Interpreting EEG/MEG data

Exploiting temporal delays in interpreting EEG/MEG data in terms of brain connectivity

Problem of volume conduction
Cross-spectrum
EEG-simulation of ERD (two sources)
Rest coherence
EEG-simulation of ERD (one source)
Change in coherence pt 1
Change in coherence pt 2
Observation
Explicit derivation
Coherence
Selfpaced movement - C3-C4 relationships
Significance - False Discovery Rate (FDR)
Simulated non-interacting sources
Results
Difference between cross-spectrum pt 1
Difference between cross-spectrum pt 2
Imaginary part - 5 dipoles
“Philosophy” pt 1
“Philosophy” pt 2
“Philosophy” pt 3
Pairwise Interacting Source Analysis (PISA)
EEG - imagined foot movement
Music pt 1
Music pt 2
Example 1
Example 2
Result ISA-pattern
Conclusion

Presentation Slides

Video

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Magnetoencephalography

Magnetoencephalography (MEG )

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


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


Diagram of MEG setup

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 fT*Hz^-1/2

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

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

Magnetic Shielding
Forward Problem
The Inverse Problem
Synthetic Aperture Magnetometry
Magnetic Source Imaging
Dipole Model Source Localization
Lead-field-based imaging approach
Independent Component Analysis
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

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


References
Magnetoencephalography (MEG).ppt

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