Tatsuya Daikoku
- Cognitive Neuroscience top 5%
- Neuroscience and Music Perception 24
- Neural dynamics and brain function 9
- Hearing Loss and Rehabilitation 5
- Signal Processing top 5%
- Music and Audio Processing 11
- Developmental Biology top 10%
- Music top 5%
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- Multisensory perception and integration 5
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- Neural Networks and Applications 4
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- Cognitive and developmental aspects of mathematical skills 2
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- Child and Animal Learning Development 2
- Co-authors
- Masato YumotoYutaka YatomiYuji K. TakahashiSebastian JentschkeStefan KoelschMasaki TanakaGeraínt A. WigginsShigeto Yamawaki
- Journals
- SHILAP Revista de lepidopterología (1 paper)PLoS ONE (2 papers)Scientific Reports (3 papers)
- Partner nations
- JapanGermanyUnited Kingdom
In The Last Decade
Tatsuya Daikoku
23 papers receiving 286 citations
Peers
Comparison fields: 5 of 27
- Cognitive Neuroscience 257
- Signal Processing 128
- Developmental Biology 22
- Music 21
- Experimental and Cognitive Psychology 57
Countries citing papers authored by Tatsuya Daikoku
This map shows the geographic impact of Tatsuya Daikoku'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 Tatsuya Daikoku with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tatsuya Daikoku more than expected).
Fields of papers citing papers by Tatsuya Daikoku
This network shows the impact of papers produced by Tatsuya Daikoku. 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 Tatsuya Daikoku. The network helps show where Tatsuya Daikoku may publish in the future.
Co-authorship network
The 20 scholars most cited alongside Tatsuya Daikoku, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 9 | |
| 6 | 2021 | 8 | |
| 7 | 2021 | 6 | |
| 8 | 2020 | 13 | |
| 9 | 2019 | 5 | |
| 10 | 2019 | 4 | |
| 11 | 2019 | 25 | |
| 12 | 2019 | 5 | |
| 13 | 2019 | 5 | |
| 14 | 2019 | 13 | |
| 15 | 2018 | 15 | |
| 16 | 2018 | 14 | |
| 17 | 2018 | 10 | |
| 18 | 2018 | 7 | |
| 19 | 2018 | 40 | |
| 20 | 2017 | 15 |
About Tatsuya Daikoku
Tatsuya Daikoku is a scholar working on Cognitive Neuroscience, Signal Processing and Developmental Biology, having authored 27 papers that have together received 286 indexed citations. Recurring topics across this work include Neuroscience and Music Perception (24 papers), Music and Audio Processing (11 papers), Neural dynamics and brain function (9 papers), Hearing Loss and Rehabilitation (5 papers), Multisensory perception and integration (5 papers), Neural Networks and Applications (4 papers), Cognitive and developmental aspects of mathematical skills (2 papers) and Child and Animal Learning Development (2 papers). The work is most often cited by research in Cognitive Neuroscience (257 citations), Signal Processing (128 citations) and Developmental Biology (22 citations). Tatsuya Daikoku has collaborated with scholars based in Japan, Germany and United Kingdom. Frequent co-authors include Masato Yumoto, Yutaka Yatomi, Yuji K. Takahashi, Sebastian Jentschke, Stefan Koelsch, Masaki Tanaka, Geraínt A. Wiggins, Shigeto Yamawaki, Yukie Nagai and Kazuaki Kanai. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.