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EEG

EEG

electroencephalography

EEG qualities

high temporal resolution, low spatial resolution (because it is affected by the layers of the head)

How do EEGs work? in short

EEG and averaged ERPs measure electrical potentials generated in the extracellular fluid as ions flow across the cell
membranes and neurons talk to one another via neurotransmitters.


In other words, it measures postsynaptic potentials

The forward and inverse problem

Forward: computing the EEG signals on the scalp given a known source configuration; predicting the scalp potentials (EEG data) from known brain activity.
easy


Inverse: estimating the brain sources (location and strength) from the measured EEG signals on the scalp; inferring where in the brain the EEG signals originate.

hard

What is the contingent negative variation?

The period of brain activity related to the preparation for performing an action.

important ERP components

- polarity
- timing

- scalp distribution

- sensitivity to task manipulation

- nomenclatures (pre, peri, post)

C1

p/n depending on where in the visual field the stimulus is
50-70

sensory processing

P1

90-100
sensory/ perceptual preprocessing

N1

170-200
called N170 for faces

perceptual processing, expert recognition, visual discrimination

N2

225-250
object recognition and categorization

N2PC

deployment of covert attention

P3

300
stimulus evaluation, encoding and maintainance

which two components evaluate performance

ERN; event-related negativity (negative)
Pe; error positivity (positive, but after negative response)

LRP

preperation of motor response

Improving methodological rigor in EEG

- Standardize electrode placement, especially reference placement
- Make sure that research has not been conducted before

- multiple comparison correction

- Make sure there is no baseline bias + baseline correction

- sufficient number of trials (or participants)

- remove artifacts (eye movement, muscle movement, noise)

- Keep in mind that different stimuli inherently create different ERPs

- Look at the entire ERP, not just the peak

what is the sampling rate?

The number of times per second the analog signal is converted to digital data. A higher sampling rate captures more data points. (normaly 512 Herz)

what are the three types of electrodes?

- active
- reference

- ground

steps for preprocessing EEG signal

- importing
where raw digital data, which represents the voltage measured over time from each electrode relative to a reference, is loaded into the analysis software or environment to begin the preprocessing sequence


- filtering

Remove unwanted frequency bands.

High-pass filters remove low drifts (attributed to sweat or amplifier issues)

Low-pass filters remove high frequencies (often associated with muscle noise)


- segmentation (epoching)

Dividing the continuous EEG recording into segments time-locked to specific events (like stimulus onset or response)


- baseline removal

Subtracting the average voltage during a baseline from the entire waveform, to remove anticipation activity.


- artifact handling

done with ICA

Examples of things that can cause noise

- bad connection (electrode pop, skin impedance, sweat)
- external electrical noise

- amplifier saturation/ drift

- ocular artifacts

- muscle artifacts

three types of EEG analysis

- time-domain (ERP)
- time-frequency

- frequency

Three rarely discussed issues of ERP

- ERP refractoriness, the time it takes for the ERP to "reset"
- Offset transient, where sudden stimulus offsets elicit their own ERP components (long or short intervals)

- individual differences, e.g., due to unique patterns of brain folding

types of signals

- gamma
- beta

- alpha

- theta

- delta

Mismatch negativety

a negative ERP response when something unexpected occurs

Frequencies of bands

Gamma - 60-30
Beta - 12-30

Alpha - 8 -12

Theta - 8-4

Delta - 4-1.5

Most used amplifier

BioSemi

How does the midline run?

From inion to nasion

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