Performing electrophysiological measurements in humans inside Magnetic Resonance Imaging scanners; applications in Epilepsy research and other areas by Louis Lemieux

1. Performing electrophysiological
measurements in humans inside Magnetic
Resonance Imaging scanners; applications in
Epilepsy research and other areas
Louis Lemieux
Department of Clinical and Experimental Epilepsy
UCL Institute of Neurology, Queen Square, London
&
MRI Unit, Epilepsy Society
Chalfont St Peter, Buckinghamshire
UK

2. Lemieux – ACES / Europe Dublin 2015
Outline
• Epilepsy
• Multimodal neuroimaging in humans
– EEG and functional MRI (fMRI)
– Mapping epileptic events using scalp EEG-fMRI
• Going deeper: intracranial EEG-fMRI
– Technique implementation
– An epileptic seizure
• Conclusions

3. Lemieux – ACES / Europe Dublin 2015
Epilepsy
• Epilepsy is the most common serious chronic neurological
condition affecting all ages
– 50 million people affected in the world
– Economic costs (~€20 billion/year for Europe).
• 30% of all people with epilepsy have seizures that do not respond to
medical treatment, leading to:
– Cognitive decline
– Poor quality of life
– Significantly increased mortality
– High societal costs
• Need for improved treatment
– Surgery
– Drug delivery
• Need for improved localisation of the epileptogenic areas

4. Lemieux – ACES / Europe Dublin 2015
• fMRI
– Allows tomographic visualisation of haemodynamic changes associated with
brain activity
– Has better temporal resolution than PET (…for epileptic spikes)
– Is non-invasive (BOLD)
• EEG
– Important observable of brain activity in humans
– Reflects neuronal signal generation and synchronisation
– Important clinical tool in epilepsy (epileptic spikes, seizures, etc)
– Non-invasive (scalp) & cheap
Basic principles: EEG & fMRI

5. Lemieux – ACES / Europe Dublin 2015
LF= 0.5 Hz HF= 30 Hz
1 sec.
25 uV
10:36:33 10:36:34 10:36:35 10:36:36
Fp2-F8
F8-T4
T4-T6
T6-O2
Fp1-F7
F7-T3
T3-T5
T5-O1
ECG1-ECG2
Epileptic spikes
• Spatially linked to the epileptic focus
• Brief (<100ms), unpredictable
• Sub-clinical: can only be seen on EEG
• Epileptic spike source localisation
– Inverse problem of EEG…
– Can fMRI better localise epileptic spike
generators?
– Clinical utility?

6. Lemieux – ACES / Europe Dublin 2015
EEG-fMRI in epilepsy
Data acquisition strategy
Subject at rest
Simultaneous EEG-MRI
• fMRI:
− Echo-planar imaging (EPI) fMRI
scanning sequences
− Whole-brain coverage
• EEG:
− 64-channel cap on scalp
− MR-compatible amplifier and digitiser
− Digital signal transmitted to recording
laptop outside the scanner room

7. Lemieux – ACES / Europe Dublin 2015
EEG-fMRI of epileptic spikes
Continuous EEG and fMRI:
EEG-based
GLM
Spike-related BOLD
[Krakow et al, 1999; Lemieux et al, 2001]
1 sec.
25 uV
10:36:33 10:36:34 10:36:35 10:36:36
Fp2-F8
F8-T4
T4-T6
T6-O2
Fp1-F7
F7-T3
T3-T5
T5-O1
ECG1-ECG2

8. Lemieux – ACES / Europe Dublin 2015
Fp1-Pz
F7 – Pz
T3 – Pz
T5 – Pz
O1 – Pz
Fp2 – Pz
F8 – Pz
T4 – Pz
T6 – Pz
O2 – Pz
Fp1 – F7
F7 – T3
T3 – T5
T5 – O1
Fp2 – F8
F8 – T4
T4 – T6
T6 – O2
ECG
OSC
1 Second LF = 0.5 Hz HF = 45 Hz
50uV
The intra-MRI EEG artefact problem

9. Lemieux – ACES / Europe Dublin 2015
Fp1-Pz
F7 – Pz
T3 – Pz
T5 – Pz
O1 – Pz
Fp2 – Pz
F8 – Pz
T4 – Pz
T6 – Pz
O2 – Pz
Fp1 – F7
F7 – T3
T3 – T5
T5 – O1
Fp2 – F8
F8 – T4
T4 – T6
T6 – O2
ECG
OSC
1 Second LF = 0.5 Hz HF = 45 Hz
50uV
[Allen et al, 2000]
The intra-MRI EEG artefact problem

10. Lemieux – ACES / Europe Dublin 2015
Fp1-Pz
F7 – Pz
T3 – Pz
T5 – Pz
O1 – Pz
Fp2 – Pz
F8 – Pz
T4 – Pz
T6 – Pz
O2 – Pz
Fp1 – F7
F7 – T3
T3 – T5
T5 – O1
Fp2 – F8
F8 – T4
T4 – T6
T6 – O2
ECG
OSC
1 Second LF = 0.5 Hz HF = 45 Hz
50uV
[Allen et al, 1999]
The intra-MRI EEG artefact problem

11. Lemieux – ACES / Europe Dublin 2015
Clinical relevance: EEG-fMRI of epileptic spikes in
Focal Cortical Dysplasia
ANN NEUROL 2011;70:822–837
Conclusion:
Scalp EEG-fMRI of epileptic spikes may predict less promising
surgical cases and therefore avoid unnecessary invasive interventions

12. Lemieux – ACES / Europe Dublin 2015
icEEG: Subdural grids and depth electrodes
• Surgically placed on cortex
• Sampling similar to high-density scalp EEG
• Used to map epileptogenic tissue in relation to eloquent
cortex
• 6x8 array of 3mm diameter Pt-Ir disk contacts
[Fried et al, 1999]
• Surgically inserted within brain
• Used to detect epileptogenicity and propagation in deep
cortex/lesions
• Sensitivity profile very different from scalp EEG and grids:
‘tunnel vision’ [see Cosandier et al 2007; Church et al, 1985]
• ‘Spencer probe’ commercial design
• Pt-Ir cylindrical contacts & Ni-Cr terminations and wires
contained in polyurethane

13. Lemieux – ACES / Europe Dublin 2015
[Carmichael et al, 2009; 2012]
•Health hazards
•RF-induced heating
•Induced voltages (stimulation)
•Factors considered:
•Field strength: 1.5T and 3T
•RF transmit coil type: head and body
•Electrodes: depths and grids
•EEG wires
•Geometry and placement
•Length
•Termination
Simultaneous icEEG-fMRI:
Safety tests in phantoms

14. Lemieux – ACES / Europe Dublin 2015
[Carmichael et al, 2009, 2012]
•RF-induced heating greatest health risk
•Excessive heating observed
•Body coil
•3T
•But for certain realistic conditions:
Max ∆T = 0.9ºC (@1.5T, SAR=2.4W/Kg,
6mins)
icEEG-fMRI possible without
excessive additional health risk
under certain conditions
Site-specific assessment necessary
Intra-cranial EEG-fMRI safety study results:
Heating tests

15. Lemieux – ACES / Europe Dublin 2015
1) Use likely safest regime
2) Strict protocol:
- 1.5T Siemens Avanto / head (quad.) Tx/Rx coil
- 90cm cables with 10cm fold along scanner central Z xis
- Foam insert designed for exact positioning
- Position EEG system and cables reproducibly
- Low SAR sequences:
- T1 volume, gradient echo EPI [TE=40ms], B0 map
- 3-4% of 3.2 W/Kg
- max duration 10 minutes
3) Close monitoring and documenting of patient responses,
images, appearance of brain surface, histology
icEEG-fMRI: Implementation

16. Lemieux – ACES / Europe Dublin 2015
icEEG-fMRI image quality:
EPI signal degradation around electrodes
[Carmichael et al, 2012]

17. Lemieux – ACES / Europe Dublin 2015
icEEG-fMRI image quality:
EPI signal degradation around electrodes
[Carmichael et al, 2012]

18. Lemieux – ACES / Europe Dublin 2015
Feasibility study case report:
• Seizures: R hand stiffening
• MRI normal
• No spikes during scalp EEG-fMRI
• icEEG implantation: grids and strips over
left frontal lobe
• Two 10-minute resting-state icEEG-fMRI
sessions:
•100’s of L fronto-central spikes
L
icEEG-fMRI
MEG: IED onset
L
L
MEG: IED propagation
L
L
irritative zone
Demonstration of spike-correlated icEEG-fMRI
[Vulliemoz/Carmichael et al, 2010]

19. Lemieux – ACES / Europe Dublin 2015
Conclusions
EEG-fMRI allows:
• Haemodynamic mapping of events with specific EEG features
• ‘Extends’ EEG: whole-brain coverage, source complexity-independent
Intracranial EEG-fMRI:
• Fascinating, complex data
• Exquisite electrophysiological sensitivity
• Image data quality is an issue:
− Electrode composition is suboptimal for MR imaging
− Clinical impact: Limits ability to locate the electrodes in relation to the
anatomy
− Research impact: Reduces the amount of fMRI signal available for
analysis

20. Lemieux – ACES / Europe Dublin 2015
Team / collaborators / funding
David W. Carmichael
Umair Chaudhary
Ana-Carolina Coan (Campinas)
Alessio De Ciantis (Firenze)
Beate Diehl
John S. Duncan
Madeline Grade
Marco Leite
Andrew McEvoy
Teresa Murta
Irene Pappalardo
Suejen Perani (King’s)
Sofia Markoula (Ioannina)
Roman Rodionov
Catherine Scott
Niraj Sharma
Rachel C. Thornton
André van Graan
Anna Vaudano (Modena)
Matthew C. Walker
Britta Wandschneider
+ The Clinical Neurophysiology and
Neuroradiology teams at the National Hospital
for Neurology and Neurosurgery, Queen Square
K Friston (UCL)
M Guye / F Bartolomei / P Chauvel / JP Ranjeva (Marseille)
S Vulliemoz / C Michel (Geneva)
P Figueiredo (Lisbon)
M Papadopoulou / D Marinazzo (Ghent)
Radhakrishnan A / Chandrasekharan K / Sreedharan S
(Trivandrum)
R Quian Quiroga / C Pedreira (Leicester)
V Kokkinos (Thessaloniki)
S Meletti (Modena)
F Cendes (Campinas)
K Mullinger / R Bowtell (Nottingham)
KR Muller / V Samek / D Blythe (Berlin)
H Laufs (Frankfurt)
J Daunizeau (Paris)
K Whittingstall (Sherbrooke)
E Formisano / F De Martino (Maastricht)
M Torkmani Azar (Konya)
Funding:
Action Medical Research
Brain Research Trust / James Tudor Foundation
NIHR (UK Department of Health)
Medical Research Council
Support in kind:
Brain Products

21. Thank you

22. Lemieux – ACES / Europe Dublin 2015
The problem of presurgical test validation
• Validation of localisation tests in epilepsy is fundamentally limited
• Gold standard is not golden:
• Surgical resection localisation and outcome data
• Ictiogenic ‘source’ must be considered a network in most patients a
priori
• Elements of a possible solution
• Improved characterisation / Modelling
• Functional connectivity networks
• Effective connectivity (“DCM”)
• Validation / Interventions:
• Surgical: connection disruptions (functional connectivity sufficient?)
• More sophisticated: stimulation (effective connectivity necessary?)

23. Lemieux – ACES / Europe Dublin 2015
What else the EEG-fMRI can tell us?
Psychophysiologial interaction (PPI)
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8
-1.5
-1
-0.5
0
0.5
1
1.5
LFdl activity
LFpresponse
Psychophysiologic Interaction
IED
seed ROI
Vaudano et al., 2013-Frontiers in Neurology
2. Connectivity analysis

24. Lemieux – ACES / Europe Dublin 2015
Interictal EEG

25. Intracranial EEG-fMRI:
Incidental Studies of Other Brain
Phenomena in Humans

26. Lemieux – ACES / Europe Dublin 2015
EEG oscillations: their functional roles and brain state
correlates
Classical EEG oscillation bands
• Delta (0.5-3.5Hz):
– deep sleep, learning, motivational processes and reward system
• Theta (4-7 Hz):
– working memory, emotional arousal and fear conditioning
• Alpha (8-12 Hz):
– cortical operations during the awake resting-state in the absence of
sensory inputs, disengagement of task-irrelevant brain areas, working
memory and short-term-memory retention
– Rolandic Alpha / ‘Mu rhythm’ (9-11 Hz)
• Suppressed during task
• Beta (13-30 Hz):
– Vigilence and attention
– Rolandic Beta
• Linked to motor functions
• Inhibited by motor imagery
• Gamma (> 30 Hz):
– feature integration, attention, etc

27. Lemieux – ACES / Europe Dublin 2015
Rolandic Alpha (‘Mu’) and Beta on Scalp EEG
• What are their respective roles?
• They fluctuate similarly but are not perfectly correlated
• Based on MEG, their spatial distributions seem to differ:
• Rolandic Alpha: post-central (primary somatosensory)
• Rolandic Beta: pre-central (primary motor)
• fMRI-based localisation?...

28. Lemieux – ACES / Europe Dublin 2015
fMRI of Rolandic Alpha and Beta on scalp EEG: Ritter
et al, 2009
• Bilateral hand motor task
• 15 healthy subjects
• Two main fMRI models:
• Band/channel
• Blind source separation
Beta – BOLD correlation:
Conclusions
Complex data quality correction and modelling methodology
BOLD of Rolandic alpha and beta rhythms differ: postcentral gyrus
(SI) for alpha and precentral gyrus (MI) for beta;
Negative Rolandic alpha and beta rhythms - BOLD correlation in the
pericentral cortex

29. Lemieux – ACES / Europe Dublin 2015
BOLD Mapping of Rolandic Alpha and Beta
oscillations on ECoG
HRF
Band
Averaging
(around
peak)
0.5mV
M1
S
1
M1
S1
Identification of
patient-specific
band peak
Spatial PCA:
1st PC
[Perani et al, in preparation]
Grid placed over left motor cortex
icEEG-fMRI:
• Rest (epileptic activity mapping)
• Alternating finger tapping task (no rest)
For each band:
Alpha and Beta

30. Lemieux – ACES / Europe Dublin 2015
L
L
L
L
[Perani et al, in preparation]
BOLD Mapping of Rolandic Alpha and Beta on ECoG:
Task data
BOLD increases
BOLD decreases BOLD decreases
BOLD increases
Alpha (Mu) Beta

31. Lemieux – ACES / Europe Dublin 2015
Intra-cranial EEG-fMRI of interictal spikes
Summary BOLD maps across all IZ1 IED
[Chaudhary - submitted]
7 cases had concordant maps:
better outcome (ILAE 1 & 3)
5 cases had discordant maps:
worse outcome (ILAE 4 & 5; 5 cases)
Case # 3 (ILAE class 1)
Case # 13 (ILAE class 4)
SPM{F} contrast across all IZ1 IED-
related effects
Summary measure for comparison:
Relationship of BOLD clusters with
the presumed, icEEG-derived EZ

32. Lemieux – ACES / Europe Dublin 2015
Conclusions (2)
• EEG-fMRI (+video) to have increased importance in neuroscience
• Intracranial EEG-fMRI
• Analysis is complex: additional layer on top of icEEG analysis & interpretation
• Abundance of activity -> more reliable maps than scalp EEG-fMRI
• Interpretation: compare it against what?
• How precious is our ‘gold’ standard?
• Surgical outcome + localisation of resected tissue: what about disruption of
wider networks?
• Effective connectivity: ‘the full multimodal generator model’ (DCM)
• Improved biophysical models of epileptogenic networks being developed
• Applicable to icEEG, then fMRI

33. Lemieux – ACES / Europe Dublin 2015
Seizure propagation in hypothalamic hamartomas (HH)
• Seizures originate in HH, and control of seizures can be achieved by
surgically removing the HH.
• Possible surgical alternative: disconnection of the underlying pathway.
• Different seizure propagation pathways have been described in HH [Leal et
al. Epilepsia 2003; Kahane et al. Epileptic Disord. 2003]:
• Aim: identify the correct seizure propagation pathway in individual
patients using DCM.
1.HH to temporal-
occipital
(posterior, PR)
to frontal lobe
(anterior, AR)
(through the fornix)
2.HH to frontal
(anterior, AR) to
temporal-occipital
(posterior, PR)
lobe
(through the
mammillo-thalamo-
cingulate pathway)
[Murta et al, 2012]

34. Lemieux – ACES / Europe Dublin 2015
Seizure propagation in HH:
Family of DCM models
•HH is the driving region
•All structures consistent with each of 2 propagation hypotheses
•Each connection: uni- or bi-directional (22=4 structures per hypothesis)
•Each connection: linear (black) or bilinear (black and green) (24=8 models per hypothesis)
[Murta et al, 2012]

35. Lemieux – ACES / Europe Dublin 2015
Seizure propagation in HH:
Bayesian model comparison
[Murta et al, 2012]
Most likely model
Model 1:
HH → temp-occ. → frontal

36. Beyond mapping:
Networks and causality
(and a detour via IGE)

37. Lemieux – ACES / Europe Dublin 2015
• Multi-modal imaging = Combinations of images or
maps
– from different sources (instruments)
or
– that show different aspects (e.g. MR contrasts)
• Fundamental assumption: measurements relate to
the same phenomenon
– Location
– Time
Multi-modal imaging: basics

38. Lemieux – ACES / Europe Dublin 2015
Estimating a network of sources and their dynamics:
Dynamic Causal Modelling
[Friston, 2009; David et al 2006]
Bi-linear model of effective
connectivity
– Effect of activity in one region on
activity in other: equations of motion
– Biophysical generative model
fMRI:EEG/MEG neural mass model:
+ Model comparison (Bayesian)

39. Lemieux – ACES / Europe Dublin 2015
EEGfMRI of GSW - QS 1.5T series
Group analysis
IGE
N=18
Sup Post Par ↓
Front ↓
Post Cing ↓
Thalam ↑
[Hamandi et al., 2006]
Th
Th

40. Lemieux – ACES / Europe Dublin 2015
Dynamic causal models of
effective connectivity in GSW
Centrencephalic
Cortico/corticoreticular
Precuneus model
[Vaudano et al, 2009]
Data:
EEG-fMRI of GSW in 7 patients with IGE
Significant GSW-related BOLD: Thalamus, Precuneus and ventromedial prefrontal
Model of effective connectivity: DCM of fMRI
GSW EEG onsets and offsets modelled as (endogenous) input
3 models:
Best in 5/7 cases

41. Lemieux – ACES / Europe Dublin 2015
Integrate and Fire Neurons
Mean Field Population
Dynamics
DCM of focal seizures
A more realistic biophysical model of (fast) ictal activity
Time (s)
Frequency(Hz)
5 10 15 20 25 30
8
16
32
64
128
Model: Coupled neural population dynamics
[M Leite, unpublished]

42. Lemieux – ACES / Europe Dublin 2015
+10mV
-70mV
E vs. I
Pyr Int
Current(pA)
Phase (%) Phase (%)
Phase (%) Phase (%)
Current(pA)Current(pA)
Current (pA) Current (pA)
Pyr Int
U
[M Leite; unpublished - In collaboration with D Kullmann and D Kuzmin]
LFP + whole cell voltage cla
Vholding = -70mV
A more realistic biophysical model
of (fast) ictal activity: Validation initial results

43. Lemieux – ACES / Europe Dublin 2015
Resting-state BOLD
BOLD increases
BOLD decreases BOLD decreases
BOLD increases
L
L
L
L
[Perani et al, in preparation]
Alpha (Mu) Beta