Thomas Macrina

3.5k citations
26 papers · 1.3k · 4 hit papers · h-index 17

Impact in

Papers in

Thomas Macrina

26 papers receiving 1.2k citations

Thomas Macrina's Hit Papers

Functional connectomics spanning multiple areas of mouse visual cortex 2025 · 64 citations
640+1Years since publication50100150200

Peers

Thomas Macrina
Comparison fields: 5 of 73
  • Cellular and Molecular Neuroscience 675
  • Structural Biology 73
  • Biophysics 212
  • Developmental Neuroscience 65
  • Cognitive Neuroscience 316
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Citations per year

Countries citing papers authored by Thomas Macrina

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Macrina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Thomas Macrina, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Thomas Macrina Line = papers co-authored together Thomas Macrina links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Neuronal wiring diagram of an adult brain
Hit paper breakdown →
2024225
2
Whole-brain annotation and multi-connectome cell typing of Drosophila
Hit paper breakdown →
2024159
3 2021149
4 2022109
5 202297
6 202072
7
Functional connectomics spanning multiple areas of mouse visual cortex
Hit paper breakdown →
202564
8 202151
9 202251
10 202446
11 201937
12 201536
13 202425
14
Functional connectomics reveals general wiring rule in mouse visual cortex
Hit paper breakdown →
202524
15 202521
16 202521
17 202419
18 202515
19 202512
20 202510

About Thomas Macrina

Thomas Macrina is a scholar working on Cellular and Molecular Neuroscience, Biophysics, Cognitive Neuroscience, Structural Biology and Neurology, having authored 26 papers that have together received 1.3k indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (11 papers), Neuroscience and Neuropharmacology Research (9 papers), Neurobiology and Insect Physiology Research (8 papers), Neural dynamics and brain function (6 papers), Visual perception and processing mechanisms (3 papers), Advanced Electron Microscopy Techniques and Applications (3 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers) and Undergraduate Neuroscience Education and Research (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (675 citations), Structural Biology (73 citations), Biophysics (212 citations), Developmental Neuroscience (65 citations) and Cognitive Neuroscience (316 citations). Thomas Macrina has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include H. Sebastian Seung, Amanda C. Kentner, Mattia M. Migliore, Kisuk Lee, Jingpeng Wu, Ran Lu, Nicholas L. Turner, Nico Kemnitz, Zhen Jia and J. Alexander Bae. Their work appears in journals such as Nature, eLife, Nature Methods, Nature Communications and Proceedings of the National Academy of Sciences.

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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