task 4 Flashcards

1
Q

pros MEG

A
  • Same temporal resolution as ERP
  • More reliable localization
  • Magnetic fields are not distorted as they pass though brain, skull and scalp
  • Useful tool in neurosurgery: identify focus of epileptic seizures and location of tumors
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2
Q

Con’s MEG

A
  • Detect current flow only if flow is oriented parallel to the surface of the skull -> neurons can be recorded mainly if they are located in the sulci
  • Magnetic fields are extremely weak: SQUIDS to detect them
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3
Q

set up MEG

A
  • SQUIDS placed at various points on the surface of scalp
  • Helmet-shaped magnetometers: with 206 SQUIDs at 102 measuring sites
  • Each of 102 sensor units is equipped with 3 transformers that provide measurements of the magnetic field B
  • 2 transformers: gradient coils: record in x and y directions
  • 1 magnetometer coil: record z component
  • Carried out in a room made of layers of aluminum and mumetal (iron and nickel): external magnetic fields are trapped in it, shielding the room inside
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4
Q

SQUIDs

A
  • To detect the brain’s weak magnetic fields, the sensors = Super-conducting quantum interference devices, are encased in large, liquid-helium-containing cylinders that keep them colder than 4 degrees Kelvin
  • can be placed no closer than 3cm from the brain
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5
Q

Inverse problem

A

-How to identify which currents in the brain are responsible for particular MEG signals using only info about the magnetic-field patterns and shape of the brain?

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6
Q

Calculating source of magnetic fields

A

Assumption made: brain is approximately spherical, active areas can be represented by single or multiple current dipoles

  • Computer guesses where the dipoles might be
  • Calculates externa magnetic field that these dipoles would produce
  • Compares computer field with measured field
  • Repeat calculation with dipoles at different positions until calculated and experimental results match as closely as possible
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7
Q

Femto-Tesla

A
  • measurement of magnetic fields in the femtotesla (fT, 10–15 tesla) range is important for applications such as magnetoencephalography
  • only sensors capable of detecting these very small fields have been based on low-temperature superconducting quantum interference devices operating at 4.2 kelvin
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8
Q

Mu-metal

A
  • MEG Carried out in a room made of layers of aluminum and mumetal (iron and nickel): external magnetic fields are trapped in it, shielding the room inside
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9
Q

Fourier transform

A

• Takes a time-based pattern, measures every possible cycle, and returns the overall cycle recipe (amplitude, offset, rotation speed for every cycle)

Example smoothie:
-filters must be independent, complete and combine-able

  • start with time-based signal
  • apply filters to measure each possible circular ingredient
  • collect full recipe, listing amount of each circular ingredient
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10
Q

Power

A

= square of the amplitude (easier to observe, because amplitudes are often very similar to each other)
-Used to quantify contribution to measured EEG signal

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11
Q

2 major classes of ERP waveforms

A
  • Stimulus locked and response locked waveform

- The earlier the deflection, the more likely it is to reflect an automatic/reflexive psychological process

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12
Q

Quantifying ERPs

A
  • waveforms are computed and then scored for analysis
  • Determine time window in which a component of interest emerges
  • Measure average voltage within window for each subject
  • Alternative: automated peak-picking
  • Peak latency may be quantified
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13
Q

attitude and evaluative processes - P3

A
  • amplitude increases when stimulus represents a category different from that of the preceding stimulus
  • Target word was inconsistent with context words -> P3 was evoked
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14
Q

Measure of implicit attitudes
P2
N2

A
  • Pictures of white faces elicited larger amplitudes of 2 components: P2 and N2
  • Response of white faces were more evaluatively discrepant from the negative context than black faces
  • The higher the amplitude, means more processing
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15
Q

Affective congruency effect

A

-Affective target word is categorized in terms of its valence (positive or negative) more quickly when preceded by prime words of the same valance (congruent trials) than by prime words of the opposite valence (incongruent trials)

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16
Q

N2 - affective priming

A
  • Conflict monitoring function of dorsal anterior cingulate cortex (ACC)
  • Conditions invoking conflicting response possibilities consistently lead to enhanced N2 amplitude
  • N2 was larger on incongruent than on congruent trials
17
Q

face perception N170

A
  • Occipital-temporal scalp regions
  • Reflect early configural/holistic encoding of a face in visual perception
  • Reflects multiple sources, e.g. fusiform gyrus
  • Can reveal differences in the extent to which an individual perceives another as a fellow human
18
Q

Mixed findings N170

A
  • Larger amplitude to racial outgroups/ingroup/no differences
  • Outgroup may be threatening, which may lead to enhanced processing
  • Explicit instructions to attend to racial outgroup faces increased N170
19
Q

stereotyping P3, N400

A
  • enhanced P3/LPP to definitional as well as stereotypical incongruities
  • larger N400 responses when subjects read sentences that are semantically correct but violate gender stereotypes
  • stereotype-based categorizations occur very rapidly
20
Q

Thalamo-cortical networks - EEG

A
  • interactions between thalamic and cortical networks are assumed to play a key role in various rhythmical EEG activities
  • thalamus: key player in generation of alpha and beta
  • thalamic oscillation in 7.5 to 12.5 Hz frequency range have been shown to activate the firing of cortical neurons
21
Q

Local scale and large scale synchronization - EEG

A
  • area of an electrode covers approx. 250.000 neurons
  • synchronization among neighboring neurons: local scale -> higher frequency oscillations
  • neuronal assemblies of distant brain regions: large scale -> low frequency oscillations
22
Q

Delta band (1-4 Hz -> low frequency, how many oscillations we see per second) - EEG

A
  • typically associated with sleep in health humans and neurological pathology
  • increases in proximity of brain lesions
  • mainly an inhibitory rhythm
  • most frequent activity in first 2 years of life
23
Q

Theta band (4 -8 Hz) - EEG

A
  • prominently during sleep
  • wakefulness:
    1) widespread scalp distribution: decreased alertness (drowsiness), impaired info processing
    2) frontal midline theta activity (ACC as generator) -> focused attention, mental effort, and effective stimulus processing
  • oscillation facilitates transmission between different limbic structures: theta activity may subserve a gating function on the info processing flow in limbic regions
24
Q

Alpha band (8-13 Hz) - EEG

A
  • relaxed wakefulness
  • large individual differences in amplitude are not uncommon
  • can be best seen during resting with eyes closed
  • alpha blockage/desynchronization: diminished/abolished band due to eye opening, sudden alerting or mental concentration
  • in cognitive tasks: lower alpha (8-10Hz) desynchronization (suppression): associated with stimulus-unspecific and task-unspecific increases in attentional demands
  • upper alpha desynchronization: task specific attention
25
Q

Beta band (13-30Hz) - EEG

A
  • Alpha & beta increase linearly with age
  • Increase with attention and vigilance
  • Mainly symmetrical frontocentral distribution
  • Replaces alpha during cognitive activity
26
Q

Gamma band (36-44Hz) - EEG

A
  • Attention, arousal, Object recognition
  • Top-down modulation of sensory processing
  • Perceptual binding
  • Directly associated with brain activation
27
Q

Reference electrode - EEG

A
  • Use of average reference
  • Hjorth method/source derivation/ Laplacian transformation: average potential difference between each electrode and the nearest 4 electrodes
  • Choice of reference electrode influences waveform but it is irrelevant for any source localization
28
Q

Sampling rate - EEG

A
  • Extent to which the digital signal reflect physiological signal depends on sampling rate
  • Rate should be twice the highest frequency present in the signal
  • Prevents aliasing
29
Q

Aliasing

A
  • Introduction of spurious low-frequency into the signal

- Occur when signal is sampled at a rate that is too low

30
Q

Ocular artifacts

A

-Essential to use additional channels to record vertical and horizontal eye movements

31
Q

Muscle artifacts

A
  • Can be troublesome for studies interested in gamma activity
  • Use of regression approaches: activity in higher frequencies (50-70Hz) is typically takes as a marker for muscle artifact: variance removed using regression or ANCOVA