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Modeling the hemodynamic response to brain activation
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Neurophysiological investigation of the basis of the fMRI signal
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001) · Nature · doi:10.1038/35084005 · Cited by 6,551
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.24.9868 · Cited by 6,483
An Energy Budget for Signaling in the Grey Matter of the Brain
Attwell, D., & Laughlin, S. B. (2001) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-200110000-00001 · Cited by 3,543
Fox, P. T., & Raichle, M. E. (1986) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.83.4.1140 · Cited by 2,056
The cost of cortical computation.
Lennie, P. (2003) · Current Biology · doi:10.1016/s0960-9822(03)00135-0 · Cited by 1,134
Bayesian Estimation of Dynamical Systems: An Application to fMRI
Friston, K. J. (2002) · NeuroImage · doi:10.1006/nimg.2001.1044 · Cited by 310
Relationship of spikes, synaptic activity, and local changes of cerebral blood flow
Lauritzen, M. (2001) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-200112000-00001 · Cited by 253
Cited by
Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009) · Human Brain Mapping · doi:10.1002/hbm.20718 · Cited by 1,924
HomER: A review of time-series analysis methods for near-infrared spectroscopy of the brain
Huppert, T. J., Diamond, S. G., Franceschini, M. A., & Boas, D. A. (2009) · Applied Optics · doi:10.1364/ao.48.00d280 · Cited by 1,817
Raichle, M. E., & Mintun, M. A. (2006) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.112819 · Cited by 1,630
Distinct patterns of brain activity in young carriers of the APOE -ε4 allele
Filippini, N., MacIntosh, B. J., Hough, M. G., Goodwin, G. M., Frisoni, G. B., Smith, S. M., Matthews, P. M., Beckmann, C. F., & Mackay, C. E. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0811879106 · Cited by 1,613
Coupled electrophysiological, hemodynamic, and cerebrospinal fluid oscillations in human sleep
Fultz, N. E., Bonmassar, G., Setsompop, K., Stickgold, R. A., Rosen, B. R., Polimeni, J. R., & Lewis, L. D. (2019) · Science · doi:10.1126/science.aax5440 · Cited by 1,197
Shmuel, A., Augath, M., Oeltermann, A., & Logothetis, N. K. (2006) · Nature Neuroscience · doi:10.1038/nn1675 · Cited by 898
Comparing families of dynamic causal models
Penny, W. D., Stephan, K. E., Daunizeau, J., Rosa, M. J., Friston, K. J., Schofield, T. M., & Leff, A. P. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000709 · Cited by 688
Shmuel, A., & Leopold, D. A. (2008) · Human Brain Mapping · doi:10.1002/hbm.20580 · Cited by 584
Diffusion MRI at 25: exploring brain tissue structure and function
Le Bihan, D., & Johansen-Berg, H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.006 · Cited by 498
Uludağ, K., Müller-Bierl, B., & Uğurbil, K. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.05.051 · Cited by 450
Self-citationComparing hemodynamic models with DCM
Stephan, K. E., Weiskopf, N., Drysdale, P. M., Robinson, P. A., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.040 · Cited by 441
Mathematical framework for large-scale brain network modeling in The Virtual Brain
Sanz-Leon, P., Knock, S. A., Spiegler, A., & Jirsa, V. K. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.01.002 · Cited by 356
A NIRS-fMRI investigation of prefrontal cortex activity during a working memory task
Sato, H., Yahata, N., Funane, T., Takizawa, R., Katura, T., Atsumori, H., Nishimura, Y., Kinoshita, A., Kiguchi, M., Koizumi, H., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.06.043 · Cited by 339
The amplitude of the resting-state fMRI global signal is related to EEG vigilance measures
Wong, C. W., Olafsson, V., Tal, O., & Liu, T. T. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.07.057 · Cited by 318
Self-citationElectrophysiological Imaging of Brain Activity and Connectivity—Challenges and Opportunities
He, B., Yang, L., Wilke, C., & Yuan, H. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2139210 · Cited by 300
Comparing dynamic causal models using AIC, BIC and free energy
Penny, W. D. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.07.039 · Cited by 298
DEM: A variational treatment of dynamic systems
Friston, K. J., Trujillo-Barreto, N., & Daunizeau, J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.02.054 · Cited by 278
Dynamic causal modelling revisited
Friston, K. J., Preller, K. H., Mathys, C., Cagnan, H., Heinzle, J., Razi, A., & Zeidman, P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2017.02.045 · Cited by 271
Integration of Visual and Tactile Signals From the Hand in the Human Brain: An fMRI Study
Gentile, G., Petkova, V. I., & Ehrsson, H. H. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00840.2010 · Cited by 274
Neuroprotection via matrix-trophic coupling between cerebral endothelial cells and neurons
Guo, S., Kim, W. J., Lok, J., Lee, S.-R., Besancon, E., Luo, B.-H., Stins, M. F., Wang, X., Dedhar, S., & Lo, E. H. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801105105 · Cited by 253
Short-term SSRI treatment normalises amygdala hyperactivity in depressed patients.
Godlewska, B. R., Norbury, R., Selvaraj, S., Cowen, P. J., & Harmer, C. J. (2012) · Psychological Medicine · doi:10.1017/s0033291712000591 · Cited by 244
Brain imaging of neurovascular dysfunction in Alzheimer’s disease
Montagne, A., Nation, D. A., Pa, J., Sweeney, M. D., Toga, A. W., & Zlokovic, B. V. (2016) · Acta Neuropathologica · doi:10.1007/s00401-016-1570-0 · Cited by 239
Fleisher, A. S., Sherzai, A., Taylor, C., Langbaum, J. B. S., Chen, K., & Buxton, R. B. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.021 · Cited by 217
Self-citationMultimodal Functional Neuroimaging: Integrating Functional MRI and EEG/MEG
He, B., & Liu, Z. (2008) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2008.2008233 · Cited by 171
Friston, K., Stephan, K., Li, B., & Daunizeau, J. (2010) · Mathematical Problems in Engineering · doi:10.1155/2010/621670 · Cited by 171
Perthen, J. E., Lansing, A. E., Liau, J., Liu, T. T., & Buxton, R. B. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.10.049 · Cited by 162
Self-citationThe physiology of developmental changes in BOLD functional imaging signals
Harris, J. J., Reynell, C., & Attwell, D. (2011) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2011.04.001 · Cited by 142
Using fMRI to study reward processing in humans: past, present, and future
Wang, K. S., Smith, D. V., & Delgado, M. R. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00333.2015 · Cited by 105
Intrusive memories to traumatic footage: the neural basis of their encoding and involuntary recall
Clark, I. A., Holmes, E. A., Woolrich, M. W., & Mackay, C. E. (2016) · Psychological Medicine · doi:10.1017/s0033291715002007 · Cited by 100
Dynamic causal modeling: a generative model of slice timing in fMRI
Kiebel, S. J., Klöppel, S., Weiskopf, N., & Friston, K. J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.10.026 · Cited by 92
Marinkovic, K., Rickenbacher, E., Azma, S., & Artsy, E. (2012) · Human Brain Mapping · doi:10.1002/hbm.21213 · Cited by 92
Linear and nonlinear relationships between visual stimuli, EEG and BOLD fMRI signals
Liu, Z., Rios, C., Zhang, N., Yang, L., Chen, W., & He, B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.01.017 · Cited by 88
Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.017 · Cited by 68
Liang, X., Connelly, A., & Calamante, F. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.013 · Cited by 48
An intrinsic diffusion response function for analyzing diffusion functional MRI time series
Aso, T., Urayama, S.-I., Poupon, C., Sawamoto, N., Fukuyama, H., & Bihan, D. L. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.05.027 · Cited by 47
Kohno, S., Sawamoto, N., Urayama, S.-I., Aso, T., Aso, K., Seiyama, A., Fukuyama, H., & Le Bihan, D. (2009) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2009.45 · Cited by 30
Energy paradox in REM sleep: balancing supply and consumption in brain metabolism
Takahashi, Y., Ikoma, Y., & Matsui, K. (2026) · Communications Biology · doi:10.1038/s42003-026-10646-6 · Cited by 1
“Although these parametersarepartlyinterdependent,theycanalsovaryindependently,and debatecontinuesoverwhichofthemmoststronglyin fl uences cerebral energysupplyandinformation-processingcapacity 34,35 .”
Metadata
- Authors
- Buxton, R. B., Uludağ, K., Dubowitz, D. J., & Liu, T. T.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2004
- Volume
- 23
- Pages
- S220-S233
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2123526233
- Cited by
- 1,229
- References
- 7
- FWCI
- 29.67
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
