Nicol S. Harper

2.1k total citations
30 papers, 1.3k citations indexed

About

Nicol S. Harper is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Sensory Systems. According to data from OpenAlex, Nicol S. Harper has authored 30 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cognitive Neuroscience, 7 papers in Experimental and Cognitive Psychology and 4 papers in Sensory Systems. Recurrent topics in Nicol S. Harper's work include Neural dynamics and brain function (22 papers), Neuroscience and Music Perception (18 papers) and Hearing Loss and Rehabilitation (9 papers). Nicol S. Harper is often cited by papers focused on Neural dynamics and brain function (22 papers), Neuroscience and Music Perception (18 papers) and Hearing Loss and Rehabilitation (9 papers). Nicol S. Harper collaborates with scholars based in United Kingdom, Hong Kong and Germany. Nicol S. Harper's co-authors include David McAlpine, Isabel Dean, Jan W. H. Schnupp, Benjamin L. Robinson, Ben D. B. Willmore, Andrew J. King, Oliver Schoppe, Vani G. Rajendran, Santani Teng and Benjamin M. Gaub and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Nicol S. Harper

29 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicol S. Harper United Kingdom 16 1.1k 321 203 140 125 30 1.3k
Thomas Lu United States 14 1.3k 1.2× 307 1.0× 221 1.1× 175 1.3× 107 0.9× 29 1.5k
Shigeto Furukawa Japan 18 825 0.7× 251 0.8× 273 1.3× 104 0.7× 68 0.5× 74 1.1k
Daniel Bendor United Kingdom 15 1.5k 1.3× 180 0.6× 350 1.7× 254 1.8× 91 0.7× 34 1.6k
Monty A. Escabı́ United States 23 1.6k 1.4× 287 0.9× 183 0.9× 501 3.6× 220 1.8× 46 1.8k
Peter Cariani United States 19 1.5k 1.3× 306 1.0× 411 2.0× 119 0.8× 266 2.1× 53 1.8k
Craig A. Atencio United States 17 835 0.7× 200 0.6× 76 0.4× 238 1.7× 74 0.6× 28 941
Christian J. Sumner United Kingdom 17 769 0.7× 432 1.3× 95 0.5× 74 0.5× 68 0.5× 48 920
Mitchell L. Sutter United States 26 1.8k 1.6× 379 1.2× 331 1.6× 267 1.9× 98 0.8× 43 2.1k
Ben D. B. Willmore United Kingdom 21 1.2k 1.1× 215 0.7× 94 0.5× 390 2.8× 150 1.2× 34 1.5k
Yonatan I. Fishman United States 19 1.3k 1.2× 106 0.3× 335 1.7× 73 0.5× 111 0.9× 33 1.5k

Countries citing papers authored by Nicol S. Harper

Since Specialization
Citations

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

Fields of papers citing papers by Nicol S. Harper

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicol S. Harper. 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 Nicol S. Harper. The network helps show where Nicol S. Harper may publish in the future.

Co-authorship network of co-authors of Nicol S. Harper

This figure shows the co-authorship network connecting the top 25 collaborators of Nicol S. Harper. A scholar is included among the top collaborators of Nicol S. Harper 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 Nicol S. Harper. Nicol S. Harper 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.
Iacaruso, M. Florencia, et al.. (2025). Prediction of future input explains lateral connectivity in primary visual cortex. Current Biology. 35(3). 530–541.e5.
2.
Millidge, Beren, et al.. (2024). Predictive coding networks for temporal prediction. PLoS Computational Biology. 20(4). e1011183–e1011183. 7 indexed citations
3.
Harper, Nicol S., et al.. (2024). Dissociable Roles of the Auditory Midbrain and Cortex in Processing the Statistical Features of Natural Sound Textures. Journal of Neuroscience. 44(10). e1115232023–e1115232023. 3 indexed citations
4.
Willmore, Ben D. B., et al.. (2023). Hierarchical temporal prediction captures motion processing along the visual pathway. eLife. 12. 6 indexed citations
5.
Auksztulewicz, Ryszard, et al.. (2023). Omission responses in local field potentials in rat auditory cortex. BMC Biology. 21(1). 130–130. 13 indexed citations
6.
Li, Kongyan, et al.. (2021). Sensitivity of neural responses in the inferior colliculus to statistical features of sound textures. Hearing Research. 412. 108357–108357. 2 indexed citations
7.
Willmore, Ben D. B., et al.. (2020). Simple transformations capture auditory input to cortex. Proceedings of the National Academy of Sciences. 117(45). 28442–28451. 24 indexed citations
8.
Harper, Nicol S., et al.. (2019). STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds. PLoS Computational Biology. 15(1). e1006595–e1006595. 6 indexed citations
9.
Willmore, Ben D. B., et al.. (2019). A dynamic network model of temporal receptive fields in primary auditory cortex. PLoS Computational Biology. 15(5). e1006618–e1006618. 12 indexed citations
10.
Rajendran, Vani G., et al.. (2016). Rhythm Facilitates the Detection of Repeating Sound Patterns. Frontiers in Neuroscience. 10. 9–9. 14 indexed citations
11.
Schoppe, Oliver, Nicol S. Harper, Ben D. B. Willmore, Andrew J. King, & Jan W. H. Schnupp. (2016). Measuring the Performance of Neural Models. Frontiers in Computational Neuroscience. 10. 10–10. 55 indexed citations
12.
Robinson, Benjamin L., Nicol S. Harper, & David McAlpine. (2016). Meta-adaptation in the auditory midbrain under cortical influence. Nature Communications. 7(1). 13442–13442. 50 indexed citations
13.
Willmore, Ben D. B., Oliver Schoppe, Andrew J. King, Jan W. H. Schnupp, & Nicol S. Harper. (2016). Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing. Journal of Neuroscience. 36(2). 280–289. 30 indexed citations
14.
Sohl‐Dickstein, Jascha, Santani Teng, Benjamin M. Gaub, et al.. (2015). A Device for Human Ultrasonic Echolocation. IEEE Transactions on Biomedical Engineering. 62(6). 1526–1534. 40 indexed citations
15.
Harper, Nicol S., Brian H. Scott, Malcolm N. Semple, & David McAlpine. (2014). The Neural Code for Auditory Space Depends on Sound Frequency and Head Size in an Optimal Manner. PLoS ONE. 9(11). e108154–e108154. 23 indexed citations
16.
Simpson, Andrew, Nicol S. Harper, Joshua D. Reiss, & David McAlpine. (2014). Selective Adaptation to “Oddball” Sounds by the Human Auditory System. Journal of Neuroscience. 34(5). 1963–1969. 11 indexed citations
17.
Harper, Nicol S., et al.. (2012). Adaptive coding is constrained to midline locations in a spatial listening task. Journal of Neurophysiology. 108(7). 1856–1868. 16 indexed citations
18.
Robinson, Benjamin L., et al.. (2008). Rapid Neural Adaptation to Sound Level Statistics. Journal of Neuroscience. 28(25). 6430–6438. 152 indexed citations
19.
Harper, Nicol S. & David McAlpine. (2004). Optimal neural population coding of an auditory spatial cue. Nature. 430(7000). 682–686. 213 indexed citations
20.
Stone, James V. & Nicol S. Harper. (1999). Temporal constraints on visual learning: a computational model. Perception. 28(9). 1089–1104. 1 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Thomas Lu Breakdown of academic impact, for papers by Shigeto Furukawa Breakdown of academic impact, for papers by Daniel Bendor Breakdown of academic impact, for papers by Monty A. Escabı́ Breakdown of academic impact, for papers by Peter Cariani Breakdown of academic impact, for papers by Craig A. Atencio Breakdown of academic impact, for papers by Christian J. Sumner Breakdown of academic impact, for papers by Mitchell L. Sutter Breakdown of academic impact, for papers by Ben D. B. Willmore Breakdown of academic impact, for papers by Yonatan I. Fishman
Rankless by CCL
2026