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Basis of the M/EEG signal
Evelyne Mercure
Bonnie Breining
Overview of EEG & ERP
Overview of MEG
 EEG/MEG vs. Other Imaging Techniques
1929: Hans Berger discovered that an
electrode applied to the human scalp could
record voltage variations attributed to the
activity of the neurons
Amplified, plotted as a function of time =>
EEG signal
The EEG signal
EEG rhythms
Action potential
When a neuron is activated, current flows from the cell body
to the axon terminal
To be registered by electrodes on the scalp many neurons
would need to fire at the same time, which is unlikely given
that action potentials lasts around 1msec
No dipole created
Not recorded by EEG!!!
Postsynaptic potentials
After an action potential
neurotransmitters are released
They bind to the receptors of
a postsynaptic neuron
Postsynaptic potential (2)
Depending on whether the
neurotransmitter is excitatory or
inhibitory, electrical current
flows from the postsynaptic cell
to the environment, or the
The membrane of the
postsynaptic cell becomes
depolarised (more likely to
generate an action potential) or
hyperpolarised (less likely to
generate an action potential)
Postsynaptic potential (3)
Electrical current begins to flow in the
opposite direction within the cell body to
complete the electrical circuit
A small dipole is created!
Lasts tens or even hundreds of
milliseconds => more likely to happen
To sum together, postsynaptic potentials
of different neurons need to
 Be simultaneous
 Be spatially aligned
Pyramidal neurons of the
cortex are spatially
aligned and perpendicular
to the cortical surface
The EEG signal results
mainly from the
postsynaptic activity of
the pyramidal neurons
Volume conduction
When a dipole is in a
conductive medium,
electrical current spreads
through this medium
The skull has a higher
electrical resistance than
the brain => the electrical
signal spreads laterally
when reaching the skull
Difficulty of source
Recording EEG
Electrode applied to the skull or brain surface
Substance with low impedance is used to conduct electricity
between the skin and electrode
Voltage is a difference in electrical potential => need a reference
Muscle movements
Eye movements
Many trials
Artefact rejection
Event-related potentials
A different way of analysing the EEG signal
Time-locked to a stimulus
Event-related potentials (2)
P2 =>
P1 =>
N170 =>
Electricity & Magnetism
•MEG measures the same postsynaptic
potentials as EEG.
•Basic Physics:
•Electric currents have corresponding
magnetic fields.
•The magnetic field generated is
perpendicular to the electric current.
•Right Hand Rule
Electricity & Magnetism 2:
MEG is sensitive to tangential but not radial components
of signal
• MEG mainly measures the
activity of pyramidal neurons
in the sulci that are oriented
parallel to the scalp
• Magnetic fields from
perpendicular oriented neurons
on gyri don’t project out of
Magnetic Fields
•Magnetic fields generated by brain
activity are tiny
•100 million times smaller than the earth's
magnetic field
•1 million times smaller than the magnetic
fields produced in an urban environment (by
cars, elevators, radiowaves, electrical
equipment, etc)
•MEG must be performed in shielded
A Bit of History
In 1963 Gerhard Baule and
Richard McFee of the Department
of Electrical
Engineering,Syracuse University,
Syracuse, NY detected the
biomagnetic field projected from
the human heart.
They used two coils, each with 2
million turns of wire, connected to
a sensitive amplifier. The
magnetic flux from the heart
generated a current in the wire.
They did this in a field in the
middle of nowhere because of the
very noisy signal.
More History
In the late 1960’s David
Cohen, at MIT, Boston
recorded a clean MCG in an
urban environment. This
was possible due to:
1) Magnetically shielding the
recording room.
2) Improved recording
sensitivity. (The introduction
SQUIDs- Superconducting QUantum Interference Devices
•Use principles of super-conduction to measure tiny magnetic fields
•300+ sensors in helmet shape
•Cool with liquid helium
The sensitivity of the SQUID to
magnetic fields may be enhanced
by coupling it to a superconducting
pickup coil (“flux transformer”)
has greater area and number of turns
than the SQUID inductor alone.
made of superconducting wire and is
sensitive to very small changes in the
magnitude of the impinging magnetic
The magnetic fields from the brain
causes a supercurrent to flow.
First Order
MEG data
brain activation film (recorded during
comprehension of a spoken word)
•Large Signal (10 mV)
•Signal distorted by
•Spatial localization ~1cm
•Sensitive to tangential and
radial dipoles (neurons in
sulci & on gyri)
•Allows subjects to move
•Sensors attached directly to
•Extracellular secondary
(volume) currents
•Good temporal
resolution (~1 ms)
•Problematic spatial
resolution (forward
& inverse
•Tiny Signal(10 fT)
•Signal unaffected by
•Spatial localization ~1 mm
•Sensitive only to tangential
dipoles (neurons in sulci)
•Subjects must remain still
•Sensors in helmet
•Requires special laboratory
•Intracellular primary currents’
magnetic fields
Thanks to last year’s slides & wikipedia
MEG/EEG vs. Other Techniques
Advantages of EEG/ERPs/MEG
Non-invasive (records electromagnetic activity, does not
modify it)
Can be used with adults, children, infants, newborns, clinical
High temporal resolution (a few milliseconds, around 1000x
better than fMRI) => ERPs study dynamic aspects of cognition
EEG relatively cheap compared to MRI
Allow quiet environments
Subjects can perform tasks sitting up- more natural than in
Limitations of EEG/ERPs/MEG
Spatial resolution is fundamentally undetermined
Signal picked up at one place on the skull does not represent the
activity directly under it
Forward problem: Knowing where the dipoles are and the
distribution of the conduction in the brain, we could calculate the
voltage variation recorded at one point of the surface
Inverse problem: Infinite number of solutions
Source localisation algorithms uses sets of predefined constraints
to limit the number of possible solutions
Anatomical information not provided
References/suggested reading
Handy, T. C. (2005). Event-related potentials. A methods handbook. Cambridge,
MA: The MIT Press.
Luck, S. J. (2005). An introduction to the event-related potential technique.
Cambridge, Massachussets: The MIT Press
Rugg, M. D., & Coles, M. G. H. (1995). Electrophysiology of mind: Event-related
brain potentials and cognition. New York, NY: Oxford University Press.
Hamalainen, M., Hari, R., Ilmoniemi, J., Knuutila, J. & Lounasmaa, O.V. (1993).
MEG: Theory, Instrumentation and Applications to Noninvasive Studies of the
Working Human Brain. Rev. Mod. Phys. Vol. 65, No. 2, pp 413-497.
Sylvain Baillet, John C. Mosher & Richard M. Leahy (2001). Electromagnetic Brain
Mapping. IEEE Signal Processing Magazine. Vol.18, No 6, pp 14-30.
Basic MEG info: