Post on 19-Dec-2015
Brain Electrical Source Analysis
This is most likely location of dipole
Project “Forward Solution”
Compare to actual data
Brain Electrical Source Analysis
• EEG data can now be coregistered with high-resolution MRI image
Anatomical MRI
Brain Electrical Source Analysis
• EEG data can now be coregistered with high-resolution MRI image
Anatomical MRI
3D volume is rendered and electrode locations are superimposed
Brain Electrical Source Analysis
• EEG data can now be coregistered with high-resolution MRI image
Magnetoencephalography
• For any electric current, there is an associated magnetic field
Magnetic Field
Electric Current
Magnetoencephalography
• For any electric current, there is an associated magnetic field
• magnetic sensors called “SQuID”s can measure very small fields associated with current flowing through extracellular space
Magnetic Field
Electric Current
SQuIDAmplifier
Magnetoencephalography
• MEG systems use many sensors to accomplish source analysis
• MEG and EEG are complementary because they are sensitive to orthogonal current flows
• MEG is very expensive
MEG/EEG
• Any complex waveform can be decomposed into component frequencies– E.g.
• White light decomposes into the visible spectrum
• Musical chords decompose into individual notes
MEG/EEG
• MEG/EEG is characterized by various patterns of oscillations
• These oscillations superpose in the raw data
4 Hz
8 Hz
15 Hz
21 Hz
4 Hz + 8 Hz + 15 Hz + 21 Hz =
How can we visualize these oscillations?• The amount of energy at any frequency is expressed as
% power change relative to pre-stimulus baseline
• Power can change over time
Fre
quen
cy
Time0
(onset)+200 +400
4 Hz
8 Hz
16 Hz
24 Hz
48 Hz
% changeFromPre-stimulus
+600
Where in the brain are these oscillations coming from?
• We can select and collapse any time/frequency window and plot relative power across all sensors
Win Lose
Where in the brain are these oscillations coming from?
• Can we do better than 2D plots on a flattened head?
• As in ERP analysis we (often) want to know what cortical structures might have generated the signal of interest
• One approach to finding those signal sources is Beamformer
Beamforming
• Beamforming is a signal processing technique used in a variety of applications:– Sonar– Radar– Radio telescopes– Cellular transmision
Beamforming in EEG/MEG
• It then adjusts the signal recorded at each sensor to tune the sensor array to each voxel in turn
Q = % signal change over baseline
Beamformer
• To apply Beamformer to EEG or MEG data we first select the band and time window of interest – in this case theta between about 175 and 375 ms
Beamformer
• Applying the Beamformer approach yields EEG or MEG data with fMRI-like imaging
L
R
Your Research Proposal Project
• A research proposal attempts to persuade the reader that:– The underlying question is highly important
– The proposed methodology and experimental design is the best approach
– That you have the knowledge and know-how to do the proposed research
L
R
Your Research Proposal Project
• A research proposal is therefore similar to many other situations in which you will try to persuade someone of something– The skill is portable
L
Your Research Proposal Project
• As in other situations, your reader should be assumed to be unconvinced and thus unwilling to spend much time and energy entertaining your argument!
• You must make your argument easy and fast
• The key to that is organization
L
Research Proposals Should be “Theory Driven”
• Most proposals are organized around a specific theory
• What is the difference between a theory and a question?
L
The Parts of a Research Proposal
• Background
• Statement of the theory
• Prediction(s) that follow from the theory
• Experimental Method and Design
• Timeline
• Budget
• References
L
The Parts of a Research Proposal
• Background
• Statement of the theory
• Prediction(s) that follow from the theory
• Experimental Method and Design
• Timeline
• Budget
• References
L
These aren’t necessary for your project