College aantekeningen
College 1 notes
- Instelling
- Erasmus Universiteit Rotterdam (EUR)
Notes of the first lecture about EEG en ERP
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Voorbeeld 2 van de 5 pagina's
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Voorbeeld van de inhoud
Lecture 1 – Introduction to EEG & ERP by Marijn van Vliet.EEG measures the difference in electrical potential between 2 points on your scalp. Electrode
on the mastoid bone because a reference location is needed. Mastoid bone is a decent neutral
reference with little brain activity, but quite close to the other sensors in the cap. Difference
between voltage measured at each sensor in the cap and reference electrode(s).
Here you see the difference in electrical potential between sensor and reference location.
Scale in micro volts (really tiny differences in electrical potential).
Peaks: eye activity blinks. Eyes are magnets. These are picked up by EEG.
Other peaks are muscle activity and not the brain. Because muscles are also driven by
electrical signals. When participant sits relaxed in the chair, the EEG will look cleaner. Blood
circulation is also seen in EEG.
Rythms in the brain
Delta: in adults in slow-wave sleep. Also seen normally in babies.
Theta: seen when very relaxed or meditation.
Alpha: emerges when eyes closed and in relaxed state.
Beta: associated with movement (across motor cortex) and active thinking.
Gamma: coordination between neurons?
Summary 1
EEG measures the difference of electric potential
Between: one or more electrodes placed on the scalp.
Versus: one or more reference electrodes placed on a “neutral” reference location.
EEG records mostly sources of interference:
Eye movement and blinks
Muscle movements
Heart beats
Any nearby electromagnetic activity
EEG also records brain activity:
Some rhythmic activity can be seen by “eyeballing” the EEG (used in hospitals)
Many types of activity only revealed by data analysis (cognitive science). For
example: Event Related Potentials (ERPs)
, Event Related Potential Analysis
Everytime the card you picked shows up, you get a little spike in your EEG signal P300
potential. We can detect this potential. You can’t see this with eyeballing, so we need data
analysis.
Frequency filters
Lowpass filter: will only keep waves who are slower than the given threshold. For example:
only keep waves slower than 2hz.
Highpass filter: will only keep waves who are faster than the threshold.
Bandpass filter: frequency range. E.g. 2-10hz.
Epochs: snippets of EEG. Cut-out seconds of EEG data.
For all the cards epochs were selected. To isolate the data is to create an average Event-
Related Potential = average. The brain activity unrelated to it will be different every time a
card is shown. These differences over time will level out because sometimes negative and
sometimes positive = 0. Only retain the portion of signal which is consistently the same every
time we present the stimulus.
Comparing ERP’s
Baseline period: time leading up to presentation of the stimulus. Some start positive and some
negative. Baseline correction: all of the stimuli need to start on 0.
P300 effect: by choosing one of the playing cards we split the game into 2 groups. The chosen
card versus the other cards. We no longer distinguish between the other cards.
ERP component naming scheme
P = positive
N = negative
Number indicates milliseconds after onset or peak number.
Communication flow: Axon of one neuron is connected to dendrite of another neuron.
Neurotransmitters are released, which are ionic charged particles. They are received by
receptors on dendrites. This is how communication flows. If we have enough neurons firing at
the same time, in the same direction all the electrical charges add up and then we can measure
in the order of micro volts a little tiny potential difference.
Pyramidical neurons are organized in columns. They are close to the cortical surface. It’s a
large group of neurons all facing the same direction. All firing at the same time can add up
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