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Neuroscience and Neural Engineering

Neuroscience and Neural Engineering is a research topic within Cellular and Molecular Neuroscience. Science Explorer counts 62k research works in it since 1950. 17.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores advancements in neural interface technology, focusing on neural stimulation, electrode arrays, neuroprostheses, retinal prosthesis, nanomaterials, chronic recording, brain tissue response to implants, biocompatible implants, and electrical stimulation. The research covers a wide range of topics related to the development and application of neural interfaces for both experimental and clinical purposes.

  • Neural Stimulation
  • Electrode Arrays
  • Neuroprostheses
  • Retinal Prosthesis
  • Nanomaterials
  • Chronic Recording
  • Brain Tissue Response
  • Biocompatible Implants
  • Electrical Stimulation
  • Neuronal Networks
Research works
62k
fractional, since 1950
In the world top 10%
11k
per year above
Top-10% rate
17.7%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+18%
the tick is no change

Which countries lead Neuroscience and Neural Engineering research?

By volume, China and the United States publish the most (2.2k and 2.1k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 2.2k works
  2. 2 United States 2.1k works
  3. 3 India 596 works
  4. 4 South Korea 529 works
  5. 5 Germany 517 works
  6. 6 United Kingdom 391 works
  7. 7 Japan 384 works
  8. 8 Italy 337 works
  9. 9 France 240 works
  10. 10 Canada 236 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 29.2%United States: 28.2%India: 7.9%South Korea: 7.0%6 others listed: 27.8%29%largest
China2,212 · 29.2%United States2,139 · 28.2%India596 · 7.9%South Korea529 · 7.0%6 others listed2,105 · 27.8%

Shares of the rows listed above, not of the whole node.

Which institutions lead Neuroscience and Neural Engineering research?

By volume in 2022–2025, Chinese Academy of Sciences publishes the most Neuroscience and Neural Engineering research, followed by Shanghai Jiao Tong University and Zhejiang University.

Who are the leading researchers in Neuroscience and Neural Engineering?

The most-cited researchers publishing on Neuroscience and Neural Engineering include A. M. Litke, W. Dąbrowski and Wei Huang.

  1. 1 A. M. Litke United States 7.4k citations
  2. 2 W. Dąbrowski Poland 6.8k citations
  3. 3 Wei Huang China 5.5k citations
  4. 4 Luca Benini Italy 4.6k citations
  5. 5 Róbert Langer United States 4.2k citations
  6. 6 Leon O. Chua United States 4.1k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Neuroscience and Neural Engineering research done?

The largest centres of Neuroscience and Neural Engineering research in 2022–2025 are Beijing (China), Seoul (South Korea), Shanghai (China) and Hangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Genoa.

Largest cities, 2022–2025

  1. 1 Beijing China 460 works
  2. 2 Seoul South Korea 281 works
  3. 3 Shanghai China 258 works
  4. 4 Hangzhou China 138 works
  5. 5 Tokyo Japan 129 works
  6. 6 Xi'an China 118 works
  7. 7 Tianjin China 117 works
  8. 8 London United Kingdom 115 works
  9. 9 Nanjing China 104 works
  10. 10 Guangzhou China 99 works

Where it is the local speciality

  1. GenoaIT · 41.3 works7.4×
← less than its size predictsmore →

Location quotient: how much more of its research is in Neuroscience and Neural Engineering than the world average.

See Neuroscience and Neural Engineering on the map

Where is the best place to study Neuroscience and Neural Engineering?

Among universities, judged by research, Daegu Gyeongbuk Institute of Science and Technology, University of Chinese Academy of Sciences and École Polytechnique Fédérale de Lausanne score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 24.31%fractional works in this node (log) →share in the world top 10% →Daegu Gyeongbuk Institute of Science and Technology: 13, 14.7%University of Chinese Academy of Sciences: 39, 32.6%École Polytechnique Fédérale de Lausanne: 34, 16.6%Dongguk University: 22, 30.7%Kwangwoon University: 12, 12.3%Pohang University of Science and Technology: 17, 21.5%Khalifa University of Science and Technology: 9, 39.9%Westlake University: 15, 16.4%Nanyang Technological University: 22, 36.0%Korea University: 30, 22.4%University of Chines…Dongguk UniversityÉcole Polytechnique …Daegu Gyeongbuk Inst…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Daegu Gyeongbuk Institute of Science and TechnologySouth Korea 53.514.7%18.5×13 +355.0%
2 University of Chinese Academy of SciencesChina 51.932.6%2.4×39 +621.9%
3 École Polytechnique Fédérale de LausanneSwitzerland 51.616.6%8.5×34 -3.6%
4 Dongguk UniversitySouth Korea 51.130.7%12.9×22 -48.6%
5 Kwangwoon UniversitySouth Korea 50.812.3%17.1×12 +195.4%
6 Pohang University of Science and TechnologySouth Korea 50.721.5%8.3×17 +124.9%
7 Khalifa University of Science and TechnologyUnited Arab Emirates 49.539.9%4.0×9 +178.8%
8 Westlake UniversityChina 48.716.4%12.5×15
9 Nanyang Technological UniversitySingapore 48.436.0%2.8×22 +90.5%
10 Korea UniversitySouth Korea 48.222.4%6.0×30 +64.5%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Neuroscience and Neural Engineering research growing?

Output in 2018–2022 was 18% higher than in 2013–2017, peaking in 2022. The fastest-growing topics are Neuroscience and Neural Engineering.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.