Magnetoencephalography! How It Works Currents in neurons

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Magnetoencephalography!
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How It Works

• Currents in neurons create very tiny magnetic
  fields
• MEG uses SQUIDs to detect these magnetic fields.
• Magnetic signals from the brain are only a few fT
  in strength.
• Needs a magnetically shielded room

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History

• First measured by David Cohen in 1968.
• He used a copper induction coil
• Presently, MEG technology uses SQUIDS
• Today, MEG machines can contain as many as 300
  SQUID sensors

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Diagram of MEG setup
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SQUIDS

• Superconducting Quantum Interference Devices
• Superconducting material is niobium or lead alloy
  with gold/indium
• Cooled to low temperature with either liquid He
  (4K) or N (77K)
• Manufactured at NIST in Boulder!
• Noise levels about 3 fTHz-1/2

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More on SQUIDS

• The magnetic field detected by
  the SQUID is converted to
  voltage by a Josephson junction
• A flux transformer or gradiometer
  is used to couple the squid to
  outside electronics
• Measures the difference in field
  between two coils
• This also reduces noise

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Josephson Junctions

• Two superconductors separated by a thin
  insulating barrier
• A small current will tunnel across the barrier
• The constant current Ic depends on temperature
  and magnetic field
• SQUIDS measure fractions of the phase difference
  in terms of the flux quantum h/2e

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Detecting Brain Activity

• 50,000 neurons need to fire to generate a
  readable signal
• Neurons near the outside of the brain generate
  the strongest signals

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Magnetic Shielding

• Rooms for MEGs have walls made of Aluminum and
  mu-metal (a type of nickel-iron alloy with
  extremely high magnetic permeability)
• Aluminum shields from high
  frequency noise
• Mu-metal shields from low
  frequency noise

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Forward Problem

• Given a specific current distribution in the
  brain, how do we determine what signal the MEG
  will read?
• This is a well posed problem with a unique
  solution
• Simple laws of Electromagnetism

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The Inverse Problem

• Infinite solutions
• Impossible to completely determine the source
  locations from magnetic field data alone
• Making sense of MEGs requires additional
  information
• What is the best solution?
• Models of known brain activity
• Independent component analysis
• Iterative procedure to localize sources
• Synthetic Aperture Magnetometry

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Synthetic Aperture Magnetometry

• Estimates the current at a fixed location
• Ignores the ill-posed inverse problem
• Estimates source location by focusing the array
  with linear weighting
• Uses beamforming to obtain good data from the
  location of interest at the cost of bad data
  elsewhere
• Interferometrically combines SQUID sensors

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Magnetic Source Imaging

• Combines MRI with MEG
• Lipid markers for MRI are matched with coils of
  wire for the MEG
• The MEG data shows up as colored probability
  regions on the MRI image

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Dipole Model Source Localization

• Calculates equivalent current dipoles
• Assumes there are a fixed number of dipoles
• Overdetermined
• Problems with determining depth in the brain and
  dealing with extended sources

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Lead-field-based imaging approach

• Divides the source space into a grid containing
  dipoles
• Underdetermined system
• Provides a statistical reconstruction
• No prior brain knowledge is needed

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Independent Component Analysis

• Used to separate signals that are statistically
  independent in time
• Removes noise generated from eye blinking,
  movement, signals from muscles, etc.
• Bad for measuring highly correlated brain sources

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Uses of MEG

• MEGs are used in research to measure the time
  course of brain activity
• MEGs can detect epilepsy, as well as detect areas
  of the brain that are most important to avoid
  during surgery

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Advantages/Disadvantages

• High 1 ms time resolution
• Completely non-invasive
• Does not depend on head geometry like EEG
• Magnetic fields decay faster over distance than
  electric fields
• MEG is best used to complement other imaging
  techniques

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References

• http//en.wikipedia.org/wiki/Magnetoencephalograph
  y
• http//en.wikipedia.org/wiki/SQUID
• http//www.aston.ac.uk/lhs/research/facilities/meg
  /
• Magnetoencephalography theory, instrumentation,
  and applications to noninvasive studies of the
  working human brain. Matti Hämäläinen, Riitta
  Hari, Risto J. Ilmoniemi, Jukka Knuutila, and
  Olli V. Lounasmaa. Rev. Mod. Phys. 65, 413 - 497
  (1993). http//prola.aps.org/abstract/RMP/v65/i2/p
  413_1
• On the non-uniqueness of the inverse MEG problem.
  G Dassios, A S Fokas and F Kariotou. Inverse
  Problems 21 No 2 (April 2005) L1-L5.
  http//www.iop.org/EJ/article/0266-5611/21/2/L01/i
  p5_2_l01.html

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