Megumi Aita

1.6k citations
22 papers · 1.2k indexed · 1 hit paper · h-index 13

Megumi Aita

22 papers receiving 1.2k citations

Hit Papers

Visualizing Hypothalamic Network Dynamics for Appetitive ...20152026201820222015100200300

Peers

Megumi Aita
Comparison fields: 5 of 86
  • Cellular and Molecular Neuroscience 725
  • Molecular Biology 503
  • Cognitive Neuroscience 302
  • Physiology 274
  • Endocrine and Autonomic Systems 270
Replace Davor Stanić with:
Davor Stanić Australia
Ju-en Zhang China
Russell Ray United States
Marie‐Jeanne Brisorgueil France
Jackson J. Cone United States
Frank J. Meye Netherlands
Valeriy Sergeyev Russia
Melloni N. Cook United States
Kerstin H. Lundgren United States
Yousheng Jia United States
Megumi Aita relative to Davor Stanić Australia Davor Stanić's profile →
Citations per field
00.5×1.5×
Davor Stanić · 1×
Citations per year

Countries citing papers authored by Megumi Aita

Since Specialization
Citations

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

Fields of papers citing papers by Megumi Aita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megumi Aita

This figure shows the co-authorship network connecting the top 25 collaborators of Megumi Aita. A scholar is included among the top collaborators of Megumi Aita 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 Megumi Aita. Megumi Aita 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
#WorkIndexed citations
1 20
2 13
3 52
4 15
5
Visualizing Hypothalamic Network Dynamics for Appetitive and Consummatory Behaviorsbreakdown →
399
6 42
7 237
8 6
9 108
10 7
11 232
12 22
13 6
14 5
15 7
16 7
17 12
18 19
19 8
20 18

About Megumi Aita

Megumi Aita is a scholar working on Cellular and Molecular Neuroscience, Sensory Systems and Physiology, having authored 22 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (10 papers), Pain Mechanisms and Treatments (6 papers) and Nerve injury and regeneration (6 papers). The work is most often cited by research in Endocrine and Autonomic Systems (270 citations), Cellular and Molecular Neuroscience (725 citations) and Behavioral Neuroscience (97 citations). Megumi Aita has collaborated with scholars based in Japan, United States and Bulgaria. Frequent co-authors include Charles Chavkin, Mei Xu, Michael R. Bruchas, Benjamin B. Land, Garret D. Stuber, Alice M. Stamatakis, Pranish A. Kantak, Sabiha K. Barot, Shuang Li and Randall L. Ung. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Nature Communications.

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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