Samenvatting practicums Neuro Imaging

EEG SUMMARY
1. To start, type “eeglab” (without quotes) within the MATLAB command window and press Enter


2. We use EEGlab to
• To load the EEG data ‘File’  ‘Load existing dataset’
Sampling rate: samples per seconde. 15Hz = 15x in seconde
Frames per epoch: all samples that are recorded
• Define the electrode locations in ‘Edit’  ‘Channel locations’ voor yes
Blue EEGlab panel  edit  channel locations  ok  next window  Plot 2D  correct?
Dan sluiten  ok in lower right corner in the edit channel info. (yes in interface)

Veranderen x en y: edit channel info window ok  coordinate system  plot 2D

Exacte locatie elektroden: edit channel info window. X is forward, Y to the left, Z upwards.

Na defining electrodes: small plot of channel  plot  channel locations  by name

Oneven getal links, even getal rechts. Zie je elektrode niet in database  masoids (0 Volt).

• look at the EEG time series in ‘Plot’  ‘Channel data (scroll)’
x-as in epoch: latency is de reactietijd (bij eventcode 9)
veranderen x-as: setting  time range to display
Normal time domain: tijd op de x-as en amplitude Y-as
Frequency domain: frequenties x-as en amplitude of power spectrum (amplitude van elke
frequentie) op y-as
• look at the powerspectra in ‘Plot’  ‘Channel spectra and maps’  ok
Veranderen van frequencies: Plot channel spectra and maps frequencies to plot
veranderen  plotting frequency range ook mogelijk om te veranderen  spectral and
scalp map options naar electrodes: on  ok
Rood in hoofd  meeste activiteit
De lijn die het hoogst komt, heeft de meeste power.
• compute independent components in ‘Tools’  ‘Decompose data by ICA’  Niet te kennen
• identify independent components in ‘Tools’  ‘Inspect/label components by map’ ok 
green rectangle
Scalp topographies of componenents, ordered by amount of contribution to the data.
Hieronder zijn 1 en 5 gelokaliseerd bij EOG channels.




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, Eye blinks (1): topography lighting up in blue at frontal EEG & VEOG channels
ECG (heart rate) (3): activity is maximal at mastoid electrode A2
EMG (muscle) (5): high frequency noise that is located mostly at both EOG channels (power
gaat boven 25 HZ ipv dalen)
• Activation of independent components in “Plot”  ‘Component activations (scroll)
Open ook epoch data (S1_EEG-filt_elist_be) door plot  channel data (scroll) 1. Vergelijk
beide EEG’s en zie welke independent component geassocieerd is met artifact met 1.
• remove independent components in ‘Tools’  ‘Remove components from data’  plot
single trails (blue: original, red:reconstructued)  accept  ok
(S1_EEG_filt_elist_be pruned with ICA)
• localize dipoles in ‘Tools’  ‘Source localization using DIPFIT’  ‘Head and model settings’

• Plot dipoles in ‘Tools’  ‘Source localization using DIPFIT’ ‘Component dipole autofit’


3. We use ERPlab for the following steps in the data analysis:
• filter the EEG in ‘ERPlab’  ‘Filter & Frequency tools’  ‘Filters for EEG data’
Y-axis (passband): 1  no suppression (geen filter). 0,5  suppression by 50%, 0  full
suppression. Dit wordt ook wel genoemd als ‘weighting of frequencies’.
Suppress high frequencies: low-pass filter
Suppress low frequencies: high-pass filter
High + low pass filter  band-pass filter (bv. high: 50, low: 150)
Inverse  band-stop filter (notch filter) (bv. high 150, low 50)
Roll-off: steepness of your filter
Octave: doubling in frequencies  van 50Hz naar 100Hz.
(S1_EEG_filt)
• create event lists in ‘ERPlab’  ‘Eventlist’  ‘Create EEG Eventlist’  continue  advanced
(Zie dat channel locations: yes)




Vul in text file ‘eventlist’  apply  save and continue  Event types: code labels  apply
 ok




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