Near-infrared neuroimaging with NinPy

Frontiers in Neuroinformatics

Volumn 3, Issue MAY, 2009, Pages

  Strangman, Gary E ^a,b   Zhang, Quan ^a,b   Zeffiro, Thomas ^b  

^a HARVARD MEDICAL SCHOOL   (United States)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

Author keywords

Brain imaging; Diffuse optical tomography; Near infrared spectroscopy; NIRS; Python

Indexed keywords

EID: 80455139075     PISSN: 16625196     EISSN: None     Source Type: Journal    
DOI: 10.3389/neuro.11.012.2009     Document Type: Article

References (52)

1. Arridge, S. R. (1999). Optical tomography in medical imaging. Inverse Probl. 15, R41-R93.
2. Berkes, P., Wilbert, N., and Zito, T. (2008). Modular toolkit for data processing (version 2.3). Available at: http://mdptoolkit.sourceforge.net (Retrieved September 2, 2008).
3. Boas, D. A. (2004). Photon migration imaging toolbox. Available at: http://www.nmr.mgh.harvard.edu/PMI/resources/tmcimg/index.htm (Retrieved August 25, 2008).
4. Boas, D. A. (2008). Monte Carlo photon transport. Available at: http://www.nmr.mgh.harvard.edu/PMI/resources/tmcimg/index.htm (Retrieved August 25, 2008).
5. Choi, J., Wolf, M., Toronov, V., Wolf, U., Polzonetti, C., Hueber, D., Safonova, L. P., Gupta, R., Michalos, A., Mantulin, W., and Gratton, E. (2004). Noninvasive determination of the optical properties of adult brain: near-infrared spectroscopy approach. J. Biomed. Opt. 9, 221-229.
6. Cox, R. W., Ashburner, J., Breman, H., Fissell, K., Haselgrove, C., Holmes, C. J., Lancaster, J. L., Rex, D. E., Smith, S. M., Woodward, J. B., and Strother, S. C. (2004). A (sort of) new image data format standard: NIfTI-1. 10th Annual Meeting of the Organization for Human Brain Mapping, Budapest, Hungary.
7. Dale, A. M. (1999). Optimal experimental design for event-related fMRI. Hum. Brain Mapp. 8, 109-114.
8. Delpy, D. T., Cope, M., van der Zee, P., Arridge, S., Wray, S., and Wyatt, J. (1988). Estimation of optical pathlength through tissue from direct time of flight measurement. Phys. Med. Biol. 33, 1433-1442.
9. Enthought (2007). Chaco. Available at: http://code.enthought.com/chaco/ (Retrieved August 25, 2008).
10. Enthought (2008). Traits. Available at: http://code.enthought.com/projects/traits/ (Retrieved August 25, 2008).
11. Farrell, T. J., Patterson, M. S., and Wilson, B. (1992). A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo. Med. Phys. 19, 879-888.
12. Franceschini, M. A., and Boas, D. A. (2004). Noninvasive measurement of neuronal activity with near- infrared optical imaging. Neuroimage 21, 372-386.
13. Franceschini, M. A., Joseph, D. K., Huppert, T. J., Diamond, S. G., and Boas, D. A. (2006). Diffuse optical imaging of the whole head. J. Biomed. Opt. 11, 054007.
14. Gratton, G., Fabiani, M., Corballis, P. M., Hood, D. C., Goodman-Wood, M. R., Hirsch, J., Kim, K., Friedman, D., and Gratton, E. (1997). Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI. Neuroimage 6, 168-180.
15. Hanke, M. (2008). PyNifti - Python-style access to NIfTI and ANALYZE files. Available at: http://niftilib.sourceforge.net/pynifti/ (Retrieved August 25, 2008).
16. Hunter, J. D. (2007). Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90-95.
17. Huppert, T. J. (2006). HomER. Available at: http://www.nmr.mgh.harvard.edu/DOT/resources/homer/home.htm (Retrieved September 2, 2008).
18. Huppert, T. J., Hoge, R. D., Diamond, S. G., Franceschini, M. A., and Boas, D. A. (2006). A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans. Neuroimage 29, 368-382.
19. Jacques, S. L., and Wang, L. (1995). Monte Carlo modeling of light transport in tissues. In Optical-Response of Laser- Irradiated Tissue, A. J. Welch and J. C. van Gemert, eds (New York, NY, Plenum), pp. 73-100.
20. Jasdzewski, G., Strangman, G., Wagner, J., Kwong, K. K., Poldrack, R. A., and Boas, D. A. (2003). Differences in the hemodynamic response to eventrelated motor and visual paradigms as measured by near-infrared spectroscopy. Neuroimage 20, 479-488.
21. Jobsis, F. F. (1977). Non-invasive, infra-red monitoring of cerebral O2 sufficiency, blood volume, HbO2-Hb shifts and blood flow. Acta Neurol. Scand. Suppl. 64, 452-453.
22. Jones, E., Oliphant, T., Peterson, P., et al. (2001). SciPy: open source scientific tools for python. Available at: http://www.scipy.org (Retrieved August 25, 2008).
23. Kohri, S., Hoshi, Y., Tamura, M., Kato, C., Kuge, Y., and Tamaki, N. (2002). Quantitative evaluation of the relative contribution ratio of cerebral tissue to near-infrared signals in the adult human head: a preliminary study. Physiol. Meas. 23, 301-312.
24. Leung, T. S., Elwell, C. E., and Delpy, D. T. (2005). Estimation of cerebral oxy- and deoxy-haemoglobin concentration changes in a layered adult head model using near-infrared spectroscopy and multivariate statistical analysis. Phys. Med. Biol. 50, 5783-5798.
25. Liechti, C. (2008). pySerial/ pyParallel. Available at: http://pyserial.wiki.sourceforge.net/pySerial (Retrieved August 25, 2008).
26. Lin, F., Witzel, T., Mandeville, J., Polimeni, J., Zeffiro, T., Greve, D., Wiggins, G., Wald, L., and Belliveau, J. (2008a). Event-related single-shot volumetric functional magnetic resonance inverse imaging of visual processing. Neuroimage 42, 230-247.
27. Lin, F. H., Witzel, T., Zeffiro, T. A., and Belliveau, J. W. (2008b). Linear constraint minimum variance beamformer functional magnetic resonance inverse imaging. Neuroimage 43, 297-311.
28. Logothetis, N. K. (2008). What we can do and what we cannot do with fMRI. Nature 453, 869-878.
29. Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., and Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature 412, 150-157.
30. Logothetis, N. K., and Wandell, B. A. (2004). Interpreting the BOLD signal. Annu. Rev. Physiol. 66, 735-769.
31. Moriera, W., and Warnes, G. R. (2004). Rpy, a robust Python interface to the R Programming Language. Available at: http://rpy.sourceforge.net/ (Retrieved September 2, 2008).
32. Morren, G., Wolf, U., Lemmerling, P., Wolf, M., Choi, J. H., Gratton, E., De Lathauwer, L., and Van Huffel, S. (2004). Detection of fast neuronal signals in the motor cortex from functional near infrared spectroscopy measurements using independent component analysis. Med. Biol. Eng. Comput. 42, 92-99.
33. NiPy Development Team (2006). NiPy: neuroimaging tools for python. Available at: http://neuroimaging.scipy.org (Retrieved September 2, 2008).
34. Okada, E., and Delpy, D. T. (2003). Nearinfrared light propagation in an adult head model. I. Modeling of low-level scattering in the cerebrospinal fluid layer. Appl. Opt. 42, 2906-2914.
35. Oliphant, T. E. (2006). Guide to NumPy. Spanish Fork, UT, Trelgol Publishing.
36. Peirce, J. W. (2008). Generating stimuli for neuroscience using PsychoPy. Front. Neuroinformatics 2, 10.
37. Pinheiro, J. C., and Bates, D. M. (2000). Mixed-effects models in S and S-Plus. New York, NY, Springer.
38. Pogue, B. W., McBride, T. O., Osterberg, U. L., and Paulsen, K. D. (1999a). Comparison of imaging geometries for diffuse optical tomography of tissue. Opt. Express 4, 270-286.
39. Pogue, B. W., McBride, T. O., Prewitt, J., Osterberg, U. L., and Paulsen, K. D. (1999b). Spatially variant regularization improves diffuse optical tomography. App. Opt. 38, 2950-2961.
40. R Development Core Team (2005). R: a language and environment for statistical computing. Available at: http://www.R-project.org (Retrieved August 25, 2008).
41. Schmolck, A. (2007). Mlabwrap v1.0. Available at: http://mlabwrap.sourceforge.net/ (Retrieved August 25, 2008).
42. Strangman, G., Boas, D. A., and Sutton, J. P. (2002a). Noninvasive brain imaging using near infrared light. Biol. Psychiatry 52, 679-693.
43. Strangman, G., Culver, J. P., Thompson, J. H., and Boas, D. A. (2002b). A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation. Neuroimage 17, 719-731.
44. Strangman, G., Franceschini, M. A., and Boas, D. A. (2003). Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters. Neuroimage 18, 865-879.
45. Strangman, G., Goldstein, R., Rauch, S. L., and Stein, J. (2006). Near-infrared spectroscopy and imaging for investigating stroke rehabilitation: test-retest reliability and review of the literature. Arch. Phys. Med. Rehabil. 87, 12-19.
46. Strangman, G. E., O'Neil-Pirozzi, T. M., Goldstein, R., Kelkar, K., Katz, D. I., Burke, D., Rauch, S. L., Savage, C. R., and Glenn, M. B. (2008). Prediction of memory rehabilitation outcomes in traumatic brain injury by using functional magnetic resonance imaging. Arch. Phys. Med. Rehabil. 89, 974-981.
47. Straw, A. D. (2008). Vision egg: an open-source library for realtime visual stimulus generation. Front. Neuroinformatics 2, 4.
48. Villringer, A., and Chance, B. (1997). Non-invasive optical spectroscopy and imaging of human brain function. Trends Neurosci. 20, 435-442.
49. Ye, J. C., Tak, S., Jang, K. E., Jung, J., and Jang, J. (2009). NIRS-SPM: statistical parametric mapping for nearinfrared spectroscopy. Neuroimage 44, 428-447.
50. Zhang, Q., Brown, E. N., and Strangman, G. E. (2007a). Adaptive filtering for global interference cancellation and real-time recovery of evoked brain activity: a Monte Carlo simulation study. J. Biomed. Opt. 12, 044014.
51. Zhang, Q., Brown, E. N., and Strangman, G. E. (2007b). Adaptive filtering to reduce global interference in evoked brain activity detection: a human subject case study. J. Biomed. Opt. 12, 064009.
52. Zhang, Y., Brooks, D. H., Franceschini, M. A., and Boas, D. A. (2005). Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging. J. Biomed. Opt. 10, 11014.