(Dynamical Brain Mapping Group)

The general objective of the Dynamap team is to develop signal processing strategies for characterizing the spatio-temporal dynamics of brain networks, for both physiological and pathological activity.

With this in view, the first strategy of the team is to combine the strength of different modalities such as EEG, MEG, fMRI, with particular emphasis on simultaneous recordings (EEG-MEG, EEG-fMRI) that allow recording the exact same activity under different points of view. The second strategy is to take the opportunity of intracerebral recordings performed in patients with epilepsy for providing a ‘ground truth’ to which non-invasive methods can be confronted.

In basic neuroscience, one application of our work is to provide methodological advances for the users of the MEG platform. In clinics, our tools are intended to improve delineation of the epileptogenic zone for presurgical planning of patients with epilepsy. A particular effort is made towards translation of our work to clinicians and researchers through the multi-platform Anywave software, which architecture specifically aims at allowing fast implementation of algorithms to the end users.




Christian BÉNAR


PHONE: +33 4 91 38 55 62


I graduated from Ecole Supérieur d'Electricité (Supélec) in 1994. I then spent one year as an engineer at the Hospital Saint-Anne in Toulon (with Franck Vidal), and two years as a programmer at Stellate Systems (Montréal). I did my PhD under the supervision of Jean Gotman at the Montreal Neurological Institute (MNI). Back to France in 2004, my postdocs were in Marseille (fMRI Center, with Jean-Luc Anton) and in Sophia Antipolis (Maureen Clerc and Theodore Papadopoulo). 
I was appointed researcher INSERM ("chargé de recherche 1ère classe" ) in 2006. Since january 2012, I am the leader of the "Dynamical Brain Mapping Group” here at INS. Since September 2014, I am scientific head of the Marseille MEG platform. 
My research interest is signal processing applied to brain signals (fMRI, EEG, MEG), in order to characterize the spatio-temporal dynamics of networks in cognition and disease. Currently, our team is working on simultaneous recordings of surface (EEG, MEG) and depth (SEEG) signals.
For more information, see my recent publications (with reprints) and projects on Research Gate, my page on the MEG wiki (with publication list) and my CV.




  1. Lambert I, Roehri N, Giusiano B, Carron R, Wendling F, Benar C, Bartolomei F. Brain regions and epileptogenicity influence epileptic interictal spike production and propagation during NREM sleep in comparison with wakefulness. Epilepsia. 2018 Jan;59(1):235-243. doi: 10.1111/epi.13958.

  2. Wirsich J, Rey M, Guye M, Bénar C, Lanteaume L, Ridley B, Confort-Gouny S, Cassé-Perrot C, Soulier E, Viout P, Rouby F, Lefebvre MN, Audebert C, Truillet R, Jouve E, Payoux P, Bartrés-Faz D, Bordet R, Richardson JC, Babiloni C, Rossini PM, Micallef J, Blin O, Ranjeva JP; Pharmacog Consortium. Brain Networks are Independently Modulated by Donepezil, Sleep, and Sleep Deprivation. Brain Topogr. 2018 May;31(3):380-391. doi: 10.1007/s10548-017-0608-5.

  3. Bartolomei F, Lagarde S, Lambert I, Trébuchon A, Villalon SM, McGonigal A, Benar CG. Brain connectivity changes during ictal aggression (a strangulation attempt). Epileptic Disord. 2017 Sep 1;19(3):367-373. doi: 10.1684/epd.2017.0925.

  4. Bartolomei F, Lagarde S, Wendling F, McGonigal A, Jirsa V, Guye M, Bénar C. Defining epileptogenic networks: Contribution of SEEG and signal analysis. Epilepsia. 2017 Jul;58(7):1131-1147. doi: 10.1111/epi.13791. Epub 2017 May 20. Review.

  5. Bartolomei F, Lagarde S, Médina Villalon S, McGonigal A, Benar CG. The "Proust phenomenon": Odor-evoked autobiographical memories triggered by direct amygdala stimulation in human. Cortex. 2017 May;90:173-175. doi: 10.1016/j.cortex.2016.12.005. Epub 2016 Dec 18.




Follow our projects in real time and get reprints on Research Gate

Simultaneous recordings of MEG, EEG and SEEG

Most previous work on the comparison of MEG, EEG and intracerebral EEG was performed on separate recordings. However, this is far from being optimal. Indeed, only simultaneous recordings of surface and depth activity permit to investigate the exact same activity, independently of spontaneous fluctuations that can occur from a session to another (depending on subject state, medication etc). Moreover, simultaneous recordings allow using interevent fluctuations as a source of information on the link between signals, as was done on simultaneous EEG-fMRI.

We have shown for the first time the feasibility of trimodal simultaneous recordings: EEG, MEG and SEEG (Dubarry et al., 2014). Technical developments have been proposed in (Badier et al., 2017) and an application to presurgical mapping in (Gavaret et al., 2016).


Activity evoked by visual stimulation (checkerboard) on MEG, EEG and intracerebral EEG (SEEG) recorded simultaneously (Dubarry et al 2014).


Time frequency methods for high-frequency activity

High frequency oscillations (HFOs) have been proposed as a new marker for delineating epileptic tissues. One difficulty in characterizing these activity is that they are of much smaller amplitude than classical spike markers. We have proposed a new method to whiten the SEEG signals in order to better visualize and detect HFOs (Roehri et al., 2016). In a latter publication, we have shown that it may be useful to combine spike and HFO information instead of considering them separately (Roehri et al., 2018).

Effect of whitening on SEEG traces (see Roehri et al 2016).

Effect of whitening on SEEG traces (see Roehri et al 2016).


The Anywave software

Within the DynaMap team, we have developed a software for visualizing electrophysiological traces (main developer Bruno Colombet). This software is multiplatform and modular, and in particular, permits easy addition of plugins in Python or Matlab (Colombet et al., 2015). In addition, our software Gardel permits to register and segment SEEG electrodes (Medina Villalon et al., 2018). Anywave software is available for download here. at .

Example of ICA decomposition in Anywave (MEG traces).

Example of ICA decomposition in Anywave (MEG traces).