Colette M. McKay

5.4k total citations
150 papers, 4.1k citations indexed

About

Colette M. McKay is a scholar working on Cognitive Neuroscience, Speech and Hearing and Signal Processing. According to data from OpenAlex, Colette M. McKay has authored 150 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Cognitive Neuroscience, 52 papers in Speech and Hearing and 47 papers in Signal Processing. Recurrent topics in Colette M. McKay's work include Hearing Loss and Rehabilitation (106 papers), Noise Effects and Management (52 papers) and Speech and Audio Processing (43 papers). Colette M. McKay is often cited by papers focused on Hearing Loss and Rehabilitation (106 papers), Noise Effects and Management (52 papers) and Speech and Audio Processing (43 papers). Colette M. McKay collaborates with scholars based in Australia, United Kingdom and United States. Colette M. McKay's co-authors include Hugh J. McDermott, Graeme M. Clark, Katherine R. Henshall, Andrew E. Vandali, Robert P. Carlyon, Louise Hickson, Valerie Looi, Hamish Innes-Brown, Gary Rance and David Copolov and has published in prestigious journals such as PLoS ONE, American Journal of Psychiatry and Scientific Reports.

In The Last Decade

Colette M. McKay

144 papers receiving 4.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Colette M. McKay Australia 39 3.5k 1.6k 1.4k 1.2k 432 150 4.1k
Michael A. Akeroyd United Kingdom 33 3.8k 1.1× 1.3k 0.8× 1.6k 1.1× 735 0.6× 108 0.3× 131 4.4k
Kurt Hecox United States 28 1.8k 0.5× 918 0.6× 320 0.2× 273 0.2× 165 0.4× 89 2.9k
Sumitrajit Dhar United States 32 2.7k 0.7× 1.9k 1.2× 1.3k 0.9× 286 0.2× 109 0.3× 112 3.0k
A. Starr United States 37 3.7k 1.1× 1.4k 0.8× 252 0.2× 78 0.1× 240 0.6× 91 5.4k
Teemu Rinne Finland 34 6.1k 1.7× 432 0.3× 135 0.1× 544 0.4× 76 0.2× 59 6.5k
Mark E. Lutman United Kingdom 31 2.1k 0.6× 1.3k 0.8× 992 0.7× 314 0.3× 73 0.2× 106 2.7k
Anthony T. Herdman Canada 20 1.5k 0.4× 395 0.2× 153 0.1× 160 0.1× 47 0.1× 47 2.0k
Kenneth B. Campbell Canada 41 2.9k 0.8× 164 0.1× 102 0.1× 142 0.1× 343 0.8× 181 4.8k
Thomas M. Talavage United States 36 2.5k 0.7× 227 0.1× 77 0.1× 148 0.1× 123 0.3× 142 5.4k
Catherine Liégeois‐Chauvel France 29 3.8k 1.1× 231 0.1× 57 0.0× 263 0.2× 60 0.1× 75 4.2k

Countries citing papers authored by Colette M. McKay

Since Specialization
Citations

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

Fields of papers citing papers by Colette M. McKay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Colette M. McKay

This figure shows the co-authorship network connecting the top 25 collaborators of Colette M. McKay. A scholar is included among the top collaborators of Colette M. McKay 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 Colette M. McKay. Colette M. McKay 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.
Jelfs, Beth, et al.. (2025). Cross-modal functional plasticity after cochlear implantation. Cerebral Cortex. 35(4). 1 indexed citations
2.
Shader, Maureen J., et al.. (2025). Comparing Patient-Specific Variations in Intra-Cochlear Neural Health Estimated Using Psychophysical Thresholds and Panoramic Electrically Evoked Compound Action Potentials (PECAPs). Journal of the Association for Research in Otolaryngology. 26(1). 77–91. 2 indexed citations
3.
Wunderlich, Julia, et al.. (2024). Two Independent Response Mechanisms to Auditory Stimuli Measured with Functional Near-Infrared Spectroscopy in Sleeping Infants. Trends in Hearing. 28. 1881571400–1881571400. 4 indexed citations
4.
Jelfs, Beth, et al.. (2024). Resting-State Functional Connectivity Predicts Cochlear-Implant Speech Outcomes. Ear and Hearing. 46(1). 128–138. 1 indexed citations
5.
6.
McKay, Colette M., et al.. (2023). Investigating the Effect of Data Length on the Performance of Frequency-Domain fNIRS Functional Connectivity Measures. PubMed. 2023. 1–4. 1 indexed citations
7.
Zhou, Xin, et al.. (2022). Effects of degraded speech processing and binaural unmasking investigated using functional near-infrared spectroscopy (fNIRS). PLoS ONE. 17(4). e0267588–e0267588. 3 indexed citations
8.
Zhou, Xin, et al.. (2020). Comparing fNIRS signal qualities between approaches with and without short channels. PLoS ONE. 15(12). e0244186–e0244186. 47 indexed citations
9.
Innes-Brown, Hamish, et al.. (2019). Fully objective hearing threshold estimation in cochlear implant users using phase-locking value growth functions. Hearing Research. 377. 24–33. 8 indexed citations
10.
Zhou, Xin, et al.. (2018). Cortical Speech Processing in Postlingually Deaf Adult Cochlear Implant Users, as Revealed by Functional Near-Infrared Spectroscopy. Trends in Hearing. 22. 2759798562–2759798562. 41 indexed citations
11.
Innes-Brown, Hamish, et al.. (2015). Cortical auditory evoked potentials as an objective measure of behavioral thresholds in cochlear implant users. Hearing Research. 327. 35–42. 36 indexed citations
12.
McKay, Colette M., et al.. (2011). A Psychophysical Method for Measuring Spatial Resolution in Cochlear Implants. Journal of the Association for Research in Otolaryngology. 13(1). 145–157. 43 indexed citations
13.
Mok, Mansze, Karyn L. Galvin, Richard C. Dowell, & Colette M. McKay. (2009). Speech Perception Benefit for Children with a Cochlear Implant and a Hearing Aid in Opposite Ears and Children with Bilateral Cochlear Implants. Audiology and Neurotology. 15(1). 44–56. 88 indexed citations
14.
Looi, Valerie, Hugh J. McDermott, Colette M. McKay, & Louise Hickson. (2008). Music Perception of Cochlear Implant Users Compared with that of Hearing Aid Users. Ear and Hearing. 29(3). 421–434. 125 indexed citations
15.
McKay, Colette M.. (2005). Spectral Processing In Cochlear Implants. International review of neurobiology. 70. 473–509. 20 indexed citations
16.
McKay, Colette M., et al.. (2005). A Different Approach to Using Neural Response Telemetry for Automated Cochlear Implant Processor Programming. Ear and Hearing. 26(Supplement). 38S–44S. 37 indexed citations
17.
McDermott, Hugh J., et al.. (1997). Preliminary results on spectral shape perception and discrimination of musical sounds by normal hearing subjects and cochlear implantees. Minerva Access (University of Melbourne). 1997. 11–14. 6 indexed citations
18.
Clark, Graeme M., Lesley A. Whitford, Richard van Hoesel, et al.. (1995). Comparison of the speak (spectral maxima) and multipeak speech processing strategies and improved speech perception in background noise. Australian Journal of Otolaryngology. 2(1). 1 indexed citations
19.
McKay, Colette M., Andrew E. Vandali, Hugh J. McDermott, & Graeme M. Clark. (1993). Speech processing for cochlear implants: variations of the spectral maxima sound processor. PLoS ONE. 10(11). e0139970–e0139970. 1 indexed citations
20.
McKay, Colette M., Hugh J. McDermott, Andrew E. Vandali, & Graeme M. Clark. (1992). A Comparison of Speech Perception of Cochlear Implantees using the Spectral Maxima Sound Processor (SMSP) and the MSP(MULTIPEAK) Processor. Acta Oto-Laryngologica. 112(5). 752–761. 30 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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