simultaneous eeg-fmri: from acquisition to application. karen mullinger sir peter mansfield magnetic...
TRANSCRIPT
Simultaneous EEG-fMRI: from acquisition to
application.Karen Mullinger
Sir Peter Mansfield Magnetic Resonance Centre,School of Physics and Astronomy
University of Nottingham
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)
Why Simultaneous EEG –fMRI?
• Very powerful spatiotemporal tool • Same experimental environment • Same attention and awareness • Same brain activity Necessary when brain activity can’t be
predicted
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fMRI
EEG
1. Gradient Artefact (GA): Switching of the gradient fields, causes large changes in magnetic flux
inducing electrical signals within the EEG.
EEG Artefact Sources
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2. Pulse Artefact (PA): Precise source unclear but linked to the cardiac cycle.
EEG Artefact Sources
1) Pulsatile blood flow
effects (Hall effect).
2) Small head nod
3) Scalp expansion
The Result!
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Good quality EEG data
Two aspects to EEG-fMRI:
‒ Experimental set-up and data collection
‒ Best post-processing methods
General advice
‒ Low impedances of EEG channels Less noisy EEG signals
‒ Subject comfort and paddingMinimise movement → reduced artefacts
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, 84×84 matrix, 3×3×4 mm3 voxels• TR=3s 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)
General advice: MotionAnalysis: • 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:
1. Continuous theta regressor
2. Head motion (from motion parameters)
3. Artefacts remaining after correction (from visual inspection)
Jansen, M. et al, NeuroImage 59, 261-270 (2012)
General advice: Motion
Jansen, M. et al, NeuroImage 59, 261-270 (2012)
Not convolved with HRF
Convolved with HRF
General advice: Motion
Not convolved with HRF
Convolved with HRF
CAREFUL how you interpret results!
Task: Foot motion
Jansen, M. et al, NeuroImage 59, 261-270 (2012)
General advice
‒ Low impedances of EEG channels Less noisy EEG signals
‒ Subject comfort and paddingMinimise movement → reduced artefacts
‒ Isolate amplifiers/cables from scanner bedMinimise vibration of equipment
General advice
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7T, no scanning
Amplifier on the scanner bore
Amplifier suspended.
Mullinger, K.J. et al, MRI 26(7), 968-977 (2008)
General advice
‒ Low impedances of EEG channelsLess noisy EEG signals
‒ Subject comfort and paddingMinimise movement → reduced artefacts
‒ Isolate amplifiers/cables from scanner bedMinimise vibration of equipment
‒ Turn cyrocooler compression pumps offMinimise noise sources
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Everything on
Cryopumps off..
...and room lights, gradient and patient airflow
Mullinger, K.J. et al, MRI 26(7), 968-977 (2008)
General advice
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Average Artefact Subtraction (AAS)
Allen, P.J. et al. NeuroImage 12, 230-239 (2000)
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
–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*
Precise sampling
*Need clinical science agreement for this
– 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
Precise sampling
Mandelkow, H. et al, NeuroImage 32(3)1120-1126 (2006)
Mullinger, K.J. et al, JMRI 27(3): p. 607-616 (2008)
Experimental Results
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Results from electrode F7 for a single subject
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Standard Deviation associated with average slice artifact
Mullinger, K.J. et al, JMRI 27(3): 607-616 (2008)
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 Fp1&2.
Yan, W.X., et al. NeuroImage 46(2):459-471. (2009)Mullinger, K.J. et al, NeuroImage, 54(3):1942-1950 (2011)
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, 84×84 matrix, 3×3×4 mm3 voxels• TR=2.5s TE =40ms; slice repetition frequency = 12.8 Hz
• Cued foot movement: 5s every 30s (total: 8 minutes): cumulative head movements of <1 mm.
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 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
[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)
ECGwithin the ECG trace.
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.
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[1] Chia et al. JMRI, 12:678-688 (2000)
[2] Fischer et al. MRM, 42:361-370 (1999)*Need research login to access physlog file
Results
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No correction
Using ECG markers
Using VCG markers
• Data gradient-corrected and low-pass filtered at 70 Hz
• EEG trace from Tp10 averaged over all cardiac cycles in 2 minute period.
• 0 time=R peak marker from VCG
Mean Standard Deviation
• Precise source unclear but linked to the cardiac cycle.
Pulse Artefact
1) Pulsatile blood flow
effects 2) Small head nod 3) Scalp
expansion
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• Variation between cardiac cycles makes correction of difficult
• Problems increase with field strength
• Need a greater understanding of pulse artefact
Debener, S. et al, Int. J. Psychophys, 2008, 67(3), p.189-199
Measuring the PA constituents
• 6 subjects• Recorded EEG data in 3T MR scanner• 4 conditions:
1. Relaxed
2. Bite Bar and vacuum cushion (stop head nod)
3. Swimming cap (stop Hall effect)
4. 2&3 (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.
PA Experimental Results
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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.
Data Acquisition Summary
‒ To improve gradient artefact correction:Chose TR and number of slices wiselySynchronise scanner clocksOptimally position the subject
‒ To improve pulse artefact correction:Use VCG to monitor cardiac trace
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.
[1] Shmuel et al. Neuron 36(6);2002. [3] Kastrup et al. Neuroimage 41(4);2008.
From: [2] Stefanovic et al. Neuroimage 22;2004.
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.
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
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 (TR=2.6s, TE=13/33ms (ASL/BOLD), label delay=1400ms, 3x3x5mm3 voxels, 212mm FOV, SENSE factor 2; background suppression TI1/TI2=340ms/560ms).
– Cardiac and respiration monitored.– MR and EEG scanner clocks synchronised.
• EEG electrode positions digitised (Polhemus system, Isotrack).
[1] Wesolowski et al. Proc. ISMRM, #6132;2009.
Paradigm
• 13 right handed subjects (8 males, 26±3 yrs)
• Stimulate median nerve of right wrist• Amplitude: just above motor threshold to
cause thumb distension • 2 Hz stimulation, 0.5ms pulses (Digitimer DS7A)
10s 20s 10s
40 blocks
20 pulses per block
Analysis
EEG pre-processing
• Gradient and pulse artefact correction using average artefact subtraction (Brain Vision Analyzer2)
• Data inspection:– 3 subjects excluded due to gross (>3mm) 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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EEG Beamformer1
Averaged over 20 responses in a block
Fitted2 basis set to SEP for each block to find peak-to-peak P100-N140 amplitude
VE timecourse for single block
T-stat map: active window: 0.01-0.16s passive window: 0.3-0.45s
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[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 TR=2.6s• ASL: perfusion weighted image: Tag-Control• BOLD image pairs averaged• Normalised to MNI template• Smoothed: 5mm FWHM kernel
Analysis
fMRI General Linear Models
SEP amplitude modulator:
Boxcar:
• 2nd level fixed effects analysis on BOLD and ASL data
Group ROI defined for positive and negative correlation.
BOLD: P<0.05 FWE
ASL: P<0.001 uncorr
Timecourse for each region & subject obtained; averaged over subjects & blocks
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BOLD ASL
MNI peak co-ordinates(-42,-20,50) Positive
(36,-18,50) SEP
(34,-16,46) Negative
Positively correlated with Boxcar
Negatively correlated with Boxcar
Negatively correlated with SEP amplitude
• No positive correlation amplitude of SEP and fMRI in S1.
Results
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Constants: M = 7.2%1, α = 0.38, β = 1.2
Coupling ratio agrees with Stefanovic3
[1] Kastrup et al., Neuroimage 41(4);2008. [2] Davis et al., PNAS, 95;1998[3] Stefanovic et al., NeuroImage 22;2004
Isocontours of CMRO2 (Davis Model2)
[1] Kastrup et al., Neuroimage 41(4);2008. [2] Davis et al., PNAS, 95;1998
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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
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
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........
[1] Mayhew et al, Proc ISMRM #1560, 2011
Positively correlated with Boxcar
Negatively correlated with Boxcar
Negatively correlated with Mu amplitude
p<0.05, FWE
Why Simultaneous recordings....food for thought
• Differences in oscillatory activity: providing evidence of a neuronal origin of the post-stimulus undershoot...
Acknowledgments
ColleaguesProfessor Richard Bowtell
Dr Susan FrancisWinston YanJade HavenhandDr Thomas WhiteDr Marjie JansenDr Elizabeth LiddleProf Peter Liddle
Birmingham UniversityDr Stephen MayhewDr Andrew Bagshaw
IndustryRobert Stormer (Brain Products)Dr Matthew Clemence (Philips)
FundingMRCEPSRCMansfield Fellowships