TASK 4 - MEG Flashcards
MEG
= measures the magnetic signals generated by the brain
- detect the magnetic fields generated from weak electric impulses transmitted between brain cells
- right-hand rule: direction of the magnetic flux outside of the head is determined by the direction of the current within a group of neurones
- MEG used when interested in accurate time measurements (less distorted)
- -> EEG might be better for detecting deep sources of currents
- combination of MEG and/or EEG with fMRI to pinpoint where and when brain activations occur
neural source
- electrical activity of neurones produces small magnetic fields that are perpendicular to the current
- femtotesla range: one ten-billionth of the size of the Earth’s steady magnetic field
- signals mainly arise from the fissures/grooves of the cortex (sulci)
methods
- neuromagnetometer
- helmet-shaped: cover whole scalp, complete magnetic field pattern can be measured simultaneously without moving the instrument
- covers large area of head with 306 SQUIDs at 102 measuring sites
methods
- SQUIDs
- magnetic fields are detected using highly sensitive superconducting quantum interference devices (= SQUIDs)
- transmitted to the SQUID by superconducting flux transformer
- sensors are immersed in liquid helium at -269C
- located close to the head (3cm) –> placing closer to the brain would increase the signal to noise ratio (if superconductors could work at higher liquid-nitrogen temperatures) –> less bulky insulation 1.5cm from the brain
methods
- sensor units/measuring sites
- sensor units are equipped with three transformers that provide independent measurements of the magnetic field in the x, y, and z directions
a) gradient coils: two transformers, record derivate of the radial magnetic field in the x and y directions
b) agnetometer coil: measures the z-component
methods
- flux transformers
- are housed in the concave base of a helium dewar flask that surrounds the head
methods
- room
- room is made from several layers of aluminium and Mumetal (= alloy of mainly iron and nickel that has such a high magnetic permeability that external magnetic fields are trapped in it)
- try to yield the room inside from contamination of external magnetic fields (= noise)
inverse problem
= identify which currents in the brain are responsible for particular MEG signals, using only information about the magnetic-field patterns
inverse problem
- solving the problem
- computer makes an initial guess where the dipole might be + uses five parameters to characterise the current dipole
a) three parameters for position: 3D space
b) one for its orientation: only currents that are tangential to the nearest point on the surface of the brain produce external magnetic fields
c) one for its strength - computer calculates the external magnetic field that these dipoles would produce –> compares the computed field with the measured field
- repeat calculation with the dipoles at different positions
- until calculated and experimental results match as closely as possible
- based on assumption that the brain is approx. spherical and its active areas can be adequately represented by a single or multiple dipoles
multi-dipole models
= two or more regions are active, have time-varying source strengths
- magnetic field depends on the position and strength of the dipoles + extent to which the neurones in the different regions fire at the same time
- important for interpreting the complex field pattern that is produced
minimum current estimate
- gives the most probable distribution of the currents in the brain calculated according to the concept of minimum norm
- another way of interpreting MEG measurements
- can be used without making any specific assumptions
MEG
- advantages
- similar temporal resolution (better than a millisecond)
- superior spatial resolution than EEG/ERPs: magnetic signals are minimally distorted by organic tissue
MEG
- disadvantages
- MEG device requires a room that is magnetically shielded from external magnetic fields: because magnetic fields generated by the brain are extremely weak
- detection only if that flow is oriented parallel to the surface of the skull
- -> some current that originate deep inside the brain are more radially oriented (use EEG)
oscillations
- thalamic, thalamocortical + cortical networks are assumed to play a key role in rhythmical EEG (MEG) activities
- thalamus important for pacing of rhythmical activities
- thalamus oscillations activate firing of cortical neurones (implicated with alpha, beta, delta waves)
oscillations
- delta band
= 1-4Hz; low frequency, high amplitude inhibitory rhythm
- sleep, proximity of brain lesions + tumours, during anaesthesia
- diminish with increasing age
oscillations
- theta band
= 4-8Hz; low frequency, high amplitude
- mostly sleep
- 2 types during wakefulness
1) widespread scalp distribution linked to decreased alertness (drowsiness) + impaired information processing
2) frontal-midline distribution and associated with focussed attention, mental effort + effective stimulus processing - generator: ACC; septo-hippocampal system, cingulate cortex
oscillations
- alpha band
= 8-13Hz, amplitude between 10-45 μV
- relaxed wakefulness/ cortical “idling”/ cognitive inactivity
- greatest amplitude over posterior regions (esp. posterior occipito-temporal + parietal regions)
- alpha blockage/desynchronization: greatly diminished by eye opening, sudden alerting, mental concentration
–> attenuated when alertness decreases to level of drowsiness but then also decrease in frequency
Different alpha sub-bands are functionally dissociated
Lower alpha (8-10Hz) desynchronization (suppression) has been associated with stimulus and task-unspecific increases in attentional demands
Upper alpha (10-12Hz) desynchronization has been linked to processing of sensory-semantic information, better semantic memory performance & stimulus-specific expectancy
oscillations
- beta band
= high frequency, small amplitude (10-20 μV)
- symmetric fronto-central distribution
- replaces alpha rhythm during cognitive activity
- increased excitatory activity coming with focused attention, diffuse arousal + vigilance
oscillations
- gamma band
= high frequency, small amplitude
- attention, arousal, object recognition, top-down modulation of sensory processes
- directly associated with brain activation
- reflect large-scale integration of + synchrony among widely distributed neurons (esp. in states of diffusely increased vigilance)
- gamma bursts occur within periods of theta phase
oscillations
- sampling
- extent to which the digital signal under investigation accurately reflects the physiological (analog) signal completely depends on the sampling rate
- sampling rate should be at least twice the highest frequency present in the signal under investigation
oscillations
- spectral/frequency analysis
= estimate contribution of various frequencies to measured EEG signal
oscillations
- time-frequency analysis
= shows when in time, frequency shifts occur
- short-time Fourier Transform (STFT): compute FFT-based time-dependent spectrum (= spectrogram)
- EEG signals viewed as composite sine waves with varying frequencies
- -> wavelet analyses: more adaptive approach, affording flexible resolution
- EEG signal viewed as shifted + scaled versions of a particular mathematical function
applications
- attitudes
- P3: increases when a given stimulus represents a category different from the preceding stimuli
a) not sensitive to subjects’ explicit reports about their attitudes (does not rely on self-reports) - -> experiment: compared truthfully and falsely reported attitudes
b) pictures of white faces more evaluatively discrepant from a negative context - -> experiment: showed white faces, black faces + positive images in context of negative image
- -> white elicited larger P2 + N2 than black faces –> responses to white faces were more evaluatively discrepant from the negative context
applications
- affective priming
- affective target words processed more quickly categorised when preceded by prime words of same valence (positive or negative)
- results from conflict during the response output stage, rather than spreading activation effects within semantic network
- under conditions where congruent trials were as likely/ more likely than incongruent trials, lateralised readiness potential (LRP) elicited by prime words showed that people activated response (before target appeared) suggested by the prime
- incongruent prime targets showed larger N2: trying to overcome initial prime-driven tendency to classify as congruent
applications
- face perception
- intergroup attitudes + goals can affect the way we see faces
- N170: reflects initial process of recognising that an object is a conspecific (earliest stage of social cognition); might be sensitive to higher-level social/motivational factors
- -> experiment: whether social categories lead people to see ingroup and outgroup members’ faces differently
a) no intergroup competition: favour own group members + are indifferent to outgroup members –> larger N170 for ingroup
b) intergroup competition: enhanced processing of outgroup faces as they may be threatening/ otherwise noteworthy –> larger N170 for outgroup - -> effects of individual differences, social goals and situational factors associated with the processing of ingroup and outgroup faces
applications
- social categorisation
- gender and race are differentiated very quickly (before N170)
- -> experiment: oddball task in which images were (in-)consistent as a function of gender and race
- negative polarity between 65 and 165 ms in parietal regions –> represent attention to overall features of a face that are anticipated by top-down processes
applications
- stereotyping
- people activate gender categories very early as they evaluate new information about a person
- P3/LPP amplitude enhanced for sentences containing definitional as well as stereotypical incongruencies (independent of overt judgement of grammatical + syntactical correctness)
- larger N400 when sentences violate gender stereotypes/social knowledge
applications
- self-regulation
- initial conflict monitoring: activity in dorsal ACC, monitors ongoing responses for conflict (plays a role in regulation of racial bias)
- –> experiment: stereotype inhibition task
- ERN always larger for incorrect than for correct responses –> related to ACC (ACC sensitive to unwanted stereotype-driven response tendencies)
- occurred implicitly + operated independently of the regulative control process - Regulative mechanism: lateral PFC, which strengthens the influence of intentional responses (play a role in regulating racial bias)
- -> experiment: compared truthfully and falsely reported attitudes
- when people worry about coming across as racist, they are less sensitive to conflict monitoring
- -> smaller ERN in response to conflict
- people with liberal political ideology more sensitive to conflict monitoring
- -> larger ERN