Lee E. Miller

10.6k total citations · 1 hit paper
158 papers, 5.9k citations indexed

About

Lee E. Miller is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Biomedical Engineering. According to data from OpenAlex, Lee E. Miller has authored 158 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Cognitive Neuroscience, 74 papers in Cellular and Molecular Neuroscience and 64 papers in Biomedical Engineering. Recurrent topics in Lee E. Miller's work include EEG and Brain-Computer Interfaces (98 papers), Neuroscience and Neural Engineering (69 papers) and Muscle activation and electromyography studies (60 papers). Lee E. Miller is often cited by papers focused on EEG and Brain-Computer Interfaces (98 papers), Neuroscience and Neural Engineering (69 papers) and Muscle activation and electromyography studies (60 papers). Lee E. Miller collaborates with scholars based in United States, United Kingdom and Philippines. Lee E. Miller's co-authors include Matthew G. Perich, Sara A. Solla, Juan Álvaro Gallego, James C. Houk, Christian Éthier, Sliman J. Bensmaı̈a, Emily R. Oby, Robert N. Holdefer, Konrad P. Körding and Luke R. Jordan and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Lee E. Miller

153 papers receiving 5.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Neural Manifolds for the Control of Movement

2017 315 citations Juan Álvaro Gallego, Matthew G. Perich et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lee E. Miller United States	45	4.8k	2.7k	1.9k	639	491	158	5.9k
Sliman J. Bensmaı̈a United States	48	6.1k 1.3×	2.7k 1.0×	2.3k 1.2×	542 0.8×	308 0.6×	126	7.2k
Jose M. Carmena United States	48	6.5k 1.3×	5.7k 2.1×	2.9k 1.6×	2.5k 4.0×	281 0.6×	144	9.2k
Nicholas G. Hatsopoulos United States	45	6.0k 1.3×	3.6k 1.3×	1.4k 0.7×	895 1.4×	225 0.5×	113	7.1k
Douglas J. Weber United States	39	3.8k 0.8×	3.5k 1.3×	2.7k 1.4×	1.2k 1.9×	444 0.9×	141	7.0k
Jiping He United States	33	1.1k 0.2×	784 0.3×	1.6k 0.9×	355 0.6×	344 0.7×	192	3.7k
Johan Wessberg Sweden	37	5.1k 1.1×	1.6k 0.6×	1.1k 0.6×	313 0.5×	311 0.6×	68	7.2k
Steven S. Hsiao United States	42	5.1k 1.0×	1.2k 0.4×	780 0.4×	197 0.3×	195 0.4×	73	5.7k
Hannes Bleuler Switzerland	39	1.5k 0.3×	625 0.2×	2.8k 1.5×	1.3k 2.1×	79 0.2×	215	5.6k
Mikhail Lebedev United States	42	7.2k 1.5×	5.0k 1.8×	1.7k 0.9×	1.5k 2.3×	210 0.4×	154	8.4k
Stephen I. Helms Tillery United States	18	2.3k 0.5×	1.4k 0.5×	1.3k 0.7×	390 0.6×	184 0.4×	28	3.2k

Countries citing papers authored by Lee E. Miller

Since Specialization

Citations

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

Fields of papers citing papers by Lee E. Miller

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lee E. Miller. 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 Lee E. Miller. The network helps show where Lee E. Miller may publish in the future.

Co-authorship network of co-authors of Lee E. Miller

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

All Works

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20 of 20 papers shown

Miller, Lee E., et al.. (2025). Simulating the people's voice: Leveraging algorithmic fidelity to assess ChatGPT's performance in modeling public opinion on Chinese government policies. Information Processing & Management. 63(3). 104567–104567.

Perich, Matthew G., et al.. (2025). A neural implementation model of feedback-based motor learning. Nature Communications. 16(1). 1805–1805. 3 indexed citations

Nason, Samuel R., Claire Nicolas, Leigh R. Hochberg, et al.. (2024). BRAND: a platform for closed-loop experiments with deep network models. Journal of Neural Engineering. 21(2). 26046–26046. 8 indexed citations

Solla, Sara A., et al.. (2023). From monkeys to humans: observation-based EMG brain–computer interface decoders for humans with paralysis. Journal of Neural Engineering. 20(5). 56040–56040. 3 indexed citations

Perich, Matthew G., et al.. (2022). Small, correlated changes in synaptic connectivity may facilitate rapid motor learning. Nature Communications. 13(1). 5163–5163. 12 indexed citations

Chowdhury, Raeed H., et al.. (2022). A large-scale neural network training framework for generalized estimation of single-trial population dynamics. Nature Methods. 19(12). 1572–1577. 35 indexed citations

Perich, Matthew G., et al.. (2022). Local field potentials reflect cortical population dynamics in a region-specific and frequency-dependent manner. eLife. 11. 27 indexed citations

Goetz, Stefan M., et al.. (2022). Characterizing the short-latency evoked response to intracortical microstimulation across a multi-electrode array. Journal of Neural Engineering. 19(2). 26044–26044. 20 indexed citations

Suresh, Aneesha K., Charles M. Greenspon, Qinpu He, et al.. (2021). Sensory computations in the cuneate nucleus of macaques. Proceedings of the National Academy of Sciences. 118(49). 20 indexed citations

10.

Rosenow, Joshua M., et al.. (2021). Encoding of limb state by single neurons in the cuneate nucleus of awake monkeys. Journal of Neurophysiology. 126(2). 693–706. 13 indexed citations

11.

Furlanello, Tommaso, et al.. (2021). Rapid adaptation of brain–computer interfaces to new neuronal ensembles or participants via generative modelling. Nature Biomedical Engineering. 7(4). 546–558. 23 indexed citations

12.

Chowdhury, Raeed H., et al.. (2021). Cuneate nucleus: the somatosensory gateway to the brain. Current Opinion in Physiology. 20. 206–215. 8 indexed citations

13.

Gallego, Juan Álvaro, Matthew G. Perich, Raeed H. Chowdhury, Sara A. Solla, & Lee E. Miller. (2020). Long-term stability of cortical population dynamics underlying consistent behavior. Nature Neuroscience. 23(2). 260–270. 176 indexed citations

14.

Tomlinson, Tucker, et al.. (2020). A comprehensive model-based framework for optimal design of biomimetic patterns of electrical stimulation for prosthetic sensation. Journal of Neural Engineering. 17(4). 46045–46045. 13 indexed citations

15.

Chowdhury, Raeed H., Joshua I. Glaser, & Lee E. Miller. (2020). Area 2 of primary somatosensory cortex encodes kinematics of the whole arm. eLife. 9. 35 indexed citations

16.

Gallego, Juan Álvaro, Matthew G. Perich, Stephanie Naufel, et al.. (2018). Cortical population activity within a preserved neural manifold underlies multiple motor behaviors. Nature Communications. 9(1). 160 indexed citations

17.

Glaser, Joshua I., Matthew G. Perich, Pavan Ramkumar, Lee E. Miller, & Konrad P. Körding. (2018). Population coding of conditional probability distributions in dorsal premotor cortex. Nature Communications. 9(1). 1788–1788. 32 indexed citations

18.

Pandarinath, Chethan, K. Cora Ames, Abigail A. Russo, et al.. (2018). Latent Factors and Dynamics in Motor Cortex and Their Application to Brain–Machine Interfaces. Journal of Neuroscience. 38(44). 9390–9401. 64 indexed citations

19.

Dyer, Eva L., Mohammad Gheshlaghi Azar, Matthew G. Perich, et al.. (2017). A cryptography-based approach for movement decoding. Nature Biomedical Engineering. 1(12). 967–976. 31 indexed citations

20.

Fagg, Andrew H., Nicholas G. Hatsopoulos, Víctor de Lafuente, et al.. (2007). Biomimetic Brain Machine Interfaces for the Control of Movement. Journal of Neuroscience. 27(44). 11842–11846. 47 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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