Task 4 Flashcards
Most ERP experiments in social cognition and affective science (SCAN) are built upon a basic behavioural task design, which typically involves the timed presentation of stimuli and the recording of behavioural responses (e.g. on a computer). But compared with behavioural experiments, ERP tasks often include
more trials (e.g. 30–50 per trial type) and longer intertrial intervals (2–4 s).
Filtering
algorithms are applied to the analog signal to attenuate frequencies that are not of interest
Aligning and averaging
EEG signals are aligned to an event of interest (e.g. a stimulus onset), EEG activity unrelated to the processing of the event will vary randomly across trials and therefore will average to zero, whereas EEG activity elicited by the event will vary according to properties of that event and will stabilize when averaged across trials of the same type
2 classes of ERP waveforms are of interest in SCAN:
1- Stimulus-locked waveforms:
arise in response to a specific stimulus, such as a visual image or auditory feedback, reflecting some aspect of perceptual or attentional processing. The earlier, the more likely it reflects an automatic / reflexive response (i.e. N1 or N100, …)
- Often reflect some part of perceptual or attentional processing
- It is assumed that the earlier the deflection emerges following stimulus onset, the more likely it is to reflect an automatic or reflexive psychological process
- Naming conventions refer to the polarity and the ordinal position or the approximate time at which the deflection peaks
2- Response-locked waveforms
useful for examining mechanisms associated with the formation and regulation of a behavioural response (i.e. error-related negativity, …).: Aligning EEG epochs to the moment when a behavioral response is made
- useful to examine mechanisms associated with the formation and regulation of a behavioral response
- named according to their polarity and the type of response (e.g. error-related negativity; error-positivity
Cacioppo discovered that the P3 (or P300) amplitude increases
a given stimulus represents a category different from that of preceding stimuli
example: The oddball paradigm used here made use of the evaluation of positive vs. negative words (in a negative or positive context) and found that when a target word was evaluatively inconsistent with context words, such as when a negative word appeared within a series of positive words (positive context), a pronounced P3 was evoked.
This affective congruency effect is
response conflicts when the response associated with the prime conflicts with the response called for by the target
Previous findings have shown that an affective target word is categorized in terms of its valence (positive or negative) more quickly when preceded by prime words of the same valence (i.e. congruent trials) than by prime words of the opposite valence (i.e. incongruent trials).
Due to their excellent temporal resolution, ERP methods offer the best approach to test many questions central to social cognitive and affective neuroscience
the lateralized readiness potential (LRP
a dynamic measure of motor cortex activation associated with preparation and initiation of behavioural responses
Face perception:
the N170 component responds to faces.
Research has found differences in N170 concerning the categorization of social groups and race (larger N170 on ingroup and Black faces compared to outgroup faces. If outgroup is perceived as a threat, the processing of the outgroup is enhanced).
- N170 can reveal differences in the extent to which an individual perceives another as a fellow human
- Sensitive to higher level social/motivational factors
ERPs can inform the process through which faces, once encoded, are categorized according to relevant social groups
the oddball task
The oddball paradigm is an experimental design used within psychology research. Presentations of sequences of repetitive stimuli are infrequently interrupted by a deviant stimulus
the self-regulation of responses to stereotyped targets involves the coordination of two complementary processe
- An initial conflict monitoring mechanism, subserved by activity in the dorsal ACC, which monitors ongoing responses for conflict (between goal intentions and a race-biased tendency)
- A regulative mechanism, associated with activity in lateral prefrontal cortex (PFC), which responds to the conflict by strengthening the influence of intentional responses to override an unwanted tendency
Advantages of ERP
- ERPs are one of the only direct measures of brain activity as it occurs in real time =high temporal
- The ability to measure psychological processes independently from, or in the absence of, any behavioural response
- Cheaper
- Data collection environment that may be less impactful on subtle social and affective processes of interest
- Participants sit upright during data acquisition
o More closely mimics how people typically interact in the social world than does a supine position
o Certain psychological processes, especially those pertaining to approach motivation, do not operate in the same manner when people are lying down compared to when seated or standing
lower. cost
Disadvantages of ERP
- Limited spatial resolution
o ERPs detect only neural activity of sufficient strength to be measurable at the scalp, rendering them insensitive to activity in subcortical structures
o The skull and scalp act as a spatial filter on neural activity, reducing the spatial resolution of the signal recorded with scalp electrodes
It is nevertheless possible to estimate the neural generators of ERPs using source localization procedures that consider the orientation and strength of a dipole signal, as measured at multiple sites across the scalp
Nonetheless, you can also use it in combination with fMRI for better data collection - Interpretational Issues
- The neural source of a particular ERP component is likely involved in multiple psychological functions and therefore a one-to-one mapping of a psychological construct onto a physiological indicator can never be assumed
- Readers are cautioned against assuming that, for example, the N2 associated with an ingroup attention bias in social categorization tasks reflects the same neural source or represents similar information processing operations as the prominent N2 often seen in tasks involving response conflict or inhibition
Magnetoencephalography
= used to detect the tiny magnetic fields generated from the weak electric impulses transmitted between brain cells
Non-invasive
Good time resolution
Use a neuromagnetometer
The magnetic fields that are generated by electrical currents in a subject’s brain are detected using highly sensitive superconducting quantum interference devices (SQUIDs), placed at various points on the surface of the scalp. The magnetic fields are transmitted to the SQUID by means of a superconducting flux transformer. The magnetic fields must be sampled over a range of locations so that the distribution of electrical currents inside the brain are able to be accurately calculated
+As with EEG, MEG traces can be recorded and averaged over a series of trials to obtain event-related fields (ERFs).
+MEG provides the same temporal resolution as with ERPs, but it can be used more reliably to localize the source of the signal and therefore has a higher spatial resolution.
+Magnetic fields (unlike electrical signals) are not distorted when they pass through all the layers (brain, skull, …)
Limitations of MEG:
1) It can only detect current flow if it is oriented parallel to the surface of the skull. For this reason, the neurons that can be recorded with MEG tend to be located within sulci.
2) Magnetic fields are very weak, meaning that to detect them, the person has to be in a toom that is completely shielded from all external magnetic fields, including the Earth’s magnetic field. MEG sensors (SQUIDS) must be held in large containers at a temperature below 4 degrees Kelvin.
inverse problem
Inverse problem: how can we identify which currents in the brain are responsible for particular MEG signals, using only information about the magnetic-field patterns and the shape of the brain?
to solve the inverse problem
To solve the inverse problem, researchers assume that the brain is approximately spherical and that its active areas can be represented by single or multiple current dipoles. Then the PC gets to work:
- On the basis of the measured distribution of magnetic fields, a computer first makes an initial guess as to where the dipoles might be
- The computer then calculates the external magnetic field that these dipoles would produce
- It compares the computed field with the measured field, before repeating the calculation with the dipoles at different positions until the calculated and experimental results match as closely as possible
b) Minimum current estimate technique: rather than assuming that the magnetic fields are generated by individual dipoles, this technique gives the most probable distribution of the currents in the brain, calculated according to the concept of minimum norm.
- Can be used without any assumptions about the way in which the currents are distributed in the head or whether they occur at the same time
MEG versus other techniques
- The magnetic fields measured outside the head with MEG are much less distorted than the electric potentials on the scalp measured with EEG
- For most info: monitor EEG and MEG at same time, but can’t really do this yet
o MEG (pro): only measures those currents that are oriented tangentially to the surface of the brain (in the sulci), even when several areas of the brain are active at the same time.
o EEG (pro): measure currents deep inside the brain or that are radially oriented well EEG and MEG get their results from partially different neurons (sulci and parallel vs. gyri and radial) and therefore give partially different information
o MEG has a much higher temporal resolution than PET or fMRI
o However, measurements on the brain with MRI, fMRI and PET provide useful constraints to the neuromagnetic inverse problem
Delta band (1–4 Hz)
- Low frequency sleep in healthy humans and neurological pathology
- In adults: delta power increases in proximity of brain lesions + tumours + during anaesthesia + sleep
- There is an inverse relationship between delta activity and glucose metabolism in pathological and normal people subgenual prefrontal cortex (low sugar consumptions means high delta activity)
- Delta is the predominant activity in infants during the first 2 years of life
o Then the faster alpha and beta bands increase linearly across the life span
Inhibitory rhythm
Theta band (4–8 Hz)
- Prominently seen during sleep
- Wakefulness: 2 different types of theta activity in adults
1. Widespread scalp distribution and has been linked to decreased alertness (drowsiness) and impaired information processing
2. Frontal midline theta activity: frontal midline distribution and has been associated with focused attention, mental effort, and effective stimulus processing
o Anterior cingulate cortex (ACC) = generator of frontal midline theta activity positive correlations between theta current density and glucose metabolism - Generation of theta oscilliations:
o Septo-hippocampal system
o Cingulate cortex
Gating function on the information processing flow in limbic regions
Alpha band (8–13 Hz)
- Healthy adults: amplitude between 10 and 45μV
- Relaxed wakefulness
- Greatest amplitude over posterior regions, particularly posterior occipito-temporal and parietal regions best seen during resting periods, eyes closed
- Diminished rhythm by eye opening, sudden alerting, and mental concentration = alpha blockage / desynchronization
- Can be attenuated when alertness decreases to the level of drowsiness accompanied by a decrease in frequency
- Role: unknown, maybe visual system functions emerging in the absence of visual input?
- Evidence suggests that different alpha sub-bands may be functionally dissociated
o Cognitive tasks, lower alpha desynchronization (suppression) has been associated with stimulus and task-unspecific increases in attentional demands
o Upper alpha desynchronization appears to be task-specific + linked to processing of sensory-semantic info, increased semantic memory performance, and stimulus-specific expectancy