Multilevel statistical inference from functional near-infrared spectroscopy data during stroop interference

IEEE Transactions on Biomedical Engineering

Volumn 55, Issue 9, 2008, Pages 2212-2220

  Çiftçi, Koray ^a   Sankur, Bülent ^a   Kahya, Yasemin P ^a   Akin, Ata ^a  

^a BOGAZICI UNIVERSITY   (Turkey)

Author keywords

General linear model (GLM); Near infrared spectroscopy; Statistical inference; Stroop task

Indexed keywords

BAYESIAN NETWORKS; CHEMICAL ACTIVATION; CONCENTRATION (PROCESS); INDEXING (OF INFORMATION); INFERENCE ENGINES; INFRARED DEVICES; INFRARED SPECTROSCOPY; MATHEMATICAL MODELS; SPECTROSCOPIC ANALYSIS; SPECTRUM ANALYSIS; STATISTICAL METHODS; TEXTILES;

ACTIVATION PATTERNS; BAYESIAN INFERENCES; BAYESIAN MODELLING; CASE STUDIES; CONCENTRATION CHANGES; FUNCTIONAL NEAR-INFRARED SPECTROSCOPY; GENERAL LINEAR MODEL; GENERAL LINEAR MODEL (GLM); GROUP LEVEL; INTERFERENCE CONDITIONS; MIXED EFFECTS; MULTI-LEVEL ANALYSIS; NEAR-INFRARED SPECTROSCOPY; NEURO-IMAGING; OXY-AND DEOXY-HEMOGLOBIN; PRE-FRONTAL CORTEX; STATISTICAL INFERENCE; STATISTICAL INFERENCES; STROOP TASK; TIME-SERIES;

TIME SERIES ANALYSIS;

DEOXYHEMOGLOBIN; OXYHEMOGLOBIN;

ADULT; ANALYTIC METHOD; ARTICLE; BAYES THEOREM; COGNITION; FEASIBILITY STUDY; FEMALE; FUNCTIONAL NEAR INFRARED SPECTROSCOPY; HEMODYNAMICS; HUMAN; HUMAN EXPERIMENT; MALE; METHODOLOGY; MULTILEVEL STATISTICAL INFERENCE; NEUROIMAGING; NORMAL HUMAN; PREFRONTAL CORTEX; STROOP INTERFERENCE; TASK PERFORMANCE;

ADULT; ALGORITHMS; BRAIN MAPPING; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; EVOKED POTENTIALS, VISUAL; FEMALE; HUMANS; MALE; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PREFRONTAL CORTEX; SPECTROPHOTOMETRY, INFRARED;

EID: 50049108492     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2008.923918     Document Type: Article

References (43)

1. A. Villringer and B. Chance, "Noninvasive optical spectroscopy and imaging of human brain function," Trends Neurosci., vol. 20, pp. 4435-442, 1997.
2. M. Cope and D. T. Delpy, "A system for the long-term measurement of cerebral blood and tissue oxygenation in newborn infants by near infra-red transillumination," Med. Biol. Eng. Comput., vol. 26, pp. 289-294, 1988.
3. I. Palada, A. Obad, D. Bakovic, Z. Valic, V. Ivancev, and Z. Dujic, "Cerebral and peripheral hemodynamics and oxygenation during maximal dry breath-holds," Respir. Physiol. Neurobiol., vol. 157, no. 2/3, pp. 374-381, Aug. 2007 (doi: 10.1016/j.resp.2007.02.002).
4. D. T. Ubbink and B. Koopman, "Near-infrared spectroscopy in the routine diagnostic workup of patients with leg ischaemia," Eur. J. Vasc. Endovasc. Surg., vol. 31, pp. 394-400, 2006.
5. K. Friston, A. Holmes, J. B. Poline, C. Frith, and R. Frackowiak, "Statistical parametric maps in functional imaging: A general linear approach," Human Brain Mapp., vol. 2, pp. 189-210, 1995.
6. K. J. Friston, W. Penny, C. Phillips, S. Kiebel, G. Hinton, and J. Ashburner, "Classical and Bayesian inference in neuroimaging: Theory," Neuroimage, vol. 16, pp. 465-483, 2002.
7. M. L. Schroeter, M. M. Bücheler, K. Miller, K. Uludag, H. Obrig, G. Lohmann, M. Tittgemeyer, A. Villringer, and D. Y. von Cramon, "Toward a standard analysis for functional near-infrared imaging," Neuroimage, vol. 21, pp. 283-290, 2004.
8. M. M. Plichta, S. Heinzel, A.-C. Ehlis, P. Pauli, and A. J. Fallgatter, "Model-based analysis of rapid event-related functional near-infrared spectroscopy: A parametric validation study," Neuroimage, vol. 35, no. 2, pp. 625-634, Apr. 2007 (doi: 10.10.16/j.neuroimage.2006.11.028).
9. J. Cohen-Adad, S. Chapuisat, J. Doyon, S. Rossignol, J.-M. Lina, H. Benali, and F. Lesage, "Activation detection in diffuse optical imaging by means of the general linear model," Med. Image Anal., vol. 11, no. 6, pp. 616-629, Jun. 2007 (doi: 10.1016/j.media.2007.06.002).
10. B. Thirion, P. Pinel, S. Meriaux, A. Roche, S. Dehaene, and J. B. Poline, "Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses," Neuroimage, vol. 35, pp. 105-120, 2007.
11. G. K. Büyükaksoy, N. S. Şengör, H. Gürvit, and C. Güzeliş, "Modelling the stroop effect: A connectionist approach," Neurocomputing, vol. 70, no. 7/9, pp. 1414-1423, Mar. 2007 (doi: 10.1016/j.neucom.2006.05.009).
12. C. MacLeod, "Half a century of research on the Stroop effect: An integrative review," Psychol. Bull., vol. 109, pp. 163-203, 1991.
13. S. Zysset, K. Muller, G. Lohmann, and D. Y. von Cramon, "Color-word matching Stroop task: Separating interference and response conflict," Neuroimage, vol. 13, pp. 29-36, 2001.
14. M. L. Schroeter, S. Zysset, T. Kupka, F. Kruggel, and D. Y. von Cramon, "Near-infrared spectroscopy can detect brain activation during a color-word matching Stroop task in an event-related design," Human Brain Mapp., vol. 17, pp. 61-71, 2002.
15. A.-C. Ehlis, M. J. Herrmann, A. Wagener, and A. J. Fallgatter, "Multichannel near-infrared spectroscopy detects specific inferior-frontal activation during incongruent Stroop trials," Biol. Psychol., vol. 69, pp. 315-332, 2005.
16. C. F. Beckmann, M. Jenkinson, and S. M. Smith, "General multilevel linear modeling for group analysis in FMRI," Neuroimage, vol. 20, pp. 1052-1063, 2003.
17. M. W. Woolrich, T. E. J. Behrens, C. F. Beckmann, M. Jenkinson, and S. B. Smith, "Multilevel linear modeling for fMRI group analysis using Bayesian inference," Neuroimage, vol. 21, pp. 1732-1747, 2004.
18. J. Neumann and G. Lohmann, "Bayesian second-level analysis of functional magnetic resonance images," Neuroimage, vol. 20, pp. 1346-1355, 2003.
19. D. B. Rowe, Multivariate Bayesian Statistics: Models for Source Separation and Signal Unmixing. Boca Raton, FL: Chapman & Hall/CRC, 2003.
20. A. B. Gelman, J. S. Carlin, H. S. Stern, and D. B. Rubin, Bayesian Data Analysis. Boca Raton, FL: Chapman & Hall/CRC, 1995.
21. A. Akin, D. Bilensoy, U. E. Emir, M. Gülsoy, S. Candansayar, and H. Bolay, "Cerebrovascular dynamics in patients with migraine: Near-infrared spectroscopy study," Neurosci. Lett., vol. 400, pp. 86-91, 2006.
22. C. B. Akgül, A. Akin, and B. Sankur, "Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals," Med. Biol. Eng. Comput., vol. 44, pp. 945-958, 2006.
23. C. B. Akgül, B. Sankur, and A. Akin, "Spectral analysis of event-related hemodynamic responses in functional near infrared spectroscopy," J. Comput. Neurosci., vol. 18, pp. 67-83, 2005.
24. D. A. Boas, K. Chen, D. Grebert, and M. A. Franceschini, "Improving the diffuse optical imaging spatial resolution of the cerebral hemodynamic response to brain activation in humans," Opt. Lett., vol. 29, no. 1, pp. 1506-1508, Jan./Feb. 2004.
25. F. Fabbri, A. Sassaroli, M. E. Henry, and S. Fantini, "Optical measurements of absorption changes in two-layered diffusive media," Phys. Med. Biol., vol. 49, pp. 1183-1201, 2004.
26. M. Firbank, E. Okada, and D. T. Delpy, "A theoretical study of the signal contribution of regions of the adult head to near-infrared spectroscopy studies of visual evoked responses," Neuroimage, vol. 8, pp. 69-78, 1988.
27. K. J. Friston, P. Fletcher, O. Josephs, A. Holmes, M. D. Rugg, and R. Turner, "Event-related fMRI: Characterizing differential responses," Neuroimage, vol. 7, pp. 30-40, 1998.
28. K. J. Friston, O. Josephs, E. Zarahn, A. P. Holmes, S. Rouquette, and J.-B. Poline, "To smooth or not to smooth? Bias and efficiency in fMRI time-series analysis," Neuroimage, vol. 12, pp. 196-208, 2000.
29. R. L. C. Mitchell, "BOLD response during Stroop task-like inhibition tasks: Effects of task difficulty and task-relevant modality," Brain Cogn., vol. 59, pp. 23-37, 2005.
30. C. Bench, C. Frith, P. Grasby, K. Friston, E. Paulesu, R. Frackowiak, and R. Dolan, "Investigations of the functional anatomy of attention using the Stroop test," Neuropsychologia, vol. 31, pp. 907-922, 1993.
31. M. L. Schroeter, S. Cutini, M. M. Wahl, R. Scheid, and D. Y. von Cramon, "Neurovascular coupling is impaired in cerebral microangiopathy - An event related Stroop study," Neuroimage, vol. 34, pp. 26-34, 2007.
32. R. Heller, Y. Golland, R. Malach, and Y. Benjamini, "Conjunction group analysis: An alternative to mixed/random effect analysis," Neuroimage, vol. 37, pp. 1178-1185, 2007.
33. S. L. Chow, Statistical Significance: Rationale, Validity and Utility. London, U.K.: Sage, 1996.
34. M. W. Woolrich, T. E. J. Behrens, and S. M. Smith, "Constrained linear basis sets for HRF modeling using variational Bayes," Neuroimage, vol. 21, pp. 1748-1761, 2004.
35. B. R. Logan and D. B. Rowe, "An evaluation of thresholding techniques in fMRI analysis," Neuroimage, vol. 22, pp. 95-108, 2004.
36. A. K. Singh and I. Dan, "Exploring the false discovery rate in multichannel NIRS," Neuroimage, vol. 33, pp. 542-549, 2004.
37. Y. Hoshi, N. Kobayashi, and M. Tamura, "Interpretation of near-infrared spectroscopy signals: A study with a newly developed perfused rat brain model," J. Appl. Physiol., vol. 90, no. 5, pp. 1657-1662, 2001.
38. M. M. Plichta, M. J. Herrmann, C. G. Baehne, A.-C. Ehlis, M. M. Richter, P. Pauli, and A. J. Fallgatter, "Even-related functional near-infrared spectroscopy (fNIRS): Are the measurements reliable?," Neuroimage, vol. 31, pp. 116-124, 2006.
39. Y. Kubota, M. Toichi, M. Shimizu, R. A. Mason, R. L. Findling, K. Yamamoto, and J. R. Calabrese, "Prefrontal hemodynamic activity predicts false memory - A near-infrared spectroscopy study," Neuroimage, vol. 31, pp. 1783-1789, 2006.
40. R. B. Buxton, E. C. Wong, and L. R. Frank, "Dynamics of blood flow and oxygenation changes during brain activation: The balloon model," Magn. Reson. Med., vol. 39, pp. 855-864, 1998.
41. G. Strangman, J. P. Culver, J. H. Thompson, and D. A. Boas, "A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation," Neuroimage, vol. 17, pp. 719-731, 2002.
42. T. J. Huppert, R. D. Hoge, S. G. Diamond, M. A. Franceschini, and D. A. Boas, "A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans," Neuroimage, vol. 29, pp. 368-382, 2006.
43. J. A. Mumford and T. Nichols, "Modeling and inference of multisubect fMRI data," IEEE Eng. Med. Biol. Mag., vol. 25, no. 2, pp. 42-51, Mar./Apr. 2006.