Grova Research Group

The Multimodal Functional Imaging Laboratory, directed by Dr. Christophe Grova, is a multidisciplinary team composed of neurologists and methodologists. The laboratory is actually based on two sites:

  • Biomedical Engineering Department and part of the epilepsy group of the Montreal Neurological Institute, McGill University
  • Department of Physics and PERFORM Centre, Concordia University

We investigate multimodal data fusion to characterize brain mechanisms and especially epileptic activity. Our research project aims at developing methods to appropriately combine multimodal data in order to detect additional information that could be missed by considering each modality individually. A typical challenge is to combine modalities directly measuring neuronal activity with high temporal resolution with other modalities indirectly measuring the same function with high spatial resolution, through hemodynamic processes for instance. The project will involve the integration of three promising functional modalities:

  1. Simultaneous ElectroEncephaloGraphy (EEG) - MagnetoEncephaloGraphy (MEG) acquisitions, measuring directly on the scalp electric and magnetic components of signals generated by neurons synchronously active (at a ms scale).
  2. Simultaneous EEG - functional Magnetic Resonance Imaging (fMRI) acquisitions to measure, within the whole brain at a second scale, hemodynamic responses that correlate with signals detected on scalp EEG.
  3. Simultaneous EEG - Near InfraRed Spectroscopy (NIRS) acquisitions to measure local changes in oxy- and deoxy-hemoglobin at the time of signals detected on scalp EEG, by exploiting absorption properties of infrared light within brain tissues using optic fibres placed on the surface of the head. Note that our EEG/NIRS laboratory is located in Biomedical Engineering dpt and easily accessible from the McConnell Brain Imaging Centre.

The principal clinical application of this project will be to combine these three modalities using multimodal data fusion techniques to characterize brain regions involved during epileptic activity.  

Multi FunkIm Research

Using cutting-edge non invasive methods involving simultaneous EEG/MEG, EEG/fMRI and EEG/NIRS recordings, our objectives consist in proposing:

Theme 1: EEG/MEG source localization

We propose a methodology to localize along the cortical surface, electrophysiology data obtained at a millisecond time scale from scalp recordings. This results in solving the so-called inverse problem of source localization. Our main goal consists in the developpment of Maximum Entropy on the Mean (MEM) source localization, in the context of EEG source imaging, MEG source imaging and also EEG/MEG fusion, as the only distributed source localization method able to recover the spatial extent of the underlying generators.

This video shows the steps and the results of Electroencephalography (EEG) source localization for a visual half field paradigm. EEG is a technique that measures the neuronal activity in the brain using electrodes that are pasted on the scalp. It can measure brain signals at every millisecond, however, without advanced mathematical and physical tools it could not provide 3-dimensional (3D) information on the brain. Our research involves fusing the EEG signals -measured with a high-density EEG system (256 electrodes, EGI)- with the 3D anatomical information of the brain, obtained with Magnetic Resonance Imaging, to localize the neuronal activity on the cortex.
Complete multimodal investigation involving MEG source localization, fMRI response and intra-cranial EEG investigation.

Theme 2: Volumetric NIRS

Spatio-temporal reconstruction of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) responses. We propose a strategy from EEG/NIRS data acquisition, signal detection to volumetric reconstruction to demonstrate the ability of NIRS to localize, in space and in time, fluctuations of HbR and HbO.

Frontal NIRS montage used for a working memory experiment Frontal NIRS montage used for a working memory experiment where optodes are depicted as spheres, with green ones being detectors and red ones emitters. A transparent template head mesh is shown in dark grey, as well as a template cortex in light grey. Finally, an atlas of the pre-frontal cortex is depicted in purple (superior prefrontal), blue (transversal frontal) and green (orbito-frontal).
Coritcal reconstruction of the variations of oxy (HbO) and deoxy (HbR) hemoglobin concentrations Coritcal reconstruction of the variations of oxy (HbO) and deoxy (HbR) hemoglobin concentrations, evoked by the visualization of flashing checkerboards. The map on the top left depicts the optimal montage placed on the primary visual cortex. The bottom pictures show reconstructed maps of the maximum evoked HbO and HbR variations. The graph with the time courses shows the temporal hemodynamics variations, evoked by the visual stimulations.

Theme 3: Multimodal characterization of Neurovascular Coupling (NVC) during normal and pathological conditions

Multimodal characterization of Neurovascular Coupling (NVC) during normal and pathological conditions using (i) EEG/MEG sources to model neuronal bioelectrical input and (ii) fMRI and NIRS data to monitor brain hemodynamic response. NVC is the main principle allowing indirect measurement of brain activity (in fMRI, NIRS or Positron Emission Tomography) exploiting processes linking neuronal activity and brain vascular response. However, these processes are not well-known, especially in pathological conditions. Our objective is to combine multimodal non-invasive data to shed light on NVC processes.

Analysis of functional Near-InfraRed Spectroscopy (fNIRS) data acquired during a motor experiment Analysis of functional Near-InfraRed Spectroscopy (fNIRS) data acquired during a motor experiment. fNIRS is a technique that measures brain activity through the absorption of near infrared light by the cerebral hemoglobin (Hb). Hb concentration indeed varies locally when there is local neuronal activity. This is the so-called neuro-vascular coupling. The curves on the right show the variations of concentration of oxy- (red) and deoxy- (blue) hemoglobin evoked by a finger tapping task. On the left part, the amplitudes of these variations are displayed, mapped onto each measurement pair of optodes.
Multimodal view of a NIRS occipital montage Multimodal view of a NIRS occipital montage. The head mesh segmented from the anatomical MRI is shown as a grey wireframe. Slices of the subject’s anatomy are shown in greyscale. The NIRS optode placement is depicted as spheres, with green ones being detectors and red ones emitters.

Theme 4: Multimodal functional connectivity (FC) characterizing resting state data in normal and pathological conditions

While resting state fMRI data have exhibited regions showing distant correlations at low frequency (<0.05Hz) organized as connected networks, the consistent Resting State Networks (RSN), our objective is to combine multimodal data to identify EEG/MEG signatures that would explain such network organization and to characterize pathological networks at the individual level, as potential disease biomarkers.

 organization of brain networks studied using the blood oxygen-level dependent (BOLD) signals The organization of brain networks can be studied using the blood oxygen-level dependent (BOLD) signals measured using functional magnetic resonance imaging (fMRI) when a subject is not performing an explicit task (resting-state). We proposed a method called SParsity-based Analysis of Reliable K-hubness (SPARK) to model and estimate “hubs” of functional networks by measuring K-hubness in each voxel with good reliability of the estimation at the individual level. Hubs are defined as voxels that are involved in multiple (a sparse number K>1) networks, promoting inter-network connectivity and global communication that are related to higher-level brain functions.
Joint acquisition of electroencephalography (EEG) and functional Magnetic Resonance Imaging (MRI) Joint acquisition of electroencephalography (EEG) and functional Magnetic Resonance Imaging (MRI). A high density EEG cap is placed on the participant’s head before he enters the MRI scanner in the back.

Multi FunkIm Members

Principal investigator

Christophe Grova

Christophe Grova, Ph.D.
(514) 848-2424 ext. 4221


Pierre Bellec

Pierre Bellec, Ph.D.
Simexp lab: laboratory for brain simulation and exploration
Phone: (514) 340 3540 ext.3367
Fax: (514) 340 3530

Habib Benali

Habib Benali, Ph.D.
Scientific Direction of the PERFORM Centre, Concordia University
Phone: (514) 848-2424 ext. 7597
Research Interests: Human brain computational modeling and functional connectivity analysis. Multimodal analysis of electromagnetic and hemodynamic processes in the brain and spinal cord.

Thanh Dang-Vu

Thanh Dang-Vu, M.D., Ph.D.
Sleep, Cognition and Neuroimaging Laboratory (SCNLab)
Phone: (514) 340-3540 ext. 3991
Research Interests: Sleep pathologies. Biomarkers in neuroimaging in sleep associated to aging. Neurodegenerative diseases and cognitive decline.

Birgit Frauscher

Birgit Frauscher, M.D., Ph.D.
ANPHY Lab, McGill University
Phone: (514) 398 1952
Research Interests: Development of novel seizure-independent EEG markers for the epileptogenic zone in for accurate diagnosis of epilepsy. Investigation of the relationship between sleep and epilepsy. Brain physiology during wakefulness and sleep.

Claudine Gauthier

Claudine Gauthier, Ph.D.
Quantitative Physiological Imaging Lab, Department of Physics, Concordia University
Phone: (514) 848-2424 ext. 2193
Research Interests: Cerebral metabolic and vascular imaging. The impact of aging and lifestyle on the brain. Functional MRI. BOLD signal modeling. Quantitative imaging of plasticity.

Jean Gotman

Jean Gotman, Ph.D.
Gotman Lab
Phone: (514) 398 1953
Fax: (514) 398 8106
Research interests: Multi-modal analysis of interictal events using EEG, fMRI, source-localization and dipole modeling, SEEG, SPECT.

Eliane Kobayashi

Eliane Kobayashi, M.D., Ph.D.
Epilepsy Research Group, Montreal Neurological Hospital
Phone: (514) 398 6644, ext 00469
Fax: (514) 398 8106

Jean-Marc Lina

Jean-Marc Lina, Ph.D.
Centre d’études avancées en médecine du sommeil (CÉAMS), Université de Montréal
Phone: (514) 396 8688
Research interests: Wavelets, statistical modeling and brain imaging, algorithms for statistical learning.

Research associates

Tanguy Hedrick

Tanguy Hedrick

Postdoctoral fellows

Chifaou Abdallah

Chifaou Abdallah, M.D.

Hassan Khajehpour

Hassan Khajehpour

Makoto Uji

Makoto Uji

Ph.D. candidates

Édouard Delaire

Édouard Delaire


Fatemeh Razavipour

Jawata Afnan

Jawata Afnan

Saurabh Maiti

Obaï Bin Ka’b Ali

Tamir Avigdor

Tamir Avigdor

Zhengchen Cai

Zhengchen Cai

M.Sc. students

Yimeng Wang

Yimeng Wang

Amanda Spilkin

Amanda Spilkin

Alumni & former fellows

Visiting Professors
  • Nicolás von Ellenrieder, Ph.D., July 2014 – December 2014
    • Montreal Neurological Institute
    • Project: High frequency oscillations in EEG
Research associates
  • Thomas Vincent, Ph.D., January 2015 – January 2018
    • Supervisor: Christophe Grova
    • Co-supervisor: Louis Bherer, Centre EPIC
    • Project: NIRS estimation and Bayesian deconvolution of the hemodynamic response
    • Currently a research associate at Centre EPIC, Montreal Heart Institute
Postdoctoral Fellows
  • Ümit Aydin, Ph.D., April 2016 – June 2019
    • Supervisor: Christophe Grova
    • Department of Physics, Concordia University
    • Project: Resting state function connectivity using MEG and simultaneous high density EEG / fMRI in healthy subjects and epilepsy
  • Giovanni Pellegrino, M.D., November 2013 – September 2016
    • Supervisor at McGill: Christophe Grova
    • Department of Biomedical Engineering, McGill University
    • Project: Epilepsy in EEG/MEG/NIRS
  • Vera Gramigna, Ph.D., March 2015 – September 2015
    • Supervisor at McGill: Christophe Grova
    • Scientific grant supervisor in Italy: Prof. Aldo Quattrone; Supervisor in Italy: Prof. Antonio Cerasa
    • Department of Biomedical Engineering, McGill University
    • Project: Multimodal Neuroimaging Correlates of Motor Disorders
  • Marcel Heers, M.D., September 2012 – September 2013
    • Supervisor: E Kobayashi MNI
    • Co-supervisor: Christophe Grova
    • Montreal Neurological Institute
    • Project: Correlation between MEG sources and EEG/fMRI responses of epileptic discharges
  • Dominique Rosenberg, M.D., July 2010 – July 2011
    • Supervisor: E Kobayashi MNI
    • Co-supervisor: Christophe Grova
    • Montreal Neurological Institute
    • Project: EEG/NIRS simultaneous recording in patients with epilepsy
Ph.D. Students
  • Kangjoo Lee, 2012–2019
    • Supervisor: Christophe Grova
    • Co-Supervisor: Jean Gotman (EEG, Imaging, and Epilepsy Laboratory)
    • Ph.D., Integrated Program in Neuroscience, Montreal Neurological Institute (MNI), McGill University
    • Project: Multimodal investigation of brain network hub reorganization in epilepsy and sleep
    • Currently a postdoc at the Yale University School of Medicine, Magnetic Resonance Research Center, Department of Radiology and Biomedical Imaging
  • Alexis Machado, August 2017
    • Supervisor: Christophe Grova
    • Ph.D., Department of Biomedical Engineering, McGill University
    • Project: Simultaneous recordings of EEG/fNIRS to characterize the neurovascular coupling in cortical regions at the time of spontaneous epileptic discharges detected using EEG
  • Rasheda Arman Chowdhury, March 2017
    • Supervisor: Christophe Grova
    • Ph.D., Department of Biomedical Engineering, McGill University
    • Project: MEG/EEG fusion source localization of epileptic spikes
  • Mona Maneshi, September 2010 – September 2014
    • Supervisor: Jean Gotman
    • Co-supervisor: Christophe Grova
    • Ph.D., Department of Biomedical Engineering, McGill University
    • Montreal Neurological Institute
    • Project: The application of functional connectivity in epilepsy
M.Sc. Students
  • Aude Jegou, December 2016 – May 2018
    • Supervisor: Christophe Grova
    • Co-supervisor: Thien Thanh Dang-Vu
    • Project: Automatic spindle detection from EEG
  • Atousa Asadi, September 2014 – September 2016
    • Supervisor: T. Milner McGill
    • Co-supervisor: Christophe Grova
    • Project: fMRI functional connectivity during motor learning
  • Christian Langlois Dansereau, September 2009 – May 2012
    • Supervisor: C. Grova
    • Co-Supervisor: J. Gotman MNI
    • M.Sc. Biomedical Engineering Department, McGill University
    • Project: Detection of abnormal resting state networks in epileptic patients
Summer students / Internships
  • Boutaïna Chafi, January 2021 – April 2021
    • Undergraduate summer student
    • Department of Behavioural Neuroscience, Concordia University
    • Project: Functional connectivity and brain networks during sleep using EEG-NIRS
  • Ines Djelkhir, January 2020 – April 2020
    • Intern
    • Institut supérieur d'ingénieurs de Franche-Comté (ISIFC), Biomedical Engineering, Besançon, France
    • Project: Use of Carbon Wire Loop to denoise EEG signals during simultaneous EEG-fMRI recordings: application for the detection of sleep spindles
  • Hugo Keraudran, Summer 2019 – Spring 2020
    • Master thesis, Intern
    • University of Bordeaux, Department of Life and Health Science
    • Projects: Analysis of NIRS data along different sleep cycles; Whole night EEG-NIRS to investigate epileptic activity
  • Christian Palmer, September 2019 – December 2019
    • Undergraduate summer student
    • Department of Physics, Concordia University
    • Project: Dependence of Functional Integration within Brain Networks on Circadian Rhythm
  • Amanda Spilkin, May 2016 – August 2016
    • Undergraduate summer student
    • Department of Physics, Concordia University
    • Project: Functional Near Infrared Spectroscopy (fNIRS)
  • Romain Lagneau, June 2016 – August 2016
    • Undergraduate summer student
    • Institut national des sciences appliquées, Rennes, France
    • Project: Source localization of ongoing brain activity recorded during resting state
  • Constance Fourcade, April 2016 – July 2016 (4 months)
    • Undergraduate summer student
    • École Centrale de Nantes in France, second year
    • Project title: Removal of physiological artefact components in SParsity-based Analysis of Reliable K-hubness (SPARK) in resting-state fMRI
  • Marie Theiß, April 2016 – June 2016 (3 months)
    • Graduate summer student
    • Westphalian University of Applied Sciences, M.Sc. dissertation
    • Project title: Accuracy of MRI/EEG coregistration using surface fitting approaches
  • Benoit Auclair, May 2012 – August 2012 (4 months)
    • Undergraduate summer student
    • Department of Biomedical Engineering at Polytechnique Montréal
    • Project title: Removal of physiological artefacts in Near-Infrared Spectroscopy (NIRS) using external measurements
  • Aude Petitjean, January 2013 – March 2013 (3 months)
    • Undergraduate summer student
    • BS, Institut Supérieur d’Ingénieurs de Franche-Comté (ISIFC), Department of Biomedical engineering, France
    • Project title: Evaluation of the Brainsight Near-Infrared Spectroscopy (NIRS) prototype
  • Lia Asquini, January 2012 – February 2012 (2 months)
    • Undergraduate summer student
    • Department of Biomedical Engineering at McGill University
    • Project title: EEG/NIRS during median nerve stimulation
  • Julien Beaudry, September 2011 – October 2011 (2 months)
    • Undergraduate summer student
    • Department of Biomedical Engineering at McGill University
    • Project title: Removal of dental artefact in MEG
  • Ziad Hamzeh, May 2011 – August 2011 (4 months)
    • Undergraduate summer student
    • Ecole Polytechnique Montreal
    • Project title: EEG/NIRS during finger tapping
  • Aymeric Blanc, April 2011 – July 2011 (4 months)
    • Undergraduate summer student
    • École Polytechnique France
    • Project title: Implementation of neural mass model to simulate epileptic paroxistic activity
  • Yann Potiez, August 2009 – August 2010 (1 year)
    • Research assistant
    • Department of Biomedical Engineering at McGill University
    • Project title: Realistic forward model for EEG and MEG

Multi FunkIm EEG/NIRS Laboratory

Our EEG/NIRS laboratory is equipped with a 64 channels EEG device (Stellate) and a 32×32 Brainsight NIRS device (Rogue-Research Inc.) as well as all the needed equipment to set up experiments (e-prime, Digitimer electric stimulator, TMS). The laboratory is located in the Department of Biomedical Engineering, in room 332 of the Lyman Duff Building, easily accessible from the BIC. Please contact us if interested in new collaborations involving this device.

Location: 332 Duff Medical Building, 3775 Rue University, Montréal, QC, H3A 2B4, Canada

Multi FunkIm EEG/NIRS Laboratory


  • Pellegrino G.*, Xu M., Alkuwaiti A., Porras-Bettancourt M., Lina J.M., Grova C., Kobayashi E. (2020). “Effects of Independent Component Analysis on magnetoencephalography source localization in pre- surgical frontal lobe epilepsy patients”. Frontiers in Neurology, section Epilepsy. 11: 479. doi:10.3389/fneur.2020.00479
  • Pellegrino G.*, Hedrich T.*, Aydin U.*, Porras-Bettancourt M., Lina J.M., Grova C., Kobayashi E. (2020). “Accuracy and spatial properties of distributed magnetic source imaging (dMSI) techniques in the investigation of focal epilepsy patients”. Human Brain Mapping. 41(11): 3019-3033. doi:10.1002/hbm.24994
  • Aydin* Ü.; Pellegrino* G.; Ali* O.B.K.; Abdallah* C.; Dubeau F.; Lina J.M.; Kobayashi E.; Grova C. (2020). “MEG resting state connectivity in epilepsy predicts surgical outcome at the single patient level”. Journal of Neural Engineering. 17(3): 035007. doi:10.1088/1741-2552/ab8113
  • Hedrich, T.* Aydin, Ü.* Grimault, S. Benali, H. Lina, J.M. Grova, C. (2020). “Effect of MR-related noise on the quality of electrical source imaging for simultaneous EEG-fMRI recordings”. Human Brain Mapping. Revision requested.
  • Machado, A.* Cai, Z.* Vincent, T.* Pellegrino, G.* Lina, J.M. Kobayashi, E. Grova, C. (2020). “Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy”. Scientific Report. Revision requested.
  • Cross, B. Paquola, C. Pomares, F. Perrault, A. Jegou, A.* Nguyen, A*. Aydin, U.* Bernhardt, B. Grova, C. Dang-Vu, T.T. (2020). “Trait-like gradients of functional connectivity are robust to state-dependent changes following sleep deprivation”. Neuroimage. 226: 226:117547. doi:10.1016/j.neuroimage.2020.117547
  • Vincent*, T. Machado*, A. Lina, J. M. Bherer, L. Grova, C. (2020). “B-spline deconvolution of fNIRS data to assess temporal uncertainty”. Neuroimage. Revision requested.


  • Lee KJ*, Khoo HM, Fourcade C*, Gotman J, Grova C. (2019). “Automatic removal of structured physiological noise for resting state functional connectivity MRI analysis”. Magnetic Resonance in Medicine. 58: 97-107. doi:10.1016/j.mri.2019.01.019.
  • Shin J., Rowley J., Chowdhury* R., Jolicoeur P., Klein D., Grova C., Rosa-Neto P., Kobayashi E. (2019). “Inferior longitudinal fasciculus’ role in visual processing and language comprehension: a combined MEG-DTI study”. Frontiers in Neuroscience, section Brain Imaging Methods. 13: 875. doi:10.3389/fnins.2019.00875
  • Bénar CG, Grova C, Jirsa V Lina JM. (2019). “Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study”. Journal of Computational Neuroscience. Jul 11: 1-11. doi:10.1007/s10827-019-00721-9
  • Jegou A.*, Schabus M., Gosseries O., Dahmen B., Albouy G., Desseilles M., Sterpenich V., Phillips C., Maquet M., Grova C., Dang-Vu T.T. (2019). “Cortical reactivations during sleep spindles following declarative learning”. Neuroimage. 195: 104-112. doi:10.1016/j.neuroimage.2019.03.051


  • A Machado, Z Cai, G Pellegrino, O Marcotte, T Vincent, JM Lina, E Kobayashi, C Grova, “Optimal positioning of optodes on the scalp for personalized functional near-infrared spectroscopy investigations”, Journal of neuroscience methods, Journal of Neuroscience Methods, vol. 209, pp. 91–108, November 2018. doi:10.1016/j.jneumeth.2018.08.006
  • Kangjoo Lee, Hui Ming Khoo, Jean-Marc Lina, François Dubeau, Jean Gotman and Christophe Grova, “Disruption, emergence and lateralization of brain network hubs in mesial temporal lobe epilepsy”, Neuroimage: Clinical, vol. 20, pp. 71–84, June 2018. doi:10.1016/j.nicl.2018.06.029
  • Rasheda Arman Chowdhury, Giovanni Pellegrino, Ümit Aydin, Jean‐marc Lina, François Dubeau, Eliane Kobayashi, Christophe Grova, “Reproducibility of EEG‐MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy”, Human Brain Mapping 39, 880–901, 2018. doi:10.1002/hbm.23889
  • Pellegrino G., Hedrich T., Chowdhury R., Hall J., Dubeau F., Lina J.M., Kobayashi E,. Grova C., “Clinical yield of magnetoencephalography distributed source imaging in epilepsy”, Human Brain Mapping 39, 218–231, 2018. doi:10.1002/hbm.23837


  • T Hedrich, G Pellegrino, E Kobayashi, JM Lina, C Grova, “Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG”, Neuroimage, June 2017. doi:10.1016/j.neuroimage.2017.06.022
  • Ü Aydin, S Rampp, A Wollbrink, H Kugel, J-H Cho, TR Knösche, C Grova, J Wellmer, CH Wolters, Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study, Brain Topography (2017) doi:10.1007/s10548-017-0568-9
  • Vasta, R. et al. “The movement time analyser task investigated with functional near infrared spectroscopy: an ecologic approach for measuring hemodynamic response in the motor system”. Aging Clin Exp Res 29, 311–318 (2017). doi:10.1007/s40520-016-0566-x


  • Maneshi M, Vahdat S, Gotman J and Grova C (2016). Validation of Shared and Specific Independent Component Analysis (SSICA) for between-group comparisons in fMRI. Front. Neurosci. 10:417. doi:10.3389/fnins.2016.00417
  • R.A. Chowdhury, I. Merlet, G. Birot, E. Kobayashi, A. Nica, A. Biraben, F. Wendling, J.M. Lina, L. Albera, C. Grova, “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, August 2016. doi:10.1016/j.neuroimage.2016.08.044
  • Roberta Vasta, Antonio Cerasa, Vera Gramigna, Antonio Augimeri, Giuseppe Olivadese, Giovanni Pellegrino, Iolanda Martino, Alexis Machado, Zhengchen Cai, Manuela Caracciolo, Christophe Grova, Aldo Quattrone, “The movement time analyser task investigated with functional near infrared spectroscopy: an ecologic approach for measuring hemodynamic response in the motor system”, Aging Clinical and Experimental Research (2016), doi:10.1007/s40520-016-0566-x
  • Giovanni Pellegrino, Tanguy Hedrich, Rasheda Chowdhury, Jeffery A Hall, Jean‐Marc Lina, Francois Dubeau, Eliane Kobayashi, Christophe Grova, “Source localization of the seizure onset zone from ictal EEG/MEG data”, Hum. Brain Mapp. (2016) doi:10.1002/hbm.23191
  • Kangjoo Lee, Jean-Marc Lina, Jean Gotman and Christophe Grova, “SPARK: Sparsity-based analysis of reliable k-hubness and overlapping network structure in brain functional connectivity”, Neuroimage, vol. 134, pp. 434–449, April 2016. doi:10.1016/j.neuroimage.2016.03.049
  • Christophe Grova, Maria Aiguabella, Rina Zelmann, Jean‐Marc Lina, Jeffery A Hall, Eliane Kobayashi “Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy”, Human Brain Mapping, Volume 37, Issue 5, pages 1661–1683, May 2016. doi:10.1002/hbm.23127
  • Nicolás von Ellenrieder, Giovanni Pellegrino, Tanguy Hedrich, Jean Gotman, Jean-Marc Lina, Christophe Grova, Eliane Kobayashi  “Detection and Magnetic Source Imaging of Fast Oscillations (40–160 Hz) Recorded with Magnetoencephalography in Focal Epilepsy Patients”, Brain Topography March 2016, Volume 29, Issue 2, pp 218–231. doi:10.1007/s10548-016-0471-9
  • Giovanni Pellegrino, Alexis Machado, Nicolas von Ellenrieder, Satsuki Watanabe, Jeffery A Hall, Jean-Marc Lina, Eliane Kobayashi, Christophe Grova “Hemodynamic response to Interictal Epileptiform Discharges addressed by personalized EEG-fNIRS recordings”, Front. Neurotic., 2016 doi:10.3389/fnins.2016.00102


  • Chowdhury R. A., Zerouali Y., Hedrich T., Heers M., Kobayashi E., Lina J.M., Grova C. “MEG–EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy”, Brain Topography, 2015 May 28, doi:10.1007/s10548-015-0437-3
  • Heers M., Chowdhury R.A., Hedrich T., Dubeau F., Hall J. A., Lina J.M., Grova C., Kobayashi E., “Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy”, Brain Topography, 2015 Jan 22; doi:10.1007/s10548-014-0423-1












  • Jannin P., Grova C., and Gibaud B. Fusion de données : Une revue méthodologique basée sur le contexte clinique, ITBM-RBM Innovation et technologie en biologie et médecine, 22(4) pp. 196–215 (2001)


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