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Cartography and Chronometry

Cartography and Chronometry. fMRI Graduate Course October 9, 2002. Why do you need to know?. Spatial resolution Tradeoffs between coverage and spatial resolution Influences viability of preprocessing steps Temporal resolution Tradeoffs between number of slices and TR

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Cartography and Chronometry

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  1. Cartography and Chronometry fMRI Graduate Course October 9, 2002

  2. Why do you need to know? • Spatial resolution • Tradeoffs between coverage and spatial resolution • Influences viability of preprocessing steps • Temporal resolution • Tradeoffs between number of slices and TR • Needed resolution depends upon design • Non-linearity of the hemodynamic response • Limits experimental designs • Affects subsequent analyses • Reduces power

  3. Spatial Resolution

  4. What spatial resolution do we want? • Hemispheric • Lateralization studies • Selective attention studies • Systems / lobic • Relation to lesion data • Centimeter • Identification of active regions • Millimeter • Topographic mapping (e.g., motor, vision) • Sub-millimeter • Ocular Dominance Columns • Cortical Layers

  5. What determines Spatial Resolution? • Voxel Size • In-plane Resolution • Slice thickness • Spatial noise • Head motion • Artifacts • Spatial blurring • Smoothing (within subject) • Coregistration (within subject) • Normalization (within subject) • Averaging (across subjects)

  6. K – Space Revisited . . . . . . . . . . . . . . . . . . . . B A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . FOV: 10cm, Pixel Size: 2 cm FOV: 10 cm, Pixel Size: 1 cm To increase spatial resolution we need to sample at higher spatial frequencies.

  7. How large are functional voxels? = ~.08cm3  5.0mm   3.75mm   3.75mm  Within a typical brain (~1300cm3), there may be about 20,000 functional voxels.

  8. How large are anatomical voxels? = ~.004cm3  5.0mm   .9375mm   .9375mm  Within a typical brain (~1300cm3), there may be about 300,000+ anatomical voxels.

  9. Costs of Increased Spatial Resolution • Acquisition Time • In-plane • Higher resolution takes more time to fill K-space (resolution ~ size of K-space) • #Slices/second • Sample rates for 64*64 images • Early Duke fMRI: 2-4 sl/s • GE EPI: 12 sl/s • Duke Spiral (1.5T): 14 sl/s • Duke Inverse Spiral (4.0T): 21 sl/s • Reduced signal per voxel • What is our dependent measure?

  10. Effects of Stimulus Duration on Spatial Extent of Activity

  11. Example: Ocular Dominance Goodyear & Menon, 2001

  12. 4sec  10sec  Goodyear & Menon, 2001

  13. Example: Visual System 100ms 500ms 1500 ms

  14. T2* Blurring • Signal decays over time needed for collection of an image • For standard resolution images, this is not a critical issue • However, for high-resolution (in-plane) images, the time to acquire an image may be a significant fraction of T2* • Under these conditions, multi-shot imaging may be necessary.

  15. Temporal Resolution

  16. What temporal resolution do we want? • 10,000ms: Change in arousal or emotional state • 1000ms: Decisions, recall from memory • 500-1000ms: Response time • 250ms: Reaction time • 10-100ms: • Difference between response times • Initial visual processing • 10ms: Neuronal activity in one area

  17. Basic Sampling Theory • Nyquist Sampling Theorem • To be able to identify changes at frequency X, one must sample the data at 2X. • For example, if your task causes brain changes at 1 Hz (every second), you must take two images per second.

  18. Aliasing • Mismapping of high frequencies (above the Nyquist limit) to lower frequencies • Results from insufficient sampling • Potential problem for designs with long TRs and fast stimulus changes

  19. Frequency Analyses t < -1.96 t < +1.96 McCarthy et al., 1996

  20. Phase Analyses • Design • Left/right alternating flashes • 6.4s for each • Task frequency: • 1 / 12.8 = 0.078 McCarthy et al., 1996

  21. Why do we want to measure differences in timing within a brain region? • Determine relative ordering of activity • Make inferences about connectivity • Anatomical • Functional • Relate activity timing to other measures • Stimulus presentation • Reaction time • Relative amplitude

  22. Timing Differences across Regions Presented left hemifield before right hemifield (0-1000ms delays) fMRI vs RT (LH) Plot of LH signal as function of RH signal fMRI vs. Stimulus Menon et al., 1998

  23. Activation maps Relative onset time differences Menon et al., 1998

  24. V1 FFG Huettel et al., 2001

  25. Secondary Visual Cortex (FFG) Primary Visual Cortex (V1) Subject 1 5.5s 4.0s Subject 2 Huettel et al., 2001

  26. Linearity of the Hemodynamic Response

  27. Linear Systems • Scaling • The ratio of inputs determines the ratio of outputs • Example: if Input1 is twice as large as Input2, Output1 will be twice as large as Output2 • Superposition • The response to a sum of inputs is equivalent to the sum of the response to individual inputs • Example: Output1+2+3 = Output1+Output2+Output3

  28. Possible Sources of Nonlinearity • Stimulus time course  neural activity • Activity not uniform across stimulus (for any stimulus) • Neural activity  Vascular changes • Different activity durations may lead to different blood flow or oxygen extraction • Minimum bolus size? • Minimum activity necessary to trigger? • Vascular changes  BOLD measurement • Saturation of BOLD response necessitates nonlinearity • Vascular measures combining to generate BOLD have different time courses From Buxton, 2001

  29. Effects of Stimulus Duration • Short stimulus durations evoke BOLD responses • Amplitude of BOLD response often depends on duration • Stimuli < 100ms evoke measurable BOLD responses • Form of response changes with duration • Latency to peak increases with increasing duration • Onset of rise does not change with duration • Rate of rise increases with duration • Key issue: deconfounding duration of stimulus with duration of neuronal activity

  30. Boynton et al., 1996 Linear model for HDR Varied contrast of checkerboard bars as well as their interval (B) and duration (C).

  31. Boynton, et al, 1996

  32. Boynton, et al, 1996

  33. Differences in Nonlinearity across Brain Regions Birn, et al, 2001

  34. SMA vs. M1 Birn, et al, 2001

  35. Caveat: Stimulus Duration ≠ Neuronal Activity Duration

  36. fMRI Hemodynamic Response 1500ms 500ms 100ms Calcarine Sulci Fusiform Gyri

  37. * Calcarine 1500ms 500ms 100ms Fusiform

  38. Refractory Periods • Definition: a change in the responsiveness to an event based upon the presence or absence of a similar preceding event • Neuronal refractory period • Vascular refractory period

  39. Dale & Buckner, 1997 • Responses to consecutive presentations of a stimulus add in a “roughly linear” fashion • Subtle departures from linearity are evident

  40. Intra-Pair Interval (IPI) Inter-Trial Interval (16-20 seconds) 6 sec IPI 4 sec IPI 2 sec IPI 1 sec IPI Single-Stimulus 500 ms duration Huettel & McCarthy, 2000

  41. Methods and Analysis • 16 male subjects (mean age: 27y) • GE 1.5T scanner • CAMRD • Gradient-echo EPI • TR : 1 sec • TE : 50 msec • Resolution: 3.125 * 3.125 * 7 mm • Analysis • Voxel-based analyses • Waveforms derived from active voxels within anatomical ROI Huettel & McCarthy, 2000

  42. Hemodynamic Responses to Closely Spaced Stimuli Huettel & McCarthy, 2000

  43. Refractory Effects in the fMRI Hemodynamic Response Signal Change over Baseline(%) Time since onset of second stimulus (sec) Huettel & McCarthy, 2000

  44. Refractory Effects across Visual Regions HDRs to 1st and 2nd stimuli in a pair (calcarine cortex) Relative amplitude of 2nd stimulus in pair across regions

  45. Intra-Pair Interval (IPI) Inter-Trial Interval (16-20 seconds) 6 sec IPI 1 sec IPI Single-Stimulus

  46. Single 05 10 15 20 25 30 35 40 45 50 55 60 6s IPI 1s IPI Signal Change over baseline (%) Time since stimulus onset (sec) Figure 2 Mean HDRs L R

  47. Refractory Effect Summary • Duration • HDR evoked by a long-duration stimulus is less than predicted by convolution of short-duration stimuli • Present for durations < ~6s • Interstimulus interval • HDR evoked by a stimulus is reduced by a preceding similar stimulus • Present for intervals < ~6s • Differences across brain regions • Some regions show considerable departures from linearity • May result from differences in processing • Source of non-linearity not well understood • Neuronal effects comprise at least part of the overall effect • Vascular differences may also contribute

  48. Using refractory effects to study cognition: fMRI Adaptation Studies

  49. Neuronal Adaptation Grill-Spector & Malach, 2001 Several neuronal populations vs. homogeneous population Adaptation If neurons are insensitive to the feature being varied, then their activity will adapt. Viewpoint Sensitive Viewpoint Invariant

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