artifact (artefact) reduction in eeg – and a bit of erp basics cnc, 19 november 2014 jakob heinzle...
TRANSCRIPT
![Page 1: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/1.jpg)
Artifact (artefact) reduction in EEG – and a bit of ERP basics
CNC, 19 November 2014
Jakob Heinzle
Translational Neuromodeling Unit
![Page 2: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/2.jpg)
EEG artefacts
Overview
• Basic Principles of ERP recording (Luck Chapter 3)
• Averaging, Artifact Rejection and Artefact Correction (Chapter 4)
• A multiple source approach to the correction of eye artifacts (Berg and Scherg, 1994)
2
![Page 3: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/3.jpg)
EEG artefacts
Hansen’s axiom
• “There is no substitute for good data!”
• Get your data “free of noise” during recording already.– No electromagnetic contamination (Faraday
cages, no screens inside etc.)
– No eye movements, no muscle artifacts, no sweating (Instruct subjects and make it comfortable for them.)
– No bridging etc. (careful setup of caps etc.)
3
![Page 4: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/4.jpg)
EEG artefacts 4
Basics of ERP (EEG) recording
• Electrodes (Ground and Reference)– Often Mastoid reference (average over both
mastoids)
– Signal is A – (Lm/2 + Rm/2), where all A, Lm and Rm are voltages relative to ground.
– Sometimes average reference.
• Typical size of ERP is about 10 mV
![Page 5: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/5.jpg)
EEG artefacts 5
EEG electrodes
![Page 6: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/6.jpg)
EEG artefacts 6
Sources of noise
• Everything that can cause a voltage difference between two electrodes and is not of “brain origin”
![Page 7: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/7.jpg)
EEG artefacts 7
Environmental noise
• Electrical noise in the environment– power line AC (50 Hz), Video monitors
(refresh rate), Impedance changes at electrodes, bridges, …
• Reduce noise as much as possible– Faraday cages, shielded room, etc.
– Reduce impedance at electrodes (gel, scratch surface of skin, …)
![Page 8: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/8.jpg)
EEG artefacts 8
Amplification, Filtering and Digitization
• Active amplifiers increase signal to range that is then digitized into 4096 (212) discrete steps.– Set gain of amplifier to use entire range
• High pass filtering of signal (often 0.01 Hz)
• Sampling rate depends on low pass filter of amplifier Nyquist.
![Page 9: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/9.jpg)
EEG artefacts 9
Averaging
• In most cases ERP signals are averaged. – Assumptions: Signal always the same and
only EEG noise varies from trial to trial.
– If noise is independent of ERP it is reduced by a factor 1/sqrt(n)
• “It is usually much easier to improve the quality of your data by decreasing sources of noise than by increasing the number of trials.”
![Page 10: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/10.jpg)
EEG artefacts 10
Averaging
![Page 11: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/11.jpg)
EEG artefacts 11
Latency variability
![Page 12: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/12.jpg)
EEG artefacts 12
Overlap between trials
Problematic if different for different trial types.
![Page 13: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/13.jpg)
EEG artefacts 13
Averaging
• Area measures are less sensitive to latency variability.
• Response locked averaging.
• Woody filter. Iterative template matching, template calculation technique.
• Time locked spectral averaging.
![Page 14: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/14.jpg)
EEG artefacts 14
Time locked spectral averaging
![Page 15: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/15.jpg)
EEG artefacts 15
Steady state ERP
Use overlap and drive responses into a steady state.
![Page 16: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/16.jpg)
EEG artefacts 16
Typical artefacts from participant
• Eye blinks
• Eye movements
• Muscle activity
• Skin potentials
• Heart artefacts
• …
All of those can create large signals and might be correlated with the task.
![Page 17: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/17.jpg)
EEG artefacts 17
Some examples
![Page 18: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/18.jpg)
EEG artefacts 18
How to deal with artefacts
• Artefact rejection: Remove all trials that contain contaminated data.
• Artefact correction: Use all data, but try to correct for the artefacts.
• But, best thing is always to avoid artefacts as much as possible.
![Page 19: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/19.jpg)
EEG artefacts 19
Post-processing of artefacts
• Detecting artefacts is a signal detection problem.
• Problem: Threshold for artefact detection. Typical ROC type problem (True positive vs. false positive)
In general: Define artifact measure, detect artifacts, reject artifacts.
![Page 20: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/20.jpg)
EEG artefacts
Electric field of the eyes
http://www.bem.fi/book/28/28.htm
20
![Page 21: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/21.jpg)
EEG artefacts
Example: Blinks
21
![Page 22: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/22.jpg)
EEG artefacts 22
Eye movement artifact correction
![Page 23: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/23.jpg)
EEG artefacts 23
Basic idea – component model
• EEG data is modeled as sum of EEG and eye artefact components.
• Spatial distribution (scalp distribution) activated by a temporally evolving factor.
![Page 24: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/24.jpg)
EEG artefacts 24
What are the components?
• Eye components are derived from a calibration session prior to the experiment.– Eye movements into different directions and
blinks (every 2 secs).
– PCA on this data: 3 components explain 95% of variance.
• EEG components are fitted dipole sources, or combination of assumed dipoles.– No details here, different paper of the authors.
![Page 25: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/25.jpg)
EEG artefacts 25
Different models
![Page 26: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/26.jpg)
EEG artefacts 26
Eye movement results
![Page 27: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/27.jpg)
EEG artefacts 27
Eye movement results
![Page 28: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/28.jpg)
EEG artefacts 28
Testing the method
Use “artefact free” data and data with artefacts.
For both compare optimizing (dipole fitting), surrogate and traditional method.
![Page 29: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/29.jpg)
EEG artefacts 29
fMRI results – Visuomotor mismatch specific activation
![Page 30: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/30.jpg)
EEG artefacts 30
![Page 31: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/31.jpg)
EEG artefacts 31
Residual variance in individual subjects
![Page 32: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/32.jpg)
EEG artefacts 32
Results - Maps
![Page 33: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/33.jpg)
EEG artefacts 33
Results - Maps
![Page 34: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/34.jpg)
EEG artefacts 34
Spatial accuracy (consistency)
Compared to uncorrected model without EOG electrodes.
![Page 35: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/35.jpg)
EEG artefacts 35
Results
• Optimized methods seems to be best
• Artefact rejection does not remove all eye movement artefacts.
• Ground truth is not known, but they take one of the fitted results to compare.
![Page 36: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/36.jpg)
EEG artefacts 36
ICA based artefact removal
• Independent component analysis (ICA) can be used to find independent sources and exclude sources that come from artifacts.
𝑥 (𝑡 )=𝐴 ∙ 𝑠(𝑡)
• ICA assumes x(t) is a linear mixture of (maximally) independent sources.
• For details see e.g.: – ICA general: Hyvärinen and Oja, Neural Networks, 13(4-5):411-430, 2000
– ICA in EEG: Delorme et al, IEEE 2005 and many other papers from Scott Makeig’s group.
![Page 37: Artifact (artefact) reduction in EEG – and a bit of ERP basics CNC, 19 November 2014 Jakob Heinzle Translational Neuromodeling Unit](https://reader036.vdocuments.mx/reader036/viewer/2022062515/56649cfb5503460f949ccfd1/html5/thumbnails/37.jpg)
EEG artefacts
Some more sources
• Some EEG artifacts reviewed:– https://www.youtube.com/watch?v=1LftSdvNXh0
• Web based EEG Atlas– http://eeg.neurophysiology.ca
• Saccadic spike artefact in MEG– Carl et al, Neuroimage 59:1657 2012
37