1. Basis of the MEG/EEG Signal
BY MAGDA DUBOIS
EXPERT: SAM EREIRA

2. Overview
EEG basics
MEG basics
EEG vs. MEG
Advantages & Disadvantages

3. EEG: Introduction
Electroencephalogram

4. EEG: Introduction A non-invasive method for measuring brain activity
Electroencephalogram
Non-invasive 
A non-invasive method for measuring brain activity

5. EEG: Introduction Used to capture cortical information processing
Electroencephalogram
Non-invasive 
Used to capture cortical information processing
Used to capture cortical information processing

6. EEG: Introduction
Electroencephalogram
Non-invasive 
Used to capture cortical information processing
High temporal resolution
The biggest difference with MRI is it’s high temporal resolution (of the order of milliseconds)

7. EEG: Introduction Makes it a efficient tool e.g. Neurofeedback
Electroencephalogram
Non-invasive 
Used to capture cortical information processing
High temporal resolution
Tool for investigation of real time processing + for the development of brain-computer interfaces
Makes it a efficient tool e.g. Neurofeedback

8. EEG: Basis of the signal

9. EEG: Basis of the signal
Cortex: six distinct cortical layers
The cortex can be divided in six distinct cortical layers

10. EEG: Basis of the signal
Cortex: six distinct cortical layers
Each layer contains different type of neurons + distinct connections
each of them contains different type of neurons and distinct connections with other subcortical and cortical areas.

11. EEG: Basis of the signal
Cortex: six distinct cortical layers
Each layer contains different type of neurons + distinct connections
It is the activation of the giant pyramidal cells in cortical layer V that is reflected in most of the EEG.
It is the activation of the giant pyramidal cells in cortical layer V that is reflected in most of the EEG.

12. EEG: Basis of the signal
Cortex: six distinct cortical layers
Each layer contains different type of neurons + distinct connections
It is the activation of the giant pyramidal cells in cortical layer V that is reflected in most of the EEG.

13. EEG: Basis of the signal
Neural transmission
Reminder of neural transmission. You have a presynaptic and a postsynaptic neuron.

14. EEG: Basis of the signal
Neural transmission
The arrival of presynaptic action potential results in a result in a release of neurotransmitters in the synaptic cleft, depolarizing the post-synaptic membrane, setting in motion the post synaptic potential.
Can be excitatory or inhibitory

15. EEG: Basis of the signal
Neural transmission
In EEG It’s this post synaptic potential (PSP) that we are able to record outside of the brain. Not the pre-synaptic AP that caused it. There are several reasons for it.

16. EEG: Basis of the signal
EEG relies on currents of many neurons summing up.
Currents of a single neuron are too small to be picked up outside of the brain. EEG relies on the currents of many neurons summing up.

17. EEG: Basis of the signal
EEG relies on currents of many neurons summing up.
Presynaptic action potential (AP):
Short
Biphasic
The presynaptic potential is very short (of the order or several milliseconds) and it is biphasic. Meaning that it has a positive and a negative deflection. This means that spikes that are not perfectly synchronized will cancel each other out.

18. EEG: Basis of the signal
EEG relies on currents of many neurons summing up.
Presynaptic action potential (AP):
Short
Biphasic
Postsynaptic potential (PSP):
Longer
Monophasic
Post-synaptic potentials are much longer as well as monophasic. This allows for these deflections to add up more easily and therefore to be captured by EEG.

19. EEG: Basis of the signal
Necessary conditions for neural signal to be detected:

20. EEG: Basis of the signal
Necessary conditions for neural signal to be detected:
Timing or Synchrony

21. EEG: Basis of the signal
Necessary conditions for neural signal to be detected:
Timing or Synchrony
Large numbers
Because the electrical field decreases in voltage as it travels from the cells to the scalp, you need large numbers of neurons.

22. EEG: Basis of the signal
Necessary conditions for neural signal to be detected:
Timing or Synchrony
Large numbers
Orientation
Orientation – Arranged in parallel (in the same direction) so charges do not cancel out
Pyramidal neurons in layer 5 meets all those conditions.

23. EEG: Basis of the signal
Necessary conditions for neural signal to be detected:
Timing or Synchrony
Large numbers
Orientation
 Pyramidal neurons in layer V
Pyramidal neurons in layer 5 meets all those conditions.

24. EEG: Basis of the signal
Necessary conditions for neural signal to be detected:
Timing or Synchrony
Large numbers
Orientation
 Pyramidal neurons in layer V
Population of pyramidal neurons create a dipole
negative and positive pole
depends on excitatory or inhibitory

25. EEG: Basis of the signal
Necessary conditions for neural signal to be detected:
Timing or Synchrony
Large numbers
Orientation
 Pyramidal neurons in layer V
Orientation determines the deflections in the EEG signal.

26. EEG: Frequency spectrum
The wave signals acquired (as on image) are usually classified in terms of their frequencies.

27. EEG: Frequency spectrum
Delta:
Frequency of < 3 Hz
Highest in amplitude + slowest waves
Dominant rhythm in infants (< 1 year) and in stages 3 and 4 of sleep
Alpha:
Frequency: Hz
Seen in posterior regions of the head, higher in amplitude on the dominant side.
Appears when closing the eyes and relaxing.
Major rhythm in relaxed adults (> 13 years)
Delta waves: has a frequency of 3 Hz or below. It tends to be the highest in amplitude and the slowest waves. It is normal as the dominant rhythm in infants up to one year and in stages 3 and 4 of sleep.

28. EEG: Frequency spectrum
Delta:
Frequency of < 3 Hz
Highest in amplitude + slowest waves
Dominant rhythm in infants (< 1 year) and in stages 3 and 4 of sleep
Alpha:
Frequency: Hz
Seen in posterior regions of the head, higher in amplitude on the dominant side.
Appears when closing the eyes and relaxing.
Major rhythm in relaxed adults (> 13 years)
Theta:
Frequency: Hz
 "slow" activity
In children (< 13 years) and in sleep.
Abnormal in awake adults.
Beta:
Frequency > 14 and greater Hz  ”Fast” activity
Seen on both sides in symmetrical distribution and is most evident frontally
Dominant rhythm in patients who are alert or anxious or have their eyes open.
Theta waves have a frequency of 3.5 to 7.5 Hz and is classified as "slow" activity. It is perfectly normal in children up to 13 years and in sleep but abnormal in awake adults.

29. EEG: Frequency spectrum
Delta:
Frequency of < 3 Hz
Highest in amplitude + slowest waves
Dominant rhythm in infants (< 1 year) and in stages 3 and 4 of sleep
Alpha:
Frequency: Hz
Seen in posterior regions of the head, higher in amplitude on the dominant side.
Appears when closing the eyes and relaxing.
Major rhythm in relaxed adults (> 13 years)
Theta:
Frequency: Hz
 "slow" activity
In children (< 13 years) and in sleep.
Abnormal in awake adults.
Beta:
Frequency > 14 and greater Hz  ”Fast” activity
Seen on both sides in symmetrical distribution and is most evident frontally
Dominant rhythm in patients who are alert or anxious or have their eyes open.
Alpha: has a frequency between 7.5 and 13 Hz. Is usually best seen in the posterior regions of the head on each side, being higher in amplitude on the dominant side. It appears when closing the eyes and relaxing, and disappears when opening the eyes or alerting by any mechanism (thinking, calculating). It is the major rhythm seen in normal relaxed adults. It is present during most of life especially after the thirteenth year.

30. EEG: Frequency spectrum
Delta:
Frequency of < 3 Hz
Highest in amplitude + slowest waves
Dominant rhythm in infants (< 1 year) and in stages 3 and 4 of sleep
Alpha:
Frequency: Hz
Seen in posterior regions of the head, higher in amplitude on the dominant side.
Appears when closing the eyes and relaxing.
Major rhythm in relaxed adults (> 13 years)
Theta:
Frequency: Hz
 "slow" activity
In children (< 13 years) and in sleep.
Abnormal in awake adults.
Beta:
Frequency > 14 and greater Hz  ”Fast” activity
Seen on both sides in symmetrical distribution and is most evident frontally
Dominant rhythm in patients who are alert or anxious or have their eyes open.
Beta: beta activity is "fast" activity. It has a frequency of 14 and greater Hz. It is usually seen on both sides in symmetrical distribution and is most evident frontally. It is generally regarded as a normal rhythm. It is the dominant rhythm in patients who are alert or anxious or have their eyes open.

31. EEG: Surface recordings
For the placing of electrodes:
International 10/20 or 10/10 system
A: earlobes, C: central,
P: parietal, F: frontal,
O: occipital
For the placing of electrodes you can use the international 10/20 or 10/10 system which indicates the location based on anatomical landmarks.
(10 percent of the distance etc)

32. MEG: Introduction Magnetoencephalography
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography

33. MEG: Introduction
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography
Non invasive
is a non-invasive imaging method, does not require any injections

34. MEG: Introduction
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography
Non invasive
High temporal + spatial resolution
High temporal and spatial resolutions, sources can be localized with millimeter and millisecond precision.

35. MEG: Introduction
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography
Non invasive
High temporal + spatial resolution
Measures magnetic fields
Unlike EEG which measure potential difference, MEG measures the magnetic fields generated by neuronal activity of the brain

36. MEG: Introduction
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography
Non invasive
High temporal + spatial resolution
Measures magnetic fields
Technology: SQUID
Those magnetic fields are detected by a technology based on super-conducting detectors and amplifiers known as SQUIDs

37. MEG: Introduction
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography
Non invasive
High temporal + spatial resolution
Measures magnetic fields
Technology: SQUID
Location of neuronal sources found via magnetic field analysis
The magnetic fields are analysed to find the locations of the neuronal sources within the brain

38. MEG: Introduction
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography
Non invasive
High temporal + spatial resolution
Measures magnetic fields
Technology: SQUID
Location of neuronal sources found via magnetic field analysis
Used for:
Surgical planning (Source locations superimposed on MRI image)
Surgical planning (before a surgery) (where the resulting source locations are superimposed on an MRI image)

39. MEG: Introduction
Electroencephalogram (EEG) electrodes
Scalp recording of electrical activity of cortex => waveform signals
Microvolts (µV) – small!
Role of EEG in neuroimaging:
Identify neural correlates
Diagnose epilepsy, sleep disorders, anaesthesia, coma, brain death
Magnetoencephalography
Non invasive
High temporal + spatial resolution
Measures magnetic fields
Technology: SQUID
Location of neuronal sources found via magnetic field analysis
Used for:
Surgical planning (Source locations superimposed on MRI image)
Neural correlates brain processes
OR in research to identify the neural correlates of cognitive or perceptual processes

40. MEG: Basis of the signal
Postsynaptic potentials (PSPs) create current
Recal from EEG.
We have our population of pyramidal cells in layer 5 of the cortex. When they are depolarized they generate Postsynaptic potentials. This creates a potential difference along the membrane which can be measure by EEG

41. MEG: Basis of the signal
Postsynaptic potentials (PSPs) create current
Current = magnetic field
From physics, we know any current in a wire (or in this case through neurons), produces a magnetic field (the green circle).
To know the direction of the magnetic fields (of those arrows) you can use the right hand rule

42. MEG: Basis of the signal
Recall from EEG, We wanted to neurons to be as parallel as possible, facing the same direction. Because voltage will be attenuated so we want the current to be as strong as possible (so charges can’t cancel out). But the overall direction doesn’t really matter.

43. MEG: Basis of the signal
MEG coil not sensitive to perfectly radial sources
radial
MEG pick-up coils
MEG coil not sensitive to perfectly radial sources
The problem is that with this sort of radial current, if you follow the right hand rule, the magnetic field (depicted in red here) will remain under the scalp and won’t be detected via MEG.

44. MEG: Basis of the signal
MEG coil not sensitive to perfectly radial sources
Only a small proportion of cell are perfectly radial (top of gyri)
radial
MEG pick-up coils
The good thing is that Only a small proportion (<1%) of cell populations are perfectly radial – i.e. on top of gyri. But there are plenty of others such as

45. MEG: Basis of the signal
MEG coil not sensitive to perfectly radial sources
Only a small proportion of cell are perfectly radial (top of gyri)
radial
tangential
MEG pick-up coils
The tangential ones. They are ideal ones for MEG.

46. MEG: Basis of the signal
MEG coil not sensitive to perfectly radial sources
Only a small proportion of cell are perfectly radial (top of gyri)
radial
tangential
MEG pick-up coils
They generate magnetic fields that can be detected outside of the skulp

47. MEG: Basis of the signal
MEG coil not sensitive to perfectly radial sources
Only a small proportion of cell are perfectly radial (top of gyri)
No distortion of magnetic fields
radial
tangential
MEG pick-up coils
Unlike the current which is measure in EEG, magnetic field are not distorted , or attenuated by conductive properties of scalp/head
no condition / requirements other than direction

48. MEG: Scale of the signal
MEG signal is tiny
The main drawback of MEG is that the signals are extremely small.

49. MEG: Scale of the signal
MEG signal is tiny
Can be hidden by noise
Can be hidden by environmental noise such as electrical equipment, traffic, heartbeat etc

50. MEG: Scale of the signal
MEG signal is tiny
Can be hidden by noise
Interference from heartbeat
Here an example of interference. MEG on top, electrocardiogram on the bottom. Interference with a heartbeat.

51. MEG: Scale of the signal
MEG signal is tiny
Can be hidden by noise
Requires:
A magnetically shielded room
Supersensitive magnetometers
Interference from heartbeat

52. MEG: Noise reduction
Magnetically shielded room (MSR)
magnetically shielded room. That’s how it looked in the 70s (David Cohen, first study using MEG). That’s how it looks now. You have either 3, 5 or 6 layers with different magnetic properties to protect from different frequencies of magnetic interference

53. MEG: Instrumentation inside of meg
Liquid helium: refrigerant
Dewar: insulation
SQUID connected to flux transformers
inside of meg
the big square is the magenetic shielded room
The core of MEG: the SQUID device which is connected to a flux transformer, or pickup coil.
What is this SQUID thing exactly

54. MEG: Instrumentation
Super conducting quantum interference device
A very sensitive magnetometer used to measure extremely subtle magnetic fields
A small ring (2-3) mm of superconducting material
The magnetic field of brain actitvity is very small. Before being measured, it needs to be amplified. This is done via flux transformers.

55. MEG: Instrumentation
Super conducting quantum interference device
A very sensitive magnetometer used to measure extremely subtle magnetic fields
A small ring (2-3) mm of superconducting material
Connected to pick up coils / flux transformers
This is done via the flux transformers to which its connected. There are 2 types of sensors. Magnetometers and Gradiometers.

56. MEG: Flux transformers
scalp
scalp
scalp
Magnetometer
Axial/planar gradiometers (1st order)
Two oppositely-wound coils – environmental noise affects both electrodes : no net noise.
Magnetometer is just a round wire. The top is connected to the SQUID and the bottom is in contact with the scalp.

57. MEG: Flux transformers
scalp
scalp
scalp
Magnetometer
Axial/planar gradiometers (1st order)
Two oppositely-wound coils – environmental noise affects both electrodes : no net noise.
Active bunch of neurons generate current (in blue). This generates magnetic field (in green).
If you place the magnetometer to the source, the magnetic field will pass through it in upwards direction. (physics).
The problem with this is that it will also capture external noise (such as heartbeat).

58. MEG: Flux transformers
scalp
scalp
scalp
Magnetometer
Axial gradiometer Planar gradiometer
The trick, is to use 2 magnetometers together. This makes a gradiometer. You can either put them on top of each other (axial), or side by side (planar).

59. MEG: Flux transformers
scalp
scalp
scalp
Magnetometer
Axial gradiometer Planar gradiometer
The important part is to have the wires in different directions. So they will perceive the magnetic field in different directions. Therefore magnetic fields that are at the same distance of both wires (such as environmental noise) will cancel out. They are efficient noise cancelers.

60. MEG: Flux transformers
scalp
scalp
scalp
Magnetometer
Axial gradiometer Planar gradiometer
Each of those 2 types have different advantages, planar gradiometers cancel noise better but axial gradiometers are good for measuring depth.

61. EEG vs. MEG EEG MEG Signal magnitude 10 mV (easily detectable)
10 fT (magnetic shielding required)
Measurement
Secondary currents
Primary currents
Signal purity
Distortion by skull/scalp
Little effect by skull/scalp
Temporal resolution
~1ms
Spatial resolution
~1cm
<1cm
Experimental flexibility
Moves with subject
Subject must remain stationary
Dipole orientation
Tangential and radial
Tangential better

62. EEG/MEG advantages Non-invasive
Direct measurements of neuronal function (unlike fMRI)
High temporal resolution (1ms or less, 1000x better than fMRI)
Easy to use clinically (adults, children)
Quiet! (can study auditory processing)
Subjects can perform tasks sitting up (more natural than MRI scanner)

63. EEG/MEG disadvantages
Not as good spatial localisation as fMRI, MRI, CT
Sensitivity depth only ~4cm (c.f. whole brain sensitivity of fMRI)
Sensitivity loss proportional to square of distance from sensor
3D Source reconstruction is ill-posed? Forward and inverse problems
Graph with spatial resolution in y axis and temporal resolution in x axis

64. Thank you for listening!
Any questions?