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Transcript
What are we measuring with
EEG and MEG ?
Isabel Zlobinski & Xavier De Tiège
Introduction
Neurophysiological background
EEG
MEG
Introduction
EEG and MEG are 2 functional cerebral imaging techniques
that are closely related
In both methods, the measured signals are generated by
the same synchronized neuronal activity in the brain
The main interest of M-EEG compared to other techniques
TEMPORAL RESOLUTION
The temporal resolution of M-EEG
Follow the rapid changes in cortical activity
Reflect ongoing signal processing in the brain
Neurophysiological background
Glial cells
Structural support
Metabolism
Ions & NTT transport
Myelin
Neurons
Information-processing units
Grey matter
cell bodies & dendrites
Cortex & basal ganglia
White matter
axones (myeline)
Like other cells, the neurons are
surrounded by a membrane
The membrane divides the tissue into
intra- & extracellular compartments
with different ions [ ]
The difference in ions [ ] is maintained against
their [ ] gradient by
special proteins that pump selected ions
Na+-K+ pump (3 Na+ out, 2 K+ in)
The differences in ions [ ] & the permeability
of the membrane for each ion
++++++++++++++
-------------------
------------------++++++++++++++
Resting potential
Goldman ’s equation
The resting state of the neurons can be modified by
Action Potentials
Axones
Postsynaptic Potentials
Synaptic junctions
Action Potentials
Depolarization
Repolarization
Generated at the cell body/axone junction
Hyperpolarization
Action potentials
Not observable with M-EEG
- Generate 2 current dipoles = quadrupole
parallel, equal intensity, opposite directions => 0
- Quadrupolar field decreases with distance as 1/r³
(compared to 1/r² for dipolar field)
- Duration = 1 ms temporal summation between neighbouring fibers difficult
Postsynaptic Potentials
Synaptic junctions
mainly on cell body &
dendrites
Action potential at the synaptic junction
of the presynaptic neuron
Action Potentials
Liberation of neurotransmitters
Receptors
Ion channels activated
De- or hyperpolarization
Acetylcholine or glutamate
Activate Na+ and Ca++ channels
Depolarization
Excitatory PSP
Summation of EPSP
Action potential at the cell body/axon junction
GABA
Activate Cl- channels
Hyperpolarization
Prevents action potential generation
Inhibitory PSP
EPSP
Are measured with M-EEG
- Generate intracellular currents and
extracellular currents
- Generate (approximately) one current dipole
- Dipolar fields decrease with
distance as 1/r²
- Duration = 10 ms
temporal summation between neighbouring fibers
more effective
A single EPSP produces a current dipole
along the dendrite with a stenght of +/- 20 fA m
Too small to be measured with M-EEG
M-EEG see sources with strenght
on the order of 10 nA m
Cummulative summation of one million of synaptic
junctions in a small region is required
As apical dendrites of pyramidal
neurons of the cortex tend
to be perpendicular to the cortical surface
Cummulative summation of EPSP
in the same direction is more easily
obtained with apical dendrites of
pyramidal cells
M-EEG signals are mainly produced by
PSP generated at apical dendrites
of pyramidal cells in the cortex
What are we measuring with MEG ?
MEG
Magneto-
-graphy
-encephalo-
Record magnetic fields
generated by brain activity
PSP induced intracellular currents (primary currents) and
extracellular currents (secondary currents)
Secondary currents yield potential differences on the
scalp of the head that can be measured by EEG
MEG measures magnetic fields induced mainly by
primary currents
Cummulative summation of
PS primary currents
of millions apical dendrites
of pyramidal cells in one cortical area
Generates a magnetic field
measurable by MEG
Primary currents
"Right Hand Law"
Induced magnetic
field
Volume currents
Tangential currents will produce magnetic fields
that are observable outside the head
Radial currents will not produce magnetic fields outside the head
MEG only detects tangential currents
MEG measures the fluctuations of frequency (Hz) and
amplitude (T) of the brain magnetic signal
10 fT (10-15) to about several pT (10-12)
BUT
Earth ’s magnetic field is about 0.5 mT
Urban magnetic noise is about 1 nT to 1 µT
Moving vehicules, moving elevators, radio, TV, powerlines, etc.
The electrical activity of the heart, eye blinks also generate a field 2 to 3 order
of magnitude larger than the signal from the brain
Noise is about a factor of 10³ to 106 larger than the MEG signal
We need very sensitive MEG sensors
to pick up the brain magnetic fields
SQUIDs
MEG measurements need noise
cancellation with extraordinary accuracy
Design of the SQUID
Magnetic shielded room
Hardware and software
Averaging
Superconducting QUantum Interference Device
SQUIDs are sensitive to very low magnetic fields
The SQUIDs "translate" the magnetic field into an electrical current
which is proportional to this field
To have their superconductive properties,
the SQUIDs need to be maintained at-269 °C
They are cooled in
liquid He
The different types of pick-up coils
CTF system
Magnetometers
Axial and planar
gradiometer
1980
1995-2000
Whole-head sensors arrays which use 100 to 300 sensors
at different locations
Noise cancellation
SQUID Design
Compensation coil
compensates for variations in the
background field
1st order axial gradiometer
This SQUID will only be
sensitive to inhomogeneous
changes of magnetic fields
between the 2 coil
Background fields will be
spatially uniform
Shielded room
Reduce the effect
of external magnetic
disturbances
Pick-up coil
picks up the signal from the brain
Hardware and softwares
Use of reference
A linear combination of the reference
output is subtracted from the
MEG primary sensor output
Use of filters
Low-pass filter, high pass filter
50-Hz filter, etc...
Use of specific softwares
Averaging of brain signals
With MEG, you can make (as in EEG) :
- Continuous acquisition of brain signals and study some
events that appear « randomly » (Epileptic abnormalities, etc.)
- Evoked response: averaged MEG signals that are synchronous with
an external stimulus or voluntary motor event
References :
- Hämäläinen et al., Reviews of Modern Physics, 1993
- Baillet et al., IEEE Signal Processing Magazine, 2001
- Jeremie Mattout PhD thesis
- Murakami & Okada, J Physiol, in press