Eric M. Trautmann

2.9k citations
19 papers · 879 indexed · 2 hit papers · h-index 11

Eric M. Trautmann

18 papers receiving 873 citations

Hit Papers

Large-scale neural recordings with single n...1372018202620202023100200300

Peers

Eric M. Trautmann
Comparison fields: 5 of 87
  • Cognitive Neuroscience 712
  • Cellular and Molecular Neuroscience 359
  • Biophysics 31
  • Computational Mathematics 2
  • Artificial Intelligence 101
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Citations per year

Countries citing papers authored by Eric M. Trautmann

Since Specialization
Citations

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

Fields of papers citing papers by Eric M. Trautmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric M. Trautmann. 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 Eric M. Trautmann. The network helps show where Eric M. Trautmann may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Eric M. Trautmann, 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 Eric M. Trautmann Line = papers co-authored together Eric M. Trautmann links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 20243
2 202410
3 20235
4 202326
5 20234
6
Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortexbreakdown →
2022137
7 202244
8 202245
9 2019142
10 201947
11 201926
12
Inferring single-trial neural population dynamics using sequential auto-encodersbreakdown →
2018306
13 201632
14 20153
15 201228
16 20119
17 20090
18 200910
19
InSAR monitoring of volcanoes at the highest resolution: Creation and analysis of 30 meter/pixel topographic maps with interferograms from Andean volcanoes
20062

About Eric M. Trautmann

Eric M. Trautmann is a scholar working on Cognitive Neuroscience, General Decision Sciences, Cellular and Molecular Neuroscience, Sensory Systems and Biophysics, having authored 19 papers that have together received 879 indexed citations. Recurring topics across this work include Neural dynamics and brain function (9 papers), EEG and Brain-Computer Interfaces (7 papers), Neuroscience and Neural Engineering (6 papers), Muscle activation and electromyography studies (3 papers), Neural and Behavioral Psychology Studies (3 papers), Photoreceptor and optogenetics research (2 papers), Visual perception and processing mechanisms (2 papers) and Cryospheric studies and observations (2 papers). The work is most often cited by research in Cognitive Neuroscience (712 citations), Cellular and Molecular Neuroscience (359 citations), Biophysics (31 citations), Computational Mathematics (2 citations) and Artificial Intelligence (101 citations). Eric M. Trautmann has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include Krishna V. Shenoy, Sergey D. Stavisky, Stephen I. Ryu, Daniel J. O’Shea, Matthew T. Kaufman, Leigh R. Hochberg, Jonathan C. Kao, Rafał Józefowicz, L. F. Abbott and Chethan Pandarinath. Their work appears in journals such as Neuron, Nature Neuroscience, eLife, Experimental Neurology and Nature Methods.

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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