J.-M. Lina

1.3k total citations
22 papers, 937 citations indexed

About

J.-M. Lina is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition. According to data from OpenAlex, J.-M. Lina has authored 22 papers receiving a total of 937 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cognitive Neuroscience, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in J.-M. Lina's work include Neural dynamics and brain function (7 papers), Functional Brain Connectivity Studies (7 papers) and Image and Signal Denoising Methods (5 papers). J.-M. Lina is often cited by papers focused on Neural dynamics and brain function (7 papers), Functional Brain Connectivity Studies (7 papers) and Image and Signal Denoising Methods (5 papers). J.-M. Lina collaborates with scholars based in Canada, France and United Kingdom. J.-M. Lina's co-authors include Rina Zelmann, Christophe Grova, Jean Gotman, B. Goulard, Katsuhiro Kobayashi, Michel Le Van Quyen, Julia Jacobs, Eliane Kobayashi, Karim Jerbi and Andreas Schulze‐Bonhage and has published in prestigious journals such as NeuroImage, Nuclear Physics B and IEEE Transactions on Signal Processing.

In The Last Decade

J.-M. Lina

22 papers receiving 909 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J.-M. Lina Canada 17 596 263 199 148 118 22 937
Mercedes Cabrerizo United States 22 596 1.0× 159 0.6× 355 1.8× 65 0.4× 254 2.2× 90 1.4k
Christian Rummel Switzerland 23 1.3k 2.1× 197 0.7× 350 1.8× 239 1.6× 65 0.6× 94 1.9k
Yi‐Ou Li United States 15 1.2k 2.1× 585 2.2× 145 0.7× 66 0.4× 118 1.0× 22 1.9k
Okito Yamashita Japan 18 1.2k 2.0× 384 1.5× 35 0.2× 126 0.9× 126 1.1× 63 1.6k
Joseph Suresh Paul India 14 593 1.0× 220 0.8× 59 0.3× 56 0.4× 51 0.4× 63 1.0k
Ünal Sakoğlu United States 15 751 1.3× 336 1.3× 59 0.3× 50 0.3× 47 0.4× 35 1.2k
Jianting Cao Japan 21 491 0.8× 84 0.3× 49 0.2× 89 0.6× 166 1.4× 118 1.1k
N. A. Thacker United Kingdom 16 167 0.3× 185 0.7× 75 0.4× 114 0.8× 459 3.9× 76 1.1k
Lawrence P. Panych United States 21 676 1.1× 647 2.5× 113 0.6× 74 0.5× 75 0.6× 46 1.3k
Peter Van Hese Belgium 13 395 0.7× 101 0.4× 70 0.4× 148 1.0× 91 0.8× 48 612

Countries citing papers authored by J.-M. Lina

Since Specialization
Citations

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

Fields of papers citing papers by J.-M. Lina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J.-M. Lina. 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 J.-M. Lina. The network helps show where J.-M. Lina may publish in the future.

Co-authorship network of co-authors of J.-M. Lina

This figure shows the co-authorship network connecting the top 25 collaborators of J.-M. Lina. A scholar is included among the top collaborators of J.-M. Lina 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 J.-M. Lina. J.-M. Lina 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.
Hedrich, Tanguy, Giovanni Pellegrino, Eliane Kobayashi, J.-M. Lina, & Christophe Grova. (2017). Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG. NeuroImage. 157. 531–544. 104 indexed citations
2.
Chowdhury, Rasheda Arman, Isabelle Merlet, Gwénaël Birot, et al.. (2016). Complex patterns of spatially extended generators of epileptic activity: Comparison of source localization methods cMEM and 4-ExSo-MUSIC on high resolution EEG and MEG data. NeuroImage. 143. 175–195. 40 indexed citations
3.
Lafortune, Marjolaine, et al.. (2015). Age-related changes in sleep spindles characteristics during daytime recovery following a 25-hour sleep deprivation. Frontiers in Human Neuroscience. 9. 323–323. 18 indexed citations
4.
Zelmann, Rina, J.-M. Lina, Andreas Schulze‐Bonhage, Jean Gotman, & Julia Jacobs. (2013). Scalp EEG is not a Blur: It Can See High Frequency Oscillations Although Their Generators are Small. Brain Topography. 27(5). 683–704. 126 indexed citations
5.
Lopes, Renaud, J.-M. Lina, Firas Fahoum, & Jean Gotman. (2012). Detection of epileptic activity in fMRI without recording the EEG. NeuroImage. 60(3). 1867–1879. 34 indexed citations
6.
Worrell, Gregory A., Karim Jerbi, Katsuhiro Kobayashi, et al.. (2012). Recording and analysis techniques for high-frequency oscillations. Progress in Neurobiology. 98(3). 265–278. 150 indexed citations
7.
Zerouali, Younes, Cyril Herry, Boutheina Jemel, & J.-M. Lina. (2011). Localization of Synchronous Cortical Neural Sources. IEEE Transactions on Biomedical Engineering. 60(3). 770–780. 7 indexed citations
8.
Lina, J.-M., Julie Tremblay, Maryse Lassonde, et al.. (2010). Detection of hemodynamic responses to epileptic activity using simultaneous Electro-EncephaloGraphy (EEG)/Near Infra Red Spectroscopy (NIRS) acquisitions. NeuroImage. 56(1). 114–125. 45 indexed citations
9.
Lina, J.-M., et al.. (2010). Wavelet-based estimation of the hemodynamic responses in diffuse optical imaging. Medical Image Analysis. 14(4). 606–616. 18 indexed citations
10.
Gargour, Christian, M. Gabrea, V. Ramachandran, & J.-M. Lina. (2009). A short introduction to wavelets and their applications. IEEE Circuits and Systems Magazine. 9(2). 57–68. 67 indexed citations
11.
Dehaes, Mathieu, et al.. (2008). $1/f$ Noise in Diffuse Optical Imaging and Wavelet-Based Response Estimation. IEEE Transactions on Medical Imaging. 28(3). 415–422. 24 indexed citations
12.
Cohen‐Adad, Julien, Julien Doyon, Sylvie Rossignol, et al.. (2007). Activation detection in diffuse optical imaging by means of the general linear model. Medical Image Analysis. 11(6). 616–629. 44 indexed citations
13.
Daunizeau, Jean, et al.. (2006). Bayesian Spatio-Temporal Approach for EEG Source Reconstruction: Conciliating ECD and Distributed Models. IEEE Transactions on Biomedical Engineering. 53(3). 503–516. 51 indexed citations
14.
Gagnon, L., J.-M. Lina, & B. Goulard. (2005). Application of Complex Daubechies' Wavelets to Numerical Simulation of a Nonlinear Signal Propagation Model. 26. 251–254. 1 indexed citations
15.
Daunizeau, Jean, Christophe Grova, Jérémie Mattout, et al.. (2005). Assessing the relevance of fMRI-based prior in the EEG inverse problem: a bayesian model comparison approach. IEEE Transactions on Signal Processing. 53(9). 3461–3472. 37 indexed citations
16.
Lina, J.-M., et al.. (2004). Biomagnetic Source Detection by Maximum Entropy and Graphical Models. IEEE Transactions on Biomedical Engineering. 51(3). 427–442. 63 indexed citations
17.
Lina, J.-M., et al.. (2003). Complex Daubechies wavelets: properties and statistical image modelling. Signal Processing. 84(1). 1–23. 46 indexed citations
18.
Belzer, Benjamin J., J.-M. Lina, & John Villasenor. (1995). Complex, linear-phase filters for efficient image coding. IEEE Transactions on Signal Processing. 43(10). 2425–2427. 23 indexed citations
19.
Gagnon, L. & J.-M. Lina. (1994). Symmetric Daubechies' wavelets and numerical solution of NLS equations. Journal of Physics A Mathematical and General. 27(24). 8207–8230. 21 indexed citations
20.
Lina, J.-M., et al.. (1991). Canonical quantization of the induced 2D gravity. Nuclear Physics B. 358(3). 713–736. 3 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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