Jean Debarros

786 total citations
10 papers, 526 citations indexed

About

Jean Debarros is a scholar working on Neurology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Jean Debarros has authored 10 papers receiving a total of 526 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Neurology, 7 papers in Cellular and Molecular Neuroscience and 3 papers in Cognitive Neuroscience. Recurrent topics in Jean Debarros's work include Neurological disorders and treatments (8 papers), Neuroscience and Neural Engineering (5 papers) and EEG and Brain-Computer Interfaces (2 papers). Jean Debarros is often cited by papers focused on Neurological disorders and treatments (8 papers), Neuroscience and Neural Engineering (5 papers) and EEG and Brain-Computer Interfaces (2 papers). Jean Debarros collaborates with scholars based in United Kingdom, China and Switzerland. Jean Debarros's co-authors include Peter Brown, Damian M. Herz, Maggie J Westby, Emmert Roberts, Lon S. Schneider, Hayriye Cagnan, Rupert McShane, Neda Minakaran, Lucy Farrimond and Gerd Tinkhauser and has published in prestigious journals such as Brain, Cochrane Database of Systematic Reviews and eLife.

In The Last Decade

Jean Debarros

8 papers receiving 515 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jean Debarros United Kingdom	8	270	258	150	97	76	10	526
Pierluigi Tocco Italy	10	272 1.0×	112 0.4×	102 0.7×	103 1.1×	76 1.0×	21	567
Brandon Barton United States	8	662 2.5×	231 0.9×	111 0.7×	63 0.6×	107 1.4×	17	818
Sara Varanese Italy	14	463 1.7×	107 0.4×	262 1.7×	66 0.7×	173 2.3×	18	789
Jooyoung Lee South Korea	12	176 0.7×	166 0.6×	96 0.6×	71 0.7×	26 0.3×	45	555
Heiko Huber Germany	10	225 0.8×	153 0.6×	111 0.7×	60 0.6×	72 0.9×	12	450
A. M. Bonnet France	12	497 1.8×	212 0.8×	122 0.8×	103 1.1×	60 0.8×	17	688
Michael Kilbourn United States	4	423 1.6×	202 0.8×	94 0.6×	75 0.8×	77 1.0×	4	730
Jos W. R. Twisk Netherlands	10	221 0.8×	54 0.2×	353 2.4×	50 0.5×	101 1.3×	15	676
Nicholas J. Cordato Australia	13	403 1.5×	112 0.4×	100 0.7×	64 0.7×	137 1.8×	24	581
Larry S. Ivanco United States	9	557 2.1×	214 0.8×	202 1.3×	98 1.0×	164 2.2×	10	915

Countries citing papers authored by Jean Debarros

Since Specialization

Citations

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

Fields of papers citing papers by Jean Debarros

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jean Debarros

This figure shows the co-authorship network connecting the top 25 collaborators of Jean Debarros. A scholar is included among the top collaborators of Jean Debarros 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 Jean Debarros. Jean Debarros 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

1.

Pogosyan, Alek, Jean Debarros, Shenghong He, et al.. (2025). Flexible and stable cycle-by-cycle phase-locked deep brain stimulation system targeting brain oscillations in the management of movement disorders. Brain stimulation. 18(5). 1705–1717.

2.

Cannon, Mark, et al.. (2024). Model Predictive Control for Closed-Loop Deep Brain Stimulation. 4034–4039.

3.

He, Shenghong, Fahd Baig, Flavie Torrecillos, et al.. (2023). Beta-triggered adaptive deep brain stimulation during reaching movement in Parkinson’s disease. Brain. 146(12). 5015–5030. 25 indexed citations

4.

Huang, Yongzhi, Bomin Sun, Jean Debarros, et al.. (2021). Increased theta/alpha synchrony in the habenula-prefrontal network with negative emotional stimuli in human patients. eLife. 10. 19 indexed citations

5.

He, Shenghong, Fahd Baig, Abteen Mostofi, et al.. (2021). Closed‐Loop Deep Brain Stimulation for Essential Tremor Based on Thalamic Local Field Potentials. Movement Disorders. 36(4). 863–873. 55 indexed citations

6.

Debarros, Jean, Shenghong He, Alek Pogosyan, et al.. (2020). Artefact-free recording of local field potentials with simultaneous stimulation for closed-loop Deep-Brain Stimulation. PubMed. 2020. 3367–3370. 12 indexed citations

7.

He, Shenghong, Jean Debarros, Saed Khawaldeh, et al.. (2020). Closed-loop DBS triggered by real-time movement and tremor decoding based on thalamic LFPs for essential tremor. PubMed. 2020. 3602–3605. 12 indexed citations

8.

Tan, Huiling, Jean Debarros, Shenghong He, et al.. (2019). Decoding voluntary movements and postural tremor based on thalamic LFPs as a basis for closed-loop stimulation for essential tremor. Brain stimulation. 12(4). 858–867. 47 indexed citations

9.

McShane, Rupert, Maggie J Westby, Emmert Roberts, et al.. (2019). Memantine for dementia. Cochrane Database of Systematic Reviews. 215 indexed citations

10.

Tinkhauser, Gerd, et al.. (2017). Adaptive Deep Brain Stimulation for Movement Disorders: The Long Road to Clinical Therapy. Movement Disorders. 32(6). 810–819. 141 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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