Meg final

Editor's Notes

• #3: Of couse we could travel very far back in time to trace the origins of EEG and MEG. A reasonable starting point is the end of the 19th century, with the work of a british physician, Richard Caton, who was the first to measure brain electrical currents in animals. He had the top of their head choped and could thus put an electrode on top of the brain and another reference electrode on the skull. And then by connecting a galvanometer (the ancester of the Ampere-meter) he could measure tiny current flows. At that time already, he already described differences in those currents, for instance between sleep and awake states, he also demonstrated that those currents were indeed coming from a living brain since after death, those currents would slowly dissapear. Later on, about 50 years later, Hans Berger, a german neurologist got interested in understanding the mind and is credited for having invented the word EEG. Indeed he was one of first to record and describe variations in scalp electric potentials in humans and described signals such as alpha and beta waves This was more or less the birth of brain electrophysiology, especially in humans and the birth of EEG.
• #4: But as you know MEG is much younger. One had to wait for another 50 years and a little revolution in physics to be able to record the first MEG signal. Indeed, in 1962, during his PhD, the british physicist Brian-David Josephson described the ‘Josephson effect’ (a special case of tunnel effect) which enables some conduction between two superconducting materials seperated by a thin layer of an insulating material, even in the absence of any external voltage. This property is exploited in the so-called Josephson junction whose one of the main application is the SQUID. And the SQUID proved of particular interest to build very sensitive magnetometers. - The SQUID itself was invented by J. Zimmerman, a north american researcher working for the Ford Compagny. - Thanks to the SQUID, David Cohen, at the MIT, significantly improved his MEG device and published the first modern MEG recordings in 1972, one year before the 30 years old Josephson was awarded the Nobel Prize in Physics.
• #5: - And this is how MEG systems look like today. They are made of about 300 sensors covering the whole head. They still involve the SQUID technology. AS it incorporates superconducting materials, it needs to be cooled down to 4°Kelvin (-269° Celsius). This is why there is a large container above the helmet. It contains liquid helium. What is also required so far is the shielded room that prevent the very sensitive sensors from recording noisy signals (we’ll come back to that in a minute). Those shielded rooms can be single-layered or double-layered, passive or active. Active means that they try to compensate, online, for field inhomogeneities. Shielded rooms are made of mu-metal (nickel, iron but also copper and molybden) against static magnetic fields (low frequencies) but also aluminium against high-frequencies. You might be aware that there are ongoing researches in physics to invent new MEG sensors and build new systems that would work at high temperature but this is future… Regarding EEG, systems are also evolving, not only to enable simultaneous recordings with fMRI but as here wireless system did appear recently and some of them even clame to be dry, meaning that you don’t even need to add conducting gel, to be tested…
• #25: Now, the MEG is a little more complex and it is useful to have a quick look inside. Here is the real aspect of the MEG recording system and here is a schematic of the inside of the Dewar. So contrary to EEG, the sensors have fixed position and this the subject’s head location that is fit to the helmet. Inside, the dewar is full of liquid helium and is thermically isolated from the outside thanks to vacuum space all around it.
• #26: There are different types of MEG sensors. In all cases, they use coils that transform the magnetic flux through the surface coil into a tiny electric current whose intensity will be instantaneously compensated and hence measured by the SQUID. This is the amount of compensatory current that is related to the magnetic field and yield the MEG signal. Now with a single coil, we get a magnetometer that measures the local magnetic field directly. Other systems like the one downstairs from CTF is using gradiometers. Here is a 1st order axial gradiometer. Axial because the z vertical axis is radially oriented with respect to the scalp. 1st order because it is made of two coils and thus computes the first derivative of the magnetic flux locally by computing the difference between the two opposite currents generated in each coil. One can even couple gradiometers to compute higher order differences and planar instead of axial gradiometers also exist. Gradiometers are less sensitive to distant sources, meaning that they are both less sensitive to noise from the environment and to deep sources. This is why some MEG systems like the finish Elekta machine do couple magnetometers and gradiometers. The type of sensors depend upon the machine you have. However, there are some mathematical tranformations that enable you to represent your data in one way or another, a bit like Laplacian operators transform the EEG data into maps of SCD.
• #27: Although this is a beautiful technology, what we essentially measure with MEG is noise. Indeed, brain activity generates magnetic fields of the order of a hundred to a thousand fT where Tesla is the common unit for magnetic fields and fT indicates a magnitude of 10-15 T; in other words brain magnetic fields are a billion time smaller than the earth magnetic field. Here are other examples with order of magnitudes: a car passing by 50 meters away creates a magnetic field that is a thousand times higher than the one generated by brain activity. This explains the need for a shielded room and it is a bad idea to enter the MEG room with metal on you. However, nowadays, MEG can be installed in city centers, not far away from MR scanners and it works!
• #29: What are the current sources within the brain that we measure with EEG & MEG ? Given our current knowledge of human brain physiology, signals of interest come from the synchronous activity of groups of neurons that are closed to each other and exhibit a similar pattern of activity. Indeed, a single neuron alone won’t be able to elicit a measurable signal on scalp but a whole population of several thousands who activate synchronously can. In fact, among cortical neurons, pyramidal cells are believed to be the main sources of the EEG and MEG signals. This is because they are roughly parallel to each other and oriented perpendicular to the cortical surface so that when they activate simultaneously, their contributions sum up into a macroscopic current. Finally, these currents reflect synaptic current mostly and not action potentials. This is because action potentials generate currents in both opposite directions along the axons so that the sum of their effects is closed to zero.
• #30: An active neuronal column is thus represented by a parametric model, a dipolar source, whose parameters are the dipole position, its orientation and its intensity, hence 6 parameters. Another feature of the source currents is that, given the size of the head, they happen to be fast enough to consider that there is no propagation delay, from the neurons to the sensors. In other words, the effect of neuronal activity is immedialty reflected on the scalp. This has the important consequence of greatly simplifying the equations one has to solve in order to model how brain sources express on the EEG or MEG sensors. We’ll come back to that in a minute.
• #31: Let’s see now how such a macroscopic source modelled by a current dipole generates EEG and MEG signals repsectively. Starting with EEG, here is the example of a single source. We refer to the synaptic (intra-cellular) currents (the dipolar curent) as primary or source current, to be distinguished with their consequences in the extra-cellular media: the secondary or conduction currents.
• #32: Let’s see now how such a macroscopic source modelled by a current dipole generates EEG and MEG signals repsectively. Starting with EEG, here is the example of a single source. We refer to the synaptic (intra-cellular) currents (the dipolar curent) as primary or source current, to be distinguished with their consequences in the extra-cellular media: the secondary or conduction currents.
• #35: Let’s now consider, as we just did with EEG, how a single source generates MEG signal. Given a source in the brain, its location and moment, the direction of the magnetic field lines is given by the (very well known) right hand rule. In this example, applying the right hand rule, one observe that a tangential source (that is parallel to the scalp surface and hence to the coil) yield to lines (here in blue) that flow through the coil. At the contrarery, radial sources such as the green one on the figure, generate lines that do not flow through the coil. This raises two questions: does MEG have a different sensitivity to tangential sources compare to radial sources, in contradistinction with EEG ? How this gradiometer which, I remind you, measures the difference in the magnetic field amplitude along the z-axis between the two coils… how does this difference can inform us about the source ?
• #36: Well, to answer the first question, indeed MEG is much more sensitive to tangential sources than to radial ones. However, to be fair with MEG, it is quite unlikely, given the non-spherical shape of the head and the folded nature of the cortex that a source would be strictly radial with respect to all sensors. As you can see on this toy example, MEG is not completely blind to a radial source… This map gives me the opportunity to emphasize that what is represented here is the amplitude of the magnetic field on the radial axis. In fact, the difference in magnetic flux in the case of gradiometers as here. Also importantly, you notice that this topography is much less blurred than for EEG. The color code is not that important here. What is important is how to interpret this map. And for 1st gradiometers it is quite convenient since a bipolar pattern like this is a strong indication in favor of a single dipole lying inbetween the two poles.
• #37: The Biot & Savart Law gives the magnetic field intensity generated by a dipolar source of size dl, at position r’ and intensity I at a sensor location r. What’s important to note is that the magnetic field, its intensity or norm since we are dealing with vector quantities here, is proportional to the inverse of the square of the distance between the source and the sensor. As a consequence: MEG is indeed less sensitive to deep sources but also, this law clarifies how MEG works. If one knows the distance between the two coils of a single gradiometer, the difference in magnetic field between the two coils will inform us about the dipole intensity, location and orientation (provided you have several sensors). Finally, you notice that the magnetic field does not depend upon tissue conductivities, contrary to EEG. The magnetic equivalent is the permeability. However, all head tissues are amagnetic and their permeability is well approximated by the vacuum permeability mu0.