Task 4 Flashcards
What is an MEG?
- used to detect tiny magnetic fields generated from the weak electric impulses, transmitted between brain cells
- related to ERP
- the electrical current associated with synaptic activity produces small magenetic fields that are perpendicular to the current (measures via SQUIDs)
- MEG traces can be recorded and averaged over a series of trials, to obtain event-related fields
- use a neuromagnetometer
What are SQUIDs?
- Superconducting Quantum Interference Devices
- pick up magnet fields generated by electrical currents in the brain
- the magnetic fields are transmitted to the SQUID by means of a superconducting flux transformer
- samples offer a range of locations: the distribution of electrical currents inside the brain are able to be accurately calculated
What is Femto Tesla ?
- unit for magnetic fields
- 1/10th billion the strength of earth´s magnetic field
What is are the measurements of EEG and MEG?
EEG:
- direct measure of activation
- electrical current stemming from synaptic activity
- precisely coincides with neural activity
- from sulci and gyiri
MEG:
- direct measure of activation
- magentic fields perpendicular to direction of electric current
- precisely coincides wuth neural activity
- only from suli
What is the difference between MEG vs. EEG ?
- MEG is better in locating, where the particular activity is occuring (= less distortion) -> MEG and brain tissues are transparent to the magnetic field (! not the case for EEG)
- MEG only measures the tangential currents (even when noise occurs)
What is more sensitive EEG or MEG ?
- EEG is able to more reliable pick up deeper sources in the brain (that might be radially oriented)
- MEG only displays surface parallel neurons
What are frequencies?
- low frequency oscilliations
> from larger neuronal populations
> show large, synchromised amplitudes
> thea, delta - high frequency oscilliations
> from smaller neuronal assemblies
> show smaller amplitues due to higher desychnronisation in underlying neuronal activity
> beta, gamma
What are the similarities between EEG and MEG?
- both have a high temporal resolution
- both have a limited spatial resolution
- both require the person to sit upright
What is the relationship between oscillations and MEG? What is the relationship between oscillations and EEG?
- ## in adults the amplitude of normative EEG oscillations lies between 10 and 100 uV
What are frequency bands?
- delta band (1-4Hz)
- Theta Band (4-8Hz)
- Alpha Band (8-13Hz)
- Beta Band (13-30Hz)
- Gamma Band (36-44Hz)
What are pros and cons about MEG?
+ same temporal resolution as ERP, but more reliable in detecting the source
+ non-invasive
- flow must be parallel to the surface of the scull
- to be effective, a magnetically shielded room is required
What happens during sleep?
- Delata Bands
- theta bands
What happens during activation?
- beta band replaces alpha bands
- gamma bands = associated with brain activation
What is the difference between frequency - amplitude - phase?
- frequency and amplitude are analysed through spectral analysis
- frequency (wie oft)
- amplitude (wie stark)
What are applications of MEG?
- attitudes
- affective priming
- social categorisation
- stereotyping
- cortex muscle coherence
- action-viewing and mirror neurons
- clinical applications (epiolepsy, tumors)
How are MEG and attitudes related?
- P3 can assess attitudes -> N170
- sensitivity to contextual inconsistency
- used to measure implicit attitudes
- oddball paradigm
what is the relevance of power?
Alpha power asymmetry index
- investigates frontal symmetry
- derive from subtracting the natural log of the lest hemisphere power value from the natural log of the right hemisphere power value
- lnR - lnL
- positive value = greater right activity
- negative value = greater left activity
How are MEG and social categorisation related?
a study investigated the affective congruency effect (investigates social cognition + priming)
-> post priming causes fast categorisation, which can be explained through the proximity of congruent primes and targets in a semantic network
What is a time-frequency analysis?
- developed because spectral analysis provides information about the frequency composition of EEG ossciliations but cannot give information , when frequency shifts occur
- STFT (short time Fourier transform): for computation of a Fast Fourier transform (FFT) based time-dependent spectrum = spectrogram
- Wavelet analysis: allows a more adaptive time-frequency approach affording flexible resolution -> EEG signals are seen as shifted and scaled mathematical functions
How are MEG and stereotyping related?
- intergroup attitudes and goals influence facial perceptions
- early perceptual bases may be contributing to downstream racial prejduice and stereotyping
what are Delta bands?
- 1-4Hz
- low frequency, high amplitude inhibitory rhythm
- sleep, proximity of brain lesions
How are MEG and affective priming related?
- Affective congruency effect:
> an affective target word is categroised in terms of valence
> more quickly, when preceded by prime words of the same valence (congruent trials) - categorisation is facilitated due to the proximity of congruent primes and targets in a semantic network
- suggests the locus for the effect in the evaluative categoriation process
- LRP
- N2
What are Theta Bands?
- 8-8 Hz
- low frequency, high amplitude
- mostly sleep, but 2 types during wakefulness
What are Alpha Bands?
- 8-13Hz
- relaxed wakefulness, cognitive inactivity
- greatest amplitude over posterior regions
- different apha subbands (low - suppression/ upper - desynchronisation)
What are Beta Bands?
- 13-30Hz
- high frequency, small amplitude
- symmetric fronto-central distribution
- replaces alpha rhythm due to cognitive activity
- increased excitattory activity coming with focused attention, diffuse arousal
What are Gamma Bands?
- 36-44Hz
- high frequency, small amplitude
- attention, arousal, object recognition
- directly associated with brain activation
- reflect large scale integration + synchrony among widely distributed neurons
What are spectral analysis
- based on the notion that any oscillatory activity can be characterisde by the sum of different sinusoidal waves with distinct frequencies and amplituedes
- = A method to provide inofmration about the frequency composition of EEG oscillations
- FFA (= fast fourier transform): coefficients indicate the strength of the siganl at a given frequency, in order to estimate the contribution of different frequencies
