.0× 636 0.7× 398 1.0× 145 8.0k
Ilana B. Witten 3.6k 0.8× 3.0k 0.9× 1.7k 1.0× 318 0.4× 582 1.5× 50 5.7k
Vikaas S. Sohal 5.4k 1.2× 5.0k 1.5× 2.1k 1.2× 349 0.4× 597 1.5× 88 8.7k
Mark A. Ungless 4.0k 0.9× 2.1k 0.6× 2.2k 1.2× 323 0.4× 517 1.3× 51 5.6k
Jeffery R. Wickens 4.1k 0.9× 3.9k 1.2× 1.4k 0.8× 1.1k 1.3× 331 0.8× 109 6.6k
François Gonon 5.9k 1.3× 1.9k 0.6× 2.9k 1.6× 1.2k 1.3× 310 0.8× 130 8.6k
Scott M. Thompson 6.2k 1.4× 2.7k 0.8× 2.8k 1.6× 460 0.5× 399 1.0× 117 9.3k
George V. Rebec 6.5k 1.5× 2.1k 0.6× 2.7k 1.5× 1.4k 1.5× 583 1.5× 200 8.5k

Countries citing papers authored by Joshua D. Berke

Since Specialization
Citations

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

Fields of papers citing papers by Joshua D. Berke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joshua D. Berke. 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 Joshua D. Berke. The network helps show where Joshua D. Berke may publish in the future.

Co-authorship network of co-authors of Joshua D. Berke

This figure shows the co-authorship network connecting the top 25 collaborators of Joshua D. Berke. A scholar is included among the top collaborators of Joshua D. Berke 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 Joshua D. Berke. Joshua D. Berke 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.
Poddar, Aunoy, Miguel Turrero Garcίa, Sean de la O, et al.. (2025). Conservation and alteration of mammalian striatal interneurons. PubMed. 647(8088). 187–193.
2.
Mohebi, Ali, et al.. (2024). Dopamine transients follow a striatal gradient of reward time horizons. Nature Neuroscience. 27(4). 737–746. 36 indexed citations
3.
Mohebi, Ali, et al.. (2024). A mismatch between striatal cholinergic pauses and dopaminergic reward prediction errors. Proceedings of the National Academy of Sciences. 121(41). e2410828121–e2410828121. 10 indexed citations
4.
Farries, Michael A., Thomas W. Faust, Ali Mohebi, & Joshua D. Berke. (2023). Selective encoding of reward predictions and prediction errors by globus pallidus subpopulations. Current Biology. 33(19). 4124–4135.e5. 11 indexed citations
5.
Mohebi, Ali, et al.. (2023). Accumbens cholinergic interneurons dynamically promote dopamine release and enable motivation. eLife. 12. 33 indexed citations
6.
Gu, Bon-Mi & Joshua D. Berke. (2022). Altered basal ganglia output during self-restraint. eLife. 11. 3 indexed citations
7.
Livezey, Jesse A., et al.. (2021). Improved inference in coupling, encoding, and decoding models and its consequence for neuroscientific interpretation. Journal of Neuroscience Methods. 358. 109195–109195. 1 indexed citations
8.
Pettibone, Jeffrey R., Paras R. Patel, Dawen Cai, et al.. (2020). Cellular-scale silicon probes for high-density, precisely localized neurophysiology. Journal of Neurophysiology. 124(6). 1578–1587. 14 indexed citations
9.
Patel, Paras R., Elissa Welle, Jeffrey R. Pettibone, et al.. (2020). High density carbon fiber arrays for chronic electrophysiology, fast scan cyclic voltammetry, and correlative anatomy. Journal of Neural Engineering. 17(5). 56029–56029. 36 indexed citations
10.
Pettibone, Jeffrey R., Jai Y. Yu, Thomas W. Faust, et al.. (2019). Knock-In Rat Lines with Cre Recombinase at the Dopamine D1 and Adenosine 2a Receptor Loci. eNeuro. 6(5). ENEURO.0163–19.2019. 20 indexed citations
11.
Mohebi, Ali & Joshua D. Berke. (2019). Dopamine release drives motivation, independently from dopamine cell firing. Neuropsychopharmacology. 45(1). 220–220. 8 indexed citations
12.
Berke, Joshua D.. (2018). What does dopamine mean?. Nature Neuroscience. 21(6). 787–793. 586 indexed citations breakdown →
13.
Howe, William M., Howard J. Gritton, Nicholas A. Lusk, et al.. (2017). Acetylcholine Release in Prefrontal Cortex Promotes Gamma Oscillations and Theta–Gamma Coupling during Cue Detection. Journal of Neuroscience. 37(12). 3215–3230. 96 indexed citations
14.
Mallet, Nicolas, Robert Schmidt, Daniel Leventhal, et al.. (2016). Arkypallidal Cells Send a Stop Signal to Striatum. Neuron. 89(2). 308–316. 153 indexed citations
15.
Klaus, Andreas, Henrike Planert, J. J. Johannes Hjorth, et al.. (2011). Striatal Fast-Spiking Interneurons: From Firing Patterns to Postsynaptic Impact. Frontiers in Systems Neuroscience. 5. 57–57. 25 indexed citations
16.
Stoetzner, Colin R., Jeffrey R. Pettibone, & Joshua D. Berke. (2009). State-dependent plasticity of the corticostriatal pathway. Neuroscience. 165(4). 1013–1018. 14 indexed citations
17.
Berke, Joshua D., et al.. (2004). Oscillatory Entrainment of Striatal Neurons in Freely Moving Rats. Neuron. 44(3). 571–571. 8 indexed citations
18.
Berke, Joshua D.. (2003). Analysis of mRNA Expression in Striatal Tissue by Differential Display Polymerase Chain Reaction. Humana Press eBooks. 79. 193–210. 1 indexed citations
19.
Karlsgodt, Katherine H., Randy L. Gollub, Robert M. Weisskoff, et al.. (1996). Activation of human brain reward circuitry by cocaine observed using FMRI. The Society for Neuroscience Abstracts. 22. 1933. 5 indexed citations
20.
Hasselmo, Michael E., Eric Schnell, Joshua D. Berke, & Edi Barkai. (1994). A model of the hippocampus combining self-organization and associative memory function. Neural Information Processing Systems. 7. 77–84. 8 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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