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Signal and Noise in fMRI

Signal and Noise in fMRI. fMRI Graduate Course October 15, 2003. What is signal? What is noise?. Signal, literally defined Amount of current in receiver coil What can we control? Scanner properties (e.g., field strength) Experimental task timing Subject compliance (through training)

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Signal and Noise in fMRI

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  1. Signal and Noise in fMRI fMRI Graduate Course October 15, 2003

  2. What is signal? What is noise? • Signal, literally defined • Amount of current in receiver coil • What can we control? • Scanner properties (e.g., field strength) • Experimental task timing • Subject compliance (through training) • Head motion (to some degree) • What can’t we control? • Electrical variability in scanner • Physiologic variation (e.g., heart rate) • Some head motion • Differences across subjects

  3. I. Introduction to SNR

  4. Signal, noise, and the General Linear Model Amplitude (solve for) Measured Data Noise Design Model Cf. Boynton et al., 1996

  5. Signal-Noise-Ratio (SNR) Task-Related Variability Non-task-related Variability

  6. E Signal Size in fMRI A 45 B 50 C 50 - 45 (50-45)/45 D

  7. Differences in SNR

  8. Voxel 1 790 830 870 Voxel 2 690 730 770 Voxel 3 770 810 850

  9. A t = 16 B C t = 5 t = 8

  10. Effects of SNR: Simulation Data • Hemodynamic response • Unit amplitude • Flat prestimulus baseline • Gaussian Noise • Temporally uncorrelated (white) • Noise assumed to be constant over epoch • SNR varied across simulations • Max: 2.0, Min: 0.125

  11. SNR = 2.0

  12. SNR = 1.0

  13. SNR = 0.5

  14. SNR = 0.25

  15. SNR = 0.125

  16. SNR = 4.0 SNR = 2.0 SNR = .5 SNR = 1.0

  17. What are typical SNRs for fMRI data? • Signal amplitude • MR units: 5-10 units (baseline: ~700) • Percent signal change: 0.5-2% • Noise amplitude • MR units: 10-50 • Percent signal change: 0.5-5% • SNR range • Total range: 0.1 to 4.0 • Typical: 0.2 – 0.5

  18. Effects of Field Strength on SNR Turner et al., 1993

  19. Theoretical Effects of Field Strength • SNR = signal / noise • SNR increases linearly with field strength • Signal increases with square of field strength • Noise increases linearly with field strength • A 4.0T scanner should have 2.7x SNR of 1.5T scanner • T1 and T2* both change with field strength • T1 increases, reducing signal recovery • T2* decreases, increasing BOLD contrast

  20. Measured Effects of Field Strength • SNR usually increases by less than theoretical prediction • Sub-linear increases in SNR; large vessel effects may be independent of field strength • Where tested, clear advantages of higher field have been demonstrated • But, physiological noise may counteract gains at high field ( > ~4.0T) • Spatial extent increases with field strength • Increased susceptibility artifacts

  21. Excitation vs. Inhibition M1 SMA M1 SMA Waldvogel, et al., 2000

  22. II. Properties of Noise in fMRICan we assume Gaussian noise?

  23. Types of Noise • Thermal noise • Responsible for variation in background • Eddy currents, scanner heating • Power fluctuations • Typically caused by scanner problems • Variation in subject cognition • Timing of processes • Head motion effects • Physiological changes • Differences across brain regions • Functional differences • Large vessel effects • Artifact-induced problems

  24. Why is noise assumed to be Gaussian? • Central limit theorem

  25. Is noise constant through time?

  26. Is fMRI noise Gaussian (over time)?

  27. Is Signal Gaussian (over voxels)?

  28. Variability

  29. Variability in Subject Behavior: Issues • Cognitive processes are not static • May take time to engage • Often variable across trials • Subjects’ attention/arousal wax and wane • Subjects adopt different strategies • Feedback- or sequence-based • Problem-solving methods • Subjects engage in non-task cognition • Non-task periods do not have the absence of thinking What can we do about these problems?

  30. Response Time Variability A B

  31. A B C D E F Intersubject Variability A & B: Responses across subjects for 2 sessions C & D: Responses within single subjects across days E & F: Responses within single subjects within a session - Aguirre et al., 1998

  32. Variability Across Subjects D’Esposito et al., 1999

  33. Young Adults

  34. Elderly Adults

  35. Effects of Intersubject Variability

  36. Parrish et al., 2000

  37. Implications of Inter-Subject Variability • Use of individual subject’s hemodynamic responses • Corrects for differences in latency/shape • Suggests iterative HDR analysis • Initial analyses use canonical HDR • Functional ROIs drawn, interrogated for new HDR • Repeat until convergence • Requires appropriate statistical measures • Random effects analyses • Use statistical tests across subjects as dependent measure (rather than averaged data)

  38. Spatial Variability? A B McGonigle et al., 2000

  39. Standard Deviation Image

  40. Spatial Distribution of Noise A: Anatomical Image B: Noise image C: Physiological noise D: Motion-related noise E: Phantom (all noise) F: Phantom (Physiological) - Kruger & Glover (2001)

  41. Low Frequency Noise

  42. High Frequency Noise

  43. III. Methods for Improving SNR

  44. Fundamental Rule of SNR For Gaussian noise, experimental power increases with the square root of the number of observations

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