Hamish Meffin

2.7k total citations
106 papers, 1.8k citations indexed

About

Hamish Meffin is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Hamish Meffin has authored 106 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Cellular and Molecular Neuroscience, 67 papers in Cognitive Neuroscience and 53 papers in Electrical and Electronic Engineering. Recurrent topics in Hamish Meffin's work include Neuroscience and Neural Engineering (79 papers), Advanced Memory and Neural Computing (47 papers) and Neural dynamics and brain function (42 papers). Hamish Meffin is often cited by papers focused on Neuroscience and Neural Engineering (79 papers), Advanced Memory and Neural Computing (47 papers) and Neural dynamics and brain function (42 papers). Hamish Meffin collaborates with scholars based in Australia, United States and Switzerland. Hamish Meffin's co-authors include Anthony N. Burkitt, David B. Grayden, David J. Garrett, Michael R. Ibbotson, Kumaravelu Ganesan, Steven Prawer, Tatiana Kameneva, Kate Fox, Wei Tong and Alastair Stacey and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and Biomaterials.

In The Last Decade

Hamish Meffin

101 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hamish Meffin Australia 25 1.2k 823 744 284 257 106 1.8k
Blaise Yvert France 28 917 0.8× 596 0.7× 1.1k 1.5× 316 1.1× 126 0.5× 67 1.9k
Timothy J. Gardner United States 28 646 0.5× 541 0.7× 566 0.8× 340 1.2× 357 1.4× 71 2.4k
Herc P. Neves Belgium 19 628 0.5× 686 0.8× 394 0.5× 532 1.9× 73 0.3× 57 1.6k
Patrick Degenaar United Kingdom 23 1.3k 1.1× 695 0.8× 572 0.8× 697 2.5× 108 0.4× 129 2.1k
Yoonkey Nam South Korea 33 1.6k 1.3× 671 0.8× 492 0.7× 1.3k 4.7× 397 1.5× 107 2.8k
Akio Kawana Japan 21 1.5k 1.2× 610 0.7× 1.1k 1.5× 311 1.1× 64 0.2× 48 2.1k
W. Nisch Germany 17 1.1k 0.9× 521 0.6× 375 0.5× 500 1.8× 71 0.3× 47 1.5k
Yael Hanein Israel 34 1.5k 1.2× 1.1k 1.3× 567 0.8× 1.3k 4.7× 603 2.3× 123 3.5k
Keith Mathieson United Kingdom 30 2.2k 1.8× 1.3k 1.6× 977 1.3× 452 1.6× 95 0.4× 97 2.9k
Chethan Pandarinath United States 19 1.2k 1.0× 517 0.6× 1.6k 2.2× 312 1.1× 118 0.5× 38 2.1k

Countries citing papers authored by Hamish Meffin

Since Specialization
Citations

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

Fields of papers citing papers by Hamish Meffin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hamish Meffin. 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 Hamish Meffin. The network helps show where Hamish Meffin may publish in the future.

Co-authorship network of co-authors of Hamish Meffin

This figure shows the co-authorship network connecting the top 25 collaborators of Hamish Meffin. A scholar is included among the top collaborators of Hamish Meffin 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 Hamish Meffin. Hamish Meffin 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.
Ibbotson, Michael R., et al.. (2024). Data-driven modelling of visual receptive fields: comparison between the generalized quadratic model and the nonlinear input model. Journal of Neural Engineering. 21(4). 46014–46014. 1 indexed citations
2.
Grayden, David B., et al.. (2024). Neural activity shaping in visual prostheses with deep learning. Journal of Neural Engineering. 21(4). 46025–46025. 1 indexed citations
3.
Meffin, Hamish, et al.. (2023). Effect of sparsity on network stability in random neural networks obeying Dale's law. Physical Review Research. 5(4). 1 indexed citations
4.
Maturana, Matias I., Hamish Meffin, Tatiana Kameneva, et al.. (2022). Preferential modulation of individual retinal ganglion cells by electrical stimulation. Journal of Neural Engineering. 19(4). 45003–45003. 3 indexed citations
5.
Grayden, David B., et al.. (2021). Learning receptive field properties of complex cells in V1. PLoS Computational Biology. 17(3). e1007957–e1007957. 9 indexed citations
6.
Spencer, M., Tatiana Kameneva, David B. Grayden, Anthony N. Burkitt, & Hamish Meffin. (2021). Neural activity shaping utilizing a partitioned target pattern. Journal of Neural Engineering. 18(4). 46025–46025. 3 indexed citations
7.
Meffin, Hamish, et al.. (2020). Mechanisms of Feature Selectivity and Invariance in Primary Visual Cortex. Cerebral Cortex. 30(9). 5067–5087. 19 indexed citations
8.
Tong, Wei, Maryam Hejazi, David J. Garrett, et al.. (2020). Minimizing axon bundle activation of retinal ganglion cells with oriented rectangular electrodes. Journal of Neural Engineering. 17(3). 36016–36016. 5 indexed citations
9.
Tong, Wei, Nicholas V. Apollo, Kumaravelu Ganesan, et al.. (2019). Improved visual acuity using a retinal implant and an optimized stimulation strategy. Journal of Neural Engineering. 17(1). 16018–16018. 26 indexed citations
10.
Tahayori, Bahman, et al.. (2019). Determination of the electrical impedance of neural tissue from its microscopic cellular constituents. Journal of Neural Engineering. 17(1). 16037–16037. 2 indexed citations
11.
Kameneva, Tatiana, Hamish Meffin, Anthony N. Burkitt, & David B. Grayden. (2018). Bistability in Hodgkin-Huxley-type equations. PubMed. 11. 4728–4731. 2 indexed citations
12.
Rattay, Frank, et al.. (2018). Upper stimulation threshold for retinal ganglion cell activation. Journal of Neural Engineering. 15(4). 46012–46012. 17 indexed citations
13.
Meffin, Hamish, et al.. (2014). Modelling extracellular electrical stimulation: III. Derivation and interpretation of neural tissue equations. Journal of Neural Engineering. 11(6). 65004–65004. 26 indexed citations
14.
Grayden, David B., et al.. (2013). Modeling intrinsic electrophysiology of AII amacrine cells: Preliminary results. PubMed. 2013. 6551–4. 4 indexed citations
15.
Spencer, M., David B. Grayden, Ian C. Bruce, Hamish Meffin, & Anthony N. Burkitt. (2012). An investigation of dendritic delay in octopus cells of the mammalian cochlear nucleus. Frontiers in Computational Neuroscience. 6. 83–83. 17 indexed citations
16.
McDonnell, Mark D., et al.. (2012). Information theoretic inference of the optimal number of electrodes for future cochlear implants using a spiral cochlea model. PubMed. 2012. 2965–2968. 5 indexed citations
17.
Meffin, Hamish, Bahman Tahayori, David B. Grayden, & Anthony N. Burkitt. (2012). Modeling extracellular electrical stimulation: I. Derivation and interpretation of neurite equations. Journal of Neural Engineering. 9(6). 65005–65005. 41 indexed citations
18.
Tahayori, Bahman, et al.. (2011). Theoretical framework for estimating the conductivity map of the retina through finite element analysis. PubMed. 3. 6721–6724. 1 indexed citations
19.
Grayden, David B., et al.. (2011). Predicting phosphene elicitation in patients with retinal implants: A mathematical study. PubMed. 2011. 6246–6249. 4 indexed citations
20.
Meffin, Hamish & Benedikt Grothe. (2009). Selective filtering to spurious localization cues in the mammalian auditory brainstem. The Journal of the Acoustical Society of America. 126(5). 2437–2454. 14 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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