EEG
Electroencephalography
Measures changes in potential
Large amounts of neurons have to be activated (hundreds of thousands)
pass through various tissue —> most often pyramidal cells
Postsynapctic activity at dendrites or cell body
Electric activity behaves like electricity
Potential difference measured by comparing to reference electrode Often: nose, mastoid bones behind ear, chest
Choice of reference electrode influences the signal
Influences Amplitude & Scalp Topographic Distribution
EEG disadvantages
Signal has to pass through various types of tissue à therefore most often pyramidal cells
IPSPs & EPSPs is measured —> indistinguishable, which of both it is
EEG advantages
temporal resolution
Electroencephalogram: measurement
highly sensitive electrodes 32 to 256
attached to head using electrode cap
standardized positions
10-20 system
extended 10-20 system
conductive gel/saline solution: increased skin conductivity
amplification & digitization of signal
active eeg electrodes measured against reference electrode —> reference electrode picks up as little brain activity as possible
offline data analysis
electro-oculogram
simultaneously measured to monitor muscle artifacts from eye movements
EOGV vertical
EOGH horizontal
muscle activity is stronger than brain activity!
variables to describe spontaneous activity of EEG
amplitude —> how strong
frequency —> number of oscillations per second
five physiologically relevant bands
five physiologically relevant frequency bands
Delta —> deep sleep
Theta: falling asleep & high concentration
ALpha: relaxed, awake, especially closed eyes
beta: mental or physical activity
hz frequency bands
Delta: 0,5-3 Hz
Theta: 4-7 Hz
Alpha: 8-13 Hz
Beta: 14-30 Hz
Gamma: >30 Hz
The more calm: slower (low frequency) and high amplitude
EEG data analysis
Raw EEG is averaged
averaged background EEG
averaged Evoked Potential
external and internal events can evoke changes
Segments of potential changes
=Components
P1: early component around 100 milliseconds after visual stimulus.
N1: early component occurring around 100-200 milliseconds, associated with initial sensory processing.
P2: Higher-order sensory processing and feature detection.
N2: Cognitive control & conflict monitoring.
P3 (P300): peaking around 300 milliseconds attention and decision-making processes.
Components are identified by different aspects:
Polarity
Latency
Distribution over the scalp
amplitude
Components: Latency
time between start of stimulus and peak of component
Sequence —> what order the components appear in
exact timing —> The specific latency values of different ERP components.
Components: Amplitude
difference between adjacent extremes
difference between baseline and peak
Approach EEG Analysis
Pre-processing
Epoch selection, baseline correction
averaging, subtraction, grand averaging
visualization
selection of channels, roi, time windows
statistical analysis - t-test, ANOVA, Regression
further analyses e.g. source localisation —> source imaging can combine eeg & mri
pre-processing eeg
automatic artifact correction
manual artifact correction
filtering —> getting rid of signal drift
Software packages used
Brain vision analyzer
BESA
matlab based:
eeglab
erplab
fieldtrip
Mne-python
MEG
Magnetoencephalography
use Magnetometers to measure magnetic currents
cooled down to extremely low temperatures w/ liquid helium —> more sensitivity
makes use more challenging
how does MEG work, what are its limits
active neurons generate small magnetic fields due to flow of electricity
better localization of signals: magnetic field passes through tissue without resistance
but nevertheless a bit weaker for deeper brain structures
radial sources invisible in MEG, only tangential sources produce measurable signal
sensory/exogonous ERP components
evoked potentials
latency = <100 ms
sensory analysis of stimuli
directly follow perceptual stimulus
dependent on physical sitmulus properties
no influence by psychological variables
endogenous ERP components
Latency >100 ms
less closely tied to stimulus
co-vary with psychological factors
surprise
recognition
e.g. p300 component
Examples for endogenous ERP components
Mismatch negativity
p300
slow potential shifts
measured by oddball paradigm
frequent standard tones with rare deviants up to 20%
mismatch negativity = Deviants-standard
reflects brain’s automatic detection of deviation from established pattern
requires no attention for standard tones
detection of rare target stimuli
after sensory processing —> around 300 ms —> positive deflection of eeg signal —> attention
contingent negative variation
observed between a warning signal & expectation of an external stimulus
motor ERPs
directly precedes a motor act
appear esp. over motor cortex
libet experiment —> unconscious brain activity in preparation before conscious intention to move
Oscillatory activity
—> Frequency analysis of the eeg
frequency distribution
power
power spectrum
proportion of different frequency bands in specific temporal window
squared amplitude
strength of an individual frequency value
shows power(energy) in total signal
as a function of frequency at given time point
Brain imaging and causality
brain imaging -> not necessarily causality
shows involvement of brain region in cognitive processes
shows involvement of brain regions associated with ERP component for specific cognitive processes
how to establish causality in brain imaging
reversible brain stimulation methods
e.g. tms
outlook on further methods
voxel-based morphometry
diffusion weighted MRI/diffusion tensor imaging
functional near-infrared spectroscopy fNIRS
TDCS
Eye tracking, pupillometrie
genetic& endocrinologic methods
o neuroimaging analysis method
o compares local concentration of gray matter across entire brain
o commonly used to detect structural brain changes related to psychiatric conditions + aging processes
o taxi driver study
o study the diffusion of water molecules in biological tissues in brain
o insights into microstructural properties of tissues
o investigation of brain connectivity and integrity
fNIRS
functional near-infrared spectroscopy
non invasive
measures changes in hemoglobin concentration
cerebral blood flow through absorption of near-infrared light by hemoglobin
transcranial direct current stimulation
electric current modulates neuronal activity
Last changed2 months ago