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Introduction to fMRI

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Introduction to MRI/fMRI
PSY101 . Lab 3 . Fall 2014

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Scanners at the PNI
Siemens Skyra Siemens Prisma

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The magnetic field
• MRI scanners create strong magnetic fields (between 1.5 and 7 Tesla)
• 1 Tesla = 10,000 Gauss
• The s...

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Introduction to fMRI

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These are slides for an introductory lecture on fMRI/MRI and analysis of fMRI data. The corresponding tutorial is available on my website kathiseidlrathkopf.com

These are slides for an introductory lecture on fMRI/MRI and analysis of fMRI data. The corresponding tutorial is available on my website kathiseidlrathkopf.com

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Introduction to fMRI

  1. 1. Introduction to MRI/fMRI PSY101 . Lab 3 . Fall 2014
  2. 2. Scanners at the PNI Siemens Skyra Siemens Prisma
  3. 3. The magnetic field • MRI scanners create strong magnetic fields (between 1.5 and 7 Tesla) • 1 Tesla = 10,000 Gauss • The strength of the magnetic field of the earth ranges from 0.25 -0.65 Gauss Risks associated with the magnetic field • magnetic field can pick up even large magnetic objects and pull them into the scanner bore with great velocity • Rotation of metal objects that are located in the body • Malfunction of electronic devices (e.g. pacemakers) • Electric burns can arise from electrically conductive objects in the magenetic field
  4. 4. Two types of scans MRI functional MRI voxel
  5. 5. MRI physics (strongly oversimplified) • a person goes into a strong magnet • atomic nuclei reorient themselves along the magnetic field • a radiofrequency pulse (1) flips the nuclei from the oriented position and (2) synchronizes the precession of their spin axis • a receiver measures the time until the nuclei return to their original orientation (structural scans) or desynchronize (functional scans) outside scanner inside scanner precession
  6. 6. What is measured in fMRI? • neurons consume oxygen and nutrients • increased neural activity requires increased supply of oxygen • oxygen is bound to hemoglobin (oxyhemoglobin vs. de-oxyhemoglobin) • to supply neurons with oxygen and glucose, blood flow is increased locally • the local increase in blood flow leads to a displacement of de-oxyhemoglobin • MR signal is higher for oxygenated compared to de-oxygenated blood
  7. 7. the blood oxygen level dependent (BOLD) response 300 10 20 0 time [s] peak undershoot hemodynamic lag stimulus
  8. 8. time [s] BOLD stimulus the BOLD response over time
  9. 9. A [BOLD] response is measured for every voxel
  10. 10. … 1 Volume = 1 image of entire brain (in this case 36 horizontal slices) 1 Run (147 TRs) TR* 1 TR 2 TR 2 TR 147 *TR = Time of Repetition = time it takes to acquire one volume 4-D datasets
  11. 11. Outline of a scan session 1 Task instruction + safety screening 2 Put subject in the scanner 3 Localizer scan 4 Anatomical scan 5 Shimming 6 Test scan 7 Data collection 8 [Field map]
  12. 12. Today’s experiments PSY101 . Lab 3 . Fall 2014
  13. 13. Face/Scene Localizer scenes faces scrambled scenes scrambled faces Stimuli presented in blocked design Task: 1-back task
  14. 14. posterior Category-selective visual cortex anterior LHRH PPA FFA > >
  15. 15. Beyond faces and scenes: The FFA and PPA as ROIs for studying other cognitive functions 0 1 2 3 4 5 6 FFA PPA attend faces attend scenes Attend faces: female vs. male Attend scenes: indoor vs. outdoor Attention enhances responses to task-relevant information! Identical physical stimulation during the two attention conditions
  16. 16. Introduction to fMRI analysis PSY101 . Lab 3 . Fall 2014
  17. 17. Before we get started … 1. Log on to a Lab PC using the VMUser account Username: .VMUser Password: @psychLAB 2. Open VMWare Player 3. Within VMWare Player, open FSLVm6_64
  18. 18. Analysis occurs in two main steps 1 Preprocessing 2 Statistical analysis
  19. 19. Preprocessing 1 Slice timing correction Correct for the timing difference in the sequential acquisition of slices 2 Motion correction Correct for subject’s head movements 3 Spatial smoothing Increase signal-to-noise ratio 4 Temporal smoothing Remove unwanted temporal components 5 Registration Align functional to anatomical data Align functional and anatomical data with a standard space (“Normalization”)
  20. 20. Slice-timing correction • In our experiment we measured one functional image (volume) of the brain every 2 seconds • Each volume was acquired in 36 interleaved horizontal slices • This means that every slice was acquired at a different time during the 2s TR Space[slices] time [s] volume (TR) volume (TR) 1 36 18
  21. 21. Slice-timing correction To correct for this difference in timing, time- series in each slice is phase-shifted so that it appears as if all slices were acquired at the same time Space[slices] time [s] volume (TR) volume (TR) 1 36 18
  22. 22. Motion correction • Data are acquired in absolute spatial coordinates. If head movement occurs, the time course of a voxel is derived from different parts of the brain • Head movement is often correlated with the task • Head motion decreases statistical power before movement after movement
  23. 23. Dealing with head motion During data acquisition • Tell participants to be still in the scanner • Head restraints During preprocessing • Remove time points with excessive movement • Spatially align functional data to one reference image • Adjust 6 parameters: translational rotational yaw pitch rollx, y, z
  24. 24. roll [°] pitch [°] yaw [°] I-S [mm] R-L [mm] A-P [mm] Rotation Translation Motion correction output
  25. 25. • Apply a Gaussian filter to effectively spread the intensity at each voxel to neighboring voxels. • Increases signal-to-noise ratio: blurring reduces high frequency noise while retaining signal Spatial smoothing FWHM = full width at half maximum before smoothing with smoothing FWHM 4mm
  26. 26. Temporal filtering The MRI signal can contain unwanted temporal components: • High-frequency noise • Low-frequency drifts Remove unwanted temporal components using filters • High pass: remove frequencies below cut-off frequency • Low pass: remove frequencies above cut-off frequency raw filtered
  27. 27. Normalization Individual brains differ largely in size, form, and location of brain areas Projecting data from different individual into a common standard space, allows for • combining data across subjects • making comparisons across studies
  28. 28. Statistical analysis: regression Core idea: observed data can be explained by a combination of weighted regressors Example: Explain miles per gallon (mpg) of a car, based on the car’s weight and the driver’s height. Observed data: mpg Regressors: car’s weight, driver’s height Weights: βcar’s weight = high; βdriver’s height = low 0 5 10 15 20 25 30 2 2.5 3 3.5 4 4.5 5 0 5 10 15 20 25 30 1.4 1.6 1.8 2 2.2 mpg mpg Driver’s height [m]Car’s weight [t]
  29. 29. observed data = BOLD response extracted from an individual voxels Regression in fMRI
  30. 30. Regressors: timing of conditions combined with assumptions about the shape of the BOLD response faces scenesscr scenes scr faces fixation scenesfixation faces scenes scr(ambled) scenes scr(ambled) faces time
  31. 31. scr(ambled) scenes scr(ambled) faces faces scenesscr scenes scr faces fixation scenesfixation faces scenes time Regressors: timing of conditions combined with assumptions about the shape of the BOLD response
  32. 32. Regressors are combined into a single model time faces scenesscr scenes scr faces fixation scenesfixation
  33. 33. Regressors that account for a lot of variance in the signal receive high beta values time faces scenesscr scenes scr faces fixation scenesfixation model data weights
  34. 34. Weights are plotted as statistical parametric maps
  35. 35. Contrasts: intact vs. scrambled objects >
  36. 36. Significance thresholds p = 1 p = 0.03 p = 0.4 p = 0.01
  37. 37. Before you leave … 1. Grab all the files you still need 2. Delete the firstlevel_R1.feat directory you created during your analysis 3. Power off the virtual machine 4. Log off the Lab PC

Editor's Notes

  • Precession
    The movement of a rotating proton within a magnetic field is similar to the movement of a top in the earth’s gravitational field. In addition to the spinning motion, axis of spin itself moves around the main axis of the magnetic field. This motion is know as precession.
  • Precession

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