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Meg final
- 2. A brief history From the electrical nature of brain signals … Richard Caton 1842 - 1926 Hans Berger 1873 - 1941 1875: R.C. measured currents inbetween the cortical surface and the skull, in dogs and monkeys 1924: H.B. first EEG in humans, description of alpha and beta waves Alpha actiity ~ 200 μV 2
- 3. A brief history About 50 years later … David Cohen 1968: first (noisy) measure of a magnetic brain signal [Cohen, Science 68] 1970: James Zimmerman invents the ‘Superconducting quantum interference device’ (SQUID) 1972: first (1 sensor) MEG recording based on SQUID Brian- David Josephson 3
- 4. A brief history About 40 years later… today! 4
- 5. Introduction EEG EEG measures the potential difference on the skin surface due to the backflowing current at the surface. + + - 5
- 6. Introduction to MEG • MEG records the gradient of the Magnetic Induction d dx B x t ( , ) The Magnetic Induction results from electrical currents 6
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- 8. Introduction to MEG Electrical current in the brain •spatial components •transmembrane current •intra-cellular current •extra-cellular current •temporal components •activation of synapses •spiking activity 8
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- 10. EEG 10
- 11. EEG “without” skull 11
- 12. MEG “without” skull 12
- 13. MEG 13
- 14. Magnetoencephalography (MEG) MEG (MagnetoEncephaloGraphy) measures the magnetic field around the head Compare EEG: Measures voltage changes on the scalp MSI (Magnetic Source Imaging) is MEG coupled to MRI Magnetoencephalography magnetic brain picture 14
- 15. Intra-Cranial Sources Papanicolaou 1998:31 Dipole (source current) 15
- 16. How MEG works Records the magnetic flux or the magnetic fields that arise from the source current A current is always associated with a magnetic field perpendicular to its direction Magnetic flux lines are not distorted as they pass through the brain tissue because biological tissues offer practically no resistance to them (cf. EEG) 16
- 17. A dipole is a small current source Dipole generates a magnetic field Dendritic current flows from apical dendrites of pyramidal neurons At least 10,000 neighboring neurons firing “simultaneously” for MEG to detect 17
- 18. Recording of the Magnetic Flux Recorded by special sensors called magnetometers A magnetometer is a loop of wire placed parallel to the head surface The strength (density) of the magnetic flux at a certain point determines the strength of the current produced in the magnetometer If a number of magnetometers are placed at regular intervals across the head surface, the shape of the entire distribution by a brain activity source can be determined (in theory) 18
- 19. Magnetic flux from source currents Source current Magnetic flux Magnetometer 19
- 20. Recording of Magnetic Signals 20
- 21. Recording of the Magnetic Flux Present day machines have 248 magnetometers The magnetic fields that reach the head surface are extremely small Approximately one million times weaker than the ambient magnetic field of the earth Because the magnetic fields are extremely small, the magnetometers must be superconductive (have extremely low resistance) Resistance in wires is lowered when the wires are cooled to extremely low temperatures 21
- 22. Recording of the Magnetic Flux When the temperature of the wires approaches absolute zero, the wires become superconductive The magnetometer wires are housed in a thermally insulated drum (dewar) filled with liquid helium The liquid helium keeps the wires at a temperature of about 4 degrees Kelvin The magnetometers are superconductive at this temperature 22
- 23. Recording of the Magnetic Flux The currents produced in the magnetometers are also extremely weak and must be amplified Superconductive Quantum Interference Devices (SQUIDS) The magnetometers and their SQUIDS are kept in a dewar, which is filled with liquid helium to keep them at an extremely low temperature 23
- 24. The EEG & MEG instrumentation Sensors (Pick up coil) SQUI Ds MEG - 269 °C 24
- 25. There are different types of sensors Magnetometers: measure the magnetic flux through a single coil Gradiometers: measure the difference in magnetic flux between two points in space (axial/planar ; order 1, 2 or 3) The EEG & MEG instrumentation 25
- 26. MEG essentially measures… noise! The EEG & MEG instrumentation Heart beat Eye movements Brain activity Evoked brain activity Biomagnetic fields Earth magnetic field Environmental noise Urban noise Car (50m) Screw driver (5m) Electronic circuit (2m) 1 femto-Tesla (fT) = 10-15 T Alpha waves ~ 103 fT 26
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- 28. From a single neuron to a neuronal assembly/column - A single active neuron is not sufficient. ~100.000 simultaneously active neurons are needed to generate scalp measures. - Pyramidal cells are the main direct neuronal sources of EEG & MEG signals. - Synaptic currents but not action potentials generate EEG/MEG signals What do we measure with EEG & MEG ? 28
- 29. The dipolar model - A current source in the brain corresponds to a neuronal column and is modelled by a current dipole - A current dipole is fully defined by 6 parameters: 3 for its position & 3 for its moment (includes orientation and amplitude) - A dipolar moment Q = I x d ~ 10 to 100 nAm What do we measure with EEG & MEG ? source sink 29
- 30. From a single source to the sensor: the quasi-static assumption What do we measure with EEG & MEG ? James Clerk Maxwell (1831 - 1879) E: electric field B: magnetic field 30
- 31. From a single source to the sensor: EEG What do we measure with EEG & MEG ? primary/source currents secondary/conduction currents Electric field lines JcJs 31
- 32. 1. Indeed, currents need to flow to complete their loop from the source to the sink. In doing so, they obey two important laws: 2. One is Ohm’s law which relates the source current to the electric field and hence to the potentials we measure with EEG on the scalp. 3. The second is the conservation law which relates the primary and secondary currents and hence the source current to the potential itself. 32
- 33. From a single source to the sensor: EEG What do we measure with EEG & MEG ? Georg Simon Ohm 1789 - 1841 Ohm’s law Jc = σ E = - σ grad(V) σ : tissue conductivities Conservation law ∇.Js + ∇. Jc = 0 => ∇. Js = ∇.[σ grad(V)] 33
- 34. > From a single source to the sensor: MEG What do we measure with EEG & MEG ? Right hand rule 34
- 35. Tangential dipoleRadial dipole What do we measure with EEG & MEG ? From a single source to the sensor: MEG 35
- 36. source locationsensor location source orientation & sizesource amplitude - The magnetic field amplitude decreases with the square of the distance between the source and the sensor => MEG is less sensitive to deep sources Félix Savart (1791-1841) Jean-Baptiste Biot (1791-1841) What do we measure with EEG & MEG ? From a single source to the sensor: MEG Biot & Savart’s law 36
- 37. Dipolar Distribution of the Magnetic Flux • In the following figure, one set of concentric circles represents the magnetic flux exiting the head and the other represents the re-entering flux • This is called a dipolar distribution • The two points where the recorded flux has the highest value are called extrema • The flux density diminishes progressively, forming iso-field contours 37
- 38. Surface distribution of magnetic signals Extrema 38
- 39. Dipolar Distribution of the Magnetic Flux From the dipolar distributions, we can determine some characteristics of the source 1. The source is below the mid-point between the extrema (points where recorded flux has highest value) 2. The source is at a depth proportional to the distance between the extrema ◦ Extrema that are close together indicate a source close to the surface of the brain ◦ A source deeper in the brain produces extrema that are further apart 1. The source’s strength is reflected in the intensity of the recorded flux 2. The orientation of the extrema on the head surface indicates the orientation of the source 39
- 40. Progress of MEG over 4 decades 40
- 41. MEG in the 1970s—first recordings • The 1970s were an era of MEG engineering, with the main interest to demonstrate the feasibility of the new method. • Recordings of evoked responses to visual, tactile and auditory stimuli demonstrated a likely origin of the signals in the sensory-specific cortices. 41
- 42. MEG in the 1980s—focus on sensory processing • In the 1980s, MEG was extensively used to pinpoint the cortical generators of various evoked and event-related potentials. • The generation of the auditory 100-ms response in the supratemporal auditory cortex was widely accepted with corresponding auditory evoked potentials. • Similarly, the tangential source of the 20-ms somatosensory response N20 (N20m) within the sulcal wall of the primary somatosensory cortex (SI) was accepted. 42
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- 46. • MEG successfully differentiated between responses generated in the primary (SI) vs. secondary (SII) somatosensory cortices based on response timing, locations and directions of source current • Other pioneering observations in the 1980s include, e.g., the first recordings of the Tonotopic organization of the auditory cortex, The somatotopic organization of the primary somatosensory and motor cortices Retinotopic organization of the visual cortex . 46
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- 48. MEG in the 1990s—brain rhythms and cognitive processing • In the 1990s, the introduction of whole-scalp systems finally transformed MEG into a genuine brain-mapping tool, with focus on activation sequences, supported by increasingly accurate visualization on spatially aligned anatomical MR images. • Whole-scalp MEG systems finally opened the path for studies on high-level cognition, such as language processing and characterization of rhythmic activity throughout the cortex. 48
- 49. Brain rhythms • MEG whole-scalp spatiotemporal mapping, focuses on frequencies from 5 to 40 Hz . • The rolandic 20-Hz rhythm similar to intracranial motor- cortex signals was modulated according to the moving body part in a somatotopical manner. • This 20-Hz component of the rolandic mu rhythm provided a tool to demonstrate, e.g., motorcortex involvement in motor imagery and action observation. 49
- 50. • Gamma activity—especially > 60 Hz—has been promoted as an efficient measure of neural activation . • However, gamma appears to be markedly harder to pick up with MEG , with the exception of visual-cortex gamma activity elicited by large, attention-capturing visual stimuli • An interplay between gamma and theta (4–7 Hz) MEG activity has been taken to reflect encoding and retrieval of short-term and long-term memories . 50
- 51. MEG in the 2000s—cognition and connectivity, training and development Language function MEG displayed a salient N400m in the left superior temporal cortex While word reading activates multiple areas in both hemispheres, • visual feature analysis at ~100 ms in the occipital cortex • letter-string analysis~150 ms in the left occipitotemporal cortex; • access to phonology was proposed to engage the left inferior frontal cortex within 100 ms . 51
- 52. • During speech perception, activation is mainly concentrated to the superior temporal cortex, reflecting at 50–100 ms sensitivity to speech-specific acoustic–phonetic features. • The cortical sequences of auditory and visual word processing converge in the superior temporal cortex , with the left- hemisphere activation at 250–450 ms reflecting lexical- semantic analysis in both sensory modalities 52
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- 54. Social interaction and naturalistic stimulation Time-sensitive imaging in naturalistic settings could help to understand, e.g., speaker–listener coupling (Fig. 3). Seeing another person being touched activates the viewer's own SI cortex (Mirroring effect). Activation sequences occurring 250–400 ms after visual stimuli can be tracked during observation, imitation of live and video-presented hand actions and of facial gestures presented as still images imply motion. Signal are delayed and/or dampened in inferior frontal lobe in subjects suffering from Asperger syndrome . 54
- 55. Interareal connectivity Subjects performed continuous lateral movements of the right index finger in the horizontal plane, at a frequency of 0.5 Hz. Coherence maps with the left motor cortex (M1) as a reference area wer computed in individual subjects in the 6–9- Hz band. Significant group-level node (p b 0.05, corrected; one-sample t-test in SPM99) were identified in the left premotor cortex (PMC), left thalamus and right cerebellum. 55
- 56. Training and development • Brain imaging is increasingly used to assess neural effects of cognitive training. • In language training (re-learning) of chronic anomic patients, behavioral improvements were accompanied by changes in cortical dynamics . • In healthy subjects, learning new names for unfamiliar pictured items resulted in enhanced involvement of the left temporal and frontal cortices in naming. 56
- 57. • Spoken word-forms of an (artificial) foreign language were integrated rapidly and successfully into existing lexical and conceptual memory networks. • Development, even during the prenatal period, can be studied with the totally noninvasive MEG. • Fetal auditory MEG responses were first found, at 34–35 weeks gestation, to sounds delivered through the mothers's abdominal wall and have since then been recorded with increasing sophistication and success . 57
- 58. Why is an MEG performed? • In the evaluation of epilepsy, MEG is used to localize the source of epileptiform brain activity. • Usually performed with simultaneous EEG. • MEG may be helpful in the following situations: – Seizure localization – Lesion – Tumours 58
- 59. • It can improve the detection of potential sources of seizures by revealing the exact location of the abnormalities, which may then allow physicians to find the cause of the seizures. • It can help when MRI scans show a lesion but the EEG findings are not entirely consistent with the MRI information. • MEG paradigms of language lateralization that could replace the highly invasive and complication-prone Wada test. 59
- 60. • In patients who have brain tumors or other lesions, the MEG may be able to map the exact location of the normally functioning areas near the lesion prior to surgery. • In patients who have had past brain surgery, the electrical field measured by EEG may be distorted by the changes in the scalp and brain anatomy. • If further surgery is needed, MEG may be able to provide necessary information without invasive EEG studies. 60
- 61. Magnetoencephalography – Epilepsy Diagnosis Epileptic seizure scan data and postprocessing
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- 63. MEG and stroke • MEG shows promise in monitoring of stroke recovery , especially since modified vasomotor reactivity in stroke easily affects the BOLD hemodynamic response but leaves the MEG signal intact . 63
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- 65. MEG and chronic pain • Clinical research of chronic pain may benefit from the possibility to differentiate between cortical representations of the first and second pain (Ploner et al., 2002) and to selectively stimulate the thin, slowly conducting C-fibers and the faster conducting Aδ-fibers . • In patients suffering from complex regional pain syndrome, both the extent of the somatosensory cortical representation of the painful hand and the reactivity of motor-cortex rhythms are altered. 65
- 66. Dyslexia and stuttering • In adult dyslexics, cortical processing in both reading and speech perception starts to differ from the normal pattern at the stage of the earliest language-sensitive processing , with a marked delay by lexical-semantic processing, particularly in reading • The left occipitotemporal dysfunction for written words was first detected with MEG and later corroborated with hemodynamic imaging. • When reading words out loud, fluent speakers first activated the left inferior frontal and then (pre)motor cortex but this sequence was reversed in stutterers, suggesting that they initiated motor programs before articulatory planning. 66
- 67. A practical consideration: Cost • Most expensive: MEG – About $2 million for the machine – $1 million for magnetically shielded room • Next most expensive: PET • Next: fMRI • Cheapest: EEG 67
- 68. Temporal resolution – summary • PET: 40 seconds and up • fMRI: 10 seconds or more • MEG and EEG: instantaneous – Theoretically it is possible to do ms by ms tracking, to follow time course of activation – Commonly used sampling rate for MEG: 4 ms – Practically, such tracking is difficult or impossible • The inverse problem • Too many dipoles at each point in time 68
- 69. Spatial Resolution • EEG: Poor • PET: Fair – 4-5 mm • fMRI: Fair – 4-5 mm – MRI: Good – 1 mm or less • MEG: Fairly good – 3-4 mm or less – Under good conditions 69
- 70. Sensitivity of Imaging Methods • All of the methods have limited sensitivity • MEG – 10,000 dendrites in close proximity have to be active to detect signal • PET and fMRI – Similar limitations • Any activation that involves fewer numbers goes undetected 70
- 71. Other limitations of MEG and EEG • Problem: orientation of dipoles • For MEG – Activity in some areas is practically undetectable • Dipoles at tops of gyri • Dipoles at bottoms of sulci • For EEG – Dipoles on sides of sulci are hard to detect 71
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- 73. References • Magnetoencephalography: Fundamentals and Established and Emerging Clinical Applications in Radiology(Sven Braeutigam) • Signal Processing in Magnetoencephalography (Jiri Vrba and Stephen E. Robinson) 73
- 74. 74 • Thank you
Editor's Notes
- 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.
- 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.
- - 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…
- 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.
- 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.
- 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!
- 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.
- 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.
- 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.
- 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.
- 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 ?
- 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.
- 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.