Simultaneous EEG-fMRI: from acquisition to application.

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Simultaneous EEG-fMRI from acquisition to
application.

• Karen Mullinger

Sir Peter Mansfield Magnetic Resonance
Centre, School of Physics and Astronomy University
of Nottingham
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Overview

• Introduction
• Aspects of getting good quality data
• Optimising experimental set-up
• General pointers
• Facilitating good
• gradient artefact correction
• pulse artefact correction
• Summary
• Application
• Neurovascular coupling.
• Latest results (food for thought)

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Why Simultaneous EEG fMRI?

• Very powerful spatiotemporal tool
• Same experimental environment
• Same attention and awareness
• Same brain activity
• Necessary when brain activity cant be predicted

fMRI
EEG
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EEG Artefact Sources

1. Gradient Artefact (GA) Switching of the gradient
   fields, causes large changes in magnetic flux
   inducing electrical signals within the EEG.

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EEG Artefact Sources

1. Pulse Artefact (PA) Precise source unclear but
   linked to the cardiac cycle.

1) Pulsatile blood flow effects (Hall effect).
2) Small head nod
3) Scalp expansion
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The Result!
200µV
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Good quality EEG data

• Two aspects to EEG-fMRI
• Experimental set-up and data collection
• Best post-processing methods

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Good quality EEG data

• Experimental set-up and data collection

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General advice

• Low impedances of EEG channels
• Less noisy EEG signals
• Subject comfort and padding
• Minimise movement ? reduced artefacts

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General advice Motion

• Aim
• To investigate effect of motion artefacts on
  EEG-BOLD correlates
• Method
• 4 subjects
• Standard 32 channel EEG recording.
• EEG data were recorded during Dual Echo EPI
• 40 slices, 8484 matrix, 334 mm3 voxels
• TR3s TE1/TE2 20/48ms
• Episodic memory task required to move a cursor
  with a roller-ball to respond.

Jansen, M. et al, NeuroImage 59, 261-270 (2012)
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General advice Motion

• Analysis
• EEG
• Gradient (AAS) and Pulse (OBS) artefact
  correction
• ICA to remove residual artefacts
• Noisy channels removed
• Filtered 4-8Hz (Theta band)
• fMRI
• Motion and physiological correction
• Echoes combined
• Regressors
• Continuous theta regressor
• Head motion (from motion parameters)
• Artefacts remaining after correction (from visual
  inspection)

Jansen, M. et al, NeuroImage 59, 261-270 (2012)
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General advice Motion
Not convolved with HRF
Convolved with HRF
Jansen, M. et al, NeuroImage 59, 261-270 (2012)
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General advice Motion
Task Foot motion
Not convolved with HRF
Convolved with HRF
CAREFUL how you interpret results!
Jansen, M. et al, NeuroImage 59, 261-270 (2012)
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General advice

• Low impedances of EEG channels
• Less noisy EEG signals
• Subject comfort and padding
• Minimise movement ? reduced artefacts
• Isolate amplifiers/cables from scanner bed
• Minimise vibration of equipment

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General advice
Mullinger, K.J. et al, MRI 26(7), 968-977 (2008)
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General advice

• Low impedances of EEG channels
• Less noisy EEG signals
• Subject comfort and padding
• Minimise movement ? reduced artefacts
• Isolate amplifiers/cables from scanner bed
• Minimise vibration of equipment
• Turn cyrocooler compression pumps off
• Minimise noise sources

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General advice
7T, no scanning Everything on Cryopumps
off.. ...and room lights, gradient and patient
airflow
Mullinger, K.J. et al, MRI 26(7), 968-977 (2008)
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• Gradient artefact

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Average Artefact Subtraction (AAS)
Allen, P.J. et al. NeuroImage 12, 230-239 (2000)
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Artefact Correction requirements

• AAS Requires
• Artefact to be highly repeatable across cycles
• Precisely recording the artefact waveform and the
  beginning of each volume.
• These requirements must be closely adhered to as
  the unfiltered GA is at least 10,000 times larger
  than an evoked response
• Residual artefacts are problematic

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Precise sampling

• Acquire EEG data at 5kHz
• Ensure your slice TR is a multiple of the scanner
  clock period (i.e. 200µs)
• WARNING
• TR entered into console is not always the TR
  outputted due to rounding issues!!
• Philips System for equidistant EPI TR
  Calculator

Need clinical science agreement for this
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Precise sampling

• Synchronise the MR Scanner and EEG clocks using
  the output from the MR scanner.
• Philips system use the 10MHz output from the MR
  scanner clock to drive the EEG clock

Mandelkow, H. et al, NeuroImage 32(3)1120-1126
(2006) Mullinger, K.J. et al, JMRI 27(3) p.
607-616 (2008)
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Experimental Results
Average slice artifact
180 dynamics, 20 slices, 3 subjects Results from
electrode F7 for a single subject
Mullinger, K.J. et al, JMRI 27(3) 607-616 (2008)
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Minimising GA amplitude

• Why?
• Prevent channel saturation
• Allow higher EEG recording bandwidth
• Improve artefact correction
• How?
• Position subjects 4cm in foot direction (naision
  at isocentre 0cm). Approximately at Fp12.

Yan, W.X., et al. NeuroImage 46(2)459-471.
(2009) Mullinger, K.J. et al, NeuroImage,
54(3)1942-1950 (2011)
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Optimal Position standard fMRI

• Aim
• Compare GA produced by a multi-slice EPI sequence
  at standard and optimal subject positions.
• Method
• 6 subjects
• Experiments were carried out with the nasion at
• iso-centre
• optimal (4 cm) z-offset
• Standard 32 channel EEG recording, 250 Hz low
  pass filter.
• EEG data were recorded during standard EPI
• 32 slices, 8484 matrix, 334 mm3 voxels
• TR2.5s TE 40ms slice repetition frequency
  12.8 Hz
• Cued foot movement 5s every 30s (total 8
  minutes) cumulative head movements of lt1 mm.

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Optimal position Results

• RMS of average artefact before correction
• 40 average reduction in RMS over all channels

• STD across slices after correction
• 36 reduction in RMS at slice harmonics after
  correction

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Pulse artefact
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Pulse Artefact Correction

• Many methods of PA correction
• Average artefact subtraction (AAS)1
• Optimal basis sets (OBS)2
• Independent component analysis (ICA)3
• Varying levels of success reported
• Most require correctly identifying the QRS
  complex

within the ECG trace.
ECG
1 Allen, P.J. et al, NeuroImage 8(3), 229-239
(1998) 2 Srivastava, G. et al, NeuroImage 24,
50-60 (2005) 3 Niazy, R.K. et al, NeuroImage
28, 720-737 (2005)
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Pulse Artifact

• Problems
• ECG is affected by gradients as well.
• Sometimes hard to get a good ECG trace.
• Trace is sometimes saturated.

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• Solution on a Philips system
• Use vector cardiogram (VCG) from MR Scanner which
  is unaffected by gradients1.
• R peak markers are also placed automatically in
  the physlog file2 which can be used for pulse
  artefact correction directly.

1 Chia et al. JMRI, 12678-688 (2000) 2
Fischer et al. MRM, 42361-370 (1999)
Need research login to access physlog file
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Results

• Data gradient-corrected and low-pass filtered at
  70 Hz
• EEG trace from Tp10 averaged over all cardiac
  cycles in 2 minute period.
• 0 timeR peak marker from VCG

No correction
Using ECG markers
Using VCG markers
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Pulse Artefact

• Precise source unclear but linked to the cardiac
  cycle.

• Variation between cardiac cycles makes correction
  of difficult
• Problems increase with field strength
• Need a greater understanding of pulse artefact

Average pulse artefact
1) Pulsatile blood flow effects
T7
R-peak
2) Small head nod
3) Scalp expansion
Debener, S. et al, Int. J. Psychophys, 2008,
67(3), p.189-199
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Measuring the PA constituents

• 6 subjects
• Recorded EEG data in 3T MR scanner
• 4 conditions
• Relaxed
• Bite Bar and vacuum cushion (stop head nod)
• Swimming cap (stop Hall effect)
• 23 (left with scalp expansion).

Yan, W.X., et al., HBM, 2010. 31(4) p.
604-620. Mullinger, K.J. et al, 667 WTh HBM
2011. Quebec.
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PA Experimental Results
Average RMS
Subject RMS
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Summary

• SNR of EEG data inside the MR scanner still lower
  than outside.
• Higher MR fields ? increasing EEG artefact
  problems.
• Experimental set-up is important.

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Data Acquisition Summary

• To improve gradient artefact correction
• Chose TR and number of slices wisely
• Synchronise scanner clocks
• Optimally position the subject
• To improve pulse artefact correction
• Use VCG to monitor cardiac trace

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Application
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Investigating origin of Negative BOLD

• Negative BOLD Response (NBR) Regions where there
  is a stimulus related decrease in BOLD signal.
• Reported in visual1, motor2 and somatosensory3
  cortices.

From 2 Stefanovic et al. Neuroimage 222004.
1 Shmuel et al. Neuron 36(6)2002. 3 Kastrup
et al. Neuroimage 41(4)2008.
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Negative BOLD

• NBR origin unclear
• Neuronal basis
• Haemodynamic artefact (blood steal)
• Invasive recordings in monkeys show a decrease in
  local field potentials (LFP) and spiking activity
  in regions of NBR, and suggest at least 60 of
  NBR is neuronal in origin1.
• Clarification in humans is needed.

1 Shmuel et al. Nat Neurosci. 9(4)2006.
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Aim

• To use simultaneous measurements of BOLD, ASL and
  EEG to investigate the relationship between
  natural fluctuations in the NBR and somatosensory
  evoked potentials (SEPs) during median nerve
  stimulation (MNS)1

1 Mullinger et al Proc. ISMRM 109 2011
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Method

• Simultaneous EEG-fMRI
• Philips Achieva 3T MR scanner 8 channel SENSE
  head coil.
• 64 channel Brain Products EEG system.
• Localiser GE-EPI BOLD sequence used for
  planning.
• Experiment
• FAIR Double Acquisition Background Suppression1
  sequence used for simultaneous BOLD and
  background suppressed ASL data acquisition
  (TR2.6s, TE13/33ms (ASL/BOLD), label
  delay1400ms, 3x3x5mm3 voxels, 212mm FOV, SENSE
  factor 2 background suppression
  TI1/TI2340ms/560ms).
• Cardiac and respiration monitored.
• MR and EEG scanner clocks synchronised.
• EEG electrode positions digitised (Polhemus
  system, Isotrack).

1 Wesolowski et al. Proc. ISMRM, 61322009.
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Paradigm

• 13 right handed subjects (8 males, 263 yrs)
• Stimulate median nerve of right wrist
• Amplitude just above motor threshold to cause
  thumb distension
• 2 Hz stimulation, 0.5ms pulses (Digitimer DS7A)

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Analysis

• EEG pre-processing
• Gradient and pulse artefact correction using
  average artefact subtraction (Brain Vision
  Analyzer2)
• Data inspection
• 3 subjects excluded due to gross (gt3mm) or
  stimulus-locked movement.
• Noisy channels and/or blocks rejected
• Down-sampled 600Hz
• Re-referenced Average of non-noisy channels
• Filtered 2-40 Hz

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Analysis

• EEG Beamformer1

Fitted2 basis set to SEP for each block to find
peak-to-peak P100-N140 amplitude
T-stat map active window 0.01-0.16s passive
window 0.3-0.45s
VE timecourse for single block
Averaged over 20 responses in a block
1 Brookes et al. NeuroImage 40(3)2008 2
Mayhew et al. Clin. Neurophysiol. 117(6)2006
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Analysis

• fMRI pre-processing
• Motion corrected (FLIRT, FSL)
• BOLD data physiologically corrected (RETROICOR)
• Interpolated to effective TR2.6s
• ASL perfusion weighted image Tag-Control
• BOLD image pairs averaged
• Normalised to MNI template
• Smoothed 5mm FWHM kernel

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Analysis

• fMRI General Linear Models

Boxcar
?
SEP amplitude modulator

• 2nd level fixed effects analysis on BOLD and ASL
  data

Timecourse for each region subject obtained
averaged over subjects blocks
Group ROI defined for positive and negative
correlation. BOLD Plt0.05 FWE ASL Plt0.001 uncorr
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Results
BOLD
ASL

• No positive correlation amplitude of SEP and fMRI
  in S1.

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Results
Solid line BOLD, Dashed line ASL
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Results
Constants M 7.21, a 0.38, ß 1.2
R 0.9704, Plt0.110-4 Gradient 0.42
Coupling ratio agrees with Stefanovic3
1 Kastrup et al., Neuroimage 41(4)2008. 2
Davis et al., PNAS, 951998 3 Stefanovic et
al., NeuroImage 222004
1 Kastrup et al., Neuroimage 41(4)2008. 2
Davis et al., PNAS, 951998
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Discussion

• No positive correlation of fMRI and evoked
  potentials in S11.
• Ipsilateral NBR cannot be explained by blood
  steal2 as bilateral S1 regions are fed from
  different vascular territories.
• CMRO2 shown in NBR region - suggests a neuronal
  origin of the response.

1 Klingner et al. Neuroimage 53(1) 2010 2
Wade et al. Neuron 36(6)2002
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Discussion

• Show for first time correlation between
  ipsilateral S1 NBR and amplitude of concurrent
  EEG evoked response from contralateral S1/M1.
• Agrees with area identified by Klingner where NBR
  is modulated by intensity of MNS1.
• Suggest that NBR-SEP relationship arises because
  NBR results from inhibition of task irrelevant
  processing in ipsilateral S1, with corresponding
  increase in excitability of contralateral S1, as
  indexed by increasing SEP amplitude.

1 Klingner et al. Neuroimage 53(1) 2010
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Why simultaneous recordings....

• Trial by trial natural fluctuations in the evoked
  response ? simultaneous recordings are essential.
• Can also study changes in oscillatory activity
  and correlations with BOLD1 and also CBF........

plt0.05, FWE
1 Mayhew et al, Proc ISMRM 1560, 2011
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Why Simultaneous recordings....food for thought

• Differences in oscillatory activity providing
  evidence of a neuronal origin of the
  post-stimulus undershoot...

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Acknowledgments

• Colleagues
• Professor Richard Bowtell
• Dr Susan Francis
• Winston Yan
• Jade Havenhand
• Dr Thomas White
• Dr Marjie Jansen
• Dr Elizabeth Liddle
• Prof Peter Liddle
• Birmingham University
• Dr Stephen Mayhew
• Dr Andrew Bagshaw
• Industry
• Robert Stormer (Brain Products)
• Dr Matthew Clemence (Philips)

Funding MRC EPSRC Mansfield Fellowships
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Thank you