W3 - EEG Flashcards
What is EEG
Method of detecting neural activity via. electrodes on the scalp. Electrodes pick up small fluctuations of electrical signals from activity of (mostly cortical) neurons
What are the properties of the raw signals picked up by EEG
- Very noisy and might not look like much, but they are systematically related to cognitive processes > Use these signals to learn something about cognition when people perform tasks
What are 2 types of EEG
Scalp: Non-Invasive Intra-Cranial: Measure directly at exposed cortex
Who invented EEG and how
Hans Berger. Detected first EEG with wife’s scalp in 1924.
What is the Alpha Rhythm
Alpha rhythm – When people closed their eyes, - Inconsistent electrical signal varying between 8 - 13 Hz - Used two electrodes (silver wires and later foil), one attached to the front of the head and one to the rear, and recorded the potential/voltage difference.
What are advantages/disadvantages of EEG
Cheap Temporal Resolution Poor Spatial Resolution
How is EEG Recorded: What are the 4 tools
Electrode Cap > Amplifier > EEG Recording Experimental Stimulation > EEG Recording
What are the channels in EEG
10 - 32 - 64 - 128 - 256
How are numbers on the scalp displayed
Odd and Even. Each corresponds. F = frontal P = parietal C = central O = occipital T = temporal
Neurophysiology: Where is the origin of EEG Signal
Post-synaptic potentials (Voltage when NT binds to post-synaptic membrane) > Causes ion channels to open/close, leading to graded changes in potential across membrane Not Action Potential
What can the post-synaptic potential be considered as
- Understood as a small “dipole” (magnet) - Signals from single cells are not strong enough - Many neurons spatially align > summed potentials add up and create the signals we can record
Many neurons spatially align > summed potentials add up and create the signals we can record: What is this called and where is the origin
Pooled activity from groups of similarly oriented neurons mostly comes from large cortical pyramid cells
What is the functional unit of EEG (How many Neurons must be spatially aligned)
The functional unit is >10,000 simultaneously activated neurons
What determines the sign of the recorded potentials
Orientation of the neurons determines the sign of the recorded potentials Some orientations lead to signals which cannot be recorded
What are the limitations of EEG (Neurophysiology)
1.) Biased to Gyri (Sulci harder to detect / masked by gri signals) 2.) Meninges, CSF and skull “smear” the EEG signal > Localisation difficult - INVERSE PROBLEM: one given scalp configuration of signals can have multiple dipole solutions!
What is EEG measured in relation to
In relation to a reference electrode - Reference either a neutral point or average of all scalp electrodes
Typical amplitude of EEG and Steps to make it clear
1.) 10μV to 100μV (Tiny) 2.) Amplified by 1,000/100,000x 3.) Signal is digitalized. Typical sample frequency is 256-1024Hz, but can be >4000Hz 4.) Signal is band-pass filtered to remove the low (<0.5-1Hz) and high frequencies (typically >35-70Hz) because they cannot reflect brain activity.
What is the most relevant step in EEG signal analysis
Finding all the artefacts that are not brain signals! - sweating - electrical noise (“notch filter”) - eye movements and blinks
How does eye movement affect EEG.
- Eye can be regarded as a dipole - Signals originating from the eye will contaminate the signal of interest (And will be much larger)
How do we remove eye movement in signal
- Record eye signal by placing electrodes next to and under the eye to capture horizontal and vertical eye movements - Remove by excluding contaminated trials, or mathematical algorithms, such as ICA
What is wrong with single EEG-trial studies
Far too noisy. Too many variance between sessions from same participants and between participants
What is P and N
Deflection in amplitude. P = Signal < 0 N = Signal > 0
How can ERP be analysized
1.) Peak-amplitude (used in 70%)) 2.) Area-under-the-curve (used in 20%) 3.) peak-to-peak (used in 10%) 4.) on-set of component (ambiguous) No clear rule, and results might differ between measures
Woodman & Luck (1999): What is the signal they used and what did it index.
N2pc (second negativity, posterior contralateral) > index attention Strongest over the posterior cortex contralateral to where the observer is attending
Woodman & Luck (1999): Study Aims
Visual Search Task: Parallel / Serial Serial Fashion: Attention switch from one hemifield to the other, until the target is found . Parallel: Nothing
Woodman & Luck (1999): Study Overview
People to attend one hemifield first by manipulating probability specific colour was target (C75 and C25)
Woodman & Luck (1999): Study Results
Target Absent + C75 v C25: N2pc Target Absent + C75 same C25: No shift Target Present + C75 (Target) v C25: No shift Target Present C75 v C25 (target): N2pc All supported serial search
Gehring et al., 1993: Study Aims
ERN: Whether a cognitive mechanism for the detection of and compensation for errors.
What is the ERN
The ERN is a negative deflection of up to 10μV in amplitude observed at central electrodes ~80-100ms after an erroneous response.
Gehring et al., 1993: Study Overview and 2 Hypotheses
Emphasise accuracy/speed in a Flanker-task H1.) Incongruent displays should lead to more errors H2.) Error detection should only matter in the accuracy condition
Gehring et al., 1993: First Hypothesis supported?
Yes. ERN on incorrect trial in comparison to correct trials (Recorded with EMG)
Gehring et al., 1993: Second Hypothesis supported?
Yes. The ERN was strongest when people emphasised accuracy, and weakest for speed
Gehring et al., 1993: Further study of ERN compensation for errors
Investigated how ERNs of different sizes were related to response parameters, which might in turn be related to correcting/avoiding errors
Gehring et al., 1993: Further study of ERN compensation results
1.) The greater the ERN, the lower the response force > trying to correct for the error 2.) The greater the ERN, the higher the probability to get it right on next trial > successful learning from errors 3.) The greater the ERN, the slower the response on next trial > successful learning from errors
