Mark L. Andermann

10.9k total citations · 2 hit papers
61 papers, 6.3k citations indexed

About

Mark L. Andermann is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Endocrine and Autonomic Systems. According to data from OpenAlex, Mark L. Andermann has authored 61 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cognitive Neuroscience, 30 papers in Cellular and Molecular Neuroscience and 15 papers in Endocrine and Autonomic Systems. Recurrent topics in Mark L. Andermann's work include Neural dynamics and brain function (29 papers), Neuroscience and Neuropharmacology Research (17 papers) and Memory and Neural Mechanisms (10 papers). Mark L. Andermann is often cited by papers focused on Neural dynamics and brain function (29 papers), Neuroscience and Neuropharmacology Research (17 papers) and Memory and Neural Mechanisms (10 papers). Mark L. Andermann collaborates with scholars based in United States, United Kingdom and Hungary. Mark L. Andermann's co-authors include R. Clay Reid, Bradford B. Lowell, Aaron Kerlin, Christopher I. Moore, Lindsey L. Glickfeld, V. K. Berezovskii, David A. Boas, Anna Devor, Anders M. Dale and Andrew K. Dunn and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Mark L. Andermann

58 papers receiving 6.2k citations

Hit Papers

Network anatomy and in vivo physiology of visual cortical... 2011 2026 2016 2021 2011 2017 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
Mark L. Andermann United States 37 3.5k 2.7k 1.0k 981 806 61 6.3k
Hong‐Wei Dong United States 30 3.7k 1.1× 3.7k 1.4× 1.6k 1.6× 952 1.0× 563 0.7× 49 8.1k
Fuqiang Xu China 38 1.5k 0.4× 2.2k 0.8× 1.3k 1.3× 588 0.6× 590 0.7× 180 5.3k
Douglas L. Rosene United States 59 4.9k 1.4× 3.8k 1.4× 1.8k 1.7× 507 0.5× 1.6k 2.0× 191 10.9k
H.B.M. Uylings Netherlands 60 7.2k 2.1× 5.3k 1.9× 1.9k 1.9× 461 0.5× 984 1.2× 160 14.3k
Tsai‐Wen Chen United States 18 2.6k 0.7× 4.3k 1.6× 2.3k 2.2× 421 0.4× 323 0.4× 23 7.1k
Douglas S. Kim United States 28 2.5k 0.7× 5.5k 2.0× 3.7k 3.6× 655 0.7× 440 0.5× 40 9.1k
Peter Redgrave United Kingdom 52 6.2k 1.8× 5.1k 1.9× 1.3k 1.3× 422 0.4× 442 0.5× 168 10.3k
Sung‐Yon Kim South Korea 22 1.6k 0.5× 2.3k 0.8× 1.5k 1.5× 451 0.5× 302 0.4× 35 5.8k
Minmin Luo China 49 2.2k 0.6× 3.9k 1.4× 1.8k 1.8× 1.3k 1.3× 594 0.7× 103 7.3k
Daniel Huber Switzerland 29 4.6k 1.3× 4.7k 1.7× 1.2k 1.2× 587 0.6× 168 0.2× 51 7.7k

Countries citing papers authored by Mark L. Andermann

Since Specialization
Citations

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

Fields of papers citing papers by Mark L. Andermann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark L. Andermann. 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 Mark L. Andermann. The network helps show where Mark L. Andermann may publish in the future.

Co-authorship network of co-authors of Mark L. Andermann

This figure shows the co-authorship network connecting the top 25 collaborators of Mark L. Andermann. A scholar is included among the top collaborators of Mark L. Andermann 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 Mark L. Andermann. Mark L. Andermann 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.
Zhang, Stephen X., et al.. (2025). Obesity dysregulates feeding-evoked response dynamics in hypothalamic satiety neurons. Scientific Reports. 15(1). 35837–35837.
2.
Lensjø, Kristian Kinden, Kristin Tøndel, Anders Malthe‐Sørenssen, et al.. (2025). Local inhibitory circuits mediate cortical reactivations and memory consolidation. Science Advances. 11(22). eadu9800–eadu9800.
3.
Alvarado, Jonnathan Singh, et al.. (2024). Transient cAMP production drives rapid and sustained spiking in brainstem parabrachial neurons to suppress feeding. Neuron. 112(9). 1416–1425.e5. 7 indexed citations
4.
Kucukdereli, Hakan, et al.. (2024). Repeated stress triggers seeking of a starvation-like state in anxiety-prone female mice. Neuron. 112(13). 2130–2141.e7. 4 indexed citations
6.
Stover, Patrick J., Martha S. Field, Mark L. Andermann, et al.. (2023). Neurobiology of eating behavior, nutrition, and health. Journal of Internal Medicine. 294(5). 582–604. 28 indexed citations
7.
Jeong, Huijeong, Vijay Mohan K Namboodiri, Min Whan Jung, & Mark L. Andermann. (2023). Sensory cortical ensembles exhibit differential coupling to ripples in distinct hippocampal subregions. Current Biology. 33(23). 5185–5198.e4. 6 indexed citations
9.
Sugden, Arthur U., et al.. (2022). Trigeminal afferents sense locomotion-related meningeal deformations. Cell Reports. 41(7). 111648–111648. 7 indexed citations
10.
Lutas, Andrew, Liang Liang, Fei Deng, et al.. (2022). Brainstem serotonin neurons selectively gate retinal information flow to thalamus. Neuron. 111(5). 711–726.e11. 9 indexed citations
11.
Lutas, Andrew, et al.. (2022). History-dependent dopamine release increases cAMP levels in most basal amygdala glutamatergic neurons to control learning. Cell Reports. 38(4). 110297–110297. 20 indexed citations
12.
Zhang, Stephen X., Andrew Lutas, Shang Fa Yang, et al.. (2021). Hypothalamic dopamine neurons motivate mating through persistent cAMP signalling. Nature. 597(7875). 245–249. 59 indexed citations
13.
Kim, Angela, Joseph C. Madara, Chen Wu, Mark L. Andermann, & Bradford B. Lowell. (2021). Neural basis for regulation of vasopressin secretion by anticipated disturbances in osmolality. eLife. 10. 15 indexed citations
14.
Sugden, Arthur U., Jeffrey D. Zaremba, Lauren A. Sugden, et al.. (2020). Cortical reactivations of recent sensory experiences predict bidirectional network changes during learning. Nature Neuroscience. 23(8). 981–991. 24 indexed citations
15.
Lutas, Andrew, et al.. (2019). State-specific gating of salient cues by midbrain dopaminergic input to basal amygdala. Nature Neuroscience. 22(11). 1820–1833. 99 indexed citations
16.
Tyssowski, Kelsey M., Nicholas R. DeStefino, Jin-Hyung Cho, et al.. (2018). Different Neuronal Activity Patterns Induce Different Gene Expression Programs. Neuron. 98(3). 530–546.e11. 223 indexed citations
17.
Kuchibhotla, Kishore V., Susanne Wegmann, Katherine J. Kopeikina, et al.. (2013). Neurofibrillary tangle-bearing neurons are functionally integrated in cortical circuits in vivo. Proceedings of the National Academy of Sciences. 111(1). 510–514. 150 indexed citations
18.
Devor, Anna, István Ulbert, Andrew K. Dunn, et al.. (2005). Coupling of the cortical hemodynamic response to cortical and thalamic neuronal activity. Proceedings of the National Academy of Sciences. 102(10). 3822–3827. 175 indexed citations
19.
Andermann, Mark L., et al.. (2004). Neural Correlates of Vibrissa Resonance. Neuron. 42(3). 451–463. 110 indexed citations
20.
Andermann, Mark L., et al.. (2002). A model of texture encoding by vibrissa resonance properties. 4503. 2 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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