Michael A. Long

7.8k total citations · 1 hit paper
68 papers, 4.9k citations indexed

About

Michael A. Long is a scholar working on Developmental Biology, Ecology, Evolution, Behavior and Systematics and Molecular Biology. According to data from OpenAlex, Michael A. Long has authored 68 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Developmental Biology, 20 papers in Ecology, Evolution, Behavior and Systematics and 19 papers in Molecular Biology. Recurrent topics in Michael A. Long's work include Animal Vocal Communication and Behavior (26 papers), Animal Behavior and Reproduction (19 papers) and Marine animal studies overview (14 papers). Michael A. Long is often cited by papers focused on Animal Vocal Communication and Behavior (26 papers), Animal Behavior and Reproduction (19 papers) and Marine animal studies overview (14 papers). Michael A. Long collaborates with scholars based in United States, Canada and Germany. Michael A. Long's co-authors include Barry W. Connors, Michale S. Fee, Xiankai Sun, Robin Scarcella, Stephen Krashen, Jie Zheng, Yanping Qin, Daniela Vallentin, Dezhe Z. Jin and Carole E. Landisman and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Michael A. Long

66 papers receiving 4.8k citations

Hit Papers

ELECTRICAL SYNAPSES IN THE MAMMALIAN BRAIN 2004 2026 2011 2018 2004 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael A. Long United States 34 1.6k 1.5k 1.2k 866 727 68 4.9k
Aaron S. Andalman United States 17 1.3k 0.8× 1.1k 0.7× 880 0.7× 714 0.8× 651 0.9× 19 4.6k
Bence P. Ölveczky United States 28 1.1k 0.7× 2.2k 1.4× 777 0.6× 659 0.8× 641 0.9× 44 4.1k
Carlos Lois United States 34 3.6k 2.3× 615 0.4× 5.1k 4.2× 211 0.2× 204 0.3× 57 10.9k
B.J. Frost United States 32 900 0.6× 1.7k 1.1× 575 0.5× 283 0.3× 402 0.6× 85 3.5k
Douglas L. Oliver United States 42 1.4k 0.9× 3.1k 2.0× 471 0.4× 452 0.5× 269 0.4× 155 5.6k
Linda Wilbrecht United States 33 3.4k 2.2× 2.4k 1.6× 1.1k 0.9× 159 0.2× 153 0.2× 64 6.3k
David F. Clayton United States 48 2.4k 1.5× 795 0.5× 2.6k 2.1× 2.7k 3.2× 3.1k 4.3× 110 11.9k
Tobias Moser Germany 65 3.9k 2.5× 3.4k 2.2× 5.1k 4.2× 288 0.3× 114 0.2× 204 12.1k
Samuel S.‐H. Wang United States 36 2.4k 1.5× 2.0k 1.3× 1.4k 1.1× 70 0.1× 201 0.3× 76 5.4k
Jian Zuo United States 39 1.2k 0.8× 1.2k 0.8× 1.8k 1.5× 98 0.1× 51 0.1× 106 5.5k

Countries citing papers authored by Michael A. Long

Since Specialization
Citations

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

Fields of papers citing papers by Michael A. Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael A. Long. 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 Michael A. Long. The network helps show where Michael A. Long may publish in the future.

Co-authorship network of co-authors of Michael A. Long

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Long. A scholar is included among the top collaborators of Michael A. Long 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 Michael A. Long. Michael A. Long 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.
Haney, James F., Xia Zhu, Michael A. Long, et al.. (2025). The influence of flow on the amount, retention and loss of plastic pollution in an urban river. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 383(2307). 20230023–20230023.
2.
Yang, Zetian & Michael A. Long. (2025). Convergent vocal representations in parrot and human forebrain motor networks. Nature. 640(8058). 427–434.
3.
Banerjee, Arkarup, et al.. (2024). Temporal scaling of motor cortical dynamics reveals hierarchical control of vocal production. Nature Neuroscience. 27(3). 527–535. 6 indexed citations
4.
Elmaleh, Margot, Jeong Woo Kim, Paul W. Frazel, et al.. (2024). Differential behavioral engagement of inhibitory interneuron subtypes in the zebra finch brain. Neuron. 113(3). 460–470.e7. 2 indexed citations
5.
Guenther, Frank H., et al.. (2022). A Theoretical Framework for Human and Nonhuman Vocal Interaction. Annual Review of Neuroscience. 45(1). 295–316. 13 indexed citations
6.
Kovach, Christopher K., et al.. (2022). A speech planning network for interactive language use. Nature. 602(7895). 117–122. 49 indexed citations
7.
Long, Michael A., et al.. (2022). Mapping the vocal circuitry of Alston's singing mouse with pseudorabies virus. The Journal of Comparative Neurology. 530(12). 2075–2099. 7 indexed citations
8.
Burgess, Jason, Sharon Chiang, A. H. Weiss, et al.. (2020). An optimized QF-binary expression system for use in zebrafish. Developmental Biology. 465(2). 144–156. 11 indexed citations
9.
Banerjee, Arkarup, et al.. (2019). Motor cortical control of vocal interaction in neotropical singing mice. Science. 363(6430). 983–988. 93 indexed citations
10.
Banerjee, Arkarup, Steven M. Phelps, & Michael A. Long. (2019). Singing mice. Current Biology. 29(6). R190–R191. 21 indexed citations
11.
Kornfeld, Joergen, Sam E. Benezra, Rajeevan T. Narayanan, et al.. (2017). EM connectomics reveals axonal target variation in a sequence-generating network. eLife. 6. 70 indexed citations
12.
Picardo, Michel A., Josh Merel, Kalman A. Katlowitz, et al.. (2016). Population-Level Representation of a Temporal Sequence Underlying Song Production in the Zebra Finch. Neuron. 90(4). 866–876. 78 indexed citations
13.
Long, Michael A., Kalman A. Katlowitz, Mario A. Svirsky, et al.. (2016). Functional Segregation of Cortical Regions Underlying Speech Timing and Articulation. Neuron. 89(6). 1187–1193. 100 indexed citations
14.
Vallentin, Daniela & Michael A. Long. (2015). Motor Origin of Precise Synaptic Inputs onto Forebrain Neurons Driving a Skilled Behavior. Journal of Neuroscience. 35(1). 299–307. 36 indexed citations
15.
English, Daniel F., Adrien Peyrache, Eran Stark, et al.. (2014). Excitation and Inhibition Compete to Control Spiking during Hippocampal Ripples: Intracellular Study in Behaving Mice. Journal of Neuroscience. 34(49). 16509–16517. 108 indexed citations
16.
Fee, Michale S. & Michael A. Long. (2011). New methods for localizing and manipulating neuronal dynamics in behaving animals. DSpace@MIT (Massachusetts Institute of Technology). 1 indexed citations
17.
Fee, Michale S. & Michael A. Long. (2011). New methods for localizing and manipulating neuronal dynamics in behaving animals. Current Opinion in Neurobiology. 21(5). 693–700. 10 indexed citations
18.
Long, Michael A., Dezhe Z. Jin, & Michale S. Fee. (2010). Support for a synaptic chain model of neuronal sequence generation. RePEc: Research Papers in Economics. 1 indexed citations
19.
Long, Michael A. & Fábio Rossi. (2009). Silencing Inhibits Cre-Mediated Recombination of the Z/AP and Z/EG Reporters in Adult Cells. PLoS ONE. 4(5). e5435–e5435. 53 indexed citations
20.
Larrivée, Bruno, Kyle Niessen, Ingrid L. Pollet, et al.. (2005). Minimal Contribution of Marrow-Derived Endothelial Precursors to Tumor Vasculature. The Journal of Immunology. 175(5). 2890–2899. 57 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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