The scientist’s investigation covers issues in Artificial intelligence, Electroencephalography, Pattern recognition, Neuroscience and Wavelet. His Artificial intelligence study combines topics in areas such as Ripple, Machine learning, Computer vision and Masking. His Electroencephalography research includes elements of Temporal lobe and Default mode network.
His studies in Pattern recognition integrate themes in fields like Inverse problem, Principle of maximum entropy, Entropy and EEG-fMRI, Epilepsy. The Inverse problem study combines topics in areas such as Ictal, Bayesian inference, Noise and Receiver operating characteristic. His study in the fields of Wavelet transform, Coiflet and Stationary wavelet transform under the domain of Wavelet overlaps with other disciplines such as Scaling.
His main research concerns Electroencephalography, Artificial intelligence, Pattern recognition, Neuroscience and Wavelet. Jean-Marc Lina works on Electroencephalography which deals in particular with Magnetoencephalography. His Artificial intelligence study incorporates themes from Inverse problem, Computer vision and Sensitivity.
The various areas that he examines in his Inverse problem study include Algorithm and Machine learning. His Pattern recognition course of study focuses on Epileptic discharge and Epileptic activity. In his research, Graphical model is intimately related to Entropy, which falls under the overarching field of Principle of maximum entropy.
Jean-Marc Lina spends much of his time researching Electroencephalography, Audiology, Sleep in non-human animals, Artificial intelligence and Amplitude. His Electroencephalography study is focused on Neuroscience in general. His Audiology research includes themes of Non-rapid eye movement sleep, Cognition and Polysomnography.
His biological study spans a wide range of topics, including Tomography, Mr imaging and Pattern recognition. His work in Pattern recognition addresses issues such as Principle of maximum entropy, which are connected to fields such as Finger tapping, Algorithm and Weighting. His Magnetoencephalography research is multidisciplinary, incorporating perspectives in Ictal and Epilepsy.
His scientific interests lie mostly in Pattern recognition, Artificial intelligence, Ictal, Principle of maximum entropy and Neuroscience. The concepts of his Pattern recognition study are interwoven with issues in Supine position and Backpropagation. His Artificial intelligence study frequently draws connections to adjacent fields such as Cohen's kappa.
Jean-Marc Lina combines subjects such as Cortical map and Magnetoencephalography with his study of Ictal. Jean-Marc Lina has researched Principle of maximum entropy in several fields, including Tomography, Surgical planning and Statistical parametric mapping. His study focuses on the intersection of Neuroscience and fields such as Age related with connections in the field of Eye movement, Human brain and Electroencephalography.
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Evaluation of EEG localization methods using realistic simulations of interictal spikes.
Christophe Grova;Jean Daunizeau;Jean Daunizeau;Jean-Marc Lina;Jean-Marc Lina;Christian G. Bénar.
Complex Daubechies Wavelets
Jean-Marc Lina;Michel Mayrand.
Applied and Computational Harmonic Analysis (1995)
Recording and analysis techniques for high-frequency oscillations
G. A. Worrell;K. Jerbi;K. Kobayashi;Jean-Marc Lina.
Progress in Neurobiology (2012)
Seizure prediction for therapeutic devices: A review.
Kais Gadhoumi;Kais Gadhoumi;Jean-Marc Lina;Florian Mormann;Jean Gotman;Jean Gotman.
Journal of Neuroscience Methods (2016)
Symmetrical event-related EEG/fMRI information fusion in a variational Bayesian framework
Jean Daunizeau;Christophe Grova;Guillaume Marrelec;Jérémie Mattout.
Scalp EEG is not a Blur: It Can See High Frequency Oscillations Although Their Generators are Small
R. Zelmann;J. M. Lina;A. Schulze-Bonhage;J. Gotman.
Brain Topography (2014)
WAVELET-BASED MULTIFRACTAL FORMALISM TO ASSIST IN DIAGNOSIS IN DIGITIZED MAMMOGRAMS
Pierre Kestener;Jean Marc Lina;Philippe Saint-Jean;Alain Arneodo.
Image Analysis & Stereology (2011)
A short introduction to wavelets and their applications
C. Gargour;M. Gabrea;V. Ramachandran;J.-M. Lina.
IEEE Circuits and Systems Magazine (2009)
Cortical Thinning Explains Changes in Sleep Slow Waves during Adulthood
Jonathan Dubé;Marjolaine Lafortune;Christophe Bedetti;Maude Bouchard.
The Journal of Neuroscience (2015)
MEG Source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches
Rasheda Arman Chowdhury;Jean Marc Lina;Jean Marc Lina;Eliane Kobayashi;Christophe Grova;Christophe Grova;Christophe Grova.
PLOS ONE (2013)
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