Michael A. Burman

456 total citations
19 papers, 344 citations indexed

About

Michael A. Burman is a scholar working on Behavioral Neuroscience, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Michael A. Burman has authored 19 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Behavioral Neuroscience, 11 papers in Cognitive Neuroscience and 8 papers in Cellular and Molecular Neuroscience. Recurrent topics in Michael A. Burman's work include Stress Responses and Cortisol (13 papers), Memory and Neural Mechanisms (9 papers) and Neuroscience and Neuropharmacology Research (8 papers). Michael A. Burman is often cited by papers focused on Stress Responses and Cortisol (13 papers), Memory and Neural Mechanisms (9 papers) and Neuroscience and Neuropharmacology Research (8 papers). Michael A. Burman collaborates with scholars based in United States and United Kingdom. Michael A. Burman's co-authors include Jonathan C. Gewirtz, Julie J. Neiworth, Benjamin M. Basile, Mark E. Stanton, Felipe L. Schiffino, Nathen J. Murawski, Jeffrey B. Rosen, Edward J. Bilsky, Lei Lei and Stephanie Shiers and has published in prestigious journals such as PLoS ONE, Brain Research and European Journal of Neuroscience.

In The Last Decade

Michael A. Burman

19 papers receiving 337 citations

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. Burman United States 12 174 144 121 115 71 19 344
Sachine Yoshida Japan 13 95 0.5× 147 1.0× 124 1.0× 338 2.9× 53 0.7× 21 635
Margaret L. Forgie Canada 14 143 0.8× 184 1.3× 205 1.7× 297 2.6× 31 0.4× 17 542
Emma C. Sarro United States 12 249 1.4× 88 0.6× 162 1.3× 193 1.7× 64 0.9× 16 569
Adi Cymerblit‐Sabba Israel 11 192 1.1× 162 1.1× 124 1.0× 204 1.8× 26 0.4× 13 482
Xianglan Wen Canada 7 70 0.4× 88 0.6× 121 1.0× 151 1.3× 100 1.4× 19 484
Karly M. Turner Australia 13 122 0.7× 97 0.7× 107 0.9× 57 0.5× 37 0.5× 22 438
Benedetta Ricci Italy 4 123 0.7× 161 1.1× 104 0.9× 91 0.8× 35 0.5× 9 446
Stephanie L. Grella United States 12 225 1.3× 250 1.7× 119 1.0× 133 1.2× 25 0.4× 21 469
Catherine E. Sykes United States 8 87 0.5× 167 1.2× 73 0.6× 126 1.1× 16 0.2× 9 420
Loïc J. Chareyron Switzerland 8 171 1.0× 99 0.7× 54 0.4× 79 0.7× 17 0.2× 13 295

Countries citing papers authored by Michael A. Burman

Since Specialization
Citations

This map shows the geographic impact of Michael A. Burman'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. Burman 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. Burman more than expected).

Fields of papers citing papers by Michael A. Burman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

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

All Works

19 of 19 papers shown
1.
Burman, Michael A., et al.. (2021). Amygdalar Corticotropin-Releasing Factor Signaling Is Required for Later-Life Behavioral Dysfunction Following Neonatal Pain. Frontiers in Physiology. 12. 660792–660792. 3 indexed citations
2.
Burman, Michael A., et al.. (2020). Maternal separation with neonatal pain influences later-life fear conditioning and somatosenation in male and female rats. Stress. 24(5). 504–513. 8 indexed citations
3.
Russo, Erica, et al.. (2019). The Effects of Acute Neonatal Pain on Expression of Corticotropin-Releasing Hormone and Juvenile Anxiety in a Rodent Model. eNeuro. 6(6). ENEURO.0162–19.2019. 15 indexed citations
4.
Burman, Michael A., et al.. (2019). Inflammatory neonatal pain disrupts maternal behavior and subsequent fear conditioning in a rodent model. Developmental Psychobiology. 62(1). 88–98. 8 indexed citations
5.
King, Tamara, et al.. (2018). Neonatal pain and stress disrupts later‐life pavlovian fear conditioning and sensory function in rats: Evidence for a two‐hit model. Developmental Psychobiology. 60(5). 520–533. 19 indexed citations
6.
Shiers, Stephanie, et al.. (2016). Limbic system development underlies the emergence of classical fear conditioning during the third and fourth weeks of life in the rat.. Behavioral Neuroscience. 130(2). 212–230. 15 indexed citations
7.
Burman, Michael A., et al.. (2016). FAAH inhibitor OL-135 disrupts contextual, but not auditory, fear conditioning in rats. Behavioural Brain Research. 308. 1–5. 13 indexed citations
8.
Burman, Michael A., et al.. (2014). Contextual and Auditory Fear Conditioning Continue to Emerge during the Periweaning Period in Rats. PLoS ONE. 9(6). e100807–e100807. 8 indexed citations
9.
Bilsky, Edward J., et al.. (2014). K-12 Neuroscience Education Outreach Program: Interactive Activities for Educating Students about Neuroscience.. PubMed. 13(1). A8–A20. 12 indexed citations
10.
Burman, Michael A., et al.. (2013). Developing and validating trace fear conditioning protocols in C57BL/6 mice. Journal of Neuroscience Methods. 222. 111–117. 20 indexed citations
11.
Burman, Michael A., et al.. (2010). Role of corticosterone in trace and delay conditioned fear-potentiated startle in rats.. Behavioral Neuroscience. 124(2). 294–299. 3 indexed citations
12.
Burman, Michael A., et al.. (2010). Evidence for hippocampus-dependent contextual learning at postnatal day 17 in the rat. Learning & Memory. 17(5). 259–266. 26 indexed citations
13.
Burman, Michael A., Nathen J. Murawski, Felipe L. Schiffino, Jeffrey B. Rosen, & Mark E. Stanton. (2009). Factors governing single-trial contextual fear conditioning in the weanling rat.. Behavioral Neuroscience. 123(5). 1148–1152. 31 indexed citations
14.
15.
Burman, Michael A. & Jonathan C. Gewirtz. (2007). Hippocampal activity, but not plasticity, is required for early consolidation of fear conditioning with a short trace interval. European Journal of Neuroscience. 25(8). 2483–2490. 19 indexed citations
16.
Burman, Michael A., et al.. (2005). Dissociable effects of hippocampus lesions on expression of fear and trace fear conditioning memories in rats. Hippocampus. 16(2). 103–113. 57 indexed citations
17.
Burman, Michael A. & Jonathan C. Gewirtz. (2004). Timing of Fear Expression in Trace and Delay Conditioning Measured by Fear-Potentiated Startle in Rats. Learning & Memory. 11(2). 205–212. 35 indexed citations
18.
Neiworth, Julie J., et al.. (2002). Use of experimenter-given cues in visual co-orienting and in an object-choice task by a New World monkey species, Cotton Top Tamarins ( Saguinus oedipus ).. Journal of comparative psychology. 116(1). 3–11. 43 indexed citations
19.
Neiworth, Julie J., et al.. (2002). Use of experimenter-given cues in visual co-orienting and in an object-choice task by a New World monkey species, Cotton Top Tamarins ( Saguinus oedipus ).. Journal of comparative psychology. 116(1). 3–11. 1 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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