Simultaneous EEG and fMRI for the localisation of

spontaneous alpha-rhythm J.C. de Munck S.I. Gonçalves P.J.W. PouwelsR. SchoonhovenJ.P.A. KuijerE.J.W. Van SomerenP. AndersonN.M. MauritsJ.M. HoogduinR.M. HeethaarF.H. Lopes da Silva

VU Medical Centre, AmsterdamAZG, GroningenInstitute of Neurobiology, UvA, Amsterdam

Outline

• Introduction

• Methodology

• Results

• Discussion and Future Work

Introduction

• The alpha rhythm is the hallmark of the resting state, therefore related to all fMRI studies.

• Different types of alpha activity: posterior alpha, mu rhythm, midtemporal third rhythm.

• Many open questions related to the nature and origin of this type of activity still remain.

IntroductionSource localisation with EEG

Find Solution to the EEG Inverse Problem

Source Model:

Current Dipole

Volume Conductor:

RealisticSpherical

specify specify

IntroductionfMRI

voxel intensity

active active activeactive

rest rest restrest

4 minutes

: each point represents intensity of voxel during one 3 second MRI - EPI scan

R/P L

A

Introduction

4 minutes

Average alpha power time series

IntroductionEEG/fMRI

voxel intensity

: each point represents intensity of voxel during one 3 second MRI - EPI scan

4 minutes

Average alpha power time series

possible with Simultaneous EEG/fMRI

The MR greatly disturbs the EEG signal

MethodologyArtifacts on the EEG

1 sliceGradientartifacts

RF pulseartifact

Methodology Artifacts on the EEG

There are also artefact that are related to the heart beat.

Methodology Artefacts on the EEG

These artefacts can be removed by an averaging procedure.

Methodology: Induced alpha rhythm f

(0-1

00H

z)

t (0-600s)

10 Hz

eyes open

eyes closed

eyes open

eyes open

eyes open

eyes open

eyes open

eyes open

eyes open

eyes open

eyes open

eyes closed

eyes closed

eyes closed

eyes closed

eyes closed

eyes closed

eyes closed

eyes closed

eyes closed

ResultsExperiment description• Data recorded from 8 healthy subjects (4 males, 4 females, mean age

34±8), 2 discarded.• Subjects instructed to lie still inside the scanner, keeping the eyes closed.• EEG acquired with MR compatible EEG amplifier (SD MRI, Micromed,

Treviso, Italy) and cap with 19 Aq/AgCl electrodes positioned in 10/20 system, Bipolar montage.

• Functional images acquired on 1.5 T MR scanner (Magnetom Sonata, Siemens, Erlangen, Germany) using T2* weighted EPI (TR=3000ms) consisting of 24 transversal slices.

• High resolution MPRAGE sequence consisting of 160 slices to provide anatomical reference.

• For each subject, 400 volumes (in a total of 20 mins of data) were acquired per subject. For 3 subjects, data was acquired in two series of 10 mins each.

Results: Spontaneous alpha rhythm

t (0-1200s)

f (0

-100

H

z)

10 Hz

Results - Subjects 1, 2 and 3

Subject 1FDR=10-7

all derivations

Subject 2FDR=0.050.15290.4000all derivations

Subject 3FDR=0.050.20000.4000all derivations

Results - Subject 4

Subject 4spectrogram

Results - Subject 4

Subject 4spectrogram

Results - Subject 4

Subject 4FDR=0.2

-0.2706-0.1647P3-O1, P4-O2

Alpha period (darker blue)

-0.3176-0.2353C3-P3, C4-P4

Beta period (lighter blue)

Results - Subject 5

Subject 5FDR=0.05-0.4000-0.1529C3-P3, C4-P4, T5-T3, T6-T4

Results - Subjects 5 and 6

Subject 5FDR=0.05-0.4000-0.1529C3-P3, C4-P4, T5-T3, T6-T4

Subject 6FDR=0.050.20000.4000C3-P3, C4-P4

Discussion and Future work• Our results suggest that inter-subject variability is important and

should be taken into account. (e.g. subjects 1, 5 and 6).

• Furthermore, the results show that even within one subject (e.g. subject 4), different states correspond to different correlation patterns.

• Since the resting state is the reference state in most fMRI studies, our results show that variability in resting state may be an important cause of the variability of fMRI results.

EEG

ECG

fMRI

EEG2

Correlation pattern

Spectrogram

The analysis of simultaneous EEG-ECG-fMRI data is quit complex.

Discussion and Future work

There is a correlation between BOLD and the heartbeat signal...

Discussion and Future work

Heart beat

Volumes

3 s. 3 s.

There is a correlation between BOLD and the heartbeat signal...

Discussion and Future work

Heart beat

Volumes

3 s. 3 s.

There are many fMRI points that correlate well with the heart beats. Thereforethe heart beat should be accounted for in the correlation analysis.

Discussion and Future work

EEG

ECG

fMRI

EEG2

Correlation pattern

Spectrogram

But in the future it will be even more complex...

MRI Source model

SSP

Discussion and Future work

Discussion and Future workThe complexity of the problem put demands on the software for the data analysis:

• High performance

•Good visualisation tool

•Efforts to keep track of raw data, intermediate results and end product.

Results - Subjects 5 and 6

Results - Temporal modulation of the

regressor

Subject 2

Subject 5

disc. sub

Results - Temporal modulation of the

regressor (all derivations)

0.0

0.1

0.2

0.3

0.4

sub 1 sub 2 sub 3 sub 4 sub 5 sub 6 disc. sub

Cm

PC tP

m

N

PP1N

0i

2

i

tP

N is the number of samples;Pi is the power value at time sample i; is the average power.P

Results - Temporal modulation of the regressor and within subject variation

0

0.1

0.2

0.3

0.4

sub 3 - all sub 3 - parieocc sub 4 - alpha sub 4 - 2nd harm

Cm

Discussion and Conclusions• Results suggest that the resting state is not comparable amongst

subjects and sometimes, not even within one subject.

• As the resting state plays an important role in fMRI analysis where the paradigms are of the type “rest-task”, the abovementioned variability should be considered when questioning how comparable are fMRI results from different subjects .

• The question raised previously could be ultimately addressed by recording the simultaneous EEG and using the average alpha power time series as a distractor in the fMRI analysis.

Future work• Technical improvements

- Signal Space Projection methods;- Dipole fitting on simultaneous EEG;- Non-linear correlation measures;- Variability of hemodynamic response.

• Scientific questions- Can the abovementioned findings be confirmed in a more systematic study?- Does the alpha rhythm variability decrease when the state of the subject is more well defined?- What is the relation between the first and second harmonics of the alpha rhythm?

MethodologyFalse Detection Rate (FDR)

In this procedure, where N null hypothesis are being tested simultaneously, the goal is to control the goal of FDR (Benjamin and Hochberg (1995)):

FT

FEFDR

whereE(.) stands for the expected value;F is the number of false detections;T is the number of true detections;FDR = 0 if T+F=0.

MethodologyFalse Detection Rate (FDR)

1. Select desired FDR bound q;

2. Order p-values from smallest to largestp1p2 …. pN;

3. Determine largest i such as:

4. Declare voxels v(1) to v(i) as active.

Nc

q

N

ipi

0.5772 ,NlnNc .2

1Nc .1

Technical requirementsSafety issues

E.g.

Presence of metal wires that canact as antennas;

Existence of wire loops generatinginduced currents;

Technical requirementsHardware solutions

Degradation of MR signal: RF contamination, ferromagnetic materials

• Shielding of EEG system

• Use of appropriate materials

EEG artifact caused by the MR

• DC amplifiers of large dynamic range and high resolution (22/24 bits)

• High sampling frequency (> 1 KHz)

Safety: limitation of induced currents and closed loops

• current limiting resistors close to electrodes

• use of carbon wires

• careful wire placement avoiding loops

• fiber optic connection between subject + EEG Amp. and the remaining system.

First ExperimentsBioSemi (24 bits, 16 KHz)

Signals after removing average over slices and volumes

Raw signals

Remaining RF pulse

First Experiments

Linear interpolation of remaining RF artifactUnfiltered data

First Experiments

Average Ballist. Art. Corrected (black) vs. uncorrected(gray) data

Methodology Artifacts on the EEG

Ballistocardiogram artifact on the EEG (time locked to the ECG)

wire displacement dueto pulsate vessel movement

Hall Effect

BvF

q

vF-

F+

B VH

MethodologyArtifacts on the MR

RF contamination of the MR signal by the EEG hardware.

MethodologyArtifacts on the MR

Degradation of the MR signal by the presence of ferromagnetic materials.