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Resting state fMRI (RS-fMRI; fcMRI) Physiological underpinnings Methodology

Resting state fMRI (RS-fMRI; fcMRI) Physiological underpinnings Methodology Areas of investigation, some results Unresolved questions Z. Snyder July 20, 2010. Why study the resting state?

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Resting state fMRI (RS-fMRI; fcMRI) Physiological underpinnings Methodology

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  1. Resting state fMRI (RS-fMRI; fcMRI) • Physiological underpinnings • Methodology • Areas of investigation, some results • Unresolved questions • Z. Snyder • July 20, 2010

  2. Why study the resting state? Conventional task-related fMRI images the representation of cognitive processes (e.g., “attention”, “control”, “perception”) the identity of which is presumed to be known. Resting state studies target intrinsic activity, i.e., internal communication within the brain without a priori assignment of psychological labels.

  3. PUBLICATIONS/YEAR | | |

  4. fcMRI: imaging the spatial structure of spontaneous (intrinsic) BOLD fluctuations. • Two principal techniques: • Seed-ROI-based correlation mapping • Spatial ICA

  5. sICA vs. seed-based mapping TECHINICAL COMPARISON

  6. Algebraic formulae for fcMRI maps regression image: I(x)f(x)=f(t)I(x,t)/2f correlation image: rI(x)f(x)=f(t)I(x,t)/[fI(x)] Fisher z-transform: zI(x)f(x) =0.5ln[(1+ rf(x))/(1- rf(x))] = tanh-1(rI(x)f(x))

  7. Biswal et al., Magn. Reson. Med. 1995

  8. Spontaneous Fluctuations in the BOLD Signal

  9. Spontaneous Fluctuations are Specifically Correlated

  10. Generation of Resting State Correlation Maps Z score, fixed effects, N = 10

  11. Physiological underpinnings

  12. Shmuel & Leopold, HBM 2008;29:751-61

  13. Ray Cooper, H. J. Crow, W. Grey Walter, A. L. Winter Brain Res. 1966:3:174-92

  14. Ray Cooper, H. J. Crow, W. Grey Walter, A. L. Winter Brain Res. 1966:3:174-92 Fig. 8

  15. E. V. Golanov, Y. Yamamoto, D. J. Reis Am. J. Phsyiol. 1994:266:204-14

  16. He et al., PNAS 2008;105;16039-44

  17. He et al., Neuron 2010; 66:353-69

  18. rCBF and the BOLD signal unequivocally reflect neuronal acitvity, specifically [gamma-band] LFPs and slow cortical potentials (SCPs). That said, fMRI signals are contaminated by physiological artifacts, i.e., spurious (non-neuronal) sources of variance: pCO2 fluctuations cardiac and respiratory pulsations eye movements head motion Critical point: This spurious variance cannot be reduced simply by averaging, as in conventional fMRI.

  19. A B

  20. Examples of “good” ICs

  21. Examples of “bad” ICs

  22. TC30273 fcMRI timeseries sd1 (excluding selected frames) Z = +12 scale max = 2% before fcMRI preprocessing after fcMRI preprocessing

  23. Vincent et al., J. Neurophysiol. 2006; 96:3517-31

  24. Some results

  25. Uses of fcMRI • investigate normal physiology - intrinsic (not task-evoked) neural activity at the systems level • topographic of organization (RSNs) • relation to conventional fMRI • relation to WM tracts • development, aging • arousal state, anesthesia, cognitive state • pathophysiology of disease • effects of experience and training

  26. Damoiseaux et al., PNAS 2006;103:13848-53

  27. Shehzad et al., CerCor 2009:19:2209-29

  28. Smith, Fox, et al., PNAS 2009;106;13040-5

  29. Uses of fcMRI • investigate normal physiology - intrinsic (not task-evoked) neural activity at the systems level • topographic of organization (RSNs) • relation to conventional fMRI • relation to WM tracts • development, aging • arousal state, anesthesia, cognitive state • pathophysiology of disease • effects of experience and training

  30. Fox et al., PNAS 2005;102:9673-8

  31. Fox et al., J. Neurophysiol. 2009;101:3270-83

  32. Fox et al., J. Neurophysiol. 2009;101:3270-83

  33. Fox et al., J. Neurophysiol. 2009;101:3270-83

  34. Courtesy of Don Zhang

  35. Vincent et al., J Neurophysiol 2008;100:3328-42

  36. Vincent et al., J Neurophysiol 2008;100:3328-42

  37. Di Martino et al., CerCor 2008;18:2735-47

  38. Di Martino et al., CerCor 2008;18:2735-47

  39. Krienen & Buckner, Cerebral Cortex 2009;19:2485-97

  40. Zhang et al., J. Neurophysiol. 2008;100:1740-8

  41. Uses of fcMRI • investigate normal physiology - intrinsic (not task-evoked) neural activity at the systems level • topographic of organization (RSNs) • relation to conventional fMRI • relation to WM tracts • development, aging • arousal state, anesthesia, cognitive state • pathophysiology of disease • effects of experience and training

  42. Zhang et al., Cerebral Cortex 2010;20:1187-94

  43. Johnston et al., J. Neurosci. 2008;28:6453-58

  44. Uses of fcMRI • investigate normal physiology - intrinsic (not task-evoked) neural activity at the systems level • topographic of organization (RSNs) • relation to conventional fMRI • relation to WM tracts • development, aging • arousal state, anesthesia, cognitive state • pathophysiology of disease • effects of experience and training

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