1. Signal to noise ratio (SNR) and data quality

2. Coils Source: Joe Gati Head coil homogenous signal moderate SNR Surface coil highest signal at hotspot high SNR at hotspot

3. Calculating Signal:Noise Ratio Pick a region of interest (ROI) outside the brain free from artifacts (no ghosts, susceptibility artifacts). Find mean (  ) and standard deviation (SD). Pick an ROI inside the brain in the area you care about. Find  and SD. SNR =  brain /  outside = 200/4 = 50 Alternatively SNR =  brain / SD outside = 200/2.1 = 95 (should be 1/1.91 of above because  /SD ~ 1.91) Head coil should have SNR > 50:1 Surface coil should have SNR > 100:1 When citing SNR, state which denominator you used. Source: Joe Gati, personal communication e.g.,  =4, SD=2.1 e.g.,  = 200

4. What affects SNR? Physical factors PHYSICAL FACTORSSOLUTION & TRADEOFF Thermal Noise (body & system)Inherent – can’t change Magnet Strength e.g. 1.5T  4T gives 2-4X increase in SNR Use higher field magnet – additional cost and maintenance – physiological noise may increase Coil e.g., head  surface coil gives ~2+X increase in SNR Use surface coil – Lose other brain areas – Lose homogeneity Voxel size e.g., doubling slice thickness increases SNR by root- 2 Use larger voxel size – Lose resolution Sampling timeLonger scan sessions – additional time, money and subject discomfort Source: Doug Noll’s online tutorial and Jody Culham’s web siteDoug Noll’s online tutorial

5. What affects SNR? Physiological factors PHYSIOLOGICAL FACTORSSOLUTION & TRADEOFF Cardiac and respiratory noiseMonitor and compensate – very difficult to do Head (and body) motionUse experienced or well-trained subjects – limited subject pool Use head-restraint system – subject discomfort Post-processing correction – often incompletely effective Single trials to avoid body motion Low frequency noiseUse smart design Perform post-processing filtering BOLD noise (neural and vascular fluctuations)Use many trials to average out variability Behavioral variationsUse well-controlled paradigm Use many trials to average out variability Source: Doug Noll’s online tutorial and Jody Culham’s web siteDoug Noll’s online tutorial

6. Physiological Noise Respiration every 4-10 sec (0.3 Hz) moving chest distorts susceptibility deep breaths particularly problematic (instruct subject well) Cardiac Cycle every ~1 sec (0.9 Hz) pulsing motion, blood changes Solutions gating avoiding paradigms at those frequencies

7. Low and High Frequency Noise

8. Head Motion: Main Artifacts Head motion Problems time1time2  1)Rim artifacts hard to tell activation from artifacts artifacts can work against activation 2) Region of interest moves lose effects because you’re sampling outside ROI Looking at the negative tail can help you identify artifacts Playing a movie of slices over time helps you detect head motion

9. Head Restraint Head Vise (more comfortable than it sounds!) Bite Bar (less comfortable than head vice!) Other: Thermoplastic Mask (used in PET) Vacuum packs Tape across forehead Foam padding

10. Motion Correction Options 2D realignment fast 2 degrees of freedom (2 translations) 3D realignment slow more accurate 6 degrees of freedom (3 translations, 3 rotations) can lose parts of brain Can realign within a run or within a session

11. Motion Correction Output gradual motions are usually well-corrected abrupt motions are more of a problem (esp if related to paradigm SPM output raw data linear trend removal motion corrected in SPM Caveat: Motion correction in BV doesn’t seem nearly as good as SPM Caveat: Motion correction can cause artifacts where there were none

12. Head Motion: Susceptibility Artifacts Stationary HeadPhantom Bag of Saline on a Stick experimenter moves saline left and right every 20 sec without touching subject or phantom or Analyze data using saline motion as “paradigm ”

13. Head Motion: Solution to Susceptibility Solution: one trial every 10 or 20 sec fMRI signal is delayed ~5 sec distinguish true activity from artifacts Especially good for motor paradigms – any artifact from the movement made by the subject should be gone once the critical data is collected! 0510 Time (Sec) fMRI Signal action activity artifact

14. Effect of Filtering – spatial smoothing. before after Source: Brain Voyager course slides

15. Trial-to-trial variability Single trials Average of all trials from 2 runs

16. Other Artifacts GhostsZebra Brains Spikes Metallic Objects (e.g., hair tie)

17. Other Artifacts Poor shimming