Sylvain Takerkart

1.4k total citations
38 papers, 816 citations indexed

About

Sylvain Takerkart is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Sylvain Takerkart has authored 38 papers receiving a total of 816 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Cognitive Neuroscience, 8 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Artificial Intelligence. Recurrent topics in Sylvain Takerkart's work include Functional Brain Connectivity Studies (15 papers), Neural dynamics and brain function (13 papers) and Neuroscience and Music Perception (8 papers). Sylvain Takerkart is often cited by papers focused on Functional Brain Connectivity Studies (15 papers), Neural dynamics and brain function (13 papers) and Neuroscience and Music Perception (8 papers). Sylvain Takerkart collaborates with scholars based in France, Canada and United States. Sylvain Takerkart's co-authors include Driss Boussaoud, Andrea Brovelli, Pascal Belin, Abdelhak Mahmoudi, Fakhita Regragui, James V. Haxby, Evangelos Roussos, Jonathan D. Cohen, W. Richter and Ingrid Daubechies and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Sylvain Takerkart

36 papers receiving 804 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sylvain Takerkart France 16 640 145 113 86 79 38 816
Kai Görgen Germany 9 1.1k 1.7× 85 0.6× 97 0.9× 86 1.0× 157 2.0× 18 1.3k
Mark Jarmasz Canada 8 444 0.7× 166 1.1× 45 0.4× 52 0.6× 62 0.8× 15 642
Keiji Iramina Japan 16 662 1.0× 159 1.1× 52 0.5× 104 1.2× 81 1.0× 134 886
Frank Morales Cuba 4 750 1.2× 333 2.3× 54 0.5× 50 0.6× 78 1.0× 8 1.0k
Sara L. Gonzalez Andino Switzerland 13 847 1.3× 78 0.5× 97 0.9× 95 1.1× 224 2.8× 27 1.0k
Mainak Jas United States 12 666 1.0× 57 0.4× 58 0.5× 69 0.8× 64 0.8× 19 802
Gijs Plomp Switzerland 24 1.3k 2.0× 166 1.1× 48 0.4× 106 1.2× 122 1.5× 58 1.4k
Mark E. Pflieger United States 11 753 1.2× 91 0.6× 52 0.5× 56 0.7× 149 1.9× 19 882
Michelle Moerel Netherlands 19 1.4k 2.2× 403 2.8× 116 1.0× 55 0.6× 203 2.6× 31 1.6k
Luís Freire Portugal 6 475 0.7× 237 1.6× 61 0.5× 29 0.3× 48 0.6× 11 628

Countries citing papers authored by Sylvain Takerkart

Since Specialization
Citations

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

Fields of papers citing papers by Sylvain Takerkart

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sylvain Takerkart

This figure shows the co-authorship network connecting the top 25 collaborators of Sylvain Takerkart. A scholar is included among the top collaborators of Sylvain Takerkart 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 Sylvain Takerkart. Sylvain Takerkart 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.
Simon, Grégory, et al.. (2024). Sulcal pits of the superior temporal sulcus in schizophrenia patients with auditory verbal hallucinations. AIMS neuroscience. 11(1). 25–38. 3 indexed citations
2.
Dupé, François-Xavier, et al.. (2024). Geometric Deep Learning for Sulcal Graphs. 1–5.
3.
Dupé, François-Xavier, et al.. (2023). Population-wise labeling of sulcal graphs using multi-graph matching. PLoS ONE. 18(11). e0293886–e0293886. 1 indexed citations
4.
Simeone, Pierre, Guillaume Auzias, Julien Lefèvre, et al.. (2022). Long-term follow-up of neurodegenerative phenomenon in severe traumatic brain injury using MRI. Annals of Physical and Rehabilitation Medicine. 65(6). 101599–101599. 7 indexed citations
5.
Kamentsky, Lee, Giacomo Mazzamuto, Alberto Lazari, et al.. (2022). Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data. Frontiers in Neuroscience. 16. 871228–871228. 10 indexed citations
6.
Velly, Lionel, et al.. (2021). FMRI-based identity classification accuracy in left temporal and frontal regions predicts speaker recognition performance. Scientific Reports. 11(1). 489–489. 16 indexed citations
7.
Sellami, Akrem, et al.. (2020). Mapping individual differences in cortical architecture using multi-view\n representation learning. arXiv (Cornell University). 6 indexed citations
8.
Belin, Pascal, et al.. (2020). Single-trial fMRI activation maps measured during the InterTVA event-related voice localizer. A data set ready for inter-subject pattern analysis. SHILAP Revista de lepidopterología. 29. 105170–105170. 2 indexed citations
9.
Wang, Qi, Thierry Artières, & Sylvain Takerkart. (2020). Inter-subject pattern analysis for multivariate group analysis of functional neuroimaging. A unifying formalization. Computer Methods and Programs in Biomedicine. 197. 105730–105730. 1 indexed citations
10.
Wang, Qi, et al.. (2019). Inter-subject pattern analysis: A straightforward and powerful scheme for group-level MVPA. NeuroImage. 204. 116205–116205. 27 indexed citations
11.
Clément, François, et al.. (2017). Enhanced Neonatal Brain Responses To Sung Streams Predict Vocabulary Outcomes By Age 18 Months. Scientific Reports. 7(1). 12451–12451. 28 indexed citations
12.
Matonti, F., Florent Dupont, L. Hoffart, et al.. (2016). Probing the functional impact of sub-retinal prosthesis. eLife. 5. 15 indexed citations
13.
Takerkart, Sylvain & Liva Ralaivola. (2014). Multiple Subject Learning for Inter-Subject Prediction. HAL (Le Centre pour la Communication Scientifique Directe).
14.
Takerkart, Sylvain, Guillaume Auzias, Bertrand Thirion, & Liva Ralaivola. (2014). Graph-Based Inter-Subject Pattern Analysis of fMRI Data. PLoS ONE. 9(8). e104586–e104586. 19 indexed citations
15.
Auzias, Guillaume, Marine Viellard, Sylvain Takerkart, et al.. (2014). Atypical sulcal anatomy in young children with autism spectrum disorder. NeuroImage Clinical. 4. 593–603. 43 indexed citations
16.
Deneux, Thomas, Sylvain Takerkart, Amiram Grinvald, Guillaume S. Masson, & Ivo Vanzetta. (2011). A processing work-flow for measuring erythrocytes velocity in extended vascular networks from wide field high-resolution optical imaging data. NeuroImage. 59(3). 2569–2588. 11 indexed citations
17.
Kilavik, Bjørg Elisabeth, et al.. (2011). Context-Related Frequency Modulations of Macaque Motor Cortical LFP Beta Oscillations. Cerebral Cortex. 22(9). 2148–2159. 61 indexed citations
18.
Deneux, Thomas, Olivier Faugeras, Sylvain Takerkart, Guillaume S. Masson, & Ivo Vanzetta. (2011). A New Variational Method for Erythrocyte Velocity Estimation in Wide-Field ImagingIn Vivo. IEEE Transactions on Medical Imaging. 30(8). 1527–1545. 4 indexed citations
19.
Reynaud, Alexandre, Sylvain Takerkart, Guillaume S. Masson, & Frédéric Chavane. (2010). Linear model decomposition for voltage-sensitive dye imaging signals: Application in awake behaving monkey. NeuroImage. 54(2). 1196–1210. 21 indexed citations
20.
Monfardini, Elisabetta, Andrea Brovelli, Driss Boussaoud, Sylvain Takerkart, & Bruno Wicker. (2008). I learned from what you did: Retrieving visuomotor associations learned by observation. NeuroImage. 42(3). 1207–1213. 16 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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