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MN: Functional Imaging Summary (MED-BMS25)
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Summary of the course MED-BMS25. All the lectures are in this summary, you should be able to pass the exam with only this summary.
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MN: Functional ImagingLecture 1
On the right you can see several techniques with their
temporal and spatial resolution. It also shows the
degree of immobility.
EEG basics
This technique measures electrical potential differences
in different parts of the brain. They measure the post-
synaptic potential because this potential lasts much
longer. They put electrodes on the scalp and measure
tiny potentials which they amplify. Nyquist frequency
will be helpful in digital sampling which has a high frequency (at least twice as much as the brain signal
frequency) so that everything of the signal of interest is visible. But why not always use high sampling
rates? This is because it produces a lot of data which is not always necessary.
The measures can be done bipolar or unipolar. With bipolar
you measure different parts of the scalp and you combine the
measurements to know the measures in the middle. With
unipolar you only measure the exact place of the scalp. With
both techniques you measure activity from the whole brain
and not only close to the source you want to investigate.
When neuron populations fire synchronously, you will see high and low amplitudes with slow
frequency measurements. When they don’t fire at the same time, you see high frequency and only low
amplitudes.
If all the neurons are superactive at the same
time locally, this person will have a seizure at
this part. When this happens over the whole
brain, this person will have a seizure over the
whole brain.
The 10-20 system: you measure at the nasion
and the inion as a starting point. At 10 or 20%
instances you place the electrodes. This will be
done in a 3D way.
You can work with several electrodes, e.g.
wearable electrodes that you can carry home and when you sleep. When you work with more
electrodes than 20 or so, they use caps where the electrodes are already placed. You have the 32- and
64-, 128- and even 256-channel systems.
You can combine EEG and fMRI systems where you shield the electrical systems from the magnetic
field of fMRI. You get a lot of artefacts in the EEG recordings, but you can clean them up afterwards
because the gradients change in a very regular fashion.
NIRS uses light that is sent into the scalp and gets picked up again so you get information from the
oxygenation of blood (there is a difference of light absorption between oxygenated and deoxygenated
blood, oxygenated absorbs more light). The light doesn’t get very far into the brain and the spatial
resolution is not very high. This can be combined with EEG.
,There are new developments in wearable EEG which can measure the brain activity during activities
and at home.
In-ear EEG are ear plugs that are developed to measure neuronal activity in the ears (before this wasn’t
possible to do). In this way more and more of the head can be measured.
Intracranial EEG & ECoG will bring in electrodes in the brain (only in clinical cases such as epilepsy).
The electrodes in the brain or grids on the surface of the brain will measure the electrical activities of
the brain which will have a way better signal than the electrodes on the skull.
Lecture 2
EEG measurements
In EEG they measure voltage differences over time. You can visually inspect these waveforms to give
you an indication for cognitive or physiological processes.
You can also look at evoked activity where you stimulate the brain and
look what happens in certain regions. When you do this a couple of times
and combine all the different responses (sensory, cognitive or motor
events), you will get an averaged event-related potentials (ERPs). Every
positive and negative deflection is coupled to a certain process (e.g.
higher perceptual process or working memory encoding). This will be
explained in more detail.
Fourier transform
You can segment the whole spectral frequencies in different bands
of frequencies (gamma, beta, alpha, theta, delta) which might give
you an indiciation for what is going on in the brain. You always see a
mix of frequencies in the normal spectral frequencies. You use
Fourier transform where you segment the complex signal into
several sines and cosines. In this way you separate the time and
frequency component. With these frequencies you know where in
the brain is more activity, this is called a topoplot. You can
also use a time-frequency plot where you see increases in
different bands (for instance the theta band from 6-7 Hz is
present after 500 ms).
The different sleep oscillations
Ripples – gamma – beta – sigma/spindles – alpha – theta –
delta – slow – infraslow – ultradian – circadian – weekly –
circalunar – annual bands. The frequency bands are all
nested into each other (the faster oscillations are often grouped by the slower ones). The slow
oscillations are mostly exogeneous (so caused by the environment).
When you sleep, you have different sleep cycles. Within the sleep cycles you have clusters (nesting
behavior) and certain oscillations that happen in the spindles. There are ripples that are grouped within
certain phases of the sleep spindle.
In the figure you can see a slow oscillation with the peak at 0 s. 1.5 s
after the peak of the slow oscillation, you will see a frequency increase
at 12-13 Hz which are sleep spindles. So the sleep spindles are nested
in this slow oscillation. If you now look at the sleep spindle, the fast
ripples are grouped within certain phases of the slow oscillation.
,Sleep deprivation
In sleep you also have circadian oscillations and annual oscillations. The cirdadian oscillations have a
down phase when you sleep and then an up phase when you are awake. It is synchronized by daylight.
This is called process C. The annual oscillations will change during the time of the year. This means that
we wake up later during the winter and wake up faster during the summer.
The sleep pressure builds up during the day and this will be high at the
end of the day. When you go to bed, this pressure will go down. This
is called process S (it is defined by behavior, when you wake up).
When you don’t sleep, the sleep pressure builds up and you get sleep
deprivation. If we measure slow wave activity of a normal night or a
night when someone had sleep deprivation, you will see that the
person with normal sleep will have high wave activity at the beginning of the night, but this will go
down. The person with sleep deprivation will have much higher wave activity at the beginning and thus
higher activity during the night (although it will also go down).
Microsleep episodes when you doze away during daytime shows theta waves (slowing down of the
frequency waves) in the EEG.
Combined EEG/fMRI shows vigilance measurements where you can compare the alert activities to the
sleepy activities and look where the differences are. These signals show differences within patients
that were awake and ones that were sleep deprived and thus sleepy and you could see differences in
brain activity at many regions. This was also done in patients that were sleep deprived, but still alert
and ones that were sleep deprived and sleepy, this also gave a lot of brain activity differences. So,
when you are sleepy and do such an experiment, this can really alter the results.
Functions during sleep
Endocrine function is regulated, immunological function is build during sleep, memory consolidation
happens during sleep, metabolic function is regulated, emotional processing happens during sleep,
dreaming happens as a sort of simulation of reality to cope with possible threats or situations. When
you don’t sleep enough, all these processes can go wrong.
There is also a clearance function during sleep where a lymph system will flush out the metabolites
that become toxic when building up in the brain. An example is amyloid beta that will eventually lead
to Alzheimer’s Disease. You can even measure sleep activity and look at the slower and faster waves.
In this way you can know how much amyloid beta was accumulated.
Experiments with sleep oscillations
Patients learned a task during the day. They saw an increase in slow wave activity during sleep in the
same area that was active during the task. The increase of this slow wave activity resulted in an
increase of doing the correct task the next day.
Spindle increases in the different areas during sleep thus help with learning successes.
Cued memory reactivation: patients heard some German words and needed to couple these to Dutch
words, these words were then replayed during sleep. After the cue reactivation during sleep you saw
an increase in slow spindle frequency, mostly the theta band which is involved in memory sequences.
1.5 s later you saw an increase in the spindle frequencies. After the sleep, patients could memorize the
words better because of the cue (you saw increases in the theta band when the cue was being played).
Emotional function of sleep: patients had to differentiate between not threatening and threatening
faces. They had to differentiate between them somewhere in the middle ground. Gamma activity was
measured on the night before during rem sleep (gamma activity predicted how well these people could
differentiate and it correlated to the emotional areas of the brain). How more gamma activity during
sleep, how better the emotional differences of the faces could be seen.
, Another example is with sleep deprivation. Sleep deprivation is a risk for developing major depression.
However, when you keep depressed patients awake for a night, the depression went back to
completely normal (the patient was happy), but when the patient went to sleep, the depression went
back to the depressed level. There are other depressed patients that did not profit from sleep
deprivation because they had microsleep episodes that could be measured by EEG.
During sleep you dream which is interpreted as a simulation of reality (threats or social situations). In
this way you can try out new behaviors in a safe environment (develop new strategies).
Fast frequencies during sleep
When you measure brain activity during sleep: people slept during the night and were awakened
several times while being recorded with EEG. Every time they asked whether the patient had dreamed
or not and whether they could recall the dream. They found that less slow frequencies were present
in posterior areas, the more they would experience a dream. The more fast frequencies were present
in the posterior parts of the brain, the more likely they were to experience a dream. It was even
possible to see the fast frequencies (yellow-reddish in a brain picture) in certain areas (e.g. fusiform
face area) so that they knew what type of dream they had (in this case they dreamed of other faces or
characters)
Lucid dreaming
During rem sleep you have rapid eye movements. During lucid dreaming you can intentionally move
your eyes from left to right when asked to. Therefore you know that the person is in a dream but can
control it now. The EEG stays at a low frequency. The activity of real hand movement and dreamed
hand movement can be measured. The brain area during dreamed hand movement was way smaller,
but in this way they still can know which hand was moving during the dream (this uses EEG and fMRI).
Lecture 3
Different sleep stages and oscillations
The measurements for sleep are separated in 30 s bins which are called epochs. The different phases
are wakefulness, stage 1-4 (non-REM) and REM. This system is called the standardized manual.
The American Academy of Sleep Medicine (ASM) also updated this standardized manual by measuring
arousals, respiratory cardiac, movement events, etc. The ASM stops at stage 3 and then goes to REM.
We need three types of signals: EEG (cortical signals), EMG (muscle signals), and EOG (eye movement
signals).
EEG signal: there are mainly alpha, beta, theta, delta waves and sleep spindles. Alpha is any signal
between 8-13 Hz (cycles/sinusoidal waves per second). The amount of waves per second is being
counted and then you know which kind of wave it is. Beta is higher than 13 Hz, theta 4-8 Hz, delta 0.5-
4 Hz, sleep spindles 12-16 Hz.
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