Megha Sehgal

842 total citations
10 papers, 497 citations indexed

About

Megha Sehgal is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Neurology. According to data from OpenAlex, Megha Sehgal has authored 10 papers receiving a total of 497 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cellular and Molecular Neuroscience, 5 papers in Cognitive Neuroscience and 3 papers in Neurology. Recurrent topics in Megha Sehgal's work include Neuroscience and Neuropharmacology Research (5 papers), Memory and Neural Mechanisms (5 papers) and Neuroinflammation and Neurodegeneration Mechanisms (3 papers). Megha Sehgal is often cited by papers focused on Neuroscience and Neuropharmacology Research (5 papers), Memory and Neural Mechanisms (5 papers) and Neuroinflammation and Neurodegeneration Mechanisms (3 papers). Megha Sehgal collaborates with scholars based in United States, Brazil and Bulgaria. Megha Sehgal's co-authors include John Lisman, Alcino J. Silva, Katherine M. Cooper, James R. Moyer, Chenghui Song, Alcino J. Silva, Peyman Golshani, Michele A. Basso, Changliang Guo and Daniel Aharoni and has published in prestigious journals such as Nature, Nature Communications and Nature Neuroscience.

In The Last Decade

Megha Sehgal

10 papers receiving 488 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Megha Sehgal United States 6 311 233 102 86 44 10 497
Rosanna P. Sammons Germany 10 286 0.9× 192 0.8× 126 1.2× 58 0.7× 14 0.3× 14 521
Marco J. Russo United States 10 368 1.2× 210 0.9× 100 1.0× 105 1.2× 12 0.3× 11 647
Nahoko Kuga Japan 8 255 0.8× 157 0.7× 77 0.8× 103 1.2× 15 0.3× 18 389
Staci A. Sorensen United States 9 309 1.0× 246 1.1× 221 2.2× 55 0.6× 27 0.6× 12 612
Thomas Hainmueller Germany 5 359 1.2× 368 1.6× 84 0.8× 117 1.4× 17 0.4× 7 593
Mina Matsuo Japan 8 415 1.3× 423 1.8× 81 0.8× 77 0.9× 14 0.3× 9 559
Su-Eon Sim South Korea 6 322 1.0× 240 1.0× 211 2.1× 68 0.8× 23 0.5× 9 571
Segundo J. Guzman Austria 10 540 1.7× 461 2.0× 136 1.3× 112 1.3× 83 1.9× 13 792
Audrey Mercer United Kingdom 15 535 1.7× 411 1.8× 194 1.9× 90 1.0× 22 0.5× 22 689
Takaaki Ozawa Japan 10 222 0.7× 251 1.1× 81 0.8× 58 0.7× 11 0.3× 22 441

Countries citing papers authored by Megha Sehgal

Since Specialization
Citations

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

Fields of papers citing papers by Megha Sehgal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Megha Sehgal. 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 Megha Sehgal. The network helps show where Megha Sehgal may publish in the future.

Co-authorship network of co-authors of Megha Sehgal

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

All Works

10 of 10 papers shown
1.
Sehgal, Megha, Daniel Almeida Filho, George Kastellakis, et al.. (2025). Compartmentalized dendritic plasticity in the mouse retrosplenial cortex links contextual memories formed close in time. Nature Neuroscience. 28(3). 602–615. 2 indexed citations
2.
Sehgal, Megha, Fernando MCV Reis, Ana C. Sias, et al.. (2025). A dual-pathway architecture for stress to disrupt agency and promote habit. Nature. 640(8059). 722–731. 3 indexed citations
3.
Yang, Long, Megha Sehgal, Alcino J. Silva, et al.. (2025). Open-source, high performance miniature 2-photon microscopy systems for freely behaving animals. Nature Communications. 16(1). 7125–7125. 3 indexed citations
4.
Reis, Fernando MCV, Sandra Maesta‐Pereira, Peter J. Schuette, et al.. (2024). Control of feeding by a bottom-up midbrain-subthalamic pathway. Nature Communications. 15(1). 2111–2111. 3 indexed citations
5.
Guo, Changliang, Megha Sehgal, Alcino J. Silva, et al.. (2023). Miniscope-LFOV: A large-field-of-view, single-cell-resolution, miniature microscope for wired and wire-free imaging of neural dynamics in freely behaving animals. Science Advances. 9(16). eadg3918–eadg3918. 56 indexed citations
6.
Wang, Weisheng, Peter J. Schuette, Mimi Q La-Vu, et al.. (2021). Dorsal premammillary projection to periaqueductal gray controls escape vigor from innate and conditioned threats. eLife. 10. 27 indexed citations
7.
Sehgal, Megha, et al.. (2019). Modulation of intrinsic excitability as a function of learning within the fear conditioning circuit. Neurobiology of Learning and Memory. 167. 107132–107132. 12 indexed citations
8.
Lisman, John, Katherine M. Cooper, Megha Sehgal, & Alcino J. Silva. (2018). Memory formation depends on both synapse-specific modifications of synaptic strength and cell-specific increases in excitability. Nature Neuroscience. 21(3). 309–314. 231 indexed citations
9.
Sehgal, Megha, et al.. (2013). Learning to learn – Intrinsic plasticity as a metaplasticity mechanism for memory formation. Neurobiology of Learning and Memory. 105. 186–199. 113 indexed citations
10.
Song, Chenghui, et al.. (2012). Trace fear conditioning enhances synaptic and intrinsic plasticity in rat hippocampus. Journal of Neurophysiology. 107(12). 3397–3408. 47 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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2026