multimodal recordings and signal processing in epilepsy · mc-ph, info f bartolomei, pu-ph a...

Institut de Neurosciences des Systèmes

Christian-G. Bénar

Institut de Neuroscience des Systèmes, Marseille

[email protected]

Multimodal recordings and signal processing in epilepsy

Séminaire GIPSA LAB, 23 Mars 2017


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The « Institut de Neurosciences des Systèmes »

Theoretical Neuroscience Group V Jirsa

Patho-Physiology of Networks C Bernard

Dynamics Cognitive processes D Schon

Dynamical Brain Mapping C Bénar

Clinical Neurophysiology F Bartolomei

Dir. V Jirsa, co-dir. P Chauvel


The Marseille MEG Platform

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http://meg.univ-amu.fr

- Within the clinical neurophysiology department

- 4D system (248 magnetometers)

- Open platform (neuroscience)

- Day hospital (2 patients a week)

JM Badier Eng AMU

S Chen Eng Inserm

B Colombet Tech AMU

- Member of France Life Imaging

- Part of 2 « Federation hospitalo universitaire » (Epinext, Dhune)

- Part of Labex BLRI, convergence project ILCB; collaboration CREx; Fédération sciences du cerveau et de la cognition; collaborations INT, LNC, LPC;

MEG sensors


Dynamap/MEG team

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Dynamap

JM Badier CG Bénar S Chen B Colombet

B Giusiano, MC-PH, Info

F Bartolomei, PU-PH

A McGonigal, PH

R Carron, MC-PH

S Medina, Eng, PhD

N Roehri, Eng, PhD

F Pizzo, MD, PhD

S Lagarde, MD, PhD

J Régis, PU-PH

I Lambert, MD, PhD


Context: presurgical evaluation of epilepsy

• 0.5 to 1% of population has epilepsy

• ~30% are pharmacoresistant

→ can be considered for surgery

• Aim of presurgical evaluation is to delineate the tissues to be resected in order to stop seizures

SEEG

EEG

Phase 1: non-invasive

Phase 2: invasive

Surgery


Theme: Multimodal brain mapping

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MEG fMRI

Intracerebral EEG

Axis 1: Links between non-invasive modalities

Axis 2: Compare non invasive/ invasive

EEG

Cognition

Epilepsy

Surgery

Dynamap

Use of simultaneous recordings: EEG-MEG, EEG-fMRI, MEG-SEEG


Neurovascular coupling

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Spike sorting

Parametric GLM => higher correlation with putative interneurons Cpnsistent with coupling with high gamma activity ( Logothetis et al 2001)

PC INT

Multimodal recordings in a animal model of epilepsy; Collab. with P Quilichini, A Ivanov, A Ghestem, C Bernard (Physionet), I Vanzetta (INT); F Wendling, S Blanchard LTSI, O David J Warnking GIN, H Benali Multimodel ANR project

Saillet et al J Neurophysiol 2016

MEG epileptic discharge

Anywave software meg.univ-amu.fr 8

Comparison MEG/EEG

SEEG

EEG MEG

Gavaret et al Brain Topogr 2014 MEG reveals bilateral sources confirmed by SEEG 9

SEEG shows complex networks at seizure onset

Bartolomei et al 2001

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Example of SEEG network dynamics

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Schwartz et al Epilepsy Res 2011

The epileptogenicity index

EI is higher for -Smaller time of involvement in seizure

-Higher ratio of energy high freq/low freq

Bartolomei et al 2008 12


Overview

1. High frequency oscillations on SEEG

2. Interictal/preictal networks in SEEG and MEG

3. Simultaneous MEG/SEEG recordings

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1. SEEG HIGH FREQUENCY ACTIVITIES

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Rationale

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Urrestarazu et al Brain 2007 Bénar et al Clin Neurophysiol 2010 See also Jmail et al 2011, 2016

-High frequency activity are a marker of epilepsy - hard to visualize + filtering can produce ringing (« false ripples ») - time frequency representation need to balance energy across frequencies

Projet ANR TechSan ‘FORCE’ (PI P. Kahane), collaboration GIN, LTSI Rennes (F Wendling), CRN Lyon (JP Lachaux), Micromed company


The « 1/f » issue: the zHO method

17 Roehri et al IEEE TBME 2016


Time-frequency detectors

18 Roehri et al IEEE TBME 2016; see also Jmail et al 2017

-30 patients studied (2930 contacts: 100.5 [89-109] per patient) -5 min NREM slow wave sleep -quantify Seizure Onset Zone with Epileptogenicity index (EI) -quantify interictal period with spike, HFO and HFO co-occuring with spikes rates -partial ROC analysis to determine which markers better predicts the EZ

Application to patients

Roehri et al. in prep 19


2. INTERICTAL/PREICTAL NETWORKS

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A) PREICTAL NETWORKS IN SEEG

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Preictal SEEG

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Courtens et al Brain Connect 2016

h2 Pijn et al 1989, Wendling et al 2001

Beginning of seizure = period of decrease of connectivity, Wendling et al 2003 → what about the preictal phase ?


Networks across frequency bands

23 Courtens et al Brain connect 2016


B) INTERICTAL NETWORKS IN MEG

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MEG ICA networks

Malinowska et al Hum Brain Mapp 2014 25

Co-occurrence testing

Cf Bourien et al 2005 for co-occurrence in SEEG 26

• significant direction (pairs of spikes)

• spike co-occurrences (significance with non-parametric technique)

Malinowska et al Hum Brain Mapp 2014

Source localisation on components

ICA1

ICA7

ICA6

ICA1

ICA6

ICA7

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L

MEG

SEEG

Malinowska et al, Hum Brain Mapp 2014

MEG ICA networks

-> very good concordance between MEG and SEEG leaders 28

L

MEG

SEEG

L

MEG ICA networks

Malinowska et al, Hum Brain Mapp 2014

-> only part of network can be retrieved 29

Limitations of separate recordings

• Separate MEEG/SEEG recordings may not

record the exact same activity (fluctuations

across brain states)

• Separate recordings do not allow using single

trial fluctuations as source of information

(as in simultaneous EEG-fMRI)

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=> The next step is to record them simultaneously !


3. SIMULTANEOUS RECORDINGS

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EEG-MEG-SEG: feasibility

Dubarry et al, NIMG 2014

23 EEG; 72 SEEG; 248 MEG Sampling rate 2035 Hz

32 Limitation in number of SEEG channels

Evoked activity

Dubarry et al, NIMG 2014 33

Source localization (Brainstorm)


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Single trial analysis


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Noise issues

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Observation of both high and low frequency noise

Improving the system

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Fixation of cables + MR-compatible 256 channels amplifier

Badier et al under review

Example: Sensitivity

Bénar et al GRETSI 2015, Badier et al under review 38

Visibility of deep mesial structures? (1)

39 PhD work of Francesca Pizzo

H

A3-A4

B5-B6

Higher coherence with contacts in amygdala

Comp. 3

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Visibility of deep mesial structures? (2)

Francesca Pizzo

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Large scale network

Francesca Pizzo

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Local correlation

Francesca Pizzo


Application (2): Validation of signal processing

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Dynamap2

MEG-ICA

SEEG

S Medina, N Roehri, AS Dubarry, M Woodman

beamformer surface

depth

Application (3): Clinical Interest

Gavaret et al Epilepsy Res 2016

SEEG-triggered spike average permit to localise a region outside of SEEG implantation 44


Translation to clinical research: the AnyWave software

B Colombet JM Badier M Woodman S Medina N Roehri

GARDEL: SEEG semi-automatic labelling

High frequency oscillations

http://meg.univ-amu.fr/AnyWave/download.html

Dynamap1

Epileptogenicity index

Independent component analysis

VIBRATIONS ANR Project

3D Viewer

Colombet et al J Neurosci Meth 2015

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Multiplatform, modular




Acknowledgements

Postdocs, students N Jmail AS Dubarry M Woodman U Malinowska S Courtens J Wirsich N Roehri S Medina F Pizzo

Engineers JM Badier S Chen B Colombet P Marquis Neuroscientists FX Alario C Liegeois Chauvel

Neurologists F Bartolomei P Chauvel M Gavaret A Trébuchon da Fonseca Neurosurgeons J Régis R Carron

[email protected]

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PhD position in MEG signal processing for foreign student!!!

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