Constraining the general linear model for sensible hemodynamic response function waveforms

Medical and Biological Engineering and Computing

Volumn 46, Issue 8, 2008, Pages 779-787

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

^a BOGAZICI UNIVERSITY   (Turkey)

Author keywords

General linear model; Gibbs sampling; Hemodynamic response function; Near infrared spectroscopy; Stroop test

Indexed keywords

CHEMICAL ACTIVATION; INFRARED DEVICES; NEAR INFRARED SPECTROSCOPY; NEUROIMAGING;

CONSTRAINED PARAMETERS; GENERAL LINEAR MODELING; GIBBS SAMPLING; HEMODYNAMIC RESPONSE FUNCTIONS; PARAMETER INTERVALS; POSTERIOR DISTRIBUTIONS; STROOP TEST; WAVEFORM PARAMETERS;

HEMODYNAMICS;

ARTICLE; BAYES THEOREM; CONTROLLED STUDY; HEMODYNAMICS; LINEAR SYSTEM; NEAR INFRARED SPECTROSCOPY; NEUROIMAGING; SIGNAL DETECTION; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICAL PARAMETERS; WAVEFORM;

EID: 48749089897     PISSN: 01400118     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11517-008-0347-6     Document Type: Article

References (30)

1. Akin A, Bilensoy D, Emir UEE, Gülsoy M, Candansayar S, Bolay H (2006) Cerebrovascular dynamics in patients with migraine: Near-infrared spectroscopy study. Neurosci Lett 400:86-91
2. Akgül CB, Akin A, Sankur B (2006) Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals. Med Biol Eng Comput 44:945-958
3. Buxton R, Wong E, Frank L (1998) Dynamics of blood flow and oxygenation changes during brain activation: The balloon model. Magn Reson Med 39:855-864
4. Buxton RB, Uludaǧ K, Dubowitz DJ, Lin TT (2004) Modeling the hemodynamic response to brain activation. Neuroimage 23:S220-S233
5. Cope M, Delpy DT (1998) 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 26:289-294
6. Devroye L (1986) Non-uniform random variate generation. Springer, New York
7. De Zwart JA, Silva AC, Van Gelterenn P, Kellman P, Fukunaga M, Chu R, Koretsky AP, Frank JA, Duyn JH (2005) Temporal dynamics of the BOLD fMRI impulse response. Neuroimage 24:667-677
8. Dunson DB, Neelon B (2003) Bayesian inference on order-constrained parameters in generalized linear models. Biometrics 59:286-295
9. Ehlis AC, Herrmann MJ, Wagener A, Fallgatter AJ (2005) Multi-channel near-infrared spectroscopy detects specific inferior-frontal activation during incongruent Stroop trials. Biol Psychol 69:315-332
10. Fabbri F, Sassaroli A, Henry ME, Fantini S (2004) Optical measurements of absorption changes in two-layered diffusive media. Phys Med Biol 49:1183-1201
11. Firbank M, Okada E, Delpy DT (1998) A theoretical study of the signal contribution of regions of the adult head to near-infrared spectroscopy studies of visual evoked responses. Neuroimage 8:69-78
12. Friman O, Borga M, Lundberg P, Knutsson H (2003) Adaptive analysis of fMRI data. Neuroimage 19:837-845
13. Friston KJ, Fletcher P, Josephs O, Holmes A, Rugg MD, Turner R (1998) Event-related fMRI: Characterizing differential responses. Neuroimage 7:30-40
14. Friston KJ, Josephs O, Zarahn E, Holmes AP, Rouquette S, Poline JB (2000) To smooth or not to smooth? Bias and efficiency in fMRI time-series analysis. NeuroImage 12:196-208
15. Gelfand AE, Smith AFM, Lee TM (1992) Analysis of constrained parameter and truncated data problems using sampling. J Am Stat Assoc 87:523-532
16. Gelman AB, Carlin JS, Stern HS, Rubin DB (1995) Bayesian data analysis. Chapman & Hall/CRC, Boca Raton
17. Handwerker DA, Ollringer JM, D'Esposito M (2004) Variation of BOLD hemodynamic responses across subjects and brain regions and their effect on statistical analyses. Neuroimage 21:1639-1651
18. Huppert TJ, Hoge RD, Diamond SG, Franceschinini MA, Boas DA (2006) A temporal comparison of BOLD, ASL, and NIRS hemodynamic responses to motor stimuli in adult humans. Neuroimage 29:368-382
19. MacLeod C (1991) Half a century of research on the stroop effect: An integrative review. Psychol Bull 109:163-203
20. Purdon PL, Weisskoff RM (1998) Effect of temporal autocorrelation due to physiological noise and stimulus paradigm on voxel-level false-positive rates in fMRI. Human Brain Mapp 6:239-249
21. Schroeter ML, Zysset S, Wahl M, von Cramon DY (2004) Prefrontal activation due to Stroop interference increases during development -an event-related fNIRS study. Neuroimage 23:1317-1325
22. Smith AFM, Roberts GO (1993) Bayesian computation via the Gibbs sampler and related Markov Chain Monte Carlo methods. J R Stat Soc Ser B (Methodological) 55:3-23
23. Smith AT, Singh KD, Balsters JH (2007) A comment on the severity of the effect of non-white noise in fMRI time-series. Neuroimage 36:282-288
24. Steinbrink J, Villringer A, Kempf F, Haux D, Boden S, Obrig H (2006) Illuminating the BOLD signal: Combined fMRI-fNIRS studies. Magn Reson Imaging 24:495-505
25. Suzuki M, Miyai I, Ono T, Kubota K (2008) Activities in the frontal cortex and gait performance are modulated by preparation. An fNIRS study. Neuroimage 39:600-607
26. Villringer A, Chance B (1997) Non-invasive optical spectroscopy and imaging of human brain function. Trends Neurosci 20:4435-4442
27. Woolrich MW, Behrens TEJ, Smith SM (2004) Constrained linear basis sets for HRF modeling using Variational Bayes. Neuroimage 21:1748-1761
28. Woolrich MW, Ripley BD, Brady M, Smith SM (2001) Temporal autocorrelation in univariate linear modeling of fMRI data. Neuroimage 14:1370-1386
29. Worsley KJ, Taylor JE (2006) Detecting fMRI activation allowing for unknown latency of the hemodynamic response. Neuroimage 29:649-654
30. Zysset S, Muller K, Lohmann G, von Cramon DY (2001) Color-word matching Stroop task: Separating interference and response conflict. Neuroimage 13:29-36