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fMRI Group

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  1. fMRI Group Natasha Matthews, Ashley Parks, Destiny Miller, Ziad Safadi, Dana Tudorascu, Julia Sacher. Adviser: Mark Wheeler

  2. Aims Learn to implement block and event-related fMRI experimental designs Develop a thorough understanding of the major choice points in the analysis stream for fMRI data Learn fMRI data post-processing: GLM and group analysis

  3. Design Block ER • Pros: • High detection power due to response summation • Simple analysis Con: • Can’t look at effects of single events (e.g., correct vs. incorrect trials; target present vs. absent) • Pros: • Good estimation of time courses and reasonable detection • Enables post hoc sorting (e.g., correct vs. incorrect; target present vs. absent) Con: • Some loss of power for the contrast between trial types.

  4. Task: Median Nerve Stimulation A nerve stimulation device is place on the subjects wrist above their median nerve An electrical pulse is applied, resulting in activation of the nerve

  5. Scanner : Siemens 3T Trio Number of subjects: 3 Anatomical Scan T1 (MPRAGE) Slices : 38 Functional Scan (Block design) Whole Brain Scan Slices : 38 Volumes:144 Voxel Size : 4 mm x 4 mm x 3.2mm Interleaved Acquisition TR : 2s T2* Contrast Data Acquisition Scanner : Siemens 3T Trio Number of subjects: 3 Anatomical Scan T1 (MPRAGE) Slices : 38 Voxel Size: 0.5mm x 0.5mm x 1.0mm Scanner : Siemens 3T Trio Number of subjects: 3 Anatomical Scan T1 (MPRAGE) Functional Scan (Event-related design) Whole Brain Scan Slices : 38 Volumes run 1: 256 Volumes run 2: 256 Voxel Size : 4 mm x 4 mm x 3.2mm Interleaved Acquisition TR : 2s T2* Contrast

  6. Blocked Design

  7. Median Nerve Stimulation Localizer Task Design Goal: Determine Motor Cortex Activation Region for Event Related Task ZAP ZAP ZAP Rest Rest Rest Rest … Time 0 s……....……….22s…….32s…………54s……64s…………86s……..96s……………. …278s Task Volumes……………….11.…….16..…….……27.……32..…………43.……...48.……………. …139 (+5 extra)

  8. Nerve Stimulation Localizer Task

  9. Data Preprocessing for individual subjects Data Format: convert scanner images to format readable by AFNI Dicom data, reformat to BRICK & .HEAD Time Shift (slice timing correction): interpolation of time series to a specific point in TR (Fourier transformation: most accurate). Spatial Registration (motion correction):of all images in the time series to a base image: we chose 6th image of run (close to structural image). Smoothing: We investigated 4mm, 8mm, 12mm.

  10. Spatial Smoothing

  11. Box-car Model

  12. Model Fit: No smoothing

  13. Model Fit: 4mm smooth

  14. Model Fit: 8mm smooth

  15. Model Fit: 12 mm smooth

  16. Data Preprocessing: Preparing for group analysis Normalize time series: Regression coefficients now expressed as % signal change. For each run divide each time point by the mean and multiply by 100. Original data Normalized data

  17. Preparing data for group analysis Registration to standard space: Can be done manually or automatically

  18. Atlas Templates TT_N27+tlrc:AKA “Colin brain”. One subject (Colin) scanned 27 times and averaged. TT_avg152T1+tlrc: Montreal Neurological Institute template, average volume of 152 normal brains.

  19. Group t-test (zap > baseline)

  20. Event-related Design

  21. Event Related Design: Stimulation with 3 different frequencies Zap ON 9.09 3.85 2.00 2 Hz 3.85 Hz 9 Hz Inter-stimulus jitter - 2, 4, 6 seconds

  22. Data from a representative subject 2 Hz 3.8 Hz 9 Hz

  23. Comparison of 9 Hz Event Related Design and Block Design Event related design Block design

  24. Creation of ROI masks to explore event-related data ROI from functional results (localizer task) ROI based on atlas coordinates

  25. Peak of the activation Time courses extracted from functionally defined ROI Area under the curve

  26. Results of ANOVA on event related datausing the PEAK of the time course

  27. Results of ANOVA on event related datausing the AREA UNDER THE CURVE

  28. Thank you Mark Wheeler Seong-Gi Kim Tomika Cohen Rebecca Clark Fellow MNTPers!