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Summary Introduction to Neuroimaging
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Introduction to NeuroimagingAcademiejaar 2020-2021
Rosanne De Waele
1. Animal Research
1.1. Why discuss animal Research?
• Human cognitive neuroscience is heavily influenced by animal research
• Human neuroimaging methods are less precise (lower spatio-temporal resolution)
You can’t put neurons in a human head
• We often need to relate our results to animal models for comprehensive view
The neuron
• Neuronal activity
− Sodium-potassium pump: located in the membrane, Sodium (NA+) out and potassium (K+) in.
But the pump pumps more NA+ out, than K+ in. This gives a negative resting potential
− Neurotransmitters open NA+ or K+ channel. This gives an excitatory or inhibitory stimulation
− Based on the summed inputs (from other neurons), the electrical membrane of the neuron
rapidly rises and falls.
→ Action potential: a change in the electrical balance
− The Action potential travels along the axon and contributes to activating the next neuron…
1.2. Selected Technique
Measuring and manipulating neuronal activity at different levels
• On a scale from small to large:
A. Recording and inducing neuronal activity: recording and
inducing electrophysiological activity just outside the cell(s)
→ related to action potentials
B. Optogenetic imaging: Manipulating cell function with light via
genetically modified neurons
C. Pharmacological manipulations: inducing receptor agonists
and antagonists (manipulating the synaptic cleft); changing
re-uptake, synthesis, break-down
D. Local field potentials (LFPs): measuring the summed
dendritic synaptic current in the tissue (not action potentials such).
Similar to the first one.
The summation of the pre-synaptic input
E. (intracranial) EEG and fMRI (“Neuroimaging”)
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, F. Behavioral observation
1.2.1. Recording and inducing neuronal activity
• Activity patterns of neurons and neuron clusters provide insights into a region’s function
A. Recording neuronal activity
• Microelectrodes (tip 1-10 µm) can isolate activity of a single neuron: voltages
generated in the extracellular matrix (not within the neuron itself) when an
action potential is generated in the cell (“spikes”). Multiple ones → several
recordings from the same region
It receives the summation of action potentials of the exact moment → gives the
ups and downs (spiking activity) (green= average)
• Carrier device mounted on skull; electrodes are moved down through the
target area until well-isolated neuronal activity is observed (supported by stereotactic reference
frame)
To find the exact location of the neuron, you have to listen to the neuron
• Example: Single-cell recordings from dopaminergic neurons in the
substantia nigra during reinforcement learning
− Conditioning task: food pallet, monkey grasp the food, neurons
react to that
When the monkeys are conditioned: when the light goes on, the
neurons already start to fire. The neurons is not specific for food,
but the predicting of it.
When the food is delivered. The neurons don’t ‘care’, because the
have already been fired/ predicting.
But there is a decrease in firing when the reward is predicted, but
does not occur
• These changes in neuronal activity lead to varying dopamine release in
the target regions (e.g., nucleus accumbens)
• This model of complex neuronal coding of reward information became
the basis of human motivation studies using fMRI and PET → very
similar to human mapping
• This can be used in freely moving animals, this can stay on for weeks. Rats, only movements.
Monkeys you can also record computer tasks
B. Inducing neuronal activity
• The same set-up can be used to stimulate the neurons in the vicinity of the electrode which can
provide insights into the function of an area and its projection regions
• Example: Electrical stimulation of the septal area (Olds & Milder 1954)
− Electrodes were placed in the septal area of the rat forebrain, part of the dopaminergic
system
− The electrodes induced electrical pulses every time the rats pushed a certain lever in their
box (instrumental conditioning)
Thought the electric simulation had an aversion effect
2
, − The rats “enjoyed” the stimulation instead of avoiding it; some rats even neglected eating
and drinking in favor of the stimulation (~ human addiction, you need more and more
because, the dopaminergic system became less sensitive). They had a very strong urge to
push the button (pleasure centre), they would sacrifice their life, just for the stimulation.
• Demonstration that electrical stimulation of neurons can be used as an operant reinforcer (and
evidence for the existence of some kind of “pleasure center”)
• Functionally, the stimulation of the septal area leads to dopamine release in the nucleus
accumbens, similar to the effects of primary rewards (previous slide)
C. Optogenetic imaging
(manipulating the cell, with light you turn a cell on/off)
• Method to control and monitor the activities of individual
neurons in living tissue - even in freely-moving animals
• Genes for light-activated ion channels (opsins) are
introduced to a population of cells by an engineered virus
• Not ready for humans, it’s playing with DNA-code, injecting
viruses
This is a fast method and more spatial precise
1.2.2. Pharmacological manipulations and lesions
Allow causal conclusions regarding the function of a region or neurotransmitter system
Pharmalogical manipulations (and lesions) → chemical : causal, you can block a brain area
(irreversible)
• Less precise: only region, not a single neuron
• Example: Manipulating dopamine transmission during effort-based choice (Salamone et al. 1994)
− T-maze with a high (high food) and low (less food) reward density arm; one group had to
cross a barrier to reach the food in the “high food” arm (effortful choice)
− The rats mostly chose the ‘high food” arm, even those in the barrier group
− If you block the dopamine receptor, rats didn’t choose for the “high food” arm with barrier
Dopamine depletion (6-hydroxydopamine) and dopamine receptor blocking (haloperidol) in
the nucleus accumbens abolished these high effort choices
They didn’t want to spend the effort on facing the barrier
• Disrupting dopaminergic signaling did not alter reward evaluation, but biased the decision
process towards investing less effort (same for blocking anterior cingulate)
1.2.3. Local field potentials, EEG and fMRU
More indirect than single-unit recordings, but comparable with human data
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,A. Local field potentials (LFPs) and EEG
Advantage: which EEG signals are
actually reflecting. To know what
EEG correspond on the neuron level
Evoked EEG on the brainsurface
Level below: LFP: cluster of
neurons. To get a global signal of a
field of neurons; Related to actual
neuroactivity
LFP rises and falls, correlate almost
exact with the EEG on the surface
There are difficulties with EEG by humans. You have the scull and the neurons activate different
areas in the brain. You get a more blurred picture
Timing very precise. Not random activity.
Human → monkey: red and blue seems very different. But difference in EEG is always relative.
Mechanism is the same, but reversed voltage
B. Local field potentials and fMRI
fMRI is not neuroactivity, but how
much oxygen is at a certain moment
in a certain region. It’s related
Some stimuli were short, other long.
Blue: neuroactivity. At some point, it
ends. If you make it longer, the
neuroactivity extend.
Red: hemodynamic, which in principal
follows the same structure, but it’s
delayed. (more related to oxygen)
More spikes when something is happening
1.3. Notes on comparability
1.3.1. Comparability in terms of function
Different research questions require different animal methods
• Rodents in the lab (mostly mice and rats)
− Rodent models are highly valuable for cognitive neuroscience especially for processes related
to “old” brain structures (brainstem, basal ganglia, hippocampus)
− Not comparable to humans on the neocortical level and more limited regarding complex
cognitive tasks (rats can’t do a stroop test)
• Cheap, easy in terms of breeding, handling, training
4
, − Primate models are more comparable on the neocortical level and thus more valuable for
investigating higher cognitive functions (e.g., monkeys can perform comparable computer
tasks)
− Still, there are neuroanatomical differences on the cortical level, which is why comparative
studies often use the expression: “monkey homologue” of a region
− Much more time consuming and
challenging to breed and train primates
1.3.2. Comparability in terms of methods
A. Animal research procedures (mostly invasive)
• Closer to the actual neuronal substrate (firing rate, LFPs, receptor binding, etc.)
• Provide insights into causal relationships (pharmacological intervention, lesions, post-mortem
histology, ...)
B. Human research procedure (mostly non-invasive)
• Recording / inducing neuronal activity: only as part of therapeutic approach (e.g., parkinson’s
patients)
• Pharmacological manipulations: mild pharmacological manipulations (healthy) and treatment
(patients)
• Lesions: “virtual lesions” TMS (healthy); real lesions (e.g., stroke); therapeutic lesion (e.g.,
epilepsy)
• EEG and fMRI: in healthy population and patients
[Clinical trials in medicine and psychiatry are special and not discussed here]
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2. Peripheral measures
2.1 Peripheral nervous system
• Broad extinction in autonomic nervous system
1. Sympathetic (SNS)
− Activating the entire body in case of fight or flight
5
, 2. Parasympathetic (PNS)
− Slow, effect 1 organ at a time
− Rest and digest
− Less important in this kind of research
→ interactions of these 2, this is interesting for research
These interactions are explained below
2.1.1. Skin conductance
A. What do we measure?
Skin conductance reflects fairly pure sympathetic NS activity
(fight/flight)
Relatively independent of the parasympathetic NS
→ if skin conductance goes up, it typically reflect arausal
• Arousal stimulates sweat glands (cools down body)
• Sweat is conductive and changes the ElectroDermal Activity
(EDA)
• It’s a very rough measure of general arousal
No difference between + and - arausal
(Mostly interpreted as an index of arousal intensity in affective or cognitive processing (not
positive vs. negative valence))
B. How do we measure?
• Two electrodes are applied to the volar surfaces of the fingers or palm of the non-dominant hand
(dominant hand is used for the task)
• A very small constant voltage is flowing to one electrode to the other
The resistance changes depending on whether your hand is wet from the sweat
More sweat productions, lower resistance, higher conductivity
• Typical units are microsiemens (μS) or micromhos (μmho)
C. Different measures
• Skin conductance level (SCL): a tonic measure of skin conductance during a task, large
interindividual differences (absolute values not very meaningful, but interesting for block
manipulations); baseline activity
6
,• Non-specific skin conductance response (NS-SCR): spontaneous phasic changes in electrical
conductivity, nothing to do with
specific events
• Event-related skin conductance
response (ER-SCR): a phasic response
to a certain event (stimulus-locked);
most interesting for experiments
Quite slow: latency: 1-3 sec
D. Example
• Response to active events
Skin conductance is often used in fear conditioning research to
detect the magnitude of a person’s fear response to conditioned
stimuli
Different phobia groups: differentiation between snake-phobia
person. Highest skin conductance-response for the stimuli snake. Spider-phobia highest skin
conductance-response for the stimuli spider…
• Decision making
Skin conductance predicts response in decision making in good performance
Divided the participants in good, bad and average task-performance
People with highest skin conductance-response to these disadvantage decisions, they did the
tasks best. Moderator role of skin conductance.
2.1.2. Pupillometry (eye-tracking, more behavioral; lecture of his own)
A. What do we measure?
• Pupil size changes based on luminance, but also reflects
fluctuations in the autonomic nervous system
• Fight-flight → larger pupil
Parasympathetic→ constriction of the pupil
• Underlying mechanism:
The system responsible for the pupil dilation is the
noradrenergic system. Located in the neurons in the
brainstem. Above: neuron firing, Below is the pupil
B. How do we measure?
• An infrared light source illuminates the eye, and an infrared-sensitive camera captures the
contrast between dark pupil and light iris.
• When luminance is kept constant, changes in pupil size can reflect cognitive processes during an
experimental task
• Avoid luminance differences between conditions in your experiment!!
C. Example
• Cognitive surprise in performance monitoring (Braem et
al. 2015)
Classic conflict task: judge central target (where is the
opening), ignore distractors
7
, Pupil size measured after congruent and incongruent trials
- pupil response was lowest for the congruent
- highest after incongruent & unexpected
2.1.3. Cardiac activity
A. What do we measure?
• The heart transports oxygen from lungs, as well as nutrients, waste
products, and regulatory substances (endocrines)
• What does the heart respond to most?
Exercise! (has to be controlled during “psychological” experiments)
But also psychological stimuli
• Cardiac cycle: Initiation of cycle via sino-atrial (SA) node (pacemaker), intrinsic rythm of 105 bpm
Slowed down by the Parasympathetic NS, sped up by the Sympathetic NS
• Further signal conduction via atrial-ventricular (AV) node
B. Main methods and measures of interest
1. Electrocardiography (ECG)
• Recording of electrical activity via surface electrodes
• No direct measure of action potentials, but reflects production
and conduction of action potentials in the heart during cardiac
cycle
• Parasympathetic NS as well as the sympathetic NS
a. Heart rate (HR)
− Based on RR interval, beats per minute (bpm)
− HR = 60/(RR interval in seconds)
− Sensitive to emotional processes
− EXAMPLE: Affective processing (Bradley et al. 2012)
▪ Heart rate drops for emotional events (especially negative ones)
▪ In contrast to skin conductance (elavated for emotional events)
→ goes opposite directions, but are related
Not very interesting for this kind of research
b. Heart rate variability (HRV)
− Treat measure: some people have a lower heart rate variability, that means the
interval is more stable. Doesn’t mean that their heart beats faster or slower than
the average
− Changes in the time intervals between consecutive heartbeats (RR interval);
termed Interbeat Intervals (IBIs)
− Reflects general measure of the influence of the Parasympathetic NS on the
heart
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, 2. Impedance cardiography/impedance variation (ICG)
• Total electrical conductivity of the thorax and its changes over time
→ summation of the electrical potentials measured on the skin of the chest (Thorax)
→ measure of resistance: if the blood flow is good, you have less resistance. Vica versa
• High-frequency current is flowing between an electrode pair (via aorta)
Collect info whatever the heart produces in electrical activity (passive)
• Impedance (measure for change in electronic activity) changes are picked up by a second
pair
• Returns Impedance pulse wave (IMP) and the ICG curve (1st derivative)
• Not common in hospitals, but for this research it can be very interesting
• First peak in green and first peek in red. Takes place in a different moment.
→ resistance after the hear conducted
If you subtract this: you get PEP. This is the time between depolarization between the
neurons that leads to the conductions of the big
chambers. And then the actual pumping, muscular
activity.
If this period is short: high performance heart
pumping ability. Fast translation from neuron to
muscular activity
• Gives more sensitive insight in how much arousal there was at that moment
a. Pre-injection period (PEP)
− Time interval from the electrical stimulation of the ventricles to the opening of
the aortic valve (~Pumping performance)
− Thought to reflect the effect of the Sympathetic NS on the
heart
− EXAMPLE: HRV and PEP in auditory attention (Giuliano et al.,
2018)
▪ high HRV and short PEP reflect selective attention (you
would be better at the task) (EEG)
▪ both Parasympathetic NS and Sympathetic NS influence attentional processing
2.1.4. Respiration
• Respiratory activity
Measured via belt around the chest that expands when you breathe in
Relationship between respiration and heart rate
A. Different measures of interest
• Respiratory rate (most relevant for cognitive neuroscience, the others are not so important)
• Inspiration time
• Expiration time
• Inspiration to Expiration ratio
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, EXAMPLE: respiration in cognitive tasks
- effect of working memory and inter trial
interval on respiration
Cognitive task (working memory), breathing +
heart beat. Respiration increased by 2 things
1. Memory load
2. Speed of the paradigm (short/long interval)
- respiration rate increases with cognitive load
an paradigm
2.1.5. Muscle activity
Electromyogram (EMG)
• Measures ‘electrical field changes’ due to muscle action potentials (~ allows us to be in close
contact with the motor cortex)
• Always on striated muscle (e.g. different from the cardiac muscle discussed earlier), needs
stimulation to contract (motor nerves)
A. Different measures of interest
• Startle blink ~ probe for surprise and negative valence
• Facial EMG ~ channel of emotion expression
• Pre-response motor EMG ~ partial errors
• [EMG during motor TMS: lecture 07.10.2020]
• EXAMPLE: startle blink
Air puff (+ manipulation)→ startle effect
Startle is bigger for very arousing event (especially unpleasant)
CAN DIFFERENTIATE BETWEEN + AND – VALENCE
• EXAMPLE: facial EMG
Participants rated objects (garage or kitchen) with left or right response (conflict, if handle was
left, you need to act with right hand)
Grip of the object could be compatible or incompatible with response → no conflict: you
zygomaticus muscle would move/activate a little bit
Conflict: corrugator muscle would be activated a little bit
• EXAMPLE: motor EMG
Simon task: respond to stimulus color and ignore the position
(conflict)
Surface electrodes to record activity of finger muscles
EMG reflects intended but not executed responses (partial errors) if
the persons instinct was to push the button congruent with the position, but repressed it.
2.2 Why?
• Immediate reactions of the peripheral nervous system (e.g., arousal) can complement behavioral
and neuroimaging data
• They are cheap, mostly univariate, and straightforward to analyze
• Although most of the methods are relatively old (e.g., used in emotion research), there is a new
interest in basic and applied neuroscience today (e.g., affective processing of effortful tasks)
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