Matthew Fellows

4.5k total citations · 2 hit papers
15 papers, 3.1k citations indexed

About

Matthew Fellows is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Biomedical Engineering. According to data from OpenAlex, Matthew Fellows has authored 15 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cognitive Neuroscience, 9 papers in Cellular and Molecular Neuroscience and 3 papers in Biomedical Engineering. Recurrent topics in Matthew Fellows's work include EEG and Brain-Computer Interfaces (11 papers), Neural dynamics and brain function (9 papers) and Neuroscience and Neural Engineering (9 papers). Matthew Fellows is often cited by papers focused on EEG and Brain-Computer Interfaces (11 papers), Neural dynamics and brain function (9 papers) and Neuroscience and Neural Engineering (9 papers). Matthew Fellows collaborates with scholars based in United States, United Kingdom and Israel. Matthew Fellows's co-authors include John P. Donoghue, Nicholas G. Hatsopoulos, Liam Paninski, Mijail D. Serruya, Wilson Truccolo, Emery N. Brown, Uri T. Eden, Shy Shoham, Richard A. Normann and Carlos E. Vargas-Irwin and has published in prestigious journals such as Nature, Journal of Neuroscience and Journal of Neurophysiology.

In The Last Decade

Matthew Fellows

15 papers receiving 3.0k citations

Hit Papers

Instant neural control of a movement signal 2002 2026 2010 2018 2002 2004 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew Fellows United States 14 2.7k 2.0k 642 581 243 15 3.1k
Gopal Santhanam United States 22 2.6k 1.0× 1.6k 0.8× 570 0.9× 541 0.9× 216 0.9× 37 2.9k
Byron M. Yu United States 35 5.1k 1.9× 2.6k 1.3× 789 1.2× 757 1.3× 549 2.3× 83 5.5k
Paul Nuyujukian United States 30 3.7k 1.3× 2.7k 1.3× 944 1.5× 1.2k 2.1× 211 0.9× 58 4.4k
Steven M. Chase United States 26 2.5k 0.9× 1.5k 0.7× 447 0.7× 458 0.8× 164 0.7× 57 2.7k
Carsten Mehring Germany 29 3.9k 1.4× 2.1k 1.0× 933 1.5× 778 1.3× 238 1.0× 54 4.4k
Joseph T. Francis United States 21 1.4k 0.5× 623 0.3× 377 0.6× 198 0.3× 202 0.8× 79 2.0k
Sergey D. Stavisky United States 20 1.7k 0.6× 980 0.5× 289 0.5× 438 0.8× 154 0.6× 39 1.8k
Afsheen Afshar United States 15 1.8k 0.6× 1.1k 0.5× 443 0.7× 351 0.6× 107 0.4× 19 1.9k
Dong Song United States 25 1.7k 0.6× 1.6k 0.8× 303 0.5× 639 1.1× 181 0.7× 190 2.4k
Tara Julia Hamilton Australia 22 1.4k 0.5× 1.0k 0.5× 481 0.7× 1.9k 3.3× 576 2.4× 114 2.8k

Countries citing papers authored by Matthew Fellows

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Fellows

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Fellows

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Fellows. A scholar is included among the top collaborators of Matthew Fellows 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 Matthew Fellows. Matthew Fellows is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Fellows, Matthew, Anuj Mahajan, Tim G. J. Rudner, & Shimon Whiteson. (2019). VIREL: A Variational Inference Framework for Reinforcement Learning. Oxford University Research Archive (ORA) (University of Oxford). 32. 7120–7134. 4 indexed citations
2.
Makin, Joseph G., Matthew Fellows, & Philip N. Sabes. (2013). Learning Multisensory Integration and Coordinate Transformation via Density Estimation. PLoS Computational Biology. 9(4). e1003035–e1003035. 40 indexed citations
3.
Kim, Sung-Phil, Frank Wood, Matthew Fellows, John P. Donoghue, & Michael J. Black. (2006). Statistical Analysis of the Non-stationarity of Neural Population Codes. 811–816. 13 indexed citations
4.
Suner, Selim, et al.. (2005). Reliability of signals from a chronically implanted, silicon-based electrode array in non-human primate primary motor cortex. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 13(4). 524–541. 324 indexed citations
5.
Eden, Uri T., Wilson Truccolo, Matthew Fellows, John P. Donoghue, & Emery N. Brown. (2005). Reconstruction of hand movement trajectories from a dynamic ensemble of spiking motor cortical neurons. PubMed. 4. 4017–4020. 25 indexed citations
6.
Shoham, Shy, Liam Paninski, Matthew Fellows, et al.. (2005). Statistical Encoding Model for a Primary Motor Cortical Brain-Machine Interface. IEEE Transactions on Biomedical Engineering. 52(7). 1312–1322. 63 indexed citations
7.
Song, Yoon‐Kyu, William R. Patterson, Christopher W. Bull, et al.. (2005). Development of a chipscale integrated microelectrode/microelectronic device for brain implantable neuroengineering applications. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 13(2). 220–226. 50 indexed citations
8.
Wood, Elizabeth A., et al.. (2005). Automatic spike sorting for neural decoding. PubMed. 4. 4009–4012. 31 indexed citations
9.
Paninski, Liam, Matthew Fellows, Nicholas G. Hatsopoulos, & John P. Donoghue. (2004). Spatiotemporal Tuning of Motor Cortical Neurons for Hand Position and Velocity. Journal of Neurophysiology. 91(1). 515–532. 289 indexed citations
10.
Truccolo, Wilson, Uri T. Eden, Matthew Fellows, John P. Donoghue, & Emery N. Brown. (2004). A Point Process Framework for Relating Neural Spiking Activity to Spiking History, Neural Ensemble, and Extrinsic Covariate Effects. Journal of Neurophysiology. 93(2). 1074–1089. 692 indexed citations breakdown →
11.
Wood, Frank, Michael J. Black, Carlos E. Vargas-Irwin, Matthew Fellows, & John P. Donoghue. (2004). On the Variability of Manual Spike Sorting. IEEE Transactions on Biomedical Engineering. 51(6). 912–918. 120 indexed citations
12.
Paninski, Liam, Shy Shoham, Matthew Fellows, Nicholas G. Hatsopoulos, & John P. Donoghue. (2004). Superlinear Population Encoding of Dynamic Hand Trajectory in Primary Motor Cortex. Journal of Neuroscience. 24(39). 8551–8561. 90 indexed citations
13.
Serruya, Mijail D., Matthew Fellows, Liam Paninski, John P. Donoghue, & Nicholas G. Hatsopoulos. (2003). Robustness of neuroprosthetic decoding algorithms. Biological Cybernetics. 88(3). 219–228. 76 indexed citations
14.
Shoham, Shy, Matthew Fellows, & Richard A. Normann. (2003). Robust, automatic spike sorting using mixtures of multivariate t-distributions. Journal of Neuroscience Methods. 127(2). 111–122. 253 indexed citations
15.
Serruya, Mijail D., Nicholas G. Hatsopoulos, Liam Paninski, Matthew Fellows, & John P. Donoghue. (2002). Instant neural control of a movement signal. Nature. 416(6877). 141–142. 1005 indexed citations breakdown →

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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