Dennis L. Barbour

1.8k total citations
50 papers, 1.2k citations indexed

About

Dennis L. Barbour is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Sensory Systems. According to data from OpenAlex, Dennis L. Barbour has authored 50 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Cognitive Neuroscience, 7 papers in Cellular and Molecular Neuroscience and 7 papers in Sensory Systems. Recurrent topics in Dennis L. Barbour's work include Neural dynamics and brain function (23 papers), Hearing Loss and Rehabilitation (10 papers) and Functional Brain Connectivity Studies (10 papers). Dennis L. Barbour is often cited by papers focused on Neural dynamics and brain function (23 papers), Hearing Loss and Rehabilitation (10 papers) and Functional Brain Connectivity Studies (10 papers). Dennis L. Barbour collaborates with scholars based in United States, Netherlands and South Africa. Dennis L. Barbour's co-authors include Paul V. Watkins, Xiaoqin Wang, Eric C. Leuthardt, Gerwin Schalk, Xiaomei Pei, Edward M. Callaway, Madelyn N. Stevens, Timothy E. Hullar, Jonathan D. Breshears and Charles M. Gaona and has published in prestigious journals such as Science, Nature Communications and Journal of Neuroscience.

In The Last Decade

Dennis L. Barbour

47 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dennis L. Barbour United States 19 934 215 211 127 101 50 1.2k
Jessica J. M. Monaghan United Kingdom 16 704 0.8× 97 0.5× 134 0.6× 295 2.3× 94 0.9× 36 1.0k
Thomas Lu United States 14 1.3k 1.4× 175 0.8× 307 1.5× 107 0.8× 138 1.4× 29 1.5k
Ben H. Bonham United States 15 776 0.8× 162 0.8× 573 2.7× 156 1.2× 207 2.0× 18 973
P.W.F. Poon Taiwan 20 576 0.6× 118 0.5× 296 1.4× 187 1.5× 55 0.5× 75 1.0k
Ruurd Schoonhoven Netherlands 16 947 1.0× 154 0.7× 430 2.0× 62 0.5× 132 1.3× 44 1.2k
Nicholas A. Lesica United Kingdom 20 1.6k 1.7× 864 4.0× 239 1.1× 76 0.6× 72 0.7× 42 1.8k
Richard A. Reale United States 24 2.1k 2.3× 314 1.5× 510 2.4× 115 0.9× 74 0.7× 42 2.4k
Özcan Özdamar United States 23 1.4k 1.5× 157 0.7× 714 3.4× 269 2.1× 186 1.8× 72 1.9k
Filiep Vanpoucke Belgium 16 666 0.7× 75 0.3× 394 1.9× 265 2.1× 257 2.5× 47 879
Adrian K. C. Lee United States 22 1.1k 1.1× 59 0.3× 171 0.8× 98 0.8× 89 0.9× 73 1.3k

Countries citing papers authored by Dennis L. Barbour

Since Specialization
Citations

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

Fields of papers citing papers by Dennis L. Barbour

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dennis L. Barbour. 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 Dennis L. Barbour. The network helps show where Dennis L. Barbour may publish in the future.

Co-authorship network of co-authors of Dennis L. Barbour

This figure shows the co-authorship network connecting the top 25 collaborators of Dennis L. Barbour. A scholar is included among the top collaborators of Dennis L. Barbour 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 Dennis L. Barbour. Dennis L. Barbour 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
1.
Twinomurinzi, Hossana, Hermanus C. Myburgh, & Dennis L. Barbour. (2024). Active transfer learning for audiogram estimation. Frontiers in Digital Health. 6. 1267799–1267799. 3 indexed citations
2.
Barbour, Dennis L., et al.. (2024). Multitask Machine Learning of Contrast Sensitivity Functions. Journal of Vision. 24(10). 1082–1082.
3.
Davey, Pinakin Gunvant, et al.. (2024). Contrast response function estimation with nonparametric Bayesian active learning. Journal of Vision. 24(1). 6–6. 2 indexed citations
4.
Seitzman, Benjamin A., Timothy J. Mitchell, Donna Dierker, et al.. (2023). Cognition and Brain System Segregation in Pediatric Brain Tumor Patients Treated with Proton Therapy. International Journal of Particle Therapy. 10(1). 32–42. 3 indexed citations
5.
Pahor, Anja, et al.. (2023). Unicorn, Hare, or Tortoise? Using Machine Learning to Predict Working Memory Training Performance. Journal of Cognition. 6(1). 53–53. 2 indexed citations
6.
Barbour, Dennis L.. (2019). Precision medicine and the cursed dimensions. npj Digital Medicine. 2(1). 4–4. 14 indexed citations
7.
Saha, Debajit, et al.. (2017). Engaging and disengaging recurrent inhibition coincides with sensing and unsensing of a sensory stimulus. Nature Communications. 8(1). 15413–15413. 23 indexed citations
8.
Garnett, Roman, et al.. (2017). Psychometric function estimation by probabilistic classification. The Journal of the Acoustical Society of America. 141(4). 2513–2525. 17 indexed citations
9.
Barbour, Dennis L., et al.. (2017). Bayesian active probabilistic classification for psychometric field estimation. Attention Perception & Psychophysics. 80(3). 798–812. 12 indexed citations
10.
Watkins, Paul V., et al.. (2017). Decoding sound level in the marmoset primary auditory cortex. Journal of Neurophysiology. 118(4). 2024–2033. 7 indexed citations
11.
Hawasli, Ammar H., et al.. (2016). Influence of White and Gray Matter Connections on Endogenous Human Cortical Oscillations. Frontiers in Human Neuroscience. 10. 330–330. 9 indexed citations
12.
Gardner, Jacob R., et al.. (2015). Psychophysical detection testing with Bayesian active learning. Uncertainty in Artificial Intelligence. 286–297. 8 indexed citations
13.
Gardner, Jacob R., et al.. (2015). Fast, Continuous Audiogram Estimation Using Machine Learning. Ear and Hearing. 36(6). e326–e335. 43 indexed citations
14.
Ledbetter, Noah M., et al.. (2014). Spike-timing computation properties of a feed-forward neural network model. Frontiers in Computational Neuroscience. 8. 5–5. 7 indexed citations
15.
16.
Leuthardt, Eric C., Xiaomei Pei, Jonathan D. Breshears, et al.. (2012). Temporal evolution of gamma activity in human cortex during an overt and covert word repetition task. Frontiers in Human Neuroscience. 6. 99–99. 64 indexed citations
17.
Gaona, Charles M., Mohit Sharma, Zachary V. Freudenburg, et al.. (2011). Nonuniform High-Gamma (60–500 Hz) Power Changes Dissociate Cognitive Task and Anatomy in Human Cortex. Journal of Neuroscience. 31(6). 2091–2100. 71 indexed citations
18.
Watkins, Paul V., et al.. (2009). A computational framework for topographies of cortical areas. Biological Cybernetics. 100(3). 231–248. 5 indexed citations
19.
Watkins, Paul V. & Dennis L. Barbour. (2008). Specialized neuronal adaptation for preserving input sensitivity. Nature Neuroscience. 11(11). 1259–1261. 93 indexed citations
20.
Barbour, Dennis L. & Edward M. Callaway. (2008). Excitatory Local Connections of Superficial Neurons in Rat Auditory Cortex. Journal of Neuroscience. 28(44). 11174–11185. 79 indexed citations

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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