Brian E. Derrick

1.5k total citations
26 papers, 1.1k citations indexed

About

Brian E. Derrick is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Brian E. Derrick has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Cellular and Molecular Neuroscience, 17 papers in Cognitive Neuroscience and 8 papers in Molecular Biology. Recurrent topics in Brian E. Derrick's work include Neuroscience and Neuropharmacology Research (24 papers), Memory and Neural Mechanisms (15 papers) and Neural dynamics and brain function (7 papers). Brian E. Derrick is often cited by papers focused on Neuroscience and Neuropharmacology Research (24 papers), Memory and Neural Mechanisms (15 papers) and Neural dynamics and brain function (7 papers). Brian E. Derrick collaborates with scholars based in United States and Mexico. Brian E. Derrick's co-authors include Joe L. Martinez, Cyndy D. Davis, Carlo O. Martinez, Joanna L. Jankowsky, Paul H. Patterson, Susan B. Weinberger, Alison York, Sarah Rodriguez, David N. Lieberman and Amanda L. Gross and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Neuroscience.

In The Last Decade

Brian E. Derrick

26 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian E. Derrick United States 18 904 614 238 200 190 26 1.1k
Wolfram Schmitt Germany 9 755 0.8× 485 0.8× 252 1.1× 266 1.3× 244 1.3× 18 1.2k
Varda Greenberger Israel 16 937 1.0× 397 0.6× 397 1.7× 221 1.1× 159 0.8× 21 1.4k
Kazuhito Nakao United States 15 780 0.9× 500 0.8× 358 1.5× 136 0.7× 93 0.5× 17 1.2k
Kinga Tóth Hungary 14 1.0k 1.1× 581 0.9× 284 1.2× 152 0.8× 203 1.1× 23 1.3k
Edit Papp Hungary 11 909 1.0× 637 1.0× 306 1.3× 79 0.4× 162 0.9× 13 1.2k
Anne Kemp Germany 12 834 0.9× 661 1.1× 249 1.0× 85 0.4× 181 1.0× 16 1.1k
Paolo Barbaresi Italy 21 937 1.0× 592 1.0× 300 1.3× 125 0.6× 193 1.0× 48 1.4k
Peter V. Massey United Kingdom 11 1.2k 1.4× 807 1.3× 567 2.4× 155 0.8× 210 1.1× 15 1.6k
Gary M. Peterson United States 19 905 1.0× 421 0.7× 359 1.5× 339 1.7× 125 0.7× 33 1.2k
Cédrick Florian France 17 802 0.9× 704 1.1× 439 1.8× 161 0.8× 341 1.8× 21 1.6k

Countries citing papers authored by Brian E. Derrick

Since Specialization
Citations

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

Fields of papers citing papers by Brian E. Derrick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Brian E. Derrick

This figure shows the co-authorship network connecting the top 25 collaborators of Brian E. Derrick. A scholar is included among the top collaborators of Brian E. Derrick 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 Brian E. Derrick. Brian E. Derrick 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.
Derrick, Brian E., et al.. (2016). Long-term Potentiation at Temporoammonic Path-CA1 Synapses in Freely Moving Rats. Frontiers in Neural Circuits. 10. 2–2. 13 indexed citations
2.
Martinez, Carlo O., et al.. (2011). Endogenous opioid peptides contribute to associative LTP in the hippocampal CA3 region. Neurobiology of Learning and Memory. 96(2). 207–217. 6 indexed citations
3.
Derrick, Brian E., et al.. (2008). Prenatal Morphine Exposure Attenuates the Maintenance of Late LTP in Lateral Perforant Path Projections to the Dentate Gyrus and the CA3 Region In Vivo. Journal of Neurophysiology. 99(3). 1235–1242. 25 indexed citations
4.
Gross, Amanda L., et al.. (2007). Modulation of CA3 Afferent Inputs by Novelty and Theta Rhythm. Journal of Neuroscience. 27(49). 13457–13467. 25 indexed citations
5.
Derrick, Brian E.. (2007). Plastic processes in the dentate gyrus: a computational perspective. Progress in brain research. 163. 417–451. 17 indexed citations
6.
Sanberg, Cyndy D., et al.. (2006). 5-HT1a receptor antagonists block perforant path-dentate LTP induced in novel, but not familiar, environments. Learning & Memory. 13(1). 52–62. 31 indexed citations
7.
Derrick, Brian E., et al.. (2004). Time-course study of SCG10 mRNA levels associated with LTP induction and maintenance in the rat Schaffer-CA1 pathway in vivo. Molecular Brain Research. 120(2). 182–187. 6 indexed citations
8.
Davis, Cyndy D., et al.. (2004). Novel Environments Enhance the Induction and Maintenance of Long-Term Potentiation in the Dentate Gyrus. Journal of Neuroscience. 24(29). 6497–6506. 94 indexed citations
9.
10.
Martinez, Carlo O., et al.. (2002). Associative long-term potentiation (LTP) among extrinsic afferents of the hippocampal CA3 region in vivo. Brain Research. 940(1-2). 86–94. 37 indexed citations
11.
Martinez, Carlo O., et al.. (2002). Long-Term Potentiation in Direct Perforant Path Projections to the Hippocampal CA3 Region In Vivo. Journal of Neurophysiology. 87(2). 669–678. 70 indexed citations
12.
Derrick, Brian E., et al.. (2001). NMDA receptor antagonists sustain LTP and spatial memory: active processes mediate LTP decay. Nature Neuroscience. 5(1). 48–52. 155 indexed citations
13.
Jankowsky, Joanna L., Brian E. Derrick, & Paul H. Patterson. (2000). Cytokine Responses to LTP Induction in the Rat Hippocampus: A Comparison of In Vitro and In Vivo Techniques. Learning & Memory. 7(6). 400–412. 78 indexed citations
14.
Derrick, Brian E., Alison York, & Joe L. Martinez. (2000). Increased granule cell neurogenesis in the adult dentate gyrus following mossy fiber stimulation sufficient to induce long-term potentiation. Brain Research. 857(1-2). 300–307. 64 indexed citations
15.
Escobar, Martha L., et al.. (1997). Opioid receptor modulation of mossy fiber synaptogenesis: independence from long-term potentiation. Brain Research. 751(2). 330–335. 33 indexed citations
16.
Derrick, Brian E. & Joe L. Martinez. (1996). Associative, bidirectional modifications at the hippocampal mossy fibre–CA3 synapse. Nature. 381(6581). 429–434. 31 indexed citations
17.
Derrick, Brian E., et al.. (1994). Opioid receptor-dependent long-term potentiation at the lateral perforant path-CA3 synapse in rat hippocampus. Brain Research Bulletin. 33(1). 17–24. 52 indexed citations
18.
Hernández, Rubén, et al.. (1994). (±)CPP, an NMDA receptor antagonist, blocks the induction of commissural-CA3 LTP in the anesthetized rat. Brain Research. 656(1). 215–219. 14 indexed citations
19.
Derrick, Brian E., et al.. (1992). Mu opioid receptors are associated with the induction of hippocampal mossy fiber long-term potentiation.. Journal of Pharmacology and Experimental Therapeutics. 263(2). 725–733. 66 indexed citations
20.
Derrick, Brian E., Susan B. Weinberger, & Joe L. Martinez. (1991). Opioid receptors are involved in an NMDA receptor-independent mechanism of LTP induction at hippocampal mossy fiber-CA3 synapses. Brain Research Bulletin. 27(2). 219–223. 65 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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