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Mark Wheeler Destiny Miller Carly Demopoulos Kyle Dunovan Martin Krönke Todd Monroe Dil Singhabahu

MNTP Summer Workshop 2011 - fMRI BOLD Response to Median Nerve Stimulation: A Comparison of Block and Event-Related Design. Mark Wheeler Destiny Miller Carly Demopoulos Kyle Dunovan Martin Krönke Todd Monroe Dil Singhabahu Elisa Torres Christopher Walker. Funded by: NIH R90DA02342.

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Mark Wheeler Destiny Miller Carly Demopoulos Kyle Dunovan Martin Krönke Todd Monroe Dil Singhabahu

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  1. MNTP Summer Workshop 2011 - fMRIBOLD Response to Median Nerve Stimulation: A Comparison of Block and Event-Related Design • Mark Wheeler • Destiny Miller • Carly Demopoulos • Kyle Dunovan • Martin Krönke • Todd Monroe • Dil Singhabahu • Elisa Torres • Christopher Walker Funded by: NIH R90DA02342

  2. MNTP Workshop: Learning Objectives • In-depth understanding of preprocessing of fMRI data • Filtering • Motion correction • Slice Time Correction • Smoothing • Registration • Conduct first-level analyses • Conduct group-level analyses • Investigate two experimental designs

  3. The Task: Median Nerve Stimulation • Electrical stimulation of the median nerve by applying pulses to the wrist of the non-dominant hand • Voltage: motor threshold

  4. Stim ON 10s 15Hz 15Hz 15Hz Stim OFF 16s Blocked Design Stim ON 10s Stim ON 10s Stim OFF 16s Stim OFF 16s 10 repetitions

  5. Event 1 Event 2 Event 3 Event 4 Event-Related Design

  6. 40Hz 80Hz 15Hz 15Hz 40Hz + + + + 4s (2TR) 2s Jitter 4s 6s Jitter Time 4s 2s Jitter 4s 4s Jitter 4s Event Related Task Design • Three different frequencies: 15Hz, 40Hz, 80Hz (Kampe, Jones & Auer, 2000) • Event length: 4s • Inter-stimulus jitter – 2, 4, 6 seconds • Exponential distribution (Dale, 1999)

  7. Data Acquisition • Scanner: Allegra 3T • N=5 • Structural Scan • T1 weighted MPRAGE • 176 slices • Voxel Size 1mm • Functional Scans: Median Nerve Stimulation • Volumes • 140 for block • 233 for event-related • Voxel Size 3.5mm • Slices 34 • Interleaved • TR 2s • T2* contrast

  8. Data-conversion • Dicom2Nifti Block Design Single Subject Demonstration • Statistical analysis • GLM Statistical Parametric Mapping Processing stream Preprocessing Slice-timing Motion correction Temporal Filtering Smoothing Registration / Normalization

  9. Preprocessing: Slice Time Correction (STC) • Stronger influence of STC for event-related vs. block-designs • sensitivity to timing / shape of HRF • Slice acquisition order • interleaved slice acquisition (34 slices in 2s) • avoids cross-slice excitation • Debate on STC before / after motion correction? • before head motion (interleaved) • Temporal non-linear sinc interpolation Huettel, Song, McCarthy 2009

  10. Motion correction • Due to subject movements inside the scanner, a voxel might represent different parts of the brain across time points, introducing artifacts Huettel, Song, McCarthy, 2004

  11. 0.003 0.2 mm radians -0.1 -0.004 time (TRs) time (TRs) Motion correction • Estimation • Rigid-body transformation 6 DOF • Interpolation • trilinear (tri-)linear Non-linear (sinc, B-spline) Nearest neighbour

  12. No Motion correction % signal change Z-Value: 3.9 Time (TRs) Crosshair location: Postcentral gyrus Motion corrected % signal change Z-Value: 3.8 Time (TRs)

  13. Temporal Filtering • Artifacts like “slow scanner drift” and changes in basal metabolism can reduce SNR • A highpass filter can remove these unwanted effects • Do not want to remove task-related signal • Block Design Task: 10s on, 16s rest • Woolrich et al. (2001) recommends filter of at least 2 epochs duration • 52s temporal filter  .019 Hz • Also compared effects of 0 Hz, .038 Hz, .01 Hz • Little difference between • .019 Hz • .038 Hz • .01 Hz

  14. 0Hz / No Temporal Filtering % Signal Change Time (TRs) 52s / .019Hz Temporal Filter % Signal Change Time (TRs)

  15. Smoothing • Spatially filters data using Gaussian Kernel to remove noise • Reduces spatial resolution • Improves signal to noise ratio • Consider ROI and voxel size in determining the size of the kernel Gaussian Weight

  16. 8mm smooth 0mm smooth 4mm smooth 20mm smooth

  17. Registration / Normalization Why? • Group analysis • Compare results in common coordinate system (MNI) Karsten Müller How? • Estimate transformation • Combining affine-linear (12 DOF) subject  standard space (FSL FLIRT) • nonlinear methods (> 12 DOF) subject  subject (FSL FNIRT) • least squares cost function • 2. Resample / Transform / Interpolate • Nearest neighbour • Linear interpolations • Bi-, trilinear • Non-linear interpolations • B-Spline, sinc (Hanning)

  18. Preprocessing Summary • Data-conversion • Dicom2Nifti Block Design • Filtering • Highpass (52s / .019Hz) • Discrete cosine transform • Statistical analysis • GLM • 1st-level • Group-analyses • Motion correction • Rigid-body, 6DOF • Trilinear interpolation • Slice-timing • Interleaved • Sinc interpolation • Smoothing • FWHM, 8mm Statistical Parametric Mapping • Registration / Normalization • Affine-linear + Non-linear

  19. Block design Event-related 15Hz 15Hz 40Hz 80Hz Design matrix comparison: Block vs. Event-related Time

  20. Block vs. Event-Related Design • Block Design • 15Hz activation map • Modeled with gamma function • Event-Related Design • 15Hz activation map • Modeled with double-gamma function

  21. Functionally vs.structurally defined ROIs ROI (structure) ROI (functional 9 mm) ROI (functional 6 mm) ROI (functional 3 mm)

  22. 0.50 Functionally Defined Structurally Defined 0.40 0.30 0.20 0.10 0.00 -0.10 15Hz 40Hz 80Hz 80Hz > All* Effect of Region of Interest on Task Related Median Percent Signal Change Median Percent Signal Change ROI – F (1, 4) = 6.431, p = .064 Frequency – F (2, 4) = 10.046, p = .007 Frequency * ROI – F (2, 8) = 5.101, p = .037

  23. Future Directions: Condition and Subject Timeseries Modeled 15 Hz response for 1 subject Arbitrary Units

  24. 80 Hz above baseline 40 Hz above baseline 15 Hz above baseline Event-Related Activation Comparison

  25. Future Directions: Overlapping Activation • Investigate condition specific differences in activation patterns

  26. References Dale, A. M. (1999). Optimal experimental design for event-related fMRI. Human Brain Mapping, 8: 109–114.doi: 10.1002/(SICI)1097-0193(1999)8:2/3<109::AID- HBM7>3.0.CO;2-W Huettel, S. A., Song, A. W. and McCarthy, G. (2004). Functional magnetic resonance imaging. Sunderland, MA: Sinauer Associates Kampe, K. K., Jones, R. A. and Auer, D. P. (2000). Frequency dependence of the functional MRI response after electrical median nerve stimulation. Human Brain Mapping, 9: 106–114. doi: 10.1002/(SICI)1097-0193 (200002)9:2<106::AID- HBM5>3.0.CO;2-Y Woolrich, M. W., Ripley, B. D., Brady, M., Smith, S. M. (2001). Temporal autocorrelation in univariate linear modeling of FMRI data. NeuroImage, 14, 1370-1386.

  27. Thank you Mark Wheeler Destiny Miller Seong-Gi Kim Bill Eddy Tomika Cohen Rebecca Clark Fellow MNTPers! Funded by: NIH R90DA02342

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