Olivier Codol

417 total citations
10 papers, 192 citations indexed

About

Olivier Codol is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Physical Therapy, Sports Therapy and Rehabilitation. According to data from OpenAlex, Olivier Codol has authored 10 papers receiving a total of 192 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 6 papers in Biomedical Engineering and 3 papers in Physical Therapy, Sports Therapy and Rehabilitation. Recurrent topics in Olivier Codol's work include Motor Control and Adaptation (8 papers), Muscle activation and electromyography studies (6 papers) and Balance, Gait, and Falls Prevention (3 papers). Olivier Codol is often cited by papers focused on Motor Control and Adaptation (8 papers), Muscle activation and electromyography studies (6 papers) and Balance, Gait, and Falls Prevention (3 papers). Olivier Codol collaborates with scholars based in United Kingdom, Canada and United States. Olivier Codol's co-authors include Joseph M. Galea, Peter Holland, Sanjay Manohar, Paul L. Gribble, J. Andrew Pruszynski, Kevin Gurney, Jonathan A. Michaels, Jeffrey Weiler, Jonathan C. Lau and Jörn Diedrichsen and has published in prestigious journals such as Nature, Journal of Neuroscience and Journal of Neurophysiology.

In The Last Decade

Olivier Codol

10 papers receiving 192 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Olivier Codol United Kingdom	6	178	91	62	24	23	10	192
Erik M. Summerside United States	5	189 1.1×	53 0.6×	60 1.0×	26 1.1×	16 0.7×	8	245
Pauline M. Hilt Italy	12	203 1.1×	61 0.7×	110 1.8×	23 1.0×	32 1.4×	23	251
Alexandra Reichenbach Germany	10	293 1.6×	97 1.1×	77 1.2×	29 1.2×	54 2.3×	19	330
Susen Werner Germany	9	312 1.8×	120 1.3×	143 2.3×	23 1.0×	59 2.6×	12	341
Scott T. Albert United States	6	161 0.9×	70 0.8×	60 1.0×	26 1.1×	26 1.1×	8	180
Simone Ferrari-Toniolo Italy	11	285 1.6×	48 0.5×	133 2.1×	7 0.3×	22 1.0×	19	336
Cristian Cuadra Chile	10	178 1.0×	152 1.7×	63 1.0×	37 1.5×	6 0.3×	17	193
Raphael Schween Germany	9	179 1.0×	112 1.2×	95 1.5×	23 1.0×	12 0.5×	10	224
James J. Burkitt Canada	10	226 1.3×	52 0.6×	56 0.9×	41 1.7×	8 0.3×	20	271
Yuming Lei United States	10	189 1.1×	147 1.6×	66 1.1×	18 0.8×	43 1.9×	25	254

Countries citing papers authored by Olivier Codol

Since Specialization

Citations

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

Fields of papers citing papers by Olivier Codol

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olivier Codol

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

All Works

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10 of 10 papers shown

Michaels, Jonathan A., Olivier Codol, Jeffrey Weiler, et al.. (2025). Sensory expectations shape neural population dynamics in motor circuits. Nature. 648(8094). 668–677. 1 indexed citations

Codol, Olivier, et al.. (2024). MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks. eLife. 12. 2 indexed citations

Codol, Olivier, et al.. (2023). Sensorimotor feedback loops are selectively sensitive to reward. eLife. 12. 11 indexed citations

Codol, Olivier, et al.. (2023). MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks. eLife. 12. 3 indexed citations

Codol, Olivier, Paul L. Gribble, & Kevin Gurney. (2022). Differential Dopamine Receptor-Dependent Sensitivity Improves the Switch Between Hard and Soft Selection in a Model of the Basal Ganglia. Neural Computation. 34(7). 1588–1615. 2 indexed citations

Codol, Olivier, et al.. (2020). Reward-driven enhancements in motor control are robust to TMS manipulation. Experimental Brain Research. 238(7-8). 1781–1793. 7 indexed citations

Codol, Olivier, Peter Holland, Sanjay Manohar, & Joseph M. Galea. (2020). Reward-Based Improvements in Motor Control Are Driven by Multiple Error-Reducing Mechanisms. Journal of Neuroscience. 40(18). 3604–3620. 38 indexed citations

Holland, Peter, et al.. (2019). Domain-Specific Working Memory, But Not Dopamine-Related Genetic Variability, Shapes Reward-Based Motor Learning. Journal of Neuroscience. 39(47). 9383–9396. 11 indexed citations

Holland, Peter, Olivier Codol, & Joseph M. Galea. (2018). Contribution of explicit processes to reinforcement-based motor learning. Journal of Neurophysiology. 119(6). 2241–2255. 71 indexed citations

10.

Codol, Olivier, Peter Holland, & Joseph M. Galea. (2018). The relationship between reinforcement and explicit control during visuomotor adaptation. Scientific Reports. 8(1). 9121–9121. 46 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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