Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre...
-
Upload
marilynn-turner -
Category
Documents
-
view
216 -
download
2
Transcript of Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre...
![Page 1: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/1.jpg)
Pre-processingand the role of horses in the history of
M/EEG
Vladimir Litvak
Wellcome Trust Centre for NeuroimagingUCL Institute of Neurology
![Page 2: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/2.jpg)
Hans Berger1873-1941
Berger originally had intended to study astronomy. While he was serving in the German army in the early 1890s, his horse slipped down an embankment, nearly seriously injuring Berger. His sister many miles away had a feeling he was in danger and got her father to telegram him. This astonished him so much that he switched to study psychology.
(Blakemore, 1977)
At the beginning there was a horse
![Page 3: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/3.jpg)
What do we need?
M/EEG signals
Time axis (sampling frequency and onset) Sensor locations
EventsPossible source
of artefact
![Page 4: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/4.jpg)
~300 sensors<128 electrodes
![Page 5: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/5.jpg)
resting state
falling asleep
sleep
deep sleep
coma
1 sec
50 uV
Evoked response vs. spontaneous activity
post-stimpre-stim
evoked response ongoing rythms
Averaging
activeawake state
![Page 6: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/6.jpg)
Arbitrary
ASCIIMatlab
MEG
CTFNeuromagBTi-4DYokogawa
EEG
EEGLABBiosemiBrainvisionNeuroscanEGIANTSPM5…Biosig
Conversion
Fieldtrip
rawtimelockfreq
Convert button(fileio)
spm_eeg_convert
spm_eeg_ft2spm
GUI script
SPM8 dataset *.dat – binary data file
*.mat – header file
![Page 7: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/7.jpg)
• The *.mat file contains a struct, named D, which is converted to an meeg object by spm_eeg_load.
• The *.dat file is memory-mapped and linked to the object.
• Special functions called ‘methods’ provide a simple interface for getting information from the object and updating it and ensure that the header data remain consistent.
Expert’s corner
![Page 8: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/8.jpg)
![Page 9: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/9.jpg)
![Page 10: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/10.jpg)
Now lets take a step back
![Page 11: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/11.jpg)
Sensor locations
MEG:
• Requires quite complex sensor representation including locations and orientations of the coils and the way MEG channels are derived from the sensors.
• Sensor representation is read automatically from the original dataset at conversion.
EEG:
• Presently only requires electrode locations. In the near future will also include a montage matrix to represent different referencing arrangements.
• Usually electrode locations do not come with the EEG data.• SPM assigns default electrode locations for some common systems
(extended 10-20, Biosemi, EGI – with user’s input).• Individually measured locations can be loaded; requires co-registration.
![Page 12: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/12.jpg)
Coordinate systems can differ in their origin, units and orientation.
• MNI coordinates are defined using landmarks inside the brain.– Advantage: locations can be related to anatomy– Disadvantage: co-registration to a structural scan is required
• Head coordinates are defined based on the fiducials. Commonly used for MEG, but the definition differs between different MEG systems.– Advantage: once the location of the head is expressed in head coordinates,
it can be combined with sensor locations even if the subject moves.– Disadvantage: requires fiducials; if the fiducials are moved, the coordinate
system changes.
• Device coordinates are defined relative to some point external to the subject and fixed with respect to the measuring device.– Advantage: head locations can be compared between different experiments
and subjects.– Disadvantage: head location needs to be tracked.
Understanding coordinate systems
![Page 13: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/13.jpg)
In SPM8
• Before co-registration– MEG sensors are represented in head coordinates in
mm.– EEG sensors can be represented in any Cartesian
coordinate system. Units are transformed to mm.
• After co-registration– MEG sensor representation does not change. The head
model is transformed to head coordinates.– EEG sensors are transformed to MNI coordinates.
Understanding coordinate systems
![Page 14: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/14.jpg)
Epoching
Definition: Cutting segments around events.
Need to know:• What happens (event type, event value)• When it happens (time of the events)
Need to define:• Segment borders• Trial type (can be different triggers => single trial type)
Note:• SPM8 only supports fixed length trials (but there are ways to
circumvent this).• The epoching function also performs baseline correction (using
negative times as the baseline).
![Page 15: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/15.jpg)
Filtering
• High-pass – remove the DC offset and slow trends in the data.
• Low-pass – remove high-frequency noise. Similar to smoothing.
• Notch (band-stop) – remove artefacts limited in frequency, most commonly line noise and its harmonics.
• Band-pass – focus on the frequency of interest and remove the rest. More suitable for relatively narrow frequency ranges.
![Page 16: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/16.jpg)
Unfiltered 5Hz high-pass 10Hz high-pass
45Hz low-pass 20Hz low-pass
Filtering - examples
10Hz low-pass
![Page 17: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/17.jpg)
Average reference
EEG – re-referencing
![Page 18: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/18.jpg)
• Re-referencing can be used to sensitize sensor level analysis to particular sources (at the expense of other sources).
• For other purposes (source reconstruction and DCM) it is presently necessary to use average reference. This will be relaxed in the future.
• Re-referencing in SPM8 is done by the Montage function that can apply any linear weighting to the channels and has a wider range of applications.
EEG – re-referencing
![Page 19: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/19.jpg)
EEG
MEG
Planar
Eye blink
Artefacts
![Page 20: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/20.jpg)
Artefacts
• SPM8 has an extendable artefact detection function where plug-ins implementing different detection methods ca be applied to subsets of channels.
• Presently, amplitude thresholding, jump detection and flat segment detection are implemented.
• Plug-in contributions are welcome.
• In addition, topography-based artefact correction method is available (in MEEGtools toolbox).
![Page 21: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/21.jpg)
In the 1870s Sir Francis Galton (1822-1911), became the first scientific sportsman. He derived the common facial features of winning horses by photographically superimposing heads of race-winning thoroughbreds. In addition to its innovation to sports, this is a first in the extraction of common features and blurring of noise.
Encouraged by his horse racing success Galton went on to identify the common physical features in the faces of violent criminals and murderers of the 1880s. He hoped to be able to detect potential violent offenders before they committed their crimes. He superimposed photographs to obtain composites that, in this case, turned out to be nothing out of the ordinary.
Averaging - horses, once again.
![Page 22: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/22.jpg)
Galton, 1880s
![Page 23: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/23.jpg)
Kilner, in prep. 2009
Robust averaging
![Page 24: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/24.jpg)
Robust averaging
• Robust averaging is an iterative procedure that computes the mean, down-weights outliers, re-computes the mean etc. until convergence.
• It relies on the assumption that for any channel and time point most trials are clean.
• The number of trials should be sufficient to get a distribution (at least a few tens).
• Robust averaging can be used either in combination with or as an alternative to trial rejection.
![Page 25: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/25.jpg)
So that’s how we got to this point
![Page 26: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/26.jpg)
Time
Quiz
What is the crucial difference between M/EEG and fMRI from the point of
view of data analysis?
![Page 27: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/27.jpg)
How can we characterize this?
?
![Page 28: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/28.jpg)
• Joseph Fourier (1768-1830)• Any complex time series can be broken down into a series of superimposed sinusoids with different frequencies
Fourier analysis
![Page 29: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/29.jpg)
Original
Different amplitude
Different phase
Fourier analysis
![Page 30: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/30.jpg)
Fre
quen
cyWavelets
![Page 31: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/31.jpg)
Wavelets – number of cycles
![Page 32: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/32.jpg)
Unweighted averaging
Robust averaging
Robust averaging for TF
![Page 33: Pre-processing and the role of horses in the history of M/EEG Vladimir Litvak Wellcome Trust Centre for Neuroimaging UCL Institute of Neurology.](https://reader035.fdocuments.in/reader035/viewer/2022062516/56649e5f5503460f94b59ace/html5/thumbnails/33.jpg)
Thanks to:
The people who contributed material to this presentation (knowingly or not):
• Stefan Kiebel • Jean Daunizeau• Gareth Barnes• James Kilner• Robert Oostenveld• Hillel Pratt• Arnaud Delorme• Christian Hesse• Laurence Hunt
and all the members of the methods group past and present