Exploring Magnetoencephalography (MEG ) Data Acquisition and Analysis Techniques

Exploring Magnetoencephalography (MEG)Data Acquisition and Analysis Techniques

Rosalia F. Tungaraza, Ph.D.

Anthony Kelly, B.A.

Ajay Niranjan, M.D., MBA

July 22, 2010

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What does MEG Measure?

Data Acquisition and Analysis Steps

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Acquisition

Coregistration

Preprocessing

Averaging

Localization

Data Acquisition and Analysis Steps

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Fitting isotrack points to structural MRI

Fitting a sphere

Acquisition

Coregistration

Preprocessing

Averaging

Localization

Data Acquisition and Analysis Steps

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Temporal FilteringBandpass 0.5 – 40Hz

Maxwell’s Filtering

Signal Source Projection (SSP)

Acquisition

Coregistration

Preprocessing

Averaging

Localization

Raw Continuous Data

Time frame: 10000 ms 6

Elekta's Maxwell Filtering Method

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After Maxwell Filtering

Time frame: 10000 ms 8

Is the Filtering Process Worth it?

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Reduction in Covariance of Magnetometer Signals

Data Acquisition and Analysis Steps

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Selecting a time region and baseline

Averaging by condition

Acquisition

Coregistration

Preprocessing

Averaging

Localization

Retrieving Trials

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Baseline: 200ms

1000ms :Time-frame

Median Nerve Stimulation

● Random 10ms long electrical stimulation of same voltage

● Purpose:● localizer● explore effect of number of trials on results

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Median Nerve Stimulation Average

14180 Trials

Hearing Your Voice in Real Time

Purpose:● explore limitations of MEG (jaw movement, head

motion, activates many simultaneous brain regions e.t.c.) 15

+ house

…+ water

- Press a button- Read word out loud

+ book

Hearing Your Voice in Real Time Stimulation Average

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- Complex task: elicits response from multiple brain regions- Variations in subject’s response

60 Trials

Data Acquisition and Analysis Steps

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Dipole Fitting

Acquisition

Coregistration

Preprocessing

Averaging

Localization

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Source Localization

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ForwardProblem

InverseProblem

Solvable!

Always anestimate

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?

Dipole Fitting Technique

1. Pick a subset of sensors (ROI)

2. Select a time point

3. Dipole fit estimates magnetic field given the two parameters

PROCEDURE

Estimated Signals Measured Signals

4.

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Goodness-of-fit a measure that shows how much the estimated signal matches the measured signal

Confidence Volume the volume within which the dipole fitting method is confident the dipole exists

Measures of Quality

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22ms 52ms 83ms

7 sensors

42 sensors

92 sensors

99.7% 99.2% 98.2%

84.6% 97.6% 85.8%

84.6% 97.6% 85.8%

Median Nerve Dipole Fitting Results

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Hearing Your Voice in Real Time Dipole Fitting Results

• Fits dipole in improbable locations (single dipole insufficient)

• Needs a different source localization technique

Brain Stem Post-central GyrusFace Area

61.0% 80.3% 82.2%

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SummaryWe have explored the following steps in MEG image acquisition and analysis:

• Acquisition of the MEG signals

• Coregistration of MEG isotrack data with structural MRI

• Preprocessing of the MEG signals

• Averaging the preprocessed signals

• Source localization of the averaged waveforms

We found both strengths and weaknesses, which the user must take into account before making inferences from their analyzed data.

Acknowledgements● MEG

– Erika Laing – Anna Haridis– Dr. Ajay Niranjan

● MNTP– Drs. Seong-Gi Kim and Bill Eddy– Tomika Cohen and Rebecca Clark

● All other MNTP participants

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