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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. What does MEG Measure?. Data Acquisition and Analysis Steps. Acquisition. Coregistration. Preprocessing. Averaging.

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Exploring Magnetoencephalography (MEG ) Data Acquisition and Analysis Techniques

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  1. 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

  2. What does MEG Measure?

  3. Data Acquisition and Analysis Steps Acquisition Coregistration Preprocessing Averaging Localization

  4. Data Acquisition and Analysis Steps Acquisition Fitting isotrack points to structural MRI Fitting a sphere Coregistration Preprocessing Averaging Localization

  5. Data Acquisition and Analysis Steps Acquisition Temporal Filtering Bandpass 0.5 – 40Hz Maxwell’s Filtering Signal Source Projection (SSP) Coregistration Preprocessing Averaging Localization

  6. Raw Continuous Data Time frame: 10000 ms

  7. Elekta'sMaxwell Filtering Method

  8. After Maxwell Filtering Time frame: 10000 ms

  9. Is the Filtering Process Worth it?

  10. Reduction in Covariance of Magnetometer Signals

  11. Data Acquisition and Analysis Steps Acquisition Selecting a time region and baseline Averaging by condition Coregistration Preprocessing Averaging Localization

  12. Retrieving Trials 1000ms :Time-frame Baseline: 200ms

  13. Median Nerve Stimulation • Random 10ms long electrical stimulation of same voltage • Purpose: • localizer • explore effect of number of trials on results

  14. Median Nerve Stimulation Average 180 Trials

  15. Hearing Your Voice in Real Time • Press a button • Read word out loud + house + book … + water Purpose: • explore limitations of MEG (jaw movement, head motion, activates many simultaneous brain regions e.t.c.)

  16. Hearing Your Voice in Real Time Stimulation Average 60 Trials - Complex task: elicits response from multiple brain regions - Variations in subject’s response

  17. Data Acquisition and Analysis Steps Acquisition Dipole Fitting Coregistration Preprocessing Averaging Localization

  18. Source Localization Forward Problem Solvable! ? Always an estimate Inverse Problem

  19. Dipole Fitting Technique PROCEDURE Pick a subset of sensors (ROI) Select a time point Dipole fit estimates magnetic field given the two parameters ? 4. Estimated Signals Measured Signals

  20. Measures of Quality 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

  21. 22ms 52ms 83ms Median Nerve Dipole Fitting Results 7 sensors 99.2% 98.2% 99.7% 97.6% 85.8% 42 sensors 84.6% 92 sensors 84.6% 85.8% 97.6%

  22. Hearing Your Voice in Real Time Dipole Fitting Results 80.3% 61.0% 82.2% Post-central Gyrus Brain Stem Face Area • Fits dipole in improbable locations (single dipole insufficient) • Needs a different source localization technique

  23. Summary • We have explored the following steps in MEG image acquisition and analysis: • Acquisitionof the MEG signals • Coregistrationof 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.

  24. 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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