• Functional reorganization in epilepsy I. Task based
II. Resting state III. Structural correlates and data fusion 3
Project 1: Task-based EEG-fMRI
• Objective: Spatio-temporal characterization of networks • Healthy controls subjects (n=14), right temporal lobe epilepsy patients (n=7) • Face recognition task: famous vs unfamiliar
4
Noise in the Scanner Scanner Gradient Artifact - Artifact Template Subtraction - Independent Component Analysis (eye blink removal) - Frequency Filtering - Averaging Pulse Artifact (balistocardiogram)
Goal: extract single trial amplitudes Problem: Noise Solution ICA New Problem: ICA components on a individual basis hardly comparable (switched signs, different nose levels)
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Method Group ICA / EEGIFT Toolbox
[Eichele et al., 2011, Computational Intelligence and Neuroscience]
10
Method Group ICA
PCA
PCA
ICA
Reconstruction
PCA Data Aggregation
11
Group ICA Analysis Controls
• PCA/ICA: 64 channels reduced to 20 components • 3 components of interest • Single-trial Zscores at component peaks are extracted
12
EEG-informed GLM
Strategy: analysis of fMRI signals informed by EEG features 13
EEG-fMRI workflow Define Subjects, Groups and parameters
Strategy: analysis of fMRI signals informed by EEG features
[Wirsich et al. 2014, NeuroImage] 15
Application Epilepsy
Ongoing study: group analysis of epileptic patients using the same experiment
• How does epilepsy change the observed cascade? • 7 patients with right temporal lobe epilepsy (rTLE) 16
Results rTLE ERP components obtained in the group (Controls + rTLE)
[Wirsich et al., Brainmodes London 2014]
17
Results rTLE EEG informed fMRI during face recognition in rTLE
Controls
N170 related fMRI activity pattern present decreases of N400 and P600 related fMRI activities rTLE
[Wirsich et al., Brainmodes London 2014]
18
Limitations – Work in Progress
• Influence of ERP changes not covered by group ICA Controls:
rTLE:
• Uncontrolled Covariables: -Response time -Epilepsy Onset 19
Resting State EEG-fMRI
Project 2: Resting State EEG-fMRI
• Question: how are resting state networks modified in epilepsy ? • Methods: measure of correlation across regions • Low frequency BOLD fluctuations • patients vs controls 20
Functional Connectivity
Parcellation
ROI timeseries
Correlation
21
Results: Right Temporal Lobe Epilepsy vs Controls
Method: Network Based Statistics [Zalesky, 2010, NeuroImage]: Multiple Comparison Correction by size of the network
=> Hyperconnectivity in rTLE patients with largest differences in frontal and occipital regions Wirsich(WIP) 22
Current directions: Measure of vigilance during scanning
Do alterations impact resting state EEG-fMRI measurements of subjects? 23
Methods Sleep Staging
• 11 healthy subjects • Context : Ancillary study of Pharmacog (IMI) • 5 x 2 resting state EEG-fMRI sessions (normal/24h sleep deprived) • Simultaneous EEG makes sleep staging during fMRI possible
24
Methods sleep staging: GLM
Y
Deprived?
Sleep Stage
No Dep
Dep
Aw
S1
S2
S3
1
0
150
50
0
0
0
1
50
50
30
20
Subj (…)
(…)
25
Results Sleep Deprivation
Sleep Stage S1 vs Awake
Sleep Stage S2 vs Awake
Model to correct resting state for sleep effects
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Relationships with structural connectivity
Project 3: Structural correlates and data fusion DTI
fMRI
EEG
Method
fiber tracking
BOLD correlation
ICA alpha power Correlation
Resolution
512 nodes
512 nodes
~30 nodes
Temporal dynamics
static
dynamic 27
Conclusion
Epilepsy
Paradigm
EEG
fMRI
MRI/Anatomical Atlas
DTI
«pipelining»
??? EEG connectivity
??? fMRI connectivity
Structural connectivity
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Collaborators Marseille CRMBM/CEMEREM Maxime Guye (directeur de thèse) Jean-Philippe Ranjeva Ben Ridley Arnaud le Troter Sylviane Confort-Gouny Elizabeth Soulier …
INS Christian Bénar (codirecteur de thèse) Viktor Jirsa Matthieu Golos Timothee Proix … Pharmacog Mark Rey Laura Lanteaume Joelle Micaleff Olivier Blin
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