High-resolution fMRI: Overcoming the signal-to-noise problem

Journal of Neuroscience Methods

Volumn 178, Issue 2, 2009, Pages 357-365

  Tabelow, Karsten ^a   Piëch, Valentin ^b   Polzehl, Jörg ^a   Voss, Henning U ^c  

^a WEIERSTRASS INSTITUTE FOR APPLIED ANALYSIS AND STOCHASTICS   (Germany)

^b ROCKEFELLER UNIVERSITY   (United States)

^c WEILL CORNELL MEDICAL COLLEGE   (United States)

Author keywords

Functional MRI; High resolution fMRI; Structure adaptive smoothing

Indexed keywords

ALGORITHM; ARTICLE; CONTROLLED STUDY; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; MALE; OPTICAL RESOLUTION; PRIORITY JOURNAL; SIGNAL DETECTION; SIGNAL NOISE RATIO; SIMULATION;

ALGORITHMS; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; FEMALE; HUMANS; IMAGE ENHANCEMENT; MAGNETIC RESONANCE IMAGING; MALE; PHANTOMS, IMAGING; PROBABILITY; PSYCHOMOTOR PERFORMANCE; SIGNAL PROCESSING, COMPUTER-ASSISTED; VISUAL PERCEPTION;

EID: 60749131026     PISSN: 01650270     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2008.12.011     Document Type: Article

References (36)

1. Andrade A., Kherif F., Mangin J.F., Worsley K.J., Paradis A.L., Simon O., Dehaene S., Le Bihan D., and Poline J.B. Detection of fMRI activation using Cortical Surface Mapping. Hum Brain Mapp 12 (2001) 79-93
2. Cox R. Software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 29 (1996) 162-173
3. Edelstein W., Glover G., Hardy C., and Redington R. The intrinsic signal-to-noise ratio in NMR imaging. Magn Reson Med 3 4 (1986) 604-618
4. Flandin G., Kherif F., Pennec X., Malandain G., Ayache N., and Poline J.B. Improved detection sensitivity in functional {MRI} data using a brain parcelling technique. In: Dohi T., and Kikinis R. (Eds). Medical Image Computing and Computer-Assisted Intervention (MICCAI'02) vol. 2488 (2002), Springer, Tokyo 467-474
5. Forman S., Cohen J., Fitzgerald M., Eddy W., Mintun M., and Noll D. Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. Magn Reson Med 33 (1995) 636-647
6. Friston K., Holmes A., Worsley K., Poline J.B., Frith C., and Frackowiak R. Statistical parametric maps in functional imaging: a general linear approach. Hum Brain Mapp 2 (1995) 189-210
7. Grova C., Makni S., Flandin G., Ciuciu P., Gotman J., and Poline J.B. Anatomically informed interpolation of fMRI data on the cortical surface. NeuroImage 31 (2006) 1475-1486
8. Harel N., Ugurbil K., Uludag K., and Yacoub E. Frontiers of brain mapping using MRI. J Magn Res Imaging 23 (2006) 945-957
9. Harrison L., Penny W., Ashburner J., Trujillo-Barreto N., and Friston K. Diffusion-based spatial priors for imaging. NeuroImage 38 (2007) 677-695
10. Harrison L., Penny W., Daunizeau J., and Friston K. Diffusion-based spatial priors for functional magnetic resonance images. NeuroImage 41 (2008) 408-423
11. Hyde J.S., Biswal B.B., and Jesmanowicz A. High-resolution fMRI using multislice partial k-space GR-EPI with cubic voxels. Magn Reson Med 46 (2001) 114-125
12. Jenkinson M. Improved unwarping of EPI images using regularised B0 maps. NeuroImage 13 6 (2001) 165
13. 0 field variations. Magn Res Med 34 (1995) 65-73
14. Kiebel S.J., Goebel R., and Friston K.J. Anatomically informed basis functions. NeuroImage 11 (2000) 656-667
15. Kleinschmidt A. Different analysis solutions for different spatial resolutions? Moving towards a mesoscopic mapping of functional architecture in the human brain. NeuroImage 38 4 (2007) 663-665
16. Kriegeskorte N., and Bandettini P. Analyzing for information, not activation, to exploit high-resolutiuon fMRI. NeuroImage 38 4 (2007) 649-662
17. Kriegeskorte N., and Bandettini P. Combining tools: activation- and information-based fMRI analysis. NeuroImage 38 4 (2007) 666-668
18. Krüger G., and Glover G. Physiological noise in oxygenation-sensitive magnetic resonance imaging. Magn Reson Med 46 (2001) 631-637
19. Lowe M., and Sorenson J. Spatially filtering functional magnetic resonance imaging data. Magn Reson Med 37 (1997) 723-729
20. Lu Y., Jiang T., and Zang Y. Region growing method for the analysis of functional MRI data. NeuroImage 20 (2003) 455-465
21. Lu Y., Jiang T., and Zang Y. Split-merge based region growing method for fMRI activation detection. Hum Brain Mapp 22 (2004) 271-279
22. Parker D., and Gullberg G. Signal-to-noise efficiency in magnetic resonance imaging. Med Phys 17 2 (1990) 250-257
23. Poline J.B., and Mazoyer B.M. Enhanced detection in brain activation maps using a multifiltering approach. J Cereb Blood Flow Metab 14 (1994) 639-642
24. Polzehl J., and Spokoiny V. Propagation-separation approach for local likelihood estimation. Probab Theory Relat Fields 135 (2006) 335-362
25. Polzehl J., and Tabelow K. fmri: a package for analyzing fmri data. RNews 7 2 (2007) 13-17
26. R Development Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2006. ISBN 3-900051-07-0.
27. Scouten A., Papademetris X., and Constable R. Spatial resolution, signal-to-noise ratio, and smoothing in multi-subject functional MRI studies. NeuroImage 30 3 (2006) 787-793
28. Siegmund D.O., and Worsley K.J. Testing for a signal with unknown location and scale in a stationary Gaussian random field. Ann Stat 23 (1995) 608-639
29. Sijbers J. Signal and noise estimation from magnetic resonance images. Ph.D. thesis, Universiteit Antwerpen; 1998.
30. Smith S.M., Jenkinson M., Woolrich M.W., Beckmann C.F., Behrens T.E., Johansen-Berg H., Bannister P.R., De Luca M., Drobnjak I., Flitney D.E., Niazy R.K., Saunders J., Vickers J., Zhang Y., De Stefano N., Brady J.M., and Matthews P.M. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 23 S1 (2004) 208-219
31. Tabelow K., Polzehl J., Ulug A.M., Dyke J.P., Heier L.A., and Voss H.U. Accurate localization of functional brain activity using structure adaptive smoothing. IEEE Trans Med Imaging 27 4 (2008) 531-537
32. Tabelow K., Polzehl J., Voss H.U., and Spokoiny V. Analyzing fMRI experiments with structural adaptive smoothing procedures. NeuroImage 33 1 (2006) 55-62
33. Triantafyllou C., Hoge R., Krüger G., Wiggins C., Potthast A., Wiggins G., and Wald L. Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. NeuroImage 26 1 (2005) 243-250
34. Triantafyllou C., Hoge R., and Wald L. Effect of spatial smoothing on physiological noise in high-resolution Fmri. NeuroImage 32 2 (2006) 551-557
35. Worsley K., and Friston K. Analysis of fMRI time series revisited-again. NeuroImage 2 (1995) 173-181
36. Worsley K., Liao C., Aston JAD, Petre V., Duncan G., Morales F., et al. A general statistical analysis for fMRI data. NeuroImage 15 (2002) 1-15