The Neurophysiological Biomarker Toolbox (NBT)

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Questions & Answers

I don't understand the question about the time-frequency plot. How do you know which regions correspond to the deflections in the signal? I tried all week to understand it and I didn't. Can you explain it to me?

It might be simpler than you think. You identify an oscillation. Then you know that one full cycle of a 10 Hz oscillation is a positive followed by a negative deflection that all together lasts 100 ms, right?

Now, if the oscillation last 1000 ms, it is 1 Hz
If the oscillation last 25 ms, it is …what?

Those frequencies you just indicate at the appropriate time points and frequencies in the x-y coordinate system

Also we are still a bit in the dark about the sink and source story, especially related to the figure with EPSC, it looks like a schematic overview of a pyramidal cell with the comment that in inhibitory state the current goes the other way around. From what we understand the sink is caused by influx of Na+. But we don't really understand what this source and 'current' is.

It’s probably more accurate to say that the sink is caused by a neurotransmitter that causes the opening of channels, which allow for Na+ to flow into the cell. Thus, there is a current sink because positive charge disappears from the extra-cellular space and into the neuron.

With inhibition, however, inhibitory neurotransmitters will cause Cl- ions to flow into the cell. From the perspective of ‘current’, movement of negative charge in one direction is the same as positive charge moving in the other direction. Thus, you will see that the arrows are reversed.

There is a mechanism of generation of neural oscillations presented, we don't really get what it's about and how it works.
So, you should only understand the following mechanism, which should be explained in the text field of the ppt slide: Pyramidal cells and interneurons are mutually connected. When you measure the firing probability of these two neurons (right figure), you notice that pyramidal (pyr) cells fire before interneurons (int). So, the sequency is:
1. Pyramidal neurons fire and connect to interneurons
2. Interneurons are excited and connect to pyramidal cells,
3. …which are then inhibited for a period of time
4. When the inhibition wears off, pyramidal neurons can fire again, starting all over from (1).
This is the cycle of events causing oscillatory activity.

What is the advantage of the normalized channels to the absolute channels? We only got results if we normalized our data, but we don't understand why

Generally speaking, because the amplitude integrated between 1 and 30 Hz (in absolute measures) can vary 3–fold between two subjects, you can reduce the variation among subjects by normalizing. All subjects will then have 100% between 1 and 30 Hz. Reduction of variance is an important determinant of whether an effect reaches significance or not. So, this is a likely reason for your effect to be more significant for normalized measures.

Wat wordt er precies bedoeld met spatial filtering en hoe werkt dit?
'Spatial filtering' filters signals that come from a specific location (“space”). A good example is to remove signals generated by the eye movements. Spatial filtering requires many channels and assigns different weights to those channels. You can also use spatial filtering to extract signals from a specific location. This is what you have done when ICA identifies a spatial topography corresponding to an alpha source. It differs from frequency filtering, which is applied to individual channels/signals, e.g., to remove the 50 Hz noise (by low-pass filtering at ~45 Hz) or slow movements related to breathing (e.g., by high-pass filtering at ~1 Hz).

Bij normalized spectra staat als drawback: Effect is not isolated to one frequency band…  maar wat wordt daar mee bedoeld (en waarom is dat dus een nadeel?)?

If the sum of the power in different frequency bands (delta, theta, alpha, beta) should add up to 100%, and a task doubles the amount of alpha without any absolute changes taking place in other frequency bands, then the alpha will go, e.g., from 40% to 80%, which means that the other frequency bands are forced to share 20% instead of 60%. Thus, you will see significant changes in the other bands, even though only alpha activity changed.
Another example would be that the brain reduces its activity with 50%, which in the absolute spectra would reveal a significant effect in all bands, but in normalized spectra in none of the bands…

How can I see from the ICA topography whether it is a bad channel or an artifact?

Current sources in the brain unavoidably will produce potentials at many electrodes instead of just one. Thus, it is a clear sign of a noisy electrode (e.g., not well attached) if the ICA does not identify correlations with the signals in the neighboring electrodes. That correlations are localized to a single electrode is seen by a very local pattern, as opposed to a smooth gradient covering a larger area.

Am I right when I say that: you only mind-wander when your default network is activated. And that your default network also is activated when you are going to bed, to store your memories of that day. And because of your stored memories you can mind-wander?

No, that’s not correct in the sense that the entire idea of a link between mind-wandering and the DMN is still very speculative. There are only very few research articles presenting convincing data, but it is an appealing working hypothesis, which you are also allowed to use. Thus, it is very well possible that day-dreaming involves other networks as well, or that DMN activation does not always reflect day-dreaming. Your last question is correct though. I don’t see how you could mind wander without reactivating stored memories. Hope this is not too vague. It’s the state-of-the-art in this young field of science…

Bij het verschil tussen MRI en EEG wordt het volgende punt genoemd 'Greater specificity? One voxel in fMRI generates multiple oscillations with distinct functions' Ik snap niet wat precies een ‘voxel’ is en wat het nadeel van MRI precies is.

A voxel is just a cube of brain tissue. In a 0.5 x 0.5 x 0.5 cm^3 cube of cortex, many processes can take place, but fMRI only measures the blood-flow changes caused by those activities.

In het college wordt gesproken over temporal resolution en spatial resolution. Aan de hand van de uitleg heb ik nu het volgende als definitie bedacht. Kunt u kijken of deze definities juist zijn? Temporal resolution: hoe snel het een verandering weergeeft → bij EEG meet je het directe proces dus bij het uitvoeren van een taak zie je meteen een verandering, terwijl dat bij fMRI langer duurt omdat je het indirect meet.

Yes, that's part of the answer. Also, at how short time intervals can you distinguish two events.

Spatial resolution: hoeveel details het kan weergeven / hoe nauwkeurig het kan meten

This can actually have two meanings: (1) How accurately can you locate something (an anatomical structure or activity), (2) How closely spaced can two activities be while still being able to separate them as two. See also my notes in the text field below the ppt slide.

Over de dipool bij EEG. Ik heb nu begrepen dat de oriëntatie van een dipool afhankelijk is van de locatie van de dipool. Gyrus → radial oriëntatie en sulcus → tangential oriëntatie. Klopt dit? En wat wordt er bedoeld met: The same activation on opposite sides of a sulcus will change the polarity.

That's correct. And if you go to the other side of the sulcus, the arrow/dipole will change direction by 180 degrees.

De slides hierna gaan over: “A paradox in the lateralization of the visual ERP”. Kunt u nog uitleggen wat daarmee bedoeld werd, want dat begreep ik niet in college.

It was known that stimulating left visual field should activate right occipital cortex, but the largest ERP was measured in over the left hemisphere. This is because even though the dipole was located at the pole of the right hemisphere, it was oriented such that it produced a larger signal over the left hemisphere.

I don't understand what you mean by 'Superficial and deep-layer activation may lead to opposite EEG polarity'.

As illustrated on the slide, the scalp EEG signal changes polarity with the two neuron-activation scenarios. When excitation is in the superficial layers, the scalp potential is negative. When excitation is in the deeper layers current runs in the opposite direction in the apical dendrites and a positive scalp potential is recorded. Note the signs of the charges indicated in the different cortical layers.

courses/q_a.txt · Last modified: 2012/12/20 11:07 by Klaus Linkenkaer-Hansen
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