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

Freq

uenc

y

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

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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

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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

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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

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Research Proposals Should be “Theory Driven”

• Most proposals are organized around a specific theory

• What is the difference between a theory and a question?

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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

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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

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These aren’t necessary for your project